International Expert on Hydro- Meteorological Monitoring System

Giovanni Crema - Milestone 4 – Final Report

UNITED NATIONS DEVELOPMENT PROGRAM BELARUS

MANAGEMENT OF THE NIEMEN RIVER BASIN WITH ACCOUNT OF ADAPTATION TO CLIMATE CHANGE UNDP Country Program 2011-2015

International Expert on Hydro- meteorological Monitoring System

Milestone 4 Final Report

Prepared by : Giovanni Crema Verona, 24 December, 2012

Giovanni Crema - Milestone 4 – Final Report

TABLE OF CONTENTS

List of figures ...... 3 List of Tables ...... 3 Acronyms ...... 4 Acknowledgments ...... 5 Executive summary ...... 6 1. Background ...... 7 1.1 Scope of work ...... 7 1.2 Limits of the Assignment ...... 7 2.Climate Change and adaptation ...... 7 2.1 IPCC global scenarios ...... 8 2.2 Getting prepared ...... 9 2.3 Cost for “no action” ...... 10 3.Climate change scenarios in the Neman river basin...... 11 3.1 Expected impacts in the Neman River Basin ...... 11 3.2 Reference studies and information ...... 11 4.Present situation of hydro-meteorological observation networks in the Project area ...... 12 4.1 Introductory note ...... 12 4.2 Belarus ...... 13 4.3 Lithuania ...... 14 4.4 The Kaliningrad Oblast ...... 15 4.5 The Neman River Basin...... 16 4.5.1 Meteorological Observation Network ...... 16 4.5.2 Hydrological Observation Network ...... 16 4.5.3 Runoff forecast in the Neman River Basin ...... 17 5. Assessment of Quality of existing stations ...... 17 6. Upgrading of the Neman River Basin Hydro-Meteorological Monitoring System ...... 19 6.1 Introductory note ...... 19 6.2 Upgrading the Neman RB network ...... 20 6.2.1 Conceptual approach ...... 20 6.2.2 Upgrading the network in neman river basin ...... 21 6.2.3 Meteorological network ……...... 21 6.2.4 Hydrological network ...... 23 6.3 Summary of proposed intervention in the Neman RB ...... 24

Giovanni Crema - Milestone 4 – Final Report

7. Preliminary cost estimate ...... 25 7.1 Introductory note ...... 25 7.2 Cost estimate ...... 25 7.3 Notes to cost estimate...... 26

LIST OF ANNEXES ANNEX 1: List of meteorological stations in Belarus ...... 28 ANNEX 2: Full List Of Hydrological And Meteorological Stations In The Kaliningrad Oblast ANNEX 3: Planning OF Automatic Weather Stations (AWS) and the network ...... 32 A3.1 General criteria ...... 32 A3.2 Guidelines for Sensors’ selection ...... 33 A3.3 Data Collection Platform (DCP)...... 34 A3.4 Main and subsidiary Control Centers ...... 35 ANNEX 4 : Configuration of trans-boundary Early Warning System and Disaster Prevention ...... 36 A4.1 Introductory note ...... 36 A4.2 Early Warning System configuration ...... 36 A4.3 Modelling and forecasting ...... 37 ANNEX 5: List of references ...... 41

Giovanni Crema - Milestone 4 – Final Report

LIST OF FIGURES

FIGURE 1 IPCC GLOBAL SURFACE AIR WARMING SCENARIO, WITH PROJECTIONS TO 2100 ...... 8

FIGURE 2: IPCC PROJECTED GLOBAL AVERAGE SURFACE WARMING AND SEA LEVEL RISE AT THE END OF THE 21ST CENTURY .... 8

FIGURE 3: IPCC SIMULATION: THE SHORTEST THE PERIOD THE WORSE IS EXPECTED TREND ...... 9

FIGURE 4: SREX - IPCC RECOMMENDATIONS FOR FLOOD RISKS AND DROUGHT MANAGEMENT ...... 10

FIGURE 5: ESTIMATED LOSSES (US$ BL) DUE TO CLIMATE CHANGE RELATED NATURAL DISASTER ...... 10

FIGURE 6: EXPECTED ECONOMIC LOSSES IN US$ BL DUE TO CLIMATE CHANGE. TWO POSSIBLE SCENARIOS ARE COMPARED .... 10

FIGURE 7 BELARUS: AVERAGE AIR TC° AND ANNUAL PRECIPITATIONS ……………………………………………………………………….12

FIGURE 8: LITHUANIA: ANNUAL PRECIPITATIONS AND AV. YC° AT VILNIUS STATIOSN – 1960-2009…………………………………12

FIGURE 9: PREDICTION OF AV. ANNUAL MAX TC° IN VILNIUS AND KLAIPĖDA IN 21ST CENTURY...... 12

FIGURE 10 BELARUS METEOROLOGICAL NETWORK : TRADITIONAL OR SEMI-AUTOMATIC STATIONS (COUNTRY LEVE) ...... 13

FIGURE 11: HYDROLOGICAL STATIONS IN BELARUS (COUNTRY LEVEL) ...... 14

FIGURE 12: METEOROLOGICAL STATIONS IN LITHUANIA (COUNTRY LEVEL) ...... 14

FIGURE 13: HYDROLOGICAL STATIONS IN LITHUANIA (COUNTRY LEVEL) ...... 15

FIGURE 14: HYDRO-METEOROLOGICAL AND WATER QUALITY MONITORING NETWORK IN THE KALININGRAD OBLAST ...... 15

FIGURE 15: METEOROLOGICAL AND HYDROLOGICAL OBSERVATION NETWORKS IN NEMAN RB ...... 16

FIGURE 16: HYDROLOGICAL NETWORK IN NEMAN RIVER BASIN ...... 16

FIGURE 17: SPATIAL DISTRIBUTION OF HYDROLOGICAL STATIONS IN THE NEMAN RB……………………………………………………. 17

FIGURE 18: METEOROLOGICAL PARK AT VALKAVYSK, BELARUS………………………………………………………………………………...19

FIGURE 19: HYDROLOGICAL STATION IN GRODNO, BELARUS …………………………………………………………………… …………... 19

FIGURE 20: EXISTING METEOROLOGICAL STATIONS AND INDICATIVE LOCATION FOR NEW STATIONS IN THE NEMAN RB ...... 22

FIGURE 21: NEW PROPOSED HYDROLOGICAL STATIONS IN THE NEMAN RB (LITHUANIA ………………………………………… …….25

FIGURE 22: TENTATIVE LOCATION OF NEW HYDROLOGICAL STATION S IN THE KALININGRAD OBLAST……………………….………26

FIGURE 23: CONFIGURATION OF AN HYDRO-METEOROLOGICAL MONITORING AND EW SYSTEM (LEFT) AND INSTRUMENTS .... 36

FIGURE 24: INFORMATION CHAIN FOR THE PREVENTION OF NATURAL DISASTERS AND RISK REDUCTION ...... 37

FIGURE 25: PO RIVER BASIN HYDRO-METEOROLOGICAL MONITORING NETWORK…………………………………………….…………..41

LIST OF TABLES

TABLE 1 : SUMMARY OF PROPOSED INTERVENTION FOR THE UPGRADE AND EXPANSION OF THE NEMAN RB ...... 24

TABLE 2: PRELIMINARY COST ESTIMATE FOR THE RECOMMENDED INTERVENTION ...... 25

Giovanni Crema - Milestone 4 – Final Report

ACRONYMS

AWOS Automatic Weather Observation Station(s) AWS Automatic Weather Station(s) COSMO Consortium for Small-scale Modeling CRICUWR Central Research Institute for Complex Use of Water Resources DCP Data Collection Platform DEM Digital Elevation Model ENVSEC Environmental and Security Initiative EWS Early Warning Systems HW Hardware IC International Consultant IPCC Intergovernmental Panel on Climate Change LAMI Limited Area Model – Italy LAN Local Area Network LHMS Lithuanian Hydro Meteorological Service N-EU North European NRB Neman River Basin RB River Basin SREX Indicates the IPCC ―Special Report for Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation‖ SW Software UNDP United Nations Development Programme UNECE United Nations Economic Commission for Europe WAN Wide Area Network WMO World Meteorological Organization WQ Water Quality

Giovanni Crema - Milestone 4 – Final Report

ACKNOWLEDGMENTS

Acknowledgments are given to all experts and professionals who were part of the mission executed in the Neman River Basin between 14 and 19 October 2012, and took part the Workshops ―River Basin Management and Climate Change Adaptation in the Neman River Basin‖, held in Grodno, Belarus, the 16 October 2012 and in Druskininkai, Lithuania, the 18 October of same month, for the useful information received, most of which were taken into great consideration for the purposes of the present report.

Special acknowledgments are given to Mrs. Sonja Koepple and Mr. Nikolay Denisov, Project Coordinators, UNECE, for the valuable recommendations and inputs given either during the mission or while reviewing and commenting the Consultant’s interim and draft reports.

Acknowledgements are also given to Dr. Vladimir Korneev, Head of Unit of Water Monitoring and Cadastre and National Expert on Water Management of the Central Research Institute for Complex Use of Water Resources in Belarus, Dr. Egidijus Rimkus, Professor of the Department of Hydrology and Climatology at the Vilnius University in Lithuania, Dr. Inna Rusaya, Deputy Head of the Central Research Institute for Complex Use of Water Resources, Belarus, and Dr. Alexander Rachevsky, Manager of the Group for Coordination of International Projects and Programmes of «Hydrometeorological Centre of the Department of Hydrometeorology Ministry of Natural Resources and Environmental Protection of Belarus, for their detailed information about the existing hydro-meteorological networks in the single Countries and recommendations.

Finally, acknowledgments are given to Dr. Carlo Cacciamani, Head of the Hydrometeorological Service of the Region of Emilia Romagna, Italy, for the support given to this activity and the information on Climate Change studies, simulations performed and results obtained by the Po Basi Management Authority and his Service, and Dr. Cinzia Mazzetti, hydrologist and model expert with the Company PROGEA srl of Italy, for the essential contribution given for the preparation of the section dedicated to hydrological and hydraulic forecast and modeling in trans-boundary basin, with account to climate change and early warning (see ANNEX 3).

