The Study on Integrated Water Management Final Report - Main Report in the Republic of Bulgaria Chapter 3

CHAPTER 3 GIS DATABASE

3.1 Introduction

The project objective, concerning GIS as stated in the Inception and Interim Report, is the development of GIS Database (GIS-DB) for storing all basic data and information needed for the river basin management. The GIS database and the integrated basin analysis model are effective tools for the development and update of the river basin management plan.

The main purpose of GIS-DB for MoEW is to create an effective geo-spatial database, using contemporary GIS principles and technologies, based on international and national standards and legislation.

The GIS-DB is designed to provide MoEW and related organizations with accurate and up-to-date geographic information, related to the river basin management.

The development of the GIS-DB is based on the existing technical infrastructure (software, hardware) of MoEW and related institutions, but it introduce and implement additional software products, technologies and procedures for use of geographical data.

The general functions for the use of the GIS-DB for MoEW are:

• Collection and integration of digital and non-digital data from variety of sources and formats to a standardized and structured model;

• Storing of geographic information and other related non-spatial information on a geodatabase level;

• Actualization of the geographic and other related non-spatial information;

• Performing of analysis and modeling of the geographic information;

• Facilitating the exchange of geographic information between the different informational databases within MoEW system;

• Exchange of geographic information with external systems (other ministries, governmental institutions, European commission).

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The organizational structure of the GIS-DB will be in MoEW (Water Directorate), ExEA and four RBDs.

The informational scope of GIS-DB includes three main parts (see Figure 3.1.1):

• Core Portion of GIS-DB – basic data, including fundamental data common to all basin directorates;

• WFD Portion of GIS-DB – specialized data, required by the Water Framework Directive;

• Local Portion of GIS-DB – specialized data, used by River Basin Directorates and MoEW, following the Water Act regulations.

This figure illustrates the main parts of the GIS Data Model.

The Core Portion includes all fundamental data, which covers the whole territory of Bulgaria. It provides the “common picture” and up-to-date map of country, including over 40 layers of information.

Local Portion of the Data Model provides information, which is generated and used by the River Basin Directorates. The Local Portion of the Data Model is build and maintained “on the top” of the Core Portion.

WFD portion of the Data Model provides information for the reporting requirements to EU. This data is generated from Core Portion and Local Portion, following the WFD data requirements.

All these three parts form an Integrated GIS Data Model for MoEW and RBDs.

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3.2 Main Principles and Stages of GIS Data Modeling and Development

3.2.1 Main Stages in GIS Data Model Development

All GIS systems are built using formal models that describe how things are located in space. A geographic data model defines the vocabulary for describing and reasoning about the things that are located on the earth.

Data modeling is simply building a structure for data, including tables, relationships, specifications, metadata, identification, feature definition, topology rules, etc. The essential tasks in these activities include: • Gathering of information and requirements analysis for: • Maps and visualization products required; • Analysis and decision support products required. • Design and development: • Conceptual design: identify data, metadata, specifications, relationships, etc; • Physical data model: identify GDB feature datasets, classes, relationships, domains, subtypes, geometric networks, linear referencing systems, topology rules, etc.

Through the project the stage of assessment and requirements analysis included two main tasks: • Collection of spatial data from MoEW, RBDs, ExEA, NIMH, NSI, MAF and many other governmental institutions; • Collection data resources regarding WFD regulations, Water Act regulation and other Bulgarian, European and International regulations and standard.

Based on the collected data and resources and after evaluation and validation of the data we started the design and development of the GIS Data Model.

The design stage including conceptual modeling of the data often require document, describing what will be in the data base, how data will be organized, etc. Developed during the project are conceptual and detail technical documents for all three main parts of the data model.

After the design of the conceptual data model we started the development of the physical data model. An ongoing procedure of these activities was constant collection and validation of spatial and non-spatial data to be loaded in the final GIS database.

The figure below gives an overview of the Data development activities and other activities during the project.

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GIS-DB Development Activities in the study

The Design for Technology or Guideline for future Integrated Information System (IIS) of MoEW and related institutions was produced in the form of Terms of Reference for IIS.

The training was organized in training courses on the main parts of the data model.

3.2.2 Main Elements of the GeoDataBase

The ESRI GeoDataBase format that is used for the physical development and implementation of the GIS Data Model. The geodatabase supports a variety of modeling, management, and analysis functions. One of its key benefits is that its implementation of tables, feature classes, feature dataset, and rules allows you model reality more closely than was possible with other data models. The geodatabase data model can minimize the differences between logical and physical models of reality by incorporating more intuitive data objects. The GeoDataBase provides many advantages such as: • Centralized spatial and attribute storage; • Easy to use standard behavior rules including domains, subtypes, topology and networks; • Multiple customization options; • Easy to import, export and share schema with or without data.

GeoDataBase contains various types of objects: • Tables - store non-spatial objects like monitoring data for hydrometric stations; • Feature classes are collections of lines, points or polygons. Specialized feature classes are used to store annotation, dimension and route features; • Feature datasets are container for feature classes that share a common spatial reference. They are required for geometric networks and topologies; • Relationship classes manage thematic relationships between tables, feature classes, or a combination of the two. They enforce referential integrity between the origin and destination classes;

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• Geometric networks are specialized topological relationships between line and point feature classes that are used to perform analysis on directed flow network systems; • Raster datasets are gridded data derived from a variety of sources (IMG, PG, etc.); • Raster catalogs are tables that reference a collection of raster image files; • Survey datasets store survey information and can group survey data into Project’s, for direct use or improvement of existing feature geometry; • Toolboxes contain geoprocessing tools used in the geoprocessing framework; • Behavior rules may be created to define legal attribute values, thematic relationships between classes, topological relationships between features, and connection between network features; • Linear referencing system – one-dimensional linear system (rivers) for input and recording of data.

All data types and the main advantages of the GeoDataBase provide state of the art capabilities for MoEW GIS data model.

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3.3 Structure of GIS Data Model

As described in the introduction the GIS data model is compiled from three main parts: Core Portion, WFD Portion and Local Portion.

All parts of the data model are in a common coordinate reference system - WGS 84, UTM Zone 35N.

The Core Portion of the data model should be stored and maintained on a central level and distributed to all users (RBD’s) on a regular basis.

The WFD Portion should be produced from the Core Portion on a regular basis as defined in the WFD requirements.

The Local Portion should be developed and maintained on the top of the Core Portion of the Data Model.

Figure 3.3.1 shows the general structure of the data model:

3.3.1 Detail Structure of Core Portion

The Core Portion of the Data Model is build following the main GIS principles for completeness, consistency and accuracy. The Core Portion uses and steps on many national and international standards and regulations in order to produce a standardized data model for the countrywide use.

Main parts of the Core portion are organized on a thematic principle and are as follows:

(1) Thematic Group “Administrative”

This thematic group of data includes information on the administrative – territorial division of the territory of Bulgaria. The data have been structured pursuant to the Administrative – Territorial Structure of the Republic of Bulgaria Act. This Act arranges the development of administrative – territorial and territorial units in the Republic of Bulgaria and the conducting of administrative – territorial changes. Pursuant to the Act administrative – territorial units are regions and municipalities, compound administrative – territorial units in the municipalities are city/town halls and districts, аnd territorial units are populated places and settlement formations. The populated places are towns and villages.

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The basic layers relationships include:

"Sub-division of municipality (Zemlishte)" is the aggregate of land properties, belonging to a certain populated place (settlement). The Zemlishtes’ borders shall be identified and defined in an order, stated in an act.

The municipality territory includes the territory of populated places, included in it. The boundary is formed by the zemlishtes’, belonging to the municipality.

Region borders’ amendments could be conducted only along the borders of existing municipalities. The amendment shall be approved by a Decree of the President of the Republic of Bulgaria on a proposal of the Council of Ministers.

Based on existing regulation and collected data we have identified the following layers of information: • A_BgBorder_Line - this layer represents information on the border of Republic of Bulgaria, like linear feature class. • A_BgBorder_Poly - this layer represents information on the border of Republic of Bulgaria, like polygon feature class. • A_BgRegion - this layer represents information on the Planning Regions in the Republic of Bulgaria, like polygon feature class. • A_BgDistrict - This layer represents information on the Regions in the Republic of Bulgaria, like polygon feature class. • A_BgMun - This layer represents information on the municipalities in the Republic of Bulgaria, like polygon feature class. • A_BgZem - This layer represents information on the Sub-divisions of municipalities in the Republic of Bulgaria, like polygon feature class. • A_BgSettle_Poly - This layer represents information on the populated places in the Republic of Bulgaria, like polygon feature class. • A_BgPlace_Point - This layer represents information on the populated places in the Republic of Bulgaria, like point feature class. • Census_2001-2005 - These Attribute Tables represent information on the population in the Republic of Bulgaria, like Attribute Tables.

(2) Thematic Group “Hydrography”

This thematic group includes information on the Basin Directorates’ borders, Water Catchments, River Network, Channels, etc.

The basic layers relationships include:

The Layer with Basin Directorate borders’ has been developed, using the water catchments’ borders on the grounds of Article 152 of the Water Act. The Basin Directorates’ borders coincide with the state border of the Republic of Bulgaria.

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The Layer of River Basins includes the main rivers’ river basins. The river basins coincide with the Basin Directorates’ borders and the state border, with the exception of parts of the border between Danube Basin Directorate and Black Sea Basin Directorate.

The Layer with Water Catchments includes the water catchments of 550 rivers in Bulgaria. The water catchments fall within the water catchment basins’ borders, the Basin Directorates’ borders and the state border. The water catchments have been organized on the basis of two rivers’ inflow or a river and a lake inflow, with the addition of “own” water catchments of significant reservoirs, as defined in Annex 1 of the Water Act.

The Layer with Rivers includes all the rivers in Bulgaria in a scale 1:100 000. Rivers have been structured from the inflow of two rivers or the inflow of a river and a lake (from junction to junction). The rivers fall into the water catchments’ borders, the river basins’ borders, the Basin Directorates’ borders (with the exception of parts of the border between Danube Basin Directorate and Black Sea Basin Directorate) and the state border.

The Layer with Lakes includes all the lakes in Bulgaria in a scale 1:100 000. The Layer with Lakes falls within the water catchments’ borders, the river basins’ borders, the Basin Directorates’ borders and the state border of the Republic of Bulgaria.

The Layer with Channels includes all the channels in Bulgaria in a scale 1:100 000. The Layer with Channels falls within the state border of the Republic of Bulgaria.

The Layer with Linear Referencing System includes a linear system of all the main rivers. The Layer with Linear Referencing System falls within the river basins’ limits, the Basin Directorates’ limits and the state border of the Republic of Bulgaria.

The Layer with Danube River includes the Danube River delineation. The Republic of Bulgaria state border passes along the river midstream and has been defined by the Chief Directorate “Border Police”.

The Layer with Islands includes all islands, which fall into Danube River (Bulgarian and Romanian). The Layer with Islands falls within the Danube River delineation.

This thematic group includes the following layers: • H_RBD: This layer represents information on the Basin Directorates’ borders in the Republic of Bulgaria, like polygon feature class. • H_RivBasin: This layer represents information on the river basins’ borders for the I rank rivers in the Republic of Bulgaria, like polygon feature class. • H_Catchment: This layer represents the Water catchments in the Republic of Bulgaria, like polygon feature class. • H_River: This layer represents information on rivers in the Republic of Bulgaria, like linear feature class. • H_Lake: This layer represents information on lakes and reservoirs in the Republic of Bulgaria, like polygon feature class. • H_Channel: This layer represents information on the Channels in the Republic of Bulgaria, like linear feature class.

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• H_River_LRS: This layer represents information on the Rivers in the Republic of Bulgaria (first, second and third rank rivers), as well as linear referencing system. • H_Danube: This layer represents information on the Danube River in the Republic of Bulgaria, like Polygon Feature Class. • H_Island: This layer represents information on the Danube River islands, like Polygon Feature Class.

(3) Thematic Group “Transportation”

This thematic group of data consists of information on the road and railroad network at the territory of Bulgaria.

The basic layers relationships include:

The Layer with Roads is linked to the point layer of settlements (the points of settlements are “attached” to the road lines). The layer of road network is represented via a geometric network, which allows navigation and optimal routes’ determination.

The Layer with Roads and the Layer with Rail Roads fall into the Republic of Bulgaria state border.

This thematic group includes the following layers: • T_BgRoad: This layer represents information on the Road network in the Republic of Bulgaria, like geometric network. • T_BgRailRoad: This layer represents information on the Rail Road network in the Republic of Bulgaria, like linear feature class.

(4) Thematic Group “Other Data-Reference”

This thematic Group of Data contains additional information on elevations, horizontals, earth cover, soils, geology, etc. for the whole country territory.

This thematic group includes the following layers: • O_BgElevPoint: This layer represents information on elevation points in the Republic of Bulgaria territory, like point feature class. • O_BgContour: This layer represents information on horizontals in the Republic of Bulgaria territory, like linear feature class. • O_BgCorine: This layer represents information on land cover in the Republic of Bulgaria territory, like polygon feature class. • O_BgErosion: This layer represents information on accessibility of soils to erosion at the territory of Republic of Bulgaria, like polygon feature class. • O_BgSoil: This layer represents information on soils at the territory of Republic of Bulgaria, like polygon feature class. • O_BgGeology: This layer represents information on the Geology at the territory of Republic of Bulgaria, like polygon feature class.

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• O_HydroGeology: This layer represents information on the hydroGeology at the territory of Republic of Bulgaria, like polygon feature class • O_ProtectedArea: This layer represents information on the Protected Areas at the territory of Republic of Bulgaria, like polygon feature class. • O_Natura2000_pSCI: This layer represents information on the Special Areas of Conservation borders, pursuant to the EC Habitats Directive, defined in NATURA 2000 Project, like polygon feature class. • O_Natura2000_SPA: This layer represents information on the Special Areas of Conservation borders, pursuant to the EC Birds Directive, defined in NATURA 2000 Project, like polygon feature class. • O_Mine: This layer represents information on Mineral Resources deposits at the territory of Republic of Bulgaria, like polygon feature class.

(5) Thematic Group “Rasters and Image Base”

This Thematic gtroup of data contains information for Digital Elevation Model, satellite images, scanned and georeferenced topographic maps for the territory of Republic of Bulgaria.

This thematic group includes five raster catalogs: • Raster catalog “Satellite”: In this Raster Catalog information is preserved on two satelite images of the Republic of Bulgaria territory. The satellite images have been represented as ortho rectification Landsat ETM (Enhanced Thematic Mapper) in 34 and 35 zones. • Raster catalog “Elevation”: In this Raster Catalog information is preserved on two Raster Layers: Digital elevation model (DEM) and Hillshade. The DEM is with pixel size 50x50 meters. Hillshade is obtained by DEM via a special algorithm for Multi-Dimensional Oblique Weighting, and the result obtained is a more realistic Hillshade. • Raster catalog “HydroRasters”: In this Raster Catalog information is preserved on two Raster Layers: Flow Direction and FlowAccumulation, for the Republic of Bulgaria territory. These two layers’ destination is their use in generating of water catchments for a random location of the terrain or for outlining the direction of outflow of a random point at the terrain. • Raster catalog “TopoMap_100000”: In this Raster Catalog information is preserved on 67 raster images of scannered and georeferenced topographic maps in a scale 1:100 000 for the Republic of Bulgaria territory. • Raster catalog “TopoMap_25000”: In this Raster Catalog information shall be preserved on raster images of scannered and georeferated topographic maps in a scale 1:25 000 for the Republic of Bulgaria territory. As these maps are present at the Basin Directorates, they could be added in addition to the Geo Data Base.

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(6) Thematic Group “Monitoring”

The Monitoring data is stored in the Time Series. The Time Series data model includes data from National monitoring. The GIS information from the stations is connected to the monitoring information from the time series for analysis purposes. Additionally an automatic import procedure is developed in order to fill in all monitoring data from different institutions, different formats and structures into a common database. The import procedure comes with tutorial and step-by step wizard.

This thematic group includes the following layers: • Climatic_Stn: This layer represents information for the climatic stations from NIMH for the territory of Bulgaria, as point feature class. • GW_Quality: This layer represents information for the GW Quality stations from ExEA for the territory of Bulgaria, as point feature class. • GW_Springs: This layer represents information for springs from NIMH for the territory of Bulgaria, as point feature class. • GW_Wells: This layer represents information for wells from NIMH for the territory of Bulgaria, as point feature class. • Hydrometric_Stn: This layer represents information for hydrometric stations from NIMH for the territory of Bulgaria, as point feature class. • Precipitation_Stn: This layer represents information for precipitation stations from NIMH for the territory of Bulgaria, as point feature class. • SW_Quality: This layer represents information for SW Quality stations from ExEA for the territory of Bulgaria, as point feature class. • Synoptic_Stn: This layer represents information for the synoptic stations for the territory of Bulgaria, as point feature class. • DHI_IDManager: This table contains information for the automatic DHI ID, which is maintained by the Time Series database. • DHI_Sensor: This table contains information for links between the GIS objects (monitoring stations) and the table data (monitoring measurement values). • DHI_TimeSeries: This table contains the information for the Time Series, for each monitoring station. • DHI_TSGroups: This table contains information for the Time Series groups of monitoring data. • DHI_TSValues: This table contains information for the Time Series Values and stores the actual measurements.

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(7) Part “Analytical Layers”

This Thematic Group of Data contains additional information on Layers, which are used for analysis and modelling in the study. This Group of data shall not be considered as a part of the Core Portion of the data model. As data have been collected and structured for the whole country, they were included as an information of reference in the model supplied.

This thematic group includes three Raster Catalogs: • Raster catalog “Precipitation”: In this Raster Catalog information is preserved on the precipitation average monthly values in 12 raster layers (one layer for each month) and an average annual value in 1 raster layer for a 50 years’ period (1950-2000). • Raster catalog “PET”: In this Raster Catalog information is preserved on the average monthly values of the potential evapotranspiration in 12 raster layers (a layer for each month) and an average annual value in 1 raster layer for a 50 years’ period (1950-2000). • Raster catalog “Temperature”. In this Raster Catalog information is preserved on the average monthly values of temperature in 12 raster layers (a layer for each month) and an average annual value in 1 raster layer for a 50 years’ period (1950-2000).

(8) Part “Supplementary Layers”

In the Core Portion of the data model there are also some “Supplementary” data, which includes information from neighboring countries and data for Irrigation systems in Bulgaria. This data is defined as “supplementary” because is collected from different sources and although checked and verified cannot follow the same data quality standards as Core Portion. For example the data for neighboring countries is collected in scale 1:1 000 000 from free sources and can be used for visualization purposes only; the data for Irrigation is collected from different sources – topographic maps in 1:100 000, 1:25 000, different sketches and drawings, site visits and local experts knowledge – although up-to-date and correct this data cannot follow the standards used for other data in Core Portion.

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(9) Thematic Group “Neighbour_Countries”

This Thematic group includes data for neighboring to Bulgaria countries. This data can be use for map preparation and general overview of the region.

This thematic group includes the following layers: • N_EU_Borders: This layer represents information for the boundaries of neighboring to Bulgaria countries, as polygon feature class. • N_EU_Districts: This layer represents information for the districts of neighboring to Bulgaria countries, as polygon feature class. • N_EU_Settle_Points: This layer represents information for the settlements of neighboring to Bulgaria countries, as point feature class. • N_EU_Urban_Areas: This layer represents information for the urban areas of neighboring to Bulgaria countries, as polygon feature class. • N_EU_Catchments: This layer represents information for some catchments of neighboring to Bulgaria countries, as polygon feature class. • N_EU_WaterObjects: This layer represents information for the water objects of neighboring to Bulgaria countries, as polygon feature class. • N_EU_Road: This layer represents information for the roads of neighboring to Bulgaria countries, as line feature class. • N_EU_RailRoad: This layer represents information for the railroads of neighboring to Bulgaria countries, as line feature class.

(10) Thematic Group “Irrigation Systems”

This thematic group of information includes data for Irrigation Systems. This data is extracted from topographic maps from scale 1:25 000, sketches and drawings from Irrigation Systems Company, etc. Additional validation is made based on rivers, settlements and lakes from the Core Portion.

This thematic group includes the following layers: • I_ChannelPipe: This layer represents information for the channels and pipes, used for irrigation purposes, as linear feature class. • I_CompensatingBasin: This layer represents information for the compensating basins, as point feature class. • I_Dam: This layer represents information for the Dam, used for irrigation purposes, as polygon feature class. • I_WaterIntake: This layer represents information for Water Intake, used for irrigation purposes, as point feature class. • I_PumpStation: This layer represents information for Pump Stations, used for irrigation purposes, as point feature class.

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• I_IrrigationSystem: This layer represents information for the Irrigation fields and Irrigations systems, as polygon feature class. • I_Dikes: This layer represents information for Dikes, as line feature class.

3.3.2 Detail Structure of WFD Portion

This part of the Data Model includes information, necessary for reporting and using of the Water Framework Directive. The information has been developed on the basis of Guidebook No 9: “Implementing the Geographical Information System Elements (GIS) of the Water Framework Directive”. The information in WFD is prepared to the extend of currently available and defined digital data.

This part of the data model includes the following layers: • Compauth: The Layer full name is Competent authority. This Layer represents information on the competent authorities’ borders, like polygon feature class. • Cwbody: The Layer full name is Coastal Waters. This Layer represents information on Coastal Water Bodies, like polygon feature class. • Ecoreg: The Layer full name is Eco region. This Layer represents information on EcoRegions, like polygon feature class. • Gwbody: The Layer full name is Ground Water Body. This Layer represents information on Ground Water Bodies, like polygon feature class. • GWStn: The Layer full name is Ground Water Monitoring Station. This Layer represents information on Ground Water Monitoring Stations, like point feature class. • Lwseg: The Layer full name is Lake Water Segment. This Layer represents information on the Lake Segments, like polygon feature class. • Lwbody: The Layer full name is Lake Water Body. This Layer represents information on Lake Water Bodies, like polygon feature class. • Protarea: The Layer full name is Protected Areas. This information represents information on Protected Areas, like polygon feature class. • RBD: The Layer full name is River Basin District. This Layer represents information on Basin Directorates’ borders, like polygon feature class. • Rivbasin: The Layer full name is River Basin. This Layer represents information on the River basins, like polygon feature class. • RivSubBasin: The Layer full name is River Sub Basin. This Layer represents information on the River Sub-basins, like polygon feature class. • Rwseg: The Layer full name is River Water Segment. This Layer representes information on River segments, like linear feature class. • Rwbody: The Layer full name is River Water Body. Тhis Layer represents information on River Water Bodies, like linear feature class. • SWstn: The Layer full name is Surface Monitoring Station. This Layer represents information on Surface Monitoring Stations, like point feature class. 3-14 JICA CTI Engineering International Co., Ltd.

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• Twbody: The Layer full name is Transitional Water Body. This Layer represents information on „Transitional Water Bodies”, like polygon feature class. • Fweccls: This Table describes the status of „Fresh” Waterbodies. • GWStatus: This Table describes the Ground Waterbodies’ status. • Pchemcls: This Attribute Table describes the Water bodies’ PhysicoChemical Classification status. • Saleccls: This Attribute Table describes the „Saline” Waterbodies’ status/ Saline Ecological Classification. • Swstatus: This Attribute Table describes the SurfaceWaterbodies’ status.

3.3.3 Detail Structure of Local Portion

Local portion of data model includes the following groups of information: • “Cadastre” group of data; • “Permissions” group of data; • “Monitoring” group of data; • “Other” data.

These groups are organized following the organizational structure of the River Basin Directorates and includes to corresponding GIS information in each department.

(1) “Cadastre” Group of Data

This thematic group of data, including information on the Sanitary Protected Areas, as defined in Regulation No 3 from 16.10.2000 of the Water Act.

The „Cadastre“ group of data is developed for the needs of „Water and Water Economy Cadastre“ Department. The information within the Department is developed and used in a Coordinate system 1970. The data in this group shall be structured in separate Groups of data (Feature Datasets) by zones. The information from this department shall be recorded in the Central Group of data in a coordinate system WGS84, UTM Projection Zone 35N for use from other departments.

“Cadastre” group of data includes the following thematic layers with spatial information and additional attribute tables. • SPA (Sanitary Protected Areas): This Layer represents information on the Sanitary Protected Areas, within the Basin Directorate territory, like polygon feature class. • PA_Bath: This Layer represents information on Protected Areas for Bathing, within the Basin Directorate, like polygon feature class. • PA_Fish: This Layer represents information on Protected Areas for Fish breeding. • MapSeries_25000: Map series of scanned and georeferenced topographic maps.

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(2) “Permissions” Group of Data

Main types of permission – water intake, water use and discharge, structure GIS data with location of permissions – the basic types of Layers. Each type of permission has corresponding purposes. For example gravel excavations or sand pits are located in layer SW_Use, Permission purpose type: gravel excavations.

“Permissions” group of data includes the following thematic layers with spatial information and additional attribute tables. A list of layers: • SPA (Sanitary Protected Areas): This Layer represents information on the Sanitary Protected Areas, within the Basin Directorate territory, like polygon feature class. • PA_Bath: This Layer represents information on Protected Areas for Bathing, within the Basin Directorate, like polygon feature class. • PA_Fish: This Layer represents information on Protected Areas for Fish breeding. • MapSeries_25000: Map series of scanned and georeferenced topographic maps.

(3) “Permissions” Group of Data

Main types of permission – water intake, water use and discharge, structure GIS data with location of permissions – the basic types of Layers. Each type of permission has corresponding purposes. For example gravel excavations or sand pits are located in layer SW_Use, Permission purpose type: gravel excavations.

“Permissions” group of data includes the following thematic layers with spatial information and additional attribute tables. A list of layers: • P_SW_Intake: This Layer represents information on the location of water intake – surface water, falling within the Basin Directorate territory, like point feature class. • P_GW_Intake: This Layer represents information on the location of water intake – surface water, falling within the Basin Directorate territory, like point feature class. • P_MW_Intake: This Layer represents information on the location of mineral water places, falling within the Basin Directorate territory, like a point feature class. • P_SW_Use: This Layer represents information on the location of places for water use – surface water, falling within the Basin Directorate territory, like point feature class. • P_GW_Use: This Layer represents information on the location of places for groundwater use, falling within the Basin Directorate territory, like a point feature class.

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• P_Discharge: This Layer represents information on the location of places for discharge (domestic and industrial water), falling within the Basin Directorate territory, like point feature class. • F_HydroFacility_Line: This Layer represents information on hydraulic facilities, falling within the Basin Directorate territory, like a linear feature class. This Layer shall be used for linking HPP and water intake for a HPP, as well as for other objectives (WWTP - discharge of a WWTP). • F_HydroFacility_Point: This Layer represents information on the location of linear infrastructure systems and facilities, crossing water bodies – aqueducts, bridges, portable networks and lines. This layer is represented as point feature class. • F_DischargeFacility_Point: This Layer represents information for the Discharge Facility Point, as point feature class. This layer is to be connected to discharge point thought F_HydroFacility_Line. • F_HPS: This Layer represents information on the location of HPP, falling within the Basin Directorate territory, like point feature class. HPP have been spatially represented with the location of HPP site. Information on the water intake for a HPP shall be available in Water intake Surface Water Layer, with an objective for water use - HPP. The relation between the HPP site and the HPP water intake shall be effected via a „straight” line from F_HydroFacility_Line Layer. • F_WWTP: This Layer represents information on the location of the Waste Water Treatment Plants, as point feature class.

(4) “Monitoring” Group of Data

The “Monitoring” group of data includes the following thematic layers with spatial information and additional attribute tables. A list of layers: • Data from permissions with location of structures by basic types of permissions; • Own monitoring Tabular data.

In addition data are used from: • Monitoring stations from “Core Portion” of data model; • Tabular data in a time series’ format.

The monitoring data at Basin Directorates shall include two basic groups of information: data from the National Network for Monitoring of Water and data from own and control monitoring, related to the procedures of issuing of permissions.

The data from the National Network for Monitoring of Water is structured in the „Core portion“ of the data model. The structure is in Time Series, allowing an analysis of statistical rows. The monitoring data are still under processing and they shall be input into the developed structure of data.

The own monitoring data, affected on the Basin Directorate territory, shall be attached to the GIS objects form the „Permissions“ Group of data. The place of performing the own

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monitoring shall coincide with the location of the permission in GIS, and the relation between the Protocols for measurements and the object in GIS shall be realized along with the number of permission and the serial number of point (оbject) from the respective permission.

(5) Group of Data “Other”

The thematic group of data „Other“ include other data, which shall be used at the Basin Directorates, but which is not directly related to cadastre, monitoring and permissions. Тhese data shall be obtained from sources outside the Basin Directorates or they shall be developed according to the needs of certain departments/experts within the Basin Directorates. Тhis group of data should be expanded and supplemented.

The group of data “Other” includes the following thematic layers with spatial information and additional attribute tables. A list of layers: • O_Waste_Landfills: This Layer represents information on waste landfills in the Basin Directorate territory, as point feature class. • О_Lagoon_Sites: This Layer represents information on earth lagoons in the Basin Directorate territory. • O_Uranium_Mines: This Layer represents information on Uranium extraction mines in the Basin Directorate territory, as polygon feature class. • O_Industry: This Layer represents information on industries (without permissions) in the Basin Directorate territory, as point feature class. • O_Tailing_Ponds: This Layer represents information on the tailing ponds in the Basin Directorate territory, as polygon feature class. • O_Pestiscide_Storages: This Layer represents information on the pesticides’ storages in the Basin Directorate territory, as point feature class. • O_CrossSection: This Layer represents information on river cross-sections, falling within the Basin Directorate borders, as point feature class.

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3.4 GIS Activities

Apart from the GIS Data Model development other main GIS activities during the project were as follows: • Establishment of GIS workgroup; • Development of Terms of Reference for Integrated Information System for MoEW and related institutions (supplied as separated Annex); • Training of counterparts.

3.4.1 GIS Workgroup Activities

The GIS Workgroup was established with the main purpose for discussion, review and acceptance of the common structure of the GIS Data Model, including all main parts.

There were five official meetings of the GIS workgroup and one additional interim meeting.

The GIS Workgroup includes participants from MoEW, all River Basin Directorates, ExEA and JICA Study Team members.

Main topics, which were discussed, were as follows: • Review of the collected data from all RBDs: data condition and structure; • Review and discussion on Core Portion of data model – review of documentation and geodatabase; • Review and discussion on WFD Portion of data model – review of documentation and geodatabase structure; • Review and discussion on Local Portion of data model – review.

Detail documentation for each main part of the data model was delivered to the Workgroup participants. All participants provided feedback with comments and recommendations for improvement of the data model. Based on the feedbacks the structure of all part of the data model was modified and finalized.

Each meeting of the Workgroup and all activities and decisions were documented with official meeting protocols signed by all participants.

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3.4.2 GIS Training

The GIS training includes trainings of all members of GIS Workgroup. For EABD and WABD there was training on their premises, which included additional GIS personal from different departments. Main topics of the trainings were: • Introduction of main building blocks of GeoDataBase; • Review and use of Core Portion of the Data Model; • Review and use of the WFD Portion of the Data Model; • Review and use of the Local Portion of the Data Model.

Each training was conducted based on a preliminary developed and approved program and with list of participants.

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3.5 Conclusions, Recommendations and Results

In the first phase of the project was conducted extensive evaluation of the current status of MoEW and RBD’s in regards to GIS.

The main conclusions of the analysis of GIS in MoEW system, as stated in the Interim Report are as follows: • A major problem specified explicitly by all four RBDs is the condition of GIS data, especially for layers standardization, work methodology standardization, boundary area issues and other. There is no consistent data format and data model for four basin directorates and MoEW; • There is a variety of different digital data, collected from different organizations, in different time periods, different coordinate systems and scale. The data is structured, maintained and use in different ways within the directorates and MoEW. This cause significant problems inside the basin directorates departments, between the basin directorates and between basin directorates and MoEW (especially for reporting activities to EC); • The condition of GIS data in all four RBDs includes (based on the collected and verified data): • Topological errors (by WFD topological rules and other standards); • Referential errors (compared to 25 000, 100 000 topographic maps, satellite images and additional map sources for reference – hydrological maps and atlases of Bulgaria); • File naming issues (layers, attributes) – use of different naming conventions in different RBDs; • Metadata issues – lack or no update and maintenance of metadata information; • Digital formats – use of different formats for data storage (GeoDatabase, shape files, MS Excel, MapInfo Tab, MS Access, ZEM, text files). • Lack of GIS working group or GIS coordination unit in MoEW, which should produce main guidelines and coordinate activities between RBDs; • A minimum GIS hardware and software is installed in the RBDs allowing initial input of basic GIS data and fulfillment of most urgent GIS tasks; • To the present day sector experts as additional tasks apart from their main obligations undertook the GIS activities in the RBDs. Generally there is constant lack of IT and GIS expert; • In all RBDs the GIS experts feel the need for specialized GIS training; • Lack of clear GIS DB specifications; • Lack of clear metadata specifications.

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The priority matters identified in the Interim report for improving GIS status are: • Increase the Number of GIS staff and additional training for existing staff; • Establishment of GIS Database Specification and Explicit metadata; • Developing of spatial data from accurate and reliable sources with will allow correct modeling and analysis activities; • GIS maintenance and guideline.

Through the second phase of the project, the GIS activities were concentrated on: • Ongoing development of data for Core Portion, WFD Portion and Local Portion, based on accurate and reliable sources; • Ongoing development and support for the development of water quality and water quantity models; • Finalization of clear GIS Database specifications for Core Portion with complete digital data; • Finalization of clear GIS Database specifications for WFD Portion and input all available and defined data in the project time frame; • Finalization of clear GIS Database specification for Local Portion and input most of the available data for WABD, EABD and pilot areas in BSBD and DBD; • Development of extensive documentation for each part of the data model; • Establishment and collaboration of GIS Workgroup for development of data model and related GIS issues; • GIS Training of counterparts.

The main results of the GIS activities from the study can be summarized as follows: • Development of standardized data model for the needs of MoEW and RBDs, which includes Core Data Model, WFD Data Model and Local Data Model; • Technical GIS training of MoEW, ExEA and RBDs personal; • Establishment and collaboration of activities of the GIS technical workgroup; • Development of TOR for future information systems of MoEW and RBDs.

The main recommendations for future work activities in regards to GIS are as follows: • MoEW should continuously maintain and expand the Core Portion of the Data Model. This could be achieved with the specialists of Water Directorate, specialists of ExEA or to be outsourced to external company. Considering the available resource may be most appropriate solution is to outsource the maintenance of Core Portion to external organization, which will be responsible to update on a regular basis; • RBDs should continuously maintain and further develop and populate the Local Portion of the Data Model; 3-22 JICA CTI Engineering International Co., Ltd.

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• RBDs should further populate the WFD portion of the data model based on the WFD time frame requirements; • MoEW should continue the meetings of the GIS workgroup on a regular basis in order to discuss the data maintenance; further data model development and all other GIS related issues (training, software, hardware, work procedures); • MoEW should use and implement the proposed TOR for Integrated Information System.

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CHAPTER 3

3.1

Main Report

Chapter 3

Figures

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Figure 3.1.1 General Structure of the Data Model

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3.2

3.3

Figure 3.3.1 General Structure of the GIS Data Model.

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CHAPTER 4 INTEGRATED RIVER BASIN ANALYSIS MODEL

4.1 Modeling Concept

4.1.1 General

Figure 4.1.1 shows the data treated in the study. There are several kinds of data to be handled as follows. • Level 1: Core Data • Level 2: Waterbodies Data • Level 3: Monitoring Data • Level 4: Basic Analysis Data • Level 5: Spatial Distribution Analysis Data • Level 6: Water Management Plan Data

The model developed in the study will be mainly used to produce the Level 5 and Level 6 data using the other level data. In other words, the model can be utilized for the following purposes. • Assessment for existing condition • Observed point data to spatially distributed presentation with some assumptions • Planning such as long term strategy for water management, program measures • Checking effectiveness of some of program measures • Reference for permission based on long term strategy for water management

The model developed in the study is not suitable for the following purposes due to insufficient data and information so far. • Operational decision such as daily reservoir operation and flood warning • It requires additional data, information and model development with additional modules and so on (or different types of model might be required).

There are general notes regarding a model as follows. • Model is not perfect. It is simplified representation of actual world. However, it can help thinking of what happens and what will happen. • If a model is used for decision support, it is not necessary for the model to be perfect. However, it should be transparent in its assumption and methodology. Conesus on the model is important.

