Final Report for Special Technical Assistance for Maintenance Dredging of the Port of La Unión in the Republic of El Salvador

COMISIÓN EJECUTIVA PORTUARIA AUTONOMA REPUBLIC OF EL SALVADOR

FINAL REPORT FOR SPECIAL TECHNICAL ASSISTANCE FOR MAINTENANCE DREDGING OF THE PORT OF LA UNIÓN IN THE REPUBLIC OF EL SALVADOR

June 2014

JAPAN INTERNATIONAL COOPERATION AGENCY

ECOH CORPORATION

EI JR 14-018

COMISIÓN EJECUTIVA PORTUARIA AUTONOMA REPUBLIC OF EL SALVADOR

FINAL REPORT FOR SPECIAL TECHNICAL ASSISTANCE FOR MAINTENANCE DREDGING OF THE PORT OF LA UNIÓN IN THE REPUBLIC OF EL SALVADOR

June 2014

JAPAN INTERNATIONAL COOPERATION AGENCY

ECOH CORPORATION

Abbreviations Table ALMOB Automatic Light Mixture Overboard C.D.L. Chart Datum Level CA4 Four Central American countries:El Salvador, Guatemala, Honduras and Nicaragua CA5 Five Central American countries:El Salvador, Guatemala, Honduras, Nicaragua and Costa Rica CEPA Comisión Ejecutiva Portuaria Autónoma or Executive Autonomous Port Commission of the Republic of El Salvador CNR National Registration Center of the Republic of El Salvador COCATRAM Comisión Centroamericana de Transporte Marítimo (The Central American Commission on Maritime Transport) CPN Comision Portuaria Nacional Guatemala (Guatemala National Port Commission) D.L. Datum Level ECOH Environmental Consultants for Ocean and Human EPN Empresa Portuaria Nacional (Nicaragua National Port Company) EPQ Empresa Portuaria Quetzal (Quetzal Port Company) GPS Global Positioning System GVD Geodetic Vertical Datum JBIC Japan Bank for International Cooperation JICA Japan International Cooperation Agency JSCE Japan Society of Civil Engineers LMOB Lean Mixture Overboard LOA Length overall MLIT Ministry of Land, Infrastructure, Transport and Tourism MLLW Mean Low Low Water MLW Mean Low Water MSL Mean Sea Level NAD27 North American Datum of 1927 NOAA National Oceanic and Atmospheric Administration United States Department of Commerce OCDI The Overseas Coastal area Development Institute OD Origin-Destination PIANC World Association of Waterborne Transport Infrastructure SAPI Study on Special Assistance for Project Implementation SIECA La Secretaría de Integración Económica Centroamericana (The Secretariat of Central American Economic Integration) TDS Tons Dry Solid TOR Terms of Reference TSHD Trailing Suction Hopper Dredger TSS Total Suspension Solid UNCTAD United Nations Conference on Trade and Development USA United States of America USDA U.S. Department of Agriculture VBA Visual Basic for Applications WGS84 World Geodetic System 1984 WID Water Injection Dredging

Executive Summary

Chapter 1 Introduction The Republic of El Salvador decided to develop the new port in the Department of La Union, and requested the Japanese Government to prepare a master plan for the port construction and to carry out a feasibility study. The latter responded to the request by executing the feasibility study of La Union Port through JICA during October 1997 to December 1998. Following the feasibility study, the detailed design was made during July 2001 to January 2003. The project of constructing La Union Port began in April 2005, and construction of the civil engineering works was completed in December 2008 (see Figure 1.1).

While capital dredging of the access channel of 22.3 km long was progressing in 2007, it was observed a large quantity of siltation in the Inner and Outer channels and the harbor basin. Because the siltation might endanger the smooth operation of the port, the government of El Salvador and Japan discussed on the necessity of study on the fast siltation in July, 2008, and they agreed upon to start the Special Assistance for Project Implementation for La union Port Development Project (hereinafter referred to as “SAPI”). The SAPI Study was undertaken by JICA and executed during November 2008 to November 2009 (see Figure 1.1).

The SAPI Study clarified that the siltation is caused by slow movement of fluid mud toward a deeper seabed. Owing to the limited quantity of bathymetric time-series data and a relatively short duration of the study, however, it was difficult to predict the siltation volume with a high accuracy for making reliable estimate of the volume of maintenance dredging.

Figure 1.1 History of La Union Port

To make the port function properly as a deep sea port, dredging method as well as cost is a vital issue in financial viability and a key factor for successful terminal operation. Hence, CEPA again requested JICA to provide an effective and efficient maintenance dredging plan. According to a result of discussion between JICA and CEPA, JICA commenced the 1st Term Study in January 2011 and conducted a series of bathymetric survey and analysis for about one year and four months up to May 2012.

1 commencement of the 2nd Term Study. In the 2nd Term Study, not only the engineering issue but also the economic issue is included in the study scope to analyze technically/financially and economically optimum channel depths at present and in the future. After about one year suspension of study, the 2nd Term Study resumed on April, 2013.

The 1st Term Study and the 2nd Term Study have the following three purposes: (1) To prepare data, information and analysis utilized by CEPA to formulate an effective and efficient maintenance dredging plan of the Port. (2) To transfer technology to cope with the siltation in the channel and basin. (3) To assist CEPA to prepare dredging plan based on the collected data and analysis.

The 2nd Term Study Team consists of two sub-teams, that is to say, the Engineering Team and the Economic Team. In order to properly implement the 2nd Term Study, the Project Support Domestic Committee has been established in JICA Headquarters to support and give advices to the Engineering Team from an academic and technical view point.

Chapter 2 Technology Transfer

In the 1st Term Study, the technical training of CEPA personals was carried out in Japan from 21 November to 9 December, 2011. Two trainees participated in the training program and studied on operation and management of dredging works, methodology of bathymetric survey and astronomical tide prediction, and so on.

In the 2nd Term Study, the Engineering Team has transferred the technology to the counterparts and participants through the twelve times of lectures, exercises, discussion and on-the-job training. The technology transferred contains the matters concerning the bathymetric survey, the prediction of tide level, the tide level correction, the mechanism and the processes of siltation, the rake-dredging, the empirical prediction models for siltation, the monitoring plan of siltation, the influence of the Semicircular Island and the types of dredging vessel, and so on.

The Economic Team has transferred the technology to the counterparts and participants through sixteen lectures and discussions. The technology transferred includes matters concerning the Vessel Calling Model, the present state of container shipping in Central America, the tariff of La Union port and neighboring countries, the expected ship waiting time by tidal change in La Union port, the navigable time of the channel by using tidal advantage, the connection between industrial development of the region surrounding the port and port planning and promotion, and so on.

The workshop on “Special Technical Assistance for Maintenance Dredging of the Port of La Union in the Republic of El Salvador” was held in CEPA Headquarter on 27 August, 2013. Numbers of participants were 17 from the El Salvador (CEPA) side, 4 from the Japanese side, 7 from the JICA Study Team and 4 from the JICA El Salvador Office.

Chapter 3 Field Survey and Results

The field survey such as bathymetric survey and mud sampling were conducted in the 1st Term Study.

The bathymetric survey was repeated three times in February 2011, August 2011 and January 2012. A preliminary analysis was made with the data obtained. La Union Port has an access channel with total length of 22.3 km and had been dredged to a depth of D.L.-14 m. At present,

2 however, the entire passage has been filled to almost the original elevation and the depth when it was completed has not been maintained.

From the analysis of mud sampled at about two years after capital dredging, it is confirmed that fluid mud layer, the wet density of which is less than 1,200 kg/m3, is formed with the height of about 0.5m in Outer channel and about 1.0 m in Inner channel.

The fluid mud layer in the channel continues in existence for relatively long period. This indicates a possibility to reduce maintenance dredging volume by making a maintenance dredging plan taking the fluid mud layer into account.

Judging from the Team’s experience in the field, it is considered that the echo sounder of 200 kHz in frequency detects the top surface of the fluid mud layer. Therefore, the depth navigable for vessels is considered to be deeper than the depth measured by the echo sounder of 200 kHz, due to the thickness of the fluid mud layer.

Chapter 4 Analysis of Siltation Process and Prediction Models

At first, an empirical prediction model is formulated with an exponential function based on the bathymetric data.

Next, a process and a mechanism of siltation in the channel are revealed through the analysis of bathymetric data. According to the result of analysis, the original exponential model has been improved to be a new model, which is named as a modified Exponential Model.

Moreover, it is shown that a rapid siltation occurs just after the dredging within several months. By taking into account a possibility that the rapid siltation does not occur during a period of maintenance dredging, a second prediction model has been newly established, which is called a Linear Model.

At present, there is a discrepancy in the volumes of siltation predicted by the modified Exponential Model and the Linear Model. The volume of siltation predicted by the former is usually equal or greater than that of the latter. Since the latter model is formulated based on a unverified hypothesis, we must refrain from the use of it until the hypothesis is verified with the bathymetric data.

Chapter 5 Estimation of Dredging Volume and Cost

By using two prediction models formulated in Chapter 4, the volume of maintenance dredging will be estimated in Chapter 5.

At present, the harbor basin, Inner channel and Outer channel have been filled to almost the original elevation. The basin and channel need to be re-dredged at first. The total volume of the re-dredging for six target navigation depths of 9 to 14 m varying by 1 m is estimated based on the latest survey result in July 2013. The estimated re-dredging volume by depths is summarized in Table 5.1.

Table 5.1 Estimated re-dredging volume (units: 1000 m3) Depth (m) Outer Ch. Inner Ch. Basin Total 9.0 0 895 0 895 10.0 25 1,535 59 1,619

3 11.0 404 2,215 344 2,964 12.0 1,161 2,936 798 4,895 13.0 2,284 3,696 1,471 7,452 14.0 3,882 4,496 2,186 10,565

The maintenance dredging volume is calculated for six levels of the target depth: i.e., 9, 10, 11, 12, 13, and 14 m. The cycle time, or the time interval of successive maintenance dredging, is set at 3, 4, 6, or 12 months. The volume of maintenance dredging at a specified cycle time and a target depth is estimated by applying the modified Exponential Model and the Linear Model. In the calculation, the fluid mud thickness is taken into account. The result of estimation is shown in Figure 5.7.

Figure 5.7 Maintenance Dredging Volume by Depths

TSHD (Trailing Suction Hopper Dredger) is regarded appropriate for the re-dredging and the maintenance dredging in La Union Port, because TSHD has the lowest impact on “other vessels traffic” with the highest “productivity” and “cost efficiency” among four types of dredger.

The dredging cost by own dredger is estimated smaller than contract base because the indirect cost is estimated cheaper than by contract base while direct costs are similar. Indirect cost of contract base includes mobilization cost, insurance cost, costs related with contingency and so on. On the contrary, indirect cost of dredging by own dredger include only mobilization, insurance cost and contingency as other cost is difficult to estimate. However, it is not appropriate to discuss about the dredging framework only with a comparison of dredging costs by contract base and own dredger, for the following reasons.

4 If CEPA owns a dredger, CEPA would have to bear considerable cost more than the cost estimation. And, dredging works could not be functioned without long experience and the accumulation of know-how. Aside from the cost, CEPA would have to handle training and education for dredger’s crew.

Furthermore, accurate prediction of the siltation volume is necessary to design the size or capacity of the dredger before its procurement. But prediction models of siltation volume developed in this report is not reliable enough and necessary to be revised through monitoring of channel siltation for a certain period.

In addition to above, in case of change of target channel depth, the flexible response is extremely difficult if CEPA owns its dredger. This problem will remain unchanged for future as well.

Judging from the above all, “dredging by contract base” for the channel maintenance dredging for a certain period is strongly recommended.

Chapter 6 Proposal of Monitoring Plan

The two models established in Chapter 4 are based on the bathymetric data which is not necessarily enough in quality and quantity. More the Linear Model is standing on the unverified hypothesis. The monitoring of the channel depth by bathymetric survey is the only method for improving the precision of prediction and for enhancing the applicability of the Linear Model to the maintenance dredging. This is the first purpose of monitoring. The second one is to confirm the phenomenon of rapid siltation just after the dredging.

The monitoring plan is set up, subject to the condition that the bathymetric survey will be conducted by CEPA themselves with their own equipment.

For the first purpose, the bathymetric survey should be conducted immediately before and just after the re-dredging in the basin and the access channel. After that, the bathymetric survey shall be repeated with the time interval of two months, or one month if possible. For the second purpose, the bathymetric survey must be conducted just after the re-dredging. After that, it is recommended that the survey is repeated at an interval of two weeks for several months. The bathymetric survey must be usually conducted with the two acoustic signals of 38 kHz and 200 kHz to have the data on the thickness of fluid mud.

The record of dredging and the record of vessels which enter into and leave from the port must be collected at the same time.

Chapter 7 Reviews of Demand Forecast Model and Market Allocation Model developed by CEPA

In this chapter, the calculation method for projecting the growth rate of container volume from CA4 (El Salvador, Guatemala, Honduras and Nicaragua) and developing the market allocation model is shown. “Port demand Study of La Union” carried out by CEPA consists of three parts: 1. Projected growth rate of container volume to and from CA4 2. Development of market allocation model 3. Projected market allocation for La Union Port

5 Chapter 8 Vessel Calling Model

The main purpose of Chapter 8 is to describe the vessel calling model which will be used to conduct the financial and economic analysis of La Union Port.

For that purpose, the current status of Salvadoran ports (8.1) as well as other major ports in other Central American countries (8.2) is summarized. The main focus is put on economic aspects because they are key for underpinning the model development, but the physical condition of each port is also described because it affects the capacity of cargo handling. In particular, the physical condition of Acajutla Port is crucial because the present and future limitation of its handling capacity is considered to directly influence the future container cargo throughput in La Union Port.

The strategy of maritime container shipping companies in the Pacific Coast of Central America is also examined prior to establishing the model ( 8.3). It is examined by two approaches; the first approach is to develop the liner shipping network of each company from the containership movement database. The second approach is to conduct interviews with shipping companies and other stakeholders.

The latter part of this chapter focuses on the vessel calling model. First, an outline of the model is described (8.4). After that, each component of the model is described; i.e., behavior of shipping companies, container cargo assignment model, and input data for the vessel calling model.

The maritime container shipping network of regular services operated by each company is vital to understanding the behavior of shipping companies ( 8.5). It is structured from the containership movement database by extracting 28 worldwide and local companies and 163 ports of the world.

The container cargo assignment model is the core element of the vessel calling model (8.6). The container cargo assignment model is an application of stochastic network assignment model on the intermodal shipping network of international container cargo, based on the generalized cost including both monetary cost and shipping time.

Preparing the input data is also important for the vessel calling model (8.7). Container cargo shipping demand (container cargo OD) between each port or region of the world is one of the most important data items. It is estimated from container cargo OD between countries and various statistics and information on regional economy, trade, and cargo handling in ports. The other necessary data is information on the shipping network including physical distance and shipping cost in the land, port, and maritime links. The information on the cost and time in border-crossing on land is also included.

The last section ( 8.8) of Chapter 8 summarizes the calculation results of the container cargo assignment model. After the description of the calculation procedure and unknown parameter estimation, the calculation results are examined from the viewpoint of the model reproducibility by several benchmarks such as container cargo throughput, share by partner countries, export and import port in CA4 countries, shares by shipping company, and estimated volume shipped by each liner service. Also, the sensitivity of the model to estimated unknown parameters is also examined.

As a result, the container cargo assignment model well describes the actual container cargo shipping market in CA4 countries and reasonably behaves against the change of the model input.

6 Chapter 9 Vessel Calls to La Union Port and Economic Analysis

Chapter 9 mainly focuses on the output of the vessel calling model.

The first part of the chapter describes the present status of navigation channel and rules in La Union Port, followed by a proposal for a new navigation rule (9.1). The “expected waiting time” is calculated based on the new rule as well as on the existing rule. It is found that the existing rule may be effective under the current situation that a small ship navigates a shallow channel, but when the channel is deepened and ships of various sizes are expected to call the new rule needs to be introduced.

Many calculation scenarios on the future liner shipping network are prepared for each channel depth in La Union Port in 2020 and 2030, and several feasible scenarios for each depth in both years are selected based on certain criteria (9.2). Figure 9.12 and Figure 9.13 show the container cargo throughput in La Union Port in 2020 and 2030, estimated by the vessel calling model based on each feasible scenario with the depth of navigation channel. In the figure, the results in both 1) modification scenarios of existing feeder and way-port service network with -9m to -12m channel depth and 2) additional vessel-calling scenarios as a transshipment hub with -12m to -14m channel depth are shown. The figures show that the container cargo throughput in La Union Port increases as the depth of navigation channel increases.

Figure 9.12 & 9.13 Container cargo throughput for each feasible scenario in port of La Union in 2020 and 2030

Based on the container cargo throughput and other outputs estimated in the model, net income (which is acquired by subtracting the expected revenue from port and handling charges by expenditure such as container operation cost except for the dredging cost) from container business of La Union Port, net income from container business of Salvadoran port sector (sum of Acajutla and La Union Port), and net benefit for Salvadoran economy of the dredging project in La Union Port (difference of the sum of the net incomes of the ports of La Union and Acajutla and shipping cost of Salvadoran import/export cargo for dredging scenarios from those of the no-dredging scenario) are estimated and compared with the dredging cost by channel depth (9.3). From the financial aspect for La Union Port, if the tariff of La Union Port is kept at the present level, the net income will be always less than the dredging cost for each channel depth (see Figure 9.18 and Figure 9.19).

However, if the tariff of La Union Port is increased, the net income (except for the dredging cost) may be larger than the dredging cost in the scenario that the expected net income is maximized by channel depth (9.4, see Figure 9.24 and Figure 9.25). It implies a need to increase the tariff in

7 La Union Port to keep a sound financial condition. However, this could weaken the competitiveness of the port against neighboring ports resulting in a decrease in the amount of containers handled. The level of the tariff will be a crucial issue when the shipping market becomes more liberalized such as when the barriers at national borders are removed (9.2.3(3)).

Figure 9.18 & 9.19 Estimated net income and dredging cost by channel depth in La Union Port (left: 2020; right: 2030)

Figure 9.24 & 9.25 Estimated net income in case of the tariff increase and dredging cost by channel depth in La Union Port (left: 2020; right: 2030)

The other important point in the simulations of the chapter is that the scenarios on the future liner shipping network are prepared not only for modification of the existing feeder and way-port network, but also for calling by vessels of the trunk route. Some of these “transshipment hub” scenarios for La Union Port are considered to be feasible as already shown in Figure 9.12 and Figure 9.13; in addition, if the transshipment hub is realized, it will be very beneficial to the economy of El Salvador. However, an important point to keep in mind is that simply deepening the channel by dredging does not guarantee that the port will become a transshipment hub. To become a transshipment hub, considerable efforts to attract the vessels of the trunk line would need to be made.

The last finding is that regional development in the eastern El Salvador would contribute to increasing the amount of container cargo as well as the revenue in La Union Port (9.2.3(3)2) and 9.4.4). As originally planned, the integrated development of La Union Port with the hinterland in the eastern area of El Salvador is also one of important keys for the future development of La Union Port.

8 Chapter 10 Optimal Dredging Plan Considering Time-Series Changes on Demand and Costs

In Chapter 10, a methodology of the time series analysis considering each year’s income, benefit and dredging cost is introduced.

Also, example results of calculation are shown in order to contribute to the discussion on the timing of investment for dredging. The calculation results on optimal year and net benefit for each combination of target depth after the first and second re-dredging and each type of dredging after increasing the tariff in La Union Port are shown. The calculation is based on many assumptions (e.g., re-dredging is allowed only twice and the second re-dredging must be carried out precisely ten years after the first dredging); in addition, a limited number of example results are shown based on the liner service network to generate the expected maximum net benefit in each channel depth is considered.

The example results imply that the best strategy to maximize the net benefit is to purchase a dredger for annual maintenance dredging within a few years and maintain a channel depth of around -12m or -13m, although there is a significant risk because this strategy will only be successful if the transshipment hub” scenario is realized. On the other hand, the second best strategy with relatively smaller risk is that the first re-dredging for a depth of around -10m is conducted with a contracted dredger and the second re-dredging for a depth of -13m. This kind of “step-wise” strategy is very useful for avoiding huge financial risks.

Chapter 11 Conclusions and Recommendations

Major findings of the study and recommendations are summarized on the following items;

11.1 Conclusions (1) Present state of siltation in the access channel (2) Thickness of fluid mud layer (3) Mechanism of siltation and prediction models foe water depth in the channel (4) Volume of re-dredging (5) Volume of maintenance dredging (6) Appropriate dredging method (7) Vessel calling model (8) Financial and economic analysis of La Union Port and policy simulation (9) Optimal dredging plan considering time-series changes (10) Navigation rule of access channel

11.2 Recommendations (1) Applicability of a empirically formulated prediction model (2) Applicability of the Linear Model (3) Appropriate dredging framework (4) Necessity of monitoring channel depth (5) Use of dual frequencies of echo sounder (6) Tariff setting (7) Transshipment hub scenario (8) Regional development in eastern El Salvador (9) Importance of step-wise investment plan for dredging to avoid huge financial risks (10) Necessity of new navigation rules for access channel of La Union Port

THE REPUBLIC OF EL SALVADOR: SPECIAL TECHNICAL ASSISTANCE FOR MAINTENANCE DREDGING OF THE PORT OF LA UNIÓN

Abbreviations Table Executive Summary

Table of Contents

Chapter 1 Introduction ...... 1-1 1.1 Overview of Development of La Union Port ...... 1-1 1.1.1 Development of La Union Port ...... 1-1 1.1.2 Harbor Facilities of La Union Port ...... 1-2 1.2 Recognition of Siltation Problem in La Union Port and Commencement of SAPI Study ...... 1-3 1.3 Result of SAPI Study ...... 1-4 1.3.1 The Gulf of Fonseca and Feeder Rivers ...... 1-5 1.3.2 Sediment classification and mechanism of siltation ...... 1-6 1.3.3 Establishment of prediction formulae for siltation speed and channel depth ...... 1-7 1.4 Objectives and Major Works of this Study ...... 1-8 1.5 Engineers concerned and Chronologies of Study ...... 1-9 1.5.1 Engineers concerned ...... 1-9 1.5.2 Chronologies of Study ...... 1-12 1.6 Composition and Abstract of Chapters in the Report ...... 1-13 Chapter 2 Technology Transfer ...... 2-1 2.1 Execution for Technical Training of CEPA Personals in Japan ...... 2-1 2.2 Technology Transfer to Counterparts ...... 2-2 2.2.1 Technology Transfer in the Field of Engineering ...... 2-2 2.2.2 Technology Transfer in the Field of Economic ...... 2-7 2.3 Workshop ...... 2-13 Chapter 3 Field Survey and Results ...... 3-1 3.1 Bathymetric Survey ...... 3-1 3.1.1 Survey lines of bathymetric survey ...... 3-1 3.1.2 Longitudinal depth profile of access channel ...... 3-3 3.1.3 Transversal depth profiles of harbor basin and access channel ...... 3-3 3.1.4 Mean depth of access channel and harbor basin ...... 3-13 3.1.5 Difference between depth measurements with 38 and 200 kHz sonic waves ...... 3-16 3.2 Seabed Mud Conditions ...... 3-18 3.2.1 Sites and methodology of mud sampling ...... 3-18 3.2.2 Description of sampled mud and vertical density profile of mud layer ...... 3-20 3.2.3 Physical properties of sampled mud ...... 3-22 3.2.4 Numerical prediction of density profile change by means of mud consolidation process ...... 3-24

i 3.2.5 Assessment of thickness of fluid mud layer for definition of nautical bottom ..... 3-29 3.3 Main Results of the Field Survey ...... 3-30 Chapter 4 Analysis of Siltation Process and Prediction Models ...... 4-1 4.1 Collected Data ...... 4-1 4.2 Siltation Speed and Depth Difference in the Channel (Exponential model) ...... 4-2 4.3 Analyses of Siltation Processes in Channel ...... 4-6 4.3.1 Siltation in Inner Channel ...... 4-6 4.3.2 Siltation in Outer Channel ...... 4-11 4.3.3 Physical consideration for rapid siltation just after dredging ...... 4-14 4.4 Siltation Prediction Models for Channel ...... 4-19 4.4.1 Modifications of original Exponential Model ...... 4-19 4.4.2 Linear model ...... 4-24 4.4.3 Applicability of two models ...... 4-26 4.5 Siltation Prediction model for Harbor Basin and Port Channel ...... 4-26 Chapter 5 Estimation of Dredging Volume and Cost ...... 5-1 5.1 Re-Dredging volume ...... 5-1 5.2 Maintenance dredging volume ...... 5-4 5.2.1 Navigable depth ...... 5-4 5.2.2 Estimation method of maintenance dredging volume ...... 5-4 5.2.3 Maintenance dredging volume by depths ...... 5-6 5.2.4 Maintenance dredging volume and over dredging depth by segments ...... 5-12 5.3 Examination of Dredging Methods and Dredger Capacity ...... 5-17 5.3.1 Types of dredger ...... 5-17 5.3.2 Appropriate dredging method ...... 5-22 5.3.3 Required capacity of dredger ...... 5-25 5.4 Cost Estimation of Dredging ...... 5-30 5.4.1 Consideration on cost estimation of dredging ...... 5-32 5.4.2 Cost for re-dredging ...... 5-41 5.4.3 Cost for maintenance dredging ...... 5-41 5.4.4 Observations on re-dredging cost ...... 5-43 5.4.5 Effect of decreasing cycle time (Case study on target channel depth of 12 m) .... 5-44 5.4.6 Recommendation on dredging framework ...... 5-46 Chapter 6 Proposal of Monitoring Plan after Re-dredging ...... 6-1 6.1 Purposes of Monitoring ...... 6-1 6.2 Verification on appropriateness of the predicted siltation volume ...... 6-1 6.3 Confirmation of rapid siltation just after the dredging ...... 6-3 6.4 Tide Correction of Bathymetric Data ...... 6-7 6.4.1 Improvement of tide correction of bathymetric survey data ...... 6-7 6.4.2 Datum level of La Union Port ...... 6-13 Chapter 7 Reviews of Demand Forecast Model and Market Allocation Model developed by CEPA ...... 7-1 7.1 Outline of Demand Forecast Model and Market Allocation Model developed by CEPA ...... 7-1 7.2 Projected the growth rate of container volume to and from CA4...... 7-1 7.3 Development of Market Allocation Model ...... 7-4 7.4 Projected market allocation for La Union Port ...... 7-8

ii Chapter 8 Vessel Calling Model ...... 8-1 8.1 Ports of El Salvador ...... 8-1 8.1.1 Outline of El Salvador ...... 8-1 8.1.2 Outline of ports of El Salvador ...... 8-1 8.1.3 Major facilities of ports ...... 8-1 8.1.4 Cargo volume by type ...... 8-1 8.1.5 Acajutla Port ...... 8-2 8.1.6 La Union Port ...... 8-24 8.2 Ports on the Pacific Coast of CA5 countries ...... 8-28 8.2.1 Basic indicator ...... 8-28 8.2.2 Locational conditions ...... 8-28 8.2.3 Physical conditions ...... 8-28 8.2.4 Port management and operation ...... 8-29 8.2.5 Characteristics of ports ...... 8-29 8.2.6 Characteristics of handling containers ...... 8-30 8.2.7 Future development and improvement ...... 8-30 8.3 Container Activities of Central American region ...... 8-38 8.3.1 Container throughput of ports of Central America ...... 8-38 8.3.2 Containership movement in the Central American region ...... 8-41 8.3.3 Views of shipping operators ...... 8-47 8.4 Outline of Vessel Calling Model ...... 8-51 8.5 Behavior of Shipping Companies ...... 8-53 8.5.1 Liner shipping network ...... 8-53 8.5.2 Shipping company ...... 8-53 8.5.3 Port ...... 8-55 8.6 Container Cargo Assignment Model ...... 8-59 8.6.1 Whole model structure ...... 8-59 8.6.2 Formulation of container cargo assignment model ...... 8-59 8.6.3 Maritime shipping submodel ...... 8-60 8.6.4 Ocean freight charge ...... 8-60 8.6.5 Land shipping time and freight charge ...... 8-61 8.7 Input Data ...... 8-63 8.7.1 Container cargo OD (container cargo shipping demand) ...... 8-63 8.7.2 Level of service in each port ...... 8-68 8.7.3 Maritime shipping network ...... 8-68 8.7.4 Land shipping network ...... 8-68 8.8 Calculation Results of the Container Cargo Assignment Model ...... 8-71 8.8.1 Calculation procedure of the model ...... 8-71 8.8.2 Unknown parameter estimation ...... 8-72 8.8.3 Model reproducibility ...... 8-72 8.8.4 Sensitivity of the model output ...... 8-77 8.9 Conclusion of Chapter 8 ...... 8-80 Chapter 9 Vessel Calls to La Union Port and Economic Analysis ...... 9-1 9.1 Present Navigation of La Union Port ...... 9-1 9.1.1 Present status of navigation channel and navigation rule ...... 9-1 9.1.2 Tidal conditions ...... 9-7 9.1.3 Navigable condition by depth of channel ...... 9-9 9.2 Vessel Calling Model Calculation and Results ...... 9-18 9.2.1 Simulation of calling at La Union Port at the present moment (as of 2010) using the

iii model developed ...... 9-18 9.2.2 Scenario setting for future simulation (2020 and 2030) ...... 9-19 9.2.3 Model calculation results ...... 9-26 9.3 Economic and Financial Analysis in the Original Model ...... 9-36 9.3.1 Definition and methodology ...... 9-36 9.3.2 Net income from container business of La Union Port and dredging cost by channel depth ...... 9-38 9.3.3 Net income from container business of Salvadoran port sector and dredging cost by channel depth ...... 9-41 9.3.4 Economic benefit of El Salvador by container handling at La Union Port ...... 9-44 9.4 Economic and Financial Analysis on Policy Simulation ...... 9-47 9.4.1 Net income from container business of La Union Port (in case of the tariff increase) and dredging cost by channel depth ...... 9-47 9.4.2 Net income from container business of Salvadoran port sector (in case of the tariff increase in La Union Port) and dredging cost by channel depth ...... 9-50 9.4.3 Economic benefit of El Salvador by container handling at La Union Port in case of tariff increase ...... 9-53 9.4.4 Net income from container business of La Union Port (in case of the advancement of regional development in the eastern El Salvador) and dredging cost by channel depth 9-56 9.5 Conclusion of Chapter 9 ...... 9-58 Chapter 10 Optimal Dredging Plan Considering Time-Series Changes on Demand and Costs ...... 10-1 10.1 Concept ...... 10-1 10.2 Dredging Cost ...... 10-1 10.2.1 Re-dredging cost ...... 10-2 10.2.2 Mobilization cost for re-dredging ...... 10-2 10.2.3 Cost for purchasing dredger (in case of own-basis dredging) ...... 10-2 10.2.4 Mobilization cost for maintenance dredger ...... 10-3 10.2.5 Regular cost for maintenance dredging ...... 10-3 10.3 Time-series estimation of container cargo throughput, net income and benefit, and dredging cost considering the timing of the dredging ...... 10-4 10.3.1 Time-series estimation of container cargo throughput, net income and benefit ... 10-4 10.3.2 Time-series dredging cost including the timing of the re-dredging...... 10-7 10.4 Methodology and example results of time-series financial and economic analysis considering the timing of the dredging ...... 10-10 10.4.1 Making a calculation sheet for time-series estimation ...... 10-10 10.4.2 Obtaining the optimal timing of re-dredging and combination of target depth .. 10-12 10.5 Conclusion of Chapter 10 ...... 10-15 Chapter 11 Conclusions and Recommendations ...... 11-1 11.1 Conclusions ...... 11-1 11.2 Recommendations ...... 11-4

ANNEXES

ANNEX A MINUTES OF MEETING ON EXECUTION OF THE PROJECT ...... A-1 ANNEX B MINUTES OF MEETING BETWEEN CEPA AND STUDY TEAM ...... B-1 ANNEX C TOPICS RELATED TO CHANNEL SEDIMENTATION IN LA UNION PORT ...... C-1 C.1 SIDE SLOPE STABILITY ...... C-2 C.2 POSSIBILITY OF CANNEL RELOCATION ...... C-7 C.3 RAKE-DREDGING ...... C-9 C.4 COMMENTS ON CEPA’S PLAN ...... C-18 C.5 DREDGING METHD ...... C-28 C.6 OVERDREDGING DEOTH AND VOLUME BY SECTIONS ...... C-46 C.7 WESTWARD OVER-DREDGING IN OUTER CHANNEL ...... C-58 C.8 RE-DREDGING VOLUME CALCULATION ...... C-61

ANNEX D TOPICS RELATED TO ECONOMIC STUDY FOR LA UNION PORT ...... D-1 D.1 A PORTS IN NEIGHBORING COUNTRIES ...... D-2 D.2 DETAIL OF MARITIME SHIPPING SUBMODEL ...... D-34 D.3 INTERVIEW AND SURVEY TOGATHER WITH CEPA ECONOMIC TEAM MEMBERS ...... D-48 D.4 COMPUTER OPERATION MANUAL OF THE VESSEL CALLING MODEL ...... D-59

v List of Tables

Table 1.1 Volume of siltation deposited from April 2007 to January 2008 in comparison . 1-3 Table 1.2 List of members of Project Support Domestic Committee in Japan ...... 1-9 Table 1.3 Members of the first term Study Team ...... 1-10 Table 1.4 Members of the second term Study Team ...... 1-10 Table 1.5 Counterparts in the first term Study ...... 1-10 Table 1.6 Counterparts in the second term Study ...... 1-11 Table 1.7 JICA Experts dispatched to CEPA ...... 1-11 Table 1.8 Others relevant person of CEPA in the first term Study ...... 1-11 Table 1.9 Relevant person of CEPA in the second term Study ...... 1-11 Table 1.10 Chronology of First Term Study ...... 1-12 Table 1.11 Chronology of Second Term Study ...... 1-12 Table 2.1 Itinerary of technical training in Japan ...... 2-2 Table 2.2 Participants (1) ...... 2-3 Table 2.3 Participants (2) ...... 2-3 Table 2.4 Participants (3) ...... 2-4 Table 2.5 Participants (4) ...... 2-4 Table 2.6 Participants (5) ...... 2-4 Table 2.7 Participants (6) ...... 2-5 Table 2.8 Participants (7) ...... 2-5 Table 2.9 Participants (8) ...... 2-5 Table 2.10 Participants (9) ...... 2-6 Table 2.11 Participants (10) ...... 2-6 Table 2.12 Participants (11) ...... 2-6 Table 2.13 Participants (12) ...... 2-7 Table 2.14 Participants (1) ...... 2-8 Table 2.15 Participants (2) ...... 2-8 Table 2.16 Participants (3) ...... 2-8 Table 2.17 Participants (4) ...... 2-9 Table 2.18 Participants (5) ...... 2-9 Table 2.19 Participants (6) ...... 2-10 Table 2.20 Participants (7) ...... 2-10 Table 2.21 Participants (8) ...... 2-10 Table 2.22 Participants (9) ...... 2-11 Table 2.23 Participants (10) ...... 2-11 Table 2.24 Participants (10) ...... 2-11 Table 2.25 Participants (12) ...... 2-12 Table 2.26 Participants (13) ...... 2-12 Table 2.27 Participants (14) ...... 2-12 Table 2.28 Participants (15) ...... 2-13 Table 2.29 Participants (16) ...... 2-13 Table 2.30 Program of workshop, titles of presentations and presenters ...... 2-14 Table 2.31 List of participants and presenters ...... 2-14 Table 3.1 Location of bathymetric survey lines ...... 3-1 Table 3.2 Mean depth of access channel and harbor basin in February 2011 ...... 3-14 Table 3.3 Mean depth of access channel and harbor basin in August 2011 ...... 3-14 Table 3.4 Mean depth of access channel and harbor basin in January 2012 ...... 3-14 Table 3.5 Approximate range of fluid mud thickness at respective transverse lines (SAPI,

vi 2009) ...... 3-17 Table 3.6 Locations of mud sampling sites...... 3-18 Table 3.7 Soil characteristics at five sampling sites ...... 3-23 Table 4.1 Periods of implementation of dredging ...... 4-1 Table 4.2 Parameters of the final depth difference in Port channel and Harbor basin ...... 4-28 Table 5.1 Estimated re-dredging volume (units: 1000 m3) ...... 5-2 Table 5.2 Estimated TDS (Tons Dry Solid) of re-dredging (units: 1000 t) ...... 5-2 Table 5.3 Siltation prediction models to estimate maintenance dredging volume ...... 5-4 Table 5.4 Maintenance dredging volume by the Modified Exponential Model ...... 5-7 Table 5.5 Maintenance dredging volume calculated by the Linear Model ...... 5-8 Table 5.6 Height and Volume of maintenance dredging (over dredging) estimated by Mod. Exp. Model for Target depth of 14 m ...... 5-16 Table 5.7 Applicability of dredging methods to La Union Port ...... 5-24 Table 5.8 Calculation example of working hours ...... 5-27 Table 5.9 Necessary dredger capacity for re-dredging (m3) ...... 5-28 Table 5.10 Necessary dredger capacity for maintenance dredging (m3), in the case of Modified Exponential Model ...... 5-29 Table 5.11 Necessary dredger capacity for maintenance dredging (m3) in the case of Linear Model ...... 5-29 Table 5.12 Building price of dredgers studied by CEPA ...... 5-32 Table 5.13 Building price of dredgers in Japan (Actual base) ...... 5-32 Table 5.14 Equipment cost of TSHD by capacity ...... 5-34 Table 5.15 Breakdown of engine power by TSHD capacity (pump power and propulsion power) ...... 5-37 Table 5.16 Number of high class crew and common crew and labor unit cost (excluding fringe benefit and other expenses) ...... 5-37 Table 5.17 Annual crew cost by each category ...... 5-38 Table 5.18 Crew cost in case of dredging by own dredger (CEPA’s unit cost including fringe benefit and other expenses) ...... 5-38 Table 5.19 Initial mobilization cost by dredger capacity and annual cost ...... 5-39 Table 5.20 Mobilization cost by dredger capacity for inspection (round trip from/to Balboa) ...... 5-40 Table 5.21 Insurance cost and contingency estimated by CEPA ...... 5-41 Table 5.22 Dredging cost by target water depth ...... 5-41 Table 5.23 Dredging cost by Modified Exponential Model ...... 5-42 Table 5.24 Dredging cost by Linear Model ...... 5-42 Table 5.25 Breakdown of indirect cost of dredging by contract base (cost that CEPA considers are described in red letters) ...... 5-48 Table 6.1 Vertical reference levels for El Salvador provided by CNR...... 6-14 Table 7.1 Real GDP Growth Rate of CA4 ...... 7-2 Table 7.2 Estimated Container Volume to CA4 ...... 7-2 Table 7.3 GDP Elasticity of Container Volume to/from CA4 ...... 7-3 Table 7.4 GDP Elasticity ...... 7-3 Table 7.5 Container Growth Rate (2010=100) ...... 7-4 Table 7.6 Container Volumeof each port in 2010 ...... 7-5 Table 7.7 Container Volume of each country in 2010 (TEU) ...... 7-5 Table 7.8 Hinterland transport matrix (2010) ...... 7-7 Table 7.9 Referencing the following locations: ...... 7-9 Table 7.10 Transportation Cost per TEU in 2010 (USD) ...... 7-9 Table 7.11 Transit Time in 2010 (Days) ...... 7-9

vii Table 7.12 Hinterland transport matrix(with La Union) ...... 7-10 Table 7.13 Hinterland transport matrix (with La Union) in 2020 (Scenario1) ...... 7-13 Table 7.14 Hinterland transport matrix (with La Union) in 2030(Scenario 1) ...... 7-14 Table 7.15 Projected market allocation for La Union Port in 2020,2030(Scenario 1) ...... 7-15 Table 7.16 Hinterland transport matrix with La Union in 2020 (Scenario 2) ...... 7-15 Table 7.17 Hinterland transport matrix with La Union in 2030 (Scenario 2) ...... 7-17 Table 7.18 Projected market allocation for La Union Port in 2020,2030(Scenario 2) ...... 7-18 Table 8.1 Tendency of ship calls and handling cargo of main ports of El Salvador ...... 8-2 Table 8.2 Dimension of the pier ...... 8-4 Table 8.3 Major facilities of Acajutla Port ...... 8-4 Table 8.4 Transition of total cargo volume in the last 10 years ...... 8-5 Table 8.5 Cargo handling by type and pier ...... 8-6 Table 8.6 Transition of container cargo in the last 10 years ...... 8-6 Table 8.7 Origin countries of import container by commodities in 2012 ...... 8-7 Table 8.8 Destination countries of export container by commodities in 2012 ...... 8-7 Table 8.9 Ship calls by type in 2012 ...... 8-8 Table 8.10 Monthly container ship calls by shipping line in 2012 ...... 8-8 Table 8.11 Berth assignment of pier by commodity category in 2012 ...... 8-9 Table 8.12 Berth assignment of pier by commodity in 2012 ...... 8-10 Table 8.13 Expected berthing/working time and container increase ...... 8-11 Table 8.14 Container handling capacity ...... 8-12 Table 8.15 Port facilities and present status in Acajutla Port ...... 8-14 Table 8.16 Test results by Schmidt hammer ...... 8-18 Table 8.17 Survey result of visual and hammering inspection for diagnosis survey of deterioration degree of the ...... 8-19 Table 8.18 Appraisal of the Remaining Service Life based on the Survey Results of the Acajutla Port Facility ...... 8-20 Table 8.19 Major facility of La Union Port ...... 8-24 Table 8.20 Cargo throughput of La Union Port ...... 8-25 Table 8.21 Container throughput of La Union Port ...... 8-26 Table 8.22 Ship calling at La Union Port on 2012 ...... 8-26 Table 8.23 Economic situations of CA5 countries ...... 8-32 Table 8.24 Locational conditions of ports on the Pacific Coast on CA5 ...... 8-33 Table 8.25 Physical conditions of ports on the Pacific Coast on CA5 (revised) ...... 8-34 Table 8.26 Port management and operation ...... 8-35 Table 8.27 Characteristics of ports on the Pacific Coast of CA5 from type of calling vessel and handling cargo (2012) ...... 8-36 Table 8.28 Characteristics of handling containers of ports on the Pacific Coast of CA5 (2012) ...... 8-37 Table 8.29 Container throughput of the ports in the Central American region ...... 8-39 Table 8.30 Standard value of dimensions of container vessels ...... 8-41 Table 8.31 Changes in number of container services calling at ports ...... 8-46 Table 8.32 Example of MDS containership database (source: MDS containership databank) ...... 8-53 Table 8.33 28 container shipping companies in the model (source: JICA Study Team) ... 8-54 Table 8.34 Central American ports included in the model and their throughput ...... 8-56 Table 8.35 Shares (cover rates) in terms of TEU capacity that containerships called at the ports included in the shipping network of the model ...... 8-57 Table 8.36 Breakdown of cargo by partner regions handled in two Guatemalan ports (2010) ...... 8-64

viii Table 8.37 Share of each coast by partner region for laden container cargo from/to Central America (in TEU basis, 2010) ...... 8-65 Table 8.38 Share of each zone by partner regions (export and import) ...... 8-65 Table 8.39 Settings of level of service in each port ...... 8-68 Table 8.40 Driving time and cost between zone representatives (O and D node) and ports ...... 8-70 Table 8.41 Border-crossing time and cost between zone representatives (O and D node) and ports ...... 8-70 Table 8.42 Estimated amount and share of containers by partner country/region of trade from/to CA4 ports (Source: JICA Study Team’s estimation) ...... 8-74 Table 8.43 Estimation results of export and import port of containers from/into CA4 countries (TEU) ...... 8-74 Table 8.44 Actual and estimated share of shipping companies in Acajutla port (2010) .... 8-75 Table 9.1 Navigation rule of La Union Port ...... 9-3 Table 9.2 Tide Levels of La Union Port provided by CNR ...... 9-7 Table 9.3 PIANC Suggestions on allowance of gross under-keel clearance by case ...... 9-10 Table 9.4 Calculation results of navigable time in the channel ...... 9-11 Table 9.5 Calculation results of average daily navigable time ...... 9-12 Table 9.6 Result of calculation for expected waiting time ...... 9-14 Table 9.7 Estimation result of container cargo throughput in CA4 ports (TEU) considering a liner service to call at La Union Port ...... 9-19 Table 9.8 Future settings of level of service in each port ...... 9-20 Table 9.9 Existing liner shipping service call at Acajutla Port as of May 2010 ...... 9-21 Table 9.10 Existing liner shipping service call at La Union Port as on February 2012 .... 9-21 Table 9.11 Possible alternatives in the level of liner service to be changed from the initial level by shipping company which call at Salvadoran ports at present ...... 9-22 Table 9.12 Possible alternatives to be added as a transshipment service into La Union Port ...... 9-23 Table 9.13 Example of scenario on maritime shipping network for model input (in case of -12m depth) ...... 9-24 Table 9.14 Example of hinterland distribution of Salvadoran ports estimated from the model ...... 9-29 Table 9.15 Example of hinterland distribution of La Union Port estimated from the model (in case of tariff increase) ...... 9-33 Table 9.16 Example of hinterland distribution of La Union Port after the tariff increase (in case of Scenario S30-5-5(14m) with -14m channel depth in 2030) ...... 9-34 Table 9.17 Revenue and expenditure of container business in La Union Port ...... 9-36 Table 9.18 Tariff of La Union Port (related to containers) ...... 9-36 Table 9.19 Container terminal operation cost ...... 9-36 Table 9.20 Revenue and expenditure of container business in the Salvadoran port sector 9-37 Table 9.21 Tariff of Acajutla Port (related to containers) ...... 9-37 Table 9.22 Economic benefit and cost of dredging project of the channel in La Union Port (comparison to the “no-dredging” scenario) ...... 9-37 Table 9.23 Estimated container throughput and ship calls in La Union Port (2020) ...... 9-38 Table 9.24 Estimated container throughput and ship calls in La Union Port (2030) ...... 9-38 Table 9.25 Dredging cost by channel depth and model ...... 9-39 Table 9.26 Maximum net income from container business in La Union Port (2020) ...... 9-40 Table 9.27 Maximum net income from container business in La Union Port (2030) ...... 9-40 Table 9.28 Maximum difference between net income and dredging cost by channel depth in La Union Port (2020) ...... 9-40

ix Table 9.29 Maximum difference between net income and dredging cost by channel depth in La Union Port (2030) ...... 9-40 Table 9.30 Container throughput and ship calls in Acajutla Port and La Union Port (2020) ...... 9-41 Table 9.31 Container throughput and ship calls in Acajutla Port and the La Union Port (2030) ...... 9-41 Table 9.32 Maximum net income from container business in Acajutla Port and La Union Port(2020) ...... 9-43 Table 9.33 Maximum net income from container business in the Acajutla Port and the La Union Port(2030) ...... 9-43 Table 9.34 Maximum difference between net income for Salvadoran port sector and dredging cost by channel depth in La Union Port (2020) ...... 9-43 Table 9.35 Maximum difference between net income for Salvadoran port sector and dredging cost by channel depth in La Union Port (2030) ...... 9-44 Table 9.36 Maximum net benefit of dredging project for Salvadoran economy by channel depth(2020) ...... 9-46 Table 9.37 Maximum net benefit of dredging project for Salvadoran economy by channel depth(2030) ...... 9-46 Table 9.38 Maximum economic benefit of dredging project for Salvadoran economy by channel depth (2020) ...... 9-46 Table 9.39 Maximum economic benefit of dredging project for Salvadoran economy by channel depth (2030) ...... 9-46 Table 9.40 New tariff set in La Union Port...... 9-47 Table 9.41 Estimated container throughput and ship calls in La Union Port in case of the tariff increase (2020) ...... 9-47 Table 9.42 Estimated container throughput and ship calls in La Union Port in case of the tariff increase (2030) ...... 9-47 Table 9.43 Maximum net income from container business in La Union Port in case of the tariff increase (2020) ...... 9-49 Table 9.44 Maximum net income from container business in La Union Port in case of the tariff increase (2030) ...... 9-49 Table 9.45 Maximum difference between net income in case of the tariff increase and dredging cost by channel depth in La Union Port (2020) ...... 9-49 Table 9.46 Maximum difference between net income in case of the tariff increase and dredging cost by channel depth in La Union Port (2030) ...... 9-49 Table 9.47 Container throughput and ship calls in Acajutla Port and La Union Port in case of the tariff increase in La Union Port (2020) ...... 9-50 Table 9.48 Container throughput and ship calls in Acajutla Port and La Union Port in case of the tariff increase in La Union Port (2030) ...... 9-50 Table 9.49 Maximum net income from container business in Acajutla Port and La Union Port in case of the tariff increase in La Union Port (2020) ...... 9-52 Table 9.50 Maximum net income from container business in Acajutla Port and La Union Port in case of the tariff increase in La Union Port (2030) ...... 9-52 Table 9.51 Maximum difference between net income for Salvadoran port sector in case of the tariff increase and dredging cost by channel depth in La Union Port (2020) ... 9-52 Table 9.52 Maximum difference between net income for Salvadoran port sector in case of the tariff increase and dredging cost by channel depth in La Union Port (2030) ... 9-52 Table 9.53 Maximum net benefit of dredging project for Salvadoran economy by channel depth in case of the tariff increase (2020) ...... 9-55 Table 9.54 Maximum net benefit of dredging project for Salvadoran economy by channel

x depth in case of the tariff increase (2030) ...... 9-55 Table 9.55 Maximum economic benefit of dredging project for Salvadoran economy by channel depth in case of the tariff increase (2020) ...... 9-55 Table 9.56 Maximum economic benefit of dredging project for Salvadoran economy by channel depth in case of the tariff increase (2030) ...... 9-55 Table 9.57 Estimated container throughput and ship calls in La Union Port in case of the advancement of regional development in the eastern El Salvador (2020) ...... 9-56 Table 9.58 Maximum net income from container business in La Union Port in case of the advancement of regional development in the eastern El Salvador (2020) ...... 9-57 Table 9.59 Maximum difference between net income in case of the advancement of regional development in the eastern El Salvador and dredging cost by channel depth in La Union Port (2020) ...... 9-57 Table 10.1 Items of dredging cost summarized in terms of the timing when it is needed 10-1 Table 10.2 Re-dredging cost (US$) estimated for each combination of existing and target depth ...... 10-2 Table 10.3 Mobilization cost (US$) of re-dredging for each combination of existing and target depth ...... 10-2 Table 10.4 Cost for purchasing dredger (US$) by target depth for both models to predict the change of water depth after the initial dredging ...... 10-3 Table 10.5 Mobilization cost for maintenance dredger (US$) estimated for each target depth ...... 10-3 Table 10.6 Regular cost for maintenance dredging (US$/year) for each target depth ...... 10-3 Table 10.7 Estimated container cargo throughput and other revenue/cost for each channel depth in 2010 ...... 10-4 Table 10.8 Example of a representative result on container cargo throughput and other revenue/cost for each channel depth in 2020 and 2030 ...... 10-5 Table 10.9 Example of calculation result on optimal year and net benefit for each combination of target depth after the first and second re-dredging and each type of dredging (before increasing the tariff in La Union Port) ...... 10-13 Table 10.10 Example of calculation result on optimal year and net benefit for each combination of target depth after the first and second re-dredging and each type of dredging (after increasing the tariff in La Union Port) ...... 10-14

xi List of Figures

Figure 1.1 History of La Union Port ...... 1-2 Figure 1.2 Changes of the sea bottom in the Inner channel ...... 1-3 Figure 1.3 Changes of the sea bottom in the Outer channel ...... 1-4 Figure 1.4 Bathymetry of Gulf of Fonseca reproduced from Chart 21521 of US NGIA .... 1-5 Figure 1.5 Satellite photograph of Gulf of Fonseca reproduced from ...... 1-5 Figure 1.6 Sediment classification and median diameter around the Inner channel ...... 1-6 Figure 1.7 Sediment classification and median diameter around the Outer channel ...... 1-7 Figure 3.1 Bathymetric survey lines of access channel ...... 3-2 Figure 3.2 Bathymetric survey lines in harbor basin ...... 3-2 Figure 3.3 Longitudinal depth variation along the centerline of access channel ...... 3-3 Figure 3.4 Transversal depth profiles of Outer Channel with the planned channel profile (L1, L2, and L3) ...... 3-4 Figure 3.5 Transversal depth profiles of Outer Channel with the planned channel profile . 3-5 Figure 3.6 Transversal Depth profiles of Outer Channel with the planned channel profile 3-6 Figure 3.7 Transversal depth profiles of Outer Channel with the planned channel profile . 3-7 Figure 3.8 Transversal depth profiles of Inner Channel with the planned channel profile . 3-8 Figure 3.9 Transversal depth profiles of Inner Channel with the planned channel profile . 3-9 Figure 3.10 Depth profiles of Turning Basin on the lines perpendicular to the wharf...... 3-10 Figure 3.11 Depth profiles of Turning Basin on the lines perpendicular to the wharf...... 3-11 Figure 3.12 Depth profiles of Turning Basin on the lines parallel to the wharf...... 3-12 Figure 3.13 Variation of mean depth of the access channel ...... 3-15 Figure 3.14 Variation of mean depth of the inner access channel and harbor basin ...... 3-15 Figure 3.15 Transversal channel profiles with the acoustic signals of 38 kHz and 200 kHz at L18 to L20 (SAPI, 2009) ...... 3-16 Figure 3.16 Location of sampling sites ...... 3-18 Figure 3.17 Lifting of sampling tube at Site E (a) and Sampling tube at Site E (b) ...... 3-19 Figure 3.18 Cutting a sampling pipe into sections of 0.3 m long ...... 3-20 Figure 3.19 Photographs of mud sample with its density ...... 3-21 Figure 3.20 Vertical profile of mud wet density outside the access channel ...... 3-22 Figure 3.21 Vertical profile of mud wet density inside the access channel ...... 3-22 Figure 3.22 Relationship between moisture content and wed density of mud samples .... 3-23 Figure 3.23 Deposition speed employed in calibration of mud consolidation analysis .... 3-25 Figure 3.24 Time evolution of (a) channel mean depth and (b) mud wet density profile at Site D ...... 3-26 Figure 3.25 Time evolution of (a) channel mean depth and (b) mud wet density profile at Site E ...... 3-26 Figure 3.26 Deposition speed employed in prediction of mud deposition after maintenance dredging ...... 3-27 Figure 3.27 Time evolution of (a) siltation height and (b) bottom mud wet density after maintenance dredging ...... 3-28 Figure 3.28 Time evolution of bottom mud wet density versus siltation height after maintenance dredging...... 3-28 Figure 3.29 Time evolution of mud wet density profile. (a) h = 3.0 m and (b) h = 4.5 m ...... 3-28 Figure 3.30 Time evolution of mud wet density profile. (a) h0 = 6.0 m and (b) h0= 7.5 m ...... 3-29 Figure 4.1 Period of dredging and times of bathymetric surveys ...... 4-1

xii Figure 4.2 Changes of water depth in the Inner and the Outer channel ...... 4-2 Figure 4.3 Bathymetric survey lines of access channel ...... 4-3 Figure 4.4 Siltation speed versus the depth difference inside and outside the access channel...... 4-3 Figure 4.5 Definition of water depths ...... 4-4 Figure 4.6 Comparison of predicted and measured channel depths for selected survey lines ...... 4-5 Figure 4.7 Changes of water depth on the reference lines from L21 to L18 in Inner channel ...... 4-6 Figure 4.8 Superposition of cross section along L21 ...... 4-7 Figure 4.9 Superposition of cross section along L20~L18 ...... 4-8 Figure 4.10 Superposition of cross sections after shifting, for L21 (Cross section in December, 2008 is shifted by 0.6m upward) ...... 4-8 Figure 4.11 Superposition of cross section along the reference lines of L20 to L18, after shifting date obtained in December, 2008 upward ...... 4-9 Figure 4.12 Corrections of depth data in Inner channel ...... 4-10 Figure 4.13 Locations of reference lines in Outer channel ...... 4-11 Figure 4.14 Changes of water depth on the reference lines from L08 to L05 in Outer channel ...... 4-12 Figure 4.15 Periods of dredging in the Outer channel and the bathymetric data utilized for consideration ...... 4-13 Figure 4.16 Situation of full-sedimentation along L08～L05 in Outer channel ...... 4-13 Figure 4.17 Conceptual diagram of dynamic equilibrium condition before dredging ...... 4-15 Figure 4.18 Conceptual diagram of siltation in Outer channel ...... 4-15 Figure 4.19 Superposition of cross sections along L07and L06 ...... 4-16 Figure 4.20 Spatial distribution of sediment ...... 4-16 Figure 4.21 Superposition of cross sections just after the second dredging, (Surveyed on 28 April and 5 May, 2008) ...... 4-17 Figure 4.22 Superposition of cross sections, 11 August, 2008, about 3 and half months after the dredging ...... 4-18 Figure 4.23 Spatial distribution of sedimentation ...... 4-18 Figure 4.24 Gap of cross section, on reference line L21（Inner channel） (Reproduce from Figure 4.8) ...... 4-19 Figure 4.25 Siltation speed versus the depth difference in the Inner channel, after the correction of data ...... 4-20 Figure 4.26 Comparison of original and modified Exponential Model with the actual depth ( for Inner c) ...... 4-21 Figure 4.27 Modification of Exponential Model by introducing a concept of final depth ( for Outer channel) ...... 4-22