Giovanni Crema - Milestone 4 – Final Report

EXECUTIVE SUMMARY

The present report is prepared in compliance with the requirements of the “Contract for Services of Individual Contractor” N° IC:2012-175-01, concerning hydro-meteorological Monitoring Systems, as part of the “Management of Nieman River Basin with account to adaptation of Climate Change”. Specific objectives of the report are: a) results of assessment of existing network for meteorological and hydrological monitoring in the Neman river basin¸b) proposals for the optimization of the network of meteorological and hydrological stations, withing the Neman River Basin area. Due to time constraints, this report shall be considered as “reference document”, opened for further in- depth investigations (number, location, typology of stations, data transmission and other issues) and common discussions, and do not pretends to bring any final solution. After a summary analysis of global and local scenarios for climate changes, the report focus its attention on expected negative effects, in terms of increased frequency and “energy contents” of extreme meteorological phenomena and their consequences, such as floods or droughts. Neman River Basin (and in general N-EU Countries) was so far mildly affected by these phenomena. Anyhow, medium and long term projections show that the situation may rapidly change: “getting prepared” is therefore mandatory and matter of urgency. To put this in practice a common action is required, setting up an highly reliable trans-boundary hydro-meteorological monitoring and Early Warning Systems on trans- national basis (regional), capable of integrating and managing data coming from the different sources. Meteorological and hydrological observations are a longstanding tradition for all Neman Countries. Existing observation networks are in general well-conceived, monitoring points are correctly distributed and sufficient in number, in accordance with most advanced international standards and WMO guidelines. Employed technologies seems however to differ on national basis. In facts, Belarus is still mostly based on traditional technologies for instruments and no (or very few) stations suitable for real-time transmission of data are existing. On the opposite, Lithuania and the Kaliningrad Oblast (as per information received but not verified on field) dispose of an almost fully renovated network, composed by automatic real-time stations of modern technology. After analyzing the single Country-by-Country situations, recommendations are: a) Go towards an integrated system, capable of responding to the needs of Climate Change and (mainly) Early Warning (i.e: getting prepared); b) Insert in the existing network a total of 21 new stations, out if which 5 meteorological (synoptic) and 16 hydrological (water level, rain and water flow in some of them); c) Upgrade remaining Belarus stations within the Neman RB (9 meteorological and 30 hydrological) to the same level of efficiency of Lithuania and the Kaliningrad Oblast; d) Integrate existing and already upgraded stations of Lithuania and the Kaliningrad Oblast in the overall trans-boundary network. e) As part of this, create 5 dedicated interconnected Control Centers: three of them for the purposes of National Hydro-Meteorological Services or Departments, and 2 of them at the service of University and Research Institutions (such as the Byelorussian CRICUWR or the Vilnius University), for the purposes of Climate Change study; The overall cost for this action is estimated in the order of magnitude of 2.5 M€. Such estimate is based on the results of a few international tenders followed by the Consultant in the recent past and in different Countries, comparing average prices of different components, on a cost-vs-quality best effective basis. Low cost instruments were not considered, taking into account that the network, other than responding to climate change monitoring purposes, shall be essentially conceived for Early Warning purposes, in an area traditionally subject to harsh climatic conditions, and where more and more intense and disruptive weather phenomena are expected as a consequence of Climate Change.

Giovanni Crema - Milestone 4 – Final Report

1. BACKGROUND

1.1 SCOPE OF WORK

The present report is prepared in compliance with the requirements of the “Contract for Services of Individual Contractor” N° IC:2012-175-01, entered the 28 August 2012 between UNECE and the IC, to act as International Expert on Hydro-meteorological Monitoring Systems, in the frame of the ENVESEC / UNECE environmental Project for the “Management of Nieman River Basin with account to adaptation of climate change”.

The report responds to the timeframe for “Milestone 3”, specified as follows:

a. results of assessment of existing network for meteorological and hydrological monitoring in the Neman river basin (Belarus, Lithuania and the Russian Federation), taking into account inter alia spatial, temporal and parametric aspects of the network;

b. proposals on the optimization of the network of meteorological and hydrological monitoring to enable the timely and harmonized monitoring of the climate change impacts on water resources in the Nieman River basin (Belarus, Lithuania and the Kaliningrad oblast of the Russian Federation) and rough cost estimated for its optimizations submitted to the UNECE‖;

1.2 LIMITS OF THE ASSIGNMENT The present report takes into account the results of the field trip1 and the several inputs and recommendations received by most of UNECE, Belorussian and Lithuanian Experts attending the mission. For its final edition, an overall time allocation of 6 days home-work (4 for draft report + 2 for revision) after the site mission was fixed by Contract. Such time constraints did not allow a sufficiently detailed assessment of the complex hydro-meteorological situation in the Neman River Basin (also taking into account the important differences existing among the three Countries sharing the river Basin), as well as the elaboration of a comprehensive and well defined proposal for the optimization of the network, to be openly discussed with Partners and agreed upon before its publication. This last step (common discussion) is considered by the Consultant as essential, because of the complexity of the issue and the impacts it may have over the integrated water management in the Neman River trans-boundary and the safety of populations. The present report shall therefore be received as a sort of “reference document”, claiming for a general approach on ―how to afford and manage” the different aspects related to hydro- meteorological monitoring, for the consideration of concerned local National Authorities, Project sponsors and (present or envisaged) donor Agencies. The Consultant takes the opportunity of expressing his high professional interest for this challenging Project, and remains at full disposal of all the above mentioned Authorities and reference Agencies, regardless of the time and budgetary limits of the present assignment.

2. CLIMATE CHANGE AND ADAPTATION

Although discussing about Climate Change is not part of the scope of work for the present report, it is considered of importance to summarize some basic concepts under the present Section, for the self-consistency of the report itself and as a reference framework for the specific issues that will follow.

1 See also Mission Report submitted the 22 October 2012 7

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2.1 IPCC GLOBAL SCENARIOS

The Intergovernmental Panel on Climate Change – IPCC, on its “2012 Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation” 2reports the “global surface air warming scenario‖ for the period 1900 – 2100, shown in Fig. 1 below:

Figure 1 IPCC Global Surface Air Warming Scenario, with projections to 2100

Two green and the blue lines were added to the original picture, to bring into evidence the importance of expected future changes. Discarding the most optimistic (and scarcely realistic) scenario of “year 2000 constant concentration” (in orange, and in facts already overtaken), even the most optimistic scenario (B1, in blue), predicts by 2050 a (worldwide) increase of air temperature in the average of 1 C° if compared with year 2000, and 0.9C° if compared with 2010. On Figure 2: IPCC Table SPM.3. Projected global average surface local basis, such figures may warming and sea level rise at the end of the 21st century become easily the double, as is – among others – often the case of Mediterranean Countries.

2 IPCC, 2012: Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change. 8

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The numbers increase of about 0.6 C° for the A2 scenario, that, to the Consultant’s opinion, is the one to be taken into account while making decisions about “what to do” to afford the consequences of climate changes. Air temperature is not the only parameter involved in climate change or having significance in terms of expected consequences. The following table is published by IPCC, indicating average surface worming and sea level rise for the same scenarios (Fig. 2).

As it can be seen, a minimum average sea level increase of 28 cm (scenario B1) is expected by the end of century, that becomes 42 cm in the worse A1F1 scenario. These numbers, well known to all scientists involved in the field, are impressive and recall the worse scenarios of “catastrophic movies”. Scenarios that are likely to make the life of future generations (including current young generations) very difficult, and that we have the “moral” obligation to avoid, or at least do our better to reduce the worse expected consequences. Figure 3: IPCC simulation: the shortest the period the worse is expected trend As a last consideration, IPCC warns that “the shortest the period (taken into account for projections), the worse is expected trend” (see Figure 3 ) and put the question “whether the space could perform as time” or not. Both statements are of particular significance, meaning that, in absence of timely and effective actions, the threaten that climate change represents for the overall world may become more and more consistent, while local effects may substantially differ. What is already a common perception. 3

2.2 GETTING PREPARED

Getting prepared is therefore not an option. In facts, it’s a common understanding that everyday weather, as well as recurrence and intensity of extreme weather events (or natural disasters) are largely depending from these parameters.

In the same Report mentioned above (section 4), IPCC warns that ―Extreme weather and climate events, interacting with exposed and vulnerable human and natural systems, can lead to disasters”. According to the Panels’ Experts, the following are the most disastrous effects against which we need to strengthen our defences4:

IPCC recommendations fully matches our common understanding and everyday experience. Response to this (getting prepared), means to put in practice a lot of interconnected prevention measures, that unfortunately cannot be discussed under the present assignment.

Among them, improvement of weather and climate monitoring techniques, by implementing highly reliable and effective Early Warning Systems, improvement of flood and drought risk management

3 Scenarios on Climate Change effects are permanently updated by IPSS. Currently, a Fifth Assessment Report (AR5)‖ is under preparation, including three work groups (Physical sciences; impacts, adaptation and vulnerability, mitigation of climate chenge). Works will be completed by April 2014. (http://www.climatechange.gov.au/en/climate-change/fifth- assessment.aspx). 4 Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) - IPCC recommendations for flood risks and Drought management, expected as the effects of Climate Change. Special Report of the Intergovernmental Panel on Climate Change, 2012. Ch. 5.

Giovanni Crema - Milestone 4 – Final Report

capacity and setting up advanced risk management policies (at Country and Regional level), are on the very first line, as clearly shown in Figure 4 below.

Figure 4: SREX - IPCC recommendations for Flood Risks and Drought management, expected as effects of climate change

2.3 COST FOR “NO ACTION”

The following Fig. 5 reports overall losses, in terms of US$ Billions, estimated from 1980 to 2010 at global level, due natural disasters that can be directly or indirectly referred to climate change. Lines in red and blue were added to show linear trend (qualitative) over the entire period (red), in comparison with last ten years (blue).

Figure 5: estimated losses (US$ BL) due to Climate Change related natural disaster

Going to expected economic damages (in case of no action), and more specifically to N-EU Countries, scenarios represented in Figure 6 are published by IPCC.