The present study proposes the model that will be directly handled by Basin Directorates and will support their river basin management activity. Transparency of the model with clear explanation on assumptions for the model will be important for this purpose.

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4.1.2 Two Different Types of Model

(1) Simple Model and MIKE11 Model

In the present study, two different types of model are proposed. One is “Simple Model”, which is based on basically simple mass balance and can be working in general software such as MS-Excel. Another one is “MIKE11 Model” which is well known but requires specific software for implementing the simulation. Characteristics of the two models are summarized as below (see also Figure 4.1.2). • Simple Model • No specific modeling software • Spread sheet calculation only • Point representation at key points for management • Time scale: Monthly or Average in whole year and/or summer time • Reference for permission • Scenario setting for improvement plan • MIKE11 Model • Specific software (MIKE11& MIKE BASIN) • Physical process-based model • Spatio-temporal representation along river network • Time scale: Daily • Detailed simulation for confirming effects of improvement plan

As for MIKE11 model, the following modules are introduced in the present study. • Rainfall-Runoff Module (MIKE11-RR) • Conversion of Precipitation to Runoff in Catchment • NAM model has been selected. • Hydro Dynamic Module (MIKE11-HD) • Conversion of Inflow (Runoff in Catchment) to Flow Condition along River • Water Quality Module (MIKE11-AD & Eco-Lab) • Conversion of Flow Condition and pollution load in River to Water Quality Condition along River

It is noted that MIKE11 can run the above components simultaneously.

MIKE11 model is selected because of its integrated treatment on water quantity and quality. HEC model, which is public domain software and thus could be one of alternatives, does not have water quality module in the current version. The Pollution Load Calculator as a part of MIKE11 model in the present study, which is an extension of ArcGIS, can be also integrated in order to prepare some of input files on pollution load for MIKE11 model simulation in a transparent way on GIS platform. Furthermore, MIKE11 model was introduced in the previous JICA Study on the Maritsa River Basin. The concept and parameter setting developed in the previous JICA Study will be referred in

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(2) Structure of Modeling Environment

Figure 4.1.3 shows the proposed structure of modelling environment. The GIS-DB is a base of the modelling environment.

MIKE11 model development and simulation are implemented within MIKE ZERO platform, which is provided by DHI as a native platform for MIKE11 model. For development of a model, some layers in the GIS-DB such as river network and catchment can be imported to MIKE ZERO platform.

MIKE11 model requires a lot of time series data for input, although format of input file is special format for MIKE11 model. For smooth implementation of the simulation using the GIS-DB, MIKE BASIN Temporal Analyst and Pollution Load Calculator, which are extensions of ArcGIS, as well as Excel sheet, are utilized for preparing input files for MIKE11 simulation. Conversion of .xls file, .txt file and/or Geodatabase (.mdb) to .dfs0 (MIKE11 time series format) will be easily implemented by using the Temporal Analyst.

MIKE View on MIKE ZERO platform can be used for visualization of the simulation result of MIKE11 model. However, output files can also be imported to ArcGIS using MIKE BASIN Temporal Analyst, and then result presentation and analysis would be conducted in GIS environment. For example, linear reference system in ArcGIS may be utilized for the analysis and presentation on the result of the simulation in GIS environment.

As for Simple model, input data for the model are extracted from the GIS-DB. Some model parameters such as runoff volume are set using the result of MIKE11 model. Simple model is rather independent from GIS software so that user can use it without any knowledge of specific GIS software.

4.1.3 Modeling Cycle

There are three stages for the modeling, which consists of modeling cycle, as follows. • Model development stage • Model usage stage • Model revision and refinement stage

The present study covers model development stage and a part of model usage stage. It is expected that Basin Directorate will continue model usage after the study. Model revision and refinement is proposed to be conducted after sufficient data and information will be accumulated in future. The best timing for model revision and refinement seems to be just before the river basin management plan will be revised.

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Model Development Coverage by the Study

Model Usage

Accumulated (Good) monitoring data, permission data and so on

At least Every 6 years Model Revision & Refinement (proposal) By conducting re-calibration

Modeling Cycle The following table summarizes the activities which the present study has conducted in the model development and usage stages and which the Study expects for RBDs to conduct in model revision and refinement stage after the study.

Activities in Each Modeling Stage Stage MIKE11 Model Simple Model

Model development -Calibration of parameters for -Preparation of Excel sheets stage rainfall-runoff module for MIKE11 model (incl. Macros) as templates (2001 – 2005: 5 years)

-Setting river-network for hydro dynamic module for MIKE11 model

-Calibration of parameters for water quality module for MIKE11 model (2004: a representative year)

Model usage stage -To run the developed model by changing -Checking of water balance for water use, pollution load based on different water use conditions scenarios -Examination on effect of pollution load reduction on water quality

Model revision and -Re-calibration of model parameters -Re-calibration of model refinement stage using accumulated data and information. parameters using accumulated data and (After the study) information.

4.1.4 Target Users

Target users for Simple model and MIKE11 model are proposed as shown in the following table. There will be two kinds of users. One is the user who will run the model for different scenarios only. Another is the user who will maintain the model. Model run for MIKE11 model and model maintenance for both models require detailed knowledge on the model. It is thus recommended that Basin Directorate keep a few responsible persons for model maintenance, who will conduct model maintenance and model run for MIKE11 model, and model maintenance for Simple model.

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Target Users

User Simple Model MIKE 11 Model

Responsible person for model maintenance in RBD Planning & Monitoring & Model Run with discussion among Permission Dept. Planning & Monitoring & Permission Dept.

Responsible person for model Responsible person for model maintenance in RBD maintenance in RBD Model Maintenance with discussion among with discussion among Planning & Monitoring & Planning & Monitoring & Permission Dept. Permission Dept.

4.1.5 Modeling Layer

Modeling layer has been prepared as one of supporting layers beside core data model and WFD layer discussed in GIS-DB as shown in the following figure and Table. The modeling layer will be utilized for: • Reference for preparing WFD layer, and • Base for preparing basin management plan. Each object in the modeling layer has its ID for modeling purpose. To avoid confusion with WFD code for water bodies, it is totally different from the WFD code.

WFD Layer

Modeling Layer

Core Data Model

Modeling Layer

Prepared Modeling Layer Layer Explanation Base unit for modeling, same as Core data, but has unique ID for Catchment modeling Base unit for Rainfall-Runoff modeling, which is prepared by NAM Catchment aggregation of Catchment Selected river segment corresponding to Catchment MainRiverSegment One Catchment has one MainRiverSegment basically. Selected reservoir and lake for modeling purpose SignificantLake Significant reservoirs specified by Water Act and lakes whose surface area is more than 5km2 are selected.

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4.2 Modeling Activities during the Study

Outline of modeling activities during the study is shown below.

Data Collection

Preliminary Analysis Model Development for Water Quantity Model Usage Model Concept Model Development for Water Quality

Technical Seminar Technical (Jun 2007) Meeting Training for Water Training for Water (Oct 2006) Quantity Modeling Quality Modeling (Jun - Jul 2007) (Nov 2007)

Phase I Phase II

Inception Report Interim Report Draft Final Report (June 2006) (Jan 2007) (Jan 2008) In Phase I of the study, data collection and preliminary analysis on the data were done. Based on the preliminary analysis, modeling concept was developed and presented at technical meeting on October 2006.

After the seminar, selection of MIKE11 river network and setting of NAM catchment for each river basin was conducted. Firstly, the Study Team proposed the initial idea. The initial idea was modified by the discussion with C/P in EABD and WABD. Some rivers are added and some are excluded. Finally, the draft version of MIKE11 river network and NAM catchment was agreed between C/P in EABD, WABD and the Study Team.

In Phase II of the Study, data collection was continued because of delay of data collection in Phase I. Actual model development was also conducted. The developed model was used for scenario simulations for formulation of river basin management plan (draft).

Technical seminar was held on June 2007 to present progress of model development. Consequently, training for water quantity model, which is total 6 days with once a week, was conducted in June to July 2007. Training for water quality model, which is total 3 days with once a week, was also conducted in November 2007. There were totally about 10 participants from EABD and WABD but also MoEW, ExEA, DRBD and BSBD for trainings for both water quantity and quality modeling.

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4.3 MIKE11 Model for Water Quantity

4.3.1 Outline of Model

MIKE11 model for water quantity consists of MIKE11-RR (Rainfall-Runoff module) and MIKE11-HD (Hydrodynamic module).

Several different rainfall-runoff models are prepared for MIKE11-RR. Among those, NAM model is selected in the present study. In the present study, snow routine for MIKE11-RR is considered, because snow-melting process in mountain region is one of key hydrological processes.

MIKE11-HD module is to simulate river flow process. One-dimensional version of governing equations for momentum transfer and continuity of fluid flow is basic equations for MIKE11-HD. In the present study, dynamic wave model is selected for solver option.

The outline of the model set-up is shown in the following table. Figures 4.3.1 – 4.3.5 show MIKE11 river network and rainfall-runoff (NAM) catchment for each river basin. Outline of MIKE11 River Network and Rainfall-Runoff (NAM) Catchment Total Modeling Number of Total Length of Number of River Basin Catchment Area Rainfall-Runoff Modeling River Branch (km2) (NAM) Catchment Network (km) Struma 8667.18 25 343.14 6 Mesta & 3397.71 14 141.80 3 Dospat Arda & Biala 5811.84 12 332.10 5 Tundzha 7890.93 20 409.46 5 Maritsa 21272.27 34 954.98 20

4.3.2 Input Data for Water Quantity Model

The following data were collected for modeling in the present study. • Meteo-Hydrological Data • Precipitation • Potential evapo-transpiration (PET) • Air Temperature • Water quantity at key HMSs • Water Transfer, Abstraction, Discharge Data • Reservoir operation (for significant reservoir) • Water abstraction • Irrigation water use • Domestic & Industrial water use • Water discharge (waste water) • River Condition Data • Cross-section data JICA CTI Engineering International Co., Ltd. 4-7

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4.3.3 Calibration

The rainfall-runoff (NAM) model has many model parameters to be calibrated. In the present study, the model parameters were calibrated using the water quantity during 2001-2005. During this period, there were both extremely dry and wet years. The calibration was conducted to reproduce reasonable hydrograph with such wide range of precipitation conditions. Therefore, it is expected that the calibrated model parameters can be valid against relatively wide range of precipitation condition.

When the calibration was conducted, it was set for duration of simulation to be from the beginning of August 2000 to the end of 2005 so as to avoid including significant influence of initial condition for the model parameters on the simulated results. Duration from the beginning of August 2000 to the end of 2000 was regarded as initial running period, which should not be used for further analysis.

The model parameters were basically calibrated against estimated quasi-natural runoff from the watershed that was determined by calibrated points and/or rainfall-runoff catchment. The quasi-natural runoff was estimated by using observed flow and estimated transferred water, abstracted water and discharged water within the watershed.

It should be noted that the effect of regime change by local reservoirs was not taken into account for estimating quasi-natural runoff in the present study, because of lack of the information.

The data used for the estimation of quasi-natural flow were sometimes monthly data. The monthly data were converted to daily data, assuming same fluctuation pattern as the reference daily data with keeping mass balance for monthly basis. The reference daily data were selected from the observed data, which were recorded at the HMS nearby same river.

During the calibration, the following priority was considered. • 1st Priority: Total mass balance during 2001-2005 • 2nd Priority: Overall fitness during 2001- 2005 • 3rd Priority: Low flow condition

Water balance for quasi-natural condition by calibrated NAM model is shown in Table 4.3.1. It can be seen that runoff rate (RO/P) ranges 20 to 45%. The storage shown in the table is mainly because of large time scale of retention in lower ground water storage.

Hydrodynamic simulation, in which water transfer, abstraction and discharge are taken into account, was tested using the calibrated parameters for Rainfall-runoff (NAM) model. Figures 4.3.6 – 4.3.10 show comparison between observed (disturbed flow) and simulated hydrograph at a representative HMS for each river basin. It can be seen that the simulated results agree fairly with the observed ones.

4.3.4 Presentation and Analysis of Simulated Results

As an output of the study, an environment that users in river basin directorates can easily see and analyze the results of MIKE11 have been prepared. Simulated results by 4-8 JICA CTI Engineering International Co., Ltd.

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MIKE11 water quantity model have been linked to ArcGIS platform using Temporal Analyst for ArcGIS. Figure 4.3.11 shows an example of presentation of results of MIKE11 model using Temporal Analyst. Many kinds of statistical analysis such as calculation of average, maximum and minimum value for the output of MIKE11 can be conducted and those results can be presented in ArcGIS platform.

The simulated results by MIKE11 water quantity model are utilized further for MIKE11 water quality analysis directly. Furthermore, the outputs of Rainfall-runoff model are utilized for Simple Model for water quantity.

4.4 MIKE11 Model for Water Quality

4.4.1 Introduction

A MIKE 11 Water Quality Model (MIKE 11 EcoLab) is set up for all the water bodies described by the MIKE 11HD Hydraulic Model for water quantity. The selected water quality module focuses on degradation of organic matter, transformation of N-components and the consequences for the oxygen concentrations. The selected model includes in addition phosphorus compounds.

The BOD, oxygen and N-transformation processes are outlined in Figure 4.4.1. The model includes both the transformation processes for the substances flowing in to the rivers as well as processes as photosynthesis and respiration of plants animals and sediment.

The Phosphorus Model used describes absorption-desorption sorption processes expanded with relevant processes related to plant, animal and sediment.

The WQ-module describes the following concentration (State Variables): • BOD (Biological Oxygen Demand) • Diluted Oxygen (DO)

• Total Ammonium (NH4-N) • Nitrate (NO3-N) • Phosphate (PO4-P) • Phosphor bound to particulate material (Particulate –P) • Temperature

4.4.2 Input Data for Water Quality Model

Data concerning the pollution load to the rivers in EABD and WABD has been collected with focus on quantification of the following groups of sources: • Agricultural sources • From domestic live stock • From use of fertiliser • Urban point sources • Out flow from WWTP (may include industrial wastewater) • Sewered but not treated sewage (may include industrial wastewater)

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• Urban non-point sources • Sewered small settlements • Non severed settlements and individual houses/farms • Industries, point sources: • Direct discharge (including big animal breeding farms)

4.4.3 Calibration of Water Quality Models

The pollution load has been relative roughly quantified and there exist significant uncertainties on domestic, industrial, as well as agricultural load. Therefore the pollution is to be regarded as estimations of the levels. The year 2004 has been chosen as the hydraulic basis for the calibration. These in spite that the pollution loads to a higher extent represent the level in the period 2005-2007. The year 2004 has been selected as hydraulic basis, because this year has been characterized closed to an average year between those for which hydrological data was available. All together this mean that it can’t be expected to achieve very precise simulation of the monitored concentration and especially not the suddenly peaks and variation through the year. For these reason it has during the calibration process been aimed to achieve a representation of the measured level not only in 2004 but also that measured other resent years.

Examples of the calibration result for the variables BOD, Oxygen (DO), Ammonium (NH4-N) and Phosphate-P (PO4-P) at a representative station in each river basin are shown in Figures 4.4.2 – 4.4.6.

Generally the simulated concentration levels correspond to the measured ones except the most upstream reach of some rivers although some of the dynamic variation is not described too well. To achieve an improved simulation of the dynamic in the river system requires at least better estimations of the variation in pollution load. No such data have been available.

The results of the simulation for several different scenarios are shown in Chapter 6.

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4.5 Simple Model

4.5.1 Water Quantity

(1) Basic Ideas of Model

The Simple model for water quantity is basically based on monthly mass balance calculation. The calculation is implemented on spread sheet such as Ms-Excel.

Unit of analysis in space for the simple model for water quantity is a catchment. The simple model analyzes water movement and balance among the catchments. To develop the simple model for water quantity, connectivity of the catchments is examined and an additional attribute for modelling catchment layer is recorded using GIS environment. The additional attribute for the catchment connectivity allows analyzing easily affected catchments by a source catchment.

“Matrix for contribution” can also be prepared based on the additional attribute table. Using this matrix, one can easily calculate the total accumulated value at an observation point from all of upstream catchments. In the present study, the matrix of contribution for each river basin has been prepared and stored in the Excel sheet as a part of the Simple Model.

In a catchment, the following sources are estimated. • Catchment Area • Run-off from Catchment • Abstraction from Catchment • Discharge from Catchment • Transfer from Catchment

For example, the simple model of water quantity utilizes the results of calibrated rainfall-runoff (NAM) model. To estimate quasi-natural runoff from each catchment, the following is assumed. • Runoff from each catchment inside a rainfall-runoff (NAM) catchment is proportional to: (Cacthment Area) x (Precipitation – Evapo-transpiration)

The other sources such as abstraction, discharge and transfer from a catchment are estimated by using same methodology for MIKE11 water quantity model.

When the sources from catchments are given, accumulated values without influence of significant reservoir such as quasi-natural flow and total abstracted water at an observation point are calculated using the matrix of contribution.

Influence of operation of significant reservoir is taken into account by introducing “matrix for reservoir influence”. At the catchments, which are affected by specific reservoir, modified water quantity by the operation of the reservoir is substituted by quasi-natural water quantity to get disturbed water quantity. All of the calculation is implemented in Excel sheet with Macros, which have been prepared in the present study.

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(2) Versions of Simple Model for Water Quantity

The simple model for water quantity has the following four versions.

Versions for Simple Model for Water Quantity

Version Purpose -To estimate existing condition SimpleModel_ver_Existing -Developed in the study (No need to change until RR model will be revised.) -To estimate probable water quantity for quasi-natural and potential flows SimpleModel_ver_Potential -Developed in the study (No need to change until RR model will be revised.) -To examine the effect of permitted water amount SimpleModel_ver_Permit -Local + Existing water abstraction by Significant Reservoir -Local + Permitted water abstraction for Significant Reservoir SimpleModel_ver_Demand -To estimate water demand with several scenarios

An example of the presentation of simple model_ver_Existing is shown in Figure 4.5.1. The user can specify any observation points to see the time series of water balance.

The results of ver_Exitsing and ver_Potential are basis for the draft basin management plan prepared by the present study. On the other hand, Basin Directorate itself has prepared Simple Model_ver_Permit and ver_Demand rather for Decision Support Tools for proper water management. Main features for each version are as follows: • Ver_Permit • Entering permission data for hydropower, irrigation, drinking water supply and industrial water supply. • Selection of reference points for management • Summary table for annual average and average during summer time (Jul. to Sep.) for year 2001 -2005 for each catchment/segment and reference point • Longitudinal plot of the summarized results along main channel • Time series plot for each reference point and/or catchment/segment • Globally and locally changeable coefficient for permitted water amount • Preparation of an input file related to local water abstraction for each NAM catchment for MIKE11 water quantity model • Ver_Demand • Entering parameters for estimation of water demand for irrigation, drinking water supply and industrial water supply • Selection of reference points for management

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• Summary table for annual average and average during summer time (Jul. to Sep.) for each catchment/segment and reference point • Longitudinal plot of the summarized results along main channel • Time series plot for each reference point and/or catchment/segment • Preparation of an input file related to local water abstraction for each NAM catchment for MIKE11 water quantity model

4.5.2 Water Quality

In order to facilitate the formulation of water quality management plan and for future use for water quality management, simple model for water quality was developed in the Study.

(1) Basic Concept of the Simple Model for Water Quality (WQL Simple Model) • The WQL Simple Model will simulate the effect of reducing pollution loads to the river water quality in terms of BOD5. • The simulation will be done at key calculation points along the rivers. • The calculation will be done by MS-Excel. • The model can be utilized for quick review of the conditions of BOD loads in the river basins comparing the future required BOD loads to attain good status of water (such as Class II with BOD5 3.0 mg/l).

(2) Procedure of Developing the WQL Simple Model

Figure 4.5.2 shows the procedure for developing the WQL Simple Model. • First to check the general co-relation between the present accumulated catchment BOD loads from the upstream of the calculation points and the river BOD loads at the calculation points. If there is junction of tributary, the calculation points are set at the upstream side of the main stream. If there is no tributary, the calculation point is just on the main stream at that point. Figure 4.5.3 shows the calculation points for EABD and WABD with NAM catchments. There is clear co-relation between the accumulated catchment BOD loads and the river BOD loads as shown in the “Main Report 6.2 Water Quality Management Plan”. • The existing sewer networks in EABD and WABD have significant loss of pollutants such as at least 50% loss for the Maritsa and Tundzha River Basin, 40% in the Arda River Basin, and 60% in the Struma and Mesta River Basin. The current loss percentage to the domestic BOD load and industrial BOD load discharged into the sewerage system is applied for calculating their inflow BOD loads to the river. This assumption is more or less acceptable because the domestic loads without sewerage system are calculated with smaller unit loads (15 g/day/PE) compared to the generated unit load of 60 g/day/PE, and it may reach to the river through ditch or gulley. • Ratios between the inflows BOD loads and river BOD loads are calculated at every calculation point. JICA CTI Engineering International Co., Ltd. 4-13

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• Under the assumed condition of reducing the loss from the sewer networks up to 10% in the long time future, inflow BOD loads based on the Near Future BOD load including under constructed WWTPs or committed for constructing WWTPs in EABD and WABD are calculated. Corresponding to this, River BOD load and the BOD concentration in the near future condition with loss of sewerage with 10% are calculated.

• In order to attain the good status of water, which is better than Class II with BOD5 of 3.0 mg/l, required inflow BOD load and corresponding accumulated catchment BOD load is calculated. • Setting the pollution reduction plan such as construction of WWTPs in the future, future accumulated catchment BOD load is calculated, and compared with the required accumulated catchment BOD load.

(3) Results of the Calculation

Based on the procedure described above, the following figures show the results of the calculations by the WQL Simple Model. Figure Contents Present Accumulated Catchment BOD Loads and River BOD Loads in Figure 4.5.4 EABD Required Accumulated Catchment BOD Loads and River BOD Loads in Figure 4.5.5 EABD with High Priority Towns for WWTPs Required Accumulated Catchment BOD Loads and River BOD Loads in Figure 4.5.6 EABD with High and Medium Priority Towns for WWTPs Present Accumulated Catchment BOD Loads and River BOD Loads in Figure 4.5.7 WABD Required Accumulated Catchment BOD Loads and River BOD Loads in Figure 4.5.8 WABD with High Priority Towns for WWTPs Required Accumulated Catchment BOD Loads and River BOD Loads in Figure 4.5.9 WABD with High and Medium Priority Towns for WWTPs

Effects of reduction of BOD loads in EABD by the high priority towns for WWTPs as well as the high and medium priority towns for WWTPs are rather good along the Maritsa and Tundzha Main Rivers in general. However, for the upstream to mid-stream part of the Tundzha River, reduction rate is slightly lower than the downstream. This reaches of the Tundzha River might have more influence from the medium and smaller settlements. Therefore, in the future, it will be necessary for reduction of pollution loads in this part from medium to smaller settlements as well.

Overall effects for reducing BOD Loads by the high priority towns for WWTPs as well as the high and medium priority towns for the Struma and Mesta Rivers are generally good. However, for the Struma River, reduction rate of the pollution loads is insufficient especially from upstream to mid-stream part. Therefore in the future, it may be necessary to treat medium and smaller settlements in the upstream to the mid-stream parts as well.

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CHAPTER 4

4.1

Main Report

Chapter 4

Tables

4.2

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Table 4.2.1 Water Balance for Quasi-Natural Condition during 2001-2005 by Calibrated NAM Model Source: JICA Study Team

Struma Mesta Dospat Arda Biala Tundzha Maritsa

Catchment Area (km2) 8541 2785 613 5213 599 7891 21272

Average Elevation (m) 919 1225 1330 639 418 386 569

Precipitation (P) (mm/y) 761 844 875 902 833 710 723 PET (mm/y) 629 577 552 671 717 689 669

ET (mm/y) 483 442 490 511 567 513 488

Total Runoff (RO) (mm/y) 231 349 321 371 232 158 173

Lower Base Flow (LBF)28568114122741

OverlandFlow (OF) (mm/y) 25 26 30 165 99 26 31 Storage (ST) (mm/y) 48 53 64 20 35 39 62

ET/P (%) 63.5 52.4 56.0 56.7 68.1 72.3 67.5

RO/P (%) 30.4 41.4 36.7 41.1 27.9 22.3 23.9

LBF/P (%) 3.7 6.6 9.3 1.6 1.4 3.8 5.7

OF/P (%) 3.3 3.1 3.4 18.3 11.9 3.7 4.3 ST/P (%) 6.3 6.3 7.3 2.2 4.2 5.5 8.6

ET/PET (%) 76.8 76.6 88.8 76.2 79.1 74.5 72.9 Total Runoff (m3/s) 62.6 30.8 6.2 61.3 4.4 39.5 116.7

2 Specific Total Runoff (l/s/km ) 7.325 11.067 10.179 11.764 7.357 5.010 5.486

1) Catchment area is only for modelled area in Bulgarian 1) Catchment 1) Catchment 1) Catchment 1) Catchment 1) Catchment 1) Catchment teritory. area is only for area is only for area is only for area is only for area is only for area is only for 2) Two modelled area. modelled area. modelled area. modelled area. modelled area. modelled area. catchments are 2) Precipitation 2) Precipitation 2) Precipitation 2) Precipitation 2) Precipitation 2) Precipitation Remarks disturbed is modified is modified is modified is modified is modified is modified condtion. considering considering considering considering considering considering 3) Precipitation elevation in the elevation in the elevation in the elevation in the elevation in the elevation in the is modified model. model. model. model. model. model. considering elevation in the model.

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CHAPTER 4

4.1

Main Report

Chapter 4

Figures

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1. Surface Water Quantity Management and Improvement Plan 2. Surface Water Quality Management and Improvement Plan 3. Groundwater Quantity and Quality Management and Improvement Plan Level 6 4. Monitoring Plan for Surface Water, Groundwater, Water Use and Wastewater Discharge Water Management Plan Data 1. Water Balance Distribution by Sub-Basin and in the River Networks 2. Pollution Load Distribution by Sub-Basin 3. Water Quality Distribution in the River Networks 4. Hydro-biological Index Distribution in the River Networks Level 5 5. Groundwater Quantity and Quality Distribution by Sub-Basin Spatial Distribution 6. Distribution of Risk (Surface Water and Groundwater) Analysis Data

Water Quantity and Quality Model 1. Time Series Data at Points: ) Model MIKE11 and Model (Simple Meteo-hydrology, Surface Water Quantity and Quality, Groundwater Quantity and Quality, Level 4 Intake Water Volume, and Reservoir Operation. Basic Analysis Data 2. Annual Condition at Points at Points Hydro-biology Wastewater Discharge and Pollution Load

1. Meteorology (Temperature, Relative Humidity and Precipitation) Level 3 2. Hydrology (Surface Water Level and Discharge) Monitoring Data 3. Surface Water Quality and Hydro-biology 4. Groundwater (Level and Quality) 5. Water Abstraction and Control (Intake and Reservoir) including Permission 6. Pollution Source and Wastewater Discharge (Quantity and Quality) including Permission Level 2 Water Bodies Data 1. Surface Water Bodies 2. Groundwater Bodies Level 1 Core Data 1. Topography, Geology, River & River Basin Boundary, Hydro-geology, 2. Administration Boundary/Towns/Villages, Population, Landuse, Economy, and 3. Natural and Social Environment including Protected Areas

Figure 4.1.1 Work Contents and Data in the Study

Input Sophisticated Model ( MIKE11) - Simulation of longitudinal variation of discharge, Precipitation -water level and water quality along rivers - Continuous simulation for time series Rainfall Runoff Simulation Discharge Q(m3/s) BOD, COD etc.(mg/l) (MIKE11-RR） Runoff Output q(m3/s/km2) Input Outflow from Dam Month 1 2 11 12Month 1 2 11 12Month Input Pollution Load from Town I rrig atio n A rea Intake Input Pollution Load from Livestock farm Input Simple Model I rrig atio n A - Simulation at key stations only rea - Simulation for monthly averaged values

Monthly. Ave. (m3/s) Monthly. Ave. Input Pollution Load BOD, COD etc.(mg/l) from Industry Output

1 2 11 12Month 1 2 11 12Month

Source: JICA Study Team Figure 4.1.2 Relationship between Simple Model and MIKE11 Model

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MIKE11 & MIKE BASIN

Boundary Ms-Excel Condition MIKE11 (MIKE Zero platform)

- Preparation of input Connection of Simple Model file for simulation (Spread sheet) output file to GIS environment MIKE BASIN Temporal Analyst & Parameters (Quasi-Natural Pollution load calculator (ArcGIS extension: Run-off etc.) part of MIKE11 GIS after ver2007) Extract from DB

Final -Extract base layer Assembling - Connection to DB

GIS-DB - Water Body - Natural & Socio-economical information - Monitoring Data for Water Quantity and Quality -Permission Data - Operation record for reservoir and irrigation Source: JICA Study Team Figure 4.1.3 Structure of Modeling Environment

4.2

4.3 ST_KON ST_M8 ST_TRE ST_M9 ST_M10 ST_DRA ST_ARK ST_M7

ST_SOV ST_M6 ST_DZH2

ST_DZH1

ST_ELE ST_RIL

ST_M5 ST_BRA

ST_GRA

ST_M4

ST_M3 ST_SAN ST_M2

ST_PIR RiverNetWorkMIKE11 ST_M1 MainRiverSegment ST_STR1 SignificantLake ST_STR2 Catchment NA M Cat chment Source: JICA Study Team Figure 4.3.1 MIKE11 River Network and Rainfall-Runoff (NAM) Catchment in the Struma River Basin

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ME_M6

ME_M5 ME_IST1

ME_ZLA ME_IST2

ME_M4 ME_GLA DO_M2 ME_KAN

ME_M3 DO_M1 ME_NEV ME_M2

ME_M1 RiverNetWorkMIKE11 MainRiverSegment SignificantLake Catchment NA M Cat chment

Source: JICA Study Team Figure 4.3.2 MIKE11 River Network and Rainfall-Runoff (NAM) Catchment in the Mesta and Dospat River Basins

AR_M3

AR_M2

AR_M4 AR_M1 AR_CHE

AR_M0 A R_KRU1 AR_VAR1 AR_M5

BI_M

AR_VAR2 AR_KRU2

RiverNetWorkMIKE11 MainRiverSegment SignificantLake Catchment NA M Cat chment Source: JICA Study Team Figure 4.3.3 MIKE11 River Network and Rainfall-Runoff (NAM) Catchment in the Arda and Biala River Basins

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TU_ASE2 TU_MOC2 TU_BEL TU_M8 TU_ASE1 TU_M5 TU_M7 TU_M6 TU_M4 TU_M9 TU_M3

TU_MOC1

TU_KAL TU_M2

TU_POP1 TU_SIN

TU_ARA TU_POP2 TU_M1

RiverNetWorkMIKE11 MainRiverSegment SignificantLake Catchment NA M Cat chment Source: JICA Study Team Figure 4.3.4 MIKE11 River Network and Rainfall-Runoff (NAM) Catchment in the Tundzha River Basin

MA_TOP4 MA_STR2 MA_TOP3

MA_RDO MA_LUD2 MA_PYA2 MA_TOP2 MA_BLA MA_STR1 MA_TOP1 MA_SAZ2 MA_LUD1 MA_PYA1 MA_M7 MA_ROV MA_M6 MA_M3 MA_SAZ1 MA_M5 MA_M2 MA_M4 MA_CPI1 MA_STA1 MA_VAC1

MA_STA2 MA_RBA MA_CPL1 MA_CPI2

MA_M1 MA_HAR2 MA_HAR1 MA_CPL2 MA_YUG MA_VAC2

RiverNetWorkMIKE11 MainRiverSegment SignificantLake Catchment NA M Cat chment Source: JICA Study Team Figure 4.3.5 MIKE11 River Network and Rainfall-Runoff (NAM) Catchment in the Maritsa River Basin

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51880 Discharge, ST_M 0.000-12713.450 4 600

500

400

300 200

(m3/s) Quantity Water 100 0 2000 2001 2002 2003 2004 2005 Time

Source: JICA Study Team Figure 4.3.6 Comparison between Observed and Simulated Hydrograph (The Struma River: HMS51880)

61550 Discharge, AR_KRU 21091.111328125 300

250 200

150

100

Water Quantity(m3/s) 50

0 2000 2001 2002 2003 2004 2005

Time Source: JICA Study Team Figure 4.3.7 Comparison between Observed and Simulated Hydrograph (The Mesta River: HMS52850)

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61550 Discharge, AR_KRU 21091.111328125 300

250 200

150 100

Water Quantity(m3/s) 50

0 2000 2001 2002 2003 2004 2005

Time

Source: JICA Study Team Figure 4.3.8 Comparison between Observed and Simulated Hydrograph (The Arda River: HMS61550)

74850 Discharge, TU_M 53379.5703125 150

100

50

Water Quantity(m3/s)

0 2000 2001 2002 2003 2004 2005

Time Source: JICA Study Team Figure 4.3.9 Comparison between Observed and Simulated Hydrograph (The Tundzha River: HMS74850)

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73750 Discharge, MA_M 50444.6015625 1200

1000

800

600 400

Water (m3/s) Quantity 200 0 2000 2001 2002 2003 2004 2005 Time

Source: JICA Study Team Figure 4.3.10 Comparison between Observed and Simulated Hydrograph (The Maritsa River: HMS73750)

Source: JICA Study Team Figure 4.3.11 Example of Presentation of Results of MIKE11 Model Using Temporal Analyst

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Sun 4.4 Pollution sources light (N ) Reaeration BOD NHN (NO) 2 4 3 -DO

(NO3) +DO nitrification NH4 -DO BOD BOD -DO degradation Org. Matter

+DO Photosynthesis

Sediment respiration -DO Respiration nitrification

Figure 4.4.1 Basic processes with respect to BOD, N-component and oxygen (DO) included in the MIKE 11 WQ Model used under this study

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ST_M 8406.41 AMMONIA ST_M 464_NH4 ST_M 8406.41 ORTHOPHOSPHATE 8406.41 ST_M 464_PO4

Concentration 1 TS External Concentration 1 TS External

23-8-2005 23-8-2005

4-2-2005 4-2-2005

at -P) Concentration 4

19-7-2004 19-7-2004

1-1-2004 -P) -N) 1-1-2004 4

4

15-6-2003 15-6-2003

27-11-2002 27-11-2002 Time Series Concentration Series Time -N) , Phosphate (PO -N) Time Series Concentration Series Time 11-5-2002

4 11-5-2002 Phosphate (PO Ammonia (NH 23-10-2001

23-10-2001

6-4-2001 6-4-2001

18-9-2000 18-9-2000

2-3-2000 2-3-2000 The Struma River The Struma 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 [mg/l] , 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 [mg/l]

OXYGEN DISSOLVED 8406.41 ST_M 464_DO ST_M 8406.41 BOD ST_M 464_BOD Concentration 1 TS External Concentration 1 TS External

23-8-2005 23-8-2005

464 Station 4-2-2005 4-2-2005

d BOD, Oxygen (DO) , Ammonia (NH d BOD, Oxygen (DO) , 19-7-2004 19-7-2004

1-1-2004 1-1-2004

15-6-2003 15-6-2003

BOD 27-11-2002 27-11-2002 Time Series Concentration Series Time

Concentration Series Time 11-5-2002 11-5-2002 Oxygen (DO)

23-10-2001 23-10-2001

6-4-2001 6-4-2001

18-9-2000 18-9-2000

4.4.2 Simulated and Monitore Figure 3-2000 2-3-2000 2- g/l] .0 .0 .0 .0 9.0 8.0 7.0 [m 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 0.0 [mg/l] Figure 4.4.2 Simulated and Monitored BOD,13 12 Oxygen11 10 (DO) , Ammonia (NH4-N) Concentration at Station 464, Struma River

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ME_M 21250.00 AMMONIA ME_M 432_NH4 ME_M 21250.00 ORTHOPHOSPHATE 21250.00 ME_M 432_PO4 Concentration 1 TS External Concentration 1 TS External

23-8-2005 23-8-2005

4-2-2005 4-2-2005

19-7-2004 19-7-2004

at -P) Concentration 4 1-1-2004 1-1-2004

-P) -N) 4 4 15-6-2003

15-6-2003

27-11-2002 27-11-2002

Time Series Concentration Series Time Time Series Concentration Series Time 11-5-2002 11-5-2002 -N) , Phosphate (PO -N)

4 23-10-2001 23-10-2001 Ammonia (NH Phosphate (PO

6-4-2001 6-4-2001

18-9-2000 18-9-2000

2-3-2000 2-3-2000 1.1 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 [mg/l] 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 [mg/l]