Figure 4.28 Longitudinal profile of final depth he of Outer channel ...... 4-22 Figure 4.29 Comparison of original and modified Exponential model with the actual depth (for Outer channel) ...... 4-23 Figure 4.30 Time variations of channel depth for Inner and Outer channels ...... 4-24 Figure 4.31 Representative siltation speed for Inner and Outer channel ...... 4-25 Figure 4.32 Connection of Linear Model to Modified Exponential Model ...... 4-25 Figure 4.33 Coordinate system in harbor basin ...... 4-27 Figure 4.34 Cross sections along the line of x=200m, perpendicular to the wharf ...... 4-27 Figure 4.35 Bottom profiles along the line of Y=-400m, parallel to the wharf ...... 4-28 Figure 4.36 Cross sections along the line of L22, perpendicular to wharf ...... 4-28

xiii Figure 4.37 Comparisons between the predicted and the measured relative siltation height ...... 4-29 Figure 5.1 Longitudinal profile on the centerline of the access channel surveyed at July 2013 ...... 5-1 Figure 5.2 Channel Shape for re-dredging volume calculation ...... 5-2 Figure 5.3 Definition of overbreak in channel dredging ...... 5-3 Figure 5.4 Definition of the navigable depth and the measured depth ...... 5-4 Figure 5.5 Sketch of rise of channel bottom between maintenance dredging...... 5-5 Figure 5.6 Maintenance dredging volume (plotted by a fixed vertical scale) ...... 5-9 Figure 5.7 Maintenance dredging volume (plotted on different vertical scales) ...... 5-10 Figure 5.8 Maintenance dredging volume by Depths ...... 5-11 Figure 5.9 Definition of height of dredging and over dredging height below the target depth ...... 5-12 Figure 5.10 Over dredging depths estimated by Mod. Exp. Model ...... 5-13 Figure 5.11 Over dredging depths estimated by Linear Model ...... 5-14 Figure 5.12 Correspondence between over dredging depth and annual dredging volume 5-15 Figure 5.13 Conceptual drawing of Cutter Suction Dredger (Source: “Dredging; A handbook for engineers” R N Bray et al., 1998) ...... 5-17 Figure 5.14 Conceptual drawing of TSHD (Source: “Dredging; A handbook for engineers” R N Bray et al.,1998) ...... 5-18 Figure 5.15 Conceptual drawing of Grab Hopper Dredger ...... 5-19 Figure 5.16 Photo and Conceptual drawing of Grab Dredger (pontoon type) ...... 5-20 Figure 5.17 Conceptual drawing of Backhoe Dredger (Source: “Mimar Sinan” Jan De Nul Group) ...... 5-21 Figure 5.18 Location of dumping site ...... 5-26 Figure 5.19 Necessary time for dredging work ...... 5-28 Figure 5.20 Necessary dredger capacity for maintenance dredging (m3) in the case of Modified Exponential Model ...... 5-30 Figure 5.21 Necessary dredger capacity for maintenance dredging (m3) in the case of Linear Model ...... 5-30 Figure 5.22 Cost estimation items of dredging by contract base ...... 5-31 Figure 5.23 Cost estimation items of dredging by own dredger intended by CEPA ...... 5-31 Figure 5.24 Building price of TSHD by capacity ...... 5-33 Figure 5.25 Relation with TSHD capacity and total engine power ...... 5-36 Figure 5.26 Relation with TSHD capacity and pump power ...... 5-36 Figure 5.27 Dredging cost of dredging by contract base (Cost comparison between Modified Exponential Model and Linear Model) ...... 5-43 Figure 5.28 Dredging cost of dredging by own dredger (Cost comparison between Modified Exponential Model and Linear Model) ...... 5-43 Figure 5.29 Structure for costs of re-dredging and maintenance dredging ...... 5-44 Figure 5.30 Relation between cycle time and annual volume of maintenance dredging .. 5-44 Figure 5.31 Relation between cycle time and working ratio in cases of ...... 5-45 Figure 5.32 Relation between cycle time and working ratio for necessary dredger capacities ...... 5-46 Figure 5.33 Relation between cycle time and annual dredging cost ...... 5-46 Figure 5.34 Dredging cost comparison between dredging by contract base and by own dredger ...... 5-47 Figure 5.35 Comparison of direct and indirect cost by contract base and own dredger (12m target depth of Modified Exponential Model with 3 months cycle) ...... 5-48 Figure 5.36 Dredging cost and dredger capacity by water depth ...... 5-49

xiv Figure 6.1 Survey lines for Inner channel with the transversal length of 500 m and the longitudinal pitch of 1 km...... 6-4 Figure 6.2 Survey lines for Inner channel with the transversal length of 500 m and the longitudinal pitch of 1 km ...... 6-5 Figure 6.3 Survey lines for Port area (basin) with the pitch length of 200 m ...... 6-6 Figure 6.4 Equipment of the bathymetric survey mounted by CEPA staffs ...... 6-7 Figure 6.5 Relation between measured and corrected water depth ...... 6-8 Figure 6.6 Variation of tide level of April 19, 2013 ...... 6-8 Figure 6.7 Tidal correction parameters related to the locations of the channel (from SAPI’s report) ...... 6-9 Figure 6.8 Screenshot of the geodetic converter which CEPA staffs use ...... 6-10 Figure 6.9 Post-processing tools coded by Excel/VBA ...... 6-11 Figure 6.10 Example of the post-processed data ...... 6-12 Figure 6.11 Vertical reference employed by CNR ...... 6-15 Figure 6.12 Vertical reference employed by DD-Report (CUT-9 is a benchmark located on the south-eastern corner of the port of La Union) ...... 6-15 Figure 6.13 Variation of water depth along the access channel before depth correction. . 6-17 Figure 6.14 Variation of water depth along the access channel after depth correction. .... 6-17 Figure 8.1 Cargo volume of main ports of El Salvador ...... 8-2 Figure 8.2 Location of Acajutla Port ...... 8-2 Figure 8.3 Port layout ...... 8-3 Figure 8.4 Transition of import / export cargo volume by category ...... 8-5 Figure 8.5 Transition of container cargo ...... 8-6 Figure 8.6 Container yard layouts ...... 8-12 Figure 8.7 Location of each berth ...... 8-13 Figure 8.8 General plan view of A berth ...... 8-13 Figure 8.9 Cross section of B berth ...... 8-14 Figure 8.10 Cross section of C berth ...... 8-14 Figure 8.11 Continuous red-orange colored rust on steel sheet piles in A berth ...... 8-15 Figure 8.12 Situation of steel pipe piles in B berth ...... 8-15 Figure 8.13 Peeled off concrete in A berth ...... 8-16 Figure 8.14 Concrete wall facing to outer sea in C berth ...... 8-16 Figure 8.15 Hammer inspection on steel sheet piles in A berth...... 8-16 Figure 8.16 Test points performed by Schmidt hammer ...... 8-17 Figure 8.17 Position of Schmidt hammer ...... 8-17 Figure 8.18 Position of Schmidt hammer for A berth ...... 8-17 Figure 8.19 Position of Schmidt hammer for B berth ...... 8-18 Figure 8.20 Planned electric power plant ...... 8-23 Figure 8.21 Road network from / to Acajutla Port ...... 8-23 Figure 8.22 Location of La Union Port ...... 8-24 Figure 8.23 Plan of La Union Port ...... 8-25 Figure 8.24 Development plan of La Union Port ...... 8-27 Figure 8.25 Container ports in the Central American region...... 8-38 Figure 8.26 Container ports on the Pacific Coast of CA5 ...... 8-40 Figure 8.27 Distribution of capacity of deployed vessels ...... 8-40 Figure 8.28 Containership movement of each shipping company ...... 8-45 Figure 8.29 Whole structure of the vessel calling model (source: JICA Study Team) ...... 8-52 Figure 8.30 Location of ports in Central America (added ports in this model are shown in red letter) (source: JICA Study Team) ...... 8-56 Figure 8.31 All ports dealt in the model (source: JICA Study Team) ...... 8-57

xv Figure 8.32 Shipping network considered in the container cargo assignment model ...... 8-59 Figure 8.33 Land shipping network considered in this project ...... 8-69 Figure 8.34 Container cargo throughput reproduced by the developed model compared with the actual throughput (Source: JICA Study Team’s estimation) ...... 8-73 Figure 8.35 Example of estimated container flow by liner service (Maersk, 2010) ...... 8-76 Figure 8.36 Sensitivity of unknown parameters [1] value of time for shippers vt and container cargo throughput by each CA4 port (Source: JICA Study Team’s estimation) ...... 8-77 Figure 8.37 Sensitivity of unknown parameters [2] distribution parameter θ and container cargo throughput by each CA4 port (Source: JICA Study Team’s estimation) ...... 8-78 Figure 8.38 Sensitivity of unknown parameters [3] adjustment parameter on bonded transportation α and container cargo throughput by each CA4 port ...... 8-79 Figure 9.1 Navigation channel of La Union Port ...... 9-2 Figure 9.2 Vertical level reference ...... 9-7 Figure 9.3 Tide level of La Union Port in 2013 ...... 9-8 Figure 9.4 Definition of under-keel clearances ...... 9-10 Figure 9.5 Concept for calculation of expected waiting time ...... 9-13 Figure 9.6 Calculation results of expected waiting time by channel depth ...... 9-15 Figure 9.7 Relationships between draft and container loading capacity in TEUs ...... 9-15 Figure 9.8 Output tool of navigable time range ...... 9-16 Figure 9.9 Calculation result of expected waiting time according to the current navigation rule ...... 9-17 Figure 9.10 Service route operated by APL and Hamburg-Sud in 2012 ...... 9-18 Figure 9.11 Base and example case of maritime shipping network (displayed only services to call at Acajutla Port or La Union Port) ...... 9-25 Figure 9.12 Container cargo throughput for each feasible scenario in La Union Port (above) and Acajutla Port (below) in 2020 ...... 9-27 Figure 9.13 Container cargo throughput for each feasible scenario in La Union Port (above) and Acajutla Port (below) in 2030 ...... 9-28 Figure 9.14 Container cargo throughput for each feasible scenario in La Union Port (above) and Acajutla Port (below) in 2020 (in case of tariff increase in La Union Port) ...... 9-31 Figure 9.15 Container cargo throughput for each feasible scenario in La Union Port (above) and Acajutla Port (below) in 2030 (in case of tariff increase in La Union Port) ...... 9-32 Figure 9.16 Difference of impact of tariff increase on container cargo throughput: current border barrier (above) and case that any border barrier is removed (below) ...... 9-33 Figure 9.17 Container cargo throughput for each feasible scenario in La Union Port (above) and Acajutla Port (below) in 2020 (in case of regional development in Eastern El Salvador) ...... 9-35 Figure 9.18 Estimated net income and dredging cost by channel depth in La Union Port (2020) ...... 9-39 Figure 9.19 Estimated net income and dredging cost by channel depth in La Union Port (2030) ...... 9-39 Figure 9.20 Estimated net income for Salvadoran port sector (sum of Acajutla Port and La Union Port) and dredging cost by channel depth in La Union Port (2020) ...... 9-42 Figure 9.21 Estimated net income for Salvadoran port sector (sum of Acajutla Port and La Union Port) and dredging cost by channel depth in La Union Port (2030) ...... 9-42 Figure 9.22 Estimated net benefit of dredging project for Salvadoran economy and dredging cost by channel depth (2020) ...... 9-45 Figure 9.23 Estimated net benefit of dredging project for Salvadoran economy and dredging cost by channel depth (2030) ...... 9-45

xvi Figure 9.24 Estimated net income in case of the tariff increase and dredging cost by channel depth in La Union Port (2020) ...... 9-48 Figure 9.25 Estimated net income in case of the tariff increase and dredging cost by channel depth in La Union Port (2030) ...... 9-48 Figure 9.26 Estimated net income for Salvadoran port sector (sum of Acajutla Port and La Union Port) in case of the tariff increase and dredging cost by channel depth in La Union Port (2020) ...... 9-51 Figure 9.27 Estimated net income for Salvadoran port sector (sum of Acajutla Port and La Union Port) in case of the tariff increase and dredging cost by channel depth in La Union Port (2030) ...... 9-51 Figure 9.28 Estimated net benefit of dredging project for Salvadoran economy in case of the tariff increase and dredging cost by channel depth (2020) ...... 9-54 Figure 9.29 Estimated net benefit of dredging project for Salvadoran economy in case of the tariff increase and dredging cost by channel depth (2030) ...... 9-54 Figure 9.30 Estimated net income in case of the advancement of regional development in the eastern El Salvador and dredging cost by channel depth in La Union Port (2020) ...... 9-56 Figure 10.1 Typical example on framework of time-series income-cost calculation (in case of contract-basis dredging for the first ten years) ...... 10-7 Figure 10.2 Typical example on framework of time-series income-cost calculation (in case of own-basis dredging) ...... 10-9 Figure 10.3 Typical example on framework of time-series income-cost calculation (in case of own-basis dredging without second re-dredging) ...... 10-9 Figure 10.4 Example of a calculation sheet (in an excel-basis) for time-series estimation of net income and benefit including container cargo throughput, revenue of both Acajutla Port and La Union Port, dredging and other cost ...... 10-11

xvii

Chapter 1 Introduction

1.1 Overview of Development of La Union Port

1.1.1 Development of La Union Port The economic structure of the Republic of El Salvador depends strongly on foreign trade, and a major of its freight distribution is a marine transportation, which plays a significant role on the development of the country. However, Acajutla Port which is only one international trade port in the country is directly exposed to the full energy of the Pacific Ocean. Because of this natural condition, there is a limit on the capacity of freight handling, especially for containers. There was no enough facility in El Salvador which could manage the increasing of seaborne traffic and a global trend of containerizing freight transportation.

The Department of La Union, which is the easternmost Department of Republic of El Salvador, is bordered with Honduras and Nicaragua across the Gulf of Fonseca. A port named Cutuco had been developed at the western waterfront of the Gulf of Fonseca at the distance of about 25 km from the entrance of the Gulf. The port handled 236 thousands ton of cargo in 1975, but the trade dwindled considerably during the civil war time late 1980s and early 1990s. The Department of La Union had been lagging in economy in comparison with other departments.

After the cease of the civil war, the Republic of El Salvador decided to develop the new port in the Department of La Union, which had an objective of stimulating economical and industrial development through the port activity in the Department of La Union. And also the new port is expected to function as a hub port of container ships along the Pacific coast of the Central American continent.

The Government of El Salvador requested the Japanese Government to prepare a master plan for the port expansion and to carry out a feasibility study for the short-term facility installation plan. The latter responded to the request by executing the feasibility study of La Union Port through Japan International Cooperation Agency (hereinafter referred to as “JICA”) during October 1997 to December 1998 and presenting the final report. Following the feasibility study, the detailed design was made during July 2001 to January 2003. The name of port was changed from Cutuco to La Union with a slight location shift of the wharf area.

The project of constructing La Union Port began in April 2005 with a total cost of about 21,400 million Japanese yen among which 11,233 million Japanese yen was provided by the Japan Bank for International Cooperation (hereinafter referred to as “JBIC”) as the low-interest loan, and construction of the civil engineering works was completed in December 2008.

The history of La Union Port mentioned above is shown in Figure 1.1.

1-1

Figure 1.1 History of La Union Port

1.1.2 Harbor Facilities of La Union Port La Union Port has been designed for Post-Panamax container ships, bulk carriers of 50,000 DWT, and passenger ships of 25,000 DWT classes. The channel had been dredged to a depth of 14 m, but the entire passage has been filled in by siltation, and the depth when it was completed has not been maintained.

The port has one container berth with a length of 340 m and a depth of 15.0 m, one multi-purpose berth with a length of 220 m and a depth of 14.0 m, and a passenger berth with a length of 240 m and a depth of 9.5 m. However, the water depth at every facility becomes shallower due to siltation. The yard areas are built by reclamation with a fill volume of 3.0 million m3.

The turning basin has a diameter of 600 m and had the depth of 14 m. Also in this area, the water depth becomes shallower due to siltation. The total area of the harbor basin with the berth area and the turning basin is measured as 65.7 ha.

The access channel of 22.3 km long is divided into the inner and outer parts by the narrow waterway between Cape Chiquirin and Zacatillo Island. The Inner channel is about 5.0 km long and the Outer channel is 17.3 km long. When the dredging works completed in 2008, the Inner channel had the width of 140 m at the bottom and the water depth of 14m, while the Outer channel had the width of 137 m and the water depth of 14.5m. About 4.5 km of the Inner channel were cut through the water area shallower than 10 m with the shallowest portion of about 6 m. The length of the outer channel pass through the area shallower than 10 m is about 1.5 km; the shallowest depth is about 9 m. The side slope is designed with a gradient of 1 on 5.

1-2 1.2 Recognition of Siltation Problem in La Union Port and Commencement of SAPI Study

When La Union Port was under construction toward its completion at the end of November 2008, it was observed a large quantity of siltation in the Inner and Outer channels and the harbor basin, based on the bathymetric surveys performed during the execution of the dredging works (see Figure 1.1).

Bathymetric surveys around the harbor basin and access channel have been conducted before and during the construction works by using an echo sounder equipped with 210 kHz frequency acoustic signals. When the reflection of the 210 kHz frequency waves is regarded to the presence/detection of the sea bottom, the volume of siltation from April 2007 up to January 2008 is calculated as listed in Table 1.1. The volume of sedimentation in the harbor basin and access channel had been predicted in the Detailed Design Report, which was submitted by Nippon Koei Ltd in 2002, and they are also listed in Table 1.1. The prediction was done by a numerical computer simulation by Hydraulic Research (HR) Wallingford, U.K. under commission. Actual siltation was 4 to 8 times the prediction as of early 2008.

Table 1.1 Volume of siltation deposited from April 2007 to January 2008 in comparison with prediction at the time of Detailed Design Study in 2002 Name Area Vo l u me ( m 3) (m2) Obs. Pred. Harbor basin 657,000 158,000 478,000 Inner channel 626,000 1,973,000 453,000 Outer channel 1,660,000 2,389,000 312,000 Total 2,943,000 4,521,000 1,243,000

Examples of the temporal progress of siltation are shown in Figure 1.2 and Figure 1.3 at three locations of the access channel at the distance of 2.78, 16.0, and 17.0 km from the harbor basin. As seen in these figures, the interface observed with a 210 kHz frequency waves rose by about 3 m in these locations in ten months from April 2007 to January 2008.

Figure 1.2 Changes of the sea bottom in the Inner channel

1-3

Figure 1.3 Changes of the sea bottom in the Outer channel

During the dredging works of the project, unexpectedly fast siltation in the channel had been observed, which might endanger the smooth operation of the port when it opens. Since the cause of such phenomenon was not identified, it was not possible to estimate the future siltation volume, nor to find an adequate measure. Then, a scrutiny of fast siltation became an acute task.

The JBIC and the Comisión Ejecutive Portuaria Autónoma (hereinafter referred to as “CEPA”) discussed on the necessity of study on the fast siltation in July, 2008, and they agreed upon to start the Special Assistance for Project Implementation for La Union Port Development Project (hereinafter referred to as “SAPI”).

The objectives of the SAPI Study are itemized as in the following: i) Clarify the present situation of the siltation in La Union Port, ii) Estimate the volume of future siltation in case of no countermeasures, iii) Propose and recommend the appropriate countermeasures against siltation, iv) Clarify the environmental conditions such as tide, currents, waves, soil, and others, through data collection, field survey, and numerical simulations. Under these objectives, the following works had been conducted:

A. Survey of the Policy and Practice of Harbor Maintenance with Nautical Bottom Concept in World Ports B. Collection and Analysis of Environmental Condition C. Estimation of Present and Future Siltation Volume D. Examination of Countermeasures against Siltation

The SAPI Study was undertaken by JICA** and executed during November 2008 to November 2009 (see Figure 1.1).

** Note: On 1st October, 2008, the Overseas Economic Cooperation Operation of JBIC has been merged with JICA.

1.3 Result of SAPI Study

The major results concerning with the siltation problem are cited from the Report of SAPI.

1-4 1.3.1 The Gulf of Fonseca and Feeder Rivers The Gulf of Fonseca is about 65 km wide and 45 km long, having an area of about 3,200 km2(see Figure 1.4). Figure 1.5 is a satellite photograph of the Gulf of Fonseca, which has three embayments. From the west to the east, they are the Bay of La Union, Bay of Chismuyo (Honduras), and Bay of San Lorenzo (Honduras). As indicated with dark green color in Figure 1.5, the periphery of the Gulf is occupied by wide stretches of mangrove forests. The total area of mangrove forests is estimated at about 780 km2. Five major rivers flow into the Gulf : Goascoran, Nacaome, Choluteca, Negro, and Estero Real from the west to the east. These rivers are discernible in Figure 1.5 with indigo color, together with many creeks and inlets that penetrate deep into mangrove swamps. Many small rivers flow directly into the Gulf; they collecting rainwater falling on open fields around the Gulf. Mud in the Gulf of Fonseca has come from the suspended sediments during floods from many rivers. Sediments of bed load are mostly caught by mangrove swamps at the head of the Gulf. Suspended sediments of silt and clay are diffused with flood discharge and uniformly spread over the whole bay areas with a thickness of 0.2 to 1.2m.

Figure 1.4 Bathymetry of Gulf of Fonseca reproduced from Chart 21521 of US NGIA

Figure 1.5 Satellite photograph of Gulf of Fonseca reproduced from

1-5

1.3.2 Sediment classification and mechanism of siltation Figure 1.6 and Figure 1.7 show the sediment content and the median diameter of the samples around the Inner and Outer channels, respectively.

In the area north of Cape El Chiquirin, most of the seabed is covered with silt and mud except for a few locations such as Stations 9, 12, 24, and 26, where local supply of fine sand seems to be available. The median diameter varies from 0.013 to 0.034 mm excluding the sites with local fine sand.

Figure 1.6 Sediment classification and median diameter around the Inner channel

In the area south of Cape El Chiquirin, the stations outside the Outer channel indicate the fine sand content of 30% to 50% except for Station 20 at the outcrop near Conchanguita Island.

Within the channel, however, sand content is few with a median diameter of 0.02 to 0.04 mm. Little sand content along the outer channel as exhibited at Stations 1 to 6 indicates that sand does not move into the channel, but silt and mud are brought into the channel. That is to say, siltation in the channel is caused by the movement of silt and clay, while fine sand remain in its original position. This supports the concept on siltation mechanism that a thin layer of fluid mud on the

1-6 sea bottom creeps down into a deeper section by gravity.

What is happening in La Union Port is the movement of fluid mud layer as a density current. Wherever there is the elevation difference on the seabed such as across a dredged channel, fluid mud flows into the lower elevation by gravity. Movement continues as long as there is an elevation difference on the surface of fluid mud between the seabed inside and outside the channel.

Figure 1.7 Sediment classification and median diameter around the Outer channel

1.3.3 Establishment of prediction formulae for siltation speed and channel depth The most reliable data for the analysis of siltation problem is the records of bathymetric surveys of the access channel since June 2006 when the capital dredging started.

A trend analysis of the temporal variation of the mean channel depth at traverse survey lines has

1-7 enabled to establish an empirical prediction formula for siltation speed as a function of difference in the depths inside and outside the channel, and the time elapsed from completion of capital dredging.

Another prediction formula for estimation of channel depth in future has also been derived from the siltation speed formula. The channel depth prediction formula has been validated with the records of previous bathymetric survey results.

1.4 Objectives and Major Works of this Study

The SAPI Study clarified that the siltation is caused by slow movement of fluid mud toward a deeper seabed. Based on the analysis of bathymetric survey data during and after the dredging works, the prediction formulae for siltation were established. By utilizing the formula for estimation of channel depth, it was predicted that the siltation volume in the access channel with the depth of 14 m would be 10 million cubic meters per year.

Owing to the limited quantity of bathymetric time-series data and a relatively short duration of the study, however, the accuracy of the predicted siltation volume was not high enough to make reliable estimate of the volume of maintenance dredging. The variation of nautical depth, which is dependent on the speed of mud consolidation, also remained as not clarified enough. Thus, it is currently recognized that a definitive plan for maintenance dredging including location, frequency and method for elaboration of dredging cost and financial analysis is difficult to be provided.

To make the port function properly as a deep sea port, dredging method as well as cost is a vital issue in financial viability and a key factor for successful terminal operation either in the contingent stage of operation or in the stage of concession. Hence, CEPA requested JICA to provide an effective and efficient maintenance dredging plan.

According to a result of discussion between JICA and CEPA, Minutes of Meeting on 28 April, 2010 (see Annex A), JICA commenced the 1st Term Study in January 2011 and conducted a series of bathymetric survey and analysis for about one year and four months up to May 2012. The 1st Term Study had the following two purposes as stated in the Minutes of Meeting:

(1) To prepare an effective and efficient channel maintenance plan to make La Union Port function properly as a deep sea port. (2) To transfer technology to cope with the siltation in the channel and basin and to assist CEPA to review/revise the prepared dredging plan based on the bathymetric monitoring data.

The survey and analysis have proved that detailed analysis of future shipping service, detailed demand forecast, and the data of trial dredging are inevitable for making valid maintenance dredging plan. Hence, JICA and CEPA discussed and agreed to revise the TOR of Special Technical Assistance for Maintenance Dredging of the Port of La Union before the commencement of the 2nd Term Study, which has done on 31 October, 2012 (see Annex A). In the 2nd Term Study, not only the engineering issue but also the economic issue is included in the study scope to analyze technically/financially and economically optimum channel depths at present and in the future.

The 2nd Term Study has the following three purposes as stated in the Minutes of Meeting between JICA and CEPA on 31 October, 2012 (see Annex A):

1-8 (1) To prepare data, information and analysis utilized by CEPA to formulate an effective and efficient maintenance dredging plan of the Port. (2) To transfer technology to cope with the siltation in the channel and basin. (3) To assist CEPA to prepare dredging plan based on the collected data and analysis.

1.5 Engineers concerned and Chronologies of Study

1.5.1 Engineers concerned (1) Project Support Committee in Japan In order to properly implement the project on “Special Technical Assistance for Maintenance Dredging of the Port of La Union in the Republic of El Salvador”, the Project Support Domestic Committee has been established in the Economic Infrastructure Department, JICA Headquarters. Table 1.2 is the list of committee members. The Committee evaluates items with respect to the following issues and gives advice to the director of department, from an academic and technical view point.

1. Issues related to siltation in the channel 1) Analysis of present situation 2) Analyses of siltation volume and speed in the whole stretch of access channel including the basin 3) Collection and Analysis of the rake-dredging data and study on the dredging method 4) Estimation of dredging cost by the target navigation depth of channel 5) Suggestion about countermeasures against channel siltation 2. Any other necessary issues

Table 1.2 List of members of Project Support Domestic Committee in Japan Name Specialism Affiliation Chairman Dr. Kazuo Siltation in General and Emeritus professor, MURAKAMI Countermeasures for Tokyo City University Channel Siltation Member Dr. Yasuyuki Coastal and Estuary Team Leader of Coastal and NAKAGAWA Sediment Dynamics Estuary Sediment Dynamics Research Group, Port and Airport Research Institute Member Mr. Tsuyoshi Administration on Operation Chief of International NAKASAKI and Maintenance of Port Policy Planning Office, Facilities Ports and Harbors Bureau Member Mr. Masanori Dredging Method Expert Adviser, Japan KURODA Dredging and Reclamation Engineering Association

(2) Study Team The first term Study Team consists of engineers mainly from ECOH Corporation as listed in Table 1.3.

Members of the second term Study Team are listed in Table 1.4. The second term Study Team can be divided into two sub-teams, that is to say, the engineering team and the economic team. The former consists of engineers mainly from ECOH Corporation, which is in charge of siltation

1-9 problem and dredging plan in the channel. The latter is consists of engineers from OCDI, which is in charge of demand forecast and economic analysis of the port.

Table 1.3 Members of the first term Study Team Name Field in Charge Affiliation Dr. Yoshimi GODA Leader, Siltation Analysis ECOH Co. Dr. Nobuyuki ONO Sub Leader, Siltation Analysis ECOH Co. Mr. Takahisa AOYAMA Dredging Works and Planning ECOH Co. Mr. Yoshimasa ITO Oceanographic Survey ECOH Co. Mr. Anuratoshimitsu Bathymetric Survey Ocean MATSUMOTO Engineering Co.

Table 1.4 Members of the second term Study Team Name Field in Charge Affiliation Dr. Kazumasa Leader, Siltation Analysis ECOH Co. KATO Dr. Nobuyuki Prediction of Siltation ECOH Co. ONO Engineering Mr. Takahisa Channel dredging works and ECOH Co. Team AOYAMA Cost Estimation Mr. Shinji Channel dredging planning DRAM SAKURAI Engineering Mr. Tatsuyuki Maritime Economics OCDI SHISHIDO Dr. Ryuichi Demand Forecast OCDI SHIBASAKI Economic Mr. Takayuki Economic Analysis OCDI Team IIJIMA Mr. Tadahiko Port Planning OCDI KAWADA

(3) Counterparts For two counterparts in the first term Study listed in Table 1.5, the technical training was carried out in Japan.

In the second term Study, CEPA named 11 engineers as the counterparts, being 3 for the engineering team and 8 for the economic team, which are listed in Table 1.6.

Table 1.5 Counterparts in the first term Study Name Affiliation Mr. Mario Orantes Navigation Aids Mr. Abelino Cruz Chief of Maintenance Department

1-10 Table 1.6 Counterparts in the second term Study Name Affiliation Mr. Andrés Abelino Cruz Maintenance Manager, Engineering La Union Port Team Mr. Carlos Alejandro Molina Bathymetry and Dredging Specialist, Paz La Union Port Ms. Egly Tatiana Chacón Bathymetry and Dredging Specialist, La Union Port Economic Mr. Carlos Federico Paredes Concessions Department, Advisor to Team the President Mr. Julio Romero Concessions Department Ms. Patricia Callejas Concessions Department Ms. Marta Eugenia Canales Concessions Department Ms. Andrea Castillo Presidency Mr. Alan Castillo Concessions Department Mr. Juan Carlos Martinez Concessions Department Mr. Damian Reyes Market Analysis Division

(4) JICA Experts dispatched to CEPA JICA experts dispatched to CEPA are listed in Table 1.7.

Table 1.7 JICA Experts dispatched to CEPA Name Period Dr. Hidefumi IKEDA In the first term Study Mr. Takashi KADONO In the second term Study

(5) Relevant person of CEPA Those who were not the counter parts but participants in the meetings and the seminars of technology transfer are also listed in Table 1.8 and in Table 1.9.

Table 1.8 Others relevant person of CEPA in the first term Study Name Affiliation Mr. Luis Enrique Córdova Macías President Mr. Alberto Arene President Mr. Milton Lacayo Director of La Union Port Mr. Salvador Villalobos Brizuela General Manager Mr. Rolando Alberto Díaz Concession Manager Mr. Juan Caros Martíinez Concession Department Mr. Alberto Jiménez Manager of La Union Port Mr.Carlos R. Cornejo Maintenance Engineer Mr. Amilto Orellana Administration Manager Ms. Karen Martínez Mr. Miguel Martíinez Operation Mr. Osman Montoya IT Manager

Table 1.9 Relevant person of CEPA in the second term Study Name Affiliation Mr. Alberto Arene President Mr. Milton Lacayo Director of La Union Port Mr. Andrées Abelino Cruz Maintenance Manager, La Union Port

1-11 Mr. Marcos Vásquez Concession Department Mr. Juan Carlos Martínez Concession Department Mr. Rolando Díaz CEPA Consultant

1.5.2 Chronologies of Study Table 1.10 and Table 1.11 show Chronologies of the first and the second term Studies, respectively.

Table 1.10 Chronology of First Term Study 2010 28 April Minutes of Meetings (by Miyake) 2011 7 January JICA made the contract with the Team for the first term Study 25 January to 21 February First On-site Works Submission of Inception Report 1 31 January to 2 February Bathymetric Survey 7 to 9 February Mud Sampling 15 August to 6 September Second On-site Works Submission of Interim Report 1 19 to 22 August Bathymetric Survey 2012 15 January to 6 February Third On-site Works Submission of Interim Report2 19 January to 21 January Bathymetric Survey

Table 1.11 Chronology of Second Term Study 2012 31 October Minutes of Meetings (by Kawakami) 2013 29 March JICA made the contract with the Team for the second term Study 1 April First Project Support Domestic Committee 10 April to 5 May First On-site Works Submission of Inception Report 14 May Report Meeting in JICA HQ on the First On-site Works 09 August Second PSDC 11 August to 1 September Second On-site Works Submission of Interim Report 27 August Workshop on “Special Technical Assistance for Maintenance Dredging of the Port of La Union in the Republic of El Salvador” 11 September Report Meeting in JICA HQ on the Second On-site Works 31 October Prior Explanation on DF/R to JICA HQ and Office in TV Meeting 19 November Third PSDC 04 to 16 December Third On-site Works Submission of Draft Final Report 10 and 11 December Explanation on DF/R to CEPA 24 December Report Meeting in JICA HQ on the Third On-site Works

1-12 2014 20 January Deadline of comments on DF/R 31 March Submission of Final Report

1.6 Composition and Abstract of Chapters in the Report

In Chapter 2, the technical training of two counterparts in Japan, contents of technology transfer in the second term Study and a workshop held on 27 August, 2013 are explained.

In Chapter 3, the field survey such as bathymetric survey and mud sampling conducted in the first term Study is explained with its results.

In Chapter 4, at first, an empirical prediction model was formulated with an exponential function based on the bathymetric data. Next, a process and a mechanism of siltation in the channel are revealed through the analysis of bathymetric data. According to the result of analysis, the original exponential model has been improved to be a new model, which is named as a modified Exponential Model. Moreover, it is shown that a rapid siltation occurs just after the dredging within several months. By taking into account a possibility that the rapid siltation does not occur during a period of maintenance dredging, a second prediction model has been newly established, which is called a Linear Model. The applicability of these models is discussed.

In Chapter 5, the volumes of re-dredging and a maintenance dredging are estimated. The volume of maintenance dredging is estimated for each target depth by two prediction models formulated in Chapter 4. In a consideration for dredging method, a Self-propelling Trailing Suction Hopper Dredger (TSHD) is selected after the comparison of four types of dredging method. The dredging cost of re-dredging is estimated for the dredging of contract base, and those of maintenance dredging are estimated for both the contract base and the own dredger by CEPA.

In Chapter 6, contents and a method of monitoring on siltation in the channel and the basin are examined, which will be carried out just after the re-dredging and during the maintenance dredging. The purpose of monitoring are to verify an appropriateness of siltation volumes predicted by two models and to confirm the phenomenon of rapid siltation just after the re-dredging.

In Chapter 7, a review of the model developed by CEPA are shown including the estimation of the growth rate of container cargo shipping demand to/from CA4 countries (El Salvador, Guatemala, Honduras and Nicaragua) and the market allocation model.

The main purpose of Chapter 8 is to describe a vessel calling model for financial and economic analysis of La Union Port. After the outline of the model is described, every component of the model including behavior of shipping companies, container cargo assignment model, and input data are stated. The calculation results of the container cargo assignment model are examined from the viewpoint of the model reproducibility by several benchmarks. The sensitivity of the model to the estimated unknown parameters is also examined.

Chapter 9 mainly focuses on the output of the vessel calling model. However, the first part of the chapter describes the present status of navigation channel and rule in La Union Port, followed by a proposal of new navigation rule. After that, according to a lot of scenarios on the future liner shipping network which are prepared for each channel depth in La Union Port, the vessel calling model is calculated to estimate the future container cargo throughput and other outputs. From the

1-13 model output, net income (except for the dredging cost) from container business of La Union Port, net income from container business of Salvadoran port sector (sum of Acajutla Port and La Union Port), and net benefit for Salvadoran economy of the dredging project in La Union Port are estimated and compared with the dredging cost by channel depth. The model calculation as well as financial and economic analysis as mentioned above is also conducted in the cases that each related policy such as tariff increase of La Union Port, regional development in the eastern El Salvador, and decrease of the barrier at national border is implemented.

Chapter 10 shows a methodology of the time series analysis considering each year’s income, benefit and dredging cost. Also, example results of calculation are shown, in order to contribute to the discussion on the timing of investment for dredging.

In Chapter 11, major findings of the study and recommendation are summarized.

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Chapter 2 Technology Transfer

2.1 Execution for Technical Training of CEPA Personals in Japan

The technical training of CEPA personals was carried out in Japan from 21 November to 9 December, 2011. Two trainees participated in the training program and studied on operation and management of dredging works, methodology of bathymetric survey and astronomical tide prediction, and so on (see Photo 2.1 and Photo 2.2). The itinerary of the training program is shown in Table 2.1.

Participants Mr. Cruz Fuentes Andrés Abelino Mr. Orantes Montiagudo Mario René

Photo 2.1 Exercise on MLIT’s survey boat, COSMO

Photo 2.2 Exercise on MLIT’s dredger, Kaisho Maru

2-1 Table 2.1 Itinerary of technical training in Japan CEPA Trainee JICA Day Date Mr. Cruz Fuentes Andres Abelino Mr. Orantes Montiagudo Mario Rene Interpriter Stay in a day of a week day of

1 11/21 Mon San Salvador -> Miami Miami

2 11/22 Tue Miami→Chicago frying overnight

3 11/23 Wed Chicago→Narita Tokyo

4 11/24 Thu Courtesy call on JICA, Orientation with Trainee Tokyo

Exercise on Shin-Tokyo Maru 5 11/25 Fri with Trainee Tokyo Seminor on Dredging at ECOH

6 11/26 Sat documentation with Trainee Tokyo

7 11/27 Sun documentation with Trainee Tokyo

8 11/28 Mon Excursion to HORS, Hasaki, Ibaraki with Trainee Tokyo Tokyo → Fukuoka 9 11/29 Tue with Trainee Kitakyushu Inspection of Hakata Port Hakata → Kitakyushu 10 11/30 Wed Exercise on MLITT's dredger, Kaisho Maru with Trainee Kitakyushu Exercise in Sounding Survey on Survey Boat Inspection of Construction site at Shinwakato Tunnel and Kanda Port 11 12/1 Thu with Trainee Tokyo Kitakyushu → Tokyo

12 12/2 Fri Seminar in Astronomical tide prediction at PARI with Trainee Tokyo

13 12/3 Sat documentation with Trainee Tokyo

14 12/4 Sun documentation with Trainee Tokyo

15 12/5 Mon Seminar in Astronomical tide prediction program at ECOH with Trainee Tokyo

16 12/6 Tue Exercise on Astronomical tide prediction program at ECOH with Trainee Tokyo

17 12/7 Wed 15:00 Assesment of the training with Trainee Tokyo

18 12/8 Thu Narita→Los Angeles Los Angeles

19 12/9 Fri Los Angeles→San Salvador

2.2 Technology Transfer to Counterparts

2.2.1 Technology Transfer in the Field of Engineering (1) Explanation of the Inception Report in the Second Term Study on 16 April, 2013 The Inception Report which contains the purposes and methods of the second term Study was explained to the participants in La Union Port. They understood the contents well. The participants are listed in Table 2.2.

2-2 Table 2.2 Participants (1) Name Affiliation Mr. Andrés Abelino Cruz Maintenance Manager, La Union Port Mr. Carlos Cornejo Maintenance Engineer, La Union Port Mr. Marcos Vásquez Concessions Department Mr. Osman Montoya Navigation Aids, La Union Port Mr. Roque Machado IT Technician, La Union Port

(2) Inspection of rake-dredging and confirmation of CEPA’s tide correction, on 17 April, 2013 The Engineering Team got the information about the rake-dredging through the interview and the discussion with the participants. The counterpart explained about their method of tide correction. The team pointed out that their method was not appropriate. The participants are listed in Table 2.3.

Table 2.3 Participants (2) Name Affiliation Mr. Andrés Abelino Cruz Maintenance Manager, La Union Port Mr. Carlos Cornejo Maintenance Engineer, La Union Port Mr. Marcos Vásquez Concessions department Mr. Osman Montoya Navigation Aids, La Union Port Mr. Roque Machado IT Technician, La Union Port

(3) Joint bathymetric survey practice on 19 April, 2013 In the field, the participants explained the Team on the items related to the bathymetric survey such as an installation of echo sounder, a calibration of measured water depth, operation of surveying vessel, a recording of sounding data and so on (see Photo 2.3). It was confirmed that their method of bathymetric surveying was correct and appropriate, and their skill has been good. The participants are listed in Table 2.4.

Photo 2.3 Setting of recording device for bathymetric survey

2-3 Table 2.4 Participants (3) Name Affiliation Mr. Andrés Abelino Cruz Maintenance Manager, La Union Port Mr. Carlos Cornejo Maintenance Engineer, La Union Port Mr. Marcos Vásquez Concessions department Mr. Osman Montoya Navigation Aids, La Union Port Mr. Roque Machado IT Technician, La Union Port

(4) Explanation on the Soft-ware program for the prediction of tide level in La Union Port, on 22 April, 2013 A basic concept of tide correction was transferred to the participants. And also, a soft-ware program for the prediction of tide level in La Union Port, which is absolutely necessary for tide correction, has been provided to them with a detailed explanation. The participants are listed in Table 2.5.

Table 2.5 Participants (4) Name Affiliation Mr. Andrés Abelino Cruz Maintenance Manager, La Union Port Mr. Carlos Cornejo Maintenance Engineer, La Union Port Mr. Marcos Vásquez CEPA Concessions Department Mr. Osman Montoya Navigation Aids, La Union Port Mr. Roque Machado IT Technician, La Union Port

(5) Joint bathymetric survey and a practice of tide correction on 21 August, 2013 The Joint Bathymetric survey of the engineering Team and counterparts was carried out. The bathymetric data obtained was used for practice of tide correction, in which the provided soft-ware program was effectively utilized. The participants are listed in Table 2.6.

Table 2.6 Participants (5) Name Affiliation Mr. Andrés Abelino Cruz Maintenance Manager, La Union Port Mr. Carlos Cornejo Maintenance Engineer, La Union Port Mr. Osman Montoya Navigation Aids, La Union Port Mr. Carlos Alejandro Molina Bathymetry and Dredging Specialist, Paz Port of La Union Ms. Egly Tatiana Chacón Bathymetry and Dredging Specialist, La Union Port Mr. Roque Machado IT Technician, La Union Port

(6) Explanation of siltation process in the channel on 22 August, 2013 A result of analysis on the siltation process in the access channel of La Union Port was explained to the counterparts. The Team and the counterparts discussed on the phenomena of siltation, which gave a basic knowledge to the counterparts for understanding the prediction models of siltation. The participants are listed in Table 2.7.

2-4 Table 2.7 Participants (6) Name Affiliation Mr. Carlos Cornejo Maintenance Engineer, La Union Port Mr. Carlos Alejandro Molina Bathymetry and Dredging Specialist, Paz La Union Port Ms. Egly Tatiana Chacón Bathymetry and Dredging Specialist, La Union Port

(7) Joint bathymetric survey on 23 August, 2013 In the Inner channel, a longitudinal bathymetric survey was conducted under the joint of the Team and counterpart. The participants are listed in Table 2.8.

Table 2.8 Participants (7) Name Affiliation Mr. Carlos Alejandro Molina Bathymetry and Dredging Specialist, Paz La Union Port Ms. Egly Tatiana Chacón Bathymetry and Dredging Specialist, La Union Port Mr. Roque Machado IT Technician, La Union Port

(8) Modification of prediction model for siltation in La Union Port, on 6 December, 2013 The engineering Team explained to the counterparts about the modified Exponential Model and newly formulated Linear Model. The counterparts could understand the applicability of these models. The participants are listed in Table 2.9.