Of course we do not know if similar events will occur as predicted, and “losses” will be as represented, but figures are as usual impressive. Whichever the case, and also dividing by 2 or 3 even the most optimistic scenario, it’s more than evident that any investment potentially afforded by Central Governments to reduce such damages (and economic losses) will have a “rate of return” Figure 6: expected economic losses in US$ BL due to higher than any other alternative investment. climate change. Two possible scenarios are compared This, not taking into account social effects and 10

Giovanni Crema - Milestone 4 – Final Report

saved human lives.

3. CLIMATE CHANGE SCENARIOS IN THE NEMAN RIVER BASIN

3.1 EXPECTED IMPACTS IN THE NEMAN RIVER BASIN

According to the results of the job performed by Belarus CRICUMWR, the Vilnius University of Lithuania and Kaliningrad Centre for Hydrometeorology and Environmental Monitoring, historical data and expected Climate Change effects in the three Countries and, as part of them, in the cross-border area of the Niemen River Basin, do not differ substantially from average prediction at global level, and more specifically from the average situation of N-EU Countries.

Anticipating specific effects on the Neman River Basin is not a task of the present assignment, and is brilliantly carried out by CRICUMWR and the Vilnius University. Based on the above, it can however be asserted that, over the medium term (5 - 15 years), impacts similar to the ones currently affecting the southern part of Europe5 will become more evident in Neman River Basin. That means that more intense and frequent storms (also occurring out of season), picks of very low or very high temperature (with consequent hail and snow increased phenomena), increased and more frequent floods (especially in the lower basin and delta area) and extended drought periods, are to be expected.

Adaptation phenomena will occur in natural environment, inducing changes in aquatic biota, migration of some bird species and so forth. Agriculture will probably be the most affected sector, forcing the introduction of new crops and/or modified agricultural practices. In spite of extended drought periods, shortage of water for the population is not to be expected, but water management practices will need to be changed and adjusted to the rapidly evolving environmental conditions.

3.2 REFERENCE STUDIES AND INFORMATION

To enter into a deeper analysis of these phenomena is also not the task of the present assignment, specifically oriented towards hydro-meteorological monitoring systems. However, for the consistency of the report and to make further analysis easier, the following information are reported as a general reference:6.

Looking at Figures 8 (a and b) and 9 below, we may appreciate that average Temperatures in Belarus increased from 6.2 to 7.1 °C between 1945 and 2010 (+0.9 C°), while precipitations decreased from 660 to 540 mm/y (- 120mm/y). In Lithuania, situation looks different, and a slight increase of precipitation is shown (1960 – 2008), while T° increase is similar to Belarus. Figure 9(7) shows projections of average maximum temperatures in Lithuania for the 21st century and starting 1971, according to different IPCC standard scenarios (only cold season is represented).

5 Reference is made to Seine, Loire and Rhone in France, Tagus in Spain / Portugal, Po in Italy (also discussed in annex 3), Rhine in Germany, Danube, Dnieper and others. 6 These information are sourced from CRICUMWR for Belaru and the Vilnius University or the Lithuanian Hydrometeorological Service LHMS for Lithuania. Part of them were already reported in the Consultant’s interim report and are repeated here for the completeness of text. 7 LHMS: Climate Change in Lithuania 11

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Figure 7

Figure 7. Belarus: average air TC° and annual Figure 8. Lithuania: annual precipitations and av. precipitations air TC° in Vilnius St. between 1960 and 2009

Fixing year 2050 as intermediate point, an average increase ranging between 0.8 and 1.2 C is reported, somewhat lower that global IPCC projections but substantially in line. In its report on climate change, LHMS warns that ―In 21st century heat waves 8/b (days when maximum temperature ≥ 30 °C) will become more frequent. In 2061- 2100 there could be 7 heat wave days per year more compared to 1971-2000‖.

Figure 8: Prediction of average annual maximum temperature (°C – cold season) in Vilnius and Klaipėda in 21st century.

4. PRESENT SITUATION OF HYDRO-METEOROLOGICAL OBSERVATION NETWORKS IN THE PROJECT AREA (COUNTRY LEVEL)

4.1 INTRODUCTORY NOTE

The present sections reports general information about the existing hydro-meteorological monitoring networks in Countries of Belarus, Lithuania, the Kaliningrad oblast and (as part of them), the Neman River basin.

These information were already reported in the consultant’s interim report (Milestone 1) and are repeated here for the thoroughly comprehension of the text. They are mainly sourced from the presentations given by the representatives of the different Countries during the site mission of October 2012 and the institutional web-sites. Part of them were directly checked with said representatives (mainly the Central Research Institute for Complex Use of Water Resources for Belarus and the Vilnius University for Lithuania) and are therefore confirmed.

Giovanni Crema - Milestone 4 – Final Report

Still the information shall be retained as partial or incomplete. A more comprehensive assessment of all stations existing in the Countries (automatic or traditional), including their “quality”, level of operation, quality of data recorded and distributed and so forth, should theoretically be done. This activity is clearly out of the scope of work (and the time limits) for the present assignment, but will be necessary before taking final decisions about the opportunity of introducing new stations, their final number and optimum locations.

However, even with all the said limits and uncertainties, the methodology introduced in the following sections and the recommendation given remain, to the consultant’s opinion, fully valid, but for the potential adjustments that shall be introduced when a more comprehensive information and knowledge of the actual “state of art” for hydro-meteorological networking in the countries will be available.

4.2 BELARUS

The Belarus meteorological network is reported to be formed by 68 weather stations, according to the list given in Annex 1 (source: Belarus Hydro- meteorological Service). Based on given geographical coordinates, all stations were mapped as shown in Figure 10 below. Some of these stations are located in Lithuania or the Kaliningrad Oblast, and may overlap with stations reported when describing the specific situation in these two Countries.

According to information received by Dr. Vladimir Korneev of the CRICWR, Figure 9 Belarus meteorological network : traditional or semi- “no automatic hydrological and/ or automatic stations (country leve) meteorological stations are existing in the (Belarus portion of the) Niemen River Basin (NRB)‖, while only 3 AHS (Automatic Hydro-meteorological Stations) were installed in the Pripyat River Basin in 2011-2012 y in the frame of NATO “Science for Peace” Program.

Hydrological network, on its turn, is composed by 136 stations, out of which 122 are placed on 84 rivers and channels and 14 on lakes and reservoirs8. The stations’ distribution is shown in the Figure 11 here below.

8 V. Korneev, International conference on innovation advances and implementation of flood forecasting technology, October 2005. The actual number of stations is likely to be increased. 13

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Figure 10: Hydrological stations in Belarus (country level)

4.3 LITHUANIA

According to information received9 and as understood, there are more than 50 automatic real-time hydrological stations in the Country, representing about two-thirds of total number of stations. The network will be completed within the next few years. Meteorological and hydrological network maps are published the Lithuanian Hydro-meteorological Service LHMS (see www.meteo.lt) and are reported here below (Figures 12 and 13).

Figure 11: Meteorological stations in Lithuania (country level)

9 Source: presentations of Dr. Egidijus Rimkus and Dr. Edvinas Stonevičius, Vilnius University. 14

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Figure 12: Hydrological stations in Lithuania (country level)

4.4 THE KALININGRAD OBLAST

7 meteorological stations and 13 hydrological are reported in the Kaliningrad Oblast (Annex 2 )10. As part of these, 4 meteorological and 10 hydrological are located within the Neman RB (Figure 14).

Figure 13: Hydro-meteorological and Water Quality monitoring network in the Kaliningrad Oblast (overall Oblast)

10 Source: presentation of Mrs. Nataliya Shagina and Mrs. Liudmila Zakharchuk of the Ros-Hydromet Kaliningrad Regional Hydrometeorological and Environmental Monitoring Centre, at the conference of 18 October in Druskininkai, Lithuania 15

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4.5 THE NEMAN RIVER BASIN

4.5.1 METEOROLOGICAL OBSERVATION NETWORK

According to information presently available, meteorological observation network in Neman RB include 46 stations, out of which 4 in the Kaliningrad oblast (fig. 14), 25 in Belarus and 17 in Lithuania (Fig.15).

The stations are evenly distributed, forming a grid of acceptable density, particularly in Byelorussian portion of the basin. This is a very important element, allowing a reliable, accurate and comprehensive monitoring over the entire territory if the river basin, and as a consequence the elaboration of reliable forecast analysis and simulations.

Employed technology is hover not homogenous, since Lithuania recently upgraded all its stations, while Belarus still relays on traditional technologies. This issue will be discussed further on, since it may represent a problem at the moment of integrating the whole trans-.boundary Figure 14: meteorological and hydrological observation system. observation networks in Neman RB

4.5.2 HYDROLOGICAL OBSERVATION NETWORK

Hydrological observations are based in 67 stations, out of which 5 in Kaliningrad Oblast (Fig. 14), 27 in Belarus and 35 in Lithuania (Fig.16) As technology is concerned, the situation apparently does not differs from meteorological network, as we will examine in more detail in the next section.

Figure 15: hydrological network in Neman River Basin

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4.5.3 RUNOFF FORECAST IN THE NEMAN RIVER BASIN

A very interesting runoff forecast analysis until 2035 and with projection to 2050 was developed by Prof. Korneev of Central Research Institute for Complex Use of Water Resources, Belarus (CRICUMWR), and Dr. 11 Rimkus of the Vilius University and 1 presented during the site mission of October 2012.