The Mesta River , ME_M 21250.00 DISSOLVED OXYGEN 21250.00 DISSOLVED ME_M 432_DO ME_M 21250.00 BOD ME_M 432_BOD

Concentration 1 TS External Concentration 1 TS External

23-8-2005 23-8-2005 Station 432 Station 4-2-2005

4-2-2005

19-7-2004 19-7-2004 d BOD, Oxygen (DO) , Ammonia (NH d BOD, Oxygen (DO) ,

1-1-2004 1-1-2004

15-6-2003

15-6-2003 27-11-2002 BOD 27-11-2002

Time Series Concentration Series Time Time Series Concentration Series Time 11-5-2002 11-5-2002 Oxygen (DO) 23-10-2001 23-10-2001

6-4-2001 6-4-2001 18-9-2000

18-9-2000

3-2000 ] 2- -3-2000 ] . 2 8.0 6.0 4.0 2.0 0.0 [mg/l Figure 4.4.3 Simulated and Monitore Figure 0 0 0 0 14.0 12 0 10.0 9. 8.0 7. 6. 5. [mg/l

Figure 4.4.3 Simulated and Monitored BOD,13.0 12.0 Oxygen11.0 10.0 (DO) , Ammonia (NH4-N) , Phosphate (PO4-P) Concentration at Station 432, Mesta River

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AR_M 13198.56 ORTHOPHOSPHATE AR_M 412_PO4 AR_M 13198.56AR_M AMMONIA 412_NH4 Concentration 1 TS External Concentration Ex ter nal TS 1

5-6-2005 5-6-2005 -P) Concentration at -P) Concentration 17-11-2004 17-11-2004

4

1-5-2004 1-5-2004 -P) -N) 4 4 14-10-2003 14-10-2003

28-3-2003 28-3-2003 9-9-2002 9-9-2002 Time Series Concentration Series Time Concentration Series Time -N) , Phosphate (PO -N) 21-2-2002 21-2-2002 4 Ammonia (NH Phosphate (PO 5-8-2001

5-8-2001

17-1-2001 17-1-2001

1-7-2000 1-7-2000

2.4 2.2 2.0 1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 [mg/l] 2.0 1.9 1.8 1.7 1.6 1.5 1.4 1.3 1.2 1.1 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 [mg/l] The Arda River The

,

AR_M 13198.56 DISSOLVED OXYGEN 13198.56 DISSOLVED AR_M 412_DO AR_M 13198.56 AR_M 412_BOD TOTA L BOD 1 TS External Concentration 1 TS External

Station 412 Station 5-6-2005 5-6-2005

17-11-2004 17-11-2004

Ammonia (NH d BOD, Oxygen (DO) , 1-5-2004 1-5-2004

14-10-2003

14-10-2003

28-3-2003

28-3-2003

BOD 9-9-2002 9-9-2002 BOD TOTAL Series Time Time Series Concentration Series Time 21-2-2002

21-2-2002 Oxygen (DO)

5-8-2001 5-8-2001

17-1-2001 17-1-2001

1-7-2000 1-7-2000 9.0 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 0.0 18.0 17.0 16.0 15.0 14.0 13.0 12.0 11.0 10.0 [MG/L] 9.0 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 [mg/l] 13.0 12.0 11.0 10.0 Figure 4.4.4 Simulated and Monitore Figure Figure 4.4.4 Simulated and Monitored BOD, Oxygen (DO) , Ammonia (NH4-N) , Phosphate (PO4-P) Concentration at Station 412, Arda River

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TU_M 31004.34 ORTHOPHOSPHATE TU_M 309_PO4 TU_M 31004.34AMMONIA TU_M 309_NH4 Concentration Ex ter nal TS 1 Concentration 1 External TS

23-8-2005 23-8-2005

4-2-2005 4-2-2005 -P) Concentration at -P) Concentration

4 19-7-2004 19-7-2004

1-1-2004 1-1-2004 -P) -N) 4 4 15-6-2003 15-6-2003

27-11-2002 27-11-2002

Time Series Concentration Series Time Time Series Concentration Series Time 11-5-2002 11-5-2002 -N) , Phosphate (PO -N) 4

Phosphate (PO Ammonia (NH 23-10-2001 23-10-2001 6-4-2001 6-4-2001

18-9-2000 18-9-2000

2-3-2000 2-3-2000 2.4 2.2 2.0 1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 [mg/l] 2.4 2.2 2.0 1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 [mg/l]

The Tundzha River The Tundzha , TU_M 31004.34 DISSOLVED OXYGEN DISSOLVED 31004.34 TU_M 309_DO TU_M 31004.34 TU_M 309_BOD

Concentration 1 TS External TOTAL BOD 1 TS External

23-8-2005 23-8-2005 Station 309 Station 4-2-2005 15-5-2005 19-7-2004 d BOD, Oxygen (DO) , Ammonia (NH d BOD, Oxygen (DO) , 4-2-2005

1-1-2004

27-10-2004

15-6-2003

19-7-2004 27-11-2002 BOD

10-4-2004 Time Series TOTAL BOD TOTAL Series Time Time Series Concentration Series Time 11-5-2002 1-1-2004 Oxygen (DO) 23-10-2001 23-9-2003

6-4-2001

15-6-2003 18-9-2000 7-3-2003

2-3-2000 9.0 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 0.0 18.0 17.0 16.0 15.0 14.0 13.0 12.0 11.0 10.0 [MG/L] 9.0 8.0 7.0 6.0 5.0 [mg/l] 12.0 11.0 10.0 Figure 4.4.5 Simulated and Monitore Figure Figure 4.4.5 Simulated and Monitored BOD, Oxygen (DO) , Ammonia (NH4-N) , Phosphate (PO4-P) Concentration at Station 309, Tundzha River

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MA_M 3640.44 AMMONIA MA_M 387_NH4 MA_M 49472.20 ORTHOPHOSPHATE MA_M 385_PO4

Concentration Ex t er nal TS 1 Concentration 1 External TS

23-8-2005 23-8-2005 -P) Concentration at -P) Concentration 4

4-2-2005 4-2-2005

19-7-2004

19-7-2004 -P) -N)

4 4 1-1-2004 1-1-2004

15-6-2003 15-6-2003 27-11-2002 -N) , Phosphate (PO -N) 27-11-2002 4

Concentration Series Time 11-5-2002 Time Series Concentration Series Time Phosphate (PO Ammonia (NH 11-5-2002

23-10-2001 23-10-2001 6-4-2001

6-4-2001

18-9-2000

18-9-2000 The Maritsa River The Maritsa 2-3-2000 , 3.0 2.5 2.0 1.5 1.0 0.5 0.0 2-3-2000 [mg/l] 2.2 2.0 1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 [mg/l]

BOD 3640.44 MA_M 387_BOD Concentration 1 TS External MA_M 3640.44 DISSOLVED OXYGEN 3640.44 DISSOLVED MA_M 387_DO Concentration 1 TS External

Station 387 Station 23-8-2005

23-8-2005

4-2-2005 d BOD, Oxygen (DO) , Ammonia (NH d BOD, Oxygen (DO) , 4-2-2005

19-7-2004 19-7-2004

1-1-2004

1-1-2004

15-6-2003 15-6-2003

BOD 27-11-2002

27-11-2002

Time Series Concentration Series Time Time Series Concentration Series Time Oxygen (DO) 11-5-2002 11-5-2002

23-10-2001 23-10-2001 6-4-2001 6-4-2001

18-9-2000 18-9-2000 Figure 4.4.6 Simulated and Monitore Figure 3-2000 3-2000 2- 2- g/l]

Figure 4.4.6 Simulated and Monitored BOD, Oxygen0 0 (DO)0 0 0 ,0 Ammonia (NH -N) ,

g/l] 4 0 0 .0 .0 .0 . .0 9. 8. 7. 6. 5. 4. [m 8.0 6. 4.0 2. [m 12 11 10 18 0 16.0 14.0 12.0 10 Phosphate (PO4-P) Concentration at Station 387, Maritsa River

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Point No. of Catchment 1: Re4.5fP oint RefPoint JICA_ID 2: Segment (for 1) (For 2) Re-plot TimeSeries 2ST4538

250.00 Quasi-Natural Flow Potential Flow with Significant Reservoir 200.00 Total Abstracted Water Disturbed Flow 150.00

100.00 Discharge (m3/s) Discharge 50.00

0.00

Jul 2001 Jul 2002 Jul 2003 Jul 2004 Jul 2005 Apr 2001 Oct 2001 Apr 2002 Oct 2002 Apr 2003 Oct 2003 Apr 2004 Oct 2004 Apr 2005 Oct 2005 Jan 2001 Jan 2002 Jan 2003 Jan 2004 Jan 2005 Time

Total Abstracted Water Abstracted Water for IRR Abstracted Water for DWS Abstracted Water for IWS 6.00 5.00 4.00 3.00 2.00 (m3/s) Discharge 1.00 0.00 Oct Oct Apr Oct Apr Oct Apr Oct Apr Apr Jan Jan Jan Jan Jan 2005 2004 2005 2005 2003 2004 2004 2002 2003 2003 2001 2002 2002 2001 2001 Jul 2005 Jul Jul 2004 Jul Jul 2003 Jul Jul 2002 Jul Jul 2001 Jul Time

Average in 2001-2005 Average in 2001-2005 Quasi-Natural Flow Potential Flow Total Abstracted Water Abstracted Water for IRR Total Abstracted Water Disturbed Flow Abstracted Water for DWS Abstracted Water for IWS 120.00 5.00 4.50 100.00 4.00 3.50 80.00 3.00 60.00 2.50 2.00 40.00 1.50 Discharge (m3/s)

Discharge (m3/s) Discharge 1.00 20.00 0.50 0.00 0.00 t ar ay ul ov eb Jul ov ec Apr un J Oc Jan F Mar Apr May Jun Aug Sep Oct N D Jan Feb M M J Aug Sep N Dec Time Time

Source: JICA Study Team Figure 4.5.1 Example of Presentation of Simple Model_ver_Existing

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1. Present Catchment BOD Load 3. Present BOD5 Concentration by NAM Catchment and Discharge in the River 1) Domestic load and industrial load BOD5 of normal maximum values discharged into sewerage system Average discharge quantity in the 2) Livestock load river during summer season 3) Industrial load directly discharged into rivers and water bodies

2. Present Accumulated Catchment 4. Present River BOD Load at the BOD Load and Inflow BOD Load Calculation Points Upstream from the Calculation

5. Co-relation of the Present Accumulated Catchment and Inflow BOD Loads and River BOD Load 1) General co-relation from upstream to downstream for accumulated catchment BOD load and river BOD load. 2) Ratios at each calculation point between inflow BOD load including current pollutant loss from sewer networks to the river BOD load.

6. Near Future Catchment BOD 7. Near Future River BOD Load

Load and Inflow BOD Load with and BOD Concentration with 10%

10 % Loss from Sewer Networks Loss from Sewer Networks

8. Required Accumulated Catchment BOD Loads BOD5 in the river to be better than Class II (3.0 mg/l). Required river BOD Load with BOD5 of 3.0 mg/l. Required accumulated catchment BOD load with 10 % loss from sewer networks.

Accumulated Catchment BOD Load

Inflow BOD Load

NAM Catchment 1 River Discharge : Q BOD concentration: C

NAM Catchment 2 River BOD Load

Calculation point Figure 4.5.2 Procedure of Developing the Simple Model for Water Quality

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with NAM Catchments WABD EABD and

4.5.3 Calculation Points for Figure

Figure 4.5.3 Calculation Points for EABD and WABD with NAM Catchments

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Figure 4.5.4 Present Accumulated Catchment BOD Loads and River BOD Loads in EABD

BOD Loads in EABD BOD Loads and River

Figure. 4.5.4 Present Accumulated Catchment 4.5.4 Present Figure.

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Figure 4.5.5 Required Accumulated Catchment BOD Loads and River BOD Loads in EABD with High Priority Towns for WWTPs

BOD Loads in ent BOD Loads and River

WWTPs for Towns EABD with High Priority

Accumulated Catchm 4.5.5 Required Figure.

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Figure 4.5.6 Required Accumulated Catchment BOD Loads and River BOD Loads in EABD with High and Medium Priority Towns for WWTPs

WWTPs for Towns y

h and Medium Priorit

g

in EABD with Hi

BOD Loads Loads and River Accumulated Catchment BOD Fig. 4.5.6 Required

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Figure 4.5.7 Present Accumulated Catchment BOD Loads and River BOD Loads in WABD

BOD Loads and River BOD Loads in WABD BOD Loads in Loads and River Accumulated Catchment BOD Fig. 4.5.7 Present

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Figure 4.5.8 Required Accumulated Catchment BOD Loads and River BOD Loads in WABD with High Priority Towns for WWTPs

WWTPs for Towns with High Priority

WABD BOD Loads in Loads and River Accumulated Catchment BOD Fig. 4.5.8 Required

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Figure 4.5.9 Required Accumulated Catchment BOD Loads and River BOD Loads in WABD with High and Medium Priority Towns for WWTPs

WWTPs for m Priority Towns

in WABD with High and Mediu with High and WABD in

BOD Loads Loads and River Accumulated Catchment BOD Fig. 4.5.9 Required

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CHAPTER 5 SOCIO-ECONOMIC FRAMEWORK

5.1 Population

Population in Bulgaria is on the decrease from the year 1985 as a peak. Nevertheless the population in Bulgaria shows a falling trend as a whole, that in some municipalities are increased during past several years as the Capital City, Sofia. Generally speaking, decrease of population is caused by hemorrhage of labor force of young generation as 20s or 30s of ages. But, on the other hand, increase in population in some cities and/or municipalities means to show a trend of concentration of the population in urban areas.

The population of the largest municipality of Plovdiv in the East Aegean River Basin has increased from 340,122 in 2001 to 341,873 in 2005 even showing some fluctuation depending on the year. And, the population itself of the Municipality of Blagoevgrad in the West Aegean River Basin is less than that in 2001, but it has slightly increased from 77,346 in 2003 to 77,462 in 2005.

Based on the above trend, the population of both the Municipalities of Plovdiv and Blagoevgrad may be increased to the year 2015, and that of the other municipalities in the West and the East Aegean River Basins may remain on the same level as it is. As shown in Figure 5.1.1, in the Plovdiv, 3 cases are assumed as (1) the most optimistic case of population increase with 0.23% to the year 2015 based on the same trend of past 3 years, (2) medium case with 0.18% based on 50% of past 3 years increase, and (3) the most pessimistic case with 0.12% based on 25% of past 3 years increase.

On the other hand, the municipality of Blagoevgrad is the largest municipality in the West Aegean River Basin, but a scale of the municipality is far small comparing with Plovdiv. Therefore, increasing rate of the population is also small. Accordingly, 3 cases are assumed as (1) the most optimistic case of population increase with 0.05% to the year 2015, (2) medium case with 0.03%, and (3) the most pessimistic case with 0.01%. Figure 5.1.2 shows a summary of population projection to the year of 2015.

5.2 Economic Growth

The clearest factor to express the economic growth is GDP. The following table shows a summary of GDP trend during past several years.

Trend of GDP and Per Capita Production for the Past Several Years

(At current price) Description 2001 2002 2003 2004 Annual Average Increasing Rate GDP (million Levs) 29,709 32,335 34,547 38,275 8.82% GDP per Capita (Levs/capita) 3,754 4,109 4,416 4,919 9.44% Source: NSI.

GDP has increased by 8.8% annually in average, and GDP per Capita has also increased by 9.4% annually in average, so these trend seems to be quite firm. However, in case taking price increase into account, the situation cannot be taken lightly.

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The following table shows a summary of GDP revised by the Consumer Price Index (CPI).

GDP and Per Capita Production Revised by CPI Annual Average Description 2002 2003 2004 Increasing Rate GDP Annual increasing rate 8.84% 6.84% 10.79% 8.82% CPI 3.81% 5.64% 3.98% 4.48% Actual annual increasing rate 5.02% 1.20% 6.82% 4.35% GDP/capita Annual increasing rate 9.46% 7.47% 11.39% 9.44% CPI 3.81% 5.64% 3.98% 4.48% Actual annual increasing rate 5.64% 1.83% 7.41% 4.96% Both the actual GDP and the actual GDP Per Capita have been fluctuated around middle to upper end of 4%. Accordingly, it may be appropriate that GDP will be increased around 5% for the future too.

5.3 Transition of Industrial Structure and Tasks of Agricultural Sector

Industrial structure for the past several years can be expressed by the share rate of production (gross value added) (see Table 5.3.1). Production of the agricultural sector (Agriculture/ Hunting/Forestry) has around remained on the same level until 2004, but has fallen in 2005 in the share rate to GDP. On the other hand, that in the manufacturing sector has increased constantly in production. The sector of Electricity/Gas/Water Supply has fallen in production in 2005, but the production has increased steadily even increasing rate is no so much great. The production of the sectors of (1) Trade/Repair of Motor Vehicles/ Personal-Household Goods, (2) Hotels/Restaurants, (3) Transport/Storage/Communi- cations, (4) Financial Intermediation, (5) Real Estate/Renting, (6) Public Administration/ Compulsory Social Security, (7) Education, (8) Health/Social Work is also increased steadily during past several years. Table 5.3.2 shows a summary of share rates of production by economic activities to GDP.

Generally speaking, Bulgaria is a national commitment of agriculture. However, according to the above, the share rate of agricultural production to GDP is less than 10%, and it has been fallen annually. In the year 2005, it has fallen to less than 8%. It may be that to ensure the agricultural production is the most urgent task for the nation. For realizing it, development of incentives of farmers may be the most important factor. For this purpose, as well as governmental policy for increasing the agricultural production, to stabilize and accessibility of farmers to agricultural market is required to ensure.

5.4 Irrigation

According to the Agricultural Statistics, a share rate of irrigated agricultural area to total arable area is only 4% as of 2005.

And, in so called potential irrigable areas (potential irrigation areas) where have formerly been laid down irrigation facilities as canals, the share rate of actual irrigated areas are, nevertheless discrepancies exist depending upon districts, and/or differs by year, less than 10% in overall average in the whole nation.

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Share rates of actual irrigated area to the total potential area in each irrigation branch are ranging from 1.29% to 19.22%, and 7.43% in overall average (see Table 5.4.1).

Each irrigation branch consists of several irrigation systems. According to this detail of irrigation systems, the share rate of the West Aegean River Basin is only 4.76% and that of the East Aegean river Basin is 7.17% in average.

Data indicated in Table 5.4.1 comes only from Irrigation Systems PLC. Actually, there exist some the other irrigation water supply companies as Hydro Melioration-Sevlievo PLC, Zeminvest PLC as quasi-largest companies as well as small-scale irrigation water supply companies located over the nation reached from 50 to 60 firms. The Irrigation Systems PLC supplies the said 2 quasi-largest companies cover only 2% of supplied water volume, and remaining 98% of irrigation water. Supplied water volume by the smallest companies is not clear, but anyway, it may say that the data above indicates overall status of actual irrigated areas of the nation.

Through the Study, it has been made clear that the reason of low actuality ratings to the potential area caused by mal-function of irrigation facilities because of its deterioration and of lack of suitable operation and maintenance. As discussed in previous sub-clause, to develop the agricultural productivity is the urgent task in the nation. However, there will be a lot of matters to be solved as financing matters, farming skills of farmers and accessibility to the market, so that to prompt realization of improvement of the agricultural production will face to a lot of difficulties.

Based on the Study, it is assumed that the irrigation areas will be expanded by 20% of the potential area in each river basin in average and this rate may be ceiling rate of irrigation improvement until the target year 2015.

5.5 Living Standard and Water Consumption

Average income level per household in Bulgaria, the level in 2001 has fallen from that in 2000, but after that the income level has been increased by 7.66% annually, and it seems that the income per household has constantly been increased, as shown in Chapter 2.3.

Among them, the income level can be illustrated as shown in Figure 5.5.1. In a simple average, the income level has been increased by 7.66% as discussed above. But the increasing rate has been decreased year by year, so that it may not be optimistic. And, during the same period, the CPI has fluctuated on the rate of 2.91% in average, so that the actual increase of income is on a level of 4%. Therefore, the increase of income is not so much.

On the other hand, according to the table “Average Annual Expenditure per Household and per Capita” in Chapter 2.3, share rate of foods to the total expenditure has improved from 42% in 2000 to 36% in 2005 that almost the same level of developed countries as summarized in the following table. But, it is rather questionable.

Share Rate of Foods to the Total Expenditure in Bulgaria

2000 2001 2002 2003 2004 2005 Engel Coefficient 42.09% 42.72% 40.30% 38.14% 36.98% 35.97%

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According to a result of “Water Utility Survey” made by JICA Study Team in 2006, the share rate of expenditure for foods to the total expenditure is more than 50% in both the Basins as shown in the following table, and it implies that the living of people may be in needy circumstances.

Share Rate of Expenditure for Foods to the Total Expenditure in Bulgaria (Lev/HH per month) Income/HH Expenditure River Basin in Overall Food and Fuel Water Others Total Average Drinks West Aegean 283.60 62.36 17.07 229.45 592.48 592.48 River Basin 47.87% 10.53% 2.88% 38.73% 100.00% East Aegean 271.22 62.83 17.56 141.73 493.33 493.33 River Basin 54.98% 12.74% 3.56% 28.73% 100.00% Both the 274.39 62.77 17.47 165.52 520.14 520.14 Basins 52.75% 12.07% 3.36% 31.82% 100.00% Source: A result of "Water Utility Survey" made by JICA Study Team, 2006. Provided that the share rate of expenditure for water of 3.36% is in average based on answers for expenditure by items, and this may be expressed for expenditure for public water supply, and it may not expressed the expenditure for water in total. Almost of people purchase a bottled mineral water. Actual expenditure for water in total is, as shown in the table entitled as “Expenditure for Water in Grand Total” in Chapter2.12, at 27.32 Lev/HH per month in weighted average in both the Basins, and its share rate to the total has reached to 5.25%.

Currently, consumed water volume has remained in low level as 92 ldc as of 2005 as shown in the following table. This is based on water charge collection record in water supply side, and so, it is the consumed water volume depending upon current public water supply systems. Namely, this consumed water volume may be the same amount of supplied water volume.

Changes of Consumed Water Volume by Public Water Supply Systems for the Past Several Years (ldc)

2000 2001 2002 2003 2004 2005

Paid Water 99 95 90 95 94 92 Volume Source: Environmental Statistics, 2005, NSI. Actual price of mineral water is 371 Lev/m3 as shown in the following table, so that the price 371 times of unit charge of water supplied by public water supply systems. Therefore, in case that the supplied water volume is enough for living, they must not purchase such expensive bottled mineral water.

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Price of Bottled Mineral Water Unit Price of Bottled Mineral Water River Basin Per Bottle Per Litre Equal: (Lev/ 1.5 (Lev/ℓ ) (Lev/m3) ℓ bottle) West Aegean 0.58 0.39 386 River Basin West Aegean 0.55 0.37 368 River Basin Both the Basin 0.56 0.37 371 Source: Water Utility Survey made by JICA Study Team, 2006. On the other hand, according to the other result of the said “Water Utility Survey”, the actual consumed water volume is 156 ldc (under the condition of 3.37 persons/HH in family scale for converting the consumed water volume per household per month) as shown in the following table. In other words, different water volume between 92 ldc and 156 ldc is to be covered by purchasing the said expensive bottled mineral water and/or some other source with heavy burden.

Actual Water Consumption Water Consumption Remarks: (m3/HH per month) Conversion River Basin into ldc Summer Winter Average (Average) West Aegean 17.55 12.45 15.00 148 River Basin East Aegean 18.77 13.25 16.01 158 River Basin Both the 18.43 13.02 15.73 156 Basins Source: A result of "Water Utility Survey" made by JICA Study Team, 2006. One of wastewater treatment plants under construction is designed under the condition of 180 ldc of discharge volume. If the discharge volume is assumed at 90% of consumed water volume, the consumed water volume is to be at 200 ldc. Taking into account of this as well as increase of consumed water volume for the future according to the current trend of water consumption as discussed above, it is assumed that envisaged consumed water volume will be increased by 220 ldc as of the target year 2015.

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CHAPTER 5

5.1

Main Report

Chapter 5

Tables

5.2

5.3

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Table 5.3.1 Fluctuation of Share Rate of Production by Economic Activities to GDP in the Past Several Years (million Lev)

Gross Value Added in Each Economic Activity Group at Basic Prices Economic Activity Group

2001 2002 2003 2004 2005

Agriculture/Hunting/Forestry 3,520 3,445 3,485 3,576 3,327 Fishing 1314141414 Mining/Quarrying 403 412 440 530 566 Manufacturing 4,606 4,966 5,516 5,989 6,750 Electricity/Gos/Water Supply 1,591 1,634 1,652 1,722 1,626 Construction 1,203 1,276 1,364 1,668 2,026 Trade/Repair of Motor Vehicles/ 1,937 2,105 2,186 2,506 2,950 Personal-Household Goods Hotels/Restaurants 535 563 625 713 899 Transport/Storage/Communications 3,386 3,950 4,166 4,570 4,952 Financial Intermediation 831 986 1,147 1,382 1,682 Real Estate/Renting 4,391 4,751 4,844 5,189 5,568 Public Administration/ 1,754 1,958 2,132 2,351 2,457 Compulsory Social Security Education 1,073 1,127 1,194 1,336 1,404 Health/Social Work 661 858 960 998 1,031 Other 450 480 503 626 771 Community/Social/Personal Total 26,356 28,526 30,227 33,169 36,023 Adjustment 3,354 3,809 4,319 5,106 5,925 FISIM* -539 -596 -753 -1,043 -1,360 Import Duties 195 188 231 292 372 Net Taxes on Products 1,057 1,143 1,434 1,938 2,115 VAT 2,641 3,073 3,407 3,918 4,798 GDP at Market Prices 29,709 32,335 34,547 38,275 41,948 (Note) *FISIM = Financial Intermediation Services Indirectly Measured. Source: Statistical Yearbook, 2006, NSI.

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Table 5.3.2 Change of Share Rates by Economic Activities to GDP

Share Rate of Gross Value Added in Each Economic Activity Group to the Total Gross Value Added Economic Activity Group 2001 2002 2003 2004 2005 Average

Agriculture/Hunting/Forestry 11.85% 10.66% 10.09% 9.34% 7.93% 9.97% Fishing 0.04% 0.04% 0.04% 0.04% 0.03% 0.04% Mining/Quarrying 1.36% 1.28% 1.27% 1.38% 1.35% 1.33% Manufacturing 15.50% 15.36% 15.97% 15.65% 16.09% 15.71% Electricity/Gos/Water Supply 5.36% 5.05% 4.78% 4.50% 3.88% 4.71% Construction 4.05% 3.95% 3.95% 4.36% 4.83% 4.23% Trade/Repair of Motor Vehicles/ 6.59% 6.52% 6.51% 6.33% 6.55% 7.03% Personal-Household Goods Hotels/Restaurants 1.80% 1.74% 1.81% 1.86% 2.14% 1.87% Transport/Storage/Communications 11.40% 12.22% 12.06% 11.94% 11.81% 11.88% Financial Intermediation 2.80% 3.05% 3.32% 3.61% 4.01% 3.36% Real Estate/Renting 14.78% 14.69% 14.02% 13.56% 13.27% 14.07% Public Administration/ 6.03% 5.90% 6.06% 6.17% 6.14% 5.86% Compulsory Social Security Education 3.61% 3.49% 3.46% 3.49% 3.35% 3.48% Health/Social Work 2.23% 2.65% 2.78% 2.61% 2.46% 2.54% Other 1.59% 1.51% 1.48% 1.46% 1.63% 1.84% Community/Social/Personal Total 88.71% 88.22% 87.50% 86.66% 85.87% 87.39% Adjustment 11.29% 11.78% 12.50% 13.34% 14.13% 12.61% FISIM* -1.82% -1.84% -2.18% -2.72% -3.24% -2.36% Import Duties 0.66% 0.58% 0.67% 0.76% 0.89% 0.71% Net Taxes on Products 3.56% 3.54% 4.15% 5.06% 5.04% 4.27% VAT 8.89% 9.50% 9.86% 10.24% 11.44% 9.99% GDP at Market Prices 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% (Note) *FISIM = Financial Intermediation Services Indirectly Measured. Source: Statistical Yearbook, 2006, NSI.

5.4

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Table 5.4.1 Potential Area and Fluctuated Actual Irrigated Area

Actual Irrigated Area (ha) Average Potential Irrigation Irrigation Irrigation Branch Portion Area (ha) 2000 2001 2002 2003 2004 2005 Average (%)

Burgas 19,922 1,390 499 379 349 63 64 457 2.29% Varna 17,246 3,276 2,301 2,849 3,306 485 757 2,162 12.54% Veliko Tarnovo 42,683 3,807 395 396 1,216 862 77 1,126 2.64% Vidin 20,737 1,208 782 870 822 306 34 670 3.23% Vratsa 47,224 4,949 1,835 720 1,085 1,103 290 1,664 3.52% Gotse Delchev 16,809 8,656 1,858 1,070 3,131 2,654 2,010 3,230 19.22% Dupnitsa 26,317 5,324 1,166 516 678 654 198 1,423 5.41% Montana 22,750 626 842 477 349 325 163 464 2.04% Pazardzhik 57,799 20,161 11,476 6,676 9,784 10,046 5,451 10,599 18.34% Pernik 16,045 1,542 570 368 426 331 339 596 3.72% Pleven 53,127 8,254 3,732 2,668 3,452 2,874 651 3,605 6.79% Plovdiv 106,878 30,600 24,792 12,441 20,024 17,598 9,233 19,115 17.88% Ruse 57,573 895 961 710 1,317 446 137 744 1.29% Sandanski 15,790 3,657 2,097 1,923 1,172 1,220 1,140 1,868 11.83% Sliven 199,816 9,738 5,595 4,880 5,469 2,408 1,557 4,941 2.47% Sofia 29,555 1,726 819 827 824 985 624 967 3.27% Stara Zagora 75,404 16,693 11,782 4,844 3,527 1,611 957 6,569 8.71% Targovishte 26,123 5,001 2,497 2,027 3,979 2,718 933 2,859 10.95% Haskovo 50,059 7,474 3,486 3,710 5,597 5,365 2,988 4,770 9.53% Shumen 37,398 2,312 2,512 2,113 3,475 1,629 604 2,107 5.64% Yambol 37,421 4,543 1,949 3,048 3,470 1,609 1,170 2,631 7.03% Total 976,673 141,834 81,946 53,513 73,451 55,289 29,376 72,568 7.43% (Remarks) West Aegean River Basin. East Aegean River Basin. (Note) Some irrigation branches cover several municipalities located in other river basins. Source: Irrigation Systems PLC.

5.5

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CHAPTER 5

5.1

Main Report

Chapter 5

Figures

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Increase Increase Increase 355,000 Optimistic against Medium against Pessimistic against Year Opptimistic case: Based on the same trend of the last 3 years Case previous Case previous Case previous 352,500 Medium case: Based on 1/2 trend of the last 3 years year year year Pessimistic case: Based on 1/4 trend of the last 4 years 2005 341,873 0.1198% 341,873 0.1198% 341,873 0.1198% 350,000 2006 342,770 0.2624% 342,508 0.1857% 342,296 0.1238% case istic ptim 2007 343,546 0.2263% 343,142 0.1852% 342,719 0.1235% O e 347,500 m cas 2008 344,321 0.2256% 343,776 0.1848% 343,142 0.1233% Mediu

Population se istic ca 2009 345,096 0.2250% 344,410 0.1843% 343,564 0.1231% Pessim 345,000 2010 345,870 0.2244% 345,043 0.1839% 343,986 0.1229% 2011 346,644 0.2238% 345,676 0.1835% 344,408 0.1227% 342,500 2012 347,418 0.2232% 346,309 0.1831% 344,830 0.1225% 2013 348,191 0.2226% 346,942 0.1826% 345,252 0.1223% 340,000 2014 348,964 0.2220% 347,574 0.1822% 345,673 0.1221% 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2015 349,736 0.2214% 348,206 0.1818% 346,095 0.1219% Year Annual Average: 0.2277% 0.1837% 0.1228% Figure 5.1.1 Population Projection of the Municipality of Plovdiv

Increase Increase Increase 77,900 case Optimistic against Medium against Pessimistic against stic Year ptimi Case previous Case previous Case previous 77,800 O year year year 77,700 2005 77,462 0.0517% 77,462 0.0517% 77,462 0.0517% m case Mediu 2006 77,502 0.0510% 77,482 0.0258% 77,472 0.0129% 77,600 ase 2007 77,541 0.0516% 77,502 0.0258% 77,482 0.0129% Pessimistic c 2008 77,581 0.0515% 77,522 0.0257% 77,492 0.0129% 77,500

2009 77,621 0.0515% 77,542 0.0257% 77,502 0.0129% Popyulation 2010 77,661 0.0514% 77,562 0.0257% 77,512 0.0128% 77,400 Opptimistic case: Based on the same trend of the last 2 years 2011 77,701 0.0514% 77,582 0.0257% 77,522 0.0128% Medium case: Based on 1/2 trend of the last 2 years 2012 77,741 0.0513% 77,602 0.0257% 77,532 0.0128% 77,300 Pessimistic case: Based on 1/4 trend of the last 2 years 2013 77,781 0.0512% 77,621 0.0256% 77,542 0.0128% 2014 77,821 0.0512% 77,641 0.0256% 77,552 0.0128% 77,200 2015 77,860 0.0511% 77,661 0.0256% 77,562 0.0128% 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Annual Average: 0.0513% 0.0257% 0.0128% Year Figure 5.1.2 Population Projection of the Municipality of Blagoevgrad

7,000

5.2 6,000 5.3

5.4 5,000

5.5 (Levs/Year) Income

4,000 2001 2002 2003 2004 2005 Year

Figure 5.5.1 Changes of Income Level per Household in Bulgaria for Past Several

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CHAPTER 6 RIVER BASIN MANAGEMENT PLAN

6.1 Formulation of River Basin Management Plan

6.1.1 Introduction

EABD and WABD have to prepare the River Basin Management Plan (RBMP) in accordance with the EU-WFD, of which the target is to attain the good physico-chemical and ecological status for surface water and groundwater by 2015. The main deadlines and milestones of the planning of the RBMP are set by the WFD as follows: • Ecological status classification (Type-B) by 2004, • Impact review completed by member states and register of protected areas by 2004, • Summary reporting of impact review to Commission by 2005, • Monitoring programme operational by 2006, • Programme of measures to be established for achieving the environmental objectives of the WFD based on sound monitoring and the analysis of the characteristics of the river basin; and the 1st River Basin Management Plan completed by 2009, including the designation of heavily modified water bodies, • Cost recovery for water services in accordance with the polluters pay principal by 2010, • Programmes of measures operational by 2012, • Revised overview of significant water issue by 2013, and • Evaluation of the first period and update the RBMP for the next two six-year cycles of planning and implementation of measures by 2015.

The Government of Bulgaria established four river basin directorates from 2002 to 2003 in accordance with the Water Act of Bulgaria, which was enacted in 2000. The four basin directorates have started the arrangement of river basin management activities and also started the preparation for the RBMP in accordance with the EU-WFD and the Water Act of Bulgaria.

The output of the present study does not correspond one by one to the form of River Basin Management Plan defined by EU-WFD. The JICA Study considered both EU-WFD and Water Act, e.g. the share of water quantity is minimal in EU-WFD, but water quality and water quantity have been dealt as two pillars in the Study. The results of the present study would be considered in the forthcoming process of the preparation of the River Basin Management Plans.

The Study has supported EABD and WABD in preparation of RBMP, of which the planning process requires the participation of stakeholders through a series of Public Consultation Meetings. The public consultations have been conducted in three stages as follows:

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Components according Planning Stages Public Consultation to EU- WFD Current and foreseen - Monitoring the current status 1st public consultation; scenarios assessment - Assessment of the current status Conducted in November 2006. Main topics: Current status of impacts

Target setting and Setting up of the environmental 2nd public consultation; preliminary objectives and preliminary Conducted in September 2007 programmes of programmes of measures Topics: Direction of measures Programmes of measures Alternative - Setting up of the programme of 3rd public consultation programmes of measures Conducted in December 2007 measures and actions - Establishment of monitoring Topics: Programmes of taking programmes measures and RBMP (Draft) - Development of River Basin Management Plans (RBMP)

6.1.2 Pressures and Impacts in the River Basin Level

The current status of surface water and groundwater in the Study Area are studied and discussed in Chapter 2 in this report. Significant pressures and impacts to be caused by human activities are listed as follows: • Discharges of wastewaters from settlements, industries and large animal breeding farms without WWTPs or with WWTPs without a proper treatment, • Discharge of pollution loads from settlements without sewerage facilities, • Discharge of pollution loads from agricultural lands and animal breeding farms, • Impacts caused by inappropriate water intakes for water supply, irrigation and inter-basin water transfer, • Physical impacts by river-morphological changes, caused by improper activities like heavy sand and gravel extraction in and along river channels, • Impacts caused by informal or illegal activities like solid waste dumping into or along the rivers, and • Combined effects of various improper management activities in and along the rivers.