Table 2.9 Participants (8) Name Affiliation Mr. Milton Lacayo Port Manager, La Union Port Mr. Andrés Abelino Cruz Maintenance Manager, La Union Port Mr. Carlos Alejandro Molina Bathymetry and Dredging Specialist, Paz La Union Port Ms. Egly Tatiana Chacón Bathymetry and Dredging Specialist, La Union Port Mr. Mmarcos Vásquez Concession Department

(9) Explanation of the Monitoring plan on siltation after re-dredging, on 6 December, 2013 As a result of technology transfer, the counterparts deepened their understanding of the importance of monitoring for improving the prediction model. The participants are listed in Table 2.10.

2-5 Table 2.10 Participants (9) Name Affiliation Mr. Milton Lacayo Port Manager, La Union Port Mr. Andrés Abelino Cruz Maintenance Manager, La Union Port Mr. Carlos Alejandro Molina Bathymetry and Dredging Specialist, Paz La Union Port Ms. Egly Tatiana Chacón Bathymetry and Dredging Specialist, La Union Port Mr. Marcos Vásquez Concession Department

(10) On the influence of Semicircle Island to the environment around it, on 9 December, 2013 CEPA has a plan to construct the Semicircular Island in order to reduce the volume of siltation. The effects of semicircular Island they expect are an alternate dumping site for dredged mud and reduction of siltation volume. The team explained a result of consideration concerning to this issue. The participants are listed in Table 2.11.

Table 2.11 Participants (10) Name Affiliation Mr. Milton Lacayo Port Manager, La Union Port Mr. Andrés Abelino Cruz Maintenance Manager, La Union Port Mr. Carlos Alejandro Molina Bathymetry and Dredging Specialist, Paz La Union Port Ms. Egly Tatiana Chacón Bathymetry and Dredging Specialist, La Union Port Mr. Marcos Vásquez Concession Department

(11) Calculation method of siltation volume and Nautical depth of navigation, on 10 December, 2013 The counterparts understood the calculation method of siltation volume by applying two prediction models. The participants are listed in Table 2.12.

Table 2.12 Participants (11) Name Affiliation Mr. Milton Lacayo Port Manager, La Union Port Mr. Andrés Abelino Cruz Maintenance Manager, La Union Port Mr. Carlos Alejandro Molina Bathymetry and Dredging Specialist, Paz La Union Port Ms. Egly Tatiana Chacón Bathymetry and Dredging Specialist, La Union Port Mr. Marcos Vásquez Concession Department

(12) Introduction of various dredgers, on 12 December, 2013 Various types of dredger were introduced (see Photo 2.4). The participants are listed in Table 2.13.

2-6

Photo 2.4 Atmosphere of presentation

Table 2.13 Participants (12) Name Affiliation Mr. Carlos Federico Paredes Concessions Manager Mr. Milton Lacayo Port Manager, La Union Port Mr. Amilto Orellana Administrative Department Manager, La Union Port Mr. Andrés Abelino Cruz Maintenance Manager, La Union Port Mr. Rafael Antonio Hernández Engineering Department Ms. Egly Tatiana Chacón Bathymetry and Dredging Specialist, La Union Port Mr. Carlos Alejandro Molina Bathymetry and Dredging Specialist, Paz La Union Port Mr. Juan Carlos Martínez Concession Department Mr. Julio Alberto Romero Concessions Management Technician Mejía Ms. Patricia Callejas Concessions Management Technician Ms. Eugenia Luna Concessions Management Technician Ms. Andrea Castillo President's Assistant Mr. Damián Reyes Economical Financial Analyst

2.2.2 Technology Transfer in the Field of Economic (1) Explanation of the Inception Report in the Second Term Study on 16 April, 2013 At the beginning of the second term Study, the JICA economic team explained the Inception Report. CEPA economic team was able to deepen their understanding of the central aim of this survey. The participants from the counterparts are listed in Table 2.14.

2-7 Table 2.14 Participants (1) Name Affiliation Mr. Carlos Federico Paredes Concessions Department, Advisor to the President Mr. Julio Romero Concessions Department Ms. Patricia Callejas Concessions Department Ms. Marta Eugenia Canales Concessions Department Ms. Andrea Castillo Presidency Mr. Alan Castillo Concessions Department Mr. Juan Carlos Martinez Concessions Department

(2) Method of calculating CEPA model, on 26 April, 2013 The JICA economic team confirmed the methodology used in the future demand forecast and market allocation conducted by CEPA. The participants are listed in Table 2.15.

Table 2.15 Participants (2) Name Affiliation Mr. Carlos Federico Paredes Concessions Department, Advisor to the President Mr. Julio Romero Concessions Department Ms. Patricia Callejas Concessions Department Ms. Marta Eugenia Canales Concessions Department Mr. Juan Carlos Martinez Concessions Department Mr. Alan Castillo Concessions Department

Photo 2.5 Presentation by a member of the economic team

(3) Vessel Calling Model [1]: Outline of the model and explanation of the maritime shipping submodel on 11 July, 2013 (by Skype meeting) The JICA economic team presented an outline of the Vessel Calling Model. In particular, the team focused on the abstract and estimated results of the maritime shipping submodel. CEPA economic team confirmed the result and was able to deepen their understanding of the model. The participants are listed in Table 2.16.

Table 2.16 Participants (3) Name Affiliation Ms. Patricia Callejas Concessions Department Ms. Marta Eugenia Canales Concessions Department Mr. Juan Carlos Martinez Concessions Department Mr. Alan Castillo Concessions Department

2-8

Photo 2.6 Skype meeting

(4) Vessel Calling Model [2]: Estimated results of the container cargo assignment model on 18 July, 2013 (by Skype meeting) The JICA economic team gave an outline of the container cargo assignment model including not only the maritime shipping submodel but also the land shipping network. The estimated results were discussed among JICA and CEPA economic team. The participants are listed in Table 2.17.

Table 2.17 Participants (4) Name Affiliation Mr. Juan Carlos Martinez Concessions Department Ms. Patricia Callejas Concessions Department Ms. Marta Eugenia Canales Concessions Department Mr. Alan Castillo Concessions Department

(5) Vessel Calling Model [3]: Confirmation of the revised results on 9 August, 2013 (by Skype meeting). The revised calculation results based on the discussion in previous meetings and new information were confirmed. The participants are listed in Table 2.18.

Table 2.18 Participants (5) Name Affiliation Ms. Patricia Callejas Concessions Department Ms. Marta Eugenia Canales Concessions Department Mr. Damián Reyes Market Analysis Division

(6) Vessel Calling Model [4]: Review of the model and discussion on the future scenarios for model simulation on 12 August, 2013 The JICA economic team reviewed the whole structure of the model which had been explained in the Skype meetings with high-level staff of CEPA. The discussion mainly focused on the possible future scenarios for the model simulation. The participants are listed in Table 2.19.

2-9 Table 2.19 Participants (6) Name Affiliation Mr. Carlos Federico Paredes Concessions Department, Advisor to the President Mr. Milton Lacayo Port Manager,La Union Port Ms. Patricia Callejas Concessions Department Ms. Marta Eugenia Canales Concessions Department Ms. Andrea Castillo Presidency Mr. Damian Reyes Market Analysis Division

(7) Basics of traffic assignment model on 15 August, 2013 The JICA economic team explained the traffic assignment model which is one of the fundamental components of the Vessel Calling Model. CEPA economic team practiced using the model, and was able to deepen their understanding of the model. The participants are listed in Table 2.20.

Table 2.20 Participants (7) Name Affiliation Mr. Julio Romero Concessions Department Ms. Patricia Callejas Concessions Department Ms. Marta Eugenia Canales Concessions Department Mr. Damián Reyes Market Analysis Division

(8) Container Service along Pacific Coast on CA5 on 16 August, 2013 The JICA economic team explained the present state of container shipping along the Pacific Coast in CA5. CEPA economic team was able to understand that the routes and frequency of container service could change depending on the strategy of shipping companies in Central America. The participants are listed in Table 2.21.

Table 2.21 Participants (8) Name Affiliation Mr. Julio Romero Concessions Department Ms. Patricia Callejas Concessions Department Ms. Marta Eugenia Canales Concessions Department Mr. Damian Reyes Markey Analysis Division

2-10 Photo 2.7 Participants of CEPA economic team

(9) Tariff of La Union port, on 25 August, 2013 The JICA economic team explained the tariff of La Union port and neighboring countries. CEPA economic team was able to deepen their understanding of the tariff. The participants are listed in Table 2.22.

Table 2.22 Participants (9) Name Affiliation Mr. Julio Romero Concessions Department Ms. Patricia Callejas Concessions Department Ms. Marta Eugenia Canales Concessions Department Mr. Damián Reyes Market Analysis Division

(10) Vessel Calling Model [5]: Improvement of the model (consideration of ocean freight charge) on 27 August, 2013 Before the workshop which was held on the afternoon of that day, improvements to the model were explained to CEPA economic team. The participants are listed in Table 2.23.

Table 2.23 Participants (10) Name Affiliation Mr. Julio Romero Concessions Department Ms. Patricia Callejas Concessions Department Ms. Marta Eugenia Canales Concessions Department Mr. Damián Reyes Market Analysis Division

(11) Estimated an expecting ship waiting time in La Union Port, on 28 August, 2013 The JICA economic team explained the estimation methodology of the expected ship waiting time by tidal change in La Union port. CEPA economic team was able to understand that the navigable time of the channel could be expanded by using tidal advantage. The participants are listed in Table 2.24.

Table 2.24 Participants (10) Name Affiliation Mr. Julio Romero Concessions Department Ms. Marta Eugenia Canales Concessions Department Mr. Damián Reyes Market Analysis Division

(12) Vessel Calling Model [6]: Validation of the model, simulation results, and execution of the program on 29 August, 2013 Of the contents which were presented at the workshop held on August 27, detailed results including the validation on the reproducibility of the model and simulation for the vessel-calling to the La Union Port were explained to the CEPA economic team. In addition, the calculation programs were distributed to the participants and executed. The participants learned how to execute the program on the computer. The participants are listed in Table 2.25.

2-11

Table 2.25 Participants (12) Name Affiliation Mr. Julio Romero Concessions Department Ms. Patricia Callejas Concessions Department Ms. Marta Eugenia Canales Concessions Department Mr. Damián Reyes Market Analysis Division

Photo 2.8 Presentation by a member of the economic team

(13) Channel Navigation by using Tidal Advantage, on 6 December, 2013 The JICA economic team explained the navigable time of the channel by using tidal advantage. CEPA economic team was able to deepen their understanding of the method used to calculate navigable time. The participants are listed in Table 2.26.

Table 2.26 Participants (13) Name Affiliation Mr. Julio Romero Concessions Department Ms. Patricia Callejas Concessions Department Ms. Marta Eugenia Canales Concessions Department Mr. Damián Reyes Market Analysis Division

(14) Regional/Industrial Development and Port Planning and Promotion, on 9 December, 2013 The JICA economic team explained the connection between industrial development of the region surrounding the port and port planning and promotion. CEPA economic team was able to deepen the understanding of the significance of port policy. The participants are listed in Table 2.27.

Table 2.27 Participants (14) Name Affiliation Mr. Julio Romero Concessions Department Ms. Patricia Callejas Concessions Department Ms. Marta Eugenia Canales Concessions Department Ms. Andrea Castillo Presidency Mr. Damián Reyes Market Analysis Division

2-12

(15) Summary of Draft Final Report [1]: Explanation of the final version of the Vessel Calling Model on 11 December, 2013 Of the contents included in the Draft Final Report, the final version of the Vessel Calling Model and its estimation results were explained by the JICA economic team. In addition, how to derive a logit model which is one of fundamental models of the stochastic assignment model was explained. The participants confirmed the final version of the model and its output as well as learned how to derive a logit model. The participants are listed in Table 2.28.

Table 2.28 Participants (15) Name Affiliation Mr. Julio Romero Concessions Department Ms. Patricia Callejas Concessions Department Ms. Marta Eugenia Canales Concessions Department Ms. Andrea Castillo Presidency Mr. Damián Reyes Market Analysis Division

(16) Summary of Draft Final Report [2]: Method of calculating Financial & Economic analysis and on 12 December, 2013 The JICA economic team explained the method of financial and economic analysis, which is included in the Draft Final Report. CEPA economic team was able to deepen the understanding about the analysis and how to use an excel file for the time-series analysis. The participants are listed in in Table 2.29.

Table 2.29 Participants (16) Name Affiliation Mr. Julio Romero Concessions Department Ms. Patricia Callejas Concessions Department Ms. Marta Eugenia Canales Concessions Department Ms. Andrea Castillo Presidency Mr. Damian Reyes Market Analysis Division

2.3 Workshop

The workshop on “Special Technical Assistance for Maintenance Dredging of the Port of La Union in the Republic of El Salvador” was held in the Seminar Room on the top floor of CEPA Headquarter on 27 August, 2013. The workshop started while participants were taking the lunch which was invited by CEPA. The program of workshop, titles of presentations and presenters are listed in Table 2.30. Among them, Dr. K. Murakami and Dr. Y. Nakagawa are the members of Project Support Domestic Committee established in JICA Headquarters, Japan. Photo 2.9 shows an atmosphere of workshop, in which persons in CEPA side were occupying on the left side as one faces the screen of projector. The participants and presenters are listed in Table 2.31.

2-13 Table 2.30 Program of workshop, titles of presentations and presenters START 12:00 0. Lunch Invited by CEPA in order to enhance awareness of participants and presenters 12:00-12:30 1. Welcome Speech By Mr. A. ARENE, President of CEPA 12:30-12-35 2. Opening Address By Mr. T. KAWAKAMI, JICA HQ 12:35-12:40 3. Interim Report on Engineering Issues By Dr. N.ONO, ECOH 12:40-13:20 4. Interim Report on Economic Issues By Dr. R.SHIBASAKI, OCDI 13:20-14:00 5. Port Promotion examples in Japan By Mr. M.KIHARA, MLIT 14:00-14:30 14:30-14:45 6. Field Study on maintenance dredging in the access channel of Banjarmashin Port, Indonesia By Dr. K.MURAKAMI, TCU 14:45-15:15 7. Harbor siltation and countermeasures in Japan By Dr. Y.NAKAGAWA, PARI 15:15-15:45 8. Case study of analysis of bathymetric data By Dr. K.KATO, ECOH 15:45-16:05 9. Regional development and port By Mr. T.SHISHIDO, OCDI 16:05-16:25 10. Closing Remarks by Mr. T.KADONO, JICA Expert 16:25-16:30 CLOSE 16:30

Photo 2.9 Workshop held in CEPA Headquarters

Table 2.31 List of participants and presenters Name Affiliation El Salvador Side Mr. Alberto Arene President Mr. Carlos Federico Paredes President Advisor Castillo Mr. Milton Lacayo Port Manager, La Union Port Mr. Padre Amilto Orellqana Financial Manager, La Union Port Mr. Andrés Abelino Cruz Maintenance Manager, La Union Port Ms. Marta Eugenia Canales Administrator Data Base, La Union Port Ms. Andrea Castillo Assistant President Ms. Patricia Callejas Financial Assistant Mr. Carlos Alejandro Molina Bathymetry and Dredging Specialist, Paz La Union Port

2-14 Ms. Egly Tatiana Chacón Bathymetry and Dredging Specialist, La Union Port Mr. Rafael Antonio Engineering Department Hernández Mr. Damián Reyes Marketing Analyst Mr. Jaime Flores Financial Technician Mr. Marcos Vásquez Concession Department Mr. Juan Carlos Martínez Concession Department Mr. Julio Alberto Romero Concession Department Mejía Mr. Takashi Kadono JICA Expert Japanese Side Mr. Taiji Kawakami Executive Technical Advisor, Economic Infrastructure Department, JICA Headquarter Dr. Kazuo Murakami Emeritus professor, Tokyo City University Dr. Yasuyuki Nakagawa Team Leader of Coastal and Estuary Sediment Dynamics Research Group, Port and Airport Research Institute Mr. Masatomo Hihara Director for International Policy, Ports and Harbors Bureau JICA Study Team Dr. Kazumasa Kato Leader, Siltation Analysis, ECOH Dr. Nobuyuki Ono Siltation Analysis and Prediction, ECOH Mr. Takahisa Aoyama Channel Dredging works and Planning, ECOH Mr. Tatsuyuki Shishido Maritime Economics, OCDI Dr. Ryuichi Shibasaki Demand Forecast, OCDI Mr. Takayuki Iijima Economic Analysis, OCDI Mr. Tadahiko Kawada Port Planning, OCDI JICA El Salvador Office Mr. Shinji Sato Adjunct President Representative Mr. Yuichiro Inoue Director of Reimbursable Financial Cooperation Ms. Miwako Kamimura Project Formulation Adviser Ms. Gabriela Alfaro Program Officer

2-15

Chapter 3 Field Survey and Results

3.1 Bathymetric Survey

3.1.1 Survey lines of bathymetric survey The bathymetric survey was conducted along one longitudinal line along the access channel, 22 transversal lines across the access channel, 7 lines in the harbor basin perpendicular to the wharf, and 3 lines in the harbor basin parallel to the wharf. The locations of the transversal lines across the access channel are shown in Figure 3.1 with their distances from the base point listed in Table 3.1, which provides the conversion relationship between the line number and KP coordinate. The line numbers L1 to L22 correspond to the lines shown in Figure 3.1. The locations of survey lines within the basin are shown in Figure 3.2. The line numbers x+0 to x+1200 are set nearly perpendicular to the wharf, while the line numbers y-200 and y-400 are set parallel to the channel centerline. The column of extension indicates approximate lengths of survey lines.

Table 3.1 Location of bathymetric survey lines KP Extension KP Extension KP Extension No No No (km) (m) (km) (m) (km) (m) L1 21.91 600 L12 10.90 400 x+1200 1.20 700 L2 20.90 600 L13 9.91 400 x+1000 1.00 700 L3 19.90 600 L14 8.90 400 L22 0.92 700 L4 18.91 600 L15 7.91 400 x+800 0.80 700 L5 17.90 600 L16 6.92 400 x+600 0.60 700 L6 16.90 600 L17 5.93 400 x+400 0.40 700 L7 15.91 600 L18 4.93 400 x+200 0.20 700 L8 14.91 600 L19 3.92 400 x+0 0.00 800 L9 13.91 600 L20 2.92 400 y -0 - 800 L10 12.91 600 L21 1.92 400 y -200 - 1300 L11 11.89 400 y -400 - 1300

3-1 KP0

Figure 3.1 Bathymetric survey lines of access channel

Survey lines in harbor basin Longitudinal L22 KP0

Figure 3.2 Bathymetric survey lines in harbor basin

3-2 3.1.2 Longitudinal depth profile of access channel Figure 3.3 shows the longitudinal depth variation along the centerline of the access channel as surveyed during the period from 31 January to 2 February 2011, that from 19 to 22 August 2011, and that from 19 to 21 January 2012. The upper diagram shows the whole longitudinal profile of the access channel, while the lower diagram shows the portion of profile shallower than 15 m. The shallowest location of the Outer channel is around KP16.000 with the depth of 10.2 m, while the Inner channel is shallowest around KP3.500 with the depth of 7.4 m.

Distance(KP) ‐1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 5.0 10.0 15.0 (m) 20.0 2012_01

Depth 25.0 2011_08 30.0 2011_02 35.0 Distance(KP) ‐1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 6.0 7.0 2012_01 8.0 2011_08 9.0 2011_02 (m)

10.0 11.0

Depth 12.0 13.0 14.0 15.0

Figure 3.3 Longitudinal depth variation along the centerline of access channel

3.1.3 Transversal depth profiles of harbor basin and access channel Figure 3.4 to Figure 3.9 exhibit the profile changes of the cross-sections of the access channel from L01 (KP21.91) to L22 (KP0.92) at the interval of 1 km; five survey results in December 2008, June 2009, February 2011, August 2011, and January 2012 are shown with the plan shape of the channel. In each figure, the origin of the distance is set on the channel centerline and positive eastward.

Figure 3.10 and Figure 3.11 show the cross-sections of the harbor basin at the interval of 0.2 km; four survey results in December 2008, February 2011, August 2011 and January 2012 are shown. The water depths at completion of capital dredging in December 2008 are also shown in the figures.

Figure 3.12 are the depth profiles of the harbor basin along the lines of y = 0, -200, and -400 m, which are parallel to the centerline of the access channel. The distance is measured southward from the northern end of the basin as indicated in Figure 3.2.

3-3 L01 = KP21.91 (200kHz) Distance(m) ‐200 ‐150 ‐100 ‐50 0 50 100 150 200 8.0 9.0 Jan/20122012_01 10.0 A2011_08ug/2011

(m) Feb/20112011_02 11.0 12.0 Jun/20092009_06 Depth 13.0 Dec/20082008_12 14.0 PLAN 15.0 L02 = KP20.90 (200kHz) Distance(m) ‐200 ‐150 ‐100 ‐50 0 50 100 150 200 8.0 Jan/20122012_01 9.0 A2011_0ug/20118 10.0 Feb/20112011_02 (m)

11.0 Jun/20092009_06 12.0 Dec/20082008_12 Depth 13.0 PLAN 14.0 15.0 L03 = KP19.90 (200kHz) Distance(m) ‐200 ‐150 ‐100 ‐50 0 50 100 150 200 8.0 9.0 Jan/20122012_01 Aug/2011 10.0 2011_08 Feb/20112011_02 (m) 11.0 Jun/20092009_06 12.0 Dec/20082008_12

Depth 13.0 PLAN 14.0 15.0

Figure 3.4 Transversal depth profiles of Outer Channel with the planned channel profile (L1, L2, and L3)

3-4 L04 = KP18.91 (200kHz) Distance(m) ‐200 ‐150 ‐100 ‐50 0 50 100 150 200 8.0 9.0 10.0 (m)

11.0 12.0 Jan/20122012_01 A2011_08ug/2011 Depth 13.0 Feb/20112011_02 14.0 Jun/20092009_06 15.0 Dec/20082008_12 PLAN

L05 = KP17.90 (200kHz) Distance(m) ‐200 ‐150 ‐100 ‐50 0 50 100 150 200 8.0 9.0 10.0 (m)

11.0 Jan/20122012_01 12.0 A2011_08ug/2011

Depth 13.0 Feb/20112011_02 Jun/20092009_06 14.0 Dec/20082008_12 15.0 PLAN

L06 = KP16.90 (200kHz) Distance(m) ‐200 ‐150 ‐100 ‐50 0 50 100 150 200 8.0 9.0 10.0 (m) 11.0 Jan/20122012_01 12.0 A2011_08ug/2011

Depth Feb/2011 13.0 2011_02 Jun/20092009_06 14.0 Dec/20082008_12 15.0 PLAN

Figure 3.5 Transversal depth profiles of Outer Channel with the planned channel profile (L4, L5, and L6)

3-5 L07= KP15.91 (200kHz) Distance(m) ‐200 ‐150 ‐100 ‐50 0 50 100 150 200 8.0 9.0 10.0 (m)

11.0 2012_01Jan/2012 12.0 2011_08Aug/2011

Depth 13.0 2011_02Feb/2011 2009_06Jun/2009 14.0 2008_12Dec/2008 15.0 PLAN

L08= KP14.91 (200kHz) Distance(m) ‐200 ‐150 ‐100 ‐50 0 50 100 150 200 8.0 9.0 10.0 (m)

11.0 2012_01Jan/2012 12.0 2011_08Aug/2011 Depth 13.0 2011_02Feb/2011 14.0 2009_06Jun/2009 2008_12Dec/2008 15.0 PLAN

L09= KP13.91 (200kHz) Distance(m) ‐200 ‐150 ‐100 ‐50 0 50 100 150 200 8.0 Jan/20122012_01 9.0 A2011_08ug/2011 10.0 Feb/20112011_02 (m)

11.0 Jun/20092009_06 12.0

Depth Dec/2008 13.0 2008_12 14.0 PLAN 15.0

Figure 3.6 Transversal Depth profiles of Outer Channel with the planned channel profile (L7, L8, and L9)

3-6

L10= KP12.91 (200kHz) Distance(m) ‐200 ‐150 ‐100 ‐50 0 50 100 150 200 8.0 Jan/20122012_01 9.0 A2011_08ug/2011 10.0 Feb/20112011_02 (m)

11.0 Jun/20092009_06 12.0 Dec/2008 Depth 13.0 2008_12 14.0 PLAN 15.0

L11= KP11.89 (200kHz) Distance(m) ‐200 ‐150 ‐100 ‐50 0 50 100 150 200 8.0 Jan/20122012_01 9.0 A2011_08ug/2011 10.0 Feb/20112011_02 (m)

11.0 Jun/20092009_06 12.0 Dec/2008 Depth 13.0 2008_12 14.0 PLAN 15.0 L12= KP10.90 (200kHz) Distance(m) ‐200 ‐150 ‐100 ‐50 0 50 100 150 200 8.0 9.0 Jan/20122012_01 A2011_08ug/2011 10.0 Feb/20112011_02 (m) 11.0 Jun/20092009_06 12.0 Dec/20082008_12

Depth 13.0 PLAN 14.0 15.0

Figure 3.7 Transversal depth profiles of Outer Channel with the planned channel profile (L10, L11, and L12)

3-7 L17= KP5.93 (200kHz) Distance(m) ‐200 ‐150 ‐100 ‐50 0 50 100 150 200 11.0 12.0 Jan/20122012_01 13.0 A2011_08ug/2011 14.0 Feb/20112011_02

(m) 15.0 Jun/20092009_06

16.0 Dec/20082008_12 17.0 PLAN Depth 18.0 19.0 20.0 21.0 L18= KP4.93 (200kHz) Distance(m) ‐200 ‐150 ‐100 ‐50 0 50 100 150 200 6.0 7.0 8.0 9.0 Jan/20122012_01

(m) 10.0 11.0 A2011_08ug/2011 12.0 Feb/20112011_02

Depth 13.0 Jun/20092008_12 14.0 Dec/20082008_12 15.0 PLAN 16.0

L19= KP3.92 (200kHz) Distance(m) ‐200 ‐150 ‐100 ‐50 0 50 100 150 200 6.0 7.0 8.0 9.0 Jan/20122012_01

(m) 10.0 11.0 A2011_08ug/2011 12.0 Feb/20112011_02

Depth 13.0 Jun/20092009_06 14.0 Dec/20082008_12 15.0 PLAN 16.0

Figure 3.8 Transversal depth profiles of Inner Channel with the planned channel profile (L17, L18, and L19)

3-8 L20= KP2.92 (200kHz) Distance(m) ‐200 ‐150 ‐100 ‐50 0 50 100 150 200 6.0 7.0 8.0 9.0 Jan/2012 (m) 10.0 2012_01 11.0 A2011_08ug/2011 12.0 Feb/20112011_02

Depth 13.0 Jun/20092009_06 14.0 Dec/20082008_12 15.0 PLAN 16.0 L21= KP1.92 (200kHz) Distance(m) ‐200 ‐150 ‐100 ‐50 0 50 100 150 200 6.0 7.0 8.0 9.0

(m) 10.0 2012_01Jan/2012 11.0 2011_08Aug/2011 12.0 2011_02Feb/2011 Depth 13.0 2009_06Jun/2009 14.0 2008_12Dec/2008 15.0 PLAN 16.0 L22= KP0.92 (200kHz) Distance(m) ‐500 ‐400 ‐300 ‐200 ‐100 0 100 200 6.0 7.0 8.0 9.0

(m) 10.0 11.0 Jan/20122012_01 12.0 A2011_08ug/2011

Depth 13.0 Feb/20112011_02 14.0 Jun/20092009_06 15.0 Dec/20082008_12 16.0 PLAN

Figure 3.9 Transversal depth profiles of Inner Channel with the planned channel profile (L20, L21, and L22)

3-9 X=1200KP 1.200 (200kHz) Distance(m) ‐700 ‐600 ‐500 ‐400 ‐300 ‐200 ‐100 0 100 200 300 6.0 7.0 8.0 9.0

(m) 10.0 11.0 12.0 Jan/20122012_01 Depth 13.0 A2011_08ug/2011 14.0 Feb/20112011_02 15.0 Dec/20082008_12 16.0

X=1000KP 1.000 (200kHz) Distance(m) ‐700 ‐600 ‐500 ‐400 ‐300 ‐200 ‐100 0 100 200 300 6.0 7.0 8.0 9.0

(m) 10.0 11.0 Jan/20122012_01 12.0 Aug/2011 Depth 13.0 2011_08 14.0 Feb/20112011_02 15.0 Dec/20082008_12 16.0

X=800KP 0.800 (200kHz) Distance(m) ‐700 ‐600 ‐500 ‐400 ‐300 ‐200 ‐100 0 100 200 300 6.0 7.0 8.0 9.0

(m) 10.0

11.0 Jan/20122012_01 12.0 Aug/2011 Depth 13.0 2011_08 14.0 Feb/20112011_02 15.0 Dec/20082008_12 16.0

Figure 3.10 Depth profiles of Turning Basin on the lines perpendicular to the wharf.

3-10 KPX=600 0.600 (200kHz) Distance(m) ‐700 ‐600 ‐500 ‐400 ‐300 ‐200 ‐100 0 100 200 300 6.0 7.0 Jan/20122012_01 8.0 A2011_08ug/2011 9.0 Feb/20112011_02

(m) 10.0

11.0 Dec/20082008_12 12.0

Depth 13.0 14.0 15.0 16.0

KPX=400 0.400 (200kHz) Distance(m) ‐700 ‐600 ‐500 ‐400 ‐300 ‐200 ‐100 0 100 200 300 6.0 7.0 Jan/20122012_01 8.0 A2011_08ug/2011 9.0 Feb/20112011_02

(m) 10.0 11.0 Dec/20082008_12 12.0

Depth 13.0 14.0 15.0 16.0 KPX=200 0.200 (200kHz) Distance(m) ‐700 ‐600 ‐500 ‐400 ‐300 ‐200 ‐100 0 100 200 300 6.0 7.0 Jan/20122012_01 8.0 A2011_08ug/2011 9.0 Feb/20112011_02

(m) 10.0 11.0 Dec/20082008_12 12.0

Depth 13.0 14.0 15.0 16.0

Figure 3.11 Depth profiles of Turning Basin on the lines perpendicular to the wharf.

3-11

Y = 0 (200kHz) Distance(m)

7.0 8.0 9.0 10.0 (m) 11.0 12.0 Jan/20122012_01

Depth 13.0 A2011_08ug/2011 14.0 Feb/20112011_02 15.0 Dec/20082008_12 16.0

Y = ‐ 200 (200kHz) Distance(m)

8.0 9.0 Jan/20122012_01 10.0 A2011_08ug/2011 11.0 Feb/20112011_02 (m) 12.0 Dec/20082008_12 13.0

Depth 14.0 15.0 16.0 17.0

Y = ‐ 400 (200kHz) Distance(m)

7.0 8.0 2012_01Jan/2012 9.0 Aug/2011 10.0 2011_08

(m) Feb/2011 11.0 2011_02 12.0 2008_12Dec/2008

Depth 13.0 14.0 15.0 16.0

Figure 3.12 Depth profiles of Turning Basin on the lines parallel to the wharf.

3-12

3.1.4 Mean depth of access channel and harbor basin The surveyed water depths over the bottom width of navigation channel (about 140 m) were averaged to yield the mean channel depth. The mean depth is listed in Table 3.2 to Table 3.4.

Figure 3.13 shows the variation of the mean water depth along the harbor basin and access channel, listed in Table 3.2 to Table 3.4, in comparison with the previous survey results which were obtained in August 2008, December 2008, and June 2009. Figure 3.14 shows an expanded plot of Figure 3.13 for the portion of Inner channel and harbor basin. The mean depth at the completion of capital dredging is also shown with the marks of black closed circles. The mean depths just after capital dredging are measured in April 2008 for the Outer channel and in December 2008 for the Inner channel and harbor basin.

In the Outer channel, siltation since June 2009 is slight and locally depression is also seen in KP13 and KP14. On the other hand, siltation in the Inner channel is heavy and the channel depth at the locations of KP3.00 to KP4.00 is about 7.5 m. The harbor basin has the mean channel depth of about 12.2 m. Though the mean depths of the survey lines of x+200 and x+400 are about 12.7 m, the mean depth just in front of the wharf is -9 to -11 m, indicating localized siltation there.

The mean water depths in the harbor basin obtained from 1st to 3rd On-site Works have changed little and indicates that siltation at the present situation seem to have almost finished because the channel has almost filled with sediments.

3-13

Table 3.2 Mean depth of access channel and harbor basin in February 2011 KP Mean depth KP Mean depth KP Mean depth (m) No No No (km) Channel (m) (km) Channel (m) (km) Channel Basin L1 21.91 -13.70 L11 11.89 -13.25 L21 1.92 -8.80 - L2 20.90 -13.03 L12 10.90 -13.54 x+1200 1.20 -10.71 - L3 19.90 -12.36 L13 9.91 -16.16 x+1000 1.00 -10.93 -11.47 L4 18.91 -11.70 L14 8.90 -22.14 L22 0.92 -11.06 -11.52 L5 17.91 -11.17 L15 7.91 -33.33 x+800 0.80 -11.34 -12.04 L6 16.91 -10.94 L16 6.92 -29.68 x+600 0.60 -11.57 -12.64 L7 15.91 -10.96 L17 5.93 -17.75 x+400 0.40 -11.69 -12.47 L8 14.91 -11.60 L18 4.93 -8.19 x+200 0.20 -10.85 -13.03 L9 13.91 -12.57 L19 3.92 -7.70 x+0 0 L10 12.91 -12.97 L20 2.92 -7.74

Table 3.3 Mean depth of access channel and harbor basin in August 2011 KP Mean depth KP Mean depth KP Mean depth (m) No No No (km) Channel (m) (km) Channel (m) (km) Channel Basin L1 21.91 -13.68 L11 11.89 -12.08 L21 1.92 -8.76 - L2 20.90 -12.94 L12 10.90 -13.96 x+1200 1.20 -10.72 - L3 19.90 -12.06 L13 9.91 -16.23 x+1000 1.00 -10.94 -11.51 L4 18.91 -11.54 L14 8.90 -22.42 L22 0.92 -11.02 -11.42 L5 17.91 -11.15 L15 7.91 -33.42 x+800 0.80 -11.23 -11.91 L6 16.91 -10.81 L16 6.92 -29.78 x+600 0.60 -11.39 -12.35 L7 15.91 -10.75 L17 5.93 -18.12 x+400 0.40 -11.63 -12.87 L8 14.91 -11.32 L18 4.93 -7.89 x+200 0.20 -10.78 -13.09 L9 13.91 -12.24 L19 3.92 -7.55 x+0 0 L10 12.91 -12.54 L20 2.92 -7.50

Table 3.4 Mean depth of access channel and harbor basin in January 2012 KP Mean depth KP Mean depth KP Mean depth (m) No No No (km) Channel (m) (km) Channel (m) (km) Channel Basin L1 21.91 -13.77 L11 11.89 -12.38 L21 1.92 -8.55 - L2 20.90 -13.25 L12 10.90 -13.91 x+1200 1.20 -10.50 - L3 19.90 -12.38 L13 9.91 -15.92 x+1000 1.00 -11.02 -11.37 L4 18.91 -11.67 L14 8.90 -22.63 L22 0.92 -10.91 -11.52 L5 17.91 -10.81 L15 7.91 -33.35 x+800 0.80 -11.35 -11.90 L6 16.91 -10.38 L16 6.92 -25.08 x+600 0.60 -11.66 -12.00 L7 15.91 -10.14 L17 5.93 -18.08 x+400 0.40 -11.61 -12.79 L8 14.91 -10.92 L18 4.93 -7.67 x+200 0.20 -10.78 -13.16 L9 13.91 -11.96 L19 3.92 -7.44 x+0 0 L10 12.91 -12.52 L20 2.92 -7.48

3-14

-6 Cap. Dredg. (Apr.08) -7 Aug. 08 Dec. 08 -8 Jun. 09 -9 Feb. 11 -10 Aug. 11 -11 Jan. 12 -12 East B. (Feb. 11) -13 East B. (Aug. 11) -14 East B. (Jan. 12) -15

Channel Channel mean depth (m) -16 -17 -18 -19 -20 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 20.0 22.0

Distance (KP) Figure 3.13 Variation of mean depth of the access channel

-6 Cap. Dredg.(Apr.08) -7 Aug. 08 -8 Dec. 08 -9 Jun. 09 -10 Feb. 11 -11 Aug. 11 Jan. 12 -12 East B. (Feb. 11) -13 East B. (Aug. 11) -14 East B. (Jan. 12) -15 basin (Feb. 11) -16

Channel (m) mean depth basin (Aug.11) -17 basin (Jan.12) -18 -19 -20 0.0 1.0 2.0 3.0 4.0 5.0 6.0

Distance (KP) Figure 3.14 Variation of mean depth of the Inner channel and harbor basin

3-15

3.1.5 Difference between depth measurements with 38 and 200 kHz sonic waves The dual frequency bathymetric survey in June 2009 during the SAPI Study indicated a certain difference between the water depth measured with the sonic waves of 38 kHz and 200 kHz, as shown in Figure 3.15, which are reproduced from the Final Report of SAPI Study (2009).

Figure 3.15 Transversal channel profiles with the acoustic signals of 38 kHz and 200 kHz at L18 to L20 (SAPI, 2009) The lower frequency waves of 38 kHz yielded the water depth greater than the one measured with those of 200 kHz. The difference varied from location to location in the range of 0 to 1.2 m as listed in Table 3.5 (from the Final Report SAPI Study, 2009). The depth difference was regarded as representative of fluid mud layer which had not been consolidated yet after the completion of capital dredging in late December 2008.

3-16

Table 3.5 Approximate range of fluid mud thickness at respective transverse lines (SAPI, 2009)

There have been many arguments on the acoustic response of fluid mud layer to the low and high frequency sonic waves, but no quantitative conclusion has been obtained yet. Vertical mud sampling conducted in the First On-site Works indicates the surface density of fluid mud layer is around 1.05 g/cm3. Judging from the Team’s experience in the SAPI and the present Project, the threshold density for activating the response of 38 kHz sonic waves seems to be around 1.05 g/cm3, while the threshold density for the 200 kHz sonic waves seems to be around 1.03 g/cm3 which is just above the seawater density with inclusion of turbid mud particles.

When maintenance dredging is undertaken, siltation process will take place immediately. During the early stage of siltation, there may be some difference in the acoustic response of the seabed with the sonic waves of 38 kHz and 200 kHz.

3-17

3.2 Seabed Mud Conditions

3.2.1 Sites and methodology of mud sampling During the First On-site Works, mud sampling was made at five locations listed in Table 3.6. The sites A and B are located outside the basin and channel, while the sites C, D, and E are located inside the basin and channel. The site locations are shown in Figure 3.16.

Table 3.6 Locations of mud sampling sites. Approx. depth of mud No KP (km) y (m) surface layer (m) Remarks As meas. Ref. to DL A 0.20 +200 -8.7 -8.5 Outside basin B 2.92 +200 -6.9 -6.7 Outside channel C 0.20 0 -13.7 -13.5 Inside basin D 2.92 0 -7.8 -7.6 Inside channel E 15.91 0 -11.6 -11.4 Inside channel

A C B D

Figure 3.16 Location of sampling sites

At each site, a pair of 1ong polyvinyl-chloride pipe (1.5 m) and a short polyvinyl-chloride pipe (0.5 m) was vertically inserted into the mud layer by a pair of divers. The pipes had the inner diameter of 50 mm. Short pipes were inserted into mud for full length, while long pipes were inserted by 1.2 m. The elevation of the top of each short pipe was monitored by a diver’s computer and later converted to the water depth relative to the port datum level. The pipes were sealed at the top and bottom with caps while drawing out from the mud layer, and they were brought to the survey boat (see Figure 3.17). The depth reported by the divers is approximately equal to the water depth measured by the sonic waves of 200 kHz. Thus, the water depth measured by the echo sounder is judged to represent the depth of the surface of fluid mud layer.

3-18

Visibility of seawater was almost zero near the seabed. The divers reported that they could not recognize the surface of mud layer by eyes. They sat on top of the mud layer and identified it by touch with their hands.

The short pipes were intended to catch the surface layer of fluid mud. Because of no visibility around the seabed, the divers seem to have inserted the short pipes somewhat deeper than the fluid mud surface. The long and short pipes were brought to the office and the weights of a pipe with and without mud content were measured using a digital scale. The wet density of fluid mud was calculated with the weight of mud contained in the pipe by dividing it by the pipe’s capacity.

Figure 3.17 Lifting of sampling tube at Site E (a) and Sampling tube at Site E (b)

The long pipes were supposed to be inserted into the seabed by the length of 1.2 m, leaving the top 0.3 m above the mud layer. At certain locations, a diver could not drive the pipe more than 0.9 m or so, because of large resistance of hard mud there. The pipes were cut into sections of 0.3 m long on board (see Figure 3.18). The top section contained seawater only. The second section usually contained mud dispersed in water. After a long pipe was brought on the boat, the settlement process of mud particles started and an interface between water and fluid mud appeared in a few minutes. The interface height was measured, and it was employed to estimate the elevation of the fluid mud surface.

3-19

(a) Cutting off the 0th and (b) Splitting the 2nd and 3rd (c) Splitting the 3rd and 4th 1st sections. sections. sections.

Figure 3.18 Cutting a sampling pipe into sections of 0.3 m long

3.2.2 Description of sampled mud and vertical density profile of mud layer The mud content in each section was measured for its wet density, and then it was poured into a plastic bag with tight sealing (Ziplock) for later shipment to Japan. Mud samples from long polyvinyl-chloride pipes are counted as 40. Each sample of mud weighed about 1 kg. The pictures of mud samples placed in plastic bags are shown in Figure 3.19.

When the mud wet density is less than 1.1 g/cm3 as shown in Figure 3.19 (a), mud is just like liquid. As the density increase, mud gains plasticity like soft clay. When a mud sample is placed into a bag from a polyvinyl-chloride pipe section, the sample maintains a cylindrical shape for a while. When the mud wet density exceeds 1.2 g/cm3, a mud sample looks like a mass of clay as shown in Figure 3.19 (d).

The measured wet density of mud layer is plotted against the mean depth of sampled layer below the seabed in Figure 3.20 and Figure 3.21 for outside and inside the channel, respectively. To indicate the trend of wet density variation, a linear regression line is drawn for each measurement site. Mud on the bank outside the channel has been left undisturbed for many years and well consolidated by its own weight and loading by wave pressure and shear stress of tidal currents. A rapid increase of the wet density with the increase of layer depth from the seabed shown in Figure 3.20 is an evidence of the well consolidated state of mud. Measured data of mud wet density show some scatter probably due to sampling variability, but the trend of density change indicated with the regression lines suggests that the mud wet density will exceed 1.4 g/cm3 at the level of 0.7 m below the seabed.

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3 t = 1.12 g/cm 3 t = 1.08 g/cm

(a) Mud sample from Site D (b) Mud sample from Site D th (2nd Section) (4 Section)

3 3 t = 1.27 g/cm t = 1.17 g/cm

Figure 3.19 Photographs of mud sample with its density

Compared with the mud wet density on the bank outside the channel, the density of mud deposited inside the channel is low and its increase with depth is slow, as shown in Figure 3.21. The site D at the location of KP2.9 has a silted mud layer of about 7 m as indicated in Figure

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3.14. The mud layer has been deposited in the past 2 years and it is still under the process of consolidation. The depth of threshold density (1.2 g/cm3) would be nearly 2 m below the seabed.

Around the site C at the location of KP0.20, the thickness of silted mud layer is about 4.5 m as seen in Figure 3.14. Around the site E at the location of KP15.91, the thickness of silted mud layer is also about 4.5 m, but the deposition since June 2009 is only 0.5 m thick. The thinner mud layer in the sites C and E than the site D may be the reason of the increase of mud wet density with the depth faster than that in the latter.

0 Outside A: Meas. Outside A: Linear (m)

‐0.2 Outside B: Meas. Outside B: Linear

seabed ‐0.4

from ‐0.6 depth

‐0.8 Layer

‐1 1.0 1.1 1.2 1.3 1.4 1.5 Density (g/cm3) Figure 3.20 Vertical profile of mud wet density outside the access channel

0 Inside C: Meas. Inside c: Linear (m) ‐0.2 Inside D: Meas. ‐0.4 Inside D: Linear seabed

Inside E: Meas. ‐0.6 Inside E: Linear from

‐0.8 depth

‐1 Layer

‐1.2 1.0 1.1 1.2 1.3 1.4 1.5 Density (g/cm3) Figure 3.21 Vertical profile of mud wet density inside the access channel

3.2.3 Physical properties of sampled mud The 40 mud samples were transported to Japan and detailed soil tests were commissioned to OYO CORPORATION. The wet density and moisture content were measured for all the samples, but other soil characteristics were investigated for the vertically mixed samples at respective sites because the mud properties are considered invariant to the depth.

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The wet density (t) satisfied the theoretical relationship with the moisture content as expressed by Eq. (3.1).   /1  w  st  %100 (3.1)  wt 1/ where w and s denote the density of water and soil grains, respectively. Figure 3.22 shows comparison between the measured data and theoretical prediction, in which the water density is 3 3 taken at w = 1.00 g/cm and the soil density at s = 2.65 g/cm . 500

Meas. 400 Theory (%)

300 content

200 Moisture 100

0 1.10 1.20 1.30 1.40 1.50 Wet density (g/cm3) Figure 3.22 Relationship between moisture content and wed density of mud samples

It should be commented that the wet density tested in laboratory in Tokyo was greater than the density measured at La Unión up to 0.1 g/cm3. Mud samples were sealed in Ziplock bags, which were placed in sealed plastic bottles. Nevertheless, a lapse of two months from the time of sealing in La Unión to that of opening in Tokyo might have caused small evaporation of water content in mud samples and increased the wet density. Thus, the wet density measured immediately after sampling from the seabed is employed as representative of in-situ density and shown in Figure 3.20 and Figure 3.21.

The test results of the soil characteristics of vertically-mixed samples are listed in Table 3.7. Because these five samples represent the mud on the surface layer of 1.0 m below the seabed, they have more clay content than those analyzed in the SAPI Study. The sample from the site D has the grain diameter much smaller than those at other sites and the higher plasticity index. It might have been caused by rapid inflow of fluid mud owing to a large depth difference there between the inside and outside of the access channel.

Table 3.7 Soil characteristics at five sampling sites Sampl Soil grain Median 75% upper Liquid Plastic Plasticity Organic Ignition ing density diameter diameter limit limit index content loss 3 site s (g/cm ) d50 (mm) d75 (mm) wL (%) wL (%) IP c0 (%) Li (%) A 2.640 0.002 0.014 111.6 33.9 77.7 4.69 13.4 B 2.648 0.006 0.042 103.7 34.0 69.7 5.20 12.9 C 2.672 0.003 0.040 105.7 33.0 72.7 4.39 13.2 D 2.626 0.001 0.008 132.4 39.0 93.4 5.14 15.1 E 2.636 0.005 0.028 113.3 34.3 79.0 4.78 14.0

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3.2.4 Numerical prediction of density profile change by means of mud consolidation process (1) Methodology of mud consolidation prediction Fluid mud deposited in the basin and channel is a mixture of fine mud particles and sea water. Its initial density is somewhere between 1.05 to 1.10 g/cm3. As time elapses, mud particles congregate together and their contact builds a 3D skeleton structure of mud particles. The weight of individual mud particles works as the load to the skeleton and squeezes out the water contained within the skeleton. Then the mud particle skeleton shrinks and the fluid mud wet density increases. This is the initial stage of mud consolidation. Fluid mud of low density gradually becomes very soft mud and then soft mud.

The key parameters of mud consolidation are the compressibility and permeability of mud. They are investigated through a mud settlement test and a low pressure consolidation test. The former employs a settlement tube of 0.2 m in diameter and 2 m in height. A mixture of mud and water with the moisture content of 1000 to 3000% is poured in the settlement tube. Immediately after pouring, mud particles begin to settle and there appears an interface between water and fluid mud. The interface settles down as time elapses and the settlement of interface is monitored over a certain period. For the mud samples taken from five locations of A to E were subjected to the settlement test for 60 days. The mud deposited at the bottom of the settlement tube was then subjected to the low pressure consolidation test. Through these tests, the compressibility and permeability parameters were estimated. Because samples from the five locations yielded similar values of the parameters, their average values were adopted in the consolidation analysis.

Computation of mud consolidation process is made by solving the consolidation equation of one dimension along the vertical axis. The weight of mud layer is the sole load activating consolidation. External loading such as the wave pressure is not taken into account. Numerical computation of mud consolidation has been executed by Dr. Masaki Kobayashi of Kobayashi SoftTech Co. Ltd..

Consolidation is computed by increasing mud layer continuously with a reducing deposition speed. A newly deposited mud is reduced in height by consolidation and the deposition speed is enhanced from the continuous siltation. The rate of enhancement is set by the try and error method. Mud consolidation was analyzed with 180 steps. During the first step, a single top-most mud layer is dealt with. During the second step, a second mud layer is added upon the first layer. The process is repeated to the 180th step, and thus the thickness and density of 180 layers are calculated. The results on 180 layers are summarized into 10 layers, each of which represents the average of 18 steps at respective depths.

Two series of mud consolidation computation have been undertaken. One series aimed at simulating the process of siltation that took place at the locations D and E in Table 3.6 and Figure 3.16 for the purpose of calibrating the consolidation prediction method. The other series simulated the siltation process in the access channel within 12 months after execution of maintenance dredging. Four levels of the depth difference between the inside and outside of the channel are employed for representing a possible range of depth difference from 3.0 to 7.5 m. The results of computation are described in the subsequent sections.

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(2) Calibration of consolidation analysis with In-situ data The site D in Table 3.6 and Figure 3.16 is located at the distance KP 2.92 (L20). The vertical profiles of mud wet density near the seabed are shown in Figure 3.21. The depth change with time and the density profile are the target of calibration of consolidation analysis.

When the capital dredging was completed at the site D in the end of December 2008, the depth difference between the inside and outside of the access channel was 7.8 m. According to the bathymetric survey results, the siltation speed was v = 0.87 m/month in early January 2009 and v = 0.25 m/month in early February 2011. In the case of the site E where the capital dredging was completed in the end April 2008 with the depth difference of 5.9 m, the siltation speed was estimated at v = 0.66 m/month in early May 2009 and 0.08 m/month in early February 2011.