The study is based on data retrieved by 24 out of the 76 hydrological stations were used for the models’ calibration and the preparation of 2 3 runoff charts (winter, spring, summer, autumn). The spatial distribution of these stations is represented in Figure 16 above, while Figure 17 on next page shows winter and summer runoff forecast projection at year 2035, under the two IPCC standard scenarios A1B and B1(7). As we may appreciate, it is possible to identify 3 to 5 zones, showing substantially homogenous runoff patterns scenarios, respectively for winter and summer forecast. Examining the location of stations in each zone, it seems that all of them are “represented” by a number of stations sufficient for the hydrological characterisation. 1

At the present level of knowledge, we may 2 assume that the actual density of stations, and in general the employed technology, are valid 3 for the purposes of climate change monitoring, 3 while a system upgrade is certainly needed for 4 early warning purposes, and in view of expected impacts. This issue will be analysed in more detail in the following chapter 6, giving 5 the necessary (preliminary) indications for future activities. However, considering the limits of the present analysis, further studies are strongly recommended, before taking decisions about actions or investments in this Figure 16: spatial distribution of hydrological stations in sector. the Neman RB, used for winter (above) and summer (below) runoff forecast until 2035

5. ASSESSMENT OF QUALITY OF EXISTING STATIONS

11 Other participants were Prof Aliaksandr Volchak, Brest State Technical University, Brest, Belarus; Prof.s Lubov Hertman, Aliaksandr Pakhomau, Ivan Bulak, CRICUWR, Minsk, Belarus.

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Unfortunately only the Valkavysk meteorological stations and the Grodno hydrological station, both in Belarus, could be visited during the site mission. No stations were visited in Lithuania or the Kalinigrad Oblast.

Valkavysk is the headquarter of the Grodno Regional Department of hydrometeorology, and a quite well equipped “meteorological park” is existing. The majority of stations are purely mechanical, and an observer is needed full time. The anemometric station, of Belorussian technology, can be consider as semi-automatic, meaning that (as we understood) date are transmitted from the station to the nearby control centre, where they are processed, validated and then transmitted to the main office of hydro-meteorological Department in Minsk.

The “park” (see Figure 18/1 and 18/2) is in general well maintained and the competence of in- charge personnel is doubtless12. Data visualization (Figure 18/4) is good, although based in a quite simple software. In general, the impression is that the station may adequately respond to the requirements of monitoring for the account of climate change, but no more than that.

FIG. 3(12)

FIG. 1 FIG. 2 FIG. 4

Figure 18: meteorological park at Valkavysk, Belarus

The hydrological station in Grodno (Figure 18) represents an outstanding example of the robustness, the longevity and the reliability (they work all time) of the “ancient technology”. It can be defined as “historical”, and once again we need to stress the almost “perfect” maintenance given and the very good status of conservation of the equipment. Of course, no way of using such station as part of an automatic network and for the purposes discussed above.

Figure 19: Hydrological station in Grodno, Belarus The general impression is that the overall technology is quite obsolete and definitely not suitable to be integrated in a “modern” meteorological monitoring network, if responses shall be given in terms

12 Some aspects are however not acceptable (e.g. external cables as in Figure 18/3) representing a critical point of weakness for the stations. If system upgrade will take place, similar ―errors‖ shall be of course corrected. 18

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of early warning against extreme weather phenomena, disaster prevention and risks reduction (or in other terms, give response to the worse expected climate change consequences).

However and advancing some concepts that will be discussed further on in more detail, it’s the consultant’s opinion that, even realizing a modern network based on automatic real-time weather stations, these technologies shall be maintained and “saved” for a quite long period of time. This for the double purpose of: a) to not dismiss the personnel working on them, whose “ability” and capacity of interpreting data, elaborate statistics and also make short-term forecast on local conditions are usually remarkable; b) use traditional stations (and local personnel experience) as a “reference” for new AWS, checking their accuracy and – if necessary – calibrate responses for the initial period of operation (usually one year).

6. UPGRADING OF THE NEMAN RIVER BASIN HYDROMETEOROLOGICAL MONITORING SYSTEM

6.1 INTRODUCTORY NOTE

Based on above information, the following introductory notes are given as a guideline , before entering into the proposed upgrade and expansion of the Neman RB monitoring network:

a. The density and spatial distribution of hydro-meteorological observation points in the Neman RB is good (responding to WMO criteria). b. The “quality” of the single stations seems however to be different in the different Countries: in particular:  Byelorussian stations (for what it could be observed and according to local experts’ reports) are quite obsolete and need to be upgraded; the concept of “integrated system” and real-time transmission of data is absent.  Lithuanian stations could unfortunately not be visited. However, according to reports and discussions had with local representatives of this Country, the network was completely renovated, all stations are automatic and transmitting data in real time, and no further upgrades are needed. The web site of the Lithuanian Hydro-meteorological service LHMS, gives in facts (only in Lithuanian version) good on-time information about hydrological and meteorological values measured by the single stations with a delay ranging from less than one hour to 24 hours, being this last time interval limited to a few stations (http://www.meteo.lt/hidro_informacija.php)  Kaliningrad Oblast shows a relatively consistent number of observation points, with good spatial distribution of hydro-meteorological observations along the Neman river and main tributaries. No information could be obtained about the technological “state” of these stations (automatic or not, real-time or not) and the network operation. c. To reach the objective of an effective hydro-meteorological monitoring of Neman RB, the “homogeneity” of the trans-boundary observation networks (to be merged in only one network) is essential, to allow not only the consistency of data measured and transmitted, but the optimum exchange of data among the “stakeholder” Countries. This concept goes beyond the “boundaries” of the river basin, encompassing the entire territory of the said Countries; d. Although considering climate change monitoring as a priority, the envisaged upgraded network shall respond to the needs of “getting prepared” for the consequences of climate change itself, in terms of expected increase (frequency and intensity) of extreme weather phenomena and relevant natural disasters. What in facts need to be build is a new trans- boundary integrated early warning and monitoring system, responding to advanced technological criteria, and to be further integrated with the overall early warning system of 19

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neighbouring Countries (Baltic area and N-EU countries). This concept, to the consultant’s opinion, is of utmost importance and shall be taken into attentive consideration by in- country decision makers and donors, at the moment of establishing the resources for the relevant interventions.

6.2 UPGRADING THE NEMAN RB NETWORK

6.2.1 CONCEPTUAL APPROACH Considering the above it is clear that, in terms of density of observation points, the existing network is respondent to the needs of climate change, as well as to the requirement (at least at the initial phase) of an integrated Early Warning System. Upgrading the system introducing (wherever necessary) more advanced technologies, and adding new sites (stations) is however an option to be considered. Location and typology of stations is subject to detailed site-by-site investigations and analysis about the “responsiveness” of the overall network(s), structure of control centres, data processing, modelling and forecasting capacity and so forth. The following consideration are laid down as a guidance for a correct conceptual approach, when deciding on how to implement the new network: a) Extreme weather phenomena or natural disasters, substantially related to climate change and potentially affecting the Neman River Basin, have effects on wider scale: national, trans-national or even regional. If the concept of “getting prepared” to correctly monitor and afford such phenomena is accepted, the upgrading / expansion of hydro-meteorological monitoring system must be regarded as a national problem, concerning the safety of all population, and cannot to be limited to a specific river basin. b) The new expanded / upgraded network, although referred to the Neman RB as a trans- boundary area, shall therefore be conceived as a component of the national hydro- meteorological monitoring and EWS. Over the Neman RB area, the “system planner” shall take into account the needs and requirement of the single Nations, in terms of climate change (occurring phenomena, expected consequences, mitigation measures), safety of populations, protection of infrastructures and so forth. In other words, the intervention recommended under the present study is dimensionally limited and spatially concentered in the Neman RB area but, to be effective (also in terms of investment), it shall be conceived for the benefit of the overall population; c) Once the final objectives are identified and described, a “phase-by-phase” implementation process is recommended, starting from the reconversion / rehabilitation of the existing (and technologically obsolete) hydro-meteorological stations in the Neman RB, installed in most significant end “environmentally critical” locations; d) Wherever possible and according to established priorities (climate change and early warning), rehabilitation shall include automatic data recording (Automatic Weather Observation Stations - AWOS) and real-time transmission, employing dedicated UHF radio frequencies, GSM/GPRS or satellite (meteosat) transmission mode. e) While “engineering” the new network (or networks), whichever the number of stations, the leading consideration shall be that the specific intervention, however limited, shall be suitable to be eventually integrated into the existing or envisaged “Regional” automatic real- time monitoring system, responding at the same time to the needs of climate change, environmental monitoring and early warning. With “Regional” in the present case is intended the “ensemble” of Baltic and EU neighbouring Countries. Details concerning location of stations, sensors to be installed, transmission mode, data processing, visualization and modelling, will be discussed in the following paragraphs;

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f) Operating such complex multi-purpose networks may not be so easy for Countries that do not dispose of consolidated experience (such as Belarus). National hydrometeorological Services, environmental Authorities, Civil Protection Services and donors shall clearly understand the process of passing from traditional stations (where physical human observation is essential) to automatic observation systems, diffusing data as needed, is quite long and need attention, to avoid waste of money and “disillusions” (systems not responding in the due form). This projects shall therefore be afforded step-by-step, maintaining as long as possible traditional stations into operation, joint with automatic ones, as already discussed in previous paragraphs. g) The majority of EU and Baltic Countries dispose however of a longstanding and remarkable experience in this field, that should be taken into attentive consideration as “lesson learned”. It is recommendable to establish, whenever possible, cooperation agreements among Countries, starting a process of “wide range” scientific and technical exchange and training of personnel. Key issues to be considered must go beyond climate change (that as said remains a priority), including network operation, maintenance, data processing, diffusion and dissemination, modelling and forecasting and so forth. Institutions involved should include Hydro-meteorological Services, Universities, Water Management Agencies, Watershed Authorities (where existing), and agencies in charge for Early Warning, Civil Protection and post-disaster intervention (such as the Ministry of Emergency Situation in Belarus).

6.2.2 UPGRADING THE NETWORK IN NEMAN RIVER BASIN13 Neman RB area is characterized by: a) flat topography; b) substantial uniformity of climatic conditions; c) still relatively limited occurrence and intensity of floods; d) high corrivation times for the Neman river (time for flood response); e) limited population density.

Considering the above, it is assumed that monitoring stations shall advantageously be distributed over the territory in an almost uniform grid. This is in facts the case of Neman River basin, composed by 28 stations (observing points) and definitely responding to the given criteria. The intervention is therefore oriented to:

a) Rehabilitate or replace those stations that are definitely obsolete (mainly in the Belorussian portion); b) Complete the “grid” by introducing a limited number of new stations, thus reducing or phasing the investments.

Details are given hereinafter.