6.1.3 Target Year for the Completion of Programmes of Measures

According to the time schedule set by the EU-WFD, the RBMP including improvement plans should be formulated by the end of 2008 and commenced in 2010. Bulgaria is paying effort to follow the schedule, however, it may not be an easy task to formulate the RBMP of the national level.

To start the implementation of programme of measures from 2010, the implementation of structural measures will require the three steps, “F/S”, “D/D” and “construction”, and require more than two years for tendering, selection of consultants and constructors. 6-2 JICA CTI Engineering International Co., Ltd.

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When the conditions of lack of implementing organization and lack of experience are considered, it may be difficult to expect effective preparation activities.

There are many existing sewerage facilities, which need rehabilitation because of poor maintenance work and superannuation, and also there may be increment of many unexpected measures to cope with.

Implementation of the proposed River Basin Management Plan by the target year 2015 is thus deemed difficult, and hence, the target year should be set at 2021 or 2027, years for every six years review defined by EU-WFD.

6.1.4 Baseline Scenario for the RBMP

According to the Study on the current status of the surface water and groundwater it is clear that both the surface water and groundwater are heavily affected by the human activities and the water related facilities have been deteriorated or superannuated. The targets of the water quality are set as follows: • To attain good physico-chemical status for surface water (Reference class-I and II), and • To attain good ecological status for surface water (Reference class High and Good). In order to attain the target, various measures composed of structural and non-structural measures shall be implemented duly within a limited period. Accordingly a systematic implementation of various measures for RBMP shall be required for the managing organization to the target by 2015.

RBMP is necessary to be formulated from integrated water resources management aspects. The programme of measures in the RBMP shall be required for improving qualitative, quantitative and river morphological conditions. The River Basin Management Plan shall be formulated based on the Integrated Water Resources Management approach. The basic scenario is proposed as follows: • To improve water quality firstly to attain the good physico-chemical status for surface water and groundwater, and secondly to attain the ecological status for surface water and groundwater by 2015, • To improve water quality by phased expansion of the municipal wastewater treatment capacities and treatment for nitrogen and phosphorous by new construction of WWTPs and also by phased rehabilitation of the existing WWTPs from major towns and settlements in priority zones, • To renovate the existing sewer networks to reduce the sewage loss to increase the efficiency of wastewater treatment and also reduce the seepage of sewerage into the ground to avoid possible groundwater pollution, • To rehabilitate water supply networks to reduce the high rate of water supply loss of 60-70%, • To improve the management and regulation in order to conduct more strong control of reducing the discharge of untreated or improperly treated wastewaters from industries, mines and animal breeding farms,

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• To improve facilities required for efficient water use of water use sectors like domestic water supply networks and irrigation facilities, • To improve the permission of water intakes and the distribution of water resources based on the water balance of each river basin, • To improve the management and regulation in order to conduct more systematic management for river morphology, river channels, river flows, sediment and also floods disaster, flood hazard areas, and • To prepare programme of measures composed of the following components:

i) Water quality improvement and management

ii) Water quantity improvement and management

iii) Management of river morphology

iv) Implementation

6.1.5 Required Management Plans

The surface water and groundwater in the EABD and WABD have been studied. The programmes of measures for the RBMP are required to be studied. The RBMP requires programmes of measures: • To improve the status of chemical and physical conditions, • To improve the status of quantitative conditions, • To improve the status of river morphological conditions, and • To improve the status of prevention of flood disasters and incidental disasters caused by toxic waste or substances.

The RBMP is to be composed of the following plans: • Water quality management plan, • Water quantity management plan, • Groundwater management plan, • River management plan, and • Implementation plan.

Each plan is to be discussed in the following sub-sections.

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6.2 Water Quality Management Plan

6.2.1 Objectives of Water Quality Management Plan • To attain good status of water in terms of ecology and common physico-chemical parameters by reducing organic pollutants and nutrients inflow to water bodies. • To prevent direct discharge of wastewater without treatment (domestic, industrial, livestock wastewaters) into the surface water bodies and relating groundwater bodies. • To reduce pollution loads from industries, livestock and agriculture mainly by strengthening of regulation. • To propose programme of structural measures with rough cost estimation. • To propose implementation plan for the programme of structural measures. • To propose non-structural measures such as monitoring, improvement of regulation, etc.

6.2.2 Pollution Loads

(1) Methods of Estimating Pollution Loads

(a) Items of the Pollution Loads Estimation in the River Basins

Reduction of pollution loads from the river basins is only the way for improving water quality in the rivers and water bodies. The following items of pollution loads were estimated in the Study. Domestic pollution loads plus industrial pollution loads, which are discharged into the sewerage systems (BOD5, TN and TP loads). Industrial pollution loads, which are discharged directly into the rivers or water bodies (BOD5, TN and TP loads). Livestock pollution loads, which are composed of the pollution loads from major livestock firms as the point sources and other small size livestock firms or livestock owned by farmers as non-point sources (BOD5, TN and TP loads). Fertilizer as non-point pollution loads (TN and TP loads).

(b) Domestic Pollution Loads plus Industrial Pollution Loads discharged into the Sewerage Systems

Domestic pollution loads are generated and discharged from people. Therefore, population in each settlement and town is the basis for calculation.

The existing Water Supply and Sewerage Companies (WSSs) have contracts with industries, which discharge their wastewater into the sewerage networks. The WSSs have obligation to send copies of the above contracts to the Basin Directorates, but this rule is not followed in many cases.

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Basin Directorates either RIEW have almost no information and data about such industries (list, contracted amount of water supply, and discharge quantity and quality of wastewater), which discharge into the sewerage system. Basin Directorates and RIEW have the information of discharge quantity and quality of wastewater (although not covering all) at the outlet of sewer pipes or outlet of the existing urban or municipal WWTPs.

Considering the above situation, the industrial loads, which are discharged into the sewerage systems, have to be estimated together with the domestic loads based on the population equivalent (PE). In order to overview and manage the total industrial loads in the river basins, it is very necessary to know the industrial loads which discharge into the sewerage systems too.

Applied Ratio of PE / Population PE size of Town / Settlement Ratio of PE / Population • 1.5 in principle, or PE ≥ 10,000 • Ratio in Document A. • 1.2 in principle, or 2,000 ≤ PE < 10,000 • Ratio in Document A. 500 ≤ PE < 2,000 • 1.2 in principle PE < 500 • 1.0 Document A: “Implementation Programme for Directive 91/271/EC concerning Urban Wastewater Treatment” (National Programme for WWTP).

The following table shows the applied unit loads for estimating the domestic loads and industrial loads, which are discharged into sewerage systems.

Unit Loads for Domestic and Industrial Load discharged into Sewerage Systems BOD TN TP Item (g/day/PE) (g/day/PE) (g/day/PE) 1) Raw: 1pe 60 11 1.8 2) Sewered without treatment 60 11 1.8 3) With primary treatment by the existing WWTP 35 11 1.8 4) With secondary treatment by the existing WWTP 10 4 1 5) Without sewerage system 15 3 1 6) With new WWTP including TN and TP treatment 6 2.5 0.9

(c) Loss of the Existing Sewer Networks

Based on the analysis of the self-monitoring data of some of the existing WWTPs in EABD and WABD, it can be known that the pollution loads, which flow through the sewer pipes, are lost, and significant dilution is occurred by infiltration of water from surrounding ground at the same time.

Percentages of above loss in terms of BOD5 are estimated at least about 40% for the sewer networks in the Maritsa and Tundzha River Basins, 50% in the Arda River Basin and 60% in the Struma, Mesta and Dospat River Basins in general.

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The existing monitoring data of RIEWs at the outlet of the existing sewer pipes also show low concentration of BOD5 in general. This fact supports the above estimation of the significant pollution loss from the sewer networks. The lost pollutants contaminate surrounding groundwater. There is a fact that many groundwater wells have problem of nitrate (NO3) contamination, and this might be caused not only by fertilizers containing nitrogen, but also by the loss from the sewer networks.

Estimated Loss of Pollution Loads at the Inlet of the Existing WWTPs PE in 2005 Loss Inflow Outflow Inflow (NSI data) Generated of BOD BOD Load BOD WWTP Treated Load to Discharge BOD BOD Total By PE Load 5 5 PE WWTP (l/s) (mg/l) (mg/l) PE (kg/day) (%) (kg/day) =1-F/G A B C D E F G H Kyustendil 210 81.3 6.1 70,688 65,638 1,477 3,938 62 WWTP Pernik 483 51.4 19.6 121,350 120,168 2,148 7,210 70 WWTP Radomir 51 53.3 2.5 21,621 19,367 236 1,162 80 WWTP Sliven 168 445.5 87.2 100,294 100,294 6,483 6,134 - WWTP Plovdiv 1,667 125.0 - 666,652 599,987 18,005 35,999 50 WWTP Nova

Zagora 162 301.4 21.2 58,463 32,388 4,318 1,943 - WWTP Data sources: 1) Self monitoring data of the above WWTPs.

Estimated Loss of BOD5 at the Outlet of the Existing Sewer Pipes Average BOD at 5 % of BOD against % of BOD against outlets of sewer 5 5 River Basin normal low value of normal value of pipes sewage (150 mg/l) sewage (200 mg/l) (mg/l) Maritsa River Basin 87 58 % (loss 42%) 44 % (loss 56%) Tundzha River Basin 114 76 % (loss 24%) 57 % (loss 43%) Arda River Basin 100 67 % (loss 33%) 50 % (loss 50%) Struma River Basin 64 43 % (loss 57%) 32 % (loss 68%) Mesta River Basin 70 47 % (loss 53%) 35 % (loss 65%) Data sources: 1) Data of EABD and WABD based on the monitoring data of RIEWs.

(d) Industrial Pollution Loads discharged directly into the River or Water Bodies

Industrial pollution loads, which are directly discharged into the rivers or water bodies are estimated based on the self monitoring data from such industries, monitoring data of RIEWs for the emission of the industrial wastewater, and permission data for the wastewater discharge by the Basin Directorates to the industries.

For estimating the TN and TP Loads from the industries, “Regulation No. 6 of 9 November 2000 on the Limit Values for Admissible Contents of Dangerous and

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Harmful Substances in the Waste Water Discharged in the Water Bodies” is also referred.

Tables 6.2.1 and 6.2.2 show the major industries in EABD and WABD, which discharge their wastewater directly into the rivers or water bodies.

(e) Livestock Pollution Loads

Livestock pollution loads are composed of the pollution loads from major livestock farms as point sources, and pollution loads from small and medium livestock farms including small numbers of livestock owned by farmers as non-point livestock farms.

The data of the major livestock farms are based on the information from National Veterinary Medical Service. Tables 6.2.3 and 6.2.4 show the major livestock farms in EABD and WABD.

Numbers of heads of livestock are based on the Agro-statistics of MoAF in 2003, which was used for estimating the non-point livestock loads. Run-off rate of the non-point livestock load is set at 5%.

Following table shows the applied unit loads for estimating the livestock loads.

Unit Loads for Livestock Livestock BOD TN TP (g/year/head) (g/year/head) (g/year/head) 1) Cattle 230 79 1.4 2) Pig 7.98 4.0 0.75 3) Hens for egg production 0.7 0.4 0.12 4) Slaughter chicken 0.05 0.03 0.002 5) Duck 0.2 0.1 0.006

(f) Fertilizer as Non-point Pollution Loads

As the pollution loads from agriculture, fertilizer as non-point pollution loads are estimated based on the data of the fertilizer amount by district in Bulgaria, which were collected from the “National Plant Protection Service”. Run-off coefficient of 10% is applied for the estimation. Unit load of fertilizer is as shown below

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Average Amount of Fertilizer by District and Unit Load Average Fertilizer Amount Area Unit Load of Fertilizer (Year 1999 to 2005) (km2) (kgN/year) (kgP/year) (kgN/y/m2) (kgP/y/m2) Plovdiv 5,961 7,366,998 234,339 0.00124 0.000039 Burgas 7,741 8,189,752 81,045 0.00106 0.000010 Blagoevgrad 6,458 1,743,346 103,836 0.00027 0.000016 Pazardzhik 4,459 2,350,964 164,106 0.00053 0.000037 Kardzhali 3,210 633,216 1,366 0.00020 0.000000 Kyustendil 3,060 760,438 20,776 0.00025 0.000007 Sofia 7,071 2,093,932 94,665 0.00030 0.000013 Stara Zagora 5,148 7,857,141 141,730 0.00153 0.000028 Haskovo 5,528 4,740,222 75,958 0.00086 0.000014 Smolyan 3,204 1,648,178 209,222 0.00051 0.000065 Sliven 3,542 4,183,851 28,153 0.00118 0.000008 Yambol 3,353 6,222,461 86,337 0.00186 0.000026 Pernik 2,397 710,138 3,531 0.00030 0.000001 Gabrovo 2,022 903,478 17,075 0.00045 0.000008 Veliko 5,961 7,366,998 234,339 0.00124 0.000039 Tarnovo Plovdiv 7,741 8,189,752 81,045 0.00106 0.000010

(2) Pollution Loads and Pollution Mechanism in EABD

(a) Present Pollution Loads and Pollution Mechanism in EABD

Present BOD loads by NAM catchment in EABD are estimated as shown in Figures 6.2.1 and 6.2.2 shows the BOD loads from unit area (= total BOD load of NAM catchment / area of NAM catchment). From these figures, it is clear that the area around Pazardjik, Plovdiv and Stara Zagora are the highest producers of BOD loads, which followed by the Dimitrovgrad and Haskovo Areas. In the Tundzha River Basin, Yambol to Elhovo areas is the highest producer of BOD loads. Sliven and Kazanlak Areas also produce high BOD loads from small areas. For the Arda River Basin, Kardzhali and Smolyan Areas are the highest producers of BOD loads.

These tendencies of the BOD load distributions coincide with the current pollution conditions along the Maritsa and Tundzha Rivers, where water quality is generally poor to moderate conditions from the upstream to the downstream. For the Arda River, the BOD load distribution also coincides with the tendency of river water quality, where the tributary along Smolyan Town and the river reach around Kardzhali Town is in poor condition.

These tendencies of BOD load distribution also coincide with the results of the Risk Analysis for the Surface Water Bodies made by the EABD Directorate.

In addition to the BOD Loads, Figures 6.2.5 and 6.2.7 show the Present TN and TP loads in EABD.

(b) Near Future BOD Loads in EABD

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WWTPs in the Maritsa River Basin, and Madan, Rudozem and Zlatograd WWTPs in the Arda River Basin. All of the new WWTPs can treat up to secondary treatment for BOD. Stara Zagora and Dimitrovgrad WWTPs have facilities of higher treatment for treating nitrogen and phosphorous. In Karlovo, construction of the new WWTP has been started only a part. However, it looks that the budget for the Karlovo WWTP construction is insufficient.

In addition to the above nine new WWTPs, rehabilitation of the existing Sliven WWTP including some improvement of sewer networks has been committed by ISPA, and it is under-tendering. New Smolyan WWTP including some improvements of sewer networks has also been committed by ISPA, and it has been already contracted with the contractor in 2007.

Figure 6.2.3 shows the BOD loads in the Near Future Conditions in EABD and Figure 6.2.4 shows the BOD loads from unit area. By the above under-constructed and soon constructed WWTPs, BOD loads will be reduced around Pazardjik, Stara Zagora, Dimitrovgrad, Haskovo, and Smolyan areas. Figure 6.2.6 and Figure 6.2.8 show the TN and TP loads in EABD in the Near Future Condition.

(3) Pollution Loads and Pollution Mechanism in WABD

(a) Present Pollution Loads and Pollution Mechanism in WABD

Present BOD loads by NAM catchment in WABD are estimated as shown in Figure 6.2.9 and 6.2.10 shows the BOD loads from unit area. In terms of BOD load in NAM catchments, Blagoevgrad area is the highest producer followed by Pernik, Dupnitsa, Sandanski and Petrich area. In terms of BOD load from unit area, Blagoevgrad, Sandanski, Gotse Delchev area are the highest density of BOD load, followed by Pernik, Dupnitsa, Bansko and Razlog area.

These tendencies of the BOD load distributions coincide with the current pollution conditions along the Struma and Mesta Rivers, and the results of the Risk Analysis for the Surface Water Bodies made by the WABD office.

Figures 6.2.13 and 6.2.15 show the Present TN and TP loads in WABD.

(b) Near Future Pollution Loads in WABD

There are two numbers of new WWTPs, which are under-construction. They are Blagoevgrad WWTP in the Struma River Basin and Razlog WWTP in the Mesta River Basin. These two new WWTPs can treat BOD up to secondary level. Razlog WWTP, which has almost completed construction by September 2007, has a partial function of nitrogen reduction.

In addition to the above two new WWTPs, rehabilitation of the existing Kyustendil WWTP including some improvements of sewer networks has been committed by ISPA, and it is under-tendering.

Figure 6.2.11 shows the BOD loads in the Near Future Conditions in WABD and Figure 6.2.12 shows the BOD loads from unit area. By the above under-constructed and soon renovated WWTPs, BOD loads will be reduced around Blagoevgrad,

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Razlog areas. Figures 6.2.14 and 6.2.16 show the TN and TP loads in WABD in the Near Future Condition.

(4) Co-relation between Catchment BOD Load and River BOD Load

Co-relation between the accumulated catchment BOD load, which accumulate BOD load of NAM catchments locating upstream from certain calculation point in the river, and the river BOD Load in dry season (July to September) is calculated.

Accumulated catchment BOD load = ∑ (BOD load of NAM catchment i)

River BOD load = (BOD concentration in the river: C) x (Average discharge of river in dry season: Q)

NAM Catchment 1 River Discharge : Q BOD concentration: C

NAM Catchment 2

Calculation point

Figures 6.2.17 and 6.2.18 show co-relation between the “Accumulated catchment BOD load” and “River BOD load”. Discharge of the river is based on the MIKE 11 Water Quantity Simulation results. BOD concentration (normal maximum values in dry season) in the river is based on the monitoring data of ExEA. Followings are the findings of this analysis. There are very high co-relation between the “Accumulated catchment BOD load” and “River BOD load” for the Maritsa, Tundzha, Arda, Stuma and Mesta Rivers in general. The above high co-relations mean that the BOD loads in the upper catchment areas reflect the BOD concentration at certain location along the river. Considering the above fact, in order to improve water quality at certain location in the river, it is necessary to reduce the accumulated catchment load upstream from that location.

6.2.3 Structural Measures of the Programme of Measures

(1) Planning Principle

Based on the analysis of the pollution loads in the present and near future conditions as well as the water quality conditions in the rivers, followings are the procedure of planning the programme of measures, which is mainly applied for planning the structural measures for water quality management and improvement. • BOD load is focused as a key parameter for the reduction of catchment pollution loads.

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• The current water quality (in terms of BOD, etc.) in the rivers is reflected by the significant loss from sewer networks (at least 40% in Maritsa and Tundzha River Basins, 50% in Arda River Basin, and 60% in Struma and Mesta River Basins). However, the loss should be reduced from now on, which is hopefully up to 10% in the long time future. This reduction of loss is necessary to stop the pollution of groundwater by the loss from the sewer networks. • In case the loss of the sewer networks will be reduced up to 10% and the treatment conditions of towns and settlements in EABD and WABD areas will be the same as the Near Future Conditions, the water quality in the river will be much worse than the present. This assumption is the basis for planning for reducing the catchment pollution loads as well as for improving future water quality conditions in the rivers. • Based on the rough estimation of the required BOD loads in the river basins for attaining the good status of water in terms of BOD (Class II: target of BOD 3.0 mg/l), the accumulated catchment BOD loads are necessary to be reduced about 50% for Maritsa, Tundzha, Stuma and mid to downstream of Mesta River Basins. For the Arda River Basin, reduction of BOD load around Kardzhali Town is required. • Based on polluter pay principle, reduction of catchment loads shall be shouldered by domestic, industry, livestock and the other sectors. • For reducing domestic loads plus industrial loads into sewerage system, new WWTPs and rehabilitation of the existing WWTPs are planned as the structural measures. • For reducing the industrial loads and the major livestock loads, strengthening of regulations are to be considered as the non-structural measures. • Based on the distribution of the catchment BOD loads and its loads from unit areas (load density), high priority zones are identified for reference. • Considering practical implementation by 2015 or 2021, the towns and settlements to be treated are selected based on the contribution for reducing the catchment BOD loads and the above zoning in principle. The target reduction of BOD loads by the high priority towns are provisionally to be set about 30%. Expert judgments are also introduced to select some additional high priority towns and settlements. • For the proposed new and to be renovated WWTPs, higher level of treatment for reducing nitrogen and phosphorous are included. • For the proposed high priority towns and settlements, improvement as well as expansion of the sewer networks are also proposed. • It is recommendable to consider how to reduce pollution loads from smaller settlements such as improvement of septic tanks to be sealed septic tank or individual treatment of houses or some small size WWTP etc. from the settlements which locate in the high priority zones. In case of improvement of septic tanks or individual treatment, their sludge should be taken out periodically and to be treated in the nearby WWTPs or brought to sanitary landfill sites for temporary solution. Financial support systems are necessary to be considered for

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the improvement of septic tanks and installing individual treatment facilities to the houses.

(2) High Priority Towns to be Treated in EABD

Considering the impacts to river basin in terms of reduction percentage of BOD Loads some other consideration to the impacts to the main rivers has been introduced. Figure 6.2.19 shows the selected high priority towns to be treated as well as the reference high priority zones. The selected high priority towns are shown in the table below. The sewer networks of these towns are also to be improved including renovation and expansion.

High Priority Towns (22 Towns) for Treatment in EABD Areas River Priority Town PE in 2015 WWTP Sewerage Remarks Basin I. New WWTPs in the Maritsa River Basin I-1 Asenovgrad Maritsa 78,054 New Improvement I-2 Plovdiv Maritsa 681,985 Existing Improvement Only SW improve. I-3 Karlovo Maritsa 37,181 New Improvement Under construction (only a part). Increase the budget is required. I-4 Velingrad Maritsa 28,752 New Improvement I-5 Peshtera Maritsa 28,691 New Improvement I-6 Harmanli Maritsa 28,538 New Improvement I-7 Svilengrad Maritsa 28,050 New Improvement I-8 Chirpan Maritsa 25,413 New Improvement I-9 Rakovski Maritsa 23,453 New New I-10 Panagyurishte Maritsa 23,029 New Improvement I-11 Parvomay Maritsa 22,200 New Improvement I-12 Stamboliyski Maritsa 18,068 New Improvement I-13 Kostenets Maritsa 11,048 New Improvement Most upstream town. II. New WWTPs in the Tundzha River Basin II-1 Yambol Tundzha 118,971 New Improvement II-2 Karnobat Tundzha 28,916 New Improvement II-3 Elhovo Tundzha 16,808 New Improvement II-4 Kalofer Tundzha 4,229 New Improvement Most upstream town. III. New WWTPs in the Arda River Basin III-1 Kardzhali Arda 67,346 New Improvement IV. Renovation of the Existing WWTPs IV-1 Nova Zagora Maritsa 36,185 Renovation Improvement IV-2 Radnevo Maritsa 20,691 Renovation Improvement IV-3 Ihtiman Maritsa 20,234 Renovation Improvement IV-4 Pavel banya Tundhza 4,407 Renovation Improvement

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(3) High Priority Towns to be Treated in WABD

In the same way as EABD, Figure 6.2.20 shows the selected high priority towns to be treated as well as the high priority zones for reference. The selected high priority towns are shown in the table below. The sewer networks of these towns are also to be improved including renovation and expansion.

High Priority Towns (9 Towns) for Treatment in WABD Areas River Priority Town PE in 2015 WWTP Sewerage Remarks Basin I. New WWTPs in the Struma River Basin I-1 Petrich Struma 45,020 New Improvement I-2 Sandanski Struma 40,358 New Improvement I-3 Simitli Struma 8,242 New Improvement II. New WWTPs in the Mesta River Basin II-1 Gotse Mesta 30,185 New Improvement Delchev II-2 Bansko Mesta 11,493 New Improvement III. New WWTPs in the Dospat River Basin III-1 Dospat Dospat 3,218 New Improvement Currently, only sewage from the town flow in the river. IV. Renovation of the Existing WWTPs IV-1 Pernik Struma 121,350 Renovation Improvement IV-2 Dupnitsa Struma 55,224 Renovation Improvement IV-3 Radomir Struma 21,621 Renovation Improvement

(4) High and Medium Priority Towns for EABD and WABD

In order to reduce pollution loads up to around 40%, high and medium priority towns are also studied. Figures 6.2.21 and 6.2.22 show the high and medium priority towns, where new WWTPs or renovation of the existing WWTPs as well as improvement or expansion or new sewer networks are to be constructed. As the numbers of the towns/settlements are total 56 in EABD, and 20 in WABD. Considering the realistic programme for constructing the proposed WWTPs, these numbers of the WWTPs may be too heavy for implementation by 2015 or by 2021. Therefore, these plans can be considered as reference for the future plans.

(5) Estimated Amount of Reduction Loss by Improvement of Sewer Networks

By improvement of the existing sewer networks, loss of pollutants from the sewer pipes to the ground will be reduced. This will improve the condition of pollution in the surrounding groundwater by the loss from the sewer pipes.

It is difficult to estimate the amount of groundwater, which is contaminated by the loss from the sewer pipes. However, supposing that the NH4 in sewer pipes (about 20 to 25

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Setting the target of loss from the sewer networks to be 10% in the future, Table 6.2.5 shows the estimated amount of reduction of groundwater contamination by the loss from sewer networks in the high priority towns. In this calculation, dilution is set at 10 times for conservative calculation. This table also shows the amount of newly treated sewage by the proposed plans for the high priority towns.

Estimated Amount of Reduction of Polluted Groundwater by Improvement of Sewer Networks Amount of polluted Reduction amount of Basin Amount of Sewage Loss groundwater by the sewage polluted groundwater by District (m3/year) loss improvement of sewer (m3/year) pipes (m3/year) EABD 32,282,000 322,820,000 290,538,000 WABD 13,833,000 138,331,000 124,498,000 Total 46,115,000 461,151,000 415,036,000

(6) Cost Estimation for the Proposed Structural Measures

(a) Construction Cost for WWTPs and Sewer Networks Data on the construction costs of recently completed WWTPs and under-constructed WWTPs are collected and analyzed. For the analysis, all the construction costs are converted to the current price level in the middle of 2007. Based on the analysis, Unit construction cost of WWTP by PE is estimated. The cost includes the normal secondary treatment for BOD as well as tertiary treatments for TN and TP load reduction facilities. Required length and cost of sewer pipes by PE is estimated. Table 6.2.6 shows the estimated rough construction costs (without VAT) for the new or rehabilitation of WWTPs and related improvements of sewer networks for the proposed high priority towns in EABD and WABD areas. Summary of the estimated costs is shown below:

Estimated Rough Construction Cost for the New and Renovation of WWTPs and Improvement of Sewer Networks in EABD and WABD Areas Basin WWTPs Sewer Networks Total District (in1000 euros) (in 1000 euros) (in 1000 euros) EABD 206,050 1,628,082 1,834,133 WABD 72,074 536,553 608,627 Total 278,124 2,164,635 2,442,760

(b) Operation and Maintenance Costs for WWTPs and Sewer Networks Operation and maintenance cost for WWTPs are estimated based on the annual rate of 7.5% to the direct construction cost. Operation and maintenance costs for sewer networks are estimated based on the annual rate of 1.5% to the direct construction cost.

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Table 6.2.7 shows the estimated operation and maintenance costs (without VAT) for the proposed WWTPs and sewer improvements for the high priority towns.

(7) Implementation Plan of the Structural Measures

For implementing the proposed WWTPs and improvement of sewer networks, following two scenarios are considered.

(a) Optimistic Scenario: All will be implemented from 2012 to the end of 2014

(b) Practical Scenario: Divided into first group and second group.

The first group will be implemented from 2012 to the end of 2014.

The second group will be implemented from 2018 to the end of 2020.

Figure 6.2.23 shows the tentative practical scenario. It can be modified based on updated information.

6.2.4 Non-Structural Measures of the Programme of Measures

(1) Cooperation with Municipality for Water Quality Management

The coverage area of each Basin Directorate is very wide, number of staff of each Basin Directorate, however, is very limited between 50 to 60 people. Even with the RIEW, number of the staff for monitoring and managing the water in the Basin District Area is very limited. It is thus physically rather difficult to monitor what is happening in the whole area of the Basin District in every moment. This will delay the actions for improving the situation. The following are proposed for the proper management. In order to conduct river basin management for the River Basins more properly and timely, it is highly recommendable to conduct monitoring for the important or problematic places such as the key monitoring stations in the river basins under cooperation from the municipality offices. Daily patrol with ocular observation is the basic way. Furthermore, it is better to conduct simple on-site measurement of water such as temperature, pH, turbidity, DO, EC and others. If any strange facts such as strange color, floating of many fish, abnormal values of pH, DO and others can be found by the daily patrol and simple measurement, it should be reported to the Basin Directorates for immediate actions including more detailed investigation, regulation to the polluters, etc. as well as warning to the people. Legislative arrangement is necessary to be made for realizing the cooperation with municipality offices for water management.

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(2) Strengthening of Regulation for Wastewater Discharge

(a) Monitoring of Industrial Wastewater discharged into Sewerage System

Wastewater discharge into the sewerage system from industries and other private sectors is controlled and managed by Water Supply and Sewerage Companies (WSSs), because WSSs have contracts with such industries under the current law. Furthermore, although the Basin Directorates issue permission for wastewater discharge into the rivers or water bodies from sewerage systems including discharge from urban or municipal WWTPs, the Basin Directorates have almost no information about the wastewater from the industries etc., which discharge into the sewerage systems. Due to this reason, it is very difficult to grasp the total view of the pollution loads in the river basin.

As the distribution pollution loads is one of the most important information for managing or improving water quality, it is very necessary to monitor the wastewater discharge from industries, etc. into the sewerage systems.

Therefore Water Act and related laws should be revised so that the Basin Directorates can collect information of the industrial wastewater, which is discharged into the sewerage systems.

(b) Treatment of Wastewater by Industries and Animal Breeding Farms by Themselves

Very often, industries discharge harmful substances such as petrol and heavy metals, which cannot be treated by urban or municipal WWTPs. It is necessary to strengthen regulation, so that industries and large animal breeding farms shall treat their wastewater by themselves. It is not recommendable to include industries into sewerage system, which discharge harmful substances or huge amount of wastewater. Furthermore, it should not be allowed that industries or large animal breeding farms to pay the fines many times, which are imposed to them in case of discharge untreated wastewater. If industries or large animal breeding farms do not improve the condition of discharging untreated wastewater by themselves such as installing wastewater treatment plants for industrial discharge or discharge from large animal breeding farms, Basin Directorates should not issue discharge permit to those industries or animal breeding farms.

(3) Strengthening of Individual Wastewater Treatment

Improvement of septic tanks to sealed type or to introduce individual treatment shall be promoted. Sludge should periodically be extracted and treated. Financial support system to people shall be necessary for the improvement.

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(4) Reduction in Pollution Load in Agricultural Area

Reduction of pollution load from the agricultural lands by changing farming methods and technology to reduce chemical fertilizer and pesticide will be introduced.

6.2.5 Improvement of Surface Monitoring System for Water Quality

(a) New Monitoring Programme for Surface Water

Based on the risk assessment of surface water bodies and groundwater bodies, MoEW and the Basin Directorates formulated a New Monitoring Programs in March 2007, which is composed of new programmes for surface water monitoring and groundwater monitoring. This sub-section proposes further improvement for the new programme for surface water monitoring.

In compliance with the requirements of the EU-WFD, the new programme for surface water monitoring includes surveillance monitoring (control monitoring) and operational monitoring. The surveillance monitoring will make overview the condition of the basin, give idea for efficient monitoring programme, and monitor long-term changes of the basin. The operational monitoring will monitor the status of the water bodies at risk, and assess the impact of the programme of measures. Figure 6.2.24 shows the locations of the surveillance and operational monitoring points.

The surveillance monitoring and the operational monitoring will monitor surface water quality in terms of hydro-biological indicators and physico-chemical parameters. Hydro-biological indicators to be monitored are Phytoplankton, Macrophytes, Phytobenthos, Macrozo benthos / Bottom invertebrate, Fishes and others. Physico-chemical parameters to be monitored are 1st Group (common parameters such as pH, temperature, DO, BOD5, COD, NH4-N, NO2-N, NO3-N, and PO4-P etc.), 2nd Group (TN, TP, Ca, Mg, hardness etc.), the Group of Priority substances (33 parameters), and the Group of Specific polluters (organic substances and heavy metals). Number of parameters to be monitored and frequency of monitoring differs for the monitoring stations. The number of the monitoring points is shown in the table below.

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Number of the New Surveillance (Control) Monitoring Points for Surface Water Basin Directorate River Lake Coastal Water DRBD 92 41 - BSBD 26 12 7 EABD 27 5 - WABD 33 16 - Sub-Total 178 74 7 Total 259

Number of the New Operational Monitoring Points for Surface Water Basin Directorate River Lake Coastal Water DRBD 55 - - BSBD 32 16 6 EABD 58 4 - WABD 80 12 - Sub-Total 225 32 6 Total 263

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(b) Proposals for Improvement

(i) Setting Key Monitoring Stations to Ensure Stable Monitoring

Total number of the monitoring points of the New Surface Water Monitoring Programme in the country is 522 points, which is slightly more than the number of the points of the existing surface water monitoring of ExEA. However, the parameters to be monitored are very much increased and their frequency for monitoring is also rather high (ex. 12 times per year for the priority substances for surveillance monitoring for one year at least). Furthermore, Bulgaria has no enough experience for measuring many items of the priority substances.

Considering this situation, it is recommendable to set Key Monitoring Stations as well as Important Monitoring Stations among the surveillance monitoring points to ensure stable monitoring and to overview the water quality conditions of the river basins. Furthermore, at these Key stations, it is necessary to measure the water quantity as well. In order to conduct this kind of permanent monitoring at the Key Monitoring Stations, the Basin Directorates are necessary to establish their own monitoring stations both for water quality and water quantity. Figure 6.2.25 shows the proposed Key Monitoring Zones as well as Important Monitoring Zones in EABD and WABD by the Study, where the Key Monitoring Stations and Important Monitoring Stations are recommendable to be set within these zones.

Proposed Key Monitoring Zones and Important Monitoring Zones in EABD and WABD Key/Important Monitoring EABD WABD Monitoring Zones Daily ocular observation and Key Monitoring Zone 12 places 7 places simple on-site measurement. Monthly sampling and analysis. Weekly ocular observation and Important Monitoring Zone 10 places 4 places simple on-site measurement. Monthly sampling and analysis. Total 22 places 11 places

If Key Monitoring Zones and Important Monitoring Zones will be set in DRBD and BSBD area as well, order of the Key Monitoring Zones in the country will be around 50 places and Important Monitoring Zones will be around 25 places.

It is recommendable to start monitoring in the above Key and Important Monitoring Zones under cooperation from some of the municipalities as the pilot cases, and will be extended to all over the Basin District Areas.

Furthermore, the results of the monitoring at the Key Monitoring Zones and Important Monitoring Zones will be reported to EU instead of above 259 surveillance stations.

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(ii) Capacity Building and Stage-wise Implementation of the New Monitoring Programme

The new monitoring programme for surface water includes several hydro-bilogical indicators. As the existing hydro-biological monitoring is mainly based on the macrozo benthos / bottom invertebrate, there are not so much experience and experts for other indicators. Furthermore, the new monitoring programme requires for measuring many priority substances, which are also new for Bulgaria.

Therefore, it is necessary to consider the way of developing human resources to conduct these measurements, and consider stage-wise implementation of the new monitoring programme, so that all of the required indicators and parameters by EU-WFD can be measured properly with sufficient accuracy.