In consideration of consolidation of deposited mud, the deposition speed was set faster than the siltation speed measured by bathymetric survey results. Several trials of consolidation computation with different deposition speeds were made, and those shown in Figure 3.23 were selected for the calibration test.

1.2 Inside D (Dh = 7.0 m) 1.0 Inside E (Dh = 5.9 m)

(m/month) 0.8 v

0.6 speed,

0.4

0.2

Deposition 0.0 0 6 12 18 24 30 36 Elapsed time, t (month) Figure 3.23 Deposition speed employed in calibration of mud consolidation analysis

3 The density of fluid mud creeping into the channel was assumed to be s = 1.100 g/cm against 3 the surrounding seawater with w = 1.025 g/cm . The computed thickness of deposited mud was employed to calculate the variation of channel mean depth with the lapse of time. Figure 3.24 (a) shows the predicted channel mean depth in comparison with the bathymetric survey results at the site D. The calculated depth was deeper than the actual depth, indicating the assumed deposition of fluid mud at the site D was not sufficient enough to simulate the actual bathymetric change. Nevertheless this was the best case among several trial simulations. Though there remains a difference of some 1 m on average between the calculation and the bathymetry, the trend of calculated depth change agrees with the bathymetric data.

Evolution of mud wet density profile at the site D is shown in Figure 3.24 (b). The ordinate is the height of silted mud layer above the channel bottom. The silted height corresponding to the density of 1.100 g/cm3 represents the total mud thickness at respective date. The mud wet density shown in this figure is the density at each level of silted height. For example, the mud wet density at the height of 2.0 m above the channel bottom was 1.13 g/cm3 in July 2009, and then increased to 1.21 g/cm3.in January 2010, 1.24 g/cm3 in July 2010, and 1.26 g/cm3 in January 2011. As the time elapses, the mud wet density profile shifts upward with little change,

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indicating the density profile measured from the surface of mud layer remains the same and the lower part of mud layer gradually gains higher density.

(a) Time evolution of channel mean depth (b) Time evolution of mud wet density at Site D. profile at Site D.

Figure 3.24 Time evolution of (a) channel mean depth and (b) mud wet density profile at Site D

(a) Time evolution of channel mean depth (b) Time evolution of mud wet density at Site E. profile at Site E.

Figure 3.25 Time evolution of (a) channel mean depth and (b) mud wet density profile at Site E

Comparison of the calculated consolidation and the in-situ data at the site E is shown in Figure 3.25(a) for the channel mean depth and in Figure 3.25(b) for the mud wet density profile. The calculated rise of the channel depth in Figure 3.25(a) was slower than the in-situ data up to 18 months after the start of siltation, but the calculation gave the final depth same as the bathymetric survey result.

The evolution of mud wet density profile at the site E shown in Figure 3.25(b) is similar with that at the site D shown in Figure 3.24 (b), but the mud wet density at the channel bottom at the site E is slightly larger than that at the site D, because of a long deposition period of 33 months in comparison with 25 months at the site D. The high mud wet density above 1.2 g/cm3 near the seabed measured in situ could not be simulated by the mud consolidation analysis. The discrepancy is thought to have been caused by the additional loading by the underwater pressure by the swell persistent along the Outer channel.

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Although the results shown in Figure 3.24 and Figure 3.25 exhibit some difference between the calculation by the consolidation analysis and the in-situ data, it can be said that the consolidation analysis does clarify the process of siltation with evolution of mud wet density increase.

(3) Prediction of mud deposition and density change after maintenance dredging With confirmation of the capability of simulating mud siltation process presented in Sec. (2), prediction of the process of mud deposition and the evolution of mud wet density after maintenance dredging has been carried out. The density of fluid mud creeping down into the channel is assumed to be 1.100 g/cm3 against the seawater density of 1.025 g/cm3. In consideration of several dredging depths, the depth difference between the dredged channel and the outside bank is set at four levels of h = 3.0, 4.5, 6.0, and 7.5 m. Figure 3.26 shows the deposition speed employed in the consolidation analysis.

1.6 Del_h = 7.5 m 1.4 Del_h = 6.0 m 1.2 Del_h = 4.5 m Del_h = 3.0 m

(m/month) 1.0 v

0.8

0.6 speed,

0.4

0.2

Deposition 0.0 036912 Elapsed time, t (month) Figure 3.26 Deposition speed employed in prediction of mud deposition after maintenance dredging

The predicted siltation height with the lapse of time is shown in Figure 3.27(a). According to Eq. (5.2), the siltation height is estimated as h = 2.2, 3.3, 4.4, and 5.5 m at 12 months after dredging for the initial depth difference of h0 = 3.0, 4.5, 6.0, and 7.5 m, respectively. The predicted siltation height is slightly lower than the estimated height, but the difference may be regarded as allowable for examination of time evolution of mud wet density.

The time evolution of mud wet density at the channel bottom is shown in Figure 3.27(b). The increase of bottom mud wet density is fast at the first three months and the effect of initial depth difference is small. The increase of bottom mud wet density with time is shown in Figure 3.28 against the siltation height. It is a combination of the data plotted in Figure 3.27(a) and (b). Four curves corresponds to the four levels of initial depth difference, and four symbols indicate the data of density and height at the lapse of 3, 4, 6, and 12 months after maintenance dredging. 3 Figure 3.27(b) indicates that the threshold density of s = 1.20 g/cm for nautical bottom will be reached in 3 to 4 months after dredging with the thickness of 1 to 2 m.

The time evolution of mud wet density profile is shown in Figure 3.29 and Figure 3.30 for the initial depth difference of h = 3.0, 4.5, 6.0, and 7.5 m, respectively. The pattern of density profile evolution is almost the same regardless of the initial depth difference.

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(a) Time evolution of siltation height after (b) Time evolution of bottom mud wet density maintenance dredging. after maintenance dredging.

Figure 3.27 Time evolution of (a) siltation height and (b) bottom mud wet density after maintenance dredging

Figure 3.28 Time evolution of bottom mud wet density versus siltation height after maintenance dredging.

(a) Time evolution of mud wet density (b) Time evolution of mud wet density profile withh = 3.0 m. profile withh = 4.5 m. 0 0 Figure 3.29 Time evolution of mud wet density profile. (a) h = 3.0 m and (b) h = 4.5 m

3-28

(a) Time evolution of mud wet density (b) Time evolution of mud wet density profile with h = 7.5 m. profile withh0 = 6.0 m.  0

Figure 3.30 Time evolution of mud wet density profile. (a) h0 = 6.0 m and (b) h0= 7.5 m

3.2.5 Assessment of thickness of fluid mud layer for definition of nautical bottom The main objective of mud consolidation analysis is to make assessment of the thickness of fluid 3 3 mud layer with the density below s = 1.20 g/cm = 1,200 kg/m , which is taken as the threshold density for defining the nautical bottom.

Outside the channel, the mud wet density exceeds the threshold value at the depth of 0.4 m below the seabed at the sites A and B as shown in Figure 3.20. Inside the Inner channel, the threshold density is exceeded at the depth of 0.5 m and more than 1.0 m at the sites C and D, respectively, as shown in Figure 3.21. Inside the Outer channel at the site E, the depth to the threshold density is 0.4 m.

Compared with the in-situ density data, the consolidation analysis predicts slow increase of mud wet density with the depth above the seabed. The result of comparison shown in Figure 3.25 (b) is an example. One reason is the absence of additional loading such as shear stress by tidal currents and underwater pressure by wave actions.

3 For the assessment of fluid mud layer thickness with the density below s = 1,200 kg/m , it would be safe to assume the thickness of 0.5 m for the Outer channel in consideration of additional loading by swell action. For the Inner channel, it is taken as h = 1.0 m on the safe side in consideration of the in-situ data at the site C, even though the consolidation analysis suggests larger depth up to 2.0 m.

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3.3 Main Results of the Field Survey

In this Chapter, results of bathymetric surveys and analysis of mud property have been summarized. Main findings from the surveys are as follows:

 From the bathymetry survey results, it is confirmed that both the Inner channel and the Outer channel have already filled with the sediment and the channel depth is presently the almost same level as the outside depth of the channel.

 Judging from the Team’s experience in the field, it is considered that the echo sounder of 200 kHz in frequency detects the top surface of the fluid mud layer. The depth navigable for vessels is considered to be deeper than the depth measured by the echo sounder of 200 kHz, due to the thickness of the fluid mud layer.

 The fluid mud layer in the channel continues in existence for relatively long period. This indicates a possibility to reduce maintenance dredging volume by making a maintenance dredging plan taking the fluid mud layer into account.

 From the analysis of mud sampled at about two years after capital dredging, it is confirmed that fluid mud layer, the wet density of which is less than 1,200 kg/m3, is formed with the thickness of about 0.5 m in the Outer channel and about 1.0 m in the Inner channel.

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Chapter 4 Analysis of Siltation Process and Prediction Models

4.1 Collected Data

The data collected for analyses of siltation processes are the bathymetric data and the records of dredging.

Figure 4.1 shows the periods of dredging and the times of bathymetric surveying by distinguishing the areas of the harbor basin, the Inner channel and the Outer channel. In Table 4.1, periods of dredging are listed. The data were selected for analyses from these bathymetric data by taking into account the dredging period and times of surveying.

Newly obtained bathymetric data, July, 2013, is partly included in the analyses.

Figure 4.1 Period of dredging and times of bathymetric surveys

Table 4.1 Periods of implementation of dredging Location of dredging Period of dredging Harbor Basin 16 ~22 June, 2006 25 April~11 May, 2007 25 November~10 December, 2008 Inner channel 17 November~21 December, 2005 22 June~17 July, 2006 13 ~22 August, 2006 25 September~6 October, 2006 12 January~10 March, 2007 5~15 May, 2008 25 November~10 December, 2008 Outer channel 17July~12 August, 2006 23 August~24 September, 2006 30 January~4 May, 2008

4-1 4.2 Siltation Speed and Depth Difference in the Channel (Exponential model)

Figure 4.2 shows the changes of water depth at representative reference lines (Figure 4.3) in the Inner and the Outer channels, in which a brown line is the mean water depth in the channel, a blue and a green line are the depths at the western and eastern banks of the channel, respectively. The periods of dredging are indicated by the gray belts for the Inner channel and orange belts for the Outer channel. The bathymetric survey was repeated irregularly and the dredging was conducted also irregularly. From this data, it is easily understood that the siltation occurred after the dredging.

Figure 4.2 Changes of water depth in the Inner and the Outer channel

As the first trial, an empirical prediction model of siltation is considered based on the bathymetric data obtained after the last dredging. The formulation makes use of the data only after completion of capital dredging operations. For the Outer channel, seven sets of survey data in April ’08, August ’08, December ’08, June ’09, February ’11, August ’11, and January ‘12 are employed. For the Inner channel, five sets of survey data in December ’08, June ’09, February ’11, August ’11 and January ‘12 are utilized.

4-2

Figure 4.3 Bathymetric survey lines of access channel

Figure 4.4 shows the relationship between the siltation speed of the access channel and the mean depth difference h (m) between the inside and outside channel depths. The definition of water depths is shown in Figure 4.5. The siltation speed v in the units of m/month is calculated as the amount of the rise of the mean channel depth during two successive surveys being divided by the period between the two surveys. The mean depth difference h is in the units of meter. The water depth outside the channel is defined as the average depth of the western and eastern banks. The water depth inside the channel is taken as the average of two successive surveys. The legend such as “Outer: Dt = 4” denotes the data of Outer channel with the lapse of 4 months after the capital dredging, i.e., the survey data in August ’08. The Outer channel includes the data of L01 to L12, while the Inner channel includes the data of L18 to L21.

0.8 Whole Channel Outer: Dt = 4 Outer: Dt = 8 0.7 Outer: Dt = 14 0.6 Outer: Dt = 33

(m/month) 0.5 Outer: Dt= 39 v Outer. Dt=44 0.4 Inner: Dt = 6 speed,

0.3 Inner: Dt = 25 0.2 Inner: Dt= 31

Siltation Inner. Dt=36 0.1 Linear Approx. 0 Linear (outer) ‐0.1 Linear (inner) ‐101234567 Mean depth difference, h (m)

Figure 4.4 Siltation speed versus the depth difference inside and outside the access channel.

4-3

Figure 4.5 Definition of water depths Although the scatter of data is large, a linear regression line is tentatively drawn for the Inner and Outer channel as follows:

hd v  .0 109 :  hhhh : Access channel (4.1) dt in out The coefficient of determination is R2 = 0.6503.

The empirical formula of Eq.(4.1) is easily integrated for derivation of a prediction formula of the depth difference h as in the following:

exp[ tahh ] (4.2) 0 where a is assigned the value of 0.109 for the access channel. This value is determined taking all available data into account.

Use of Eq.(4.2) enables to predict the change of mean water depth in the access channel. Figure 4.6 compares the predicted and measured mean channel depth for selected sections of the Inner and Outer channel. The prediction formula produces better agreement with measured depth data. In case of the Outer channel in Figure 4.6 (b), the predictions for the sections at KP16 (L07) and KP17 (L06) overestimate the measured results.

4-4 ‐6 ‐7

(m) ‐8 in

h ‐9 , KP2_pred ‐10 KP2_meas depth ‐11 KP3_pred ‐12 KP3_meas

mean ‐13 KP4_pred KP4_meas ‐14 KP5_pred Channel ‐15 KP5_meas ‐16 0 6 12 18 24 30 36 42 48 Elapsed time, t (month)

(a) Depth change prediction and measurement for the Inner channel

‐9

‐10 (m)

in ‐11 h , ‐12 KP20_pred depth

‐13 KP20_meas KP17_pred ‐14 mean KP17_meas KP16_pred ‐15 KP16_meas ‐16 KP15_pred Channel KP15_meas ‐17 0 6 12 18 24 30 36 42 48 Elapsed time, t (month)

(b) Depth change prediction and measurement for the Outer channel Figure 4.6 Comparison of predicted and measured channel depths for selected survey lines

4-5 4.3 Analyses of Siltation Processes in Channel

In Chapter 4.2, as the first step to predict the siltation the empirical model (Eq.(4.2)) is formulated, which is the exponential function (hereinafter referred to as “ the original Exponential Model” ). In order to improve this model, CEPA tried to conduct the spot re-dredging by using the rake. However, the data which is necessary for improving the original Exponential Model have not been obtained yet as explained (see Annex C.3).

Then, there is nothing else to do, an existing bathymetric data has been analyzed to understand the siltation processes, and also to look for the possibility of improving the model.

4.3.1 Siltation in Inner Channel Figure 4.7 shows the changes of water depths on the reference lines from L21 to L18, in which a brown line is the mean water depth in the Inner channel, a blue line and a green line are the depth at the western and eastern banks of the Inner channel, respectively. The periods of dredging are indicated by the gray belts. Among these bathymetric data, those in the Term A and in the Term B were selected for analyses because the dredging work was suspended in these two terms.

Figure 4.7 Changes of water depth on the reference lines from L21 to L18 in Inner channel

4-6 In Figure 4.7, paying attention to the Term A, the water depth linearly changed on all reference lines. That is, the speed of sedimentation was constant. On the other hand, the water depth in the Term B became shallower with relatively high speed just after the dredging and the speed became slower with a decreasing of water depth. In short, the water depth changed exponentially. The tendency of exponential change of water depth in the Term B is recognized on every reference line in Figure 4.7.

The reason why the water depth changed exponentially in the Term B is examined. The speed of sedimentation was faster just after the dredging, which is denoted by a red arrow for the data on the reference line L21 as an example in Figure 4.7. In order to check the situation in detail, three cross sections are superimposed in Figure 4.8 for the reference line L21. They are the cross section before the dredging in August, 2008 (which is denoted by “a” in Figure 4.7), that of December, 2008 just after the dredging (“b”) and that of 6 months after dredging in June, 2009 (“c”).

The cross section “a” (August, 2008) and “c” (June, 2009) are very similar to each other. However, the cross section “b” (December, 2008) is different from them in two points. First point of difference is the channel depth, which was due to the dredging of course. The second point is elevation of the tops of slope which is surrounded by red broken lines in Figure 4.8. The elevation of the tops of slope just after the dredging (“b”) is about 60cm lower than those of remains, which is undoubtedly unnatural.

Aug. 2008 Dec. 2008 Jun. 2009 abc 6 L21 7 8 9 10 11 12 13 14 15 16 -300 -200 -100 0 100 200 300

Figure 4.8 Superposition of cross section along L21

Figure 4.9 shows the similar superposition of the cross sections along the remaining reference lines of L20 to L18. The unnaturalness at the tops of slopes which is pointed out in Figure 4.8 is recognized on every reference line.

Seeing Figure 4.7 again, it is understood that the water depth at the eastern bank and the western bank were stable during 6 years from 2005 to 2011, except one case in December 2008, of which data are shifted downward. Therefore, it is probably due to some systematic error such as an inappropriate correction for the tide level or a mistaken of datum level.

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Figure 4.9 Superposition of cross section along L20~L18 In Figure 4.10, the cross section just after the dredging (“b” in Figure 4.7) along the reference line L21 has been shifted by 60cm upward by way of trial so that three cross sections are well overlapped. As a result, the consistency of cross sections as the whole is improved well. This correction is considered to be well adequate.

Aug. 2008 Dec. 2008 Jun. 2009

6 L21 7 8 9 10 11 ↑ 0.6m 12 13 14 15 -300 -200 -100 0 100 200 300

Figure 4.10 Superposition of cross sections after shifting, for L21 (Cross section in December, 2008 is shifted by 0.6m upward)

4-8

Figure 4.11 Superposition of cross section along the reference lines of L20 to L18, after shifting date obtained in December, 2008 upward In Figure 4.11, the cross sections along the reference lines of L20 to L18 are superimposed in the same way, by shifting the bathymetric data obtained in December, 2008 upward. An amount of shifting is written for each reference line in Figure 4.11. As a result, the consistency of cross sections as the whole are improved well, too. The tide level correction may be inappropriate for the bathymetric data obtained in December, 2008.

Next, the mean water depth measured in January, 2011 is examined, which is denoted by “d” in Figure 4.7. The water depth inside the Inner channel agrees approximately with that of outside. Therefore, there are two possible interpretation concerning to this data “d”.

a. The channel was full of sediments in January, 2011.

b. The channel had been already full of sediments in January, 2011.

In the latter case, it is necessary to identify the date when the channel was full of sediments, which should be some day between “c” and “d” in Figure 4.7. However, it is nearly impossible to identify the date of full sedimentation because there is no more data and information at present. It is strongly desired to resume and continue the monitoring on sedimentation.

In Figure 4.12, the data are corrected by way of trial, in which the water depth in December, 2008 (“b”) is shifted upward and time of full-sedimentation is backed from January, 2011 (“d”) to some day between (“c”) and (“d”) in Figure 4.12. An amount of shifting upward is depending

4-9 on the result of consideration in Figure 4.10 and Figure 4.11, while there is no evidence which supports an amount of going back to the past indicated in Figure 4.12. The purpose of preparing Figure 4.12 is to show the possibility that the change of water depth is constant, or speed of sedimentation is constant also in the Term B. If so, the characteristics of sedimentation in two Terms of A and B do not contradict each other.

The hypothesis that the speed of sedimentation is constant without depending on the water depth in the channel will have significantly important meanings. In short, even if the target of maintenance depth of channel increases, only the volume of initial dredging increases but the volume of maintenance dredging does not increase. In order to confirm a validity of this hypothesis, it is basically important to resume and continue the monitoring of sedimentation in the channel.

Figure 4.12 Corrections of depth data in Inner channel

4-10 4.3.2 Siltation in Outer Channel Figure 4.13 shows the locations of the reference lines in the Outer channel.

Figure 4.14 shows the changes of water depths on the reference lines from L08 to L05, in which a brown line is the mean water depth in the Outer channel, a blue line and a green line are the depth at the western and eastern banks of the Outer channel, respectively. The periods of dredging are also indicated by the orange belts.

Figure 4.13 Locations of reference lines in Outer channel

As all of water depth changes at the reference lines from L08 to L05 have nearly the same features, then that of L07 will be explained as a representative example. The mean depth in the Outer channel became deeper due to the dredging. Just after the dredging, the water depth in the Outer channel rapidly became shallow and it gradually became shallower with time in the following period. These two processes, which are rapid and slow siltation processes, have been considered simultaneously in the original Exponential Prediction Model.

The depth of full-sedimentation in the Outer channel predicted by utilizing the original Exponential Model in the Outer channel is nearly 1 meter shallower than the actual depth. Then the cause of discrepancy between the predicted depth and the actual one is examined.

As seen in Figure 4.14, in June, 2006, before the dredging, three kinds of water depth, which are the mean water depth in the Outer channel, the water depth of the western and the eastern banks outside the channel, were of equal. At the outside of the Outer channel, the water depth was kept almost constant on the western bank, while it increased, became deeper, gradually on the eastern bank. The water depth in the channel became shallower with time due to the siltation up to the same elevation as the eastern bank, which is lower than its original elevation before dredging in 2006.

4-11

Figure 4.14 Changes of water depth on the reference lines from L08 to L05 in Outer channel

Next, the feature of cross section in full-sedimentation is examined on the reference lines of L08 to L05 in the Outer channel. The dredging periods in the Outer channel and the dates of bathymetric data which are utilized for consideration are shown in Figure 4.15. The three kinds of the bathymetric data are utilized, that is,

Data①(surveyed on 10 June, 2006); before the first dredging,

Data②(on 18 January, 2008); about 1 year and 4 months after the first dredging in 2006,

Data③(on 01 February, 2011); about 2 years and 8 months after the re-dredging in 2008.

4-12

Figure 4.15 Periods of dredging in the Outer channel and the bathymetric data utilized for consideration

Figure 4.16 shows the superposition of three cross sections along the reference lines of L08 to L05. A black line is a planned channel section, toward which the dredging were conducted in 2006 and in 2008. It seems that the full-sedimentation occurred two times at all the reference lines, and there features are qualitatively same. Then, the feature of sedimentation along the reference line L07 will be explained as a representative example.

Figure 4.16 Situation of full-sedimentation along L08～L05 in Outer channel

4-13 Along the reference line L07, the sea bottom was flat in June, 2006, which was a situation before dredging. The first stage dredging was completed by 24 September, 2006. In January, 2008, which was about 1 year and 4 months after the dredging, the Outer channel was almost full with sediments. The volume of sedimentation was larger in the western area than in the eastern area of the channel. The sediments deposited asymmetrically inside the channel. Outside the channel, the change of the sea bottom topography was also asymmetrical. The sea bottom did not changed, being stable, in the western area from a point of -100 meters, while in the eastern area the sea bottom was eroded by January, 2008 and further by February, 2011. These features are also recognized in the cross sections along the remaining reference lines. It is the most important and interesting situation that the water depth in the channel is usually equal to or deeper than that of eastern bank on the every reference line. This condition should be taken into the original Exponential Model.

In addition, as the sedimentation occurred from the west, which made the width of channel narrow, an extra dredging in the westward direction may be required to widen the channel width in a future dredging.

4.3.3 Physical consideration for rapid siltation just after dredging Let’s move on to the next topic of rapid sedimentation. As already explained, just after the dredging, the water depth in the Outer channel rapidly became shallower. However, in the following period, that is to say in the Term A and in the Term B in Figure 4.14, the water depths became gradually shallower with a constant speed as approximated by the straight broken lines. The approximate straight line has the same gradient for every reference line in the Term A, and the approximate line in the Term B has another gradient which is the same for every reference line in the Term B.

By taking this situation into consideration, a new prediction model of siltation speed can be developed, which is a so-called linear prediction model of constant siltation speed. However, there is a hard barrier which refuses the introduction of the new model. If the approximate lines in the Term A and the Term B are extrapolated back to the past of just completing of dredging, there are large gaps between the extrapolated lines and the measured depths, which are indicated by red arrows in Figure 4.14. The measured depths are deeper. Then, there is a danger that the linear model underestimates the siltation speed just after the dredging.

Before discussing the process of rapid siltation, the slow siltation with a constant speed is examined. Based on the feature of sedimentation seen in Figure 4.16, the process of sedimentation can be conceptually explained as follows.

Figure 4.17 shows the sea bottom topography before excavating the channel. It is assumed that the sea bottom is flat and the sediment is transported from the left to the right. In the control segment B, if the volume of sediment transported into the control segment B is equal to that of going out from the segment B, the sea bottom does not change. In short, it is in the dynamic equilibrium condition. The same situation is established in the control segments A and C.

4-14

Figure 4.17 Conceptual diagram of dynamic equilibrium condition before dredging

Let’s consider the condition that the channel is built in the control segment B, which is shown in Figure 4.18. The volumes of sediment going out and in the control segment A are the same as before. The dynamic equilibrium condition is still kept in the control segment A and the sea bottom does not change. The sediment transported into the control segment B deposits in the channel, then the volume of sediment going out decreases. As a result, the volume of sediment transported into the segment C becomes small. The volume of sediment going out from the control segment C is the same as before. The budget balance is lost, and the sea bottom is eroded in the control segment C.

Figure 4.18 Conceptual diagram of siltation in Outer channel

Figure 4.19 shows the superposition of cross sections along the reference lines of L07 and L06. During a period from October, 2006 to January, 2008, the dredging work was suspended. From the changes of cross sections, it can be seen the process of sediment accumulation from the west bank and the evolution of erosion in the east bank. A new knowledge we can obtain from Figure 4.19 is a situation that the accumulation continued with rising of the flat and horizontal bed in the east side in the channel which is surrounded by red broken lines. This is considered to be due to the deposition of sediment having high fluidity, e.g. fluid mud, in the east side in the channel.

4-15

Figure 4.19 Superposition of cross sections along L07and L06

By taking these situations into account, it is inferred that the characteristics of sediment deposited during the second slow siltation in the Outer channel is as shown in Figure 4.20. In short, on the western side-slope the coarse material having the high falling velocity accumulated, while the sediment having the high fluidity such as the fluid mud deposited in the east side in the channel.

Figure 4.20 Spatial distribution of sediment

At last, the rapid siltation is examined. Let’s see Figure 4.14 again. The rapid siltation occurred two times, just after the first dredging and the second dredging. In the former rapid siltation

4-16 occurred between the depth of 12 and 13 meters, while in the latter it occurred around the depth of 14 meters. Then an occurrence of rapid siltation does not depend on the water depth, but depends on the timing of just after the dredging.

Figure 4.21 shows the superposition of cross sections along the reference lines from L08 to L05, which were surveyed on 24 April and 5 May, 2008, just after the completion of second dredging in 2008. Although there are small leaving parts of unexcavated earth in the cross sections on reference lines L08 and L07, the channel was dredged almost more than planned cross section.

Figure 4.22 shows the cross sections at the time of about 3 and half months after the dredging, 11 August, 2008, in which it can be seen that the rapid siltation occurred with the embedding thickness of 1.5 to 2 meters during this period. As accumulations were horizontal in the full width of channel on all reference lines, and there is no deposition on the side slope, it is inferred that high fluidity material, e.g. fluid mud, deposited in the channel. In short, just after the dredging, it is within the bounds of possibility that the rapid siltation occurred due to the inflow of high fluidity sediment which existed in the area surrounding the channel before dredging.

Figure 4.21 Superposition of cross sections just after the second dredging, (Surveyed on 28 April and 5 May, 2008)

4-17

Figure 4.22 Superposition of cross sections, 11 August, 2008, about 3 and half months after the dredging

The siltation process in the Outer channel can be divided into two successive stages, that is to say, the rapid siltation in a few months just after the dredging and the slow siltation in the following period. In the first stage, the accumulation with high fluidity sediment were horizontal in the full width of channel, while in the second stage of slow siltation, as explained in Figure 4.18 and Figure 4.20, the deposition of coarse material on the western side-slope and the sea bottom erosion on the eastern bank, and the siltation of high fluidity sediment such as fluid mud occurred simultaneously. By taking these situations into account, it is inferred that the characteristics of sediment deposited in the Outer channel is as shown in Figure 4.23. In short, during a period just after the dredging, high fluidity material such as the fluid mud rapidly flowed into the channel and deposited horizontally there. After that, on the western side-slope the coarse material having the high falling velocity accumulated, while the sediment having the high fluidity such as the fluid mud deposited in the east side in the channel.

Figure 4.23 Spatial distribution of sedimentation

As explained in Figure 4.14, the rapid siltation just after the dredging does not depend on the channel depth, but on the timing of dredging. Then, the rapid siltation just after the dredging is also considered to be due to inflow of very movable sediment which existed surrounding the channel before excavation. If so, the rapid siltation may be the bound phenomenon only once in the channel newly excavated, and it does not occur in the case that the maintenance dredging is continuously conducted.

4-18 4.4 Siltation Prediction Models for Channel

4.4.1 Modifications of original Exponential Model In section 4.2, the prediction model for the depth change in the channel has been formulated empirically. However, a close examination on the siltation process based on the bathymetric data gives us two concerns. In the Inner channel, the bathymetric data obtained in December, 2008, just after the second dredging, is unnaturally shifted downward. In the Outer channel, the water depth in the channel did not become shallower than that of the eastern bank. By taking these concerns into consideration, the original Exponential Model is modified.

(1) Modification for Inner Channel The water depth in December, 2008, just after the second dredging, was deepest in the Inner channel during a period from 2006 to 2011. As the corresponding data was shifted downward, as shown in Figure 4.24 by example, it has been corrected by shifting upward. The results of correction to the reference lines L21 to L18 are shown in Figure 4.25, in which the original data in the Inner channel reproduced from Figure 4.4 are denoted by the symbol ○ and the corrected data are plotted by the symbol ●. As the whole data of cross section are shifted upward, the depth difference between inside and outside of channel does not change on an abscissa, while the siltation speed decreases on an ordinate.

Aug. 2008 Dec. 2008 Jun. 2009 abc 6 L21 8

16 -300 -200 -100 0 100 200 300

Figure 4.24 Gap of cross section, on reference line L21（Inner channel） (Reproduce from Figure 4.8)

4-19

Figure 4.25 Siltation speed versus the depth difference in the Inner channel, after the correction of data

As seen in Figure 4.25, the slope of linear relation between the siltation speed and the depth difference decreases from a=0.109 to

a=0.089, (4.3) which is introduced into Eq. (4.2) for the Inner channel.

Figure 4.26 shows a comparison of the predicted curves by the original Exponential Model in the upper and by the modified one in the lower with the actual water depth in the Inner channel. The depth data corresponding to correction are surrounded by the red broken lines. After the modification of the original Exponential Model, in the lower figure, the slope of predicted curve around the depth from 9 to 14 meters becomes a little bit gentler than that of the original one, which means a decrease of siltation speed.

4-20

Figure 4.26 Comparison of original and modified Exponential Model with the actual depth ( for Inner c)

(2) Modification for Outer Channel In the Outer channel, a shoaling of water depth due to siltation approaches asymptotically to the elevation of the eastern bank. Because the eastern bank is eroded after dredging, the water depth is deeper than that of before dredging. If the channel is left further without a maintenance dredging, the water depth will recover to the original depth before long, which is the same depth as that of the western bank. It is, however, considered that the depth of eastern bank is usually deeper than that of western bank when a maintenance dredging is conducted continuously.

The simplest method for taking the effect of eastern bank is shown in Figure 4.27. The water depth outside the channel, hout , and the depth difference between inside and outside the channel,

h0 , in the original Exponential Model are replaced with he and h0e respectively, which are defined in Figure 4.27. The water depth at the east bank, he , is called “final depth” hereinafter. The coefficient is fixed without change, being a =0.109.

4-21

Figure 4.27 Modification of Exponential Model by introducing a concept of final depth ( for Outer channel)

Figure 4.28 Longitudinal profile of final depth he of Outer channel

Figure 4.28 shows a longitudinal profile of final depth, he , which is adopted in the calculation. A black line is the longitudinal profile of sea bottom before the first dredging, June 2006, and a blue line is the longitudinal profile of the Outer channel when it was in full-siltation, which is the mean profile of three data, that is February and August 2011, January 2012. The final depth on each reference line is determined so that it agrees with the mean profile. Figure 4.29 shows a comparison of the predicted curves by the original Exponential Model in the upper and by the modified one in the lower with the actual water depth in the Outer channel. By introducing the final depth in the model, the predicted curve and the actual water depth become to almost agree in the shallow area surrounded by a red dotted line. Furthermore, paying attention to the points denoted by red arrows in the figure, concerning to the reference lines of L07 and L06, it takes 12 months to shoal up to the depth of 11meters in the original model while it takes 18 months in the modified model. In short, the modification for the Outer channel also makes the siltation speed slow.

4-22

Figure 4.29 Comparison of original and modified Exponential model with the actual depth (for Outer channel)

4-23 4.4.2 Linear model In section 4.2, it is explained that the siltation process in the Outer channel can be divided into two successive stages, that is to say, the rapid siltation just after the dredging and the slow siltation in the following period. The rapid siltation might be the bound phenomenon only once in the newly excavated channel. If this be so, the rapid siltation does not occur in the case that the maintenance dredging is continuously conducted. This hypothesis must be verified with the data. However, there is no more suitable data for it at present. In the second stage of slow siltation, the speed of siltation is constant without depending on the water depth in the channel. Therefore, as for a trial, a tentative linear model is formulated by picking up only the convenient data, which are the data such as that lying on the dotted lines in Figure 4.30.

Figure 4.30 Time variations of channel depth for Inner and Outer channels

In Figure 4.31, the mean siltation speed at each reference line is plotted. The mean siltation speed for Inner channel is 0.39 m/month in average, and that for Outer channel is 0.14 m/month.

dh  .0 39 (Inner channel) v   (4.4) dt  .0 14 (Outer channel)

By integrating Eq.( 4.5), the water depth in the channel is obtained as the linear expression of the elapsed time,

(4.5) where h is the depth in the channel, h0 is the initial channel depth, t is the elapsed time after

4-24 dredging (unit in months), and v is the siltation speed of 0.14 m/month for Outer channel and 0.39 m/month for Inner channel. Equation (4.5) represents that the depth changes linearly with time, and hereinafter we call it ‘Linear Model’.

Figure 4.31 Representative siltation speed for Inner and Outer channel

Since the Linear Model does not take into account the phenomenon of rapid siltation, it predicts the slower siltation speed than that predicted by the Modified Exponential Model when the water difference between inside and outside the channel is large. Meanwhile, however, when the water difference is small, it predicts the faster speed than those of measured one. Furthermore, after a time elapses, it yields the conflicting situation that the water depth inside the channel becomes shallower than that of outside. In order to avoid this discrepancy and to increase the conformity with the data, the Linear Model has been connected to the Modified Exponential Model in the area where the depth difference is small. Specifically, a continuity of both models is secured by the siltation speed as shown by solid lines in Figure 4.32.

Figure 4.32 Connection of Linear Model to Modified Exponential Model

4-25

4.4.3 Applicability of two models The modified Exponential Model can be adopted for predicting the change of water depth after the re-dredging and in the maintenance dredging.

There is a possibility that the Linear Model could be applied to predict the siltation volume when the dredging is being conducted continuously. It is very important, however, to stress that the Linear Model is formulated as for a trial. There is still a big hypothesis that the rapid siltation just after the dredging might be the bound phenomenon only once in the newly excavated channel. Then, we must refrain from the use of the Linear Model until the hypothesis is verified with the bathymetric data, or the applicability of Linear Model is confirmed with the data.

4.5 Siltation Prediction model for Harbor Basin and Port Channel

Siltation also occurs in the harbor basin including the channel portion (hereinafter referred to as “the port channel”) which is defined as the section between x=0 to 1200 with the width of x=140 m in Figure 4.33.

Figure 4.34 shows superposition of the cross sections along the reference line x=200 m which is perpendicular to the wharf. Figure 4.35 shows the bottom profiles along the reference line Y=-400m which is parallel to the wharf. The bathymetric survey data available are those measured in December 2008, February 2011, August 2011 and January 2012. As seen in these figures, the water depth in the harbor basin and the port channel was deeper than 15 m after dredging in December 2008. The first bathymetric survey was conducted in February 2011 since December 2008, which was 26 months after dredging. During about one year from February 2011 to January 2012, the bathymetric surveys were repeated three times. The three bottom profiles obtained from these surveys almost overlap each other, which means that the water depth has already reached an equilibrium condition and the siltation does not occur any more. The equilibrium water depth, or final depth, in the harbor basin is deeper than that of the bank outside the basin.

Only along the reference line L22, of which location is shown in Figure 4.33, the bathymetric data obtained in June 2009 is available, which are shown in Figure 4.36. The volume of siltation was already about half of final volume after 6 months of dredging. The siltation speed was likely fast just after the dredging also in the harbor basin.

4-26

Figure 4.33 Coordinate system in harbor basin KP 0.200 (200kHz) Distance(m) ‐700 ‐600 ‐500 ‐400 ‐300 ‐200 ‐100 0 100 200 300 6.0 7.0 2012_01 8.0 2011_08 9.0 2011_02

(m) 10.0 11.0 2008_12 12.0

Depth 13.0 14.0 15.0 16.0 Figure 4.34 Cross sections along the line of x=200m, perpendicular to the wharf

4-27 Y = ‐ 400 (200kHz) Distance(m)

7.0 8.0 2012_01 9.0 10.0 2011_08 (m) 11.0 2011_02 12.0 2008_12

Depth 13.0 14.0 15.0 16.0

Figure 4.35 Bottom profiles along the line of Y=-400m, parallel to the wharf

Distance(m) ‐500 ‐400 ‐300 ‐200 ‐100 0 100 200 6.0 7.0 8.0 9.0

(m) 10.0 11.0 2012_01 12.0 2011_08

Depth 13.0 2011_02 14.0 2009_06 15.0 2008_12 16.0 PLAN

Figure 4.36 Cross sections along the line of L22, perpendicular to wharf

Unfortunately since there is no more available bathymetric data, we cannot go farer in our understanding of this process. Then, the prediction model of exponential type, Eq. (4.6), for the Outer channel, in which the concept of the final depth is considered, is applied to the harbor basin.

e  0e  tahhh ]exp[ (4.6)

where he is the final depth difference between inside and outside the port channel and harbor basin. The final depth he is determined at a location to a location based on the obtained bathymetric data, and is given as listed in Table 4.2 Parameters of the final depth difference in Port channel and Harbor basin.

Table 4.2 Parameters of the final depth difference in Port channel and Harbor basin x1200 x1000 L22 x800 x600 x400 x200 Location KP1.2 KP1.0 KP0.9 KP0.8 KP0.6 KP0.4 KP0.2 Port channel 1.70 1.88 1.88 2.17 2.53 2.75 1.94 Harbor basin -- 2.35 2.35 2.79 3.29 3.78 4.15

4-28 Figure 4.37 shows comparison between the predicted and the measured relative siltation height for the port channel and the harbor basin. In Figure 4.37, the prediction is conducted by Eq. (4.6) with he listed in Table 5.2 and a = 0.109. It is found that Eq. (4.6) well reproduces the observed depth change in the port channel and the harbor basin where the siltation height changes from location to location.

1.00

0.90 0

h 0.80 KP  1.20 h/

 0.70 ‐

1 1.00

0.60 0.91 (L22) 0.80 Height, 0.50 0.60 0.40 0.40 Siltation 0.20 0.30 Pred. Port Ch. (Kp=1.0) 0.20

Relative Pred. Port Ch. (Kp=0.4) 0.10 Pred. Port Ch. (Kp=0.2)

0.00 0 1020304050 Elapsed Time, t (month)

(a) In the port channel

1.00

0.90 0

h KP 0.80 1.20 h/  

‐ 0.70

1 1.00

0.60 0.91(L22) 0.80 Height, 0.50 0.60 0.40 0.40 Siltation 0.30 0.20 Pred. Port Ch. (Kp=1.2) 0.20

Relative Pred. Port Ch. (Kp=1.0) 0.10 Pred. Port Ch. (Kp=0.2) 0.00 0 1020304050 Elapsed Time, t (month)

(b) In the harbor basin Figure 4.37 Comparisons between the predicted and the measured relative siltation height

4-29

Chapter 5 Estimation of Dredging Volume and Cost

5.1 Re-Dredging volume

Maintenance dredging will be conducted so that the harbor and channel depth will be maintained for the required depth until the next cycle of dredging. In the case of La Union port, the harbor basin and channel have been already filled with a large amount of mud and must be re-dredged at first before the start of maintenance dredging. It is hereby called the re-dredging. The re-dredging volume is estimated based on the water depth from the latest bathymetric survey results at July 2013. Figure 5.1 shows the longitudinal depth variation along the centerline of the access channel as surveyed in the end of July 2013.

Inner Channel Outer Channel

Line No. 22 21 20 19 18 17 16 15 14 13 12 11 10 9 8 7 65 4 3 2 1 6.0

7.0 Jul‐2013 8.0

9.0

10.0 (m)

11.0

12.0 Depth 13.0

14.0

15.0

16.0 0 1 2 3 4 5 6 7 8 9 1011121314151617181920212223 Distance KP(km)

Figure 5.1 Longitudinal profile on the centerline of the access channel surveyed at July 2013

The harbor basin, Inner channel, and Outer channel need to be re-dredged before any maintenance dredging begins. The total volumes of the re-dredging for six target navigation depths of D.L.-9 to D.L.-14 m varying by 1 m has approximately estimated as listed in Table 5.1. The re-dredging volume is calculated taking the channel shape as shown in Figure 5.2 into account.

The re-dredging volume depends on the channel depth at the start of the re-dredging. In the present report, the re-dredging volumes are calculated based on the latest survey result at July 2013.

It is noted that the re-dredging volume shown in Table 5.1 does not include over-dredging volume. Actually, in the period when the re-dredging is conducted, siltation also happens at the same time. Therefore, in addition to the re-dredging volume, maintenance dredging volume must be added to calculate the total dredging volume (=re-dredging volume + maintenance dredging volume). The maintenance dredging volume will be described in the next Section.

5-1

B=140m

DL-10.0 DL-11.0 1:5 DL-12.0 DL-13.0 DL-14.0

Figure 5.2 Channel Shape for re-dredging volume calculation

Table 5.1 Estimated re-dredging volume (units: 1000 m3) Depth (m) Outer Ch. Inner Ch. Basin Total D.L.-9.0 0 895 0 895 D.L.-10.0 25 1,535 59 1,619 D.L.-11.0 404 2,215 344 2,964 D.L.-12.0 1,161 2,936 798 4,895 D.L.-13.0 2,284 3,696 1,471 7,452 D.L.-14.0 3,882 4,496 2,186 10,565

Table 5.2 Estimated TDS (Tons Dry Solid) of re-dredging (units: 1000 t) Depth (m) Outer Ch. Inner Ch. Basin Total D.L.-9.0 0 401 0 401 D.L.-10.0 11 688 26 726 D.L.-11.0 181 993 154 1,329 D.L.-12.0 521 1,317 358 2,195 D.L.-13.0 1,024 1,658 660 3,342 D.L.-14.0 1,741 2,016 980 4,738

The dredging volume in Table 5.1can be converted to TDS (Tons Dry Solid) by means of the following formula:

V   )025.1(65.2 TDS  s (5.1)  025.165.2 where V denotes the dredging volume and s refers to the in-situ density of mud. The quantity in TDS may be utilized when a re-dredging contract is made on the basis of the reported amount of TDS executed by dredgers. The result of conversion from V to TDS under an assumption of s = 1.300 g/cm3 is listed in Table 5.2 for example.

5-2 It is also noted that the re-dredging volume shown in Table 5.1 does not include overbreak. The overbreak is an extra portion of dredging to make the bed level lower than the plan shape because the channel shape cannot be dredged evenly as illustrated in Figure 5.3.

Figure 5.3 Definition of overbreak in channel dredging

5-3 5.2 Maintenance dredging volume

5.2.1 Navigable depth According to Figure 5.1, the shallowest location of Outer channel is around KP16.0 (L07) with the depth of 9.5 m, while in Inner channel the shallowest location is around KP4.50 (L18- L19) with the depth of 7.0 m. As discussed in Chapter 3, the channel bottom at KP2.90 is covered with a mud layer with the density less than the threshold of 1,200 kg/m3. The survey result shows that the fluid mud layer extends more than 1.0 m deep. It is too early to assess the thickness of the soft mud layer, but it may be tentatively set as 1.0 m. Under this assumption, the navigable depth can be regarded as the depth of 8.0 m at the present situation.

Figure 5.4 shows the definition of navigable depth. In this study, the navigable depth is the depth with fluid mud layer, the density of which is less than 1200 kg/m3. In the estimation of dredging volume introduce in the next Section, the fluid mud thickness is set as 1.0m for Inner channel and 0.5m for Outer channel and harbor basin, which are based on the result of Chapter 3. However, if no dredging will be undertaken, the fluid mud in the channel will consolidate and the thickness of fluid mud layer will be small. Frequent maintenance dredging is also needed to keep the fluid mud layer navigable.

; tide level

Chart Datum Level (C.D.L.)

Navigable Depth Depth measured by echo sounder (200kHz)

Fluid mud layer (density < 1,200 kg/m3)

Figure 5.4 Definition of the navigable depth and the measured depth

5.2.2 Estimation method of maintenance dredging volume After the re-dredging works are completed to the designated target depth, siltation process will take place. In this report, the siltation speed was analyzed and two prediction models were developed based on the previous bathymetric survey results as described in Chapter 4. Hereinafter, two prediction models of the modified Exponential Model and the Linear Model are applied to estimate maintenance dredging volume.

Table 5.3 Siltation prediction models to estimate maintenance dredging volume Prediction Model Remarks V=ah 1. Modified Exponential Model  a=0.089 (Inner ch.)  a=0.109 (Outer ch.) with final depth (he)

V= min(ah, Vmax) 2. Linear Model  Vmax = 0.39 m/month (Inner ch.)  Vmax = 0.14 m/month (Outer ch.)

5-4 The dredging volume must be proportional to the siltation depth during the maintenance dredging cycle time. When the depth difference between the target channel depth and the outside depth is denoted by htar and the maintenance dredging is carried out with the cycle time of T months, the required dredging depth of DX, which includes over-dredging, is calculated as,

1) Modified Exponential Model

X  tar expaThD  for Inner channel (5.2)

eX  etar expaThhhD  for Outer channel, Port Channel and Basin (5.3)

2) Linear Model

X  linearTvD (5.4) where a is assigned the value of 0.089 for Inner channel, and 0.109 for Outer channel, port channel, and basin, he is the depth difference between the final depth and the outside depth (=

hh oute ), and vlinear is the constant siltation speed of the Linear Model and is assigned 0.39 m/month for Inner channel or 0.14 m/month for Outer channel.

To illustrate the use of Eq. (5.2), the location of L20 (KP2.9) with the assumed outside depth of DL-6.9 m is taken. If the target navigation depth is DL-11.0 m, the depth difference is actually htar = 4.1 m. Here, if the soft mud layer of 1.0m is taken into account, the depth difference is assumed as htar = 3.1 m. For the dredging cycle time of T = 6 months for example, the initial depth difference of DX = 5.3 m must be secured and therefore the initial target dredging depth is DL-12.2 m. Within the maintenance cycle time of 6 months, the channel bottom will gradually rise and finally reach DL-10.0 m, where the navigable depth is DL-11.0m. After 6 months, the channel will be re-dredged to DL-12.2 m again. The process of dredging and rise of channel bottom is illustrated in Figure 5.5.

‐6

‐7 hout = Outside depth

(m) ‐8 Dredging bottom h Outside bottom htar DX ‐9 Maintenance-Dredg. Navigable fluid mud layer depth, ‐10 (1.0m for Inner, 0.5m for Outer) Depth to be maintained ‐11 (Target Navigation Depth)

Bottom ‐12 Dredging Depth Navigable bottom (include over dredging) ‐13 036912 Elapsed time, t (month)

Figure 5.5 Sketch of rise of channel bottom between maintenance dredging.

5-5 5.2.3 Maintenance dredging volume by depths The maintenance dredging volume is calculated for six levels of the target depth: i.e., DL-9.0 m, DL-10.0 m, DL-11.0 m, DL-12.0 m, DL-13.0 m, and DL-14.0 m. The cycle time of successive maintenance dredging, is set at 3, 4, 6, or 12 months. The volume of maintenance dredging at a specified cycle time and a navigation depth is estimated by the two prediction models: the modified Exponential Model and the Linear Model. The results of calculation are shown in Table 5.4 and Table 5.5. In the calculation, the fluid mud thickness with the wet density less than 1,200 kg/m3 is taken into account. The thickness is assumed 1.0 m for Inner channel and 0.5 m for Outer channel and basin, as the allowance of sedimentation.

Figure 5.6 and Figure 5.7 show the annual dredging volumes for each target depth with respect to the cycle time. The annual dredging volumes are plotted on a fixed vertical scale in Figure 5.6, and they are plotted on different vertical scales in Figure 5.7. From these diagrams, it is confirmed that the annual dredging volume increases with the target depth. Also, the maintenance dredging volume estimated by the modified Exponential model tends to increase with increasing of the cycle time. The maintenance dredging volume estimated by the Linear model has almost the same value as that estimated by the modified Exponential model in cases of the targets depth of DL-9m, DL-10m, DL-11m, and DL-12m. In cases of DL-13m, and DL-14m, the maintenance dredging volume by the Linear model is smaller than that estimated by the modified Exponential model.

Figure 5.8 shows all calculation results of annual dredging volume with respect to the target depth. The volumes estimated by the modified Exponential Model are represented by blue symbols and those by the Linear Model are represented by orange symbols. The blue curve on the diagram is drawn to connect minimum values of each target depth estimated by the modified Exponential Model, and the orange curve is drawn in the same manner for the Linear Model.

By comparing the modified Exponential Model and the Linear Model, it is observed that the difference of calculated volume becomes larger in case the target depth is deeper than 13m. Because in the Linear model the constant siltation speed is applied when the channel depth is deeper than around 12m, a difference between the modified Exponential model and the Linear model appears in case when the target depth is deeper than 12 m.