6.2.3 METEOROLOGICAL NETWORK

Belarus and Lithuanian portions of river basin

Once established the basic criteria, in the present paragraph we will try to set up more specific rules for the system upgrade.

As already remarked, the purpose is introducing a preliminary methodology, in order to arrive at the definition of possible “order of magnitude” of the eventual investment. After this, and according

13 See also Interim Report, paragraph 7.3. 21

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to the results of site-by-site investigations, further studies to be done and (last but not least) available funding, both the number of stations and locations may change, but (hopefully) remaining in the frame of the given concepts and methodology.

To preliminary design the new grid, it is now considered the vast majority of Lithuanian station were recently upgraded, are fully automatic and with real-time transmission of data, while Belarus still need to start such a process. Therefore, interventions in the Lithuanian portion of the basin are limited to the insertion of two new stations as part of the existing network, and (most likely) the improvement of data transmission from the single stations to the new Neman BR Control Centres, different from LHMS main centre.

A more incisive (although still limited) intervention is envisaged for the Belarusian side, with full rehabilitation of a minimum number of 9 stations (existing) and the insertion of a new one in the upper part of the basin, mainly to improve rain (and possibly snow) monitoring and runoff calculations.

Figure 17: existing meteorological stations and indicative location for new stations in the Neman RB (Belarus and Lithuania)

Figure 20 gives an indication of stations to be inserted in the envisaged “Neman RB monitoring and early warning network” and tentative locations for new stations.

Changing of locations will not alter the general concept and the scope for which the network is conceived. Changing the number of stations to be upgraded or the number of new installations, may on the opposite have an influence on the overall system performance, in a measure depending from the extent of the intervention, and of course on relevant budget in the opposite sense.

The Kaliningrad Oblast

An integration of meteorological network is possibly needed in the Kaliningrad Oblast (figure 20) where apparently only one station is operating in the city of Sovetsk. In principle, two more stations should be considered, to be tentatively placed in the lowest part of basin, and somewhere in the upper basin (an option could be the proximity of Sheshupe River). Both stations shall be equipped with meteorological and hydrological parameters.

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6.2.4 HYDROLOGICAL NETWORK

Concepts similar to the ones used for the meteorological network will be applied to hydrological, with following remarks: a. The concept of “grid” is not applicable to hydrological monitoring stations, that shall concentrate on river confluence (closure of sub-catchments), flood prone areas and upper part of basins (as their actually are in the Neman RB). b. An hydrological stations is conceived to be equipped with sensors for water level and rain. Wherever it’s possible, location should coincide with a meteorological station, to concentrate collection of data, have a single “data logger”, make maintenance easier and so forth.

About the grid, the following strategy is recommended: a. Belarus, the full upgrade all hydrological stations used by CRICUWR and the Vilnius University for the modelling and forecasting of runoff in the Neman RB (about 30) is recommended, with the possible integration of the 10 additional monitoring stations proposed by Dr. Inna Rusava during the presentations held in Grodno and Druskininkai the 16 and 18 October this year. Identified locations are: Usha, Vilia, Issa, Western Berezina, Sula, Ilya, Nieman, Krinka, Servech and Gojka. Criteria followed by Dr. Rusava are very similar to the ones exposed in previous paragraph 6.2.1, with the addition of covering areas of particular interest for the climate change, i.e. where particularly harsh climatic conditions are expected, while no monitoring stations are present. These criteria seem to be very reasonable, and locations selected by Dr. Rusava are so far retained. Considering that the envisaged network should respond not only to climate change, but (mainly) to early warning purposes, it is recommended that all these stations shall be automatic and with real-time transmission of data. This will be also essential in order to increase timely transmission of data during intense phenomena (data should arrive at control centres every 3 minutes), and accuracy of information, to allow reliable hydrological and hydraulic forecast and modelling (see paragraph 8.3 ).

b) Lithuania: integration of existing network (at least the 11 stations used for runoff forecasting) with tentatively 4 new stations is proposed (see Figure 22 for tentative locations), applying the same criteria already exposed for Belarus (completing the observation grid), but giving priority to the lower part of river basin. Improvement of data transmission mode (GPRS / radio or satellite) in all stations is also recommended, to be consistent with the overall network.

Figure 21: new proposed hydrological stations in the Neman RB (Lithuania)

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c) Kaliningrad Oblast: existing hydrological network seems to be good (see figure 21). According to information retrieved in the website of the Russian Federal Service for Hydro- meteorology and Environmental Monitoring, Roshydromet, and conversations held with Russian representatives during the site mission, it is assumed that all stations are automatic and suitable for real-time transmission of data. Recommended intervention is therefore limited to the installation of two additional hydro- meteorological new, to complete the grid, and the integration of existing stations (apparently 5 hydrological and 1 meteorological) with the overall Niemen RB monitoring system. Tentative location for new stations is shown in figure 22 below (yellow circles).

Figure 22 : Tentative location of new hydrological station s in the Kaliningrad Oblast (yellow circles)

6.3 SUMMARY OF PROPOSED INTERVENTION IN THE NEMAN RB

Considering all the above, the proposed intervention for the upgrade and expansion of the Neman RB hydro-meteorological monitoring and early warning system is summarized as follows (Table 1):

Table 1 : Summary of proposed intervention for the upgrade and expansion of the Neman RB Hydro-meteorological monitoring and Early Warning system

Stations to be integrated Country (sub- Stations to be in the overall system portion of river New stations upgraded (additional to new or basin) upgraded) Meteo Hydro Meteo Hydro Meteo Hydro Belarus 1 10 9 30 - - Lithuania 2 4 - 8 11 Kaliningrad Ob. 2 2 - - 1 5 Total 5 16 9 30 9 16

It is however assumed that meteorological and hydrological stations will be located wherever possible in the same site, to reduce installation costs, have a unique Data Collection Platform (see next paragraph) and ease maintenance operations. 24

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Annex 2 and 3 report respectively basic elements for the planning of Automatic Weather Stations (AWS) and the network (Annex 2) and for the configuration of trans-boundary monitoring and early warning systems.

These issues, although not strictly related to the present assignment, are considered essential for the full understanding on how a modern hydro-meteorological and early warning system shall be conceived, planned, implemented and operated, and its main purpose should be.

7. PRELIMINARY COST ESTIMATE

7.1 INTRODUCTORY NOTE

Cost estimation has been revised in comparison with interim report. The full system is taken into consideration, based on the number of stations reported in previous table 2, including control centres but for the hardware facilities. The estimation is still for purely budgetary purposes and internal use of Partners. Final cost for the system may be correctly evaluated only after site-by-site revision, common decision of what to do in terms of system expansion, rehabilitation of existing stations, technologies to be employed, number of Control Centres (main and subsidiaries), SW packages to be installed, additional services required and so forth.

The given evaluation is based on the “turn-key” concept, including all necessary engineering services (such as preliminary, investigation, system lay-out and detailed planning for the single stations), transport and installation, training and full maintenance services for three years, including spare parts and whatever necessary for the correct system / network operation

Estimated costs are based on average results from international tenders, in Italy and elsewhere. Relevant data shall be made available to representative of local institutions if required. Only “top- class” technology from international manufacturers is therefore taken into account, to preserve the characteristics of heavy duty, long-lasting duration of equipment, accuracy of data registered, received and transmitted, reliability of entire system. Low cost equipment, that are also widely represented in the international market (but very seldom represent a good investment for National Services) are excluded from this evaluation and are not recommended.

Cost of models for hydrological or hydraulic forecasting, data exchange platform and similar are included in the estimation, according to the general concepts illustrated in previous chapters. Cost for climate change modelling is not included.

7.2 COST ESTIMATE

The overall cost for the full upgrading and expansion of the Neman River Basin hydro- meteorological monitoring system, with account to climate change, early warning and monitoring, is estimated in the order of 2.5 M€. Summary of cost estimate is given in table 2 on next page.

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Table 2: preliminary cost estimate for the recommended intervention

Neman River Basin Hydro-meteorological upgrading and expansion N. of Cost per Cost per Total cost Project, with account to Climate Change, early warning and monitoring. Unit units unit (€) item (€) Preliminary cost estimate (€)

1. Manufacturing and supply of monitoring stations 1.517.000

1.1 New meteorological stations Units 5 27.000 135.000

1.2 New hydrological stations Units 16 22.000 352.000

1.3 Upgraded meteorological stations Units 9 20.000 180.000

1.4 Upgraded hydrological stations Units 30 20.000 600.000

1.5 Stations to be integrated in the overall system Units 25 10.000 250.000

2. Control Centres (excluding hardware) 435.000

Main (includes SW facilities for visualization, archiving, formation 2.1 Units 3 45.000 135.000 of data bank etc.)

Models for hydrological / hydraulic forecast (to be installed in 2.2 Units 1 250.000 250.000 main CC - include calibration Subsidiaries (only visualization and remote access to main 2.3 Units 2 25.000 50.000 centres)

3. 3) Engineering services / technical assistance 217.600

3.1 Preliminary site inspection, investigations and planning No of sites 60 2.000 120.000

3.2 Engineering services / technical assistance (% of 1+2) 5% 1.952.000 97.600

4. 4) Maintenance (3 years - Include spare parts, guarantee etc.) (% of 1+2) 24% 1.952.000 468.480 257.400

5. 5) Contingencies % of total 5% 121.350

6. Total cost of project 2.548.350

7.3 NOTES TO COST ESTIMATE 1. Unit costs come from average of past international tenders (in some cases at lowest price) that the consultant had the opportunity of assisting in the past years. Evidence can be given if requested or necessary. 2. Only “top-class” technology from international manufacturers is therefore taken into account, to preserve the characteristics of heavy duty, long-lasting duration of equipment, accuracy of data registered, received and transmitted, reliability of entire system and so forth. Figures are sourced from average cost of most recognized EU / US manufacturers, and the Consultant’s experience in the field.