(iii) Quality Control Programme to be formulated and implemented

In terms of physico-chemical measurement, the existing data such as BOD5, CODMn, and heavy metals seem to be unreliable in many cases. Therefore, it is very necessary to formulate quality control programme for sampling and laboratory analysis. As many priority substances are required to be measured, quality control is also important. It is recommendable to include followings in the quality control programme. • Central laboratory in ExEA shall formulate quality control teams with qualified experts. • In order to check the quality of the sampling and analysis by different laboratories, conduct inter-calibrations (analyze the same sample by different laboratories at the same time). In this case, the central laboratory (ExEA) should coordinate the checking activity. • Send samples to the reliable laboratories of other countries and compare the test results made by the laboratories in Bulgaria (heavy metals and priority substances, etc.) • The quality control team of the central laboratory shall periodically go around the regional laboratories in the country for checking the results of analysis, and make guidance and training to the staff of the regional laboratories.

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6.3 Water Quantity Management Plan

6.3.1 Programme of Measures for Water Supply Improvement

(1) Direction of Structural Measures

Direction of structural measures is the improvement of water supply pipes to reduce water loss, mainly for asbestos cement and steel pipes.

(2) Necessary Length of Pipes to be improved in Bulgaria and Rough Cost Estimation

The existing asbestos cement pipes and the steel pipes are necessary to be replaced for reducing the loss of water from the pipes. For a reference, Table 6.3.1 shows the necessary length of pipes to be replaced together with rough cost estimation for all over Bulgaria. To estimate the cost, information of length of pipes with their composition of pipe diameter for different population size of towns were collected and analyzed. Based on this analysis and unit price of pipe, unit construction cost for water supply pipes are estimated, and applied for estimating the construction cost.

(3) Necessary Length of Pipes to be improved for Some Sample Municipalities in EABD and WABD and Rough Cost Estimation

In order to study feasibility for improving water supply pipe networks, based on the limited answers to the questionnaire to WSSs in EABD and WABD to JICA Study Team by August 2007, some sample municipalities are selected for further analysis. They are Haskovo, Yambol and Kardhali in EABD and Kyustendil in WABD.

The following table shows the estimated cost for the improvement of the water supply pipes in these 4 municipalities. Total estimated cost of improvement for these municipalities will be 325.84 million euros.

Economic feasibility has finally been conducted for each WSS as presented in Table 6.3.1 applying the same rule for the benefit calculation as shown in the next page as “Water Loss Reduction by the Improvement of Water Supply Networks of 4 Sample Municipalities”.

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Improvement of Water Supply Networks of 4 Sample Municipalities

Existing Pipes for Water Supply Related Served Informat. Asbestos PVC + No. Municipality WSS Co. Owner Basin populat. by Steel Cast iron Other Total length Necessary cement HDPE District WS Improve. (m) (m) (m) (m) (m) (m) (m) 1 Haskovo Haskovo State EABD 98,697 461,171 156,429 627 3,702 621,929 12,610 2 Yambol Yambol State EABD 79,235 136,745 59,450 5,962 12,246 214,403 State & 3 Kardzhali Kardzhali Municp. EABD 64,847 231,858 24,786 0 21,301 22,549 300,494 166,000 State & 4 Kyustendil Kyustendil Municp. WABD 66,298 669,409 172,903 12,212 19,553 113,074 987,151 Total 309,077 1,499,183 413,568 12,212 47,443 151,571 2,123,977

Estimated Necessary Improvement of WS Pipes Replace-ment Related Engineering Administratio Physical Length of No. Municipality WSS Co. Owner Basin Unit Cost Direct Cost (A) Cost (5% of n Cost (5 % Contingency Total Cost Pipe District A) of A) (10% of A) (AS+ST) (m) (EUR / m) (EUR) (EUR) (EUR) (EUR) (EUR) 1 Haskovo Haskovo State EABD 617,600 160 98,816,000 4,940,800 4,940,800 9,881,600 118,579,200 2 Yambol Yambol State EABD 196,195 160 31,391,200 1,569,560 1,569,560 3,139,120 37,669,440 State & 3 Kardzhali Kardzhali Municp. EABD 256,644 150 38,542,437 1,927,122 1,927,122 3,854,244 46,250,924 State & 4 Kyustendil Kyustendil Municp. WABD 842,312 151 127,474,993 6,373,750 6,373,750 12,747,499 152,969,991 Total 1,912,751 622 296,224,629 14,811,231 14,811,231 29,622,463 355,469,555

Note: Estimated cost is without VAT.

Data Source: 1) Answer to the questionnaires to the WSS Companies in EABD and WABD areas by the end of August 2007, which have been received by this Study. The following table shows possible reduction of water supply loss by the above improvement. In this calculation, per-capita water consumption is supposed to be 220 l/day/person in the future condition. By the improvement, about 22 million m3 per year of water can be saved in these 4 municipalities.

Water Loss Reduction by the Improvement of Water Supply Networks of 4 Sample Municipalities

Necessary Necessary Remarks Supplied Supplied Difference of Related Served Water with Water with Water Demand Necessary Current No. Municipality WSS Co. Owner Basin populat. by current improved Supplied Water Supplied Water District WS physical loss physical loss (50%) (10%) (m3/day) (m3/year) (m3/year) (m3/year) (m3/year) (m3/year) 1 Haskovo Haskovo State EABD 98,697 21,713 7,925,369 15,850,738 8,805,966 7,044,773 10,320,000 2 Yambol Yambol State EABD 79,235 17,432 6,362,571 12,725,141 7,069,523 5,655,618 14,432,000 State & 3 Kardzhali Kardzhali Municp. EABD 64,847 14,266 5,207,214 10,414,428 5,785,793 4,628,635 5,148,000 State & 4 Kyustendil Kyustendil Municp. WABD 66,298 14,586 5,323,729 10,647,459 5,915,255 4,732,204 2,062,000 Total 309,077 67,997 24,818,883 49,637,766 27,576,537 22,061,229 31,962,000 Note1) Per-capita water demand in the future is supposed to be 220 l/day. 2) Served population by watter supply in 2015 is supposed to be same as the current served population.

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6.3.2 Programme of Measures for Irrigation Facility Improvement

(1) Introduction

The agricultural lands cover about a half of the country and the agriculture is one of the fundamental sectors in the country. The stability of agricultural production will be the basis for sustainable development of the rural areas. The irrigation facilities are basic infrastructure for stable agricultural production. The country had developed about 1.2 million ha during the old order by 1980s, however, currently the potential irrigation area is about 500,000 ha, of which irrigation systems are owned by the government and managed by Irrigation Systems Co. (IS).

In 1980s the irrigation area covered over 1.0 million ha and used water resources, as much as 3.5 billion m³/year, but in the new order, the agricultural sectors has not rebuilt yet. The current utilized irrigation areas are estimated at a level of 20,000 ha to 30,000 ha with the water at 100 to 200 million m³/year.

The irrigation systems and facilities are deteriorated and reported having large water losses over 60-70% because of poor maintenance. The existing irrigation systems were designed only for the original scale of irrigation, but not for small scale or controlled irrigation. The current water loss is by far larger than the reported volume. The irrigation area and water are supposed to be increased in future and the existing irrigation systems should be improved in order to provide irrigation water properly to the demand areas and to reduce the loss in the system.

(2) Direction of Improvement

(a) Structural Measures

Improvement of irrigation facilities aims to provide irrigation area with the optimum water volume and to make efficient water use including reduction of water loss.

Basic concepts for improvement are as follows: • The existing irrigation systems are deteriorated with high water loss over 60-70%, and need rehabilitation in order to utilize the systems. • Although real water consumption is small, water abstraction seems by far larger due to water loss and poor intake facilities and distribution facilities (gate and canal). • It will be necessary for the region to renovate the irrigation system considering the efficient water use based on the current and future demands of irrigation water. • Irrigation improvement will be one of the key improvements for sustainable water use and also for the sustainable development of agriculture and regional development based on the efficient water abstraction and use.

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(b) Non-structural measures

For water quantity management and improvement purposes necessary measures are as follows: • To review and improve the current water use permissions to conduct optimum water intake and use, and also the water transfer to the other river basins, • To conduct monitoring the volume at water intakes by installing measurement devices by water users for intake sides as well as Basin Directorate at key locations in the rivers, • To improve the quality of data required for water quantity management, including collaboration with National Institute for Meteorology and Hydrology (NIMH) as well as other relevant institutes, and • To establish a system for a good coordination among RBDs, MoAF and related municipalities for implementation of the proposed project.

(3) Objectives for Irrigation Water Improvement

The objectives for irrigation water improvement are: • to use water resources efficiently, and • to supply irrigation water in response to the demand by improving irrigation facilities and reducing a high level of loss in the irrigation systems.

(4) Management Organization

Irrigation System Co. (IS), which is 100% owned by the MoAF manages all the state owned facilities (water reservoirs, canals, pumping stations and compensating basins). The company has 21 regional branches, of which 12 branches are located in EABD/WABD. They are as follows: • EABD: Sliven, Yambol, Stara Zagora, Haskovo, Plovdiv, Pazardijik, Sofia. • WABD: Pernik, Dupnitsa, Gotse delchev and Sandanski.

The location of each irrigation branch is shown in Figures 6.3.1 and 6.3.2. The irrigation branches and proposed improvement area are 316,468.6 ha in EABD and 50,738.3 ha in WABD as shown in the following tables.

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Irrigation Branches and Potential Areas in EABD Irrigation Potential area Area fit for irrigation Number of Branch (ha) (ha) Irrigation systems 1 Burgas 3,246.7 2,863.4 2 2 Haskovo 48,338.6 29,154.2 47 3 Pazardzhik 57,799.0 26,181.3 6 4 Plovdiv 106,116.3 72,041.0 15 5 Sliven 33,116.8 25,698.3 1 6 Sofia 3,901.3 3,901.3 1 7 Stara Zagora 38,515.6 36,004.7 6 8 Yambol 25,434.3 23,197.2 4 Sub total 316,468.6 219,041.4 82

Irrigation Branches and Potential Areas in WABD Irrigation Potential area Area fit for irrigation Number of Branch (ha) (ha) Irrigation systems 1 Dupnitsa 13,581.7 11,487.0 6 2 Gotse Delcev 8,201.0 5,950.8 3 3 Pernik 14,864.6 13,258.1 23 4 Sandanski 14,091.0 12,780.8 9 Sub Total 50,738.3 43,476.7 41

Some of the former state and cooperative property are managed and maintained by the established 74 Irrigation Associations registered in Bulgaria, 32 associations are located in WABD/EABD

The overall coordination and supervision of the management and maintenance is carried out by the Executive Agency of Irrigation and Drainage of the Ministry of Agriculture and Forestry. This agency carries out all activities related to planning, management and control of the irrigation and drainage systems throughout the country.

(5) Improvement of Existing Irrigation Systems in EABD and WABD

The existing systems are required to be improved with their facilities including construction of new intake structures, rehabilitation of intake structures, distribution structures, etc. The detailed data of facilities for improvement, the cost estimation are shown in Tables 6.3.2 and 6.3.3. The total costs estimated for the improvement are shown as follows: EABD • A total of 8 irrigation branches composed of 82 irrigation systems with total irrigation area at 316,468.6 ha • Total project cost: 230.7 million euros

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WABD • A total of 4 irrigation branches composed of 41 irrigation systems with total irrigation area at 50,738.3 ha • Total project cost: 42.0 million euros It should be noted that the total costs shown here are composed of construction cost, administration cost (5% of construction cost), engineering service cost (10% of construction cost) and physical contingency cost (10% of construction cost).

(6) Priority Irrigation System for Improvement

The irrigation systems are classified into three groups considering the assumed improvement of water use efficiency and also expected development effects, and the first group is selected as the priority group for early implementation. The priority irrigation systems are listed as follows:

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First Group for Implementation

EABD: A total of 2 irrigation branches composed of 5 irrigation systems with total irrigation areas at 94,948.0 ha. EABD Irrigation Branch Irrigation System Topolnitsa 1. Provdiv Stryama-Chirpan Topolnitsa 2. Pazardzhik Aleko pazardzhik Karabunar WABD: A total of 4 irrigation branches composed of 22 irrigation systems with total irrigation areas at 17,730.6 ha. WABD Irrigation Branch Irrigation System 1. Pernik Kjustendil composed of 18 small systems Sandanska Bistritsa 2. Sandanski Mendovo-Karvrakirovo Strumeshnitsa 3. Gotse Delcev Gotse Delchev

Total construction cost of the priority group is as follows: EABD: 84 million euros WABD: 20 million euros

The total costs shown here are also composed of construction cost, administration cost (5% of construction cost), engineering service cost (10% of construction cost) and physical contingency cost (10% of construction cost).

Second Group for Implementation

EABD: A total of 5 branches composed of 7 irrigation systems with total irrigation areas at 106,030.0 ha

WABD: A total of 1 branch composed of 10 irrigation systems with total irrigation areas at 20,237.1 ha.

Total project costs:

EABD: 83.2 million euros

WABD: 14.4 million euros

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Third Group for Implementation

EABD: A total of 8 irrigation branches composed of 70 irrigation systems with total irrigation areas at 115,490.6 ha.

WABD: A total of 4 branches composed of 9 irrigation systems with total irrigation areas at 12,770.6 ha.

Total project cost:

EABD: 63.1 million euros

WABD: 7.2 million euros

Implementation plan of the improvement measure for implementing the proposed improvement of irrigation systems the implementation plan are as follows:

Implementing agency: • Leading implementing agency shall be MoAF, and cooperating organizations shall be composed of RBD and the related municipalities, considering effective water use and sustainable regional development. • In order to improve the irrigation systems for promoting the sustainable regional development it is necessary for the implementing agency to conduct the study on required extension services and marketing systems for the region and also the analysis on the role of the reservoirs in the annual water use.

Implementation: • First group shall be improved in structural measures as a pilot project by 2015 and activities for water management and regional development shall be started. • Second and Third groups shall be prepared for the implementation by 2015 and improved in structural measures by 2021 and activities for water management and regional development shall be started.

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6.4 Preliminary Programme of Measures for Groundwater Management (Directions)

6.4.1 Introduction

In this sub-section, preliminary programme of measures for groundwater management is proposed in the sense of directions for improvement and management of the groundwater. Furthermore, some recommendations are also presented for the New Monitoring Plan for groundwater, which was formulated by MoEW and the RBDs in March 2007.

6.4.2 Directions for Groundwater Management (Some Recommendations)

(1) General Recommendations

Some general problems exist that hamper real work: • The inter-institutional interaction and cooperation are not sufficient and efficient in some cases. This hampers effective work in the domain of the environment protection. • Access to data is rather difficult and costly (e.g. the geological record office “Geofond” at MoEW). • Young people are low motivated to be employed in Laboratories and Institutes. Maybe the only positive example of free data access in Internet is “General Master Plans for Utilization of the Water Resources in Bulgaria”, 2000 available in web-page (http://www.bluelink.net/water/) prepared jointly by NGO “ECOSOUTHWEST” with assistance of MoEW and Institute of Water Problems at Bulgarian Academy of Sciences. Public accessibility of data was realized thanks to assistance of the Bluelink electronic network.

(a) General Recommendations To improve inter-institutional interaction and cooperation, to ameliorate data exchange, to set information networks where appropriate. To make easier access to available reports, data, publications, etc. This will facilitate competence development of the staff in RBDs, institutes, universities and private companies, and contribute to timely solving of pressing problems. To find ways for motivation of personnel and attracting of young people in RBDs. To find forms for proper education of young staff in RBDs – balance between Bulgarian traditions and new European practice. Involvement of retired specialists in some activities is desirable under appropriate form. Special attention should be paid to protect groundwater resources, control the protection of water supply wells and to work on abandonment for unused wells. Abandoned mine sites inventory and cleanup programme for investigation and remediation are necessary.

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(b) Recommendations related to Providing Data for GW Models

Different groundwater related problems might arise, both regional and local.

Groundwater modeling is a powerful tool for solving a variety of groundwater problems concerning groundwater flow, resources and contamination. Data acquisition is important in initial phase for preceding modelling.

Before the proper application, the model should be calibrated. Different data are necessary both for calibration of the model and for forecasts based on GW modeling: • Right GW abstraction volume for water supply wells, including its variability, • Data on GWL drawdown both in observational and water supply wells, • GWL in monitoring stations expressed in altitudes a.s.l. Exact altitude of the measuring (reference) point is necessary, • Water stage in rivers (expressed in altitudes a.s.l.), • Spring discharge (if applicable), along with its inherent variability, • River discharge, especially during low flows, and • GW quality parameters.

To expedite preparatory work for the model, many data should be obtained. Data that are not registered on time are lost, and hence correct and comprehensive documentation are necessary.

In general, good documentation concerning different groundwater use aspects is necessary. If possible, different databases should be made.

(2) Specific Recommendations for EABD Main ore mining sites are concentrated in EABD. There are old tailings that present threat to ecological safety. Database and GIS-map of old pollutions, especially tailings, is necessary. Abandoned mine sites inventory and cleanup programme for remediation are especially important for EABD. There are cases of low quality rehabilitation of mining areas. An appropriate cleanup programme will improve water quality and enhance public safety. The problem with arsenic in drinking waters in Poibrene village is not yet solved. It is situated downstream from mining area; pollution from old tailing may occur from that point. It is a hot spot problem and necessary to assist the WSS in solving this problem. To apply good agricultural practices to reduce nitrate content in the region of Stara Zagora. To plan regional model of the groundwater flow in the region of Yambol-Elhovo area.

(3) Specific Recommendations for WABD To pay special attention to quantitative monitoring of Blagoevgrad GWB – “At risk”. JICA CTI Engineering International Co., Ltd. 6-31

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Groundwater research and modeling should be planned to re-assess groundwater resources of this groundwater body. To use existing data on chemical composition from reports (for assessment of specific natural GW quality in mountain regions impacted by ore mineralization – for reference) – for the Upper Struma region. Establishment of database is necessary. To control carefully groundwater abstractions in the region of the winter resort Bansko.

6.4.3 Some Recommendations for the New Monitoring Plan

(1) New Groundwater Monitoring Plans for River Basin Managements

The New Groundwater Monitoring Plans for River Basin Managements have been developed in implementation of the requirements of the WFD. The number of monitoring sites to be reported in EU is presented in the Table for different River Basins.

Number of Monitoring Sites from the New Monitoring Programmes Monitoring EABD WABD Danube BD BSBD network Surveillance 38 33 49 66 Operational 12 - 21 37 Quantitative 41 34 86 63

Quantitative network is planned most usually with frequency of four, sometimes 12 times per year, and encompasses monitoring of the next parameters: • Groundwater levels in boreholes or wells, • Spring flows, and • Discharge from artesian wells and drains.

There are cases of multiple uses of monitoring sites for different networks.

Operational monitoring is planned for all groundwater bodies “At risk” along with groundwater bodies “At risk” with low confidence in the risk assessment, for which additional information is necessary (see table below).

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GWBs at Risk and Operational Monitoring Number of GWBs EABD WABD Danube BD BSBD ‘At risk’ 4 - 21 3 ‘At risk’ with low confidence in 3 - - 7 the risk assessment Total ‘At risk’ 7 - 21 10 With operational monitoring 7 - 21 10 planned No groundwater bodies “At risk” have been identified in WABD. On the one hand, there are only sparse monitoring data about pollutants in groundwater, and the pressure is lower compared to the other river basins. As a result, no operational monitoring has been planned up to now in WABD.

RBDs report almost total coverage of GWBs with GW monitoring networks. Because of their importance for national or regional development, large regional groundwater systems have received a higher priority than local-scale systems. Networks do not cover only GWBs with local importance and low pressure. They are usually difficult of access and with low population density.

New Groundwater Monitoring Plans are presented on Figures 6.4.1 and 6.4.2.

The proposed monitoring frequencies for surveillance monitoring are usually four times yearly for the basic physico-chemical indicators, and rarely for specific pollutants. This monitoring has an intention to conduct only one year within the operation of the River Basin Plan. For operational monitoring, they are usually one to four times yearly for the specific indicators, which present a real threat. Many of sampling points from surveillance and operative monitoring refer to the groundwater for drinking purpose.

(2) Recommendations for Improvement of the Groundwater Monitoring

(a) Evaluation of the Proposed New Monitoring Programmes

The proposed groundwater monitoring programmes by EABD and WABD are very ambitious. Its overview shows some weaknesses and obstacles, some of them are foreseen by the RBDs. The difficulties marked by RBDs are as follows: • Possible cooperation with NIMH and WSSs has no legal basis – no agreements signed between MoEW and NIMH and WSSs. • Laboratories have low human resource to respond to increasing tasks due to insufficient staff. Several vacancies are in laboratories in Blagoevgrad and Sofia.

In our opinion, additional problems are: • Technical infrastructure for GW quantity measurements is lacking, • Need for trained technical staff, and • Need of hydrogeological work that requires involvement of experienced staff.

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The staff of the RBDs has made preliminary agreement of the owners of private wells concerning access for the monitoring purposes. Later clear arrangements should be made with them.

At present, the proposed groundwater monitoring programmes do not fully correspond to the existing capacity of RBDs. Here general recommendations are presented, which are related to the improvement of GW monitoring.

(b) General Recommendations • RBDs are institutions engaged in GW monitoring. To fulfill this task, capacity building is the most important prerequisite. Monitoring requires knowledge and experience. There is a need of experienced hydrogeologists, dealing with groundwater issues, involved in planning and implementation of GW monitoring. On the other hand, technical staff is necessary, which should be well trained. • Analysis of institutional setting is necessary. RBDs are institutions having the responsibility and mandates for groundwater monitoring. Possible involvement of other institutions (NIMH, WSSs or other) through delegated tasks to them should be considered. Roles and administrative responsibilities should be cleared. • To furnish GW monitoring handbook (for quantitative monitoring) that documents procedures, which must be followed to ensure good quality and integrity of the data collected.

(c) Some Practical Recommendations • Gradual growth of the monitoring network from low profile to the right level of groundwater monitoring, always adjusted to the needs. • To begin with small number of points. • To carefully plan tasks. • To provide for high standard and full documentation concerning implementation of the monitoring programme.

Important aspects of GW monitoring are presented below. Groundwater monitoring programmes should be developed based on inventory of data needs and specification of the objectives. Here some of the possible objectives are presented: • Characterization of the groundwater system(s), • Identification of possible trends in relation to groundwater use, • Estimation of the potential for further groundwater development, • Provision of historical and reference values for detailed investigations, • Meeting the requirements of the WFD, and • Early warning system for GW related problems.

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GW monitoring programmes have been developed taking into account specific data needs and are based on conceptual model for HG systems. The data needs are often related to possible or identified GW related problems. Evidently, additional work is necessary. • Need of additional preparatory work • List of (main) stakeholders. • Inventory of data needs - what data for what needs, for what stakeholders. • To set priorities of data needs. • To set priorities of monitoring points. • Inventory of available wells with compiled fact sheets (information passports/sheets). • Need of thorough hydrogeological work • Preparation of conceptual model for HG systems. To a large extent, the conceptual model represents a statement by the professional hydrogeologist on how the groundwater system being studied “works”. • Analysis of the available data for GW quantity and quality. • Synthetic representation of the above mentioned aspects (maps, cross-sections, tables, graphs, problem statement). • Preparation of options for GW monitoring. Good practice says that groundwater monitoring programmes should be adopted based on considering and weighting different options.

This work may be done in parallel with implementation of the first stage of the monitoring programme.

(d) Recommendations for Three Specific Cases • For unconfined aquifers that are subject to diffuse pollution from the land surface, a reference monitoring point should exist within non-impacted zones (i.e. forests, protected areas) for comparative assessments. • To prioritize the monitoring points, it is worthwhile to assess whether the measured value is a limiting factor for GW management or not. • For alluvial aquifers along rivers, GW levels are usually close to the water stage in the river. In this case, an option of complex monitoring including surface and GW has to be considered. High accuracy of topographic measurements is necessary.

Documentation of groundwater monitoring is an important aspect. Examples of standard forms may be found in Annex E (Guideline, 2006), and are enumerated below. A proper monitoring programme should encompass:

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• A monitoring handbook that documents procedures which must be followed to ensure good quality and integrity of the data collected, • A monitoring station file of each well that contains all important information, and • A field report form sheet that must be filled out upon arrival at the site and contains all relevant information about the fieldwork conducted.

(e) Conclusion

Establishing of appropriate GW monitoring network is a gradual and iterative process. Good idea is to apply a phased start of the GW monitoring programme. Such approach will allow for more gradual investments and means prioritizing monitoring efforts.

Our proposal is to prepare GW monitoring programme for the period up to 1.VII.2008, and to continue work for the next period. Much preparatory work should be done to propose a good and feasible monitoring programme.

The design of GW monitoring starts with defining of objectives. In our opinion, the main objective should be: “Groundwater monitoring integrated in water resources management and environmental protection”. That is why it is important to know specific data needs. State of the art presumes the design of the GW monitoring network to be based on conceptual model of the hydrogeological system. On the other hand, the monitoring programme has to be feasible. Different examples of approaches used in designing GW monitoring in Europe may be useful.

(f) General Recommendation for the New Groundwater Monitoring Plan • To prioritise monitoring efforts based on specific data needs. • To reconsider feasibility of the plans. • To revise fact sheets of sites in respect of their long-term use in the networks. • To reconsider involvement of other institutions through delegated tasks to them.

(g) Some Recommendations for the New Groundwater Monitoring Plans of EABD and WABD: • To reconsider the new plan for quantitative monitoring – who will measure and data flow. • To pay special attention to quantitative monitoring of Blagoevgrad GWB - “At risk”. • To use existing data on chemical composition from reports (for assessment of specific natural GW quality in mountain regions impacted by ore mineralization – for reference) – for Upper Struma region, for example. • Special attention to the region of the winter resort Bansko (WABD) and related impacts. 6-36 JICA CTI Engineering International Co., Ltd.

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6.5 River Management

6.5.1 Introduction

There are non-pollution pressures such as water abstraction, water flow regulation and morphological changes have a major impact on water body quality. These pressures are often caused by improper human activities, and should be reduced by the proper river management. Also there are pressures from flood disasters, of which pressures and impacts should be assessed and preventive measures should be prepared in order to reduce the risks of flood disasters.

As for the river management, there are many agencies and organizations along the river and they have been conducting the management activities ad hoc manners within their responsibilities and authorities, without considering about the effects to the upper and lower reaches from river engineering aspects.

In the country the river course is owned partly by the government and partly by municipalities, MoAF and others including private sectors. Accordingly the responsibility and authority for management of the river reach and river facilities are divided into many segments and facilities due to their ownerships of them. Figure 6.5.1 shows the ownership and maintenance responsibility of dykes in Bulgaria. The River Basin Directorates are difficult to control the improper activities along rivers to reduce the adverse impacts because of their lacking responsibilities and authorities in managing the river course and morphology. Improvement of river management is to strengthen the RBD to conduct a better management of the river basin. For river basin management purposes it is necessary for the RBD to be a dominant managing agency for the river basin from technical aspects.

6.5.2 River Morphology Management

In the study area the river morphology is the product of water use and the other economic activities. The rivers are not so intensively used, though there are dams for power generation, intakes for irrigations and dikes for flood protection. However, major problems caused by human activities are the intensive and extensive sand and gravel extractions in and along rivers, which are affecting the river courses and river flows, by causing instability of river courses and eroding of river beds and banks, also scoring the foundation of structures and flood dykes.

There are identified many improper activities as well as the sand and gravel extraction activities, development works and solid waste dumping into rivers. In order to reduce pressures and impacts caused by human activities, the direction of required programme of measures for river management is proposed as follows: • To regulate sand/gravel extraction more strictly, so that the river channel and surrounding flood plain areas have not unstable conditions, • To control any illegal activities or improper activities along the river, including solid waste dumping and land development,

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• To conduct a study on “ River Maintenance Plan for Floods Control and Sediment Yield ” for the basis of prevention of flood damages and control sand and gravel extraction, and • To conduct study on pressures and impacts caused by priority substances, heavy metals and closed mines to protect people from the possible hazard caused by toxic materials.

6.5.3 Floods and Prevention Measures

(1) Responsible Organization

The new European Flood Directive 2007/60/EC on the assessment and management of the flood risk has been in force from November 2007 for all members of the EU.

The government enacted legislation “Disaster Protection Act” against natural disasters in response to the critical situation caused by the floods of 2005, and created “the Ministry of State Policy for Disasters and Accidents (MoSPDA).

The Minister develops, coordinates, and supervises the implementation of the state policy for prevention of disasters and accidents, and also the Minister manages the implementation of the state policy of taking control of and recovering from the impact of disasters and accidents.

As for the emergency measures MoSPDA as the successor of the Civil Defense shall organize and discharge on the basis of regional plans for performance of rescue and emergency repair and recovery works. Ministries, district governor’s offices, Municipalities and Basin Directorates have already had their emergency units for emergency responses. However, preventive measures should be prepared urgently.

(2) Direction of Required Measures

Preparedness against floods is very important to reduce damages caused by floods. The prevention measures are also composed of structural and non-structural measures. There is numerous flood protection dykes constructed by MoAF and municipalities etc., but still no flood warning system has not established yet, though some international studies are on going in EABD.

For establish flood warning systems directions of the required measures to be conducted are as follows: • It is necessary for MoEW, EABD and WABD to conduct a basic technical study for formulation of flood disaster prevention plan as the river basin managing organization. • It is necessary for MoEW, EABD and WABD to conduct technical assist to MoSPDA and municipalities to protect people in flood hazard areas from flood damages. • Based on the basic study it is necessary for EABD and WABD to install automatic rainfall stations and river stages required for implementation of the flood prevention plans. In establishment of observation networks it is better to collaborate with NIMH. 6-38 JICA CTI Engineering International Co., Ltd.

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• Based on the basic study it is necessary for MoEW, EABD and WABD to assess the existing flood protection facilities and to prepare improvement plan of them.

(3) Prevention Measures against Floods

For disaster prevention measures it is necessary for EABD and WABD to conduct: • To establish warning systems for floods and incidental pollutions, and • To assess the existing flood prevention facilities and conduct remedial works if necessary. There are many existing flood prevention dykes required remedial works.

For formulation of flood warning systems basic information is as follows: • Identification of flood areas in the past, • Preparation of flood maps based on the past flood events, • Analysis of the hydrological data, which caused floods in the past, • Assumption of possible flood areas by the design flood events, • Establishment of flood warning system composed of observation systems and information system among related organizations, municipalities and communities, EABD, WABD, MoEW and MoSPDA, and • Enhancement of public awareness for disasters caused by flood events.

(4) Measure against Incidental Pollution

There may be various possible risk areas from incidental pollution. As well as for floods an early warning for risk areas of incidental (or accidental) pollution is required. For formulation of warning system basic measures required are as follows: • Identification of possible risks caused by incidental pollutions, • Identification of risk areas from incidental pollution, • Assessment of risk areas caused by incidental pollution sources, including tailing dams, mining, industry etc, • Analysis of the incidental pollution events, which caused incidental pollutions in the past, and • Establishment of an early warning system composed of observation or inspection systems and information system among communities, municipalities, RBDs, MoEW and MoSPDA.

6.5.4 Future Studies Related to the River Basin Management to be conducted

It is recommended that the RBD conduct further basic studies for the river basin management as follows: The study on “River Management Plan” for the basis for prevention of flood damages and controlling sand and gravel extraction as well as improvement of environmental

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status, including river structures like dykes, weirs and fish passages, of water bodies from the view point of river morphology. • The study on pressures and impacts from discharges or priority substances, which are 33 harmful substances defined by the EU-WFD, and heavy metals, and also closed mines in the basin necessary to protect people from possible hazard caused by discharge of toxic substances. In addition, the present study is of the viewpoint of basin management, thus water resources development aspect has not been included. Furthermore, the data related to water resources used in the present study is limited due to constraints on availability of the data. It is also recommended that the study shall be conducted on water resources development and river flow regulation, which include the following items: • The detailed and/or localized regime of the river flow, including the more detailed and/or localized water transfer, water use, and environmental flow. • The detailed assessment of the needs of additional hydro-technical facilities to be constructed as well as the restarting of construction of the suspended ones to regulate water flow for more efficient use of water resources, as a part of the integrated water management in Bulgaria and to meet the challenges of global climate change.

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6.6 Result of Water Quantity Simulation

6.6.1 Water Resources Potential

In Bulgaria, almost all of the observed water quantities at hydrometric stations are under disturbed condition. The measured disturbed water quantities have been traditionally used for the statistical analysis for estimating available water resources with different probability, although it may be difficult to know quasi-natural water resources.

In the present study, probable water quantities are estimated based on the calibrated rainfall-runoff model. Firstly, quasi-natural water quantities are estimated under the precipitation with different probability. Secondly, by assuming the reservoir operation pattern, potential flows under influence of significant reservoirs are estimated. The estimated water quantities can be regarded as water resources potential, especially for surface water.

For setting the meteorological conditions for the rainfall-runoff model, the following principles are applied. • Precipitation amount in continues 2-year should be considered, because 2-year total precipitation amount seems to be related to water quantity more than one in a single year. • Adjusting total precipitation amount uses precipitation pattern in the representative year. • Temperature pattern in the representative year is used.

The results of the statistical analysis for precipitation in EABD and WABD show that year 2004 is almost average year in terms of precipitation amount. Therefore, in the present study, year 2004 is selected as the representative year for considering water resources.

Continuous 2-year simulations have been conducted using the calibrated NAM model, which is rainfall runoff module of MIKE11 (see Chapter 4). Initial condition for the simulation has been set as same as the condition at the beginning of year 2004 for the existing condition. The simulated result shows that the runoff volume in the 2nd year is almost always smaller than the one in the 1st year, even though the precipitation amount in the 2nd year is larger. This seems to be because of the influence of smaller precipitation amount in summer time in the 1st year. In the present study, the result in the 2nd year is utilized for further analysis.

The results have been imported to the Simple Model. Then, quasi-natural water quantities for x% probability of exceedence are estimated. The Simple Model_ver_Potential is utilized for estimating potential flow with significant reservoirs. For estimating potential flows with influence of significant reservoirs, the followings are assumed.

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• Outflow volume • Annual Total Outflow = Annual Total Inflow is assumed. • Same outflow pattern as the one in the representative year (2004) with adjustment to attain “Annual Total Outflow = Annual Total Inflow” is applied. • Transfer by feeder channels • Average transfer rate during 2001-2005 is applied.

The estimated probable water quantities at the downstream end (country border) of each river basin for quasi-natural flow and potential flow are shown below.

Probable Water Quantity at the Downstream End (Country Border) of Each River Basin

Struma Mesta Dospat Arda Biala Tundzha Maritsa Quasi- Natural 66.79 34.22 6.82 63.30 2.64 31.79 103.66 Average Flow (NF) Year (2004) Potential 65.35 30.58 2.40 50.09 2.64 22.50 113.85 Flow (PF) Quasi- Probability of Natural 51.62 23.65 5.06 47.87 0.83 28.34 80.04 Exceedence Flow (NF) 75% Potential 50.67 21.05 1.88 43.89 0.83 21.06 91.37 Flow (PF) Quasi- Probability of Natural 39.43 20.01 3.88 39.20 0.55 19.62 61.98 Exceedence Flow (NF) 90% Potential 38.65 17.84 1.43 35.89 0.55 14.54 70.34 Flow (PF) Quasi- Probability of Natural 31.04 13.25 2.99 33.61 0.43 14.66 51.68 Exceedence Flow (NF) 95% Potential 30.40 11.86 1.10 30.74 0.43 11.01 57.96 Flow (PF) Unit: m3/s The year with 95% of probability of exceedence (equivalent to drought with 1/20) provides almost half water quantity compared to one in the average year.

The estimated probable water quantities are stored in the Simple model_ver_Permit and the Simple model_ver_Demand. Using those tools, one can check water quantity including monthly variation at several different points in the river basin.

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6.6.2 Water Resources Potential and Demand Analysis

Balance of water resources potential and water demand under several scenarios are analyzed. Because condition of irrigation water use gives most significant impact on water balance, several scenarios on irrigation water use are analyzed under the following situations. • Drinking Water Demand • To keep current surface water dependency • Unit water use = 220 litter/day /person • Loss rate =50% • Industrial Water Demand • No change from current condition (Increase by GDP growth, but recycling rate will also increase) • Irrigation Water Demand • To keep current unit water demand for each irrigation branch • For current loss rate, the value showed by Irrigation Systems Ltd. is used.

The Simple Model is used for the analysis. Examples of the simulated results are shown in Figures 6.6.1 to 6.6.5. Based on the simulated results, the followings are discussed for each river basin.