5-6

Table 5.4 Maintenance dredging volume by the modified Exponential Model 3 3 Dredging Volume by areas (10 m /cycle) Total Total Target Navi. Cycle time 3 3 3 3 Depth (m) (month) Outer Inner Basin (10 m /cycle) (10 m /year) 3.00 0 54 0 54 215 4.00 0 75 0 75 224 9.00 6.00 0 123 0 123 245 12.00 0 323 0 323 323 3.00 0 193 0 193 770 4.00 0 267 0 267 802 10.00 6.00 0 435 0 435 871 12.00 0 1,107 0 1,107 1,107 3.00 5 358 3 365 1,461 4.00 7 495 4 505 1,516 11.00 6.00 11 798 6 815 1,631 12.00 33 1,937 19 1,988 1,988 3.00 164 519 53 736 2,944 4.00 230 715 74 1,020 3,060 12.00 6.00 384 1,140 125 1,650 3,300 12.00 1,057 2,401 355 3,813 3,813 3.00 438 677 182 1,297 5,188 4.00 613 928 256 1,797 5,390 13.00 6.00 1,011 1,463 428 2,902 5,804 12.00 2,620 2,532 1,190 6,342 6,342 3.00 818 831 419 2,068 8,272 4.00 1,139 1,133 589 2,861 8,584 14.00 6.00 1,857 1,766 982 4,605 9,210 12.00 3,904 2,846 2,691 9,442 9,442

5-7 -

Table 5.5 Maintenance dredging volume calculated by the Linear Model 3 3 Dredging Volume by areas (10 m /cycle) Total Total Target Navi. Cycle time 3 3 3 3 Depth (m) (month) Outer Inner Basin (10 m /cycle) (10 m /year) 3.00 0 54 0 54 215 4.00 0 75 0 75 224 9.00 6.00 0 123 0 123 245 12.00 0 323 0 323 323 3.00 0 193 0 193 770 4.00 0 267 0 267 802 10.00 6.00 0 435 0 435 871 12.00 0 1,103 0 1,103 1,103 3.00 5 358 3 365 1,461 4.00 7 495 4 505 1,516 11.00 6.00 11 797 6 815 1,630 12.00 33 1,776 19 1,827 1,827 3.00 161 516 53 729 2,918 4.00 220 699 74 994 2,981 12.00 6.00 346 1,071 125 1,542 3,083 12.00 752 2,078 355 3,186 3,186 3.00 296 610 182 1,088 4,352 4.00 397 807 256 1,460 4,379 13.00 6.00 597 1,185 428 2,209 4,418 12.00 1,203 2,170 1,190 4,563 4,563 3.00 422 628 419 1,469 5,875 4.00 562 825 589 1,976 5,928 14.00 6.00 842 1,201 982 3,025 6,050 12.00 1,675 2,183 2,691 6,548 6,548

5-8

1. Mod Exp. model

2. Linear model

10,000

) 10,000 ) 3 3 m

9,000 m 9,000 3 -9m 3 -10m 8,000 8,000 7,000 7,000 6,000 6,000 5,000 5,000 mod I & O 4,000 4,000 Linear 3,000 3,000 2,000 2,000 1,000 1,000 Annual Dredging Volume (x10 Volume Dredging Annual

0 (x10 Volume Dredging Annual 0 036912 036912 CycleDredging of Dredging Cycle (month) (month) CycleDredging of Dredging Cycle (month) (month)

10,000 10,000 ) ) 3 3 m 9,000 m 9,000 3 -11m 3 -12m 8,000 8,000 7,000 7,000 6,000 6,000 5,000 5,000 mod I & O 4,000 4,000 Linear 3,000 3,000 2,000 2,000 1,000 1,000 Annual Dredging Volume (x10 Volume Dredging Annual 0 (x10 Volume Dredging Annual 0 036912 036912 CycleDredging of Dredging Cycle (month) (month) CycleDredging of Dredging Cycle (month) (month)

10,000 ) 10,000 ) 3 3

m 9,000 m 3 9,000

-13m 3 8,000 8,000 7,000 7,000 6,000 6,000 5,000 5,000 mod I & O 4,000 4,000 Linear -14m 3,000 3,000 2,000 2,000 1,000 1,000

Annual Dredging Volume (x10 Volume Dredging Annual 0

Annual Dredging Volume (x10 Volume Dredging Annual 0 036912 036912 CycleDredging of Dredging Cycle (month) (month) CycleDredging of Dredging Cycle (month)(month)

Figure 5.6 Maintenance dredging volume (plotted by a fixed vertical scale)

5-9 1. Mod Exp. model

2. Linear model

350 1,200 ) ) 3 3 m m 3 300 3 1,000 -10m 250 800 200 600 mod I & O 150 -9m Linear400 100

50 200 Annual Dredging Volume (x10 Volume Dredging Annual 0 (x10 Volume Dredging Annual 0 036912 036912 CycleDredging of Dredging Cycle (month) (month) CycleDredging of Dredging Cycle (month) (month)

2,500 )

3 4,500 ) 3 m 3 m

3 4,000 2,000 -11m 3,500

1,500 3,000 2,500 mod I & O 1,000 2,000 -12m Linear 1,500 500 1,000 500

Annual Dredging Volume (x10 Volume Dredging Annual 0

Annual Dredging Volume (x10 Volume Dredging Annual 0 036912 036912 Cycle of Dredging (month) Dredging Cycle (month) DredgingCycle of Dredging Cycle (month) (month)

7,000 10,000 ) ) 3 3 m m 9,000 3 6,000 3 8,000 5,000 7,000

4,000 6,000 5,000 3,000 mod I & O 4,000 -13m Linear 2,000 3,000 -14m 2,000 1,000 1,000 Annual Dredging Volume (x10 Volume Dredging Annual 0 (x10 Volume Dredging Annual 0 036912 036912 DredgingCycle of Dredging Cycle (month) (month) CycleDredging of Dredging Cycle (month) (month)

Figure 5.7 Maintenance dredging volume (plotted on different vertical scales)

5-10 10,000

9,000 Cycle time (month) ◆：３ ■：４ ▲：６ ●：12 Mod. Exp. M. 8,000 /year)

3 7,000 m 6,000

5,000

4,000 Linear M. (thousand

3,000

2,000 Volume 1,000

0 8 9 10 11 12 13 14 15 Depth (m)

Figure 5.8 Maintenance dredging volume by Depths

5-11 5.2.4 Maintenance dredging volume and over dredging depth by segments For estimating dredging cost accurately, the maintenance volume by segments is needed. In this study, 12 segments with 1 km interval are set for Outer channel, 4 segments with 1 km interval for Inner channel, and 13 segments with 0.2 km interval for Port Channel and Basin area. The segments are set corresponding to each reference Line number.

The calculation results of dredging height and dredging volume by segments are summarized as shown in Table 5.6. In Table 5.6, the results calculated by modified Exponential model are listed for the target depth of 14 m, for example. All calculation results for target depth of 9, 10, 11, 12, 13, and 14 m are listed in Annex C.

The dredging height in Table 5.6 is the height needed to be dredged by the next cycle of dredging and it is included the fluid mud layer thickness defined as 1.0m for Inner channel or 0.5 m for Outer channel and Basin. The over dredging height below the target depth is also listed in this table. The definition of the height of dredging and the over dredging height below the target depth is illustrated in Figure 5.9. The over dredging height is calculated by subtraction from the dredging height to the fluid mud thickness.

Figure 5.10 and Figure 5.11 show over dredging depth estimated by modified Exponential model and Linear model, respectively. The over dredging depth is calculated by the sum of the target depth and the over dredging height below the target depth. From the figures, it is confirmed that the shorter the cycle time of dredging is, the shallower the over dredging depth.

‐6 ‐7 Outside depth

(m) ‐8 Dredging bottom h Outside bottom Navigable fluid mud layer ‐9 (1.0m for Inner, 0.5m for Outer) Maintenance-Dredg.

depth, ‐10 Height of Dredging

‐11 Target depth

Bottom ‐12 Navigable bottom ‐13 Over dredging height below 036912the target depth Elapsed time, t (month)

Figure 5.9 Definition of height of dredging and over dredging height below the target depth

5-12 ‐5 ‐5

‐10 ‐10 3 month 3 month (m) (m) ‐15 ‐154 month 4 month 6 month 6 month Depth Depth

‐20 -9m ‐2012 month -10m 12 month

Water Water h_maintain h_maintain ‐25 ‐25hout hout h_FM h_FM ‐30 ‐30 0246810121416182022 0246810121416182022 Distance along centerline of the channel (km) Distance along centerline of the channel (km)

‐5 ‐5

‐10 ‐10 3 month 3 month (m) (m)

‐15 ‐154 month 4 month 6 month 6 month Depth Depth

‐20 -11m ‐2012 month -12m 12 month Water Water h_maintain h_maintain ‐25 ‐25hout hout h_FM h_FM ‐30 ‐30 0 2 4 6 8 10121416182022 0246810121416182022 Distance along centerline of the channel (km) Distance along centerline of the channel (km)

‐5 ‐5

‐10 ‐10 3 month 3 month (m) (m)

‐15 ‐154 month 4 month 6 month 6 month Depth Depth

‐20 ‐2012 month 12 month Water Water h_maintain h_maintain -13m ‐25 ‐25 hout -14m hout h_FM ｈ_FM ‐30 ‐30 0 2 4 6 8 10121416182022 0246810121416182022 Distance along centerline of the channel (km) Distance along centerline of the channel (km)

Figure 5.10 Over dredging depths estimated by Mod. Exp. Model

5-13 ‐5 ‐5

‐10 ‐10 3 month 3 month (m) (m) ‐15 ‐154 month 4 month 6 month 6 month Depth Depth

‐20 -9m ‐2012 month -10m 12 month

Water Water h_maintain h_maintain ‐25 ‐25hout hout h_FM h_FM ‐30 ‐30 0246810121416182022 0 2 4 6 8 10 12 14 16 18 20 22 Distance along centerline of the channel (km) Distance along centerline of the channel (km)

‐5 ‐5

‐10 ‐10 3 month 3 month (m) (m)

‐15 ‐154 month 4 month 6 month 6 month Depth Depth

‐20 -11m ‐2012 month -12m 12 month Water Water h_maintain h_maintain ‐25 ‐25hout hout h_FM h_FM ‐30 ‐30 0 2 4 6 8 10121416182022 0 2 4 6 8 10 12 14 16 18 20 22 Distance along centerline of the channel (km) Distance along centerline of the channel (km)

‐5 ‐5

‐10 ‐10 3 month 3 month (m) (m)

‐15 ‐154 month 4 month 6 month 6 month Depth Depth

‐20 ‐2012 month 12 month Water Water h_maintain -13m h_maintain ‐25 ‐25hout -14m hout h_FM h_FM ‐30 ‐30 0 2 4 6 8 10121416182022 0 2 4 6 8 10 12 14 16 18 20 22 Distance along centerline of the channel (km) Distance along centerline of the channel (km)

Figure 5.11 Over dredging depths estimated by Linear Model

It is noted that the over dredging depth does not correspond directly to the annual volume of maintenance dredging. For example, in the case that the cycle time is 3 months, the dredging has to be repeated 4 times in a year. Then, the annual volume of maintenance dredging is a product of over dredging depth and repeat count as conceptually shown in Figure 5.12. Even if the over dredging depth becomes shallower with decreasing of cycle time, the annual volume of dredging does not decrease so much. However, since the slight decrease of annual volume with decreasing of cycle time, selecting the shorter cycle time of dredging is considered favorable.

5-14

Figure 5.12 Correspondence between over dredging depth and annual dredging volume

5-15 Table 5.6 Height and Volume of maintenance dredging (over dredging) estimated by mod. Exp. Model for Target depth of 14 m

Mod.Exponential Model Height of Dredging (m) Target Depth = 14m (Over dredging height below the target depth, m) Dredging Volume (x103 m3/km/cycle) Location Dredging cycle Dredging cycle Line No. KP 3 month 4 month 6 month 12 month 3 month 4 month 6 month 12 month Outer Ch. L1 21.91 0.00 0.00 0.00 0.00 0 0 0 0 0.19 0.27 0.46 1.35 L2 20.91 (0.00) (0.00) (0.00) (0.85) 26 37 62 176 0.46 0.65 1.10 3.21 L3 19.91 (0.00) (0.15) (0.60) (2.71) 62 87 144 388 0.77 1.09 1.83 5.36 L4 18.91 (0.27) (0.59) (1.33) (4.86) 102 143 234 591 1.02 1.44 2.44 7.13 L5 17.91 (0.52) (0.99) (1.94) (6.63) 135 187 305 513 1.16 1.64 2.77 8.09 L6 16.91 (0.66) (1.14) (1.27) (7.59) 152 211 341 581 1.19 1.69 2.85 8.34 L7 15.91 (0.69) (1.19) (2.35) (7.84) 157 217 350 598 0.93 1.31 2.22 6.48 L8 14.91 (0.43) (0.81) (1.72) (5.98) 123 171 279 678 0.45 0.64 1.07 3.14 L9 13.91 (0.00) (0.14) (0.57) (2.64) 61 85 141 381 L10 12.91 0.00 0.00 0.00 0.00 0 0 0 0 L11 11.91 0.00 0.00 0.00 0.00 0 0 0 0 L12 10.91 0.00 0.00 0.00 0.00 0 0 0 0 Inner Ch. 1.45 2.02 3.34 9.04 L18 4.91 (0.45) (1.02) (2.34) (8.04) 192 228 225 186 1.74 2.43 4.00 10.83 L19 3.91 (0.74) (1.43) (3.00) (9.83) 263 310 306 254 1.71 2.39 3.94 10.67 L20 2.91 (0.71) (1.39) (2.94) (9.67) 412 480 474 399 1.40 1.95 3.22 8.72 L21 1.91 (0.40) (0.95) (2.22) (7.72) 657 783 772 635 Port Ch. & Basin 1.19 1.69 2.85 8.33 X1200（P) 1.20 (0.69) (1.19) (2.35) (7.83) 49 69 114 298 1.05 1.49 2.51 7.34 x1000(P) 1.00 (0.55) (0.99) (2.01) (6.84) 14 20 34 89 1.00 1.41 2.38 6.97 L22(P) 0.91 (0.50) (0.91) (1.88) (6.47) 14 19 32 85 0.91 1.28 2.16 6.33 x0800(P) 0.80 (0.41) (0.78) (1.66) (5.83) 25 35 58 157 0.86 1.22 2.06 6.03 x600(P) 0.60 (0.36) (0.72) (1.56) (5.53) 24 33 56 151 0.84 1.19 2.01 5.89 x0400(P) 0.40 (0.34) (0.69) (1.51) (5.39) 23 33 54 148 1.19 1.68 2.84 8.31 x0200(P) 0.20 (0.69) (1.18) (2.34) (7.81) 49 69 113 297 0.87 1.23 2.08 6.08 x1000(B) 1.00 (0.37) (0.73) (1.58) (5.58) 15 21 34 88 0.82 1.15 1.95 5.70 L22(B) 0.91 (0.32) (0.65) (1.45) (5.20) 19 26 44 117 0.67 0.94 1.59 4.65 x0800(B) 0.80 (0.17) (0.44) (1.09) (4.15) 40 56 93 257 0.57 0.80 1.36 3.97 x600(B) 0.60 (0.07) (0.30) (0.86) (3.47) 50 70 117 332 0.45 0.63 1.06 3.11 x0400(B) 0.40 (0.00) (0.13) (0.56) (2.61) 46 65 109 314 0.34 0.48 0.80 2.35 x0200(B) 0.20 (0.00) (0.00) (0.30) (1.85) 52 74 125 359 *) (P):Port Channel, (B):Basin

5-16 5.3 Examination of Dredging Methods and Dredger Capacity

5.3.1 Types of dredger This section presents an overview on several major types of dredgers. For more information on the types of dredger, please refer to C5 Types of dredger in ANNEX C.

(1) Non-Self-Propelling Cutter Suction Dredger (CSD) This is a method to suck up soil together with water by pump agitating sea bottom with powered cutter head mounted at the end of the ladder. Sucked soil with water is then hydraulically discharged through pipeline to the dumping area. Economical range for discharge distance is generally 2 to 3 km. This type of dredger is positioned by spuds, which are 2 sets of piles to be able to elevate and to insert into sea bottom, and by swing winch wires drawing through the end of the ladder connecting to anchors installed on sea bottom. The photo and the conceptual drawing of typical Cutter Suction Dredger are shown in Photo 5.1 and Figure 5.13.

Photo 5.1 Cutter Suction Dredger (Source: “IHC Beaver Cutter Suction Dredger” International Marine Consultancy)

Figure 5.13 Conceptual drawing of Cutter Suction Dredger (Source: “Dredging; A handbook for engineers” R N Bray et al., 1998)

5-17 (2) Self-Propelling Trailing Suction Hopper Dredger (TSHD) This is a method to suck up soil together with water by pump, sucking soil and water from drag head mounted at the end of the suction pipe. Sucked soil is loaded onto hopper mounted on the dredger. When the hopper becomes full of soil, the dredger is self-propelling to dumping site and dump the dredged material through the bottom door of the hopper. The photo and the conceptual drawing of a typical TSHD are shown in Photo 5.2 and Figure 5.14.

Photo 5.2 TSHD (Source: “TSHD Glenn Edwards 10,000 m3” The art of dredging.com)

Figure 5.14 Conceptual drawing of TSHD (Source: “Dredging; A handbook for engineers” R N Bray et al.,1998)

5-18 (3) Grab Hopper Dredger (GD) This is a method to dredge sea bottom by grab bucket operated by crane. Grabbed soil is loaded onto hopper mounted on the dredger. When the hopper becomes full of soil, the dredger is self-propelled to soil dumping area and dispose soil through the bottom door of the hopper. Besides grab hopper dredger, there is pontoon-type grab dredger, which does not have own hopper or self-propulsion system. Pontoon-type grab dredger loads dredged material into hoppers of soil transporting barges. These sketches and photos are shown in Photo 5.3, Photo 5.4 and Figure 5.15, Figure 5.16.

Photo 5.3 Grab Hopper Dredger (Source: “Hopper Dredger CRANE” Axeonalias, RC Groups.com)

Figure 5.15 Conceptual drawing of Grab Hopper Dredger (Source: “Dredging; A handbook for engineers” R N Bray et al.)

5-19

Photo 5.4 Grab Dredger (pontoon type) (Source: “The closing process of clamshell dredges in water-saturated sand” Dr. ir. S.A. Miedema et al.)

Figure 5.16 Photo and Conceptual drawing of Grab Dredger (pontoon type) (Source: “Dredging; A handbook for engineers” R N Bray et al.)

5-20 (4) Non-Self-Propelling Backhoe Dredger (BHD) This is a method to excavate soil by bucket operated by backhoe hydraulic arm. Main component is land-based backhoe. The dredged soil is normally loaded onto supported soil barges. Backhoe Dredger is normally equipped with 2 or 3 sets of spuds for positioning and for resisting the force of bucket excavation. The photo and the conceptual drawing of a typical Backhoe Dredger are shown in Photo 5.5 and Figure 5.17.

Photo 5.5 Backhoe Dredger (Source: “Mimar Sinan” Jan De Nul Group)

Figure 5.17 Conceptual drawing of Backhoe Dredger (Source: “Mimar Sinan” Jan De Nul Group)

5-21 5.3.2 Appropriate dredging method In the former Section, four major types of dredgers are presented. In this section, the comparison study of dredgers particularly for the conditions of La Union Port is summarized.

Selection of dredging method and dredger suitable for the particular dredging work should be performed considering the following points:

1) Material to be dredged 2) Access for dredging area 3) Water depth 4) Configuration of dredging area 5) Sea conditions 6) Other vessel traffic 7) Soil dumping site 8) Productivity 9) Cost efficiency

1) Material to be dredged In La Union Port, original soil of sea bottom of Inner Channel and Outer channel is clay, clayey silt, silty sand with N-value of 1 only. Then, for maintenance dredging, any types of dredger can be applied.

2) Access to dredging area Access to a dredging area in case of mobilization is important to select a dredger. The water depth in the access channel of La Union Port and that of around the channel is usually deeper than about 7m. The sea condition is generally calm. Therefore, there is no critical condition in an access to the dredging area.

3) Water depth In this project, the planed depth of channel is 14m, which is rather deep for the usual backhoe dredger. Therefore, the backhoe dredger is not very much suitable. Other dredging methods are applicable without limit for this project.

4) Configuration of dredging area Configuration of dredging area such as the length and width of channel sometimes becomes severe condition for TSHD, because the dredging method of TSHD is different from others. TSHD is a dredger to dredge while it is sailing forward, which requires a long length of channel. Both of Inner Channel and Outer Channel of La Union Port are long enough to be suitable to TSHD. TSHD needs a certain width of the area with enough depth at the end of dredging area for it to turn. The water depth in the area outside the channel is more than 7m, which is enough for turning of any normal TSHD.

The length and width of access channel to La Union Port is no critical condition for remaining dredgers.

5) Sea conditions

5-22 Wind conditions of the area of La Union are of calm for the whole a year therefore they are not critical. Waves in the Inner channel are weak enough for all types of dredger to be applied. However, Outer Channel is considered to be subject to wave and swell. Spuds and the spud holders should stand for the forces generated by wave or swell. Consequently, Cutter Suction Dredger and Backhoe Dredger with spud positioning system should not be recommended. Tidal current reaches 1.79 m/s at the maximum in La Union Port. The maximum operational limit against tidal current by Grab Hopper Dredger is 1.5 knot (0.77 m/s), the one by Cutter Suction Dredger and Backhoe Dredger is 2 knot (1.03 m/s) and the one of TSHD is 3 knot (1.54 m/s). TSHD is considered less affected by tidal current than the others.

6) Other vessel traffic For maintenance dredging, other vessels navigation in the dredging area cannot be ignored. The interruption rate against other vessels traffic is related to the positioning system of the dredgers. Grab dredgers use anchor wires which may interrupt the traffic of the other vessels nearby. Grab Hopper Dredger may have to loosen the anchor wires to make the depth safe enough for the draft of the vessel passing over and thus it needs to stop dredging operation at the time. The spud system does a little affect against vessel traffic. In case of the Cutter Suction Dredger, the discharge pipe lines if floated on surface, they may block the navigation channel. In order to avoid it, the discharge pipe lines should be placed on sea bottom and it needs more work effort. All dredgers in the above are usually fixed at the dredging site, which makes hard to be moved smoothly for the emergency. TSHD does little affect against the vessel traffic since it does not have anchors.

Therefore, TSHD is the best type of dredger among the four types described above.

7) Dumping site In this project, the soil dumping site locates offshore 15.0 to 36.0 km away from the dredging site. The normal soil disposal method for the Cutter Suction Dredger is to discharge dredged material from the end of pipeline to the dumping site. Although it may be possible to discharge dredged material to far using booster pumps, usually, the maximum discharge distance of Cutter Suction Dredger is around 2 or 3 km. Therefore, Cutter Suction Dredger becomes not suitable for this project.

8) Productivity In general, productivity is more depending on the size and capacity of individual dredger not depending on the types of dredger. Also productivity highly depends on the skill of operators and management and other factors other than equipment itself.

However, in the case of grab dredging, since the dredging work is not continuous, the productivity of grab dredging is considered worse. Particularly in La Union Port, tidal current reaches 1.79 m/sec and therefore, comparing the operational limit against maximum tidal current of dredgers described above, the productivity of Grab Hopper Dredger is the lowest and one of TSHD is the highest.

5-23 9) Cost efficiency Cost efficiency is related to the productivity and the mobilization cost. The mobilization cost for TSHD and Grab Hopper Dredger is less than non-propelled dredgers such as Cutter Suction Dredger and Backhoe Dredger. Both TSHD and Grab Hopper Dredger can be self-propelled therefore, the comparison of mobilization between TSHD and Grab Hopper Dredger is difficult. After all, cost efficiency becomes depending on the productivity. The cost efficiency of TSHD can be regarded as the best due to the best productivity.

The above considerations are listed in Table 5.7. According to Table 5.7, the Cutter Suction Dredger is rejected mainly due to the item of the sea conditions and dumping site, together with the items of interruption to other vessel traffic in channel. Also, the Backhoe Dredger is rejected mainly due to the items of sea conditions in channel, together with the items of water depth. And, the Grab Hopper Dredger is rejected mainly due to the items of interruption to other vessel traffic in channel and productivity, together with the items of Cost efficiency. Consequently, TSHD is selected as the dredger being applicable to La Union Port.

TSHD is especially superior in the appraisals of “Other vessel traffic”, “Productivity” and “Cost efficiency” in comparison with other dredgers as shown in Table 5.7.

Table 5.7 Applicability of dredging methods to La Union Port Appraisal item of NON-SELF- SELF- SELF- NON-SELF conditions for PROPELLING PROPELLING PROPELLING PROPELLING dredging CUTTER TRAILING GRAB BACKHOE SUCTION SUCTION HOPPER DREDGER DREDGER DREDGER DREDGER 1) Material to be Good Good Good Good dredged 2) Access to Good Good Good Good dredging area 3) Water depth Good Good Good NG 4) Configuration of dredging Good Good Good Good area 5) Sea conditions NG Better Good NG 6) Other vessel NG Best NG NG traffic 7) Dumping site NG Good Good Good 8) Productivity NG Best NG NG 9) Cost efficiency NG Best NG NG Possibility to apply overall Judgment Selected selection of dredging method Note: The words of “NG” stand for No Good

5-24 5.3.3 Required capacity of dredger Dredgers of small capacity cannot complete dredging within the target period, and dredgers of big capacity are uneconomical. Therefore, an economic dredger suitable for the dredging volume and the dredging period must be selected.

For example, in case of a 3 months dredging cycle and employing a dredger which capacity allows complete the dredging in one month, the working ratio will be only 33% (one month/three months); then, the waiting time for the dredger becomes longer than the working time. This waiting time would not be necessary if a dredger of smaller capacity requiring 3 months to complete the dredging is employed. While, the working ratio will be 133% (4 months/3 months) if the dredger capacity is small and 4 months are required to complete the dredging. Then, in this case the 3 months dredging cycle cannot be maintained.

That is, as the dredger capacity is smaller, the dredging period is longer. And, since the working ratio is given by the following equality

Working Ratio=(required dredging period by a dredger of certain capacity / dredging cycle)×100, the dredger capacity should be selected as big as possible within a range not exceeding 100% of the working ratio.

This statement is valid for the evaluation method of the working ratio and study on the dredger capacity in cases of re-dredging and maintenance dredging.

(1) Physical condition of dredging

Physical condition to determine dredger capacity is shown below.

1) Dredging Material: Silt and Clay 2) Soil loading efficiency in hopper: 60% 3) Distance from dredged site to dumping site: from 15 to 36 km (Refer to Figure 5.18) 4) Dredging and Turning time: 0.5 hr and 0.25 hr (total 0.75 hr) 5) Dumping and Turning time: 0.15 hr and 0.15 hr (total 0.3 hr) 6) Speed of Dredger (full load) : 10.2 kn 7) Speed of Dredger (light load): 10.8 kn

CEPA evaluates the loading efficiency with from 65% to 75%. However, according to the report of “Seiryuu Maru, in its improvement of the dredging efficiency with new trailing suction hopper dredger/oil recovery vessel, by MLIT Chubu Regional Development Bureau in Japan” the silt volume in hopper was 59.2%. Therefore, in this study is employed the loading efficiency of 60%.

The location of dumping site at the time of initial dredging of channel (year of 2007) was decided through the approval of Ministry of Environment, El Salvador. The direction was to use the same water area as the dumping site of spottily dredging from Ministry of Environment, El Salvador in this study. (refer to Figure 5.18)

It is regarded that the dredging time is 0.5 hr and the time for turning is 0.25 hr, 0.75 hr as total. The dumping time is 0.15 hr and the time for turning is 0.15 hr, 0.3 hr as total.

5-25 The dredger’s speed with full load to the dumping site is considered to be 10.2 kt, and 10.8 kt for that with light load.

Figure 5.18 Location of dumping site

(2) Working condition of dredging Working condition of dredging is shown below.

1) Annual working weeks: 44 weeks (220 days) 2) Annual inspection and the unworkable weeks: 8 weeks (Periodical inspection in dock :) (4 weeks) (Repair, replacement of consumable, usual maintenance and etc. :) (3 weeks) (Unworkable days due to bad weather :) (1 week) 3) Weekly working day 5 days 4) Daily actual working hour (work efficiency 0.8): 19.2 hrs Five (5) days as weekly working days is set based on commencing works in the morning of Monday and returning to the port in the morning of Saturday. Checking equipment and tools is made on Saturday and Sunday is set as holiday.

5-26

(3) Consideration on working ratio Considerable time is occupied to move the distance from dredging site to dumping site out of total time for dredging. The distance to dumping site is the nearest 15 km and the farthest 36 km since the channel length of La Union Port is about 22 km long. Therefore, the working ratio must be calculated in each section zoning the channel into short sections as the round-trip time to dumping site varies greatly depending on the dredging site. Here, the calculation was made on every 1 km section of channel.

Figure 5.19 shows particular example of time using that a dredger dredges, moves to offshore dumping site and returns to original dredging site. This example is as shown in Table 5.8

Table 5.8 Calculation example of working hours

Target channel water depth (for maintenance dredging) : 12 m Dredged Site: 1 km section at L19 lateral line Distance to dumping site: 33.5 km Target dredging volume(for maintenance dredging): 151,000 m3 (every 3 months) (Predicted value by modification exponential model) Dredging cycle: 3 months Hopper capacity: 5,000 m3（effective capacity 3,000 m3）

【Time for one dredging rotation】refer to Figure 5.19 Dredging work and turning 0.75 hr Outward to dumping site 1.77 hrs Dumping work and turning 0.30 hr Return from dumping site 1.67 hrs ______Total: 4.49 hrs

【Necessary time to perform target dredging volume】

Soil volume to be able to handle by a dredger when makes a round trip to dumping site ： 3,000 m3

Maintenance dredging volume for 1km section at L19：151,000 m3

Therefore, a dredger must make 50.3 round trips in order to dredge the volume of maintenance dredging. The total time becomes 225.8 hrs since necessary time for one round trip is 4.49 hrs.

【Working Ratio】 The above result is the necessary time to dredge 1km section of channel including L19 lateral line. The same calculation is made on other 1km sections where dredging are necessary and obtain their summation. This is the necessary time to perform maintenance dredging of total channel by a dredger equipping 5,000 m3 hopper capacity. Total time summation was 1,047 hours in this example.

While, as the working days in 3 months are 55 days (220 days/4) taking it from working condition, the actual working time becomes 55 days × 19.2 hrs. = 1,056 hours.

5-27 Therefore, in this case,

Working Ratio= (1047 hrs / 1056 hrs) × 100=99 %

Figure 5.19 Necessary time for dredging work

(4) Decision process of necessary dredging capacity Each target channel water depth is got decided the volume of maintenance dredging by re-dredging and dredging cycle in the sections of 5.1 and 5.2. In case of re-dredging, the case to dredge in one year is studied. In case of maintenance dredging, the study is made on each cycle cases of 3, 4, 6 and 12 months.

Calculation commences from the working ratio of 1,000 m3 dredger capacity for each case. In case that the calculated working ratio exceeds 100%, the working ratio will be re-calculated adding 500 m3 dredger capacity. The calculation will be repeatedly made on every other 500 m3 and regard the dredger capacity being firstly below 100% as “necessary dredger capacity” for that case.

(5) Necessary dredger capacity Table 5.9 shows necessary dredging volume for re-dredging and the working ratio by water depth under the condition of one year dredging period.

Table 5.9 Necessary dredger capacity for re-dredging (m3) Target water depth for maintenance dredging 9 m 10 m 11 m 12 m 13 m 14 m Dredger Capacity (m3) 2,000 3,000 5,500 8,500 15,000 18,000 Working Ratio (%) (80) (96) (93) (97) (82) (95)

Table 5.10 and Table 5.11 show necessary dredger capacity and the working ratio of each dredging cycle by water depth in cases of applying the modified Exponential Model and the Linear Model.

5-28 Table 5.10 Necessary dredger capacity for maintenance dredging (m3), in the case of modified Exponential Model Maintenance water depth Dredging 9 m 10 m 11 m 12 m 13 m 14 m cycle 1,000 1,500 3,000 5,000 8,500 15,000 3 months (39) (92) (87) (99) (99) (88) 1,000 1,500 3,000 5,500 9,500 15,000 4 months Dredger (40) (96) (90) (94) (92) (91) Capacity 3 1,000 2,000 3,000 6,000 9,500 15,000 m 6 months (44) (78) (97) (92) (99) (98) 1,000 2,000 4,000 6,500 11,000 15,000 12 months (58) (99) (89) (97) (92) (100) Figures shown in parentheses are working ratio (%).

Table 5.11 Necessary dredger capacity for maintenance dredging (m3) in the case of Linear Model Maintenance water depth Dredging 9 m 10 m 11 m 12 m 13 m 14 m cycle

1,000 1,500 3,000 5,000 7,500 10,000 3 months (39) (92) (87) (98) (96) (98) 1,000 1,500 3,000 5,500 7,500 10,000 4 months Dredger (40) (96) (90) (91) (97) (99) Capacity 3 1,000 2,000 3,000 5,500 7,500 11,000 m 6 months (44) (78) (97) (94) (98) (92) 1,000 2,000 4,000 5,500 8,000 15,000 12 months (58) (99) (82) (97) (96) (74) Figures shown in parentheses are working ratio (%).

Figure 5.20 and Figure 5.21 are illustrated one of Table 5.10 and Table 5.11.

Necessary dredger capacity to maintain 9 to 11 m water depths is 1,000 to 4,000 m3 that is the same figure both in modified Exponential Model and Linear Model. But, there is slight difference between modified Exponential Model and Linear Model when the target water depth becomes deeper than 12 m. modified Exponential Model shows the necessary dredger capacity as 15,000 m3 at 14 m target water depth against 10,000 to 15,000 m3 in Linear Model.

5-29

Figure 5.20 Necessary dredger capacity for maintenance dredging (m3) in the case of modified Exponential Model

Figure 5.21 Necessary dredger capacity for maintenance dredging (m3) in the case of Linear Model

5.4 Cost Estimation of Dredging

Cost estimation of dredging is studied on two cases, one is the case that a dredging company dredges with the consignment (dredging by contract base) and the other one is the case that CEPA dredges directly owning a dredger by oneself. (dredging by own dredger). The cost by own dredger was estimated based on the concept that CEPA considers now.

Figure 5.22 and Figure 5.23 show the factors of cost estimation both dredging by contract base and by own dredger. The same colored items in these figures means that the same cost estimation is considered in both cases. While no colored (white color) items means that the considerations for the cost estimation differ from each other.

5-30 The structures of cost estimation in both cases is the total of direct and indirect costs in any event. The direct cost is composed of equipment cost, fuel cost and manpower cost. However, the breakdown items are slightly different between each other. The concepts of cost estimation and its content of indirect cost differs in the dredging by contract base and the dredging by own dredger except in the mobilization cost.

In what follows, the explanation is made collectively concerning the same concept of cost estimation and separately concerning the different concept of cost estimation between the dredging by contract base and the dredging by own dredger.

(1) (2) (3) (4) Direct C. ( Equipment C. ＋ Fuel C. ＋ Manpower C. )＋ Indirect C.

2) 1) 1) Operating Depreciation C. Japanese Temporary Time + Construction Work Cost Dredging C. 2) 1) Time Maintenance Mobilization & Repair C. Cost + Site Expense + Over Head

Total Cost

Figure 5.22 Cost estimation items of dredging by contract base

(1) (2) (3) (4) Direct C. ＋＋＋ ( Equipment C. Fuel C. Manpower C. ) Indirect C.

1) 2) 3) Operating Depreciation C. CEPA Insurance + Time Material Interest C. + + Dredging Contingency + Time 2) Maintenance + & Repair C. 1) Mobilization Cost

Total Cost

Figure 5.23 Cost estimation items of dredging by own dredger intended by CEPA

5-31 5.4.1 Consideration on cost estimation of dredging (1) Equipment cost (Direct cost) Equipment cost (direct cost) is composed of depreciation expense and maintenance and repair expense.

1) Depreciation expense The basic of depreciation expense common to dredging by contract base and dredging by own dredger is the dredger building price of TSHD (Trailer Suction Hopper Dredger). Firstly, it is described the dredger building price common to both.

Table 5.12 shows the building prices of new and used dredgers of ship builders studied by CEPA. Table 5.13 is the actual building price of TSHD in Japan.

Table 5.12 Building price of dredgers studied by CEPA No. Ship Builder Capacity Price (US$) New or Used IHC 1 2,400 m3 34,318,967 New MERWEDE 2 DAMEN 2,500 m3 25,639,000 New IHC 3 3,300 m3 26,620,967 Used (10 years) MERWEDE

Table 5.13 Building price of dredgers in Japan (Actual base) No. Ship Builder Capacity Price (US$) Year built Remarks 1 MHI 1,000 m3 20,600,000 2007 Newly built (Beira Port) Seiryu Maru ( Dredger with oil recovery and 2 MHI 1,700 m3 65,000,000 2005 disaster prevention functions) Hakusan Maru (Dredger 3 IHI 1,350 m3 55,000,000 2002 with oil recovery function) Kaisho Maru (Dredger 4 IHI 2,000 m3 63,000,000 2000 with oil recovery function) Kairyu Maru (equipping 5 IHI 750 m3 50,000,000 2011 with latest features)

In spite of smaller dredger capacity than the dredgers studied by CEPA, the actual Japanese building prices are comparatively expensive referring to Table 5.12 and Table 5.13. This is because that Seiryu Maru, Hakusan Maru, Kaisho Maru and Kairyu Maru are not only having dredging functions but also equipped the latest system such as fully automatically operated as well as equipping oil recovery and disaster prevention functions. Therefore, they should not be directly compared.

Checking "Dredging: A Handbook for Engineers" R N Bray, A D Bates & J M Land 1997 Arnold, UK as a separate information source, a present cost evaluation was made based on the building prices of TSHD.

Figure 5.24 shows the data input of building prices based on the Handbook and data from CEPA.

5-32 However, the data for used dredgers have excluded from the data of CEPA. Data of the Handbook and the one from CEPA are corresponded each other often. Thus, the estimation was made by an approximated straight line showing the building prices of dredgers in the figure. The result of estimation is shown in Table 5.14 as the building prices.

100,000 90,000 80,000 70,000 60,000 50,000

US$1,000 40,000 30,000 20,000 10,000 0 0 2,000 4,000 6,000 8,000 10,000 12,000 Hopper Capacity(m3)

Hand Book CEPA

Figure 5.24 Building price of TSHD by capacity

【Dredging by contract base】

Depreciation expenses are composed of a rental fee per one hour operation time and a rental fee per one day operation time in the dredging by contract base. These expenses can be calculated with the formula shown below based on the “Calculation Standard of Rental Fees of Ships and Machinery Equipment of Japan”.

Hourly Rental Fee=

Ship building 1/2×(Depreciation rate+Maintenance & repair cost ratio) 1 ×× cost Durable years Working hours in year

(5.5)

Daily Rental Fee=

Ship building 1/2×(Depreciation rate+Maintenance & repair cost ratio) 1 ×+Yearly administration cost × cost Durable years 365

(5.6) The following assumptions were made with these formulas.

5-33 Depreciation Rate: 0.9 Maintenance & Repair Rate: 1.3 Service Life: 20 years Annual operation time: 4,224 hrs. (working condition of dredging: 220 days × 19.2 hrs.) Annual administration fee: 0.06

Substitution of these values on Eqs. (5.5) and (5.6), we have

Hourly rental fee = dredger building price × (1.30208 × 10-5) (5.7) Daily rental fee=dredger building price × (3.15 × 0-4) (5.8) Hourly and daily rental fees by dredger capacity are shown in Table 5.14 .

Annual depreciation expense is estimated with equation shown below based on these rental fees.

Depreciation expense = (hourly rental fee) × (annual operation hours of dredger) + (daily rental fee) × (annual operation days of dredger) (5.9) For example, in the of Figure 5.19, the annual operation hours of dredger become 4,188 hours (1,047 hours × 4 times) and the annual operation days of dredger become 365 days.

Table 5.14 Equipment cost of TSHD by capacity Hopper Ship building Hourly Daily in-service capacity cost operating Depreciation (m3) (US$) cost (US$) cost(US$) 1,000 15,800,000 205.73 4,978.08 1,500 20,200,000 263.02 6,364.38 2,000 24,600,000 320.31 7,750.68 2,500 29,000,000 377.60 9,136.99 3,000 33,400,000 434.90 10,523.29 3,500 37,800,000 492.19 11,909.59 4,000 42,200,000 549.48 13,295.89 4,500 46,600,000 606.77 14,682.19 5,000 51,000,000 664.06 16,068.49 5,500 55,400,000 721.35 17,454.79 6,000 59,800,000 778.65 18,841.10 6,500 64,200,000 835.94 20,227.40 7,000 68,600,000 893.23 21,613.70 7,500 73,000,000 950.52 23,000.00 8,000 77,400,000 1,007.81 24,386.30 8,500 81,800,000 1,065.10 25,772.60 9,000 86,200,000 1,122.40 27,158.90 9,500 90,600,000 1,179.69 28,545.21 10,000 95,000,000 1,236.98 29,931.51 11,000 103,800,000 1,351.56 32,704.11 15,000 139,000,000 1,809.90 43,794.52

5-34 【Dredging by own dredger】 Depreciation expenses for the dredging by own dredger are based on the dredger building price (Table 5.14 ) and are calculated as the annual depreciation expense and the interest born by the loan amount for dredger building price.

Annual depreciation expense is set as 1/20 of dredger building price. Total sum of interest to depreciate in 20 years with the rate of 7% is set as the annual average interest with the average of 20 years.

2) Maintenance and repair cost Maintenance and repair cost is different from the dredging by contract base and dredging by own dredger. And the voyage cost for periodical inspection is counted separately on in-direct cost.

【Dredging by contract base 】 Depreciation expense of dredging by contract base already includes necessary cost for maintenance and repair such as maintenance and repair cost and annual management cost. (refer to Eq. (5.5) and Eq. (5.6). Therefore, it is not necessary to consider the maintenance and repair cost especially here.

【Dredging by own dredger】 The annual maintenance and repair cost accounts for 8 % of the dredger building price just like CEPA’s idea.

(2) Fuel cost Hourly fuel cost is calculated as

Hourly fuel cost = total engine power (kw) × fuel consumption rate (ℓ/kw/h ) × fuel unit price (US$/ ℓ) Total engine power of dredger is the total of pumping power and propulsion power. It is necessary to handle to separate pumping power and propulsion power and not total engine power in the calculation of fuel. Because, not only pump power but also propulsion power are necessary to consider at the dredging (dredging is made while moving) although it considers only propulsion power when making a round trip to dumping site. However, there is no data (information) to separate pump power and propulsion power, the following consideration was made here.

Figure 5.25 shows the relation of total engine power of TSHD and the capacity of TSHD now operated. Both relationship approximates with the straight line (R2=0.9215) and the total engine power was obtained corresponding to TSHD capacity. Figure 5.26 shows the relation between TSHD capacity and pump power. The pump power corresponding to TSHD capacity was obtained from this Figure.

Table 5.15 shows the total engine power, pump power and propulsion power by TSHD capacity. Of these figures, the propulsion power is obtained by subtracting pump power from total engine power.

5-35 Fuel consumption rate is set as 0.277 ℓ /kw/h (figure for grab hopper dredger in Japanese cost estimation standard).

Fuel unit price is set as US$0.99/ ℓ in April, 2013.

Fuel cost is estimated as shown below dividing dredging time and mobilization time.

Fuel cost at the time of dredging (hourly) = (pump power + propulsion power) (kw) × fuel consumption rate (ℓ /kw/h) × fuel unit price (US$/ ℓ) Fuel cost at the time of navigation (hourly) = propulsion power (kw) × fuel consumption rate (ℓ /kw/h) x fuel unit price (US$/ ℓ)

23,000 22,000 21,000 20,000 19,000 18,000 17,000

kw ） 16,000

（ 15,000 14,000 13,000 12,000 11,000 10,000 9,000 8,000 7,000 6,000 Total Engine Power Engine Total 5,000 4,000 3,000 2,000 1,000 0 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 10,000 11,000 12,000 TSHD Capacity

Figure 5.25 Relation with TSHD capacity and total engine power

Figure 5.26 Relation with TSHD capacity and pump power (Source: “Dredging : A Handbook for Engineers Second Edition” R N Bray, A D Bates & J M Land

5-36 1997 Arnold, UK)

Table 5.15 Breakdown of engine power by TSHD capacity (pump power and propulsion power) Hopper capacity (m3) Total installed power(kw) Dredging pump (kw) Propulsion power(kw) 1,000 2,100 500 1,600 1,500 2,800 700 2,100 2,000 3,400 700 2,700 2,500 4,100 1,000 3,100 3,000 4,800 1,100 3,700 3,500 5,500 1,300 4,200 4,000 6,100 1,500 4,600 4,500 6,800 1,700 5,100 5,000 7,500 1,900 5,600 5,500 8,100 2,200 5,900 6,000 8,800 2,500 6,300 6,500 9,500 2,800 6,700 7,000 10,200 3,100 7,100 7,500 10,800 3,400 7,400 8,000 11,500 3,700 7,800 8,500 12,200 4,000 8,200 9,000 12,900 4,400 8,500 9,500 13,500 4,800 8,700 10,000 14,200 5,100 9,100 11,000 15,500 5,600 9,900 15,000 20,900 7,000 13,900

(3) Manpower cost 1) Dredging by contract base Crew cost under dredging by contract base was calculated with the following assumption.

Three (3) different categories depending on dredger capacity are considered on the number of crew for the calculation of crew cost. The number of crew is set as 12 for small scale category targeting dredger capacity less than 5,000 m3. 21 crews are set for dredger capacity from 5,000 m3 and up to 10,000 m3 as middle scale category. And 34 crews are set for dredger capacity exceeding 10,000 m3 as large scale category.

The detail of above number of crew and the labor unit cost are shown in Table 5.16. Column of Officers is corresponded with high class crew such as captain, first officer, chief engineer, electric engineer, chief dredging operator and the Sailor means usual crew. “Labor unit cost for design works of public construction works of Japan (Cost Estimation Data)” is used as the reference for the crew cost shown in Table 5.16.

Table 5.16 Number of high class crew and common crew and labor unit cost (excluding fringe benefit and other expenses) Crew Rank Officers Sailor Total （Daily labor cost） (US$ 259) (US$ 202) Crew Small-scale category 5 7 12 Capacity：less than 5,000 m3 Middle-scale category 9 12 21 Capacity : 5,000 to 10,000 m3 Large-scale category 15 19 34 Capacity ：more than 10,000 m3

5-37

Crew cost per one year operation is calculated with Eq. (5.10).

Crew cost per one year operation = number of crew × one crew cost × 365days (5.10)

The annual crew cost of small-scale category is calculated using Eq.(5.10) with as follows,

Crew cost per one year operation (high class crew) = 5 persons × US$259 × 365 days= US$472,675 Crew cost per one year operation (common crew) =7 persons × US$202 × 365 days= US$516,110 Total: US$988,785 Table 5.17 shows calculated results of crew costs for other two categories.

Table 5.17 Annual crew cost by each category Crew rank Officers Sailor Annual crew cost (US$) (US$) （US$） Small-scale category Capacity ：less than 472,675 516,110 988,785 5,000 m3 Middle-scale category Capacity：5,000 to 850,815 884,760 1,735,575 10,000 m3 Large-scale category Capacity ：more than 1,418,025 1,400,870 2,818,895 10,000 m3

2) Dredging by own dredger In case of dredging by own dredger, the number of crew was separated also into 3 categories depending on dredger capacity. The category and the number of crew are set in the same manner with the case of dredging by contract base (Table 5.16).

Unit crew cost was decided based on the annual crew cost assuming it by CEPA for the dredging by own dredger. CEPA estimates US$622,440 as the annual crew cost (including fringe benefit and other expenses) when necessary number of sailor works by 7 sailors in 1 crew with 3 shifts.

It considers in case of the dredging by own dredger that the same number of crews with the dredging by contract base. For instance, as small-scale category sets 12 sailors in 1 shift as explained in the above, the annual crew cost is obtained with 12/7 times of CEPA’s annual crew cost. In turn, it becomes 21/7 times for middle-scale category and 34/7 times for large-scale category. This result is shown in Table 5.18.

Table 5.18 Crew cost in case of dredging by own dredger (CEPA’s unit cost including fringe benefit and other expenses) Crew rank Number Annual crew cost sailor in 1 (US$) crew Small-scale category 12 1,067,040 Capacity ：less than 5,000 m3 Middle-scale category 21 1,867,320 5-38 Capacity：5,000 to 10,000 m3 Large-scale category 34 3,023,280 Capacity：more than 10,000 m3 (4) Indirect cost 1) Mobilization cost Mobilization cost is consisted of mobilization cost to navigate to dredging site at first (initial mobilization cost) and the one to navigate for periodical inspection (mobilization cost for inspection).

The mobilization cost itself is the same with the dredging by contract base and the one by own dredger. The initial mobilization is regarded from Europe to La Union and the one way mobilization cost is shown by dredger capacity in the second column of Table 5.19.

The cost estimation of annual initial mobilization cost is the same for both cases but there is slight difference between two. In case of dredging by contract base, the contract for dredging works is assumed as 10 years and 1/10 of the initial mobilization cost is counted as the cost of every year (third column of Table 5.19).

While, in case of dredging by own dredger, the initial mobilization cost is counted every year as the depreciation expense in 20 years following to the depreciation period of dredger by CEPA (Fourth column of Table 5.19).

Table 5.19 Initial mobilization cost by dredger capacity and annual cost Annual cost of initial Annual cost of initial Initial Mobilization mobilization cost in mobilization cost in Dredger Capacity Cost (one way from 3 case of dredging by case of dredging by (m ) Europe) contract base own dredger (US$) (US$) (US$) 1,000 450,006 45,001 22,500 1,500 552,061 55,206 27,603 2,000 668,511 66,851 33,426 2,500 756,170 75,617 37,809 3,000 872,625 87,262 43,631 4,000 1,062,338 106,234 53,117 4,500 1,164,393 116,439 58,220 5,000 1,266,447 126,645 63,322 5,500 1,339,710 133,971 66,986 6,500 1,515,032 151,503 75,752 7,000 1,602,691 160,269 80,135 7,500 1,675,953 167,595 83,798 8,000 1,763,612 176,361 88,181 8,500 1,851,270 185,127 92,564 11,000 2,246,381 224,638 112,319 15,000 3,062,827 306,283 153,141

Periodical inspection is done once annually at Balboa city in Panama. The mobilization cost for inspection is calculated based on the navigation distance (round trip) and the days (Table 5.20). As the periodical inspection is done one time in a year, the total sum of the round trip for the

5-39 mobilization cost of the periodical inspection becomes the annual cost.