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3. Low cost equipment, that are also widely represented in the international market (but very seldom represent a good investment for National Services), are excluded from this evaluation and are definitely not recommended. 4. The concept of “turn-key Project” was followed. Costs include full installation of new and upgraded station, all SW facilities and licenses for a total of 5 Control Centres (3 main and 2 subsidiaries), models for hydrological and hydraulic forecast to be installed in one of the main centres, as well as full technical assistance and system maintenance for three years. Revision of this parameters, and /or of the number of new or upgraded stations shall of course lead to a correspondent increase or decrease of the final cost. 5. Local taxes or other duties for the import of equipment are excluded. 6. At this stage of the evaluation, en error of +/- 30% is reasonable to be expected.

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ANNEX 1: LIST OF METEOROLOGICAL STATIONS IN BELARUS

Annex 1 - Weather stations in Belarus

Station Elevation Latitude (DD) Longitude (DD)

Auce 1040 56467 22900 Baltijsk 20 54650 19867 Baranovici 1940 53117 26000

Berezino-in-min 1690 53833 28983 Bobrujsk 1650 53117 29250 Borisov 1840 54217 28517 Bragin-in-gomel 1140 51783 30267

Brest 1440 52117 23683 Budslav 1770 54783 27450 Cernjahovsk 320 54617 21817 Chechersk-in- gomel 1420 52917 30900 Doksicy 1930 54883 27767 Ganevici 1570 52750 26433 Gomel` 1270 52450 31000 Gorki-in-mogilev 2030 54300 30983 Grodno 1350 53683 23833 Ivatsevichi 1500 52717 25350 Kazdanga-in-latvia 950 56733 21733 Khelterma (port) 40 58867 23050 Klichev-in-mogilev 1580 53500 29333 Kostjukovici 1640 53350 32067 Lelchitsi-in-gomel 1410 51783 28333 Lepel` 1740 54883 28700 Lida 1580 53883 25317 Lyntupy 2090 55050 26317 Madona 2510 56850 26217 Mamonovo 230 54467 19950 Maryina gorka 1740 53533 28117 Minsk 2340 53883 28033 Mogilev 1930 53900 30317 Molodecno 1550 54267 26867 Mozyr` 1730 52033 29183 Naissaar island 20 59600 24500

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Negoreloye-in-min 1900 53617 27083

Novogrvdok 2770 53600 25833 Orsa 1920 54517 30383 Osmjany 2110 54433 25933 Osmussar island 50 59300 23350 Piieaspea 50 59217 23517 Pinsk 1440 52117 26133 Polock-in-viteb 1320 55467 28767 Pruzany 1670 52567 24467 Radoskovici 1980 54150 27233 Ristna (cape) 90 58917 22067 Rucava 180 56150 21167 Ruhnu saar island 20 57800 23250 Scucin 1780 53617 24767 Senno 1730 54817 29683 Sharkovshchina 1310 55367 27467 Slavgorod 1700 53450 31017 Slavnoye 1930 54300 29433 Sluck 1570 53033 27550 Sorve 20 57917 22050 Sovetsk 370 55083 21867 Stende 700 57167 22500 Svetlogorsk 370 54950 20167 Taurage 350 55250 22283 Telekhani 1550 52517 25850 Urechye 1460 52950 27883 Vasilyevichi 1400 52250 29833 Verhnedvinsk 1330 55817 27950 Vileyka-in-min 1690 54483 26900 Vitebsk 1760 55167 30133 Volkovisk-in- grodno 1520 53167 24450 Vysokoje 1630 52367 23383 Zeleznodorozny 490 54367 21300 Zhlobin-in-gomel 1440 52900 30050 Zitkovici 1380 52217 27883

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ANNEX 2: FULL LIST OF HYDROLOGICAL AND METEOROLOGICAL STATIONS IN THE KALININGRAD OBLAST14

A2.1 HYDROLOGICAL STATIONS

1. 74803 Neman River, Sovetsk city, hydrological post category 2, Rack. Observations are made since 1946. Measurement rate level - at 8 and 20 pm daily. Coordinate system 55005' 21056' 2. 74804 Neman distributary. Matrosovka river, village Mostovoe. Hydrological post 1 category, Rack. Observations are made since 1968. Measurement rate level - at 8 and 20 hours every day, the speed and flow rate of at least 3 times a month. Coordinate system 55008' 21045' 3. 74362 Sheshupe river, village Dolgoe, Hydrological post category 1. Pile. Observations are made since 1955. Measurement rate level - at 8 and 20 pm daily. Coordinate system 54058' 22028' 4. 74413 Pregel river, Chernyakhovsk city. Hydrological post category1, Rack. Observations are made since 1948. Frequency of measurement of - 8 hours daily i20, velocity and flow rate of at least 3 times a month. 5. 74416 Pregel river, Gvardeysk city. Hydrological post category1, Rack. Observations are made since 1946. Measurement rate level - at 8 and 20 h. daily, velocity and flow rate of at least 3 times a month 6. 74416 p. Pregel river distributary – Deima, Gvardeysk city. Hydrological post category 1. Observations are made since 1960. Frequency of flow and speed - at least 3 times a month. 7. 748 428. Angrapa river, Berestovo village. Hydrological post category 1. Rack. Observations are made since 1949. Measurement rate levels at 8 and 20 hours every day, flow rate and the rate of at least 3 times a month. 8. 74431 Pissa river, Green Forest village. Hydrological post category 1, rack-and-pile. Observations are made since 1948. Frequency of measuring the level of 8 and 20 h. daily, flow rate and the rate of at least 3 times a month. 9. 74434 Lava river Springs village. Hydrological post category 1. Observations are made since 1958. Frequency level measurement at 8 and 20 hours every day, flow rate and the rate of at least 3 times a month. 10. 74412 Nelma river, Kostrovo village. Hydrological post category 1, Rack. Observations are made since 1963. Frequency level measurements at 8 and 20 h daily, velocity and flow rate of at least 3 times a month. 11. 74438 p. Mamonovka river, Mamonovo city. Hydrological post category 1, Stake measurements Observations were conducted from 1959. Frequency of measuring the level of 8 and 20 h. daily, velocity and flow rate of at least 3 times a month. 12. 74425 Instruch river, Ulyanovo village. Hydrological post category 1. Observations were conducted from 1946. Stake measurements. Measurement rate - at 8 and 20 hours every day, the speed and flow rate of at least 3 times a month

14 Source: Ros-Hydromet - Kaliningrad Regional Hydrometeorological and Environmental Monitoring Centre 30

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13. 74443 Golubaya river, Ugryumovo village. Hydrological post category 1. Observations were conducted from 1983. Measurement rate levels at 8 and 20 hours every day, the speed and flow rate of at least 3 times a month.

 Currently not working at the post and a number of posts Sheshupe run rough

A2.2 METEOROLOGICAL STATIONS

1. Meteorological Station II М-II Kaliningrad Kaliningrad city discharge

2. Meteorological Station II М-II Mamonovo Mamonovo city discharge

3. Hydrological station I H-I Sovetsk Sovetsk city

discharge and Meteorological 0 0 Station 55 05' 21 56'

4. Meteorological Station II М-II Chernyakhovsk city discharge Chernyakhovsk 54038' 21048

5 Meteorological Station II М-II Zheleznodorozhnyu discharge Zheleznodorozhny settlement

6 Sea hydrographic station I МH-1 Baltiysk Baltiysk city discharge and Meteorological Station

7 Meteorological Station II M-II Pionerskiy Pionerskiy city discharge

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ANNEX 3: PLANNING OF AUTOMATIC WEATHER STATIONS (AWS) AND THE NETWORK

A3.1 GENERAL CRITERIA

A3.1.1 Composition of the single station The single station will be composed by:  one set of sensors, according to the type of station;  one local Data Collection Platform (DCP or Data Logger);  one communication devise (UHF radio, GSM or GPRS mobile data transmitter or satellite);  one power supply subsystem (local network or solar panel + back-up batteries);  all necessary additional devices, accessory and installation materials.

A3.1.2 Sensors

In principle, the following sensors are recommended for the new and upgraded stations:

A3.1.3 Meteorological stations (AWS)

 Atmospheric pressure  Air temperature and humidity  Wind speed and direction  Rain (heated wherever possible)  Snow height  Evaporation  Sunshine duration  Solar radiation (energy)

A3.1.4 Hydrological stations

 Water level  Rain gauge

A3.1.5 Additional notes

Additional sensors, such as visibility for meteorological stations or water flow for hydrological, may be added in specific sites if necessary. These sensors (often relatively costly) are not considered in the current evaluation.

All stations installed in isolated sites, where no energy sources are available, shall be equipped with solar panels for powering. Solar panels shall be dimensioned according to sunshine duration and solar radiation, and shall be resistant to any adverse weather condition, ultraviolet radiation, wind, mechanical impacts and penetration of dust and humidity. For these stations, the installation of heating system for rain will not be possible (no solar panel is able to generate the necessary power); it will be however installed in all stations located in sites equipped with external energy source, usually from public network.

Preliminary indication about sensors’ technology to be applied are given hereinafter:

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A3.2 GUIDELINES FOR SENSORS’ SELECTION

A3.2.1 Wind speed and Direction Most common sensors are composed by a wind vane gonio-anemometer and (usually) three -cups tacho-anemometer, equipped with high quality bearings. Other sensors are based on ultrasonic or even radar technology, the last one being mostly used for marine applications.

Considering the harsh environmental conditions (winter) in the Neman RB, all connectors shall be military watertight type, with all cables sheltered in stainless steel support arms for total protection.

Sensors shall be installed at 10 m height, according to WMO guidelines.

A3.2.2 Air temperature Usually are of integrated type with natural ventilation, painted aluminium housing with double shield protection against solar radiation. Sensor are pre-calibrated and shall not require field re- setting. Reference parameters for the thermometer should range between - 25°C to +60°C or higher. Operating conditions shall however range between -45°C ÷ +60 °C; 0 ÷100 % R.H.

A3.2.3 Relative humidity Reference parameters are 0 ÷ 100% R.H., with accuracy not exceeding 2% over the entire range, and operating conditions between -45°C ÷ +60 °C. Different technical solutions for both air temperature and relative humidity are available, provided that technical specifications are not lower than specified transducers and demonstrating the operative effectiveness.