(1) The Struma River Basin • Ratio of water demand against potential water resource is high in upstream area and low in downstream area. It is not spatially well balanced. At upstream of the confluence with the Dzherman River, water resources potential is quite limited compared to water demand. Demand control could be required for drinking, industrial and irrigation water. • On the other hand, from downstream reach of the confluence with the Dzherman River, water resources potential is rather large compared to water demand. • Under current loss rate (48 to 74%) and current unit water demand for irrigation water, about 40% of potential irrigation area can be irrigated with almost no water flow at the confluence with the Dzherman River in the Struma River when precipitation amount is 75% probability of exceedence. When we consider river environmental condition, at least minimum water should be kept. In this case, possible irrigation area is less than 40% of the potential area. • Under the condition that loss rate is 30% with current unit water demand for irrigation water, almost 100% of potential irrigation area can be irrigated with almost no water flow at the confluence with the Dzherman River in the Struma River when precipitation amount is 75% probability of exceedence. Considering necessity of minimum environmental flow, possible irrigation area is less than 100% of the potential area.

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(2) The Mesta River Basin • Water resources potential is large enough compared to water demand. • Ratio of water demand against potential water resource is large in downstream area and small in upstream area in general. • Under current loss rate (64%) and current unit water demand for irrigation water, almost 100% of potential irrigation area can be irrigated with about 20% of potential water flow being kept at the reach near Gotche Dolchev to the downstream end of the Mesta River when precipitation amount is 75% probability of exceedence. • Under the condition that loss rate is 30% with current unit water demand for irrigation water, almost 100% of potential irrigation area can be irrigated with about 50% of potential water flow being kept at the reach near Gotche Dolchev to the downstream end of the Mesta River when precipitation amount is 75% probability of exceedence. • However, water resources balance at local level should be further investigated using more detailed data. Especially, it should be careful on effect of water abstraction for local hydro power plant.

(3) The Arda River Basin • Water resources potential is generally large enough against water demand along main channel of the Arda River. • Under current loss rate (73%) and current unit water demand for irrigation water, about 100% of potential irrigation area can be irrigated without significant impact on main channel of the Arda River. • However, water resources balance at local level should be further investigated using more detailed data. Generally, annual water resources seem to be enough. To utilize water resources more in drought season, local reservoir or pond could be useful.

(4) The Tundzha River Basin • Ratio of water demand against potential water resource is large in upstream area and small in downstream area. It is not spatially well balanced. This is mainly because of decrease of water resources potential in the upstream area due to water transfer from the Koprinka Reservoir to the Maritsa River Basin. • Reduction of water resources potential at the area between the Koprinka Reservoir and the Zhrebchebo Reservoir can be constraints against recovering of irrigation activity in the area. If the current water transfer will be kept, demand control may be required in this area. • Under current loss rate (61-84%) and current unit water demand for irrigation water, about 35% of potential irrigation area can be irrigated with almost no water flow at the reach from the Zhrebchebo Reservoir to Yambol in the Tundzha River when precipitation amount is 75% probability of exceedence. When we consider

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river environmental condition, at least minimum water should be kept. In this case, possible irrigation area is less than 35% of the potential area. • In the current situation, almost all of water can be abstracted at the reach from the Zhrebchebo Reservoir to Yambol according to the permission issued to irrigation purpose．On the other hand, actually irrigated area in this area (Mainly Sliven branch) is less than 10% according to the record provided by Irrigation Systems Ltd. Water abstraction in this area is obviously too much compared to actual demand. Proper control of water abstraction based on actual demand is necessary. • Under the condition that loss rate is 30% with current unit water demand for irrigation water, almost 70% of potential irrigation area can be irrigated with almost no water flow at the reach from the Zhrebchebo Reservoir to Yambol in the Tundzha River when precipitation amount is 75% probability of exceedence. Considering necessity of minimum environmental flow, possible irrigation area is less than 70% of the potential area.

(5) The Maritsa River Basin • Water demand against potential water resource is spatially rather well balanced from upstream to downstream of the Maritsa River. • Without water transfer from other basins, water resources potential against water demand would be very small. • Under current loss rate (60 to 74%) and current unit water demand for irrigation water, about 15% of potential irrigation area can be irrigated with almost no water flow in the Maritsa River when precipitation amount is 75% probability of exceedence. When we consider river environmental condition, at least minimum water should be kept. In this case, possible irrigation area is less than 15% of the potential area. • Under the condition that loss rate is 30% with current unit water demand for irrigation water, about 30% of potential irrigation area can be irrigated with almost no water flow in the Maritsa River when precipitation amount is 75% probability of exceedence. Considering necessity of minimum environmental flow, possible irrigation area is less than 30% of the potential area.

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6.7 Result of Water Quality Simulation

The calibrated MIKE11 water quality models, which is described in Chapter 3, have been used for simulation of the scenarios: • Present situation (corresponds to the calibration simulation) • Near Future • Near Future with 10% loss • High Priority Future • High and Medium Priority Future For all of the scenarios the hydrological and hydraulic condition from year 2004 has been used as was done for the calibration. The time axis on all plots are therefore showing dates in 2004 although the represent different future years / scenarios.

The results are illustrated with plan plots of the rivers with colours corresponding to the Bulgarian Water Quality Classes with respect to BOD concentrations show in the following figure. Furthermore, the BOD concentration has been shown for selected station (cross section) in the river systems in Figures 6.7.1 to 6.7.10.

18.00 < 7.00 18.00 3.50 7.00 2.00 3.50

< 2.00

Color Legend for Plan plot of Concentration of Organic Pollutants (BOD) in the Rivers (mg/l)

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6.8 Summary of the Programmes of Measures

6.8.1 Introduction

The proposed programmes of measures are composed of structural measures and non-structural measures, and the non-structural measures are including proposed basic studies for the management of morphology in river basin.

The Structural measures will require feasibility studies and detailed designs for their implementation, and non-structural measures will require necessary arrangement for the execution.

6.8.2 Proposed Structural Measures

The proposed structural measures are composed of measures as follows:

(1) Water Quality Improvement and Management • Construction of new WWTPs. • Renovation of existing WWTPs, and • Renovation and expansion of sewer pipe networks.

(2) Water Quantity Improvement and Management • Improvement and replacement of water supply pipe networks, and • Improvement of irrigation systems with intake, water, transfer and distribution facilities.

The more detailed information is shown in Table 6.8.1.

6.8.3 Proposed Non Structural Measures

The proposed non-structural measures are summarized as follows:

(1) Measures for Water Quality Improvement and Management • Regulation for controlling and reducing pollution loads from industries and big livestock farms by strengthening of regulation. • Regulation for improving septic tanks to sealed type or for introducing individual treatment and periodical sludge extraction and treatment. Financial support system to people for improvement and installation of sealed type septic tanks and individual treatment is to be considered. • Regulation for controlling and reducing pollution load from the agricultural lands by changing agricultural methods and technology to reduce chemical fertilizer and pesticide, and • Establishment of a system to conduct a good cooperation with municipalities for monitoring and river basin management activities.

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(2) Measures for Water Quantity Improvement and Management • Regulation for reviewing and improving the current water use permissions to conduct optimum water intake and use, and also the water transfer to other river basin. • Regulation for conducting monitoring the water volume at water intakes by installing measurement devices by water users for intake sides as well as Basin Directorate at key locations in the rivers. • Regulation for controlling and improving the quality of data required for water quantity management, and • Regulation for establishing a system for a good coordination among RBDs, MoAF and related municipalities for river basin management and for implementation of the proposed project.

(3) Measures for River Morphology Improvement and Management To set up a new regulation for controlling and regulating sand/gravel extraction more strictly in order to protect the river channel and surrounding flood plain areas from unstable conditions. • Regulation for controlling any illegal activities or improper activities along the river, including solid waste dumping and land development, and • Regulation for establishing a good coordination system between the RBDs and the relating agencies/organizations responsible for management of forest areas, national parks and protection areas in the basin in order to cooperate in the RBM activities, particularly in the upstream of the river basin.

(4) Basic Study for River Basin Management and Flood Disaster Prevention • To conduct a study on “River Management Plan” for the basis for prevention of flood damages and controlling sand and gravel extraction as well as improvement of environmental status of water bodies from the view point of river morphology, • To conduct a basic study on pressures and impacts from discharges of priority substances and heavy metals, and also on pressures and impacts from the existing and closed mines in the basin for protect people from possible hazard caused by discharge of toxic substances, and • To conduct a study on water resources development and river flow regulation, which includes the following items: • The detailed and/or localized regime of the river flow, including the more detailed and/or localized water transfer, water use, and environmental flow. • The detailed assessment of the needs of additional hydro-technical facilities to be constructed as well as the restarting of construction of the suspended ones to regulate water flow for more efficient use of water resources, as a part of the integrated water management in Bulgaria and to meet the challenges of global climate change.

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CHAPTER 6

6.1

Main Report

Chapter 6

Tables

6.2

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3 8 9 9 0 3 1 1 0 2 5 7 7 9 Tabler 6.2.1 Major Industries in EABD: Directly Discharging Wastewater into the Total P kg/yea 9 0 3 0 001000 5 10 4 0 10 6 0020 4 00 0 20 7 0 4 Rivers02 6 or Water Bodies mg/l Total P

kg/year Total N 1.1 2319 0.01 3 5.0 11979 0.20 479 1.1 3373 1.95 597 2.8 551 2. 39 1.0 1203 0.20 241 1.1 1054 0.20 192 6.0 635 1. 11 2.1 399 5. 95 5.0 654 1. 14 1.5 199 0. 2 6.01.1 624 110 1. 5. 11 50 0.4162.0080 0.8 321 0.33 13 6.0 643 0.20 2 1.5 107 0. 1 8.1 650 5. 40 3.0 146 0.20 1 1.1 50 5.00 227 1.7 432 2.01 50 1.1 416 0. 6.7951.1016 4.12.8 3015.0 106 0.20 165 0.20 0.20 1 10.0 5676 5.00 283 10.0 3150 0.5 186 10.0 79471 0.70 559 34.3 104 1.1 27.3 21313 2.00 155 10.0 146 2.00 2 14.0 13338 0.20 190 10.0 1923.33 5.0 962 10.018.0 522 306 5.00 1.00 261 17 mg/l

N Total 73238 30764 BOD kg/year mg/l

BOD5

/s 3 m Discharge

NAM Catch. MA_M2 0.010 25 7875 MA_M2 0.032 25 MA_M2 0.252 34.4 2 MA_M6 0.014 33.076 14488 MA_M4 0.029 9.2 8414 MA_M6 0.001 26 993 MA_M3 0.004 15 2045 MA_M5 0.008 4.6 1138 MA_M4 0.002 15 1100 MA_STA1 0.002 15 783 MA_TOP3 0.025 34 26764 MA_HAR1 0.018 90 51088 MA_VAC2 0.002 25 1785

RIVER TRIBUTARY Chepinska river MA_CPI1 0.006 30 5884 Stara reka river reka Stara MA_STA2 0.020 80.13 50540 Chepinska riverChepinska MA_CPI1 0.001 65 2600 Srebarna riverSrebarna MA_M3 0.002 24 1188 Dzhurovska riverDzhurovska MA_YUG 0.067 25 52697 Ovacharitsa river MA_SAZ1 0.004 25 3272 Topolnitsa riverTopolnitsa MA_M3 0.000 1438 20995 gully Maritsa river Maritsa Pyasachnik river Pyasachnik MA_M4 0.006 15 3083 Rozovetska riverRozovetska MA_M3 0.000 2050 6232 Chepelarska riverChepelarska MA_M4 0.097 15 45989 riverChepelarska MA_M4 0.012 25 9145 Rozovetska riverRozovetska MA_M3 0.003 15 1609 Sechim dere /gully/ dere Sechim MA_CPI1 0.003 25 2000 Domlyanska riverDomlyanska MA_STR2 0.000 80 1133 Vozodel/Chelopeshka/ river; Maritsa river Sokolitsa river MA_SAZ1 0.003 25 2645 Dzhurovska riverDzhurovska MA_YUG 0.012 25 9463 Stryama riverStryama MA_STR2 0.001 25 1137 Mechka river Mechka Malka reka river reka Malka MA_TOP3 0.030 15 14250 Vacha river Vacha Koru dere /gully/ dere Koru MA_STR2 0.003 25 2502 Blatnitsa riverBlatnitsa MA_BLA 0.003 25 2600 Batovo dere /gully/ MA_STR2 0.001 25 825 drain canal /main canal drain 2/ collector Stryama riverStryama MA_STR2 0.001 25 816 1.1 36 5.00 16 riverShirokolashka MA_VAC2 0.001 45 765 stewater into the Rivers or Water Bodies (1/2) Water Rivers or into the stewater

Peshtera Laki Haskovo Kuklen Kuklen Brezovo Laki Brezovo Belovo Devin Karlovo Radnevo Stamboliyski canal Drain Karlovo Devin u u

Location

Settlement Municipality v. Kurtovo Konare

Maritsa Pazardzhik Pazardzhik Maritsa river Maritsa Peshtera BASIN Maritsa Velingrad Velingrad Maritsa Velingrad Velingrad Maritsa Dimitrovgrad Dimitrovgrad Maritsa river Maritsa Laki Maritsa v.Belozem Rakovski Maritsa v.Troyanovo Radnevo Maritsa Haskovo Maritsa izvor v.Dalbok Parvomay Maritsa Septemvri Septemvri Maritsa Dimitrovgrad Dimitrovgrad Maritsa river Maritsa Pazardzhik Pazardzhik Pishmanska river MA_M5 0.077 25 59897 Maritsa Brezovo Maritsa K land, municipality Maritsa v.Domlyan Karlovo Maritsa Stamboliyski Stamboliyski Maritsa river Maritsa v. ChelopechMaritsa Panagyurishte Chelopech Panagyurishte river Luda Yana MA_LUD2 0.030 25 23950 Maritsa Ignatievo v.Graf Maritsa Maritsa Belovo MaritsaMaritsa Karnare Parvomay Parvomay Maritsa Radnevo Maritsa v.Mirkovo Sofia Maritsa Dimitrovgrad Dimitrovgrad Maritsa river Maritsa Pazardzhik Pazardzhik Pishmanska river MA_M5 0.013 4 1576 Maritsa v.Choba Maritsa Devin Maritsa v.Orizovo Daskalovi Bratya river dere Suho MA_M3 0.006 50 9617 Maritsa v.Mednikarovo Galabovo Maritsa v.Bogdan Karlovo Maritsa v.Radinovo Maritsa Maritsa Laki Maritsa Kostenets Kostenets Maritsa v.Iganovo Karlovo Maritsa Maritsa Devin Maritsa Karlovo RIVER

Business

Production of veterinary products veterinary of Production Different type of lime Electric - power production - crystal ware Glass Brewery Paper products Paper Dairy Processing of meat of Processing Chemical industry Production of paper, corrugated cardboard and cardboard corrugated paper, of Production packings Extraction of brown coal Wine-production Cupper ore dressing ore Cupper ore copper of and processing Extraction metallurgy Parfume / rose oil Repair military technics, aeroplanes technics, military Repair Production of paper, corrugated cardboard and cardboard corrugated paper, of Production packings rubber retreading / tyre Petroleum and petroleum products+C59 and petroleum Petroleum Service for carriage and engine carriage for Service machine-building, bearing elements Iron-casting Coal output Coal Cupper ore dressing ore Cupper Accumulation factory /production of accumulators/ Canning factory Process of ballast Processing of vegetables Workshop for milk production milk for Workshop Machine-building, elements bearing Extraction of brown coal Process andProcess package cherry of Mining Production of paper and pasteboard paper of Production Machine Anti-Tank factory/ guided Missiles, Missiles,AVIATION Anti-Tank UnguideD Missiles,Artillery UNGUIDED Grinding Abrasive and ammunition,FUZES/ for Discs Abrasive and Grinding Wheels,Cutting Tools,Machinery and Non-metal,Diamond Metal f and Equipment Canning - vegetable production Process of fish of Process HERBICIDES INSECTICIDES, FUNGICIDES. Maritsa land, municipality K

hop for milk production hop for

of industry Name

6.2.1 Major Industries in EABD: Directly Discharging Wa Discharging Industries in EABD: Directly 6.2.1 Major

Laki - Orc-dressing with tailing pond "Laki-2-complex" tailing with Orc-dressing - Laki Mining Laki - Mining "Druzhba" - Laki о о Table

5 JSCo 6 Biovet Plovdiv KCM-S.A., 4 Haskovo brewery Plovdiv, JSCo, Kamenitsa 1NEOHIM JSCo 1NEOHIM 2 Trakya Paper JSCo 3Gorubs 7 "Maritsa TTP 3" Dimitrovgrad 9Asarel-Medet JSCo 8 Bimak Maining JSCo/Chelopech EAD 9Asarel-Medet 16 Stambolyski AD, Factory Paper 17 Vulkan JSCo 18 Brezovo Ltd, - Rikom 20 Mines"Trayanovo sever" and "Trayanovo 1" 19 JSCo Kristal 10 Dairy izvor, vDalbok 95 Elit Ltd, 23 2 Boni Oborot 22 Mine "Trayanovo 3", v.Mednikarovo 21 Benkovski - Georgi Terem - Plovdiv SPLTD 11 Belovo - Paper Mill JSC - Belovo 27 -Engine-shed EAD BDZ 25Sofia Bulgaria, Bearings SKF 26 JSCo Invest Chugunoleene 24 EAD Radnevo Remotex 12 JSCo - Med Elatsite 31 Rakovski Ltd, Oil Insa 30 JSCo Elhim-Iskra 29 Ltd Tiva Konex 28SPLTD - Hydro 13 Konex Tiva Ltd, v.Orizovo 32 Ognyanovo-K EAD 14 Gorubs 34 Polidey 2 Ltd, Karlovo, works 33Sofia Bulgaria, Bearings SKF 15 Plovdiv JSCo, Agrya 35 Bulgaria Agri SPLTD 39 canninga factory Plovdiv, Ltd, Ioka 36 JSCo HHI Kostenets 37 Bulgarian Rose JSCo, Karlovo 38 JSCo VMZ 40 BG - SPLTD P.A.L. No Basin River Maritsa 1.

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Total P kg/year

mg/l Total P

kg/year Total N 66 5496 97 0.200 55 0.200 18.30 0.200 3.24 1.82 6 1084266 0.027 9461 48.79 47496 0.200 0.921 315.36 1900 729.25 0.040 12.53 000.102 6941.1017 10 205 5.00 102 1.12.8910.5016 16 0.122.6 2 542.1235.0054 10.00 210 4.10 11814.04 0.609.006.00 242 173 6.00 343 1.10 273 5.00 150 1.10 66 1.10 191 50 28 56.7 3558 4.110 257.94 25.0 66 2.00 5 12.0 100 11.0060.5 91 7824.10 0.406.00 11738 3784 5 0.60 1.10 1718 694 30.06 5200 2.10 363 22.00 763214.05 0.43 110 149 1.10 9 mg/l N Total 405 911 750 739 234 476 228 720 415 259 307 104 6 25 0.200 0.84 425 315 953 271 1500 9360 7200 2288 4096 6 983 0.200 32.77 4325 7917 59047 31536 12552 45175 19789 39420 BOD kg/year 12869.84 25 mg/l

BOD5

/s 3 .025 25 m Discharge

NAM Catch. TU_M6 0.001 30 AR_M5 0.001 25 AR_M5 0.000 25 AR_M2 0.000 25 AR_M2 0.005 25 AR_M5 0.050 25 MA_M3MA_M3 0.001 0.001 15 15 MA_M5 0.001 25 MA_M6 0.000 25 MA_BLA 0.000 15 MA_STR1 0.000 50 AR_VAR1 0.002 200 TU_MOC2 0.002 25 TU_MOC1 0.005 25 y/ AR_M2 0.100 25

RIVER river river TRIBUTARY Tundzha riverTundzha TU_M7 0.091 21 open canalopen Arda river Arda Asenovska riverAsenovska TU_ASE1 0.020 50 Arda river Arda Lazova river Lazova Dam-lake PetkovetsDam-lake TU_MOC2 0.000 1200 Drain canal Drain Drain canal Drain Drain canal Drain Topolnitsa riverTopolnitsa MA_M3 0.000 280 Tundzha riverTundzha TU_M2 0.011 37.1 Enyovche river AR_M5 0 Pikla river Pikla Belyata riverBelyata MA_STR2 0.000 50 Madanska river AR_M5 0.003 25 Kriva vadaKriva river TU_M7 0.001 20 Tundzha riverTundzha TU_M9 0.001 25 gully Golyama Golyama river AR_VAR2 0.057 /gull dere Kodzha Chorbadzhiysko dere Chorbadzhiysko /gully/ Asashtitsa riverAsashtitsa Drain canal, in inlet river Mochuritsa TU_M6 0.009 25 and river Arda Chepinska river

Bodies (2/2) Water Rivers or into the stewater

Kazanlak Sliven Rodopi Madan Gurkovo Yambol Karnobat Madan Rudozem Kazanlak Karlovo Kazanlak Brezovo

Location

Settlement Municipality Kardzhli Kardzhli Kardzhli Kardzhli Arda Kardzhli Kardzhli Kardzhli Kardzhli Arda

zha v.Venets Arda Madan Arda Rudozem Rudozem Arda v.Enyovche Ardino Arda Madan Arda Rudozem Arda Zlatograd Zlatograd Arda Kardzhali Kardzhali Arda Momchilgrad Momchilgrad river Arda BASIN Maritsa v.Milevo Maritsa izvor v.Dalbok Parvamay Maritsa Parvomay Parvamay Maritsa Danov v.Hristo Karlovo Maritsa KostenetsMaritsa v.Radnevo Kostenets Maritsa Maritsa Panagyurishte Panagyurishte river Luda Yana MA_LUD2 0.001 15 Maritsa Brezovo Maritsa v.Zhitnitsa Brezovo Maritsa Bratsigovo Bratsigovo Umishka river MA_STA2 0.000 20 "Studen "Studen RIVER Tundzha Sliven Tundzha v.Lozarevo Sungulare Tund Tundzha Yambol Tundzha Kalofer Tundzha Kazanlak Tundzha v.Tserkovski Karnobat Tundzha Kazanlak Tundzha Maglizh reservoir reservoir Kladenets" Kladenets"

Business

Textiles Dairy Wine Production /WWTP/ Production Wine concrete of Production Mining /Process of lead-zink orc / orc lead-zink of Mining /Process Mining /Process of lead-zink orc / / orc lead-zink of Mining /Process Enamel UTENSIL Building Parfume / rose oil / rose Parfume Slaughterhouse aeroplanes technics, military Repair Processing of oriental tobaccos Machine-building, elements bearing Mining /Process of lead-zink orc / and raw material non-metal other of Extraction Textiles materials Factory for opitcs for Factory Production of tiling-stone from marble, limestone Workshop meat production Spirits and distiller /WWTP/ distiller and Spirits Meat production and processing of meat of and processing production Meat Weapons Chemistry Weapons Mining /Process of lead-zink orc / Workshop for production of essential oils essential production of for Workshop Tundzha Gurkovo Mining /Process of lead-zink orc / orc lead-zink of Mining /Process drinks Bottling Alcoholic

of industry Name

Wa Discharging Industries in EABD: Directly 6.2.1 Major

Table

7 Ltd Industries SIS 9 Ltd Betonstroy 8/IW/ Sofia Bulgaria, Bearings SKF 7 dol" "Krushev Mining Madan - JSCo 8 Gorubso Progresstroy 9 Bulgaria JSCo - K 6 Ltd VIN.S.Industries 2 Gorubso Rudozem - in EAD porcess of closing 5 "Pcheloyad" Mine Kardzhali, JSCo, Gorubso-Kardzhali 34 Gorubso-Kardzhali JSCo, Kardzhali, Mine "Enyovche" 95 Ltd mladost Baydano 1Arsenal JSCo 1Arsenal 1 Gorupso Zlatograd, Tailing pond "Erma river" 2 Sliven JSCo 3 Mirolio-Bulgaria JSCo Yambolen 6 Orc-dressing JSCo, Kardzhali Gorubso 5Arsenal JSCo 5Arsenal 4 JSCo Slaviantsi Vinex 50 Sokotab Bulgaria, Sofia, workshop for /SS/ 47 bird slaughterhouse Plovdiv, Ltd, TER-M 48 JSCo Terem 49 Kaomet 10 JSCo Bentonit 42 Karlovo JSCo, Rose Bulgarian 46 bird slaughterhouse Sofia, SPLTD/ Ltd,/Glaus-2004 Volex poultry Slaughterhouse 41 Dairy izvor, v.Dalbok D.Minev, - Chvor Bor 43 SPLTD Optikoelektron 44 town Plovdiv Ltd, Yulit - AS 45 Delikates-2 Ltd, v.Zhitnitsa, workshop meat production 10 Sofia Ltd Viganlex No 2. Tundzha River Basin 3. Arda River Basin

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Table 6.2.2 Major Industries in WABD: Directly Discharging Wastewater into the Rivers or Water Bodies 5 2 0 8 9 39 85 73 68 90 6544 2909 1129 Total P kg/year

mg/l

Total P 568 1.10 104 1766 5.00 1104 1135 0.27 101 9398 19.00 7440 2628 6910 50.49 1 42006 0.43 4551 2131865965 0.33 50.65 80894 873 88427 0.67 14850 57680 1.34 2 94989 0.40 3527 17936 0.93 123516 0.35 5519 126650 2.00 30853 kg/year N Total

mg/l Total N

BOD (kg/year) 5 mg/l

BOD

/s 3

m Discharge

ST_M1 0.500 20 319039 7.83 ST_M9 0.001 117 4441 10.20 386 2.76 104 ST_M1 0.008 8 1892 10.00 2365 0.16 ST_M6 0.002 123 8452 2.32 160 1.31 ST_M9 0.002 25 1577 6.00 378 0.27 17 ST_M9 0.051 39 62778 41.30 ST_M4 0.005 6 965 8.70 1482 2.31 393 ST_M9 0.015 3 1419 6.00 2838 0.43 205 ST_M2 0.002 18 1107 5.21 329 2.19 138 ST_M6 0.085 25 66620 8.00 ST_M6 0.013ST_M4ST_M4 25 0.012 10157 0.006 18 4.00 27 6365 1625 2.22 0.02 5090 2.01 805 0.30 381 0.38 107 ST_M6 0.006 25 4888 8.00 1564 0.43 ST_M4 0.006 13 2517 2.34 467 0.03 ST_M4 0.008 25 6306 8.00 2018 0.27 6 ST_M4 0.003 10 1080 4.00 432 0.20 22 ST_M4 0.002 10 650 3.20 202 1.08 68 ST_M9 0.489 22 334238 8.21 ST_RIL 0.006 8 1552 2.42 458 0.21 39 ST_SAN 0.012 79 14874 3.00 ST_SAN 0.500 19 299592 10.00 1 ST_SAN 0.010 2 694 10.00 3154 5.00 1577 ST_BRA 0.005 6 978 3.70 583 2.00 315 ST_BRA 0.008 40 10092 3.00 757 0.27 ST_BRA 0.007 8 1770 4.66 1029 5.00 1104 ST_BRA 0.004 12 1674 6.82 932 5.00 683 ST_BRA 0.008 4 1012 1.75 428 5.00 1222 ST_KON 0.003 164 15468 6.00 ST_STR1 0.333 10 105015 4.00 ST_STR1 0.007 136 30077 8.00

NAM Catch.

RIVER stewater into the Rivers or Water Bodies (1/2) Water into the Rivers or stewater TRIBUTARY Blagoevgradska River Bistritsa Aydarowsko Dere Aydarowsko /Gully/ Sandanska Bistritsa Sandanska River mirror water After /settling/

Sandanski Stream Radomir Collector Radomir Gully Varba Pernik River Turska Pernik /Gully/ Kalkas Pernik River Struma Pernik dere/gully/ Momishko ST_M9 0.002 25 1595 5.00 319 0.27 17 Simitli River Struma Pernik Krivobarska River ST_M9 0.010 36 11733 21.09 Pernik Buchinsko dere/gully/ ST_M9 0.006 25 4888 5.00 978 0.27 5 Radomir River Lyulyakova ST_M9 0.003 19 1798 9.84 931 1.47 139 Simitli River Struma Petrich Collector Pernik /gully/ "Kalkas" Dere ST_M9 0.278 6 56134 10.83 Petrich Collector Radomir River Struma Petrich channel Drainage ST_STR1 0.012 135 53019 24.00

Location

Settlement Municipality

Struma Radomir Struma Blagoevgrad Blagoevgrad Collector Struma Sandanski Sandanski Collector Struma v.Sklave Struma Radomir Struma Blagoevgrad Blagoevgrad Collector Struma Pernik Struma Blagoevgrad Blagoevgrad Collector Struma Topolnitsa v. Petrich Collector Struma Sandanski Sandanski Gully Struma Simitli Struma KocherinovoStruma v. Valkovo Kocherinovo River Struma Sandanski River Struma Struma Sandanski Sandanski Struma v. Krupnik Simitli river Struma Struma Petrich Struma Dol Bobov dol Bobov Struma River Razmetanitsa Pernik ST_DZH1 0.701 9 196643 4.00 Struma Pokrovnik v. Blagoevgrad River Struma Struma Kyustendil Kyustendil River Struma Struma Radomir Struma Breznik Struma KyustendilStruma Simitli Struma v. Senokos Kyustendil Simitli load avarage Luda reka river Struma Katuntsi v. Sandanski river Bistritsa Pirinska ST_PIR 0.001 25 919 10.00 368 1.50 55 Struma Damyanitsa v. Sandanski channel Drainage ST_M1 0.023 3 1826 1.26 922 0.14 105 Struma Blagoevgrad Blagoevgrad Struma v. Krupnik Simitli Collector Struma Pernik Struma Petrich Struma Petrich Struma Kyustendil Kyustendil Struma Izgrev v. Blagoevgrad Struma Pernik Struma Radomir Struma v. Garlyano Kyustendil Smolyanska Bistritsa ST_SOV 0.014 25 10950 6.00 Struma Pernik Struma Pernik Struma Bobov Dol Bobov dol Razmetanitsa River ST_DZH1 0.099 57 177015 5.75 Struma Kopilovtsi v. Kyustendil River Struma Struma Zhilentsi v. KyustendilRiver Radushka ST_M6 0.000 156 616 12.00 48 2.10 8 BASIN RIVER l

w

t

Business

t ndustry ndustry ndustry Car-wash and service-stationCar-wash Steel - metal industry metal - Steel Textile Iouioupioi Extraction of ballast Extraction of ballast Electrical appliance. Electrical no data no Sand extraction Sand Mechanicals / meters / Mechanicals Extraction of ballast Coal extraction Coal Car-washing Sand and gravel washing Mine industry Mine transpor industry, Extraction of ballast Leather industry Leather Energetics Electronics / speakers etc speakers / Electronics Tobacco processing Mechanicals /Water-meter Mechanicals greenhouse / agricultural-plants / greenhouse Food mea - Mine and transport industry Equipment for cron spirits Steel / metals articles metals / Steel Paint Steel production Steel plate printing / articles Electrical Struma Blagoevgrad Blagoevgrad Collector S

Wa Discharging Directly WABD: Industries in 6.2.2 Major

Table 2 Spartak PSK 1 SPLTD Co WWTP Leko 3 Bodzhinov & Co Ltd 4Bobov Plant Dol SPJ Power Thermal 5 Mines Bobov Dol JSCo 6 Ltd Versay 8 JSCo industry Stomana 9 EAD Pernik - Toploficatsia pond Tailing 7Gausto-gold JSCo 7Gausto-gold 4097 JSCo Yug - Hydrostroy gravel and + Sand washing (lorry) Car 36 ONIX Ltd 37 Rila-S.T.H Kombinat Mlechen products milk - Food 38 JSCo Strumateks 39 Ltd Rosela 33 TMSI Ltd Bistritsa 35 TMSI - Ltd 2002 Stoun 34 M.Stoilova Okeania-P.Stoilov, Production Concrete 30 SPLTD ZPP 31JSCo Vagledobiv Otkrit Mines 32 JSCo Metali Radomir i Mine 29 SA Visokogovoriteli 21 TMSI Ltd Bistritsa 20 EkoengineeringPM - SPLTD22 SA Vitren -pollution Uranium mine radio-nuk with 43 TPK Strimon-3 23JSCo Vagledobiv Otkrit Mines 24 JSCo Elektrik i Mine 26Ltd BULS 27 /vinprom/ JSCo. Damianitza 28 Ltd komers Alpha Wine - industry Food 14JSCo Vagledobiv Otkrit Mines 15 "Osogovo" - EAD/sanitry sewage/ i Mine 17 Mining JSCo Standart ZIIU 18 JSCo Gausto-gold 13 JSCo Sanel 16 SPLTD-Frukta Bugarkoop fruit - industry Food 19 SPLTD Georesurs 41 SPLTDSandanski - Mesokombinat 42 meat - industry Food J P DilarsLld 25 BT S.A. Blagoevgrad 11 Belasitsa S.A. 10 V&VGD Orandzherii-Petrich Ltd 12 Ltd Benet No of Name industry River Basin 1. Struma

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1261 Total P kg/year

mg/l Total P

kg/year N Total

mg/l Total N

BOD (kg/year) 2 2606 1.65 2472 5.00 7490 5 388 10.00 736 1.14 84 2 568 1.80 681 1.10 416 3 475 2.56 484 0.27 51 3 76 5.98 151 0.32 8 3 331 2.20 243 0.13 15 3 540 3.00 540 0.23 41 5 290 3.60 227 0.24 15 5 12 24053 1.95 3889 0.57 1145 18 540 3.00 90 0.80 24 10 500 4.00 200 0.20 10 10 56940 4.00 22776 0.50 2847 25 48 10.00 19 1.50 3 72 11031 8.00 1230 0.27 42 10 2489 5.93 1496 5.00 74 238 4.75 15 0.27 1 10 540 4.00 216 0.43 23 25 50 10.00 20 1.50 3 25 125 10.00 50 1.50 8 25 18 5.00 4 1.00 1 50 227 10.00 45 5.00 23 25 189 4.00 30 1.10 8 mg/l

BOD

/s 3

m Discharge

ST_M2 0.002 ST_M6 0.004 ST_M6 0.006 DO_M1 0.000 50 225 10.00 45 2.00 9 DO_M2 0.007 25 5566 5.00 1113 0.27 60 ME_M2 0.000 ME_M5 0.000 ME_M5 0.000 ME_M1 0.000 ST_BRA 0.000 ME_IST2 0.048 ME_IST2 0.181 ME_GLA 0.063 ST_STR1 0.012 ME_GLA 0.001 ME_IST2 0.000 ME_GLA 0.001 ME_GLA 0.008 ME_NEV 0.006 ME_NEV 0.005 ME_NEV 0.002

NAM Catch.