Table 5.20 Mobilization cost by dredger capacity for inspection (round trip from/to Balboa) 3 Dredging by contract base Dredging by own Dredger capacity (m ) (US$) dredger (US$) 1,000 115,630 104,582 1,500 144,788 130,889 2,000 178,060 161,310 2,500 203,105 183,504 3,000 236,378 213,924 4,000 290,582 262,426 4,500 319,740 288,733 5,000 363,221 315,041 5,500 384,153 333,122 6,500 434,245 377,510 7,000 459.290 399,704 7,500 480,223 417,785 8,000 505,268 439,980 8,500 530,313 462,174 11,000 663,978 560,806 15,000 897,248 771,264

2) Temporary expense, site expense and administration expense (dredging by contract base) These expenses were calculated as below based on the cost estimation standard of Japan.

And, the detail breakdown of temporary expenses, site expenses and administration expenses are shown in Table 5.25.

Temporary expenses are consisted of cost for mobilization, navigation, preparation and etc. and the lump sum of these are calculated with following Eq. (Mobilization was explained in the above 1). )

Temporary expense= Kr・Direct expenses + Mobilization Where, Kr=a･ (direct expenses + mobilization)b a=357.8, b=-0.2223 Site expenses are consisted of labor management expense, taxes and levies, insurance and etc. and the lump sum of these are calculated with following Eq.

Site expense=Jo・(direct expenses + temporary expenses) Where, Jo=a･ (direct expenses + temporary expenses) b A=57.6、b=-0.0687 Administration expenses are consisted of executive salaries, employee salaries, retirement allowance and etc. and the lump sum of these are calculated with following Eq.

Administration expense=Gp・(direct cost + temporary expenses + site expenses) Where, Gp=a × log+b (direct expenses + temporary expenses + site expenses) A=-2.57651、b=31.63531 5-40 Eventually, indirect expenses becomes as follow,

Indirect expenses=temporary expenses + site expenses + administration expenses

3) Insurance cost and contingency (dredging by own dredger) CEPA regards only insurance cost and contingency as the indirect cost. The insurance cost covers “All risks Insurance”. Contingency includes price variations of spare parts, fuels and etc. that may be possible however, at this moment it should be understood that these are uncertain and latent costs that cannot be quantified are contained.

CEPA estimates these annual expenses targeting 2,500 m3 dredger capacity as shown in Table 5.21.

Here, proportion of these expenses to dredger building price is calculated (last row of Table 5.21) and indirect expenses of dredgers by capacity is estimated multiplying this rate by dredger building prices.

Table 5.21 Insurance cost and contingency estimated by CEPA Building price of Dredger with Insurance cost Contingency （US$） capacity of 2,500 m3（US$）（US$）

25,700,000 300,000 375,000

1 1.167% 1.459%

5.4.2 Cost for re-dredging Re-dredging is commenced by contract base and the dredging by own dredger is not considered. Table 5.22 shows re-dredging volume and dredging cost by target depth under the contract base. These costs include one way initial mobilization cost from Europe and one round trip cost for periodical inspection.

Table 5.22 Dredging cost by target water depth Dredging Dredging Hopper Operating Operating cost by Depth Volume cost by capacity hour month contract (m) 3 contract base 3 (h) (m) (m ) base (m ) (US$) (US$/m3) 9 2,000 3,366 9.6 895,000 13.79 12,342,319 10 3,000 4,064 11.5 1,619,000 10.87 17,603,115 11 5,500 3,941 11.2 2,964,000 9.34 27,686,793 12 8,500 4,096 11.6 4,895,000 7.15 35,010,001 13 15,000 3,464 9.8 7,452,000 7.31 54,466,014 14 18,000 4,020 11.4 10,565,000 6.47 68,371,225

5.4.3 Cost for maintenance dredging The volume of maintenance dredging for the channel is predicted with modified Exponential Model and Linear Model. The result to estimate maintenance dredging cost for necessary volume to maintain channel predicted by each model is shown in Table 5.23 and Table 5.24 for the

5-41 dredger by contract base and by own dredger. Each table shows dredging cost by water depth and the dredging cycle. Least and owned dredging cost at each target depth are highlighted with yellow color.

Table 5.23 Dredging cost by modified Exponential Model

Dredging Hopper Working Dredging Cost by Dredging Cost by Dredging Cost by Dredging Cost by Target Navi. Total Cycle Capacity Ratio Contract base Contract base own Dredger own Dredger Depth (m) (103 m3/year) (mon) (m3) (%) (US$/m3) (US$/year) (US$/m3) (US$/year)

9.00 3.00 215 1,000 39 28.62 6,180,915 23.19 5,008,901 9.00 4.00 224 1,000 40 27.79 6,253,477 22.41 5,043,348 9.00 6.00 245 1,000 44 26.06 6,410,989 20.80 5,117,958 9.00 12.00 323 1,000 58 21.65 6,992,536 16.70 5,393,737 10.00 3.00 770 1,500 92 13.41 10,356,241 9.76 7,536,076 10.00 4.00 802 1,500 96 13.19 10,562,431 9.53 7,636,554 10.00 6.00 871 2,000 78 13.14 11,434,443 9.48 8,244,892 10.00 12.00 1,107 2,000 99 11.61 12,850,584 8.40 9,298,730 11.00 3.00 1,461 3,000 87 10.78 15,737,961 8.05 11,759,663 11.00 4.00 1,516 3,000 90 10.59 16,037,415 7.86 11,910,356 11.00 6.00 1,631 3,000 97 10.22 16,657,935 7.50 12,223,564 11.00 12.00 1,988 4,000 89 9.78 19,451,535 7.35 14,617,232 12.00 3.00 2,944 5,000 99 8.71 25,640,767 6.47 19,055,502 12.00 4.00 3,060 5,500 94 8.66 26,488,048 6.52 19,941,380 12.00 6.00 3,300 6,000 92 8.50 28,063,393 6.29 20,763,960 12.00 12.00 3,813 6,500 97 7.66 29,200,604 5.75 21,920,876 13.00 3.00 5,188 8,500 99 6.45 33,463,184 5.55 28,807,197 13.00 4.00 5,390 9,500 92 6.48 34,928,837 5.67 30,540,773 13.00 6.00 5,804 9,500 99 6.26 36,348,925 5.40 31,333,449 13.00 12.00 6,342 11,000 92 6.45 40,901,032 5.64 35,784,399 14.00 3.00 8,272 15,000 88 6.43 53,165,719 5.66 46,817,552 14.00 4.00 8,584 15,000 91 6.32 54,219,444 5.52 47,411,039 14.00 6.00 9,210 15,000 98 6.12 56,335,308 5.28 48,602,842 14.00 12.00 9,442 15,000 100 6.04 57,014,795 5.19 48,985,036

Table 5.24 Dredging cost by Linear Model

Dredging Hopper Dredging Cost by Dredging Cost by Dredging Cost by Dredging Cost by Target Navi. Total Working Cycle Capacity Contract base Contract base own Dredger own Dredger Depth (m) (103 m3/year) Ratio (%) (mon) (m3) (US$/m3) (US$/year) (US$/m3) (US$/year)

9.00 3.00 215 1,000 39 28.80 6,180,915 23.34 5,008,901 9.00 4.00 224 1,000 40 27.88 6,253,477 22.48 5,043,348 9.00 6.00 245 1,000 44 26.14 6,410,989 20.87 5,117,958 9.00 12.00 323 1,000 58 21.68 6,992,536 16.72 5,393,737 10.00 3.00 770 1,500 92 13.45 10,356,241 9.78 7,536,076 10.00 4.00 802 1,500 96 13.16 10,562,431 9.52 7,636,554 10.00 6.00 871 2,000 78 13.13 11,434,443 9.47 8,244,892 10.00 12.00 1,103 2,000 99 11.63 12,829,553 8.10 8,936,712 11.00 3.00 1,461 3,000 87 10.77 15,737,961 8.05 11,759,663 11.00 4.00 1,516 3,000 90 10.58 16,037,415 7.86 11,910,356 11.00 6.00 1,630 3,000 97 10.22 16,655,968 7.50 12,221,218 11.00 12.00 1,827 4,000 82 10.20 18,635,676 7.77 14,204,350 12.00 3.00 2,918 5,000 98 8.40 24,496,627 6.24 18,197,121 12.00 4.00 2,981 5,500 91 8.77 26,154,960 6.51 19,417,834 12.00 6.00 3,083 5,500 94 8.63 26,611,492 6.49 20,001,788 12.00 12.00 3,186 5,500 97 8.49 27,048,217 6.35 20,225,698 13.00 3.00 4,352 7,500 96 7.15 31,116,587 5.90 25,675,580 13.00 4.00 4,379 7,500 97 7.13 31,236,238 5.88 25,739,572 13.00 6.00 4,418 7,500 98 7.11 31,411,086 5.85 25,834,421 13.00 12.00 4,563 8,000 96 7.15 32,635,385 5.91 26,989,699 14.00 3.00 5,875 10,000 98 6.42 37,703,511 5.54 32,566,017 14.00 4.00 5,928 10,000 99 6.40 37,923,832 5.51 32,688,028 14.00 6.00 6,050 11,000 92 6.76 40,903,783 5.91 35,756,291 14.00 12.00 6,548 15,000 74 7.40 48,455,017 6.74 44,140,424 Figure 5.27 shows dredging cost of dredging by contract base in modified Exponential Model and Linear Model based on the values of Table 5.23 and Table 5.24. In the Figure 5.27, final dredging cost of each water depth is drawn by curve line. In the same manner, Figure 5.28 illustrates the dredging cost of dredging by own dredger.

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Figure 5.27 Dredging cost of dredging by contract base (Cost comparison between modified Exponential Model and Linear Model)

Figure 5.28 Dredging cost of dredging by own dredger (Cost comparison between modified Exponential Model and Linear Model)

5.4.4 Observations on re-dredging cost Over-dredging foreseeing future siltation is also necessary when re-dredging is done. However, the cost of re-dredging is estimated only the cost to dredge up to the target water depth. And so, the cost of over-dredging when re-dredging is done is referred with simple method shown in

5-43 Figure 5.29. That is, the cost for over-dredging is set as same as the cost for maintenance dredging. Therefore, the cost including over-dredging becomes the total cost of re-dredging and maintenance dredging.

Figure 5.29 Structure for costs of re-dredging and maintenance dredging

5.4.5 Effect of decreasing cycle time (Case study on target channel depth of 12 m)

It is examined how the dredging cost changes when the cycle time is decreased to be shorter in case of the target depth of 12 m. The volume of maintenance dredging is predicted by the modified Exponential Model.

It is impossible to dredge the whole area of channel instantaneously, and it takes a certain period of time. Then, a minimum cycle time is assumed to be one month. If you want very much to infer the situation in the cycle time shorter than one month, you can get some idea of it by extrapolating the curved lines to the zero point of cycle time in the figures from Figure 5.30 to Figure 5.33.

Figure 5.30 shows a relation between the cycle time and the volume of maintenance dredging predicted by the modified Exponential Model. The volume of maintenance dredging decreases when the cycle time becomes shorter. In this figure, the black broken line indicates that the annual dredging volume decreases by 0.11 million m3 when the cycle time decreases by one month. When the cycle time is reduced from 3 months to 1 month, a rate of decrease in the annual dredging volume is 7.5 %.

Figure 5.30 Relation between cycle time and annual volume of maintenance dredging

5-44 (predicted by modified Exponential Model for target channel depth of 12 m)

Figure 5.31 shows the working ratio when the required dredging volume shown in Figure 5.30 is dredged by the dredger the capacity of which is 2,500 m3 or 4,500 m3. The working ratios of these dredgers are over 100 % at any cycle time. That is to say, these dredgers cannot maintain the target channel depth of 12 m.

Figure 5.31 Relation between cycle time and working ratio in cases of dredger capacity of 2,500 m3 and 4,500 m3

Figure 5.32 shows the necessary dredger capacity which is determined in a way explained in Section 5.3.3 and its working ratio for each cycle time. By changing the dredger capacity corresponding to each cycle time, the working ratio is kept within the range of 90 to 100 %. The dredger capacity is the smallest in case of cycle time from 1 to 3 months. Even so, it is still 5,000 m3.

Figure 5.33 shows the annual dredging cost by the dredger with necessary capacity. The cost decreases with decreasing of the cycle time. When the cycle time is reduced from 3 months to 1 month, a rate of decrease in the dredging cost is 3.9 %, which is about a half of that of dredging volume in Figure 5.30.

5-45

Figure 5.32 Relation between cycle time and working ratio for necessary dredger capacities

Figure 5.33 Relation between cycle time and annual dredging cost

5.4.6 Recommendation on dredging framework (1) Comparison of dredging cost between dredging by contract base and dredging by own dredger Figure 5.34 collectively illustrates the least dredging cost from Table 5.23 and Table 5.24 (highlighted by yellow color). As the dredging cost by contract base is described with red line and the one by own dredger is described with green line, both comparison can be made easily. According to this Figure, green line always lies underneath of red line. That is to say, the dredging cost by own dredger that CEPA considers is always smaller.

5-46

Figure 5.34 Dredging cost comparison between dredging by contract base and by own dredger

In order to find this reason, study is made on both direct cost and indirect cost. Figure 5.35 shows the comparison separating direct and indirect cost for dredging costs at the circled part in Figure 5.34 by contract base and by own dredger. According to Figure 5.35, the direct cost is almost same but the indirect cost is way cheaper in its dredging cost by own dredger. Indirect cost of contract base includes mobilization cost, insurance cost, costs related with contingency and so on as shown in Table 5.25. On the contrary, indirect cost by own dredger includes only mobilization, insurance cost and contingency, as explained in 5.5.1(4), since other cost is difficult to estimate. However, it is not appropriate to discuss about the dredging frame only with a comparison of dredging cost by contract base and own dredger, for following reasons.

In fact, many kinds of cost considering in dredging by contract base are needed for the operation of own dredger by CEPA. For example, related with temporary cost, the followings are required.

・Fleet and the crew are required for safety boat to control navigation safety at the time of channel dredging, survey boat to conduct field survey and progress control, tag boat to support berthing and leaving of dredger, transportation boat to carry crew for emergency and etc.

・New organization for the maintenance and repair like having facility to maintain and repair (berth, slipway and repair factory) is necessary in order to repair and maintain dredger fleet.

・Organization for the technical management such as dredging quality, progress control, and work schedule the organization to control overall dredging works becomes necessary.

・And, with the above three organizations, service cost such as land, water, electricity and etc. will be increased.

Therefore, in case of dredging by own dredger, more cost than CEPA considers will be borne.

5-47 Furthermore, there are matters to be necessary in case of dredging by own dredger although it is no need to consider in the dredging by contract base. For example, workability of crew at the initial stage will be poor and a cost for crew training at the time of initial dredging period will be required.

20,000,000 18,000,000 16,000,000 14,000,000 12,000,000 (US$)

10,000,000 Direct C. 8,000,000 Indirect C. Cost 6,000,000 4,000,000 2,000,000 0 Contract Base Own Dredger

Figure 5.35 Comparison of direct and indirect cost by contract base and own dredger (12m target depth of modified Exponential Model with 3 months cycle)

Table 5.25 Breakdown of indirect cost of dredging by contract base (cost that CEPA considers are described in red letters)

Temporary cost mobilization cost, transportation cost, preparation cost, temporary facility to prevent loss by dredging, safety cost, service cost, technical management cost , accident insurance by torpedo, repair cost, PR cost

Site cost Labor management cost, cost needed for safety training, taxes and levies, insurance cost, crew salary and other fees, retirement fund, fringe benefit, office supplies, communication cost, entertainment cost, compensation cost, consignment cost, cost for work registration, incidental cost

Administration executive salaries, employee’s salaries and other fees, retirement fund, cost statutory fringe benefit, welfare cost, maintenance and repair cost, office supplies, communication cost, utility charges, study and research cost, PR cost, entertainment cost, donation, rent account, depreciation cost, depreciation for new test and research, depreciation of development cost, taxes and levies, insurance cost, cost for securement of contract, incidental cost

(2) Accuracy of silting volume prediction model According to the result of bottom sounding, two models to predict channel siltation were empirically made. Unfortunately, at present there are differences in two models in the result of prediction of silting volume (Figure 5.8) and dredging cost estimated (Figure 5.27 and Figure

5-48 5.28) as well. It involves taking serious risks for CEPA to own a dredger under the situation that the prediction accuracy of siltation volume is not high. This is explained using Figure 5.36.

Figure 5.36 is the one added necessary dredger capacity to the figure (Figure 5.28) showing dredging cost by CEPA’s own dredger. For example, in case of 13m target water depth at the channel, a dredger with the capacity of 8,500m3 is required in order to dredge target dredging volume predicted by modified Exponential Model, it becomes possible to dredge by a dredger with the capacity of 7,500 m3 in case of target dredging volume by Linear Model. So, at this stage, even if target water depth is fixed as 13m, as there is difference between two models of siltation prediction volume, it is difficult to properly judge the dredger capacity therefore, there is big risk that CEPA will own a dredger fixing its capacity.

Figure 5.36 Dredging cost and dredger capacity by water depth

(3) Target channel water depth in conjunction with development of La Union Port According to Figure 5.36, it is understood that deeper target water depth of channel, bigger dredger capacity to be necessary. That is, the relation that CEPA owns a dredger and the development of port becomes difficult.

The reason is explained with necessary dredger capacity (blue line in the Figure 5.36) against siltation volume predicted by modified Exponential Model. For example, in the assumption that target channel water depth is set as 10 m and build necessary dredger with the capacity of 1,500 m3. After a while, it is needed to correspond to deeper draft vessel for her calling to the port and the target channel water depth is changed to 11 m, the necessary dredger capacity becomes 3,000 m3 in order to maintain the water depth. For the satisfaction of this demand, it has to dispose or sell the dredger with the capacity of 1,500 m3 and newly secure a dredger with the capacity of 3,000 m3. Alternatively, remaining a dredger with the capacity of 1500 m3 and owns another new dredger with the capacity of 1500 m3 can be considered.

There arising the same problem if La Union Port is further developed and changes target water depth as 12 m. In other words, in case that CEPA owns a dredger, additional cost is required for properly maintaining channel water depth in conjunction with the development of La Union Port.

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(4) Recommendation

If CEPA owns a dredger, CEPA would have to bear considerable cost more than the cost estimation. And, dredging works could not be functioned without long experience and the accumulation of know-how. Aside from the cost, CEPA would have to handle training and education for dredger’s crew.

In addition to above, in case of change of target channel depth, the flexible response is extremely difficult if CEPA owns its dredger. This problem will remain unchanged for future as well.

Judging from the above all, “dredging by contract base” for the channel maintenance dredging for a certain period is strongly recommended.

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Chapter 6 Proposal of Monitoring Plan after Re-dredging

6.1 Purposes of Monitoring

In order to manage the economical and efficient maintenance dredging, it is basically important to predict the siltation volume with a high precision. The empirically established two models are based on the bathymetric data which is not necessarily enough in quality and in quantity. More the Linear model is standing on the unverified hypothesis.

The monitoring of the channel depth by bathymetric survey is the only method for improving the precision of prediction and for enhancing the applicability of the Linear Model to the maintenance dredging.

So far the bathymetric data is not enough in the basin to formulate an empirical prediction model. At present the modified Exponential Model has been applied for estimating the siltation volume. In order to confirm the appropriateness of application, it is important and necessary to collect the bathymetric data in the Port area.

In the present section, a monitoring plan is proposed for the channel depth after the re-dredging. The purposes of monitoring are following two issues;

(1) To verify an appropriateness of siltation volume and required volume of maintenance dredging which are predicted by the empirically established prediction models, that is to say, the modified Exponential Model and the Linear Model.

* Monitoring Locations; Inner channel, Outer channel and Harbor basin

(2) To confirm the phenomenon of rapid siltation just after the dredging

* Monitoring Locations; Inner channel and Outer channel

The monitoring plan for achieving the purposes is explained in the following sections. The plan is set up, subject to the condition that the bathymetric survey will be conducted by CEPA themselves with their own instruments.

Through the technical transfer in this research, the Team has provided post-processing tools of the obtained bathymetric data, which are briefly explained in the next section. The Team has also confirmed that CEPA staff can execute bathymetric survey smoothly. Then, the Team supposes that CEPA could execute the monitoring by themselves with their own equipment.

6.2 Verification on appropriateness of the predicted siltation volume

In order to verify an appropriateness of the siltation volume predicted by the empirical prediction model, which are the modified Exponential Model and the Linear Model, it is basically necessary to measure the actual siltation volume. In the case that there is no artificial action in the channel and in the Harbor basin after the dredging, the siltation volume can be estimated based on the difference between the successive two data of bathymetric survey. However, since the re-dredging will be carried out to activate the use of La Union Port, frequent maintenance dredging should be also carried out after completion of the re-dredging. Although the repeating of bathymetric survey is required also in this case, the siltation volume cannot be obtained only

6-1 by bathymetric surveys. Collecting records of maintenance dredging, such as the excavated volume and location, are required for more accurate estimation of siltation volume. In addition, if marine traffic of large vessels increases, siltation speed may decrease due to the strong turbulence generated by the screws which propel a ship. Therefore, the record of vessels which enter into and leave from the port must be collected.

(1) Bathymetric survey 1) A bathymetric survey shall be conducted over the designated sections of the Inner channel, the Outer channel and the Harbor basin. 2) The survey lines shall consist of transversal lines of 500 meters long with an interval of one (1) km in the longitudinal direction. The survey lines in the Inner channel and the Outer channel are shown in Figure 6.1 and Figure 6.2 respectively. 3) The survey lines in the Harbor basin shall be a grid with a side length of 200m as shown in Figure 6.3. 4) The bathymetric surveys should be conducted immediately before and just after the re-dredging. The re-dredged volume is to be calculated using the difference between the depths before and after the re-dredging works. After that, the bathymetric survey shall be repeated with the time interval of two months, or one month if possible. 5) The bathymetric survey must be usually conducted with the two acoustic signals of 38 kHz and 200 kHz to have the data on the thickness of fluid mud.

(2) Volume of dredging The volume of dredging can be estimated by multiplying the capacity of TSHD (Trailing Suction Hopper Dredger) and the number of round trips to the dumping site. As the sea water is mixed when the dredged soil is sucked in to the vessel, the effective capacity of vessel decreases to about 60 percent. The data such as the capacity of vessel, number of round trips, location and date of dredging, which are recorded in the job diary, is supposed to be obtained easily.

(3) Effect of ship navigation It can be understood, setting aside the question of the degree, that the volume of siltation may be decreased a little due to the advection of soil sediment which is suspended by the strong turbulence generated by the screws of vessel. However, the phenomena related to this issue are not known enough and the volume of decreasing may not be large. Then, the profits gained from the minute monitoring are a little. It is enough to collect only the records of vessels, such as length, width, and draught. In addition, the time of entrance into and leave from the port is necessary because the tide level, or elevation of screws from the bottom of channel, and direction of tidal currents can be estimated based on the collected data.

(4) Estimation of siltation volume At first, the volume of topographic change in the channel is calculated by use of the successive two bathymetric data. The volume of dredging, of which location and period are corresponding to those of the bathymetric data, is added to the volume of topographic change. The result is the volume of siltation fundamentally. If the calculation is repeated several times for the different period at the same segment of channel, the estimated siltation volume is not always constant but is expected to scatter. So, the relation is greatly desired to be analyzed between this scattering and the frequency and the volumetric capacity of vessels which enter into and leave from the port. It is inferred that the siltation volume decreases in a period when the vessels navigate more

6-2 frequently.

If the effect of vessel navigation on the siltation volume could be evaluated quantitatively, the estimated siltation volume excluding this effect is compared with the predicted volume of siltation.

6.3 Confirmation of rapid siltation just after the dredging

The rapid siltation occurred just after the dredging. Since the bathymetric surveys conducted about a few months after the dredging, an accumulation of bathymetric data related to the rapid siltation is not enough. In order to confirm this phenomenon, it is necessary to repeat the bathymetric survey at a short interval.

As explained in the Section 5.3, it is inferred that the rapid siltation occurs only just after the dredging and it does not occurs when the maintenance dredging is being conducted. Therefore, note that a chance of confirming the phenomenon of rapid siltation might be limited to only one time when the re-dredging will be completed.

(1) Bathymetric survey

1) The same as Subsection 6.2 (1) 1)

2) Locations of surveying are the reference lines from L21 to L18 in the Inner Channel and those from L09 to L05 in the Outer Channel (see Figure 6.1 and Figure 6.2).

3) The bathymetric survey just after the dredging must be conducted, which is also carried out in 6.2 (1). After that, it is recommended that the survey is repeated at an interval of two weeks for several months.

4) The same as Subsection 6.2 (1) 5)

(2)Volume of dredging

The same as Section 6.2 (2)

(3)Effect of Ship navigation

The same as Section 6.2 (3)

(4)Estimation of siltation volume

At first, the volume of topographic change in the channel is calculated by use of the successive two bathymetric data. The volume of dredging, of which location and period are corresponding to those of the bathymetric data, is added to the volume of topographic change. The result is the volume of siltation fundamentally. If the effect of vessel navigation on the siltation volume could be evaluated quantitatively in Section 6.2 (4), it is taken into consideration for estimation of siltation volume.

6-3

Figure 6.1 Survey lines for Inner channel with the transversal length of 500 m and the longitudinal pitch of 1 km.

6-4

Figure 6.2 Survey lines for Inner channel with the transversal length of 500 m and the longitudinal pitch of 1 km

6-5

Figure 6.3 Survey lines for Port area (basin) with the pitch length of 200 m

6-6

6.4 Tide Correction of Bathymetric Data

6.4.1 Improvement of tide correction of bathymetric survey data (1) Bathymetric survey by CEPA’s staffs For maintenance of the channel, continuous monitoring of channel depth is required. During 1st on-site work in April 2013, the team inspected the bathymetric survey that CEPA staffs carried out. In the bathymetric survey, CEPA’s staffs smoothly operated the field works such as mounting the equipment and measurement. However, CEPA staffs took a lot of time for analysis of the surveyed data, because of lack of post-processing tools.

Therefore, the team prepared tools for smooth post-processing of bathymetric survey data as a part of technology transfer.

GPS

Echo sounder EA-400

Figure 6.4 Equipment of the bathymetric survey mounted by CEPA staffs

(2) Depth correction by tide level One of the post-processing of bathymetric survey data is tide correction. The relation between water depth and tide level is as illustrated in Figure 6.5. To obtain the water depth below chart datum level (C.D.L.), tide correction has to be made with the following equation,

mes ahh )(   tide (6.1)

where h is the water depth below C.D.L., hmes is the measured depth by echo sounder, a is the draft of the echo sounder, and  tide is the tide level.

Equation (6.1) shows that the accuracy of bathymetric data is influenced by the accuracy of tide data. Figure 6.6 shows an example chart of tide level. According to the interview with CEPA staffs, their tide correction was the method to read a tide level at arbitrary time by linear interpolation of high and low tide of published tide table data, as shown in Figure 6.6. This method is less accurate for tide prediction, and may also affect the accuracy of bathymetric data. To improve the tide prediction, the team introduces a new method of tide correction by using a tide prediction computer program by applying a harmonic method that has been developed on the SAPI study.

6-7

The tide prediction program developed by the SAPI study includes some correction parameters of mean water level, tidal amplitude, and phase lag due to location along the access channel as shown in Figure 6.7.

Figure 6.5 Relation between measured and corrected water depth

Tide table Linear interpolation Predicted by harmonic method

Figure 6.6 Variation of tide level of April 19, 2013

6-8

Figure 6.7 Tidal correction parameters related to the locations of the channel (from SAPI’s report)

6-9

(3) Coordinate conversion Another important part of post-processing of bathymetric survey data is coordinate conversion of the positioning data (GPS outputs). Bathymetric survey data includes GPS outputs that are usually written by geodetic data of latitude and longitude. The geodetic data has to be appropriately converted to a local coordinate system for further use. In La Union, Lambert/NAD27 system is used as the local coordinate system.

For the coordinate conversion, CEPA staffs have used a simple program as shown in Figure 6.8, which cannot convert many data at the same time. The team, therefore, offered a coordinate conversion program to assist quick conversion.

Figure 6.8 Screenshot of the geodetic converter which CEPA staffs use

6-10

(4) A Excel macro book for post processing of bathymetric survey data In order to make post-processing of bathymetric survey data quickly, the team developed Excel macro book with tools for post-processing. The macro book is coded by VBA and the main functions are as follows.

 Open and Read a measured data file of the echo sounder, EA-400  Tide prediction taking measurement position into account  Tide correction of bathymetric data  Coordinate conversion between geodetic / WGS84 and Lambert / NAD27  Remove abnormal data (quasi-automatic)  Make a dataset with coordinates based on the channel center line

Figure 6.9 shows a screenshot of the Excel macro book as an example. As shown in the figure, depth data and positioning data are all converted on the macro book by just clicking the command buttons. Figure 6.10 shows a function of the macro book that making a dataset based on the coordinates along/across the channel center line. The macro book and its usage will be introduced in the 2nd on-site work in August, 2013.

Output from the echo sounder (EA-400) Results of Conversion

Geodetic Depth Tide level Depth Local Coordinates Macro Command Date/Time (WGS84) (measured) (Predicted) (Corrected) (Lambert / NAD27) (Excel / VBA)

Calculated by latidude, longidude, date, and time. Figure 6.9 Post-processing tools coded by Excel/VBA

6-11

Local Coordinates Coordinates of along/across (Lambert / NAD27) Depth the Channel Center Line

Kp_Y

Kp_X

Figure 6.10 Example of the post-processed data

6-12

6.4.2 Datum level of La Union Port (1) Discussion with CNR officials In order to maintain the navigability of access channel, frequent monitoring of water depth by bathymetric survey is required. The surveyed water depth must be measured by using a unified reference level to estimate siltation of the access channel and harbor basin appropriately. CEPA conducted bathymetric survey in June, 2011, and the result showed some different tendencies from the previous results. As the survey result by CEPA seems to be taking different reference level from the previous results, the Team discussed with the CNR officials, who are in charge of tide prediction for the coasts of El Salvador, to confirm the reference levels used in previous surveys.

The meeting with CNR officials was made in the office of CNR, San Salvador, at August 24, 2011. The objective of the meeting is to clarify the tide levels, the methodology of tide prediction, and the vertical reference level employed in El Salvador. In the meeting, CNR officials who are responsible for tide prediction and publication of tide tables of El Salvador sincerely explained to the Team on its questions. The following information is confirmed in the meeting.

1) CNR uses the tidal constituents from the NOAA Harmonic Constituents Database for the tide prediction of La Unión. The harmonic constituents can be found in NOAA’s web page (http://tidesandcurrents.noaa.gov/). The tidal constituents are completely the same as those the Team uses for tide prediction.

2) The tidal constituents were determined in 1960, based on the tide observation data for 9 years at La Unión. The information is reported in the document of “El Salvador Elevations of Benchmarks referred to mean sea level.”

3) The reference level used in the tide table published by CNR is 5 ft (=1.524 m) below MSL for the port of La Unión.

4) The geodetic vertical datum (GVD) of El Salvador was determined in 1960 and the zero-level was set as the MSL based on the survey in 1960.

5) The relation between the GVD and tide levels is shown in Table 6.1. The data in Table 6.1 are provided by CNR.

6) In La Unión, the reference level of water depth in the sea has been set as the height of MLLW (= -1.3381 m) since 1960. For the purpose of marine navigation, however, the water depths are calculated with the reference level of 1.5381 m (=1.3381+0.2) below MSL, where the additional 0.2 m is the security factor for safe navigation. This indicates that the actual chart datum level (CDL) is 1.5381 m.

6-13

Table 6.1 Vertical reference levels for El Salvador provided by CNR.

La Unión Acajutla La Libertad Highest Tide Obserbed HTO 1.9812 1.5240 1.6154 High Water Springs HWS 0.9601 1.0211 Mean High High Water MHHW 1.2710 0.8656 0.9235 Mean High Water MHW 1.1704 0.7711 0.8260 Mean Sea Level MSL 0.0000 0.0000 0.0000 Mean Tide Level MTL -0.0518 0.0000 0.0061 Mean Low Water MLW -1.2771 -0.7742 -0.8138 Mean Low Low Water MLLW -1.3381 -0.8169 -0.8595 Low Water Springs LWS -0.9601 -1.0211 Low Tide Obseved LTO -2.2860 -1.4021 -1.4935

(2) Setting of chart datum level of La Unión Port From the item 6) of the meeting with CNR, it is confirmed that the actual C.D.L. for the purpose of navigation is 1.5381 m below MSL. The relation between MSL and C.D.L. can be drawn as shown in Figure 6.11. The height of benchmark of CUT-9 is also shown in Figure 6.11, where the CUT-9 is located at the southeast corner of the container wharf in the port of La Unión.

In the detail design stage of construction of the port of La Unión, the Detailed Design consultant team has set C.D.L. at 1.652 m below MWL as described in Appendices B and F to the Final Report of the Detailed Design on Port Reactivation Project in La Unión Province (JICA) in 2002. Here, the MWL is defined as the mean tide level at Cutuco jetty and differs from MSL which is defined by CNR as the mean sea level. Also, according to design drawings of the container wharf in the port of La Unión, the top elevation of the wharf is written as C.D.L.+5.00 m. Based on the information, the relation between MSL and C.D.L. is drawn as shown in Figure 6.11. Using the C.D.L. defined in the DD-Report, the MSL is calculated as C.D.L. +1.7166 m.

As described above, two C.D.L. s have been defined for the Port of La Unión as shown in Figure 6.11 and Figure 6.12. The water depth based on the C.D.L. by CNR is calculated 0.1785 m deeper than that by DD-Report. The difference may be slight, but it can influence on estimations of siltation and dredging volume. Therefore, it is recommended to unify the C.D.L. for efficient maintenance of the access channels in the future.

6-14

CUT-9 4.8215 CNR reference CDL=MSL-1.3381 - SF 3.2834 Ref. level MSL CDL CUT-9 3.2834 4.8215 1.5381 MSL MSL 0.0000 1.5381 MLLW -1.3381 0.2000 1.3381 CDL -1.5381 0.0000 0.2000 MLLW 0.20 0.0 CDL (actual) (S.F)

h, water depth

Figure 6.11 Vertical reference employed by CNR

CUT-9 5.0000 DD reference CDL=MWL-1.652 Ref. level MSL CDL 3.2834 CUT-9 3.2834 5.0000 MSL 0.0000 1.7166 1.7166 MSL MWL -0.0646 1.6520 0.0646 1.6520 MWL(DD)? CDL -1.7166 0.0000

1.652

0.0 CDL (DD)

h, water depth

Figure 6.12 Vertical reference employed by DD-Report (CUT-9 is a benchmark located on the south-eastern corner of the port of La Union)

6-15

(3) Correction to Bathymetric Chart of CEPA Figure 6.13 exhibits the water depth along the access channel surveyed by the JICA Team in early February 2011 and that by TOPONORT S. A. for CEPA in June 2011, together with the water depth on the east bank. Though some siltation is expected to have occurred during the period between the two bathymetric surveys, the CEPA survey results indicate only slight siltation in the section of inner access channel and some deepening in the outer access channel. Because such changes in water depth are not likely to have occurred in reality, the difference in water depth must have been brought by the difference in the method of tidal level adjustment to the bathymetric raw data.

According to TOPONORT S. A, their survey result was organized with the reference level of MLLW (= -1.3381m) and was not taking the security factor of 0.2 m into account. On the other hand, water depths surveyed by the JICA Team is organized with the CDL defined by DD-Report as shown in Figure 6.12. In this case, the difference of water depth due to the difference of the reference levels reaches 0.3785 m (= 0.1785 + 0.2). In order to compare the water depths and estimate the siltation height accurately, the survey data have to be appropriately organized with the same reference level. Figure 6.14 shows a converted result that the all water depths are adjusted with the C.D.L. defined by CNR, the reference level of which is 1.5381 m below MSL. It is found that the depth change between JICA and CEPA has become natural compared with Figure 6.13.

From the above example, it is also found that the water depth in the channel has to be organized with a unified C.D.L. Although the C.D.L. by DD-Report has been used in the previous bathymetric survey results, the C.D.L. does not match the reference level of tide. The relation between tide and water depth is quite important for navigation, and the Team recommends to CEPA to use C.D.L.by CNR in the future, which is the same as the reference level of tide.

In the present report, therefore, all data of water depth have been converted to the basis of C.D.L. by CNR, and the all plots in the previous chapters have been modified.

6-16

‐6 East bank ‐7 Before Correction JICA Feb. '11 ‐8 CEPA Jun '11 ‐9 (m)

‐10 Depth ‐11

‐12 Water

‐13

‐14

‐15 0 2 4 6 8 10121416182022 Distance (KP)

Figure 6.13 Variation of water depth along the access channel before depth correction.

‐6 East bank ‐7 After Correction JICA Feb. '11 ‐8 CEPA Jun '11 ‐9 (m) ‐10 Depth ‐11

‐12 Water

‐13

‐14

‐15 0 2 4 6 8 10121416182022 Distance (KP)

Figure 6.14 Variation of water depth along the access channel after depth correction.

6-17

Chapter 7 Reviews of Demand Forecast Model and Market Allocation Model developed by CEPA

In this chapter, the outline of how to calculate the projected growth rate of container volume from CA4 (El Salvador, Guatemala, Honduras and Nicaragua) and develop the market allocation model that carried out by CEPA is shown. 7.1 Outline of Demand Forecast Model and Market Allocation Model developed by CEPA

“Port demand Study of La Union” carried out by CEPA consists of three parts:

1. Projected the growth rate of container volume to and from CA4 2. Development of market allocation model 3. Projected market allocation for La Union Port The first part provides the historical correlation between the growth of gross domestic product (GDP) of the region with the growth in the volume of containers which moved through the ports of Central America from 2000 to 2010, as well as along TEUs and Containers projected to 2030. The second part will develop market assigning model of present states for each of the countries. The third part will project market allocation and future volume of container for La Union Port. 7.2 Projected the growth rate of container volume to and from CA4

(1) Acquisition of historical time series data on GDP and container volume In order to estimate the past GDP elasticity of container cargoes, it is necessary to obtain historical time series of GDP and container volume to/from each CA4 country (El Salvador, Guatemala, Honduras and Nicaragua).

Historical data of GDP in CA4 can be obtained from UNCTAD (United Nations Conference on Trade and Development) and World Bank.

Historical data of container volume to/from each CA4 country were estimated from trade statistics database of SIECA (The Secretariat of Central American Economic Integration). The data from 2000 to 2010 were used for the analysis.

The procedure of estimating container volume from SIECA trade data is as follows:

・ Elimination of bulk commodities ・ Elimination of cargoes transported by land ・ Addition of bulk commodities transported by land (in order to avoid duplicated elimination)

7-1 Table 7.1 Real GDP Growth Rate of CA4 (%) El Salvador Guatemala Honduras Nicaragua 2000 2.15 3.61 5.75 4.10 2001 1.71 2.33 2.72 2.96 2002 2.34 3.87 3.75 0.75 2003 2.30 2.53 4.55 2.52 2004 1.85 3.15 6.23 5.31 2005 3.09 3.26 6.05 4.28 2006 4.18 5.38 6.57 4.15 2007 4.61 6.30 6.31 3.64 2008 2.43 3.28 3.97 2.76 2009 -3.54 0.54 -1.91 -1.47 2010 0.96 2.59 2.60 4.48 (source: UNCTAD: El Salvador, Guatemala, Honduras, World Bank: Nicaragua)

Table 7.2 Estimated Container Volume to CA4 (ton) El Salvador Guatemala Honduras Nicaragua Import Export Import Export Import Export Import Export 2000 879,440 248,311 1,231,486 1,665,777 920,431 860,442 314,518 237,684 2001 900,729 219,684 1,323,346 1,521,243 905,108 1,119,479 322,130 237,984 2002 985,373 292,144 1,514,115 1,577,175 987,449 1,082,915 355,330 231,022 2003 1,025,225 270,932 1,767,615 1,650,752 1,054,317 1,207,982 370,227 258,791 2004 1,040,092 305,404 1,811,812 1,754,197 936,813 1,429,273 375,237 297,126 2005 1,170,806 324,841 1,705,398 1,813,622 1,139,577 1,461,146 397,739 322,993 2006 1,405,739 514,911 2,011,199 1,785,137 1,171,416 1,536,370 419,989 341,409 2007 1,400,514 519,407 1,919,922 2,296,940 1,370,217 1,590,373 470,314 391,362 2008 1,407,026 615,508 1,880,834 2,444,374 1,402,625 1,614,979 496,481 473,040 2009 1,186,362 509,387 1,646,527 2,629,030 1,096,060 1,398,156 438,768 464,924 2010 1,316,762 568,705 1,836,156 2,365,200 1,444,448 1,588,256 528,815 518,651 (source: CEPA calculated based on the trade database of SIECA.)

7-2 (2) Estimation of the present GDP elasticity of container volume The present GDP elasticity of container volume growth was estimated using the time series of GDP and container volume between 2000 and 2010.

CEPA used a regression analysis to estimate the degree of correlation between the growth of the production of CA4 (independent variable) and the volume of import and export containers of the same (dependent variable).

Table 7.3 GDP Elasticity of Container Volume to/from CA4 GDP Elasticity El Salvador import 2.11 export 4.57 Guatemala import 0.96 export 1.55 Honduras import 0.99 export 1.18 Nicaragua import 1.59 export 2.82 Source: CEPA, the Expert

(3) Estimation of the future GDP elasticity of container volume CEPA assumed that the present GDP elasticity calculated in the previous subsection would basically remain unchanged until 2030. Nevertheless, the GDP elasticity is assumed to decrease linearly to 2.0 toward the target year of 2030 when the present GDP elasticity exceeds 2.0 because the elasticity of 2.0 is upper limit of average elasticity in developing economies and there is a need to avoid overestimation in the forecast.

Table 7.4 GDP Elasticity

Source: CEPA's calculations based on data from United Nations Conference on Trade and Development (UNCTAD),Central American Trade Statistics System (SIECA) and United States Census Bureau

7-3 (4) Calculation of the growth rate of container volume The container growth rate was estimated using the future GDP growth rate and the GDP Elasticity. The future GDP growth rate was provided by USDA (Economic Research Service, U.S. Department of Agriculture) and IMF.

The calculation formula is as follows.

Container Growth Rate = (GDP Growth Rate) x (GDP Elasticity)

Table 7.5 Container Growth Rate (2010=100) 2010-2020 2010-2030 El Salvador 200 395 Guatemala 167 278 Import Honduras 158 252 Nicaragua 203 343 El Salvador 340 776 Guatemala 167 277 Export Honduras 160 248 Nicaragua 207 349 Source: El Salvador, Guatemala:USDA, Honduras, Nicaragua:IMF

7.3 Development of Market Allocation Model

(1) Estimated volume of import and export containers In order to project the market share, CEPA has estimated the Hinterland matrix by collecting and analyzing the various container flow data of CA4.

Since the exact data of the container flow in CA4 did not exist, CEPA was using some assumption. Procedure of estimation by CEPA is described below.

1) Calculate the container volume of the geographical areas where cargo is imported and exported to each port in CA4.

1. The data of total volume of containers imported / exported to ports in the CA4 is acquired from COCATRAM (The Central American Commission on Maritime Transport). 2. The data of Quetzal port and Santo Tomas on distribution of the total volume cargo imported / exported between different geographical areas are acquired from CPN (Guatemala National Port Commission). Geographical areas of CPN are divided into 6 areas (United States West coast: USWC, United States East coast: USEC, EU, Asia, Other Pacific and Other Atlantic).With these data we calculate the cargo share of each of the geographical areas. 3. Since the management situation and the handling situation is similar, the same share of Puerto Quetzal applies to Corinto and Acajutla. Similarly, the same share of Santo Tomas is applied to Pt Cortes and Pt Castilla. 4. To calculate the container volume of the geographical areas, total volume of containers of each port and the share of each geographical area are multiplied.

7-4 Table 7.6 Container Volumeof each port in 2010 Imported Container Other USEC, Other USWC Asia EU Total Volume in 2010 (TEU) Pacific USG Atlantic Acajutla 26,627 11,748 13,340 6,825 5,845 6,485 70,870 Quetzal 33,290 14,688 16,678 8,533 7,307 8,108 88,604 Santo Tomas 68 2,202 13,415 107,586 13,705 14,254 151,230 Pt. Barrios 0 0 0 45,247 3,016 2,011 50,274 Pt. Cortes 95 3,061 18,649 149,560 19,052 19,815 210,232 Pt. Castilla 6 192 1,169 9,373 1,194 1,242 13,176 Corinto 11,591 5,114 5,807 2,971 2,544 2,823 30,851 TOTAL 71,677 37,005 69,058 330,095 52,663 54,738 615,237

Exported Container Other USEC, Other USWC Asia EU Total Volume in 2010 (TEU) Pacific USG Atlantic Acajutla 14,262 7,282 5,497 1,633 2,191 5,970 36,834 Quetzal 27,729 14,157 10,687 3,175 4,260 11,606 71,614 Santo Tomas 32 5,946 3,455 116,036 10,100 18,787 154,356 Pt. Barrios 0 0 0 88,626 5,908 3,939 98,473 Pt. Cortes 44 8,324 4,837 162,437 14,139 26,299 216,081 Pt. Castilla 7 1,322 768 25,807 2,246 4,178 34,330 Corinto 6,518 3,328 2,512 746 1,001 2,728 16,834 TOTAL 48,592 40,359 27,756 398,462 39,847 73,507 628,522

2) Calculate the container volume of the geographical areas where cargo is imported and exported to each country in CA4.

1. The data of each CA4 country of distribution of the total cargo volume imported / exported between different geographical areas are acquired from SIECA. 2. Geographical areas of SIECA are divided into 5 areas (USA, EU, Asia, Other Pacific and Other Atlantic). In order to divide the USA data to USWC and USEC, we calculate the proportion of USWC and USEC by using the data of US TRADE ONLINE. With these data we calculate the share of each of the geographical areas. 3. To calculate the container volume between each country of CA4 and the geographical areas, we multiply the share of the geographical areas by the total container volume of the geographical areas. Table 7.7 Container Volume of each country in 2010 (TEU)

Imported Container Other USEC, Other USWC Asia EU Total Volume in 2010 (TEU) Pacific USG Atlantic

El Salvador 28,453 10,321 16,373 62,853 13,908 12,946 144,854 Guatemala 28,392 15,966 33,677 137,889 26,937 19,115 261,976 Honduras 6,617 5,527 16,375 109,278 9,125 5,948 152,870 Nicaragua 8,215 5,191 2,634 20,075 2,693 16,729 55,537 TOTAL 71,677 37,005 69,058 330,095 52,663 54,738 615,237

7-5

Exported Container Other USEC, Other USWC Asia EU Total Volume in 2010 (TEU) Pacific USG Atlantic

El Salvador 6,002 5,973 2,288 39,109 3,503 11,931 68,806 Guatemala 33,227 20,089 21,368 222,201 14,205 39,609 350,698 Honduras 4,872 9,355 2,401 106,786 18,023 11,347 152,784 Nicaragua 4,492 4,942 1,699 30,365 4,115 10,620 56,234 TOTAL 48,592 40,359 27,756 398,462 39,847 73,507 628,522

(2) Estimation of containers imported / exported by land, as the area of influence of the ports

The area of influence of the Ports and hinterland refers to how cargo entering or leaving through the Ports of CA4 is distributed in the Central American region which is the second step in developing the model. It was necessary to calculate the volume of container exported and imported by land by area of influence of the different ports under study. Data was calculated based on the data that different countries customs CA4 provided as follows:

Santo Pt. Pt. Cortes/ IMPORT Acajutla Quetzal Corinto Tomas Barrios Pt. Castilla

El Salvador 93.50% 6.63% 6.63% 6.63% 15.27% 21.53% Guatemala 3.73% 71.17% 18.97% 9.47% 10.93% 0.00% Honduras 1.70% 1.20% 1.20% 1.20% 65.53% 10.69% Nicaragua 0.17% 0.00% 0.00% 0.00% 5.26% 43.44% Others 0.89% 8.55%8.55% 8.55% 0.00% 24.33%

Santo Pt. Pt. Cortes/ EXPORT Acajutla Quetzal Corinto Tomas Barrios Pt. Castilla

El Salvador 48.08% 17.00% 6.00% 8.00% 7.20% 21.53% Guatemala 0.42% 70.68% 70.68% 70.68% 10.93% 0.00% Honduras 2.67% 4.22% 4.22% 4.22% 53.67% 10.69% Nicaragua 0.25% 0.00% 0.00% 0.00% 5.26% 43.44% Others 48.58% 8.10%19.10% 17.10% 22.93% 24.33%

El Salvador is divided into eastern and western and Honduras can be divided into north and south. The ratio was adjusted through the interviews etc.

West 94% North 70% El Salvador Honduras East 6% South 30%

7-6 To calculate the container volume, we multiply this share by the total container volume of the each port calculated above.Data was classified into imports / exports of the Pacific, import / export of the Atlantic, for each country.

Table 7.8 Hinterland transport matrix (2010) Hinterland transport matrix Import: Pacific (2010) (TEU) S Tomas / Pt. Cortes / Acajutla Quetzal Corinto Total P Barrios Pt. Castilla El Salvador (E) 484 43 10 16 25 578 El Salvador (W) 47,870 4,246 1,030 1,606 2,479 57,232 Guatemala 1,930 51,725 13,117 2,534 0 69,306 Honduras (N) 617 541 131 10,543 658 12,491 Honduras (S) 264 232 56 4,519 282 5,353 Nicaragua 89 0 0 1,220 15,504 16,813 Total 51,254 56,786 14,345 20,437 18,949 161,772 Hinterland transport matrix Import: Atlantic (2010) (TEU) S Tomas / Pt. Cortes / Acajutla Quetzal Corinto Total P Barrios Pt. Castilla El Salvador (E) 179 16 123 140 9 468 El Salvador (W) 17,731 1,573 12,203 13,876 918 46,301 Guatemala 715 19,158 150,550 21,894 0 192,318 Honduras (N) 229 200 1,555 91,107 244 93,335 Honduras (S) 98 86 666 39,046 105 40,001 Nicaragua 33 0 0 10,542 5,743 16,317 Total 18,984 21,033 165,097 176,606 7,019 388,739

Hinterland transport matrix Export: Pacific (2010) (TEU) S Tomas / Pt. Cortes / Acajutla Quetzal Corinto Total P Barrios Pt. Castilla El Salvador (E) 230 1 0 11 27 269 El Salvador (W) 22,754 145 20 1,060 2,634 26,614 Guatemala 114 37,157 6,667 1,673 0 45,612 Honduras (N) 505 17 279 6,570 925 8,296 Honduras (S) 216 7 119 1,643 396 2,382 Nicaragua 68 0 0 806 5,369 6,242 Total 23,888 37,328 7,085 11,763 9,351 89,415 Hinterland transport matrix Export: Atlantic (2010) (TEU) S Tomas / Pt. Cortes / Acajutla Quetzal Corinto Total P Barrios Pt. Castilla El Salvador (E) 83 1 11 165 10 269 El Salvador (W) 8,241 53 1,094 16,293 954 26,635 Guatemala 41 13,458 172,028 25,707 0 211,234 Honduras (N) 183 6 7,195 100,946 335 108,665

7-7 Honduras (S) 78 3 3,083 25,237 144 28,545 Nicaragua 25 0 0 12,378 1,944 14,347 Total 8,652 13,520 183,411 180,725 3,387 389,695

7.4 Projected market allocation for La Union Port

The potential market share of La Union Port and the future volume of container are calculated by Logit Model.