A3.2.4 Air Pressure

Shall be of fully electronic technology, thus maintaining top reliability and accuracy of measurement under any weather conditions and even in presence of mechanical vibrations. Operating conditions shall be the same as before, i.e. in the range of -45°C ÷ +60 °C; 0 ÷100 % R.H.

A3.2.5 Rain gauge

Rain measurement, joint with T°, is of utmost importance due to climatic change (as very effectively brought to evidence during the mission) and in general N-EU weather conditions. A highly reliable technology must therefore be employed for rainfall sensors.

Tipping bucket sensors with knife support, fully manufactured with metallic material and anti- corrosion protection shall be preferred, in consideration of top performance proved by this type of instruments during WMO testing campaign conducted between 2005 and 2009, comparing in laboratory and field world-wide technologies (WMO intercomparison testing campaign) .

Very good sensors are also available based on precipitation weight measurement. Selection will depend from location and (mainly) “preference” of users. Whichever the employed solution, it is essential that the instrument had successfully passed WMO intercomparison testing campaign. Usual reference parameters are: Funnel (rain collection) area: ≥400 square cm; Resolution: 0,2 mm of rain; measurement range: 0 - 400 mm/h and accuracy: 0.2mm/h maximum at 10mm/h (± 1 %) with temperature 20°C. Operating T° is the usual -45°C to + 60 °C.

A3.2.6 Solar radiation 33

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Sensor for solar radiation (solarimeter) shall permit an accurate and stable measurement of the energy transmitted by the sun for radiation. Reference technology shall be based on high-quality multiple-element thermopile, placed in an airtight double-domed glass container, physically protecting the sensitive element and optimising measurement conditions. Sensor must be protected from condensation. Calibration is essential, and calibration certificates must be supplied by the manufacturers.

A3.2.7 Sunshine duration

Is also a very important sensor for climate change. Photo-diodes technology with specially designed diffusers to record presence or absence of sunshine are the most diffused sensor in use. Spectral range is usually in the interval of 400 - 1100 nm (nanometres = 10-6 mm wave length); accuracy of sunshine hours must exceed 90% on monthly basis; operating temperature in this case shall exceed 70 °C.

A3.2.8 Evaporation

The evaporation gauge is mainly used for agro-meteorological purposes. In this case, it may be of importance to set the hydrological balance, especially during dry seasons. Sensors are usually based on a 1000 mm or more pan in class A stainless steel x 250 mm h. The pan is rested on a painted wooden support to avoid contact with soil, and equipped with a solid-state electronic transducer (pressure gauge) to measures real-time water level. This sensor will also allow comparison with rain pattern, what may be of importance in case of very heavy rains or out-of- service of rain gauges.

Location is very important, to allow easy maintenance (cleaning, water refill during dry season and so on). For these sensors, heating is usually not an option, but their importance is mostly significant during summer. Operating temperature shall exceed 60 °C.

A3.2.9 Water level sensors These sensors are the “core” of hydrological stations, of outmost importance for climate change, flood warning and regular monitoring of surface waters (rivers, lakes, reservoirs). They can also be used for monitoring of underground waters, with proper installation.

In principle and whenever possible, automatic sensors shall be installed avoiding direct contact with water. Ultrasonic or radar sensors are therefore to be preferred, Alternative solutions, such as depth-gauges pressure transducers (where installation problems do not permit the use of ultrasonic or similar) may also be fully viable, but considering that maintenance is more difficult.

Ultrasonic or radar level sensors shall be protected by anti-corrosion radiation shielded for air ventilation with temperature compensation. Acceptable range of measure is 0 – 20 m for ultrasonic and 0-4o m for radar. Accuracy and resolution depend from the distance of sensor from water. Usually admissible error is +/- 1 1 cm. Depth-gauges pressure transducers shall be used mainly in locations where it is impossible or costly to install ultrasonic or radar instruments, because of absence of adequate infrastructure to sustain the ultrasonic or radar sensor, or where variation of water level exceed 20 m (e.g. reservoirs). Measurement range is 0 - 20 m., according to the site; accuracy 0.1% of the full scale. Operating conditions are 0°C ÷ 50 °C for water temperature.

A3.3 DATA COLLECTION PLATFORM (DCP)

With the acronym DCPs are the intended the local acquisition and processing units, to be installed at all automatic observation sites. These are the “brains” of the stations and must guarantee

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efficiency, flexibility and durability. A “normal” DCP shall be able to perform the following basic functions:

a) Automatic acquisition of hydro-meteorological data: it shall be possible to set acquisition intervals and recording intervals independently for each acquisition channel (i.e. the different sensors installed, or other units such as data transmission device, battery, solar panel, sometime key pad and so forth) , and configure acquisition parameters according to the request of the System Administration. It shall be possible to enter commands trough an integrated keyboard

b) Data processing and storage: the acquisition unit shall be capable of doing local treatment of measured data, in order to grant a very reliable data acquisition. Storage is normally operated through a removable memory, capable to store at least 6 months of data on hourly basis (all sensors). c) Data transmission and communication system: i.e. the module(s) to transmit measured data to remote control centres. As already mentioned, this could be Ultra High Frequency (UHF) radio, GSM or GPRS telephone or satellite. A mixed system is also an option, as a function of the specific location of stations. In the case of Neman RB, radio could be a good option if a sufficient (and limited) number of repeaters could be installed in hills or towers (already existing), to cover the whole area. Whichever the proposed solutions, the system shall guarantee the permanent operation of the whole network, with virtually no loss of data. High performing systems may reach the level of 99% of data measured, recorded transmitted and received by control Centres.

A3.4 MAIN AND SUBSIDIARY CONTROL CENTERS

In the case of Neman RB, main Control Centres are recommended to be installed in the three capital cities of Minsk, Vilnius and Kaliningrad, at NHMS headquarters. It is assumed that HW facilities will be already available, or any case will not be considered for the economic evaluation. These centres shall be equipped to perform the following functions:

Shall be equipped with all hardware, LAN/WAN network and software equipment necessary for execution of following main tasks:

 Direct acquisition of data from field stations (Front End functionality)  Data exchange among Centres (main and subsidiary) and authorized users;  Formation and management of a database for the entire river basin, accessible to all Centres and authorized users;  SW modules for hydrological and hydraulic modelling and forecasting. To perform this function, the Centre shall be able to receive also data from meteorological radars and satellite, to be merged with data from ground stations (see paragraphs ____);  Data distribution and dissemination;  Alert and warning dissemination;

As part of Governmental network, it is also recommended to install Subsidiary Centres at CRICUWR, the University of Vilnius and (if necessary) other research institutions, for the corresponding studies and elaboration relevant to Climate Change, as well as for their respective scientific and consultant work. Data processed from these institutions shall be transmitted to main Control Centres and eventually integrated in the Government network, as an essential tool for decision making.

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ANNEX 4 : CONFIGURATION OF TRANS-BOUNDARY EARLY WARNING SYSTEM AND DISASTER PREVENTION

A4.1 INTRODUCTORY NOTE

As pointed out in the initial part of the present report, the most important impact of Climate Change on our environment (actual and expected), is the increased frequency of extreme weather events and the increased “energy content” of the single event. Energy that is more and more producing damages (that often worth billions of Euros) and endangering human lives. Floods and droughts are on the very first line all over the world. But modern technology allow us to “get prepared” against all that, building more and more reliable “Early Warning System” (EWS) and making our forecast capacity more and more accurate, thus offering us the tools we need to reduce disastrous effects, avoid the “impoverishment” of the environment and degradation of common life-style.

The analysis of EWS system, retrieval, diffusion and dissemination of information, active Civil Protection and Disaster Prevention Mechanisms, within the Neman River Basin area (and more in general within the three share-holding Countries), goes beyond the scope of work for the present assignment. The consultant however considers that some preliminary considerations on this regard may be useful, if the decision of upgrading and expanding the Neman River Basin hydro- meteorological monitoring system will ever be taken, according or not with the recommendations of the present report.

A4.2 EARLY WARNING SYSTEM CONFIGURATION

A “modern” EWS is a complex network of monitoring instruments, data transmission devices, interconnected control centres and users, as shown in figures 22 /a (system) and 22/b (monitoring instruments) below::

22/a 22/b

Figure 18: configuration of an hydro-meteorological monitoring and EW system (left) and instruments (meteorological satellites, radars, ground stations) to be integrated (left)

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The following components are necessary:

 Meteorological satellites, capable to furnish information at very wide scale (regional) (image 1 from left);  Meteorological radars, capable to provide rough estimation on probability of rain at mesoscale application (image 2 in middle);  Ground network of Automatic Weather Stations (AWS), generally including meteorological and hydrological stations, soil monitoring, wave sea level and automatic water quality level monitoring and others. Ground based AWS are indispensable not only for the punctual and constant information provided, but for the correct calibration of mesoscale information received from radars, often source of serious misinterpretations (under or over-estimation of phenomena).  Reliable dedicated data transmission system, for the real-time delivery of recorded data to equally dedicated Control Centers.  Duly equipped Control Centers, able to receive the data transmitted and make the necessary elaborations, for the use of national meteorological and hydrological services, the Civil Protection, Disaster Management Agencies and so forth. The overall “information chain”, for the use of Civil Protection and/or Disaster Management Agencies is illustrated in FIG 23 below.

Figure 19: information chain for the prevention of natural disasters and risk reduction

A4.3 MODELLING AND FORECASTING The present section was elaborated by Dr. Cinzia Mazzetti, hydrologist and model expert of PROGEA srl, Bologna, Italy. Dr. Mazzetti gave an essential contribution to the preparation of set of models used for hydrological and hydraulic forecast of floods and droughts in the Po river basin, Italy. The understanding of concepts reported is considered of fundamental importance for a discussion centred on climate change, actual and expected effects and potential remediation measures)

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A4.3.1 Raising preparedness to climate change effects

Recent advances in climate modelling suggest that climate change will is likely to produce effects of increasing intensity in central and N-EU Countries, until present relatively “protected” in comparison with Mediterranean or tropical Countries15. These effects will definitely affect the overall hydrological cycle, magnitude and frequency of intense rains or prolonged dry periods, resulting on increased flood hazards or droughts. Flood hazard may also rise during wetter and warmer winters, with increasingly more frequent rain and less frequent snow.