RIVER

TRIBUTARY Blagoevgradska Bistritsa Satovchenska Bistritsa river riverKrivopadinska ST_KON 0.000 river Dospat

t k Razlog Razlog Collector Kresna Manhole Razlog river Iztok Razlog river Bela Belitsa Mesta river Bansko Collector Belitsa Belishka river Bansko River Mesta Razlog river Iztok Dospa Petrich Collector Petrich channel Irrigation ST_STR1 0.002

Location

t Settlement Municipality

Mesta v.Banya Mesta Razlog Mesta Hadzhidimovo Hadzhidimovo river Matenitsa ME_M2 0.002 Mesta v.Banya Mesta Bansko Mesta Delchev Gotse Delchev Gotse Collector MestaMesta Belitsa Mesta v.Dabnitsa Belitsa Garmen river Varbitsa Mesta Delchev Gotse Delchev Gotse River Mesta Mesta Bansko Mesta Delchev Gotse Delchev Gotse River Mesta Mesta Razlog Mesta v.Satovcha Satovacha Struma Kresna Dospat kamak Pobit Dospat v. Dospa Velingrad Gully Struma Boboshevo Boboshevo settling After Struma Petrich Struma Blagoevgrad Blagoevgrad Struma Nevestino v. Nevestino River Struma Struma v.Meshtitsa Perni Struma Petrich BASIN RIVER s g k

y Business

y Food -meat Food Building materials Building Furniture factor Furniture Sand and gravel washing - WWTP - washing gravel and Sand Mesta Razlog Furniture factory Furniture Sand, stone and gravel extraction gravel and stone Sand, Dair Road building Road Electronic / telephone Sand and gravel washing gravel and Sand Meat production Meat Car washing, TradingCar washing, complex, oil and Extraction of ballast of Extraction Import of electrics materials electrics of Import Sand and gravel washing gravel and Sand gas and oil service, motor washing, Car /

odopi Washing Car

Bodies (2/2) Water into the Rivers or Wastewater Discharging Directly WABD: Industries in 6.2.2 Major

Table

SPLTD 2002 Belasitsa 1 JSCo Pirinhard 2 JSCo Holding Telecom Incoms items Electical 1 EkoengineeringPM - SPLTD pollution - radio-nu mine Uranium with 3 4 JSCo technology hand Magnetic heads magnetic / Electronic 2Rosi Ltd 2Rosi 9 JSCo Kalida 7 SPLTD Story Pirin 8 SPLTD Inkes 5 JSCo aparatura za telephonna Zavod 6 TMSI Ltd Bistritsa-2002 50JSCo Invest Arm 49 JSCo Tehnika Saobshtitelan Machine-building 48 Manev Tri Valentin Bora- no data 10 SPLTD Bulgaria Hemefa 13Ltd Neftotrans-2001 11 Dzhildzhov-R Ahmed 12 SPLTD Strazhite 14 Ilya Ivanov Dimitrov 15 JSCo Mebelplast 44 SPLTD Mes-Co 45 Ltd-YMSI B V D 46 JSCo Energoremont-Kresna 47 97 SA Granit appliance. Electrical No of Name industry Basin River 2. Mesta Basin River 3. Dospat

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Table 6.2.3 Major3 Livestock Farms3 with their Pollution Loads in EABD

21 21

11 11 42,000 24,000 7,200 63,000 36,000 10,800 kg / year/ kg year / kg year / kg year/ kg year / kg year / kg

01 01 TP BOD TN TP TP BOD TN TP head head kg / year / / year kg kg / year / / year kg Total 69,000 39,600 11,040 Total 374,959 181,017 25,853 4 0.12 4 0.12 3 0.7385 33,723 17,031 3,121 3 0.7385 10,318 5,211 955 3 0.7385 14,763 7,456 1,366 3 0.7385 14,204 7,173 1,315 3 0.002 6,000 3,600 240 3 0.7385 95,760 48,360 8,862 79 1.4 0 0 0 79 1.4 69,000 23,700 420 79 1.4 0 0 0 03 0.002 60,000 36,000 2,400 79 1.4 0 0 0

91 91 head head

/ year / kg / year / kg

0.7 0. 0.7 0. head head BOD TN BOD TN kg / year/ kg / year/

NAM NAM TU_M5 230 TU_M5 230 TU_M3 230

Catchment Catchment

in EABD (1/2) Pollution Loads r 300 TU_MOC1 230 153 TU_MOC2 230 79 1.4 35,190 12,087 214 1850 TU_M4 7.98 4.0 1293 TU_MOC1 7.98 4.0 4226 TU_M2 7.98 4.0 1780 TU_MOC1 7.98 4.0 90000 AR_CHE 12000 TU_M2 7.98 4.0 60000 TU_M3 Head Head

Municipality Municipality Tvarditsa Tvarditsa Momchilgrad 120000 AR_VAR1 0.05 0.0 Karnobat Yambol

Location Location

Settlement Settlement

6.2.3 Major Livestock Farms with thei 6.2.3 Major Species Species

roylers Momchilgrad roylers village Bolyarsko Tundzha 1200000 TU_KAL 0.05 0. pigs village Mechkarevo Sliven pigs Yambol b b pigs village Vodenichane Straldzha laying hanslaying zone industrial - Smolyan Smolyan CATTLES village Samuilovo Sliven pigs hanslaying village Kalchevo village Samuilovo Tundzha Sliven CATTLES village pigs Venets Gradishte Krumovo Karnobat

Table

Region/Name Region/Name

po svinevadstvo" "Reproduktor JSCo 12 34 5678 12 34 5678 2. PLC "Kokoimpex" 3. ST asorti" Eko "ZK 7. ST Mihaylov" Iliya - "SELEKT CATTLES Tvarditsa 4. 5. "Geomeks" 1. 2005" Ltd. Farm "Eko 6. Ltd. -02" "MCD 2. " JSCo "Svinekomplex 6. DM" - "Bulmaks 2. Angelov" Ivan - "Gradus 1. 2000" PLC "Furazhi 3. ST "Todor Uzunov" 5. ST Lyubenov" "Lyubomir CATTLES village Lozarevo Sungurlare 8. ST Penchev" Plamen - "ASKENT CATTLES Tvarditsa No No

1. Arda River Basin Basin River Tundzha 2.

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3

21

11 56,000 32,000 9,600 84,000 48,00049,000 14,400 28,000 8,400 46,200 26,400 7,920 108,500 62,000 18,600

year/ kg year / kg year / kg

01 head kg / year / / year kg Total 2,614,047 1,134,909 151,044 3 0.7385 11,970 6,045 1,108

head / year / kg 0.70.7 0.4 0.4 0.12 0.12 0.70.7 0.4 0.4 0.12 0.12 0.7 0.4 0.12 head BOD TN TP BOD TN TP kg / year/

NAM Catchment r Pollution Loads in EABD (2/2) Pollution Loads r 950 MA_M3 230 79 1.4 218,500 75,050 1,330 150 MA_M5 230 79 1.4 34,500 11,850 210 120 MA_LUD1 230 79 1.4 27,600 9,480 168 250 MA_M3 230 79 1.4 57,500 19,750 350 200 MA_HAR1 230 79 1.4 46,000 15,800 280 110 MA_M5 230 79 1.4 25,300 8,690 154 7000 MA_M3 7.98 4.03 0.7385 55,860 28,210 5,170 4500 MA_M3 7.98 4.03 0.7385 35,910 18,135 3,323 9800 MA_M3 7.98 4.03 0.7385 78,204 39,494 7,237 2186 MA_TOP2 230 79 1.4 502,780 172,694 3,060 1200 MA_M2 7.98 4.03 0.7385 9,576 4,836 886 1160 MA_M4 230 79 1.4 266,800 91,640 1,624 3600 MA_STA2 7.98 4.03 0.7385 28,728 14,508 2,659 2424 MA_M4 7.98 4.03 0.7385 19,344 9,769 1,790 10000 MA_M3 7.98 4.03 0.7385 79,800 40,300 7,385 70000 MA_STR1 80000 MA_M4 28000 MA_SAZ2 7.98 4.03 0.7385 223,440 112,840 20,678 66000 MA_M5 92000 MA_HAR1 0.2 0.1 0.006 18,400 9,200 552 Head 155000 MA_M4 560000 MA_M3 0.05 0.03 0.002 28,000 16,800 1,120

k

n itrovgrad 1500 MA_M2 7.98 4.0

Municipality Rakovski Rakovski Maritsa Maritsa Rodopi Pazardzhik Dimitrovgrad 100 MA_M2 230 79 1.4 23,000 7,900 140 Peshtera 120000 MA_STA2 Haskovo Stamboliyski 1000 MA_M4 7.98 4.03 0.7385 7,980 4,030 739 Nova ZagoraNova 410000 MA_BLA 0.05 0.03 0.002 20,500 12,300 820 Nova Zagora Nova 508 MA_BLA 230 79 1.4 116,840 40,132 711 Pshtera Plovdiv Rakovski Chirpa Pazardzhi Nova ZagoraNova 5015 MA_BLA 7.98 4.03 0.7385 40,020 20,210 3,704 Haskovo Pazardzhik 12000 MA_M5 7.98 4.03 0.7385 95,760 48,360 8,862

Location

k Settlement

Aleko Konstantinovo village

Livestock Farms with thei 6.2.3 Major Species roylers Zagora Nova roylers Chirpan roylers village Pamukchi Zagora Stara 100000 MA_SAZ2 0.05 0.03 0.002 5,000 3,000 200 pigspigs Belozem village Bolyartsi Sadovo pigsvillage Manole CATTLE village Krepost laying hans Pazardzhi laying hanslaying Peshtera pigs Stamboliyski CATTLE Rakovski laying hanslaying village Trilistnik Maritsa pigspigspigs village Asparuhovo Han village Preslaven Zagora Stara village Oryahovitsa Zagora Stara 5800Zagora Stara MA_SAZ2 3900 3200 7.98 MA_SAZ2 MA_SAZ2 4.03 7.98 7.98 0.7385 4.03 4.03 46,284 0.7385 0.7385 23,374 31,122 25,536 4,283 15,717 12,896 2,880 2,363 laying hanslaying Tsalapitsa CATTLE Pazardzhik laying hanslaying Plovdiv pigs village Klokotnitsa Haskovo CATTLE village Dinevo b b b pigs village Bozduganovo Radnevo CATTLE pigs village Krumovo Rodopi CATTLE village Tsalapitsa CATTLE Rakovski CATTLEvillage Korten ducks Haskovo pigs Zagora Nova pigs village Apriltsi pigs village Chernogorovo Dim

Table

Region/Name

"Mihaela - Vasilka Zhelyazkova" ST "Dimitar Madzharov- svinevadstvo 12 34 567891 8. 2003" ST Kartevi "Bratya pigsvillage Manole 3. JSCo Invest" "Stomar 6.ST 96" - "Reya 9. 96" ST - "Reya 6. PLC "Gradus" 5. tsentar" "Ucheben 6. "ZhK Gendov" 8. JSCo "Galus" 3. Cooperation Levski" "Vasil CATTLE village Levski 1. ST "Angelov" 7. PLC "Apetit" 4. JSCo "Kalmitsa" 1. 95" - "Maritsa ZK 7. 95" ST - "Elit 2. "Ilma- Il" Ltd 4. "KOMSO" 4. 3. 92" ST "Andip 9. JSCo Milk" - "Deniker 5.ST Nikolov" Kiril - "Oskar 5. PLC "Aerkok" 7. 2000" - Milk - 95", "Elit - "Elit pigs CATTLE Popovitsa village Zhitnica Kaloyanovo 11290 MA_STR1 7.98 4.03 0.7385 90,094 45,499 8,338 2. ST Hiusein" H. - "GRMI pigs Pshtera 8. ST MI" "DIANA 2. 90" "DANIELA 1. JSCo "SVIKOM" No 10. ST Mihaylov" "Emil 15.ST PK "Agromax" 16. PLC "Elis" 10. PLC Rodopa" - "VZhK 10. "Zhuliv"PLC 12. 13. PLC "Agroslavyanin" 14. COM" - "TEDDI 11. 95" - "Ayaks

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P P Table 6.2.4 Major3 Livestock Farms3 with their Pollution Loads in WABD

21 21

9,576 4,836 886 11 11 9,576 4,836 886 7,980 4,030 739 24,380 8,37431,280 148 10,744 190 27,140 9,322 165 60,095 34,340 10,302

year/ kg year / kg year / kg year/ kg year / kg year / kg

1.4 1.4 1.4

01 01 head head kg / year / / year kg / / year kg Total Total 150,875 66,810 11,545

TN TP BOD TN T

head head

/ year / kg / year / kg 0.7 0.4 0.12 230 79 230 79 230 79 7.98 4.03 0.7385 7.98 4.03 0.7385 head head BOD BOD TN TP BOD TN T kg / year/ kg / year/

NAM NAM

Catchment Catchment

106 ST_M6 136 ST_DZH1 Head Head WABD in Pollution Loads their

Municipality Municipality Gotse DelchevGotse 1200 ME_M3 Kocherinovo 118 ST_RIL

Location Location

Settlement Settlement

Livestock Farms with 6.2.4 Major pigs village Borovo CATTLE village Bersin CATTLE village Kamenik Boboshevo laying henslaying village Shishkovtsi Kyustendil 85850 ST_M6 CATTLE Kocherinovo

Table

Species Region/Name Species Region/Name

12 34 567891 12 34 567891 1 "Valdis" farm Poultry 1. "Yosifov" "Atanas 1. plast" Pirin "GHT - 1. 5" JSCoMM "Kembarou pigs village Dol Zelen Blagoevgrad 1000 ST_M5 1. Malinov" "Nikola 2. "Boris Kiroychev" No No 1. Struma River Basin River Struma 1. Basin River Mesta 2.

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Table 6.2.5 Estimated Quantity of Newly Treated Sewage and Reduction of Wastewater Loss for the High Priority Towns in EABD and WABD

Improvement Improvement of Sewerage Estimated Reduction of of WWTP Currently Existing Networks Total Sewage Estima Currently lost polluted Groundwater Sewage to be discharged Town / coverage to be treated: ted sewage into groundwater by Pollution by No. PE in 2015 newly treated: sewage into the Settlement of SW: P New A=200 l/d x Loss of ground: D=C the loss sewage: Renovation of B existing sewer Renov (%) Reno or PE SW: L x L suppose E=10 x Sewer pipes: New pipes: C=A*P at. vat. Expan D F=0.9 x E sion

(m3/year) (m3/year) (m3/year) (%) (m3/year) (m3/year) (m3/year) I. EABD Area 1. New WWTPs and Improvements of SW in the Maritsa River Basin 1-1 Asenovgrad 78,054 x 46% x x 5,697,942 5,697,942 2,621,053 40% 1,048,421 10,484,213 9,435,792 1-2 Plovdiv 681,985 85% x x 49,784,920 7,467,738 42,317,182 40% 16,926,873 169,268,727 152,341,854 1-3 Karlovo 37,181 x 85% x x 2,714,177 2,714,177 2,307,050 40% 922,820 9,228,200 8,305,380 1-4 Velingrad 28,752 x 90% x x 2,098,896 2,098,896 1,889,006 40% 755,603 7,556,026 6,800,423 1-5 Peshtera 28,691 x 99% x x 2,094,407 2,094,407 2,073,462 40% 829,385 8,293,850 7,464,465 1-6 Harmanli 28,538 x 67% x x 2,083,238 2,083,238 1,395,769 40% 558,308 5,583,077 5,024,769 1-7 Svilengrad 28,050 x 38% x x 2,047,650 2,047,650 778,107 40% 311,243 3,112,428 2,801,185 1-8 Chirpan 25,413 x 85% x x 1,855,149 1,855,149 1,576,877 40% 630,751 6,307,507 5,676,756 1-9 Rakovski 23,453 x 0% x 1,712,033 1,712,033 0 1-10 Panagyurishte 23,029 x 86% x x 1,681,137 1,681,137 1,445,778 40% 578,311 5,783,113 5,204,802 1-11 Parvomay 22,200 x 65% x x 1,620,600 1,620,600 1,053,390 40% 421,356 4,213,560 3,792,204 1-12 Stamboliyski 18,068 x 74% x x 1,318,928 1,318,928 976,006 40% 390,403 3,904,025 3,513,623 1-13 Kostenets 11,048 x 95% x x 806,533 806,533 766,207 40% 306,483 3,064,826 2,758,344 1,034,460 75,515,608 33,198,426 59,199,888 23,679,955 236,799,551 213,119,596 2. New WWTPs and Improvements of SW in the Tundzha River Basin 2-1 Yambol 118,971 x 80% x x 8,684,883 8,684,883 6,947,906 40% 2,779,163 27,791,626 25,012,463 2-2 Karnobat 28,916 x 100% x 2,110,832 2,110,832 2,110,832 40% 844,333 8,443,326 7,598,993 2-3 Elhovo 16,808 x 84% x x 1,226,948 1,226,948 1,030,636 40% 412,254 4,122,544 3,710,289 2-4 Kalofer 4,229 x 70% x x 308,702 308,702 216,092 40% 86,437 864,367 777,930 168,923 12,331,364 12,331,364 10,305,465 4,122,186 41,221,862 37,099,676 3. New WWTPs and Improvements of SW in the Arda River Basin 3-1 Kardzhali 67,346 x 90% x x 4,916,252 4,916,252 4,424,627 50% 2,212,313 22,123,135 19,910,821 67,346 4,916,252 4,916,252 4,424,627 2,212,313 22,123,135 19,910,821 4. Renovation of the Existing WWTPs and Improvements of SW 4-1 Nova Zagora 36,185 x 97% x x 2,641,469 79,244 2,562,224 40% 1,024,890 10,248,898 9,224,008 4-2 Radnevo 20,691 x 100% x 1,510,443 0 1,510,443 40% 604,177 6,041,772 5,437,595 4-3 Ihtiman 20,234 x 95% x x 1,477,046 73,852 1,403,193 40% 561,277 5,612,773 5,051,496 4-4 Pavel banya 4,407 x 60% x x 321,711 128,684 193,027 40% 77,211 772,106 694,896 81,516 5,950,668 281,781 5,668,887 2,267,555 22,675,549 20,407,994 1,352,245 98,713,892 50,727,823 79,598,867 32,282,010 322,820,097 290,538,087 II. WABD Area 1. New WWTPs and Improvements of SW in the Struma River Basin 1-1 Petrich 45,020 x 100% x 3,286,424 3,286,424 3,286,424 60% 1,971,854 19,718,541 17,746,687 1-2 Sandanski 40,358 x 100% x 2,946,098 2,946,098 2,946,098 60% 1,767,659 17,676,585 15,908,927 1-3 Simitli 8,242 x 100% x 601,637 601,637 601,637 60% 360,982 3,609,821 3,248,839 93,619 6,834,158 6,834,158 6,834,158 4,100,495 41,004,947 36,904,452 2. New WWTPs and Improvements of SW in the Mesta River Basin 2-1 Gotse Delchev 30,185 x 96% x x 2,203,469 2,203,469 2,115,330 60% 1,269,198 12,691,979 11,422,781 2-2 Bansko 11,493 x 71% x x 839,011 839,011 595,698 60% 357,419 3,574,186 3,216,768 41,678 3,042,479 3,042,479 2,711,027 1,626,616 16,266,165 14,639,548 3. New WWTPs and Improvements of SW in the Dospat River Basin 3-1 Dospat 3,218 x 40% x x 234,943 234,943 93,977 60% 56,386 563,864 507,477 3,218 234,943 234,943 93,977 56,386 563,864 507,477 4. Renovation of the Existing WWTPs and Improvements of SW 4-1 Pernik 121,350 x 94% x x 8,858,550 531,513 8,327,037 60% 4,996,222 49,962,222 44,966,000 4-2 Dupnitsa 55,224 x 91% x x 4,031,352 362,822 3,668,530 60% 2,201,118 22,011,182 19,810,064 4-3 Radomir 21,621 x 90% x x 1,578,333 157,833 1,420,500 60% 852,300 8,522,998 7,670,698 198,195 14,468,235 1,052,168 13,416,067 8,049,640 80,496,402 72,446,762 336,710 24,579,815 11,163,748 23,055,230 13,833,138 138,331,378 124,498,240 Note: 1) Loss of new or renovated sewer pipes is assumed to be 10 %. 2) Loss from the newly expanded sewer networks is assumed to be almost same as the current condition with the loss from the septec tanks.

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Table 6.2.6 Estimated Construction Cost for the Proposed Wastewater Treatment Plants and Sewerage Improvements for the High Priority Towns in EABD and WABD

New Construction or Renovation of the WWTPs Improvement (including Expansion) or New Sewer Networks

Total Cost of Town / New Physical Require Physical No. Municipality PE in 2015 Non- Engineering Administratio Engineering Administratio Sub-total Cost of WWTPs and Settlement or Unit Mechani. Electrical Contingency: Sub-total Cost of Improv. / d Required Unit Contingency: Direct Cost Civil Works construction Cost: Direct n Cost: Direct Direct Cost Cost: Direct n Cost: Direct Sewer Sewer Networks Renov Cost Works Works Direct Cost x WWTPs New Length Length Cost Direct Cost x 10 Activities Cost x 10 % Cost x 5 % Cost x 5 % Cost x 5 % Improvement at. 10 % per PE % (EUR/ (m / (EUR/ (EUR) (EUR) (EUR) (EUR) (EUR) (EUR) (EUR) (EUR) (EUR) (m) (EUR) (EUR) (EUR) (EUR) (EUR) (EUR) PE) PE) m) 12 3 4567 8 9 1011121314 151617181920 2122 23 24 25 I. High Priority Towns and Settlements in EABD I-1 New WWTPs and Improvements of SW in the Maritsa River Basin I-1-1 Asenovgrad Asenovgrad 78,054 New 210 16,391,340 7,376,103 4,917,402 2,458,701 1,639,134 737,610 819,567 1,639,134 19,587,651 Improv. 3.2 249,773 398 99,409,574 4,970,479 4,970,479 9,940,957 119,291,489 138,879,141 I-1-2 Plovdiv Plovdiv 681,985 - 0 Improv. 0.9 613,787 750 460,340,010 23,017,001 23,017,001 46,034,001 552,408,012 552,408,012 I-1-3 Karlovo Karlovo 37,181 New 295 10,968,248 4,935,711 3,290,474 1,645,237 1,096,825 493,571 548,412 1,096,825 13,107,056 Improv. 4.0 148,722 340 50,565,480 2,528,274 2,528,274 5,056,548 60,678,576 73,785,632 I-1-4 Velingrad Velingrad 28,752 New 320 9,200,640 4,140,288 2,760,192 1,380,096 920,064 414,029 460,032 920,064 10,994,765 Improv. 4.1 117,883 333 39,255,106 1,962,755 1,962,755 3,925,511 47,106,127 58,100,892 I-1-5 Peshtera Peshtera 28,691 New 320 9,180,960 4,131,432 2,754,288 1,377,144 918,096 413,143 459,048 918,096 10,971,247 Improv. 4.1 117,631 333 39,171,140 1,958,557 1,958,557 3,917,114 47,005,368 57,976,615 I-1-6 Harmanli Harmanli 28,538 New 320 9,132,000 4,109,400 2,739,600 1,369,800 913,200 410,940 456,600 913,200 10,912,740 Improv. 4.1 117,004 333 38,962,249 1,948,112 1,948,112 3,896,225 46,754,699 57,667,439 I-1-7 Svilengrad Svilengrad 28,050 New 320 8,976,000 4,039,200 2,692,800 1,346,400 897,600 403,920 448,800 897,600 10,726,320 Improv. 4.1 115,005 332 38,181,660 1,909,083 1,909,083 3,818,166 45,817,992 56,544,312 I-1-8 Chirpan Chirpan 25,413 New 335 8,513,355 3,831,010 2,554,007 1,277,003 851,336 383,101 425,668 851,336 10,173,459 Improv. 4.2 106,735 330 35,222,418 1,761,121 1,761,121 3,522,242 42,266,902 52,440,361 I-1-9 Rakovski Rakovski 23,453 New 340 7,973,850 3,588,233 2,392,155 1,196,078 797,385 358,823 398,693 797,385 9,528,751 New 4.2 98,501 329 32,406,665 1,620,333 1,620,333 3,240,666 38,887,997 48,416,748 I-1-10 Panagyurishte Panagyurishte 23,029 New 340 7,829,955 3,523,480 2,348,987 1,174,493 782,996 352,348 391,498 782,996 9,356,796 Improv. 4.2 96,723 329 31,821,859 1,591,093 1,591,093 3,182,186 38,186,231 47,543,027 I-1-11 Parvomay Parvomay 22,200 New 340 7,548,000 3,396,600 2,264,400 1,132,200 754,800 339,660 377,400 754,800 9,019,860 Improv. 4.2 93,240 328 30,582,720 1,529,136 1,529,136 3,058,272 36,699,264 45,719,124 I-1-12 Stamboliyski Stamboliyski 18,068 New 380 6,865,650 3,089,543 2,059,695 1,029,848 686,565 308,954 343,283 686,565 8,204,452 Improv. 4.6 83,111 325 27,010,913 1,350,546 1,350,546 2,701,091 32,413,095 40,617,547 I-1-13 Kostenets Kostenets 11,048 New 395 4,364,118 1,963,853 1,309,235 654,618 436,412 196,385 218,206 436,412 5,215,121 Improv. 5.7 62,976 320 20,152,282 1,007,614 1,007,614 2,015,228 24,182,738 29,397,859 Sub-total I-1 1,034,460 106,944,116 48,124,852 32,083,235 16,041,617 10,694,412 4,812,485 5,347,206 10,694,412 127,798,218 2,021,089 943,082,074 47,154,104 47,154,104 94,308,207 1,131,698,489 1,259,496,707 I-2 New WWTPs and Improvements of SW in the Tundzha River Basin I-2-1 Yambol Tundzha 118,971 New 145 17,250,795 7,762,858 5,175,239 2,587,619 1,725,080 776,286 862,540 1,725,080 20,614,700 Improv. 2.5 297,428 455 135,329,513 6,766,476 6,766,476 13,532,951 162,395,415 183,010,115 I-2-2 Karnobat Karnobat 28,916 New 320 9,252,960 4,163,832 2,775,888 1,387,944 925,296 416,383 462,648 925,296 11,057,287 Improv. 4.1 118,554 333 39,478,332 1,973,917 1,973,917 3,947,833 47,373,999 58,431,286 I-2-3 Elhovo Elhovo 16,808 New 365 6,134,738 2,760,632 1,840,421 920,211 613,474 276,063 306,737 613,474 7,331,011 Improv. 4.8 80,676 324 26,139,024 1,306,951 1,306,951 2,613,902 31,366,829 38,697,840 I-2-4 Kalofer Karlovo 4,229 New 455 1,924,104 865,847 577,231 288,616 192,410 86,585 96,205 192,410 2,299,304 Improv. 7.2 30,447 299 9,103,761 455,188 455,188 910,376 10,924,513 13,223,817 Sub-total I-2 168,923 34,562,597 15,553,168 10,368,779 5,184,389 3,456,260 1,555,317 1,728,130 3,456,260 41,302,303 527,104 210,050,629 10,502,531 10,502,531 21,005,063 252,060,755 293,363,058 I-3 New WWTPs and Improvements of SW in the Arda River Basin I-3-1 Kardzhali Kardzhali 67,346 New 215 14,479,373 6,515,718 4,343,812 2,171,906 1,447,937 651,572 723,969 1,447,937 17,302,850 Improv. 3.4 228,976 382 87,468,881 4,373,444 4,373,444 8,746,888 104,962,657 122,265,508 Sub-total I-3 67,346 14,479,373 6,515,718 4,343,812 2,171,906 1,447,937 651,572 723,969 1,447,937 17,302,850 228,976 87,468,881 4,373,444 4,373,444 8,746,888 104,962,657 122,265,508 I-4 Renovation of the Existing WWTPs and Improvements of SW I-4-1 Nova Zagora Nova Zagora 36,185 Renovat 140 5,065,830 1,773,041 2,026,332 1,013,166 253,292 177,304 253,292 506,583 6,003,009 Improv. 4.0 144,738 340 49,210,920 2,460,546 2,460,546 4,921,092 59,053,104 65,056,113 I-4-2 Radnevo Radnevo 20,691 Renovat 245 5,069,295 1,774,253 2,027,718 1,013,859 253,465 177,425 253,465 506,930 6,007,115 Improv. 4.3 88,971 326 29,004,644 1,450,232 1,450,232 2,900,464 34,805,573 40,812,687 I-4-3 Ihtiman Ihtiman 20,234 Renovat 245 4,957,208 1,735,023 1,982,883 991,442 247,860 173,502 247,860 495,721 5,874,291 Improv. 4.3 87,004 326 28,363,320 1,418,166 1,418,166 2,836,332 34,035,984 39,910,275 I-4-4 Pavel banya Pavel banya 4,407 Renovat 338 1,487,363 520,577 594,945 297,473 74,368 52,058 74,368 148,736 1,762,525 Improv. 7.3 32,171 297 9,554,817 477,741 477,741 955,482 11,465,780 13,228,305 Sub-total I-4 81,516 16,579,695 5,802,893 6,631,878 3,315,939 828,985 580,289 828,985 1,657,970 19,646,939 352,884 116,133,701 5,806,685 5,806,685 11,613,370 139,360,441 159,007,380 Total of I. 1,352,245 172,565,780 75,996,632 53,427,704 26,713,852 16,427,593 7,599,663 8,628,289 17,256,578 206,050,310 3,130,054 1,356,735,285 67,836,764 67,836,764 135,673,529 1,628,082,342 1,834,132,652 II. High Priority Towns and Settlements in WABD II-1 New WWTPs and Improvements of SW in the Struma River Basin II-1-1 Petrich Petrich 45,020 New 250 11,254,875 5,064,694 3,376,463 1,688,231 1,125,488 506,469 562,744 1,125,488 12,324,088 Improv. 3.8 171,074 347 59,362,713 2,968,136 2,968,136 5,936,271 71,235,255 83,559,343 II-1-2 Sandanski Sandanski 40,358 New 260 10,492,950 4,721,828 3,147,885 1,573,943 1,049,295 472,183 524,648 1,049,295 11,489,780 Improv. 3.9 157,394 343 53,986,228 2,699,311 2,699,311 5,398,623 64,783,473 76,273,254 II-1-3 Simitli Simitli 8,242 New 420 3,461,472 1,557,662 1,038,442 519,221 346,147 155,766 173,074 346,147 3,790,312 No info. 6.3 51,922 313 16,251,611 812,581 812,581 1,625,161 19,501,933 23,292,245 Sub-total II-1 93,619 25,209,297 11,344,184 7,562,789 3,781,395 2,520,930 1,134,418 1,260,465 2,520,930 27,604,180 380,390 129,600,551 6,480,028 6,480,028 12,960,055 155,520,662 183,124,842 II-2 New WWTPs and Improvements of SW in the Mesta River Basin II-2-1 Gotse Delchev Gotse Delchev 30,185 New 320 9,659,040 4,346,568 2,897,712 1,448,856 965,904 434,657 482,952 965,904 10,576,649 Improv. 4.1 123,756 335 41,458,411 2,072,921 2,072,921 4,145,841 49,750,093 60,326,742 II-2-2 Bansko Bansko 11,493 New 400 4,597,320 2,068,794 1,379,196 689,598 459,732 206,879 229,866 459,732 5,034,065 Improv. 5.6 64,362 320 20,595,994 1,029,800 1,029,800 2,059,599 24,715,192 29,749,258 Sub-total II-2 41,678 14,256,360 6,415,362 4,276,908 2,138,454 1,425,636 641,536 712,818 1,425,636 15,610,714 188,119 62,054,404 3,102,720 3,102,720 6,205,440 74,465,285 90,075,999 II-3 New WWTPs and Improvements of SW in the Dospat River Basin II-3-1 Dospat Dospat 3,218 New 430 1,383,912 622,760 415,174 207,587 138,391 62,276 69,196 138,391 1,515,384 Improv. 7.3 23,494 300 7,048,296 352,415 352,415 704,830 8,457,955 9,973,339 Sub-total II-3 3,218 1,383,912 622,760 415,174 207,587 138,391 62,276 69,196 138,391 1,515,384 23,494 7,048,296 352,415 352,415 704,830 8,457,955 9,973,339 II-4 Renovation of the Existing WWTPs and Improvements of SW II-4-1 Pernik Pernik 121,350 Renovat 84 10,193,400 4,077,360 3,567,690 2,038,680 509,670 407,736 509,670 1,019,340 11,110,806 Improv. 2.7 327,645 445 145,802,025 7,290,101 7,290,101 14,580,203 174,962,430 186,073,236 II-4-2 Dupnitsa Dupnitsa 55,224 Renovat 175 9,664,200 3,382,470 3,865,680 1,932,840 483,210 338,247 483,210 966,420 10,485,657 Improv. 3.7 204,329 353 72,128,066 3,606,403 3,606,403 7,212,807 86,553,680 97,039,337 II-4-3 Radomir Radomir 21,621 Renovat 245 5,297,145 1,854,001 2,118,858 1,059,429 264,857 185,400 264,857 529,715 5,747,402 Improv. 4.3 92,970 328 30,494,258 1,524,713 1,524,713 3,049,426 36,593,110 42,340,512 Sub-total II-4 198,195 25,154,745 9,313,831 9,552,228 5,030,949 1,257,737 931,383 1,257,737 2,515,475 27,343,865 624,944 248,424,350 12,421,217 12,421,217 24,842,435 298,109,220 325,453,085 Total of II. 336,710 66,004,314 27,696,137 21,807,099 11,158,384 5,342,694 2,769,614 3,300,216 6,600,431 72,074,143 1,216,948 447,127,602 22,356,380 22,356,380 44,712,760 536,553,122 608,627,265 Total of I. and II. 278,124,454 Total of I. and II. 2,164,635,464 2,442,759,918

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Table 6.2.7 Estimated Operation and Maintenance Cost for the Proposed WWTPs and Sewer Improvements

New Construction or Renovation of the Improvement (including Expansion) or New WWTPs Sewerage Networks No. Town / Settlement Municipality PE in 2015 Total O&M Cost New or Improv. / Direct Cost O&M Cost Direct Cost O&M Cost Renovat. New (EUR) (EUR/year) (EUR) (EUR/year) (EUR) I. High Priority Towns and Settlements in EABD I-1 New WWTPs and Improvements of SW in the Maritsa River Basin I-1-1 Asenovgrad Asenovgrad 78,054 New 16,391,340 1,229,351 Improv. 99,409,574 1,491,144 2,720,494 I-1-2 Plovdiv Plovdiv 681,985 - 0 Improv. 460,340,010 4,603,400 4,603,400 I-1-3 Karlovo Karlovo 37,181 New 10,968,248 822,619 Improv. 50,565,480 758,482 1,581,101 I-1-4 Velingrad Velingrad 28,752 New 9,200,640 690,048 Improv. 39,255,106 588,827 1,278,875 I-1-5 Peshtera Peshtera 28,691 New 9,180,960 688,572 Improv. 39,171,140 587,567 1,276,139 I-1-6 Harmanli Harmanli 28,538 New 9,132,000 684,900 Improv. 38,962,249 584,434 1,269,334 I-1-7 Svilengrad Svilengrad 28,050 New 8,976,000 673,200 Improv. 38,181,660 572,725 1,245,925 I-1-8 Chirpan Chirpan 25,413 New 8,513,355 638,502 Improv. 35,222,418 528,336 1,166,838 I-1-9 Rakovski Rakovski 23,453 New 7,973,850 598,039 New 32,406,665 486,100 1,084,139 I-1-10 Panagyurishte Panagyurishte 23,029 New 7,829,955 587,247 Improv. 31,821,859 477,328 1,064,575 I-1-11 Parvomay Parvomay 22,200 New 7,548,000 566,100 Improv. 30,582,720 458,741 1,024,841 I-1-12 Stamboliyski Stamboliyski 18,068 New 6,865,650 514,924 Improv. 27,010,913 405,164 920,087 I-1-13 Kostenets Kostenets 11,048 New 4,364,118 327,309 Improv. 20,152,282 302,284 629,593 Sub-total I-1 1,034,460 106,944,116 8,020,809 943,082,074 11,844,531 19,865,340 I-2 New WWTPs and Improvements of SW in the Tundzha River Basin I-2-1 Yambol Tundzha 118,971 New 17,250,795 1,293,810 Improv. 135,329,513 2,029,943 3,323,752 I-2-2 Karnobat Karnobat 28,916 New 9,252,960 693,972 Improv. 39,478,332 592,175 1,286,147 I-2-3 Elhovo Elhovo 16,808 New 6,134,738 460,105 Improv. 26,139,024 392,085 852,191 I-2-4 Kalofer Karlovo 4,229 New 1,924,104 144,308 Improv. 9,103,761 136,556 280,864 Sub-total I-2 168,923 34,562,597 2,592,195 210,050,629 3,150,759 5,742,954 I-3 New WWTPs and Improvements of SW in the Arda River Basin I-3-1 Kardzhali Kardzhali 67,346 New 14,479,373 1,085,953 Improv. 87,468,881 1,312,033 2,397,986 Sub-total I-3 67,346 14,479,373 1,085,953 87,468,881 1,312,033 2,397,986 I-4 Renovation of the Existing WWTPs and Improvements of SW in EABD I-4-1 Nova Zagora Nova Zagora 36,185 Renovat. 5,065,830 542,768 Improv. 49,210,920 738,164 1,280,931 I-4-2 Radnevo Radnevo 20,691 Renovat. 5,069,295 543,139 Improv. 29,004,644 435,070 978,208 I-4-3 Ihtiman Ihtiman 20,234 Renovat. 4,957,208 531,129 Improv. 28,363,320 425,450 956,579 I-4-4 Pavel banya Pavel banya 4,407 Renovat. 1,487,363 148,736 Improv. 9,554,817 143,322 292,059 Sub-total I-4 81,516 16,579,695 1,765,772 116,133,701 1,742,006 3,507,777 Total of I. 1,352,245 172,565,780 13,464,728 1,356,735,285 18,049,329 31,514,057 II. High Priority Towns and Settlements in WABD II-1 New WWTPs and Improvements of SW in the Struma River Basin II-1-1 Petrich Petrich 45,020 New 11,254,875 844,116 Improv. 59,362,713 890,441 1,734,556 II-1-2 Sandanski Sandanski 40,358 New 10,492,950 786,971 Improv. 53,986,228 809,793 1,596,765 II-1-3 Simitli Simitli 8,242 New 3,461,472 259,610 No info. 16,251,611 243,774 503,385 Sub-total II-1 93,619 25,209,297 1,890,697 129,600,551 1,944,008 3,834,706 II-2 New WWTPs and Improvements of SW in the Mesta River Basin II-2-1 Gotse Delchev Gotse Delchev 30,185 New 9,659,040 724,428 Improv. 41,458,411 621,876 1,346,304 II-2-2 Bansko Bansko 11,493 New 4,597,320 344,799 Improv. 20,595,994 308,940 653,739 Sub-total II-2 41,678 14,256,360 1,069,227 62,054,404 930,816 2,000,043 II-3 New WWTPs and Improvements of SW in the Dospat River Basin II-3-1 Dospat Dospat 3,218 New 1,383,912 103,793 Improv. 7,048,296 105,724 209,518 Sub-total II-3 3,218 1,383,912 103,793 7,048,296 105,724 209,518 II-4 Renovation of the Existing WWTPs and Improvements of SW in WABD II-4-1 Pernik Pernik 121,350 Renovat. 10,193,400 1,274,175 Improv. 145,802,025 2,187,030 3,461,205 II-4-2 Dupnitsa Dupnitsa 55,224 Renovat. 9,664,200 1,035,450 Improv. 72,128,066 1,081,921 2,117,371 II-4-3 Radomir Radomir 21,621 Renovat. 5,297,145 567,551 Improv. 30,494,258 457,414 1,024,965 Sub-total II-4 198,195 25,154,745 2,877,176 248,424,350 3,726,365 6,603,541 Total of II. 336,710 66,004,314 5,940,894 447,127,602 6,706,914 12,647,808 Total 19,405,622 24,756,243 44,161,865