The utility functions used were:

∪=-θ*(∁+γ*τ) where:

∪ = Utility θ = Coefficient of Cost ∁ = Cost γ = Coefficient of time τ = time

(1) Acquisition of data on the present transit time and cost Two essential elements for the calculation of the potential demand for the CA4 countries are transit times and shipping costs and land, which were calculated with the following assumptions:

(1)Costs (U.S. $) of TEU seaborne transportation to and from the various ports are the same that were calculated in the study of Nathan.

(2)To calculate the costs (U.S. $) of land in TEU transport to and from the different ports use the following source:

http://www.globalshippingcosts.com/calc/#lat=25.95804&lon=-80.15625&zoom=

Taking as reference the following locations:

Landmark Reference El Salvador East San Miguel West San Salvador Guatemala Guatemala City Honduras North San Pedro Sula Sourth Tegucigalpa Nicaragua Managua

(3)The results in miles were multiplied by 1.6093 to convert it to kilometers, and this result was multiplied by the price equivalent to 1.5 kilometers.

7-8 (4)The handling charge for the port terminal was obtained in the case of the ports on the Atlantic (except for Puerto Barrios) http://www.hapag-lloyd.com page, for the rest of the ports, CEPA considered the tariff structure of each port.

(5) The data on the transit time (in days) were obtained from the following source: http://www1.axsmarine.com/distance/

Table 7.9 Referencing the following locations: Landmark Reference Western U.S. Los Ángeles U.S. east and Gulf Miami China Shanghái Europa Algeciras

Table 7.10 Transportation Cost per TEU in 2010 (USD) Santo Pt. Pt. Acajutla La Union Quetzal Pt. Cortes Corinto Tomas Barrios Castilla Ocean Freight Rate to USWC 1,823.53 1,266.49 1,764.71 1,188.28 1,188.17 2,000.00 1,254.76 1,304.87 from USWC 1,823.53 1,266.49 1,764.71 1,188.28 1,188.17 2,000.00 1,254.76 1,304.87 to USG 1,764.71 2,115.00 1,647.06 2,115.00 2,115.00 1,647.06 2,115.00 2,058.82 from USG 1,764.71 2,115.00 1,647.06 2,115.00 2,115.00 1,647.06 2,115.00 2,058.82 to China 2,400.00 2,400.00 2,400.00 2,400.00 2,400.00 2,400.00 2,400.00 2,400.00 from China 4,411.76 2,400.00 4,411.76 2,400.00 2,400.00 5,000.00 2,400.00 4,470.59

to EU 2,400.00 2,400.00 2,400.00 2,400.00 2,400.00 2,400.00 2,400.00 2,400.00 from EU 3,529.41 2,400.00 2,941.18 2,400.00 2,400.00 3,235.29 2,400.00 3,470.59 THC (Terminal 73.48 65.79 117.65 64.7 64.70 64.70 58.82 Handling Charge) Land Transportation El Salvador East 346.64 73.67 621.88 764.35 769.66 562.45 558.88 623.67 West 127.07 269.98 402.79 560.23 565.25 604.12 520.35 429.15 Guatemala 287.04 629.68 150.51 450.66 450.66 568.68 623.45 976.88 Honduras North 680.95 495.70 786.22 233.91 233.91 88.81 86.90 746.71 South 614.98 274.47 1,079.59 542.82 542.82 452.33 368.56 395.74 Nicaragua 877.13 536.62 1,151.70 1,053.09 1,053.09 962.59 878.82 212.33

Table 7.11 Transit Time in 2010 (Days) Santo Acajutla La Union Quetzal Pt. Barrios Pt. Cortes Pt. Castilla Corinto Tomas Ocean Transit Time USWC 6.90 7.38 6.76 12.09 12.09 12.11 11.55 7.55

7-9 USG 6.57 6.33 6.74 2.60 2.59 2.67 2.36 6.09 China 24.77 25.25 24.63 29.96 29.96 29.98 29.42 25.42 EU 18.16 17.92 18.33 15.65 15.65 15.73 15.42 17.68 Dwell Time 2.50 2.50 2.50 2.50 2.50 2.50 2.50 2.50 in Port Land Transit Time El Salvador East 0.17 0.17 0.75 0.94 0.94 0.65 1.03 0.45 West 0.31 0.17 0.32 0.63 0.63 0.80 1.37 0.84 Guatemala 0.70 1.20 0.17 0.50 0.50 0.64 1.27 1.09 Honduras North 0.76 0.30 0.88 0.26 0.26 0.10 0.59 0.84 South 0.69 0.60 1.21 0.61 0.61 0.51 0.68 0.44 Nicaragua 0.98 0.59 1.29 1.18 1.18 1.08 1.24 0.24

(2) The potential market share of La Union Port

1)Total Cost including Time Value is calculated from the above-mentioned data. Cost is Ocean Freight Rate and Land Transportation. 2) We calculate θ = Coefficient of Cost and γ = Coefficient of time, for Estimated Share (%) is as closest to Share in 2010 (%). 3) With these data, we calculate the Utility of each port and the potential market share of La Union Port.

Table 7.12 Hinterland transport matrix(with La Union) Hinterland transport matrix Import: Pacific (2010) (TEU)

S Tomas / Pt. Cortes / La Acajutla Quetzal Corinto Total P Barrios Pt. Castilla Union

El Salvador (E) 67 6 1 2 4 498 578 El Salvador (W) 30,012 2,890 289 285 2,134 10,692 46,302 Guatemala 9,802 59,481 9 0 0 14 69,306 Honduras (N) 15 1 1,029 10,995 1 449 12,490 Honduras (S) 11 0 1 8 113 5,220 5,353 Nicaragua 0 0 0 0 16,813 016,813 Total 39,907 62,378 1,329 11,290 19,065 16,873 150,842 Hinterland transport matrix Import: Atlantic (2010) (TEU) S Tomas / Pt. Cortes / La Acajutla Quetzal Corinto Total P Barrios Pt. Castilla Union El Salvador (E) 85 23 29 61 18 253 469 El Salvador (W) 15,313 1,412 11,769 10,434 1,262 6,111 46,301 Guatemala 4,577 17,212 149,886 20,555 0 87192,317 Honduras (N) 0 0 1,891 91,444 0 0 93,335 Honduras (S) 0 0 576 28,012 15 11,397 40,000 Nicaragua 38 0 0 10,145 5,524 61016,317 Total 20,013 18,647 164,151 160,651 6,819 18,458 388,739

7-10

Hinterland transport matrix Export: Pacific (2010) (TEU) S Tomas / Pt. Cortes / La Acajutla Quetzal Corinto Total P Barrios Pt. Castilla Union El Salvador (E) 18 2 0 0 0 248 268 El Salvador (W) 19,808 1,950 73 29 293 4,482 26,635 Guatemala 4,286 41,324 1 0 0 1 45,612 Honduras (N) 75 10 1,486 5,669 13 1,043 8,296 Honduras (S) 19 0 2 7 167 2,186 2,381 Nicaragua 0 0 0 0 6,242 06,242 Total 24,206 43,286 1,562 5,705 6,715 7,960 89,434 Hinterland transport matrix Export: Atlantic (2010) (TEU) S Tomas / Pt. Cortes / La Acajutla Quetzal Corinto Total P Barrios Pt. Castilla Union El Salvador (E) 7 0 1 13 0 248 269 El Salvador (W) 6,926 1,307 7,057 6,408 1,238 3,699 26,635 Guatemala 3,189 11,791 171,402 24,780 0 73211,235 Honduras (N) 0 0 7,457 101,208 0 1 108,666 Honduras (S) 1 0 1,782 24,247 11 2,504 28,545 Nicaragua 27 0 0 12,134 1,905 28114,347 Total 10,150 13,098 187,699 168,790 3,154 6,806 389,697

7-11 (3) The future volume of container for La Union Port 1) Scenario 1:Change of competitiveness due to difference of inflation rate among CA4 countries

Given the differences in inflation levels of CA4, it is important to estimate the potential demand variations due to changes in inflation as follows:

a)The inflation rates were taken from USDA (United States Department of Agriculture), selected base year is 2010.

b)The elements were varied: +Shipping costs: The costs of sea transport for 2020 and 2030 were calculated by multiplying the cost of 2010 for global inflation in 2020 and 2030 respectively, and dividing the result by the global inflation base year.

+Cost management terminal: The terminal handling costs for 2020 and 2030 were calculated by multiplying the cost of 2010 for inflation in each country in 2020 and 2030 respectively, and dividing by the country's inflation to year base.

+ Overland transport costs: Inflation data were used for land transport costs by country, by multiplying the cost of each country by its respective inflation in 2020/2030.

+ Coefficients: The time factor remains constant; at factor cost in turn is added to the country's inflation analysis.

Hinterland transport matrix with La Union in 2020, 2030 are below. (Case where capacity of Acajutla port is not limited.)

2010 2020 2030 World 100 135.7 179.73 El Salvador 100 136.26 174.63 Guatemala 100 156.13 228.59 Honduras 100 170.93 270.93 Nicaragua 100 191.48 311.75

7-12 Table 7.13 Hinterland transport matrix (with La Union) in 2020 (Scenario1) Hinterland transport matrix with La Union in 2020 (IMPORT: Pacific) (TEU) S Tomas / Pt. Cortes / La Acajutla Quetzal Corinto Total P Barrios Pt. Castilla Union El Salvador (E) 136 8 0 2 2 1,006 1,154 El Salvador (W) 62,941 4,306 419 315 1,985 22,422 92,388 Guatemala 25,600 0 0 0 0 0 25,600 Honduras (N) 3,170 2,302 4,606 5,674 2,020 1,987 19,759 Honduras (S) 33 0 3 16 81 8,335 8,468 Nicaragua 0 0 0 0 34,045 6 34,051 Total 91,880 6,616 5,028 6,007 38,133 33,756 181,420 Hinterland transport matrix with La Union in 2020 (IMPORT : Atlantic) (TEU) S Tomas / Pt. Cortes / La Acajutla Quetzal Corinto Total P Barrios Pt. Castilla Union El Salvador (E) 186 38 48 90 22 551 935 El Salvador (W) 38,176 2,566 20,696 14,233 1,485 15,235 92,391 Guatemala 11,792 36,157 250,113 23,533 0 315 321,910 Honduras (N) 0 0 2,566 145,072 0 0 147,638 Honduras (S) 3 0 539 11,327 16 51,388 63,273 Nicaragua 160 0 0 19,660 11,321 1,908 33,049 Total 50,317 38,761 273,962 213,915 12,844 69,397 659,196 Hinterland transport matrix with La Union in 2020 (EXPORT: Pacific) (TEU)

S Tomas / Pt. Cortes / La Acajutla Quetzal Corinto Total P Barrios Pt. Castilla Union

El Salvador (E) 36 2 0 0 0 499 537 El Salvador (W) 41,267 2,015 76 26 235 9,528 53,147 Guatemala 12,987 63,351 2 0 0 5 76,345 Honduras (N) 191 14 2,645 8,249 6 2,017 13,122 Honduras (S) 52 0 5 11 125 3,573 3,766 Nicaragua 697 0 0 958 10,293 697 12,645 Total 55,230 65,382 2,728 9,244 10,659 16,319 159,562 Hinterland transport matrix with La Union in 2020 (EXPORT : Atlantic) (TEU)

S Tomas / Pt. Cortes / La Acajutla Quetzal Corinto Total P Barrios Pt. Castilla Union

El Salvador (E) 14 0 2 8 0 513 537 El Salvador (W) 16,584 2,518 13,289 10,135 1,768 8,856 53,150 Guatemala 58,620 212,757 71,185 8,912 0 2,099 353,573 Honduras (N) 0 0 15,158 156,722 0 5 171,885 Honduras (S) 13 0 2,243 18,785 40 24,070 45,151 Nicaragua 93 0 0 24,210 3,959 792 29,054 Total 75,324 215,275 101,877 218,772 5,767 36,335 653,350

7-13 Table 7.14 Hinterland transport matrix (with La Union) in 2030(Scenario 1) Hinterland transport matrix with La Union in 2030 (IMPORT: Pacific) (TEU) S Tomas / Pt. Cortes / Acajutla Quetzal Corinto La Union Total P Barrios Pt. Castilla El Salvador (E) 268 8 0 0 0 1,997 2,273 El Salvador (W) 128,358 5,988 537 288 1,855 45,726 182,752 Guatemala 59,770 132,676 44 0 0 178 192,668 Honduras (N) 113 3 3,762 27,168 0 385 31,431 Honduras (S) 86 0 8 25 86 13,268 13,473 Nicaragua 3 0 0 0 26,983 30,600 57,586 Total 188,598 138,675 4,351 27,481 28,924 92,154 480,183 Hinterland transport matrix with La Union in 2030 (IMPORT: Atlantic) (TEU) S Tomas / Pt. Cortes / Acajutla Quetzal Corinto La Union Total P Barrios Pt. Castilla El Salvador (E) 395 63 75 126 24 1,164 1,847 El Salvador (W) 89,625 4,227 34,245 17,197 1,689 35,768 182,751 Guatemala 26,980 47,847 424,867 33,705 0 1,243 534,642 Honduras (N) 0 0 9,376 225,478 0 3 234,857 Honduras (S) 13 0 380 4,011 315 95,934 100,653 Nicaragua 360 0 0 48,404 4,881 2,243 55,888 Total 117,373 52,137 468,943 328,921 6,909 136,355 1,110,638 Hinterland transport matrix with La Union in 2030 (EXPORT: Pacific) (TEU) S Tomas / Pt. Cortes / Acajutla Quetzal Corinto La Union Total P Barrios Pt. Castilla El Salvador (E) 71 0 0 0 0 987 1,058 El Salvador (W) 83,302 2,092 71 20 182 19,467 105,134 Guatemala 34,041 92,735 3 0 0 22 126,801 Honduras (N) 455 23 4,524 11,978 5 3,888 20,873 Honduras (S) 43 0 18 50 136 5,747 5,994 Nicaragua 0 0 0 0 12,464 8,916 21,380 Total 117,912 94,850 4,616 12,048 12,787 39,027 281,240 Hinterland transport matrix with La Union in 2030 (EXPORT: Atlantic) (TEU) S Tomas / Pt. Cortes / Acajutla Quetzal Corinto La Union Total P Barrios Pt. Castilla El Salvador (E) 28 0 0 4 0 1,030 1,062 El Salvador (W) 38,444 4,575 24,215 14,876 2,491 20,529 105,130 Guatemala 143,134 333,642 95,343 8,888 0 6,224 587,231 Honduras (N) 0 0 29,546 243,882 0 3 273,431 Honduras (S) 60 0 1,744 9,313 58 60,650 71,825 Nicaragua 164 0 0 45,975 2,117 880 49,136 Total 181,830 338,217 150,848 322,938 4,666 89,316 1,087,815

7-14 Table 7.15 Projected market allocation for La Union Port in 2020,2030(Scenario 1) Projected market allocation for La Union Port in 2020 (TEU) IMPORT: IMPORT : EXPORT: EXPORT : La Union Port Pacific Atlantic Pacific Atlantic El Salvador (E) 1,006 551 499 513 El Salvador (W) 22,422 15,235 9,528 8,856 Guatemala 0 315 5 2,099 Honduras (N) 1,987 0 2,017 5 Honduras (S) 8,335 51,388 3,573 24,070 Nicaragua 6 1,908 697 792 Total 33,756 69,397 16,319 36,335

Projected market allocation for La Union Port in 2030 (TEU) IMPORT: IMPORT : EXPORT: EXPORT : La Union Port Pacific Atlantic Pacific Atlantic El Salvador (E) 1,997 1,164 987 1,030 El Salvador (W) 45,726 35,768 19,467 20,529 Guatemala 178 1,243 22 6,224 Honduras (N) 385 3 3,888 3 Honduras (S) 13,268 95,934 5,747 60,650 Nicaragua 30,600 2,243 8,916 880 Total 92,154 136,355 39,027 89,316

2) Scenario 2: Change of competitiveness due to increase of 30% in PHC of Acajutla

This scenario increased the cost of cargo handling port terminal currently charged in Acajutla by 30%. Since the objective was to estimate the effect of this increase on the demand of the CA4 Ports, only data that affects cargo-handling charges were considered while other costs and times for Acajutla and the rest of the ports under study were maintained.

Hinterland transport matrix with La Union and projected market allocation for La Union are below. (Case where capacity of Acajutla port is not limited.)

Table 7.16 Hinterland transport matrix with La Union in 2020 (Scenario 2) Hinterland transport matrix with La Union in 2020 (IMPORT: Pacific) (TEU) S Tomas Pt. Cortes / La Acajutla Quetzal / P Corinto Total Pt. Castilla Union Barrios El Salvador (E) 116 12 2 4 10 1,012 1,156 El Salvador (W) 56,394 6,385 639 629 4,717 23,626 92,390 Guatemala 11,200 104,767 15 0 0 23 116,005 Honduras (N) 16 2 1,629 17,398 2 710 19,757 Honduras (S) 13 0 2 13 179 8,262 8,469 Nicaragua 0 0 0 0 34,051 0 34,051 Total 67,739 111,166 2,287 18,044 38,959 33,633 271,828

7-15 Hinterland transport matrix with La Union in 2020 (IMPORT : Atlantic) (TEU) S Tomas Pt. Cortes / La Acajutla Quetzal / P Corinto Total Pt. Castilla Union Barrios El Salvador (E) 158 46 58 124 36 513 935 El Salvador (W) 27,569 2,953 24,619 21,826 2,640 12,783 92,390 Guatemala 6,021 28,961 252,196 34,587 0 147 321,912 Honduras (N) 0 0 2,991 144,646 0 0 147,637 Honduras (S) 0 0 911 44,309 24 18,028 63,272 Nicaragua 69 0 0 20,553 11,190 1,235 33,047 Total 33,817 31,960 280,775 266,045 13,890 32,706 659,193 Hinterland transport matrix with La Union in 2020 (EXPORT: Pacific) (TEU) S Tomas Pt. Cortes / La Acajutla Quetzal / P Corinto Total Pt. Castilla Union Barrios El Salvador (E) 30 4 0 0 0 503 537 El Salvador (W) 37,163 4,567 172 68 686 10,496 53,152 Guatemala 4,335 72,009 2 0 0 2 76,348 Honduras (N) 89 16 2,357 8,988 21 1,655 13,126 Honduras (S) 22 0 3 11 266 3,466 3,768 Nicaragua 0 0 0 0 12,642 0 12,642 Total 41,639 76,596 2,534 9,067 13,615 16,122 159,573 Hinterland transport matrix with La Union in 2020 (EXPORT : Atlantic) (TEU) S Tomas Pt. Cortes / La Acajutla Quetzal / P Corinto Total Pt. Castilla Union Barrios El Salvador (E) 10 0 2 26 0 499 537 El Salvador (W) 12,793 2,676 14,449 13,122 2,536 7,573 53,149 Guatemala 4,247 19,798 287,798 41,607 0 122 353,572 Honduras (N) 0 0 11,795 160,091 0 2 171,888 Honduras (S) 0 0 2,819 38,354 17 3,961 45,151 Nicaragua 51 0 0 24,579 3,858 569 29,057 Total 17,101 22,474 316,863 277,779 6,411 12,726 653,354

7-16

Table 7.17 Hinterland transport matrix with La Union in 2030 (Scenario 2) Hinterland transport matrix with La Union in 2030 (IMPORT: Pacific) (TEU) S Tomas / Pt. Cortes / Acajutla Quetzal Corinto La Union Total P Barrios Pt. Castilla El Salvador (E) 229 24 4 8 20 2,001 2,286 El Salvador (W) 111,551 12,631 1,263 1,243 9,331 46,733 182,752 Guatemala 18,601 174,003 25 0 0 39 192,668 Honduras (N) 25 3 2,592 27,677 3 1,130 31,430 Honduras (S) 20 0 3 20 284 13,143 13,470 Nicaragua 0 0 0 0 57,586 0 57,586 Total 130,426 186,661 3,887 28,948 67,224 63,046 480,192 Hinterland transport matrix with La Union in 2030 (IMPORT: Atlantic) (TEU) S Tomas / Pt. Cortes / Acajutla Quetzal Corinto La Union Total P Barrios Pt. Castilla El Salvador (E) 312 91 114 245 71 1,014 1,847 El Salvador (W) 54,532 5,842 48,699 43,173 5,222 25,285 182,753 Guatemala 10,000 48,100 418,860 57,443 0 245 534,648 Honduras (N) 0 0 4,758 230,101 0 0 234,859 Honduras (S) 0 0 1,449 70,487 38 28,678 100,652 Nicaragua 116 0 0 34,758 18,924 2,089 55,887 Total 64,960 54,033 473,880 436,207 24,255 57,311 1,110,646 Hinterland transport matrix with La Union in 2030 (EXPORT: Pacific) (TEU) S Tomas / Pt. Cortes / Acajutla Quetzal Corinto La Union Total P Barrios Pt. Castilla El Salvador (E) 59 8 0 0 0 995 1,062 El Salvador (W) 73,510 9,035 339 134 1,358 20,761 105,137 Guatemala 7,200 119,596 3 0 0 3 126,802 Honduras (N) 141 25 3,749 14,298 33 2,632 20,878 Honduras (S) 35 0 5 18 423 5,513 5,994 Nicaragua 0 0 0 0 21,379 0 21,379 Total 80,945 128,664 4,096 14,450 23,193 29,904 281,252 Hinterland transport matrix with La Union in 2030 (EXPORT: Atlantic) (TEU) S Tomas / Pt. Cortes / Acajutla Quetzal Corinto La Union Total P Barrios Pt. Castilla El Salvador (E) 20 0 4 51 0 987 1,062 El Salvador (W) 25,304 5,293 28,581 25,956 5,017 14,979 105,130 Guatemala 7,053 32,882 477,990 69,102 0 203 587,230 Honduras (N) 0 0 18,764 254,670 0 3 273,437 Honduras (S) 0 0 4,484 61,013 28 6,301 71,826 Nicaragua 86 0 0 41,567 6,525 962 49,140 Total 32,463 38,175 529,823 452,359 11,570 23,435 1,087,825

7-17 Table 7.18 Projected market allocation for La Union Port in 2020,2030(Scenario 2) Projected market allocation for La Union Port in 2020 (TEU) IMPORT: IMPORT : EXPORT: EXPORT : La Union Port Pacific Atlantic Pacific Atlantic El Salvador (E) 1,012 513 503 499 El Salvador (W) 23,626 12,783 10,496 7,573 Guatemala 23 147 2 122 Honduras (N) 710 0 1,655 2 Honduras (S) 8,262 18,028 3,466 3,961 Nicaragua 0 1,235 0 569 Total 33,633 32,706 16,122 12,726

Projected market allocation for La Union Port in 2030 (TEU) IMPORT: IMPORT : EXPORT: EXPORT : La Union Port Pacific Atlantic Pacific Atlantic El Salvador (E) 2,001 1,014 995 987 El Salvador (W) 46,733 25,285 20,761 14,979 Guatemala 39 245 3 203 Honduras (N) 1130 0 2,632 3 Honduras (S) 13,143 28,678 5,513 6,301 Nicaragua 0 2,089 0 962 Total 63,046 57,311 29,904 23,435

7-18

Chapter 8 Vessel Calling Model

8.1 Ports of El Salvador

8.1.1 Outline of El Salvador Republic of El Salvador faces the Pacific Ocean and borders between the Republic of Guatemala and the Republic of Honduras. Its land area is 21,949 km2 and it has a population of 6.23 million people in 2011 (World Bank data). San Salvador is the capital. Acajutla Port faces the Pacific Ocean while La Union Port is located at the west side of the Gulf of Fonseca connected to the Pacific Ocean via a navigation channel.

Main industries are garment industry whose products are manufactured in Maquiladoras. GDP is USD 23,054 million and Per Capita is USD 3,728.6 in 2011 (Central Bank). GDP has sustained positive growth despite damage inflicted by an earthquake and hurricane after the end of the civil war.

The exports amounted to USD 5,308.8 million (FOB) and the imports to USD 10,118.2 million (CIF) in 2011. Main export goods are garments, coffee and sugar and main import goods are raw and in-process materials such as oil and fertilizer, consumer products and capital goods such as vehicles. Major trading partner countries are USA, Central American countries, Germany and Canada for export, and USA, Central American countries, China and Japan (Central Bank).

8.1.2 Outline of ports of El Salvador Four ports such as Acajutla, La Unión, Corsain and Boyas Alba Petróleos, Cenergica y RASA are listed in the statistics of COCATRAM (2012). Acajutla Port and La Unión Port are commercial ports managed by CEPA. Corsain Ports is a port for fishery activities and managed by CORSAIN. Boyas Alba Petróleos, Cenergica y RASA is a private port owned by Alba Petróleos.

8.1.3 Major facilities of ports In El Salvador, there are no ports with complete advanced loading/unloading systems. La Union Port, which was completed in 2009, is scheduled to be equipped with the country’s only container use quay side gantry crane. Acajutla Port, which handles more cargo than any other port in the country, loads and unloads containers mainly using a ship’s crane, but has no quay side gantry crane. This port is equipped with a bulk unloader, and advanced equipment linked to the storage area in the rear yard by a belt conveyor has been installed and is now operating.

8.1.4 Cargo volume by type In 2012, calling vessels at these ports amounts to 742 and cargo volume through these ports was 5,806 thousand tons. A breakdown of import and export cargo by type is shown in Figure 8.1. Container cargo accounts for 42.5% of export cargo and 18.6% of import cargo. Table 8.1 shows the trend of ship calls and cargo volume of these four ports from 2007 to 2012.

8-1

Cargo Volume by Type (El Salvador) in 2012 Export

Import

0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 10,000 (1000 tons) General Cargo Container Cargo Ro-Ro Cargo Liquid Bulk Solid Bulk Others

Source: JICA study team Figure 8.1 Cargo volume of main ports of El Salvador Table 8.1 Tendency of ship calls and handling cargo of main ports of El Salvador 2007 2008 2009 2010 2011 2012 Ship Call 855 729 651 620 725 742 Cargo Volume Import 1,068 1,211 980 1,204 1,119 1,199 Export 5,087 4,800 3,951 4,187 4,729 4,607 Total 6,156 6,010 4,931 5,392 5,848 5,806 Source: JICA study team

8.1.5 Acajutla Port (1) Overview Acajutla Port is located in western El Salvador on the Pacific coast of the State of Sonsonate near Guatemala. It takes about 2 hours to travel by road from the capital city of San Salvador; about 50 years have passed since it came into use during the 1960s.

Source: Worldatlas Figure 8.2 Location of Acajutla Port

8-2

(2) Port facilities Acajutla Port has three piers jutting into the Pacific to form an “F” (see Figure 8.3). Pier A has a total berth length of 300m and its depth is 12m. The oldest pier, constructed between 1957 and 1960, is now more than 50 years old. It is a steel sheet pile cellar-bulkhead pier, and its side facing the outer ocean is a continuous structure which acts as a breakwater. The inner side is transparent type at fixed intervals (see Table 8.2).

Pier B is an open-type wharf on a vertical piled jetty, with length of 328m on the side facing the ocean and 345m on the side facing the land. It was completed 9 years after pier A. With depth between 10 and 12m it is used mainly by bulk and container vessels. An unloader connected to the back yard by a conveyor belt is installed in the center of pier B, and is used to unload dry bulk cargoes. When no bulk vessels are at the pier, it is used to unload container vessels. Unloading is done on both the left and right sides of the pier.

Pier C was completed 5 years later than pier B. It starts at the tip of pier A, which is the top line of the F-shape. Angled slightly to the land it is 270m in length and its depth is 14m. It is a caisson structure that also acts as a breakwater, preventing waves from flowing into the inner harbor.

Figure 8.3 Port layout

8-3

Table 8.2 Dimension of the pier Apron Pier Length(m) Pier Depth (m) Construction Year Width(m) A 300 12 37 1957-1960 B – outer side 328 12 28 1969 ‐inner side 345 10 C 270 14 19.3 1973-1974 Source: Acajutla Port 1961~ 2013, 52Years Acajutla Port is also equipped with a container yard, bulk unloader, conveyor belt system, a control tower to manage the navigation safety system of vessels entering and leaving the port, fire-fighting vehicles, and security systems based on the ISPS code (see Table 8.3).

Table 8.3 Major facilities of Acajutla Port Facility/Equipment Specification Number Note Grain Silo 18,000t 1 Grain Warehouse 12,000t 1 Roofed warehouse /General Cargo 117,000t 1 Container Yard 2,788TEUs 1 Vehicle Yard 2,000 cars 1 Emergency Powerplant 1,176KVA 1 Tugs 2 Straddle Carrir 5 Spreaders (From 20 'and 40') 20ft-5, 40ft-7 12 Loading Un-loading Unit (AAU) 450t/h 1 Conveyor System 1 Forklifts 2.7t~25t Wagons 30~50t Serveilance Camera 43 Source: Acajutla Port 1961~2013, 52 Years

(3) Port activities 1) Cargo throughput a) Total cargo

Cargo handled by the port is classified into 4 categories: general cargo, containerized cargo, dry bulk, and liquid bulk. Total cargo volume reached 3.96 million tons in 2012, a 36% increased from 2003, but still a 11% decrease from 2008. It increased steadily for 6 years from 2003 until 2008, but the world economic recession caused by the Lehman shock of 2009 caused it to fall by 24% from the previous year. A recovery the following year restored throughput to more than 4 million tons in 2011, equivalent to the level achieved prior to the Lehman Shock (see Table 8.4). Imports represent 71% of total trade while exports account for 29%.

8-4

Table 8.4 Transition of total cargo volume in the last 10 years (Unit: tonnes) Cargo Type 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Import General Cargo 307,977 292,870 255,067 327,349 266,176 277,171 53,280 127,675 154,500 148,546 Containarized Cargo 310,821 453,372 534,028 684,572 780,837 823,501 690,744 781,950 915,974 788,010 Dry Bulk 1,216,942 1,256,900 1,411,050 1,512,140 1,522,860 1,363,816 1,164,247 1,338,799 1,508,263 1,353,986 Liquid Bulk 479,709 523,877 581,030 883,170 776,204 813,220 572,004 384,864 493,456 538,153 Import Total 2,315,449 2,527,019 2,781,175 3,407,231 3,346,077 3,277,708 2,480,275 2,633,288 3,072,193 2,828,695 Export General Cargo 14,098 10,300 5,637 1,024 543 6,975 527 5,697 1,797 5,435 Containarized Cargo 159,733 234,321 261,889 286,697 401,046 471,500 401,812 516,365 615,086 489,907 Dry Bulk 278,487 249,389 344,646 321,442 251,787 244,574 265,481 322,448 281,763 323,771 Liquid Bulk 150,573 174,712 215,381 409,537 372,927 434,800 235,324 228,324 178,320 309,758 Export Total 602,891 668,722 827,553 1,018,700 1,026,303 1,157,849 903,144 1,072,834 1,076,966 1,128,871 Import+Export Total 2,918,340 3,195,741 3,608,728 4,425,931 4,372,380 4,435,557 3,383,419 3,706,122 4,149,159 3,957,566 Source: Acajutla Port Statistiucs 2012

Source: Prepared by the Study Team based on the data from Acajutla Port Statistics 2012 Figure 8.4 Transition of import / export cargo volume by category b) Cargo handling by type and pier

Cargoes handled by Acajutla Port using the three piers and the petroleum receiving pipe installed offshore are loaded and unloaded. Table 8.5 shows quantities of cargoes handled in 2012 by type and by pier. Containers handled mainly by berth A-2 and C-7/8 account for 78% of total container volume. Most dry bulk is handled by piers B and C. Among types of liquid bulk, petroleum is received from the offshore buoy, molasses etc. are handled by pier A while others are handled by pier C.

8-5

Table 8.5 Cargo handling by type and pier (Unit: tonnes) Pier Cargo Type A-1 A-2 B-3 B-4 B-5 B-6 C-7/8 Total Container 0 624,806 8,927 31,280 19,322 219,005 374,577 1,277,917 General Other General Cargo Cargo 3,033 49,169 2,990 5,477 11,505 49,847 31,960 153,981 Total 3,033 673,975 11,917 36,757 30,827 268,852 406,537 1,431,898 Liquid Bulk 212,586 301,825 0 0 0 0 284,062 798,473 Dry Bulk 0 88,156 238,504 543,358 57,010 38,646 699,776 1,665,450 Mixed Cargo 0 8,515 0 31,925 0 0 21,305 61,745 Total 215,619 1,072,471 250,421 612,040 87,837 307,498 1,411,680 3,957,566 Percentage by Berth 5.4% 27.1% 6.3% 15.5% 2.2% 7.8% 35.7% 100% Percentage by Pier 32.5% 31.8% 35.7% 100% Source: Acajutla Port Statistics 2012

c) Container cargo in TEUs

Container cargoes handled at Acajutla Port came to 160,000 TEU in 2012: 82,000 (51%) TEU of imports, and 78,000 (49%) TEU of exports. Containers also fell by 19% in 2009 as a result of the Lehman Shock, but in 2011 they had quickly recovered to a higher level than before the Lehman Shock (see Table 8.6 and Figure 8.5).

Table 8.6 Transition of container cargo in the last 10 years (Unit: TEUs) 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Import 32,816 47,541 54,332 65,146 76,431 79,575 64,516 64,516 84,259 81,939 Export 32,760 45,316 49,151 58,183 68,027 76,748 61,853 71,913 75,810 77,940 Total 65,576 92,857 103,483 123,329 144,458 156,323 126,369 136,429 160,069 159,879 Source: Acajutla Port Statistiucs 2012

Source: Prepared by the Study Team based on the data from Acajutla Port Statistics 2012 Figure 8.5 Transition of container cargo

Table 8.7 and Table 8.8 show origin countries of import and export commodities in container cargoes in 2012. Volume of trade with China (27.3%) and the United States (25.0%) was high,

8-6 with these two countries supplying more than half of all imports. Concerning major import products, the port imported large quantities of apparel materials, paper, tires, fruit, canned goods, and miscellaneous items from the United States, and large quantities of apparel materials, metal products, and electrical appliances from China (see Table 8.7).

Among destination countries of exports, the United States was first (47.7%) followed by Chile (5.6%), Taiwan (5.6%), and South Korea (4.3%). The top products exported to the United States were apparel, coffee, and frozen foods. The top exports to Chile were apparel, frozen foods, and used paper, etc. For Taiwan and South Korea, the top exports were apparel and coffee respectively (see Table 8.8).

Table 8.7 Origin countries of import container by commodities in 2012 ESTADOS UNIDOS TAIWAN‐ SOUTH HONG PRODUCTOS CHINA MEXICO CHILE TAIWAN PERU INDIA SINGAPUR ESPAÑA AUSTRALIA JAPON PANAMA CANADA Total DE FORMOSA KOREA KONG AMERICA DESPERDICIOS DE PAPEL O CARTON 21,172.49 59.55 0.10 15.89 21.64 21,269.67 MATERIA PRIMA P/INDUSTRIA DEL TEXTIL 1,457.58 7,556.02 4,452.00 968.92 763.92 546.61 12.03 837.18 437.42 22.97 8.50 17.72 44.89 17,125.76 RESINAS 102.72 49.01 463.67 10,493.88 157.23 2,760.61 356.68 14,383.80 FERRETERIA 1,424.02 6,339.55 2,776.95 820.96 545.44 188.82 204.62 572.41 319.22 98.28 16.58 310.02 53.94 55.49 123.05 4.85 13,854.20 PAPEL EN RESMA, FARDOS O PLIEGOS 4,272.01 556.54 74.28 0.44 110.51 1,420.48 5.15 149.38 1,649.75 311.32 35.55 339.23 8,924.64 LLANTAS DE HULE O CAUCHO 2,330.32 1,391.65 116.84 498.86 1,186.05 35.78 35.88 27.56 111.39 209.59 1,631.03 65.66 526.58 8,167.19 PRODUCTOS ELECTRICOS Y ELECTRONICOS 302.89 3,706.49 2,278.51 233.29 787.31 56.94 97.51 25.41 165.87 96.76 35.38 65.68 4.32 23.16 187.46 53.97 8,120.95 FRUTAS 1,659.71 48.54 20.49 5,291.26 21.01 21.80 102.95 7,165.76 QUIMICOS EN SACOS 450.67 2,609.26 482.80 535.09 765.16 32.08 60.98 95.62 18.76 716.10 5.60 39.81 5,811.93 ARTICULOS DE PLASTICO Y SIMILARES 333.56 1,586.05 853.88 634.86 76.35 55.47 688.36 866.68 312.74 46.35 37.06 21.69 38.07 15.72 20.18 5,587.02 TELAS 552.96 2,148.25 630.57 589.69 384.30 50.65 29.67 184.58 19.20 19.63 4,609.50 TEXTILES,PRENDAS DE VESTIR Y CUERO 386.71 2,004.36 329.82 455.65 226.21 204.32 16.88 309.80 191.06 18.41 249.97 4,393.19 REPUESTOS P/VEHICULOS 636.56 1,211.48 160.38 833.43 678.25 27.72 130.39 25.58 141.68 16.22 399.57 45.70 4,306.96 ARTICULOS PARA EL HOGAR 877.13 2,139.07 461.79 49.60 62.51 34.61 138.46 89.13 28.05 36.40 1.28 236.98 10.46 4,165.47 ALIMENTOS ENLATADOS 1,386.72 458.96 533.78 136.94 171.84 29.31 34.68 103.41 6.29 8.80 109.79 2,980.52 MOTOS 0.54 2,197.19 29.23 25.30 21.33 155.37 302.07 0.26 56.62 2,787.91 POLIPROPILENO 118.49 63.92 950.61 244.19 102.50 1,048.57 2,528.28 CARGA GENERAL 1,283.48 619.27 98.74 58.11 140.21 52.48 11.06 26.13 19.85 24.67 118.90 8.10 1.28 37.61 27.09 2,526.98 PRODUCTOS FARMACEUTICOS 380.27 736.55 661.91 20.57 178.87 107.52 1.60 45.43 1.48 61.34 44.32 92.50 72.98 19.33 46.74 17.44 2,488.85 DETERGENTES Y SIMILARES 18.51 2,424.93 41.26 2,484.70 PULPA O PURE DE FRUTAS NATURAL 431.94 62.13 39.68 1,810.66 0.04 2,344.45 ALUMINIO 19.79 792.16 423.30 19.32 5.60 16.84 190.33 708.54 22.95 71.42 2,270.25 CALZADO 303.34 1,480.06 26.08 7.31 6.06 9.43 282.56 3.50 150.13 2,268.47 PRODUCTOS LACTEOS 569.26 143.92 409.80 127.52 807.25 145.68 2,203.43 ALIMENTOS PARA ANIMALES 175.98 1,808.38 18.99 70.18 2,073.53 LAMINA EN BOBINAS 83.08 373.77 23.26 1,365.28 40.69 138.78 2,024.86 VIDRIO EN LAMINAS 74.27 1,045.52 729.40 50.00 7.70 1,906.89 MADERA 41.59 1,218.01 58.43 0.80 26.50 412.12 22.29 28.59 1,808.33 MUEBLES 312.94 1,017.58 122.65 95.97 53.33 50.17 3.47 37.85 1,693.96 ACIDOS 22.70 483.99 34.33 21.17 98.12 166.40 105.48 15.34 219.20 1,166.73 CERAMICA 16.33 610.64 3.44 2.50 341.68 168.25 1,142.84 Total general 41,080.07 44,985.52 17,880.75 16,504.10 8,695.05 10,575.06 4,936.09 3,394.27 3,316.12 2,740.01 2,027.53 1,711.02 1,606.28 2,348.36 1,697.18 1,089.61 164,587.02 Source: Prepared by Acajutla Port officials

Table 8.8 Destination countries of export container by commodities in 2012 ESTADOS PAISES SOUTH HONG PUERTO Productos UNIDOS DE CHILE TAIWAN PANAMA JAPON CHINA MEXICO POLONIA ECUADOR VENEZUELA PERU ESPAÑA BAJOS Total KOREA KONG RICO AMERICA HOLANDA FRUTAS 51,873.85 34.92 598.58 136.25 54,046.18 TEXTILES,PRENDAS DE VESTIR Y CUERO 14,815.31 4,400.10 5,794.52 1,063.33 500.60 3,613.59 1,615.39 771.11 1,166.32 501.70 20,602.56 CAFE ORO LAVADO 7,844.18 156.15 1,622.45 6,222.64 263.72 847.20 217.13 19.00 46.22 42.16 19,269.62 ALIMENTOS CONGELADOS 6,186.70 2,518.83 2,874.48 463.31 1,608.12 258.93 3,107.02 1,799.66 1,708.92 129.63 16,836.78 CHATARRA EN PACAS 1,756.13 14.70 6.58 194.27 0.51 8.82 8.26 7.82 29.83 15,911.74 ALIMENTOS ENLATADOS 1,739.77 19.17 141.71 4,407.58 73.23 76.67 15,705.04 CERVEZA 1,687.32 241.04 42.68 116.17 159.81 212.66 87.99 11,447.22 MADERA 1,150.53 24.04 174.95 19.60 223.59 216.36 23.03 6,956.87 DESPERDICIOS DE PAPEL O CARTON 890.32 2,646.94 94.84 5.35 2,753.67 CARNES CONGELADAS 607.98 941.89 21.78 66.46 254.04 225.68 8.16 12.10 82.67 21.53 2,230.40 FRIJOL 601.77 19.39 36.00 142.34 50.62 2,073.15 MATERIA PRIMA P/INDUSTRIA DEL TEXTIL 533.34 1,825.40 96.71 1,981.93 FERRETERIA 438.51 1,932.89 RECIPIENTES 394.95 1,447.72 1,486.33 GALLETAS 387.11 66.25 128.55 179.29 321.90 3.07 19.40 1,167.07 CUEROS SALADOS 273.00 758.80 158.62 95.68 1,074.08 CAMARONES 270.24 44.25 206.42 89.99 4.40 41.03 1,016.82 Total general 91,451.01 10,808.28 10,702.56 8,364.37 4,692.88 4,693.65 4,484.77 4,049.61 3,613.59 2,558.30 2,541.85 2,298.49 1,976.75 1,432.85 1,305.64 1,018.23 191,584.39 Source: Prepared by Acajutla Port officials

8-7

2) Ship calling Most cargo ships calling at Acajutla Port were container ships. A total of 269 container ships called in 2012, followed by 115 dry bulk ships, 83 general cargo ships, 78 liquid bulk ship and 7 mixed ships. A total of 82 liquid bulk ships docked at the offshore petroleum buoy (see Table 8.9).

Table 8.9 Ship calls by type in 2012 Type of Cargo Items General Cargo Container Dry Bulk Liquid Bulk Mixed Total Calling Vessels at Pier by Tonage and Numbers DWT (MT) 1,915,976 6,928,816 4,728,352 2,466,637 343,339 16,383,120 Average DWT of Vessels (MT) 23,084 25,758 41,116 31,624 49,048 - No's of Vessels (Ship) 83 269 115 78 7 552 Calling Vessels at Offshor Bouy by Tonage and Numbers No's of Vessels 82 82 Sours: Acajutla Port Statistics 2012

The numbers of container ship calling each month by shipping line are shown in Table 8.10. A total of 100 Maersk Line ships called during the year, which is an average of about 2 each week. APL ships called at a rate of 1 per week, and NKY ships called at a rate of 1 to 1.5 every 2 weeks.

Table 8.10 Monthly container ship calls by shipping line in 2012 (Unit: ship)

Shipping Line Total July May June April March August January October February September November December

Maersk Line 989789889898100 APL(American President Line) 45744545445455 NYK Line 45332232333235 CSAV (Compania Sudamericana de 23132222222225 Agencia de Vapores) CMA-CGM Line 12222232221223 HapagLLoyd Line 3 2211111212320 Evergreen Line 222200000001 9 Hamburg Sud 100000000000 1 Total 262726221921212022202222268 Source: Acajutla Port Statistics 2012

8-8

3) Berth assignment

Berthing hours by type of ship and by berth are shown in Table 8.11. Container ships most often used berth A-2 followed by C-7/8 and B-6. Dry bulk ships used C-7/8 and B-4, while liquid bulk ships used A-1, A-2, and C-7/8 almost equally. This is the case because a pipe is installed to transmit liquid bulk.

Table 8.11 Berth assignment of pier by commodity category in 2012 Type of Cargo Items General Cargo Container Dry Bulk Liquid Bulk Mixed Total Vessel Berthing Hour at Pier by Commodities (Unit: hour) A-1 13.4 0.0 0.0 1,009.4 0.0 1,022.8 A-2 144.8 2,104.3 336.1 1,210.2 33.0 3,828.3 B-3 11.5 33.6 791.5 0.0 0.0 836.6 B-4 66.1 129.2 1,636.3 0.0 193.0 2,024.6 B-5 174.6 82.6 226.2 0.0 0.0 483.4 B-6 227.4 854.7 171.5 0.0 0.0 1,253.7 C-7/8 170.7 1,331.2 2,471.3 952.9 116.7 5,042.7 Total Hours 808.5 4,535.6 5,632.9 3,172.4 342.7 14,492.1 Sours: Acajutla Port Statistics 2012

(4) Capacity of container handling 1) Management of container operation

The piers in Acajutla Port were constructed about 50 years ago and structural limitations prevent the installation of cranes to handle containers, so containers are loaded/unloaded using a ship’s crane. Chassis trucks carrying containers to the back yard are provided by private stevedore companies. For each operation, about 10 trucks are used by each gang.

Loading and unloading container cargo is done mainly at berth A-2, B-6 and C-7/8, but the handling efficiency per hour per ship’s crane is 13.5 boxes/1 ship’s crane/hour. The cargo handling system is contracted out to a private stevedore company.

It takes about 10 minutes for a truck to carry a container to the container yard from the pier. Its area is about 40,000m2, its storage capacity is 2,500 TEU, and reefer plugs are installed at 120 locations.

The average number of days containers dwell in the container yard is 8 days for imported containers, 4 days for imported reefer containers, 4.5 days for exported containers, and 3 days for exported reefer containers. The empty container ratio is 1% for imports and 33% for exports.

2) Container handling capacity

Factors determining container handling capacity of a container terminal are the handling capacity of the gantry cranes, harbor cranes and other cargo handling machinery at the berths plus the size and handling capacity of the container yard where containers are stored for handling. The handling capacity of a container terminal is the smaller values of quay side capacity or container yard capacity.

8-9 a) Quay side capacity

In Acajutla Port there are three piers: A, B, and C. Pier A is 300m (150m each for A-1 and A-2) in length. Pier B is constructed so both sides are used, and the offshore berths, B-3 and B-4, are 328m in length, while the inland side piers, B-5 and B-6 are 345m in length. Pier C is 270m long. Table 8.12 shows the Berth assignment of pier by commodities in 2012.

The berth occupancy rates of each pier are 12% for A-1, 44% for A-2, 10% for B-3, 23% for B-4, 6% for B-5, 14% for B-6, and 58% for C. Typically, when BOR reaches approximately 60%, usage of the berth is high and congestion gradually begins; when BOR exceeds 65%, construction of a new berth is usually required.

A-2, B-6 and C-7/8 berths mainly handle container cargo and BOR of each berth are 24%, 10% and 26%. However, other cargo such as general cargo, bulk cargo and mixed cargo are handled at those berths so the overall BOR values of each berth are 44%, 14% and 58% respectively. Berth C-7/8 is already in a state of high usage while it would be difficult to significantly increase the volume of containers handled at berth B due to the installation of a bulk unloader with conveyor system at the middle of the pier. Berth A-2, however, can still handle more containers (see Table 8.12).

Table 8.12 Berth assignment of pier by commodity in 2012

Vessel Type (hours) BOR Pier Berth Length (m) Total General Container Bulk Tanker (Liquid Bulk) Mixed (%) A-1300 150 A 13 0.2% 0 0.0% 0 0% 1,009 12% 0 0% 1,023 11.7% A-2 150 145 1.7% 2,104 24.0% 336 3.8% 1,210 14% 33 0.4% 3,828 43.7% B-3 673 328 12 0.1% 34 0.4% 791 9.0% 0 0.0% 0 0.0% 837 9.6% B-4 B 66 0.8% 129 1.5% 1,636 18.7% 0 0.0% 193 2.2% 2,025 23.1% B-5 345 175 2.0% 83 0.9% 226 2.6% 0 0.0% 0 0.0% 483 5.5% B-6 227 2.6% 855 9.8% 172 2.0% 0 0.0% 0 0.0% 1,254 14.3% C-7/8 270 270 C 171 3.4% 1,331 26.4% 2,471 49.0% 953 18.9% 117 2.3% 5,043 57.6% Total berthing - time (hours) 808 6% 4,536 31% 5,633 39% 3,172 22% 343 2% 14,492 Source: Annual Report of Acajutla Port in 2012 The value of expected container increase in TEU is considered based on the condition of difference between present berth assignment and the upper limit value of BOR (65% is adopted). Regarding container handling efficiency of quay-side, one ship-gear handles 13.5 boxes per hour which is equal to 22 TEUs based on 40ft container ratio (62%). Generally, a ship is equipped with two ship-cranes and thus the container handling efficiency becomes 44 TEUs/hour while container handling hours are calculated at 3,634 hours (159,879 TEU/44 TEU/hour) per year at the berth compared with 4,536 hours based on the statistics of Acajutla Port. In this case, workable time at the berth account for about 80% of the berthing time with the remaining time being used for preparations such as mooring works etc.