Flood control and protection measures have played an important role in protecting people and socio-economic development from flooding in the past. Until recently, they have been “engineering centred” and they have largely relied on structural solutions, such as embankments, bypass channels, dams and reservoirs. However climate change poses a major conceptual challenge to water managers, shaking the foundation of the normal assumption that the past is the mirror to future.

It can no longer be assumed that past hydrological conditions will continue into the future. The scientific knowledge about the climate change and its impacts on the hydro-meteorological extremes, such as floods and droughts, is far from fully understood, thereby making it difficult to assess future risks. Due to uncertainty in flood and drought risk scenarios provided by scientists, managers can no longer face effects of climate change using structural measures only, because such approach would oblige them to build oversized structures to deal with extremely low probability events.

When preventive measures are not sufficient, effects of climate change can still be reduced through raised preparedness. Operational Real-Time Early Warning systems form a key part of preparedness strategies for disastrous flood events and drought. Most systems rely on real-time detection of floods through hydro-meteorological observation networks, and while the use of observations is a primary element of a flood warning system, more state-of-the art systems incorporate also a (model based) flood forecasting system. Flood forecasting systems typically use hydrological models to predict short term flood evolution due to a combination of recent and forecast precipitation with the objective of increasing the lead time with which warnings can be delivered. In particular in case of flood events, flood forecasting systems can provide early warnings several days ahead, giving flood forecasting services, civil protection authorities and the public adequate preparation time and thus reducing the impacts of the flooding.

To take the risk of flooding properly into account requires insight into the nature and magnitude of the risks; in other words, the probability of floods and their consequences. Improved hydro- meteorological networks can minimize uncertainties in forecasting and prediction, thereby lessening decision-making risk. This can be achieved in several ways, including new and better- quality information from improved measurements (quantity, quality, timeliness) and measurement techniques. For medium term forecasts (2–15 days ahead), numerical weather prediction (NWP) models should also be used, especially when upstream river discharge data is not available. In general NWPs are essential to establish longer lead-times than the catchment concentration time.

15 Christensen OB, Christensen JH (2003) Severe summertime flooding in Europe. Nature 421:805–806; Semmler T, Jacob D (2004) Modeling extreme precipitation events—a climate change simulation for Europe. Glob Planet Chang 44:119–127; Frei C, Schöll R, Fukutome S, Schmidli J, Vidale PL (2006) Future change of precipitation extremes in Europe: inter-comparison of scenarios from regional climate models. J Geophys Res 111:D06105). 38

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A4.3.2 The Po river (Italy) Early Warning Systems

A remarkable similarity exists between Neman River Basin and Po River Basin, in terms of river catchment extension, river length, flat area crossed (the Po valley), extension and configuration of delta area. However, the two areas differ substantially in terms of vulnerability, because on the density of population in Po river basin (16 M people), compared with still very low density of Neman RB (see figure 24 below).

A number of operational flood warning systems are in use both in Europe and overseas. In recent years a system has been implemented by Italian National Civil Protection Department on the main Italian river. The Po River flows in the Po Valley which is a flat and densely populated area in Northern Italy. The catchment extension is about 71’000 Km2, average flow is 1.540 m³/s and maximum flow at river outlet can raise up to 13.000 m³/s. Due to climate characteristics and river regimes, the catchment area is prone to both flood and drought risk.

Even though it is not a trans- boundary catchment, water management in the Po valley has many characteristics in common with trans-boundary river basins: the river catchment is governed by different Regional Authorities, who play as independent actors in taking decisions both in ordinary water management and emergency situations, thus resembling independent National Authorities. Moreover, due to Italian laws, a large number of local, regional and national authorities are involved in decision making process.

The Po River basin is monitored Figure 25: Po river basin hydro-meteorological monitoring network by a telemetric network of rain gauges, thermometers,

hydrometers (a total of 650 AWS is installed) and from a RADAR network. The monitoring network provides real-time inputs to the Early Warning system. Moreover, in order to increase lead time in flood forecasting, the system is fed with meteorological forecasts provided by LAMI limited area model (deterministic) and COSMO-LEPS system (limited area ensemble prediction system). Real-time hydro-meteorological data and forecasts are used as input to hydrologic and hydraulic models to simulate main stream and affluent behaviour and to forecast emergency situations.

One of the main peculiarities of Po River Early Warning system is that it is composed by two twin systems: the first one devoted to flood forecasting and the second one devoted to drought forecasting. The Early Warning systems share the same fully-distributed hydrological model (TOPKAPI), which is run at hourly time steps in the flood forecasting environment and at daily time steps to forecast drought. This achievement could be reached thanks to the distinctive features of the hydrological model. TOPKAPI is a fully-distributed and physically-based model providing high resolution information on the hydrological state of the catchment. Model equations are based of physical parameters that can be retrieved from thematic maps (DEM, soil type, land cover, ect.) in terms of measurable quantities like soil permeability and channel roughness. The physical

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soundness of the model granted representative simulations of the main component of the hydrologic cycle at different time steps, during both flood events and drought periods.

A4.3.3 Benefits of early warning systems in climate change investigation

The implementation of hydrological and hydraulic models for Early Warning systems can provide benefits to other fields than emergency management, thus supplying to river authorities and the scientific community an instrument to investigate effects of climate change and management decisions on the river basins and river structures.

When a fully-distributed and physically-based hydrological model is linked to a hydraulic model of the river, like in the case of the Po River in Italy, a detail insight on climate change effects on river structures and flood prevention measures can be easily gained. Scenarios of different rainfall patterns, both in spatial distribution and frequency, can be simulated for a large number of years.

If a distributed and physically based hydrologic model is used, simulations can consider significant trigger factors for floods, like antecedent conditions of rivers and the drainage basins (frozen or not or saturated soil moisture or unsaturated) and status. Different simulations can be performed varying precipitation intensity, volume and timing.

Numerical models allow simulating a large variety of scenarios at affordable costs and can be used as a valuable starting point in planning and implementation of adaptive actions.

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ANNEX 5: LIST OF REFERENCES

A5.1 General Interest 1) Information Statement of the American Meteorological Society on Climate Change (AMS Council 20 August 2012). http://www.ametsoc.org/policy/2012climatechange.pdf; 2) Agricultural and Forest Meteorology, 84/1997: Application of geostatiscs to evaluate partial weather station networks: 3) TFWC/2012/2 June 2012: Convention of the Protection and Use of Transboundary 4) Watercourses and International Lakes. Task Force on Water and Climate. Fifth meeting 5) Geneva, Switzerland, 27 April 201; 6) EU Wite paper: adaptating to climate change: towards a European framework for action, Brussels, 2009; 7) EU Common Implementation Strategy for the Water Framework Directory (2006/60/90) 8) IPCC: Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation: Special Report of the Intergovernmental Panel on Climate Change; 9) IPCC: Towards New Scenarios for Analysis of Emissions, Climate Change, Impacts and Response Strategies. Technical Summary of panel held from 19 to 21 September, 2007, Noordwijkerhout, The Netherlands (http://www.ipcc.ch/ipccreports/supporting-material.htm). 10) WMO: Regulatory material, Item 4: Guide on the GOS and Vol. A. Networks of weather observing stations and variables to be measured at these stations; planning of meteorological stations; 11) WMO: Climate Change and Monitoring WCDMP-No 72- Guidelines on Analysis of extremes in a changing climate in support of informed decisions for adaptation, 2009; 12) Danish Meteo Institue: European and global climate change projections: discussions on Climate Change Model Outputs, Scenarios and Uncertainty in the EC RDT Climate Cost Projections. Briefing Note 01. 13) Jurnal of Climate: Empirically Downscaled Multimodel Ensemble Temperature and Precipitation; Scenarios for Norway; Rasmus E. Benestad, The Norwegian Meteorological Institute, Oslo, Norway;

A5.2 Specific interest 1) Belorussian Hydrometeorological Department website (http://hmc.by and www.pagoda.by); 2) Belarus : floods in the past (from www.climateadaptation.eu); 3) Lithuanian hydrometeorological service website (www.meteo.lt); 4) UNCECE Water Convention (several documents) ( http://www.unece.org/env/water/ and http://www.unece.org/env/water/npd.htm)); 5) Management of the Neman River basin with account of adaptation to climate change; Vladimir Korneev (Central Research Institute for Complex Use of Water Resources (CRICUWR), Minsk, Belarus) , Egidijus Rimkus, Edvinas Stonevicius (Vilnius University, Lithuania); 6) Analysis of the monitoring systems in the Niemen River Basin and elaboration of proposals to optimize the systems with account of climate change: Inna Rusaya , Republican Centre of Radiation Control and Monitoring, Minsk, Belarus 7) Forecasting of the Niemen River basin natural runoff in the context of climate change: methodology and results achieved (Belarusian model), Vladimir Korneev (CRICUWR), Aliaksandr Volchak (Brest State Technical University, Brest, Belarus); 8) Forecasting of the Niemen River basin natural runoff in the context of climate change: methodology and results achieved (Belarusian model) 9) Forecasting of the Niemen River basin natural runoff in the context of climate change: methodology and results achieved (Belarusian model) 10) Monitoring of pollution of the River Neman in Kaliningrad, Russia: Natalia Shchagina, Roshydromet, Kaliningrad; 11) Neman RD - Climate change monitoring - Temperature change (°C)(1986-2010 minus 1961-1986) (transmitted by Dr. Vladimir Korneev); 12) Belarus - Assessment of the future change of precipitation in the Niemen River Basin until 2035 (mean value of 2021- 2050) - Scenarios A1b / B1 (transmitted by Dr. Vladimir Korneev); 13) Possible approaches for forecast of the future climate change impact on the water quality: Paul Buijs, the Netherlands; 14) Flood Monitoring System Progress Protects Against Floods in Belarus, Ukraine. Alexei Iarochevitch, NATO project partner director at Kiev, Belarus / Ukraine, 21 June 2012; 15) OECD: adaptation for climate change: key terms. Ellina Levina and Dennis Tirpak, May 2006