Container throughput by berth in TEUs is calculated by dividing the total container volume by berthing time. Expected increase in berthing time of container is calculated by deducting the present berthing time from the berthing time in the case of a BOR of 65%. In addition, expected increase in working time is 80% of expected increase in berthing time. Expected increase in container becomes 36,115 TEU (159,879 TEU x (821/3,634)) in Berth A-2, 6,054 TEU (159,879 TEU x (138/3,634)) in Berth C-7/8, totally 42,000 TEU and thus overall capacity of the quay side is estimated at 202,000 TEU per annum (see Table 8.13). 8-10

Table 8.13 Expected berthing/working time and container increase A-1 A-2 B-3 B-4 B-5 B-6 C-7/8 Total

Container throughput (TEUs) 0 74,159 1,198 4,547 2,925 30,136 46,914 159,879

Berthing time (hours/year) 0 2,104 34 129 83 855 1,331 4,536 Working time at the berth 0 1,685 27 103 66 685 1,066 3,634 (hours/year) Expected increase in berthing 0 1,026 0 0 0 0 172 1,198 time (hours) Expected increase in working 0 821 0 0 0 0 138 958 time (hours) Expected container increase 0 36,115 0 0 0 0 6,054 42,170 in TEU (TEUs) Quay side container capacity 202,000 in TEU (TEUs) Source: Prepared by the Study Team

b) Container yard capacity Since containers are handled and stored in the container yard, the annual cargo handling capacity of a container terminal is determined by the storage capacity and turnover rate of the container at the yard. The handling capacity of a container yard can be calculated based on the following factors.

1. Number of container storage ground TEU slots in the container yard 2. Number of container stacking height 3. Container Yard (CY) Peak Factor: The ratio of the monthly maximum quantity handled and the average monthly quantity handled 4. Dwelling days in the container yard 5. Annual number of days of operation of the container yard 6. Annual turnover rate The number of container storage ground TEU slots of Acajutla Port is 1,390. As a straddle carrier system is adopted in the container yard, maximum stacking height of the containers should be 3.0 high. Dead Max CY Capacity of Acajutla Port becomes 4,170 TEU/time, then Workable Max CY Capacity becomes 3,128 TEU/time (75% of the Dead Max CY Capacity), and Sustainable Max CY Capacity becomes 2,463 TEU/time, assuming 1.27 as CY peak factor.

Based on the sustainable max CY capacity per time (2,463 TEU), annual capacity of the port becomes 183,000 TEU when average CY dwell-days for containers are 4.9 days. On the other hand, CEPA’s declared Port Capacity is 145,000 TEU per annum.

Table 8.14 shows the results of the calculation.

8-11

Table 8.14 Container handling capacity (Unit: TEUs) Stacking Yard handling Dead Max CY Workable Max CY Sustainable Max Annual CY yard system Capacity Capacity CY Capacity Capacity Main yard Straddle carrier 4,170 3,128 2,463 183,000 Remarks: 1. Number of container storage ground TEU slots in the container yard: 1,390 Slots 2. Number of container stacking height : 3 levels 3. Container Yard (CY) Peak Factor : 1.27 4. Dwelling day in the container yard : 4.9 days 5. Annual number of days of operation of the container yard : 365 days 6. Annual turnover rate : 74.5 Source: Prepared by the Study Team

CEPA plans to introduce measures for increasing the volume of container cargo through Acajutla Port. With these measures, the yard can be used to handle 183,000 TEU per year. It will be possible to secure capacity of 26,000 TEU/year (75%×35,000 TEUs) by reallocating 11,000m2 of unused space between warehouses in the yard as container yard space. Increasing the number of stacking levels in the yard from 3 to 4 is also being studied, and the two renovated straddle carriers are being upgraded for use with 4 levels. This will increase the yard capacity to about 61,000 TEU/year (75%×81,500 TEU) and overall capacity to approximately 270,000 TEU per annum (See Figure 8.6).

JICA Study Team

Figure 8.6 Container yard layouts

8-12

(5) Diagnosis survey of deterioration degree of berth in Acajutla Port

1) Each berth of Acajutla Port

Acajutla Port has three berths: A, B and C. The oldest berth was constructed 53 years ago and the newest one 39 years ago. Their structures are cell, steel pipe pile and caisson types. The locations of the berths are shown in Figure 8.7. A general plan view and cross section of each berth are shown in Figure 8.8, Figure 8.9, and Figure 8.10. Also, Features of port facilities in Acajutla Port are shown in Table 8.15.

C Berth

B Berth

A Berth

Source: CEPA

Figure 8.7 Location of each berth

Source: CEPA

Figure 8.8 General plan view of A berth

8-13

Source: CEPA

Figure 8.9 Cross section of B berth

Source: CEPA

Figure 8.10 Cross section of C berth

Table 8.15 Port facilities and present status in Acajutla Port Berth A berth B berth C berth Year constructed 1957 to 1960 1969 1973 to1974 Structure Cell type Steel pipe pile type Caisson type Heaviest Allowable A1,2,3: B1,2,3: 3.5ton/m2 Load 3.0ton/m2 0.815ton/m2 A4,5:AASHTOH※ B4:1.56ton/m2 20-S16 Age (years) 53 44 39 Present situation Repair works for steel No repairs are No repairs are sheet pile portion are being currently scheduled currently scheduled undertaken Repair Performed as needed Performed as needed Performed as needed Current Cathodic External power supply External power supply Status protection method method Steel Painting on steel sheet piles Painting on steel pipe structures Now repairing on steel piles sheet pile portion Concrete Painting on concrete Painting on concrete side surface ※AASHTO：American Associations of State Highway and Transportation Officials Source: CEPA, JICA Study Team

8-14

2) Diagnosis survey of deterioration degree a) Visual and hammering inspection Visual and hammering inspections were performed from a boat for the substructures of A, B, and C berths. Continuous red-orange colored rust was observed on steel sheet piles in A berth as shown in Figure 8.11.

source: JICA study team Figure 8.11 Continuous red-orange colored rust on steel sheet piles in A berth

Rust could not be observed on steel pipe piles in B berth. Although something like red rust is observed as shown in Figure 8.12, it is assumed to derive from the anticorrosive paint of base black paint which has peeled off.

Figure 8.13 shows peeling of the side surface of slab concrete underneath of A berth.

Figure 8.14 shows that neither cracks nor rust can be observed from painted surface of C berth facing to outer sea.

Figure 8.15 shows the hammer inspection on steel sheet piles in A berth.

source: JICA study team Figure 8.12 Situation of steel pipe piles in B berth

8-15

Source: JICA Study Team

Figure 8.13 Peeled off concrete in A berth

Source: JICA Study Team

Figure 8.14 Concrete wall facing to outer sea in C berth

Source: JICA Study Team

Figure 8.15 Hammer inspection on steel sheet piles in A berth b) Schmidt hammer test

Concrete strength measurement was performed by Schmidt hammer on concrete beam of substructure in A berth slab and apron concrete portion in C berth. Figure 8.16 shows the location of the tests. Position for performing Schmidt hammer test is shown in Figure 8.17. Position for A berth is shown in Figure 8.18 and that for C berth is shown in Figure 8.19.

8-16

Results of Schmidt hammer tests are shown in Table 8.16. Tests were conducted at 15 points at each site. The five points where the obtained values were exceedingly low or high were excluded and then the average value was obtained from the remaining ten points.

C Berth

B Berth

A Berth

Source: JICA Study Team

Figure 8.16 Test points performed by Schmidt hammer

A berth : C berth： Concrete Slab

Schmidt Hammer Schmidt hammer

Concrete Slab

Figure 8.17 Position of Schmidt hammer

Source: JICA Study Team

Figure 8.18 Position of Schmidt hammer for A berth

8-17

Source: JICA Study Team

Figure 8.19 Position of Schmidt hammer for B berth

Table 8.16 Test results by Schmidt hammer Compressive Compressive Compressive Rebound Rebound Rebound Point No. Strength Point No. Strength Point No. Strength (α＝+90°） (α＝‐90°） (α＝‐90°） (kg/cm2) (kg/cm2) (kg/cm2) Pier A 1 46 390Pier C 1 43 440Pier C 1 48 530 2 48 420 2 44 460 2 46 490 (Bottom 3 46 390(End of 3 52 580(Center of 3 33 290 of Beam 4 50 460Superstru 4 40 390Sperstruct 4 41 410 between 5 39 280 cture at 5 48 530 ure at the 5 33 290 Cells) 6 44 360 the 6 46 490 side of 6 28 220 7 45 370 center of 7 44 460 outer 7 33 290 8 45 370 width) 8 40 390 sea） 8 28 220 9 50 460 9 44 460 9 28 220 10 48 420 10 44 460 10 28 220 11 50 460 11 43 440 11 19 - 12 44 360 12 46 490 12 28 220 13 47 410 13 49 540 13 33 290 14 51 480 14 44 460 14 45 480 15 48 420 15 49 540 15 28 220 Average of 10 point 391 Average of 10 point 469 Average of 10 point 248 Source: JICA Study Team

8-18

c) Survey Result

Survey results are shown in Table 8.17. Table 8.18 shows the appraisal in consideration of the survey results.

Table 8.17 Survey result of visual and hammering inspection for diagnosis survey of deterioration degree of the Acajutla Port facility Deterioration Survey A Berth B Berth C Berth Date surveyed April 13, 2013 April 13, 2013 April 13, 2013 Steel structure Steel sheet piles： Steel pipe piles: Continuous red-orange No rust is observed (Figure colored rust is observed. 8.12) ― (Figure 8.11) Visual inspection Concrete structure Slab concrete side surface： Slab concrete ： Concrete side surface： Partial peeling and falling are Neither cracks nor rust are Neither cracks nor rust are observed (Figure 8.13) observed observed (Figure 8.14)

Steel structure Steel sheet piles：

8-19 Heavy rusting is observed. (Figure 8.15) ― ― Hammering test Concrete structure Concrete side surface ： No weak sections are ― ― observed

Result 391kg/cm2 469kg/cm2 (Head) （Figure 8.16） ― 248kg/cm2 (Middle) Test by (Figure 8.17) Schmidt Member PC Girder between sells Surface of upper slab hammer ― Judgment Good ― Good

Source: JICA Study Team

8-19

Table 8.18 Appraisal of the Remaining Service Life based on the Survey Results of the Acajutla Port Facility

Appraisal item A berth B berth C berth Steel Steel sheet piles： Steel pipe pile: structure Performance of members is No deformation is observed. ― considered to be lowered.

Deterioration Concrete Slab concrete side surface ： Slab concrete: Concrete side level structure Performance of members is No deformation is surface: considered to be lowered. observed. No deformation is Slab bottom: observed. No deformation is observed.

Steel Steel sheet pile part: Facility Steel pipe pile: structure performance is considered to No deterioration of facility be deteriorated. performance is observed but ― ongoing observation is required. 8-20 Facility Concrete Slab concrete side surface: Slab concrete: structure Facility performance is No deterioration of facility Concrete side surface: considered to be deteriorated. performance is observed but No deterioration of facility performance is observed but ongoing observation is ongoing observation is required. required. Steel Steel sheet pile: Steel pipe pile: structure Performance deterioration is No deformation is observed observed and immediate though 44 years have passed Remaining inspection is required to since its construction, ― service life ensure safety. periodical inspection should be continued under the present maintenance management.

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Appraisal item A berth B berth C berth Concrete Slab concrete side surface: Slab concrete: Concrete side surface: structure Performance deterioration is No deformation is observed No deformation is observed observed and immediate though 44 years have passed though 39 years have passed Remaining inspection is required to since its construction, since its construction, service life ensure safety. periodical inspection should periodical inspection should be continued under the present be continued under the present maintenance management. maintenance management.

Steel Steel sheet piles ： Steel pipe pile: structure Immediate repair on design Accumulation of data by section is required. periodical inspection is ― required for future counter measure. Counter measure Concrete Slab concrete side surface： Slab concrete: Accumulation Concrete side surface: structure Immediate repair to original of data by periodical Accumulation of data by

8-21 design section is required. inspection is required for periodical inspection is future counter measure. required for future counter measure.

Steel Steel sheet piles： Steel pipe pile: structure Currently being repaired to No special repair work is ― meet original design standard. being done. Maintenance status Concrete Slab concrete side surface： Slab concrete: Concrete side surface: structure It is scheduled to be repaired No special repair work is No special repair work is to meet original design being done. being done. standard. Source: JICA Study Team

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d) Consideration on the remaining service life of port facilities at Acajutla Port

Concerning A berth, CEPA performed periodical inspection such as measuring thickness of steel materials and is conducting patching or other applying other repair methods to meet the original design standard. The section in A berth where concrete has fallen off is scheduled to be repaired based on the original design. Therefore, the current structural problems are being addressed which will extend the service lives of the facilities. B and C berths are relatively well maintained in spite of the advanced age of the structures. It is required to continue current maintenance management in future.

Accordingly, based on inspection results and the age of berths, it is assumed that these facilities can be used for a period of 5 to 10 years if the current maintenance system continues to be followed. CEPA has no plan of large scale rehabilitation or expansion of the existing facilities but the service life of facilities can be extended through repair works. In order to predict the remaining life of steel structures, measuring the thickness of steel material thickness using cathodic protection as at the steel pipe pile for B berth are effective measures. The use of anti-corrosive paint to protect concrete structures from sea water is an effective measure which has already been introduced. In order to predict the remaining service life of concrete structures, methods using nondestructive testing equipment such as breaking a part of collected core for measuring penetration depth of chloride ion in the concrete, visually observing salt damage or alkali-silica reaction etc. can be applied.

In order to perform proper maintenance management of facilities in Acajutla Port, it is important to perform periodical inspections (measuring thickness of steel materials, penetration depth of alkali-silica in concrete or etc.) and compile obtained data which can then be used to predict maintenance needs for the next 10 to 20 years.

(6) Port development plan CEPA has no plan to expand the container terminal in Acajutla Port, but the construction of a 200 MW capacity electric power plant fueled by gas inside the port area has been proposed (see Figure 8.20). This plan includes the construction of a gas pipeline from Pier C to provide natural gas as fuel.

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Source: Acajutla Port 1961~2013, 52 Years Figure 8.20 Planned electric power plant

(7) Road network from/to Acajutla Port The road network linked to the port is a lifeline as important or even more important than the port facilities, in that it permits the smooth distribution of cargoes handled by the port. Figure 8.21 shows the road network from/to Acajutla Port. It is 85 km from this port to San Salvador, which is the capital city and an area of concentrated industries, 45km to Hachadura on the border with Guatemala, 205 km to Quetzal Port on the Pacific Coast of Guatemala, 209 km to San Jose on the Atlantic side, and 527 m to Santo Tomas. And it is 273 km to Amatillo on the border with Honduras, and 486km to Cortes Port on the Atlantic Coast of Honduras.

Source: Acajutla Port 1961~2013, 52 Years

Figure 8.21 Road network from / to Acajutla Port

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8.1.6 La Union Port (1) Overview La Union Port is located in La Union Department in the east end of El Salvador about 185km from the capital, where it faces the Gulf of Fonseca. It is counted on to be a base which will stimulate industrial development in the eastern part of El Salvador to improve its slow economy. It has been developed as a new port with container handling as its principal role. Financed by yen loans provided by Japan, construction began in 2005 and was completed in 2009. The port opened in 2010 (See Figure 8.22).

La Union Port

Gulf of Fonseca

Source: Google earth

Figure 8.22 Location of La Union Port

(2) Port facilities La Union Port consists of a container berth (total length of 340m and depth of 14m), a multi-purpose berth (total length of 220m and depth of 14m), and a passenger vessel berth (total length of 240m and depth of 9.5m). Major cargo loading/unloading machines consist of five straddle carriers, 10 truck-chassis, and 5 reach stackers. A quay-side gantry crane is scheduled to be procured. There is an approximately 22km navigation channel. Immediately after it was completed, siltation became a serious problem, reducing the depth of the passage which was -14m immediately after completion to -7.3m at some places. This means the navigation channel must be dredged (see Table 8.19 and Figure 8.23).

Table 8.19 Major facility of La Union Port Length/Area Depth Port Facility Passenger/Cargo type (m) (m) Container Berth 340 15 Container Multi-purpose Berth 220 14 General cargo, Dry bulk Passenger and Ro-Ro Berth 240 9.5 Passenger, Ro-Ro Cargo Source: CEPA

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Passenger Berth Multipurpose Berth

Container Berth

Source: Google earth

Figure 8.23 Plan of La Union Port

(3) Port activities La Union Port started operation in 2010. Regular container ship service was provided, but by the end of 2012, it was difficult for container ships to visit the port. Later, dry bulk ships transporting fertilizer visited once a week. As a result of siltation, which has been a concern since the time of construction, the depth of the passage has been reduced.

1) Cargo throughput La Union Port began to handle cargoes in 2010. After container vessels stopped calling at the port in December 2012, bulk carriers transporting fertilizer visited the port once a week. Table 8.20 shows the cargo throughput. In 2010, total import and export throughput reached 19,670 tons. In 2011, it rose to 42,820 tons and to 118,424 tons in 2012, but this is a small quantity. The port handled general cargo in 2010 and 2011, but none in 2012. Dry bulk was limited to imports in 2012, when 37,540 tons were handled.

Table 8.20 Cargo throughput of La Union Port Year Cargo Type 2010 2011 2012 Import （Unit: tonne） General Cargo 600 40,073 0 Container 449 1,328 14,800 Dry Bulk 15,861 0 37,540 Import Total 16,910 41,401 52,340 Export （Unit: tonne） General Cargo 0 601 0 Container 155 818 66,084 Dry Bulk 2,605 0 0 Export Total 2,760 1,419 66,084 Import+Export Total 19,670 42,820 118,424 Source: La Union Port Statistiucs 2010~2012 8-25

Table 8.21 shows the container throughput at La Union Port for 3 years from 2010 to 2012. Operation started in 2010, and in 2012, 18,398 TEU were handled. Operation ended in December 2012, and since that time, no container ships have called at the port. At this time, a dry bulk ship carrying fertilizer calls once a week.

Table 8.21 Container throughput of La Union Port Cargo Type 2010 2011 2012 Container (Unit: TEU's) Import 765 2,446 10,317 Export 121 1,512 8,081 Total 886 3,958 18,398 Source: La Union Port Statistiucs 2012 2) Ship calling In 2012, 57 cargo ships called at La Union Port. Most were container ships, at 48 ships, followed by 5 general cargo ships and 4 dry bulk ships. The average container ship type was 18,600 DWT carrying from 1,000 to 1,200 TEU. Similarly, the average dry bulk ship was 37,000 DWT and the average general cargo ship was 2,200 DWT (see Table 8.22).

Table 8.22 Ship calling at La Union Port on 2012 Type of Cargo Items General Cargo Container Dry Bulk Total Calling Vessels at Pier by DWT and Numbers DWT 11,197 893,470 148,487 1,053,154 DWT (Average) 2,239 18,614 37,122 - No's of Vessels 548 4 57 Sours: La Union Port Statistics 2012

(4) Port development plan The master plan for La Union Port is divided into four phases from phase I to Phase IV. Phase I, which is now in progress, will be followed by Phase II, extending the port to the south-east, then Phase III, which will be an extension in the opposite direction to the north-west. Phase IV will further extend the south-east extension constructed in Phase II. The container cargo handling capacity is planned to be 750,000 TEU after Phase I, and 2.5 million TEU after Phase III. Figure 8.24 shows the proposed expansion plan.

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Phase-III Phase-I

Phase-II

Phase-IV

Source: CEPA

Figure 8.24 Development plan of La Union Port

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8.2 Ports on the Pacific Coast of CA5 countries

In order to grasp the characteristics of each port and what the ports have in common, the economic situation of CA5 countries, location of the ports along the Pacific Ocean, physical conditions of the ports, outline of ship call and handling cargo, container handling, management and operation and future development of the ports are summarized. A comparison of the ports from such viewpoints is shown from Table 8.23 to 8.28. 8.2.1 Basic indicator Land areas of Guatemala, Honduras and Nicaragua exceed over 100, 000 km2. Land area of Costa Rica, about 50,000 km2, is approximately half of that while that of El Salvador, about 20,000 km2, is less than half of Costa Rica.

Guatemala has the largest population of 15 million, followed by Honduras (7.75 million), El Salvador (6.23 million), Nicaragua (5.87 million) and Costa Rica (47.2 thousand).

GDPs of Guatemala and Costa Rica exceed USD 40 billion, that of El Salvador is about USD 20 billion, that of Honduras is about USD 17 billion. GDP of Nicaragua is USD 7 billion. Per capita of Costa Rica exceeds USD 8,000. El Salvador and Guatemala are USD 3000 levels, Honduras is 2,000 USD level and Nicaragua is USD 1000 level.

8.2.2 Locational conditions There are six container ports along the Pacific Ocean of CA 5 countries: Quetzal Port (Guatemala), Acajutla Port (El Salvador), La Union Port (El Salvador), San Lorenzo Port (Honduras), Corinto Port (Nicaragua) and Caldera Port (Costa Rica).

Acajutla Port, Corinto Port and La Union Port are located far from the capital of the countries while the other ports are located less than 100 km from the capital city.

Ports besides Corinto Port and Quetzal Port are located within less than 15 km from trunk roads.

Distances between Acajutla Port and the border to Guatemala, La Union Port and the border to Honduras and San Lorenzo Port and the border to El Salvador are approximately 50 km while those between other ports and the borders are 100 km to 400 km.

Ports on the Pacific Coast of CA5 are located within one-day navigational distance at a speed of 20 knots. Nautical Distances between ports on the Pacific Coast of CA5 and Manzanillo Port in Mexico or Balboa Port in Panama which are international hub ports on the Pacific Coast of Central American region are approximately two to three-day or one to two-day navigational distance at a speed of 20 knots respectively.

8.2.3 Physical conditions Quetzal Port is an excavated-type port with quays and yards located at several areas. Acajutla Port has several finger-type piers and land area for cargo storage. La Union Port is a newly developed port with several berths and wide back yards by reclamation in Fonseca Bay. San Lorenzo Port has a T-shaped detouched pier and land area for cargo storage and is located on Fonseca Bay. Corinto Port is located at the inner side of the peninsula and has a marginal wharf with a back yard for cargo storage.

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Ports except Acajutla Port do not have a problem concerning calmness of port waters but all ports need to take measures for maintaining appropriate depth of port waters;

La Union Port and San Lorenzo Port which are located in Fonseca Bay have a long approach channel;

According to Guide to Port Entry published by Shipping guides ltd. which provides useful information to those who intend to enter a port, the depths of wharves for container vessels at each port are 11.0 m at Quetzal Port, 8.00 – 12.00 at Acajutla Port, 10.70 m at San Lorenzo Port, 10.30 to 11.30 m at Corinto Port and 7.50 to 11.0 m at Caldera Port. The maximum draft of vessels which can be accommodated is 11.1 m (MLSW) at Quetzal Port, 11.89 m at Acajutla Port, 9.45 m (MLW) at San Lorenzo Port, 11.15 m at Corinto Port and 10.0 m at Cardela Port. Information on the new La Union Port is not included in the Guide.

Many containers are loaded/unloaded at wharves not dedicated to container handling. Ports except Corinto Port do not have gantry cranes while the crane at Corinto Port is out of order at present. Yard capacities of each port are 1,974 TEU at Quetzal Port, 3,753 TEU at Acajutla Port, 1,500 TEU at Corinto Port and 700 TEU at Caldera Port.

8.2.4 Port management and operation Acajutla Port and La Union Port are managed by Comision Ejecutiva Portuaria Autonoma (CEPA), San Lorenzo Port is managed by Empresa Nacional Portuaria (ENP) and Corinto Port is managed by Empresa Portuaria Nacional (EPN) .CEPA, ENP and EPN are the governmental agencies which are responsible for port management and operation of the ports in each country. Quetzal Port is managed by Empresa Portuaria Quetzal (EPQ) which is a governmental agency. EPQ is responsible for management and operation of Quetzal Port but a new container terminal will be constructed and operated by a private company under a concession contract. Regarding Caldera Port, the Costa Rican Institute of Pacific Ports (INCOP) is a governmental agency and plays a role of a regulator on the port. Puerto Caldera SPC and Puerto Caldera SPGC which are consortiums of a Costa Rican company and Columbian company are responsible for port operation under a concession contract.

Each port is open 24 hours but La Union Port, San Lorenzo Port and Corinto Port place restrictions on port use based on tidal conditions.

8.2.5 Characteristics of ports In 2012, 1,47 ships called Quetzal Port, 552 called Acajutla Port, 57 called La Union Port, 190 called San Lorenzo Port, 403 called Corinto Port and 611 called at Caldera Port. Total number of vessels which called at these ports in 2012 is 3,059.

Container vessels account for the largest portion among the vessel types at every port except San Lorenzo Port.

Quetzal Port and Caldera Port receive all types of vessels except oil tankers. Acajutla Port also receives almost all types but refrigerator vessels, oil tankers and cruisers do not use the port. At San Lorenzo Port, most calls are from RoRo vessels, solid vessels and oil tankers. Corinto Port receives many conventional vessels.

Cargo handling volume of Quetzal Port in 2012 was 11,258 thousand tons (8,560 thousand tons of import and 2,698 thousand tons of export), while it was 5,096 thousand tons (3,967 8-29

thousand tons of import and 1,129 thousand tons of export) at Acajutla Port, 118 thousand tons (52 thousand tons of import and 66 thousand tons of export) at La Union Port, 3,903 thousand tons (2,395 thousand tons of import and 1,598 thousand tons of export) at San Lorenzo Port, 3,439 thousand tons (2,750 thousand tons of import and 689 thousand tons of export) at Corinto Port and 4,732 thousand tons (4,032 thousand tons of import and 700 thousand tons of export) at Caldera Port. The total volume of cargo handled at these ports in 2012 is 28,546 thousand tons (21,756 thousand tons of import and 6,790 thousand tons of export).

Export cargo volumes are larger than import cargo volumes at every port. Percentages of export cargo volume of each port in 2012 are 76.0 % for Quetzal Port, 77.8 % for Acajutla Port, 61.3 % for San Lorenzo Port, 79.9 % for Corinto Port and 85.2 % for Caldera Port.

Dominant cargo types of each port are:

Imported and exported solid bulk and exported containers for Quetzal Port; Imported and exported solid bulk, exported containers and exported liquid bulk for Acajutla Port; Imported liquid bulk and exported solid bulk for San Lorenzo Port Imported liquid bulk, imported and exported solid bulk and exported containers for Corinto Port; and Imported and exported containers and imported solid bulk for Caldera Port 8.2.6 Characteristics of handling containers Container throughput of Quetzal Port in 2012 was 324,507 TEU, while it was 160,981 TEU at Acajutla Port, 13,398 TEU at La Union Port, 89,538 TEU at Corinto Port and 184,315 TEU at Caldera Port. Total container throughput of these ports in 2012 was 777, 379 TEU.

Ratios of empty containers are approximately one fourth to one third. Percentages of empty containers in all loading containers are high such as 53.8 % at Acajutla Port, 47.5% at Corinto Port, 41.9% at Caldera Port and 33.2 % at Quetzal Port.

Quetzal Port and Corinto Port handle transit containers and transshipment containers. Acajutla Port handles transshipment containers.

8.2.7 Future development and improvement Quetzal Port has a plan to develop a new container terminal. It is scheduled to be open next to the existing commercial berth in 2015 Phase I). A 540m long berth with 14.5 m in depth and four gantry cranes (300 m in Phase I)will be constructed by Terminal de Contenedores de Barcelona (TCB) under a concession contract. The targeted container volume is 150 thousand TEU in 3-5 years and 450 to 600 thousand TEU in 5-10 years. There is another project of expanding the existing commercial berth to a multipurpose berth with 400 m in length. Quetzal Port aims to become a transshipment port in the Central America and South Mexico region.

Acajutla Port has a plan to improve the access road and expand container yard capacity corresponding to the urgent requirements.

La Union Port is planning the improvement of the channel. In addition, concession contract procedures are in process.

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San Lorenzo Port Office of ENP has a plan to deepen the channel up to 11 m.

EPN plans to dredge the outer channel of Corinto Port in 2014. The volume is estimated to reach 5.6 million m3. The dredging cost was USD 12 per m3 in the previous work but it is estimated to be USD 5-7 per m3 at this time because the dumping cost and ship mobilization cost is expected to be less than the previous time. In addition to the dredging, EPN would like to improve the south wharf which is not used at present. Quay crane which is out of commission at present will be repaired. Productivity of a gantry crane is 18-22 boxes/h. That of a ship gear is 13-15. Owing to its high usage charge, only Maersk used the gantry cranes. Corinto Port has a possibility to introduce a concession scheme under the act in the future.

At Caldera Port, a new bulk berth with 180 m in length and 13 m in depth is under construction. The project was planned by INCOP and is being implemented by SPGC. Regarding dredging work, the government is responsible for improving and maintaining the channel and basin and SPC is responsible for dredging the water area in front of the berths.

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Table 8.23 Economic situations of CA5 countries Guatemala El Salvador Honduras Nicaragua Cost Rica Area 108,889 km2 21,040 km2 112,492 km2 129,541 km2 51,100 km2 Population 14.71 million1) 6.23 million1) 7.75 million1) 5.87 million1) 4.72 million1) Agricultural, forestry, Agriculture/ stock breeding Agriculture and textile Agriculture, Garment Agriculture, manufacture Main industry fishery and stock breeding industries and garment industry industry and tourism industries industry GDP USD 46,910 million2) USD 23,054 million2) USD 17,200 million2) USD 7,297 million2) USD 41,004 million2) Per capita USD 3,1882) USD 3,728.62) USD 2,105.02) USD 1,239.22) USD 8,6782) Export amount USD 10,450 million2) USD 5,308.8 million2) USD 7,204.3 million2) USD 4,507 million2) USD 10,408 million2) garments, textile/needle integrated circuits, coffee, banana, cultured Main export work products, coffee, machinery parts of garments, coffee and sugar shrimp and cultured coffee, beef, gold and sugar goods precious stones, precious automatic data processing, freshwater fish metals sugar, banana banana, pineapple USA, Central American USA, Central American USA, El Salvador, Main export USA, Central American USA, Netherland, China countries, EU, Mexico, countries, Germany, Venezuela, Honduras and

8-32 partner countries, EU and Japan and CA countries Panama Canada Costa Rica Import amount USD 16,613 million2) USD 10,118.2 million2) USD 10,337.6 million2) USD 6,125.4 million2) USD 16,219.5 million2) food products, mineral raw and in-process manufactures, electronic materials such as oil and fuels, machinery and consumer products, Main import fuels, integrated circuits manufactures, chemical fertilizer, consumer electronic products and in-process materials and oil goods and vehicles products and textile/needle products and capital goods chemical products products work products such as vehicles USA, Mexico, China, USA, Venezuela, Costa Main import USA, Central American USA, Central American USA, Mexico, China and Central American countries Rica, Mexico and partner countries, China and Japan countries, EU and Japan Japan and EU Guatemala Ship call 2,7233) 7423) 2,1653) 5693) 3,3223) Import cargo 9,987 thousand tons3) 4,607 thousand tons3) 7,427 thousand tons3) 2,883 thousand tons3) 7,926 thousand tons3) volume Export cargo 5,751 thousand tons3) 1,199 thousand tons3) 5,630 thousand tons3) 768 thousand tons3) 6,766 thousand tons3) volume 1) National Statistics (2011) 1) World Bank (2011) 1) World Bank (2011) 1) World Bank (2011) 1) World Bank (2011) 2) Central bank (2011) 2) Central bank (2011) 2) Central bank (2011) 2) Central bank (2011) 2) Central bank (2011) 3) COCATRAM (2012) 3) COCATRAM (2012) 3) COCATRAM (2012) 3) COCATRAM (2012) 3) COCATRAM (2012) Source : Ministry of Foreign Affairs of Japan

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Table 8.24 Locational conditions of ports on the Pacific Coast on CA5 Port Quetzal Acajutla La Union San Lorenzo Corinto Caldera Hinterland (approximate distance) Distance from the capital (km) 98 100 200 108 160 80 Distance to trunk road (km) 40 5 10 4 140 15 Distance to northern/eastern border (km) 260 50 300 60 100 250 Distance to southern/western border (km) 150 320 45 100 290 400 Nautical distance Nm/ h Nm/ h Nm/ h Nm/ h Nm/ h Nm/ h (nautical mile / hour by20 knot) Manzanillo (Mexico) 874 44 937 47 1,078 54 1,080 54 1,095 55 1,316 66 Quetzal - 81 4 221 11 224 11 238 12 472 24 8-33 Acajutla 81 4- 166 8 169 8 184 9 420 21 La Union 221 11 166 8 - 35 2 89 4 344 17 San Lorenzo 224 11 169 8 35 2- 91 5 346 17 Corinto 238 12 184 9 89 4 91 5 - 276 14 Calera 472 24 420 21 344 17 346 17 276 14 - Balboa (Panama) 886 44 833 42 757 38 760 38 689 34 471 24

Source : JICA study team

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Table 8.25 Physical conditions of ports on the Pacific Coast on CA5 (revised) Port Quetzal Acajutla La Union San Lorenzo Corinto Caldera Natural condition On the Pacific On the Pacific Location Fonseca Bay Fonseca Bay El Realejo Estuary Caldera Bay Coast Coast Calmness Swell Calm Calm Calm Calm 2.27 (Neat) 3) 0.3 (Neat) 4) Tidal range (m) 2.612) 1.682) 1.81) 3.11 (Spring) 3) 2.5 (Spring) 4) Sedimentation Sedimentation Sedimentation Sedimentation Sedimentation Sedimentation Sedimentation Channel - - - - Entrance to deep Location Approach - Outer and Inner Outer and Inner Approach inside of a bay Length (km) 22 (17 and 5) 32 6.5 (3.4 / 3.1) 1) 13.0 (MLW) 4) Width (m) 2101) - 137/140 120-2001) 150 / 1151) - 1) 1) 14.0 (-7.3 at 9.0(MLLW) 1) 8-34 Depth (m) 15.0(HWS) - 14.6/13.35(MSL) - shallowest part) 10.6 (MHW) 1) Dock for container

vessel use Type Marginal Wharf Pier type Marginal Wharf Detached Pier type Marginal Wharf Marginal Wharf A1, A2, B3, B4, Name Commercial berth1) Container berth Berth 1 ,2 Berth 2, 3, 4 Berth 1, 2 B5, B6, C7,C8 Total length 8101) 1,2432) 3402) 29/6 6103) 490 4) 10.67 (9.6-10.5 in Depth (m) 11.00(CDL)1) 12.0-14.02) 15.02) 10.30-11.303) 7.5 - 11.04) 2008) 1) Maximum draft (m) 11.10 (MLWS)1) 11.89(container)1) 9.45(MLW) 1) 11.5 1) 10.0 1) Maximum LOA (M) 174 1) 2001) 200 1) 205 1) 5 portal cranes (40 Shore Crane Mobile crane1) None None 1 Gantry (45 t) 3) 1 shore crane t, 20t) Yard capacity (TEU) 1,9741) 3,7531) - 1,500 1) 700 1) Prepared such sources as Guide to Port Entry (2013-2014) 1),, Publications of and interview with CEPA2), Empresa Portuaria National (EPN) 3), Costa Rican Institute of Pacific Ports INCOP4), Empresa Portuaria Quetzal (EPQ)5) and information from other organizations

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Table 8.26 Port management and operation Port Quetzal Acajutla La Union San Lorenzo Corinto Caldera Port authority/Port management body Empresa Portuaria Comision Ejecutiva Comision Ejecutiva Empresa Nacional Empresa Portuaria The Costa Rican Quetzal(EPQ) Portuaria Autonoma Portuaria Autonoma Portuaria (ENP) Nacional (EPN)/ Institute of Pacific (CEPA) (CEPA) Ports (INCOP) Terminal operator EPQ. CEPA CEPA ENP. EPN Puerto Caldera SPC Stevedoring by private Stevedoring by private Stevedoring by three and SPGC companies. companies. private companies. Restriction - 24 hours. -Vessels can navigate -24 hours. -24 hours. -None. the channel two hours -Vessels of draft 9.5 m -Entry is restricted in -Vessels can enter or before and after high or greater may have accordance with tide depart at any time. tide. to await a favorable and vessel's draft.

8-35 -The shallowest depth tide. -Speed limit is 8 knots of channel is 7.3 m -No restrictions on in Corinto Bay and 3 arrival at anchorage knots in the vicinity or pilot station areas. of berths/ other craft -No restriction at night Others -During congested -ENP is considering -Exemption of -During the period of period, vessels with the introduction of container vessel’s the dredging work, maximum draft up to tariff incentives. port entry due was average waiting time 4.50 m may be ceased in 2012. was more than 40 ordered to shift to the -Container storage hours but has auxiliary berth for charge was raised to decreased to 10 -14 deeper draft vessel alleviate congestion. hours at present. allocation. -A new port act which -Berth occupancy ratio allows a concession No1(84%),No2(48%) of port operation may No3(24%) in 2012. pass the Congress in -Priority policy to 2013. passenger vessels Source: Guide to Port Entry, interview

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Table 8.27 Characteristics of ports on the Pacific Coast of CA5 from type of calling vessel and handling cargo (2012)

Characteristics of Port Quetzal Acajutla La Union San Lorenzo Corinto Caldera

Ship Call 1,247 552 190 402 611

Conventional 85 6.8% 28 5.1% 5 8.8% 14 7.4% 106 26.4% 33 5.4% Refrigerators 174 14.0% 25 4.1% Container 517 41.5% 268 48.6% 48 84.2% 150 37.3% 284 46.5% Ro-Ro 84 6.7% 55 10.0% 57 30.0% 70 17.4% 74 12.1% Liquid bulk 94 7.5% 80 14.5% 17 8.9% 12 2.0%

Solid bulk 204 16.4% 114 20.7% 4 7.0% 60 31.6% 112 18.3% Oil 42 22.1% 61 15.2% Cruiser 42 3.4% 15 3.7% 51 8.3% Others 47 3.8% 7 1.3% 20 3.3% 8-36 Import (thousand tons) 5,797 2,829 52 880 2,014 3,241

General cargo 399 6.9% 140 5.0% 59 6.7% 36 1.8% 225 6.9% Container cargo 1,024 17.7% 789 27.9% 15 28.9% 439 21.8% 911 28.1% Ro-Ro cargo 44 0.7% 16 0.6% 26 1.29% 57 1.8%

18.5% 18.1% 89.8% 43.3% 4.4% Liquid bulk 1,074 513 790 871 141 Solid bulk 3,207 55.3% 1,371 48.5% 37 71.2% 31 3.5% 642 319% 1,907 58.8% Others 49 0.9% Export (thousand tons) 2,698 1,129 66 1,508 689 700

General cargo 66 2.4% 10 0.9% 6 0.4% 48 6.9% 90 12.9%

Container cargo 1,020 37.8% 490 43.4% 66 100% 339 49.2% 609 86.9% Ro-Ro cargo 2 0.1% 0 0.0% - 0 0.0% 0 0.1% Liquid bulk 113 4.2% 285 25.3% - 53 3.5% 80 11.6% 1 0.1%

Solid bulk 39.3% 30.4% - 96.1% 32.3% 1,060 344 1,449 223 Others 437 16.2% -

Source: COCATRAM and Statistics of La Union Port

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Table 8.28 Characteristics of handling containers of ports on the Pacific Coast of CA5 (2012) Container activity (throughput/1000TEU) Quetzal Acajutla La Union San Lorenzo Corinto Caldera

Unloading/Laden 117,052 36.1% 78,247 48.6% 10,317- 56.1％ - 42,070 47.0% 89,360 48.5% Unloading/Empty 55,124 17.0% 6,247 3.9% - - 4,477 5.0% 7,850 4.3%

Loading/ Laden 101,755 31.4% 35,307 21.9% 8,081- 43.9％ - 22,578 25.2% 50,562 27.4% Loading/Empty 50,576 15.6% 41,180 25.6% - - 20,413 22.8% 36,543 19.8% Local/Unloading/ Laden 103,846 34.0% 76,164 48.3% - - 40,250 46.3% 89,360 48.5% Local/Unloading/Empty 54,423 17.8% 5,026 3.2% - - 4,475 5.1% 7,850 4.3% Local/Loading/ Laden 96,744 31.7% 35,307 22.4% - - 21,799 25.1% 50,562 27.4% Local/Loading/Empty 50,576 16.6% 41,180 26.1% - - 20,413 23.5% 36,543 19.8% 8-37 Transit/Unloading/ Laden 3,793 43.1% - - 748 99.9% Transit/Unloading/Empty - - Transit/Loading/ Laden 5,011 56.9% - - 1 0.1% Transit/Loading/Empty - - Transshipment/Unloading/ Laden 9,413 93.1% 2,083 63.0% - - 1,072 57.9% Transshipment/Unloading/Empty 701 6.9% 1,221 37.0% - - 2 0.00% Transshipment/Loading/ Laden - - 778 42.1% Transshipment/Loading/Empty - -

Source: COCATRAM and Statistics of La Union Port

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8.3 Container Activities of Central American region

8.3.1 Container throughput of ports of Central America (1) Recent feature of container throughput of ports in the Central American region Container movement of the Central American region has been increasing and container throughput of ports in the region reflects such a situation. Container throughputs of the ports in Figure 8.25 since 2001 are shown in Table 8.29. Number of containers handled in Central American ports has been growing steadily in these ten years and total number of containers handled in these twenty two ports has exceeded 10 million TEUs since 2008.

Container throughputs of the ports of Cristobal, Balboa and Manzanillo show distinctive features. These ports function as international hub ports and their activities have been increasing. Another characteristic feature which this table shows is the increase of container throughput at the ports on the Pacific Coast. It accounted for a quarter of container throughput at the ports on the Caribbean Sea Coast in 2001. However container throughput of the ports along the Pacific Ocean Coast in 2010 exceeded that at the ports on the Caribbean Sea Coast.

Enhancement of hub functions of ports at Mexico and Panama and increase of container activities along the Pacific coast are noteworthy features regarding ports of the Central American region in recent years.

Altamira Tampico Progres Puerto Morelos Manzanill Veracruz

Lazaro Cardenas Belize City

Santo Tomas Puerto Castilla Puerto Barrios Puerto Cortes Puerto Quetzal Acajutla La Union Corinto

Puerto Limon Caldera Colon Cristbal Almiraute Balboa

0 500km

Note: Ports of Ensenada and Mazatlan are located at the northern coast of Manzanillo Figure 8.25 Container ports in the Central American region

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Table 8.29 Container throughput of the ports in the Central American region Port Name 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Ensenada (M/P) 57,503 49,210 39,795 75,105 127,360 127,271 110,423 116,041 143,660 Mazatlan (M/P) 18,315 12,900 16,394 16,128 18,170 30,946 29,349 27,938 27,938 21,730 Manzanillo (M/P) 457,946 638,597 707,404 830,777 873,976 1,252,215 1,409,614 1,409,782 1,110,356 1,509,378 Lazaro Cardenas (M/P) 174 1,646 43,445 132,479 160,696 270,238 524,791 591,467 796,011 Altamira (M/A) 206,864 225,937 256,417 297,017 322,458 342,656 407,657 431,208 386,161 473,152 Tampico (M/A) 29,531 18,848 14,347 9,966 9,001 10,243 11,040 11,152 5,936 2,229 Veracruz (M/A) 543,327 548,422 571,765 591,736 631,858 671,281 729,717 716,046 564,314 662,537 Progreso (M/A) 65,353 59,140 60,369 68,165 71,851 75,939 75,584 66,477 53,517 56,434 Puerto Morelas (M/A) 7,250 6,958 7,515 7,508 8,245 8,917 7,942 7,586 Belize City (B/A) 27,074 30,312 33,789 35,565 36,388 37,527 39,191 38,211 31,344 31,919 Puerto Quetzal (G/P) 126,006 130,645 166,112 183,353 223,902 230,426 257,289 280,281 212,857 254,525 Santo Tomas de Castilla (G/A) 201,090 229,516 312,154 411,153 323,045 333,816 376,660 381,199 375,823 431,001 Puerto Barrios (G/A) 188,044 220,000 242,112 232,242 229,448 236,003 218,888 248,797 317,646 326,834 Acajutla (E/P) 17,674 43,135 65,576 92,857 103,483 123,329 144,458 156,323 126,369 145,774 Puerto Cortes (H/A) 338,900 352,984 399,839 466,697 468,563 507,946 553,139 572,382 484,148 538,853 Puerto Castilla (H/A) 64,424 58,346 69,451 88,792 84,450 85,714 83,296 97,420 87,572 81,014 Corinto (N/P) 12,000 8,875 10,936 15,675 18,002 46,088 58,614 58,879 55,742 64,816 Caldera /P© 38,211 57,275 66,744 51,857 68,649 133,718 169,827 127,658 155,307 Puerto Limon ©/A 563,825 564,357 622,404 647,616 672,020 765,672 842,903 835,144 748,029 858,176 Balboa (P/P) 358,868 377,774 457,134 465,091 663,762 988,583 1,833,778 2,167,700 2,011,778 2,758,506 Almirante (P/A) 17,827 15,344 13,948 16,781 13,226 10,897 12,947 9,477 19,468 23,018 Colon-Cristobal (P/A) 948,635 943,159 1,512,365 1,943,712 2,386,844 2,025,702 2,219,982 2,945,302 2,563,106 2,288,734 Total 4,218,969 4,581,137 5,648,162 6,570,815 7,418,133 8,140,605 9,843,275 11,266,345 10,017,270 11,623,608 Mexico 1,354,602 1,568,479 1,685,067 1,904,537 2,143,143 2,680,253 3,068,412 3,305,403 2,855,730 3,665,131 Belieze 27,074 30,312 33,789 35,565 36,388 37,527 39,191 38,211 31,344 31,919 Guatemara 515,140 580,161 720,378 826,748 776,395 800,245 852,837 910,277 906,326 1,012,360 El Salvador 17,674 43,135 65,576 92,857 103,483 123,329 144,458 156,323 126,369 145,774 Honduras 403,324 411,330 469,290 555,489 553,013 593,660 636,435 669,802 571,720 619,867 Nicaragua 12,000 8,875 10,936 15,675 18,002 46,088 58,614 58,879 55,742 64,816 Costa Rica 563,825 602,568 679,679 714,360 723,877 834,321 976,621 1,004,971 875,687 1,013,483 Panama 1,325,330 1,336,277 1,983,447 2,425,584 3,063,832 3,025,182 4,066,707 5,122,479 4,594,352 5,070,258 Pacific Ocean 1,016,825 1,307,814 1,531,687 1,753,865 2,160,736 3,028,292 4,264,329 4,905,944 4,380,206 5,849,707 24% 29% 27% 27% 29% 37% 43% 44% 44% 50% Caribbean Sea 3,202,144 3,273,323 4,116,475 4,816,950 5,257,397 5,112,313 5,578,946 6,360,401 5,637,064 5,773,901 76% 71% 73% 73% 71% 63% 57% 56% 56% 50% Source: Container International Online and Container International Yearbook

(2) Container throughputs of ports in CA5 Eleven ports which handle containers are located in CA5 countries (Guatemala/Honduras/El Salvador/ Nicaragua/Costa Rica) and container throughput of these countries from 2001 to 2010 is also shown in Table 8.29. Container handling at these ports has been increasing in recent years. Total container throughput of these ports in 2010 amounts to 2,856,300 TEU which is approximately twice as much as that in 2001. In 2010, Puerto Limon with a throughput of 858,176 TEUs ranks first among container ports in CA5. Puerto Cortes, Santo Tomas de Castillo and Puerto Barios which are located on the Caribbean Sea Coast follow while Quetzal Port which is the first container port on the Pacific Coast is the fifth largest container port among CA5 countries. Approximately three fourths of container throughput of ports in CA5 is handled at ports on the Caribbean Sea Coast and approximate one fourth is handled at ports on the Pacific Coast. The share of ports on the Pacific Coast is increasing as shown as Figure 8.26.

Quetzal Port in Guatemala is the largest container port among the ports on the Pacific Coast. Cardela Port in Costa Rica, Acajutla Port in El Salvador and Corinto Port in Nicaragua follow. San Lorenzo Port in Honduras handled containers in 2011 but did not handle any in 2012. La Union Port in El Salvador started regular container service in 2011 however the service is suspended in 2013.

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Source: JICA study team Figure 8.26 Container ports on the Pacific Coast of CA5

According to MDS Containership Databank provided by MDS Transmodal Inc. (hereinafter referred to as MDS data) in May 2013, thirty-one vessels are deployed in the container service to the ports on the Pacific Coast of CA5. The largest vessel has 5040 TEU of capacity and the smallest one 860 TEU. Distribution of capacity of vessels is shown in Figure 8.27.

Principal dimensions of container vessels which are prepared based on a statistical analysis of the dimensions of existing vessels with a coverage ratio of 75% are shown in Technical Standards for Port and Harbour Facilities (2007 The Ministry of Land, Infrastructure, Transport and Tourism of Japan) as standard values. The category of capacities in Table 8.30 is not consistent with that of Figure 8.27 but the ports on the Pacific Coast of CA5 receive mostly vessels with less than 11.0 m of full load draft. Larger vessels with full load draft of more than 13.0 may call at the ports when these vessels enter the port in half loaded conditions.

Source: JICA study team Figure 8.27 Distribution of capacity of deployed vessels

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Table 8.30 Standard value of dimensions of container vessels Dead Weight Length Length between Molded Full load draft Reference: Tonnage overall perpendiculars breadth d (m) Container Carrying DWT (t) Loa (m) Lpp (m) B (m) Capacity (TEU) 10,000 139 129 22.0 7.9 500～ 890 20,000 177 165 27.1 9.9 1,300～1,600 30,000 203 191 30.6 11.2 2,000～2,400 40,000 241 226 32.3 12.1 2,800～3,200 50,000 274 258 32.3 12.7 3,500～3,900 60,000 294 279 35.9 13.4 4,300～4,700 100,000 350 335 42.8 14.7 7,300～7,700 Source: Technical Standards for Port and Harbour Facilities (2007 MLIT Japan)

8.3.2 Containership movement in the Central American region The data of containership movement is acquired from the MDS data, which includes various information on containership movement for each vessel such as name of service, ports to call and their order, names of carriers which operate the vessel, partner and slot-chartered companies of the service if any, frequency of the service, TEU capacity of the vessel, and vessel speed.

According to the MDS data in May 2010 and February 2012, the service routes of each shipping company are shown in Figure 8.28. The figure shows that all shipping companies changed their service route between May 2010 and February 2012 except Maersk. Some companies not only changed their route but also their partners. It turns out that the service route is very changeable in the Central America west coast region.