6.3

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Table 6.3.1 Water Supply Networks to be Improoved in Bulgaria

Existing Pipes for Water Supply Estimated Necessary Improvement of WS Pipes Number Served Informat. Replacement Physical Related Basin of Asbestos PVC + Engineering Administration No. WSS Co. Owner populat. by Steel (ST) Cast iron Other Total length Necessary Length of Pipe Unit Cost Direct Cost (A) Contingency Total Cost District municip. cement (AS) HDPE Cost (5% of A) Cost (5 % of A) WS Improve. (AS+ST) (10% of A) supplied (m) (m) (m) (m) (m) (m) (m) (m) (EUR / m) (EUR) (EUR) (EUR) (EUR) (EUR) 1 Burgas State BSBD 14 424,080 2,471,360 923,855 75,547 32,752 201,486 3,705,000 3,395,215 160 543,234,400 27,161,720 27,161,720 54,323,440 651,881,280 2 Dobrich State BSBD 8 225,987 2,975,000 181,000 4,000 52,000 52,000 3,264,000 3,156,000 160 504,960,000 25,248,000 25,248,000 50,496,000 605,952,000 3 Shumen State & Municp. BSBD 10 214,880 1,857,607 442,894 33,496 3,550 0 2,337,547 2,300,501 160 368,080,160 18,404,008 18,404,008 36,808,016 441,696,192 4 Varna State & Municp. BSBD 12 461,126 3,207,775 432,270 212,556 14,692 833,707 4,701,000 3,640,045 160 582,407,200 29,120,360 29,120,360 58,240,720 698,888,640 Sub-total 44 1,326,073 10,511,742 1,980,019 325,599 102,994 1,087,193 14,007,547 12,491,761 160 1,998,681,760 99,934,088 99,934,088 199,868,176 2,398,418,112 5 Pleven State DRBD 10 314,965 2,461,471 527,336 8,692 47,771 8,730 3,054,000 2,988,807 160 478,209,120 23,910,456 23,910,456 47,820,912 573,850,944 6 Razgrad State DRBD 5 133,122 1,271,700 306,720 6,200 5,480 0 1,590,100 1,578,420 160 252,547,200 12,627,360 12,627,360 25,254,720 303,056,640 7 Vidin State DRBD 11 149,382 1,432,572 100,621 29,636 92,968 0 1,655,797 1,533,193 160 245,310,880 12,265,544 12,265,544 24,531,088 294,373,056 8 Sofia-district State DRBD & EABD 21 218,509 2,289,400 751,400 16,600 32,400 206,200 3,296,000 3,040,800 160 486,528,000 24,326,400 24,326,400 48,652,800 583,833,600 9 Gabrovo State & Municp. DRBD 3 100,927 910,230 48,480 27,000 21,430 99,860 1,107,000 958,710 160 153,393,600 7,669,680 7,669,680 15,339,360 184,072,320 10 Isperih State & Municp. DRBD 3 47,727 500,900 171,100 31,800 0 31,200 735,000 672,000 136 91,716,307 4,585,815 4,585,815 9,171,631 110,059,569 11 Lovech State & Municp. DRBD 7 137,323 1,334,140 354,822 3,600 18,092 44,346 1,755,000 1,688,962 160 270,233,920 13,511,696 13,511,696 27,023,392 324,280,704 12 Montana State & Municp. DRBD 10 148,096 1,252,100 167,980 3,700 59,926 17,294 1,501,000 1,420,080 160 227,212,800 11,360,640 11,360,640 22,721,280 272,655,360 13 Russe State & Municp. DRBD 8 275,538 1,846,008 364,123 122,370 107,281 408,218 2,848,000 2,210,131 160 353,620,960 17,681,048 17,681,048 35,362,096 424,345,152 14 Silistra State & Municp. DRBD 7 142,786 1,707,308 47,280 24,661 72,555 0 1,851,804 1,754,588 160 280,734,080 14,036,704 14,036,704 28,073,408 336,880,896 15 Targovishte State & Municp. DRBD 3 99,205 1,313,615 65,576 2,156 2,559 22,094 1,406,000 1,379,191 160 220,670,560 11,033,528 11,033,528 22,067,056 264,804,672 16 Veliko Tarnovo State & Municp. DRBD 9 266,229 2,387,936 252,647 30,180 9,893 239,344 2,920,000 2,640,583 160 422,493,280 21,124,664 21,124,664 42,249,328 506,991,936 17 Vratsa State & Municp. DRBD 10 242,975 2,311,842 302,967 52,460 25,174 0 2,692,443 2,614,809 160 418,369,440 20,918,472 20,918,472 41,836,944 502,043,328 18 Berkovitsa Municipality DRBD 1 21,466 173 20,294 0 147 20,614 20,467 115 2,363,426 118,171 118,171 236,343 2,836,111 19 Botevgrad Municipality DRBD 1 41,203 282,943 32,191 0 2,300 317,434 315,134 131 41,365,560 2,068,278 2,068,278 4,136,556 49,638,672 20 Knezha Municipality DRBD 1 17,501 188,910 1,700 0 1,690 192,300 190,610 112 21,405,846 1,070,292 1,070,292 2,140,585 25,687,015 21 Kubrat Municipality DRBD 1 28,357 227,275 99,883 0 3,161 330,319 327,158 121 39,581,734 1,979,087 1,979,087 3,958,173 47,498,081 22 Sevlievo Municipality DRBD 40,989 551,755 38,388 0 6,811 596,954 590,143 131 77,363,144 3,868,157 3,868,157 7,736,314 92,835,773 23 Sofia City Municipality DRBD 1 1,177,577 878,000 1,105,000 812,000 455,000 3,250,000 1,983,000 160 317,280,000 15,864,000 15,864,000 31,728,000 380,736,000 24 Svishtov Municipality DRBD 1 50,000 360,000 80,000 0 20,000 460,000 440,000 138 60,852,440 3,042,622 3,042,622 6,085,244 73,022,928 25 Troyan Municipality DRBD Sub-total 113 3,653,877 23,508,278 4,838,508 1,171,055 984,638 1,077,286 31,579,765 28,346,786 157 4,461,252,298 223,062,615 223,062,615 446,125,230 5,353,502,757 26 Haskovo (*) State EABD 9 194,895 1,861,319 229,800 3,027 7,176 20,606 2,121,928 27,420 2,091,119 160 334,579,040 16,728,952 16,728,952 33,457,904 401,494,848 27 Pazardzhik State EABD 3 165,426 749,680 162,511 116 31,980 0 944,287 912,191 160 145,950,560 7,297,528 7,297,528 14,595,056 175,140,672 28 Plovdov State EABD 16 720,416 3,187,898 332,965 75,404 27,921 1,581,812 5,206,000 3,520,863 160 563,338,080 28,166,904 28,166,904 56,333,808 676,005,696 29 Smolyan State EABD 11 141,013 1,015,171 215,940 2,619 36,424 120,846 1,391,000 1,231,111 160 196,977,760 9,848,888 9,848,888 19,697,776 236,373,312 30 Stara Zagora State EABD 18 388,182 2,418,375 444,124 65,344 75,736 310,421 3,314,000 2,862,499 160 457,999,840 22,899,992 22,899,992 45,799,984 549,599,808 31 Yambol (*) State EABD 5 145,948 1,420,653 311,865 0 34,488 26,369 1,793,375 1,732,518 160 277,202,880 13,860,144 13,860,144 27,720,288 332,643,456 32 Dimitrovgrad State & Municp. EABD 1 64,981 465,000 36,000 20,300 16,698 0 537,998 501,000 150 75,293,186 3,764,659 3,764,659 7,529,319 90,351,823 33 Kardzhali (*) State & Municp. EABD 7 140,175 1,059,464 74,958 0 121,432 65,955 1,321,809 692,000 1,134,422 160 181,507,520 9,075,376 9,075,376 18,150,752 217,809,024 34 Sliven State & Municp. EABD 4 234,000 1,301,000 537,000 10,000 17,000 14,000 1,879,000 1,838,000 160 294,080,000 14,704,000 14,704,000 29,408,000 352,896,000 35 Batak Municipality EABD 1 7,000 66,000 15,000 0 1,500 82,500 81,000 104 8,415,981 420,799 420,799 841,598 10,099,177 36 Belovo Municipality EABD 1 12,000 45,000 3,000 0 1,200 49,200 48,000 108 5,179,248 258,962 258,962 517,925 6,215,098 37 Bratsigovo Municipality EABD 38 Panagyurishte Municipality EABD 1 31,000 76,000 60,000 0 2,000 138,000 136,000 123 16,741,736 837,087 837,087 1,674,174 20,090,083 39 Peshtera Municipality EABD 1 25,000 95,000 25,000 4,000 3,000 127,000 120,000 118 14,196,120 709,806 709,806 1,419,612 17,035,344 40 Rakitovo Municipality EABD 1 16,200 32,000 1,200 0 2,100 35,300 33,200 111 3,693,865 184,693 184,693 369,387 4,432,638 41 Strelcha Municipality EABD 1 6,000 46,020 23,610 0 10,070 79,700 69,630 103 7,178,923 358,946 358,946 717,892 8,614,707 42 Velingrad Municipality EABD 1 41,450 250,236 2,070 41,031 4,800 298,137 252,306 131 33,168,399 1,658,420 1,658,420 3,316,840 39,802,079 43 Sub-total 81 2,333,686 14,088,816 2,475,043 221,841 393,525 2,140,009 19,319,234 16,563,859 158 2,615,503,138 130,775,157 130,775,157 261,550,314 3,138,603,765 44 Blagoevgrad State WABD 10 219,629 947,639 416,836 9,226 35,055 19,244 1,428,000 1,364,475 160 218,316,000 10,915,800 10,915,800 21,831,600 261,979,200 45 Kyustendil (*) State & Municp. WABD 8 103,211 1,159,066 276,962 27,348 31,753 184,740 1,679,869 1,479,600 1,436,028 160 229,764,480 11,488,224 11,488,224 22,976,448 275,717,376 46 Pernik State & Municp. WABD 6 105,867 1,005,034 217,607 38,258 1,075 97,026 1,359,000 1,222,641 160 195,622,560 9,781,128 9,781,128 19,562,256 234,747,072 47 Breznik Municipality WABD 48 Dupnitsa Municipality WABD 1 51,715 113,718 89,644 16,273 9,949 229,584 203,362 140 28,404,181 1,420,209 1,420,209 2,840,418 34,085,017 49 Kovachevtsi Municipality WABD 50 Kresna Municipality WABD 51 Petrich Municipality WABD 1 65,000 310,290 9,970 700 3,300 324,260 320,260 150 48,135,398 2,406,770 2,406,770 4,813,540 57,762,478 52 Sandanski Municipality WABD 1 43,943 301,594 37,373 0 3,214 342,181 338,967 133 45,236,977 2,261,849 2,261,849 4,523,698 54,284,372 Sub-total 27 589,365 3,837,341 1,048,392 91,805 84,346 301,010 5,362,894 4,885,733 765,479,595 38,273,980 38,273,980 76,547,960 918,575,515 Total 265 7,903,001 51,946,177 10,341,962 1,810,300 1,565,503 4,605,498 70,269,440 62,288,139 158 9,840,916,791 492,045,840 492,045,840 984,091,679 11,809,100,149 Note: Estimated cost is without VAT. Data Source: 1) "Management and Development Strategy for Water Supply and Sewerage Sector in the Republic of Bulgaria", MoRDPW, 2004 2) WSS Companies with (*) mark and gray color are based on the answer to the questionnaires to the WSS Companies in EABD and WABD areas by the end of August 2007, which have been received by this Study.

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Table 6.3.2 Rehabilitation of Irrigation System List (EABD)

Intake structure: Irrigation Reservoir Pump station Other structures on the canal (number) Required cost for improvement (EURO) ITS canal Potential Suitable Type of rehabilitation Cost for rehabilitation 10 % design, Irrigation System: area area Priority Regional Branch IS_ID Total Distribution Distribution 5 % for control IS (dka=0.1ha (dka=0.1ha Name of intake Capacity Length Number of Volume Number of Siphon: Tunnel: Aqueduct: Renovation Rehabilitation TOTAL capacity points: structures: New Intake Lining of Machinery Electricity acuities, ) ) ( RI : River Intake , WI : Water Intake) (m3/s) (m) Dam (103 m3) Pump S T A ITS, DP, DS, ITS, DP, DS, Const. cost TOTAL cost (liter/sec) DP DS structure canal cost cost 10 % physical S, T, A S, A, T contingency Pazardzhik Topolnitsa 70 121,968 39,217 Lesichevo weir WI 15.0 117,738 1 137,000 0 0.0 317 0 22 0 12 0 4,500 3,154,550 10,646,583 13,805,633 655,970 400,000 14,861,603 3,715,401 18,577,004 Pazardzhik Aleko-Pazardzhik 73 240,353 111,750 Zlokuchene WI, Pasha ark WI 18.0157,5220021,490.0359025011040,6492,300,80011,316,51013,657,959305,34668,00014,031,3053,507,82617,539,131 Pazardzhik Karabunar 71 88,602 48,013 Momina klisura WI, Boshulsko dere WI 7.5168,4100000.041705822850,00027,3753,534,0007,264,94610,876,32183,07242,00011,001,3932,750,34813,751,741 Plovdiv Stryama-Chirpan 132 132,800 92,907 Ivan Vazovo WI 17.0 82,453 1 20 0 0.0 0 93 0 11 0 0 12,000 1,048,500 6,202,576 7,263,076 1,074,500 0 8,337,576 2,084,394 10,421,970 Potoka RI km8 + 300, WI of Kachana main 1 drianage channel-1 km 0+476, WI of Plovdiv Topolnitsa 130 365,757 274,789 Pelinitsa main drainage channel-1 km 10.7 213,796 5 213,300 0 0.0 375 8 48 0 63 50,000 164,440 3,922,500 15,085,136 19,222,076 80,900 5,500 19,308,476 4,827,119 24,135,595 2+986, WI main drainage channel-5 , Strelcha WI, Chernozem weir WI Sub Total 949,480 566,676 Sub Total 68.2 739,919 7 350,320 2 1,490.0 1,468 101 153 13 114 100,000 248,964 13,960,350 50,515,751 64,825,065 2,199,788 515,500 67,540,353 16,885,088 84,425,441 Haskovo Trakiets 186 136,899 70,568 N/A 0.0 128,790 2 115,260 2 1,925.0 228 0 21 3 19 0 43,250 1,575,900 6,770,818 8,389,968 26,000 31,000 8,446,968 2,111,742 10,558,710 Plovdiv Karavelovo 125 19,549 11,357 N/A 0.0 18,133 2 5,600 1 48.0 43 0 6 0 2 0 25,825 98,200 372,502 496,527 1,225 500 498,252 124,563 622,815 Plovdiv Plovdiv 127 68,666 51,377 Polatovo weir 10.067,5560003,000.08007010150,00038,500599,5004,309,4175,097,4177,45005,104,8671,276,2176,381,084 Plovdiv Rozino 126 7,196 1,000 Saraysoyu WI 0.310,5070000.0240200 022,00065,500251,015338,5150 0338,51584,629423,144 Binkos weir intake,Mechkarevo weir, The Sliven Sredna Tundzha 155 331,168 256,983 47.0 198,801 0 400,000 6 4,390.0 213 3 23 4 14 0 41,299 3,571,330 19,809,165 23,439,794 1,275,570 19,500 24,714,864 6,178,716 30,893,580 2 bridge of Samuilovo intake Saltachnitsa RI, Stara RI, Maglizhka RI, Stara Zagora Stara Zagora 169 355,606 337,677 Dabovska RI, Tundzha RI (serving Yagoda 0.8222,4000033,965.049157501127,00049,9003,370,50021,265,44124,712,84171,800106,22024,890,8616,222,71531,113,576 PS) , Suytliyka RI Yambol Sredna Tundzha 243 141,216 136,679 N/A 0.0 21,575 1 855 0 0.0 12 0 1 0 8 0 10,000 341,000 2,210,503 2,561,503 40,000 0 2,601,503 650,376 3,251,879 Sub Total 1,060,300 865,641 Sub Total 58.1 667,762 5 521,715 12 13,328.0 1,091 8 135 7 64 177,000 230,774 9,621,930 54,988,861 65,036,565 1,422,045 157,220 66,595,830 16,648,958 83,244,788 Burgas Tserkovski 6 6,362 3,664 Azmak RI 2.08,66016,50000.040300 012,00051,600340,941404,5410 0404,541101,135505,676 Burgas Kayabash 8 26,105 24,970 N/A 0.0 15,911 6 12,266 0 0.0 10 0 0 0 6 0 22,000 99,200 738,068 859,268 5,000 2,500 866,768 216,692 1,083,460 Haskovo Brod IA 197 6,687 N/A 0.07,7400011,400.0290200 0 0169,000175,974344,97452,00056,000452,974113,244566,218 Haskovo Ezerovo IA 195 11,704 4,144 Varbishka RI 0.7 17,231 1 5,500 0 0.0 26 0 3 0 4 0 18,000 82,000 463,746 563,746 11,000 0 574,746 143,687 718,433 Haskovo Dimitrovgrad IA 198 1,557 N/A 0.08900011,000.010210 04,000115,00034,000153,00027,00038,000218,00054,500272,500 Haskovo Trakiets-VІІ 193 65,387 64,387 Banska RI 0.80125,00062,810.000000 017,000295,8000337,80044,800192,400575,000143,750718,750 Haskovo Garvanovo IA 194 8,035 7,001 N/A 0.00002918.000000 0 020,000020,0002,00015,00037,0009,25046,250 Haskovo Bolyartsi IA 241 2,000 2,000 N/A 0.00126000.000000 0 0 0 02,6000 02,6006503,250 Haskovo Nevestino IA 234 506 506 N/A 0.01,898071140.000000 08,50066,000074,500018,00092,50023,125115,625 Haskovo Zvinitsa IA 224 4,282 4,282 N/A 0.0011,23000.000000 0 059,000059,00050,0005,000114,00028,500142,500 Haskovo Prileptsi IA 230 3,870 3,870 N/A 0.00002680.000000 05,00017,000022,0005,5004,00031,5007,87539,375 Haskovo Daskalovo-Yavoritsa IA 222 1,700 N/A 0.00137100.000000 0 0 0 03,7100 03,7109284,638 Haskovo Petelovo IA 220 3,805 3,341 N/A 0.00270500.000000 0 025,000025,0005,000030,0007,50037,500 Haskovo Minzuhar IA 227 1,593 1,593 N/A 0.00156000.000000 0 0 0 05,6000 05,6001,4007,000 Haskovo Dyadovsko IA 228 2,548 2,548 N/A 0.00154400.000000 08,0000 08,0005,000013,0003,25016,250 Haskovo Zagorsko IA 236 570 440 N/A 0.0000184.000000 0 016,500016,50016,000032,5008,12540,625 Haskovo Iskril IA 237 1,250 1,250 N/A 0.0000156.000000 0 070,000070,00025,00025,000120,00030,000150,000 Haskovo Dobromirtsi-Benkovski 232 15,383 15,383 N/A 0.044318,00000.000005 08,00048,00017,19973,19915,000088,19922,050110,249 Haskovo Parvitsa IA 233 2,698 2,298 Drainage WI Parvitsa 0.20001100.000000 06,00040,000046,00010,00030,00086,00021,500107,500 Haskovo Gruevo IA 235 1,645 1,645 N/A 0.00001210.000000 0 096,000096,00021,00025,000142,00035,500177,500 Haskovo Momina salza IA 238 1,060 910 N/A 0.00117500.000000 0 0 0 02,0000 02,0005002,500 Haskovo Nanovitsa IA 226 3,400 3,400 N/A 0.0021,02500.000000 0 020,000020,0000 020,0005,00025,000 Haskovo Lale IA 225 2,350 2,350 Drainage WI Nanovishka river 100.001350184.000000 05,0000 08,5000 08,5002,12510,625 Haskovo Karamfil-Sindeltsi IA 223 1,875 1,570 N/A 0.00157200.000000 05,0000 05,0000 05,0001,2506,250 Haskovo Kamenyane IA 240 800 800 Drainage WI Krumovitsa river 60.00002104.000000 05,00060,000065,00016,00024,000105,00026,250131,250 Haskovo Strandzhevo IA 221 3,820 3,820 N/A 0.00001342.000000 0 024,000024,00012,0002,00038,0009,50047,500 Haskovo Knizhovnik IA 188 8,390 3,146 N/A 0.0 9,386 1 2,516 0 0.0 25 0 4 0 0 0 12,000 140,400 242,236 394,636 20,000 0 414,636 103,659 518,295 Haskovo Sirakovo IA 189 5,220 3,840 N/A 0.01,81112,17200.020000 0 017,50045,46762,96710,000072,96718,24291,209 Haskovo Mandra IA 187 4,640 4,640 N/A 0.0011,49800.000000 03,000111,0000114,00010,0000124,00031,000155,000 Haskovo Krivo pole IA 190 8,660 8,660 N/A 0.0012,8201354.000000 010,00015,200025,2007,10011,00043,30010,82554,125 Haskovo Gledka IS 191 6,640 N/A 0.0012,32000.000000 0 031,100031,10010,000041,10010,27551,375 Haskovo Troyan-Navasen 202 10,640 N/A 0.0016,0002572.000000 0 0203,0000263,00040,00081,000384,00096,000480,000 Haskovo Polyanovo 204 10,970 10,970 N/A 0.00081800.000000 05,000130,0000135,00050,00050,000235,00058,750293,750 Haskovo Izvorovo 201 11,490 7,348 N/A 0.0013,81000.000000 06,00022,000028,00012,0005,00045,00011,25056,250 Haskovo Dositeevo 200 30,482 26,255 N/A 0.0019,00011,350.000000 0 0150,0000240,00040,00070,000350,00087,500437,500 Haskovo Oreshets 203 7,400 7,400 N/A 0.0001200.000000 06,0000 06,0000 06,0001,5007,500 3 Haskovo Preslavets 205 8,451 N/A 0.012,0000011,050.080300 0 0127,000371,325498,32525,00030,000553,325138,331691,656 Haskovo Harmanli-greenhouse 207 1,880 N/A 0.03,950001245.0120000 0 048,00070,225118,2255,00020,000143,22535,806179,031 Haskovo Harmanli drop 206 936 N/A 0.0000164.000000 0 040,000040,00010,00025,00075,00018,75093,750 Haskovo Biser 209 35,377 10,590 N/A 0.0 42,832 3 2,070 1 1,660.0 31 0 7 0 1 0 0 230,000 2,122,076 2,363,776 10,000 0 2,373,776 593,444 2,967,220 Haskovo Novo selo 211 9,006 N/A 0.08,160051880.0480100 03,000209,000255,062467,06230,00050,000547,062136,766683,828 Haskovo Momkovo 212 17,091 5,572 N/A 0.012,0490011,260.010500 0 078,500340,471418,9715,0000423,971105,993529,964 Haskovo Svilengrad 210 1,980 N/A 0.03,3400000.0120001 0 016,00062,31578,3150 078,31519,57997,894 Haskovo Lyubimets-1 217 8,100 N/A 0.07,600001800.0140200 0 060,000207,920267,9200 0267,92066,980334,900 Haskovo Gugutka 215 3,583 1,188 Arpa dere RI 280.00001280.000000 010,00020,000030,0005,00010,00045,00011,25056,250 Haskovo Dolno Lukovo 216 895 895 N/A 0.00001130.000000 0 0 0 0 0 0 0 0 0 0 Haskovo Mandaritsa 219 1,411 N/A 0.00001200.000000 0 080,000080,00030,00030,000140,00035,000175,000 Haskovo Bunarcha-Kapitan 208 4,720 2,932 N/A 0.0012,33600.000000 0 0 0 023,3600 023,3605,84029,200 Pazardzhik Varvara 72 73,517 37,210 Vetren dol WI, Eli dere RI 5.264,1040000.0183039023051,081907,0003,181,0674,139,14829,76504,168,9131,042,2285,211,141 Kleptuza WI, Velingrad-2 PS WI, Manerovi Pazardzhik Velingrad 75 17,582 6,664 1.3 61,484 1 1,105 1 990.0 70 0 34 0 12 30,000 22,401 512,820 1,807,422 2,372,643 37,611 43,000 2,453,254 613,314 3,066,568 skali WI Pazardzhik Peshtera 74 35,968 18,959 Gerena WI, Kozarski ark WI, GG 0.036,3370000.097030220,00020,900245,5001,255,2871,541,6874,44001,546,127386,5321,932,659 Plovdiv Domlyan 128 70,816 35,494 Kurtovo WI 7.5 57,244 3 28,914 0 0.0 82 0 13 3 11 0 66,620 585,000 2,933,579 3,585,199 1,000 1,060 3,587,259 896,815 4,484,074 Plovdiv Chaya 1233 57,237 32,458 N/A 0.0 78,119 1 70 0 0.0 179 0 7 0 0 0 12,000 591,800 4,006,432 4,610,232 60,000 0 4,670,232 1,167,558 5,837,790 Plovdiv Popovitsa 1246 38,484 24,751 Cherkezitsa WI 1.239,9640024,600.59901702 0 0480,0001,637,5892,117,589050,0002,167,589541,8972,709,486 Plovdiv Sushitsa 1232 19,925 15,465 N/A 0.04,75014,60000.080100 0 0106,000175,449281,44950,00015,000346,44986,612433,061 Plovdiv Bryagovo 1242 29,519 16,669 N/A 0.0 25,466 1 9,050 0 0.0 57 0 7 0 0 0 7,000 239,500 1,022,899 1,269,399 10,000 0 1,279,399 319,850 1,599,249 Plovdiv Vacha 122 115,852 75,385 Krichim WI, Bash weir WI 68.5128,2500000.022932504 030,0001,430,5008,267,7139,728,21390,00030,0009,848,2132,462,05312,310,266 Plovdiv 40-te izvora 1231 27,495 27,253 N/A 0.0 13,202 1 3,800 0 0.0 45 0 2 0 0 0 3,000 139,000 487,934 667,934 0 0 667,934 166,984 834,918 Plovdiv Lenovo 1244 26,178 23,228 N/A 0.0 12,250 2 7,780 0 0.0 26 0 10 0 0 0 0 133,000 1,415,000 1,625,800 0 0 1,625,800 406,450 2,032,250 Plovdiv Mechka 1243 35,238 14,023 N/A 0.0 19,578 1 6,800 1 0.0 24 0 16 0 0 0 5,200 257,900 767,852 1,030,952 0 0 1,030,952 257,738 1,288,690 Plovdiv Parvomay 124 46,451 24,254 Beliya kamak WI 1.2 30,934 2 229 2 4,460.0 43 0 11 0 1 0 26,000 259,500 1,045,874 1,331,374 50,000 0 1,381,374 345,344 1,726,718 Sofia Ihtiman gravity 162 39,013 39,013 Baba RI (to B. dere) 1.2 21,578 1 11,100 0 0.0 12 0 0 8 0 0 8,000 92,000 783,212 894,212 0 0 894,212 223,553 1,117,765 Stara Zagora Dobri Dol 171 13,279 10,854 N/A 0.03,22813,46541,754.000200 027,000130,000126,543283,54379,80037,500400,843100,211501,054 Stara Zagora Naydenovo 173 2,412 1,395 N/A 0.0 6,203 1 800 0 0.0 20 0 0 0 0 0 11,400 22,000 120,526 153,926 2,000 0 155,926 38,982 194,908 Stara Zagora Dolno Novo Selo 174 3,888 3,138 N/A 0.0 6,000 1 1,200 1 50.0 12 0 2 0 0 0 4,000 20,000 96,126 132,126 0 0 132,126 33,032 165,158 Stara Zagora IP-Chirpan PS IA 172 3,590 602 N/A 0.00145500.000000 0 0 0 04,5500 04,5501,1385,688 Stara Zagora Yulievo 170 6,381 6,381 N/A 0.02,896001630.050101 0 074,200180,000254,2003,600200258,00064,500322,500 Yambol Bolyarovo 246 49,754 49,754 N/A 0.04,573244,86000.020100 012,00044,400317,051373,4516,0003,000382,45195,613478,064 Yambol Elhovo 245 39,954 22,120 Popovska RI 2.029,915112,60041,550.060210 019,60096,270856,098971,96841,35025,6201,038,938259,7351,298,673 Yambol Yambol 244 23,419 23,419 Zaporna vrata intake 5.0 37,635 1 2,770 1 1,000.0 15 0 1 1 0 0 8,600 129,500 1,848,501 1,989,601 6,000 0 1,990,601 497,650 2,488,251 Sub Total 1,154,906 758,097 Sub Total 536.8 837,611 56 237,229 53 32,607.5 1,437 3 226 14 73 50,000 513,302 9,598,690 37,819,179 48,354,991 1,112,966 1,024,280 50,487,237 12,621,809 63,109,046

Total 3,164,686 2,190,414 Total 663.0 2,245,292 68 1,109,264 67 47,426 3,996 112 514 34 251 327,000 993,040 33,180,970 143,323,791 178,216,621 4,734,799 1,697,000 184,623,420 46,155,855 230,779,275

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Table 6.3.3 Rehabilitation of Irrigation System List (WABD)

Intake structure: Irrigation Reservoir Pump station Other structures on the canal (number) Required cost for improvement (EURO) ITS canal Potential Suitable Type of rehabilitation Cost for rehabilitation 10 % design, Irrigation System: Distributio Priority Regional Branch IS_ID area area Total Distributio 5 % for control IS Name of intake Capacity Length Number of Volume Number of n Siphon: Tunnel: Aqueduct: Renovation Rehabilitation TOTAL dka dka capacity n points: New Intake Lining of Machinery Electricity acuities, ( RI : River Intake , WI : Water Intake) (m3/s) (m) Dam (103 m3) Pump structures: S T A ITS, DP, DS, ITS, DP, DS, Const. cost TOTAL cost (liter/sec) DP structure canal cost cost 10 % physical DS S, T, A S, A, T contingency Gospodintsi village water intake, Tufcha Gotse Delcev Gotse Delchev 56 50,818 39,130 river intake-MIC-4, Toplika river intake- 19.4 85,910 0 0 1 280 114 0 14 6 10 0 5,000 793,500 4,325,100 5,123,600 25,000 7,500 5,156,100 1,289,025 6,445,125 MIC-8 and MIC-9 Pernik Svircha IC IA 91 614 614 Svircha water intake 0.1 6,357 0 0 0 0 10 0 0 0 0 0 5,300 59,500 65,189 129,989 32,000 0 161,989 40,497 202,486 Pernik Dragovishtitsa 99 13,562 10,657 Dragovishtitsa water intake 2.5 33,490 1 150 0 0 66 0 2 0 1 0 4,000 232,500 1,308,088 1,544,588 113,000 12,000 1,669,588 417,397 2,086,985 Pernik Yamborano IA 85 2,038 1,831 N/A 0.0 9,052 0 0 0 0 28 0 4 0 0 0 10,000 60,000 212,782 282,782 7,500 0 290,282 72,571 362,853 Pernik Stensko PS IA 101 1,141 874 Stensko water intake 0.4 5,112 0 0 1 400 37 0 1 0 0 0 4,000 68,000 95,402 167,402 6,000 500 173,902 43,476 217,378 Pernik Razhdavitsa PS IA 81 1,933 1,609 Razhdavitsa PS water intake 0.4 5,031 0 0 1 440 17 0 1 0 0 0 10,000 47,000 90,972 147,972 11,500 0 159,472 39,868 199,340 Kopilovski gravity Pernik 87 5,913 5,913 3.0 19,567 0 0 1 2,100 25 0 7 0 0 0 45,000 520,000 569,706 1,134,706 132,000 200,000 1,466,706 366,677 1,833,383 channel IC IA Struma water intake Pernik Konyavo IC IA 110 5,858 5,858 Konyavski gravity channel water intake 1.4 19,391 0 0 0 0 51 0 2 0 0 0 13,000 131,000 698,086 842,086 0 0 842,086 210,522 1,052,608 Pernik Dolna Grashtitsa PS IA 88 1,430 N/A 0.0 267 0 0 0 0 0 0 0 0 0 0 0 5,000 0 5,000 0 0 5,000 1,250 6,250 Pernik Katrishte PA IA 89 1,755 Girchevtsi water intake 2.0 3,205 0 0 2 1,090 7 0 0 0 0 0 0 278,500 90,000 368,500 24,000 176,500 569,000 142,250 711,250 Pernik Lozno IA PS 84 2,100 2,100 Nov chiflik PS water intake 0.2 0 0 0 1 230 0 0 0 0 0 0 12,000 49,000 0 61,000 28,000 17,000 106,000 26,500 132,500 1 Pernik Nevestino PS IA 83 1,396 896 Nevestino PS water intake 0.8 3,835 0 0 1 615 11 0 1 0 0 0 15,200 21,500 65,244 101,944 18,000 0 119,944 29,986 149,930 Pernik Chetirtsi PS IA 108 849 609 Chetirtsi PS water intake 0.4 960 0 0 1 100 2 0 0 0 0 100,000 0 48,400 19,704 168,104 17,000 11,000 196,104 49,026 245,130 Gorna Grashtitsa Pernik 100 1,521 1,521 0.0 1,839 1 200 0 0 16 0 0 0 0 0 9,000 19,000 21,862 49,862 11,200 0 61,062 15,266 76,328 reservoir IA N/A Pernik Nikolichevska vada IC 104 100 100 N/A 0.0 1,858 0 0 0 0 3 0 0 0 0 0 0 6,000 20,289 26,289 0 0 26,289 6,572 32,861 Pernik Dromuharska vada IC IA 105 248 248 N/A 0.0 5,110 0 0 0 0 5 0 0 0 0 0 0 8,000 72,144 80,144 0 0 80,144 20,036 100,180 Pernik Drenov dol IA 96 12,288 8,180 Banska river water intake 1.0 11,277 2 3,505 0 0 2 0 0 0 0 0 13,000 34,000 198,757 245,757 30,000 0 275,757 68,939 344,696 Pernik Bersin-Bagrentsi IA 86 20,193 18,544 M-1 Bersin water intake, Granitsa water 0.5 46,111 2 6,800 0 0 142 0 13 0 0 20,000 10,000 313,500 1,036,696 1,380,196 56,700 3,000 1,439,896 359,974 1,799,870 Pernik Belia kamak IC IA 107 241 161 N/A 0.0 13,717 0 0 0 0 7 0 0 0 0 0 2,000 35,500 133,822 171,322 1,800 0 173,122 43,281 216,403 Water intake to HPP Sandanski Sandanski Sandanska Bistritsa 154 37,495 31,754 0.0 68,160 1 960 1 800 73 0 0 6 0 0 23,775 243,000 1,910,255 2,177,030 122,400 5,000 2,304,430 576,108 2,880,538 compensating basin Sandanski Mendovo-Kavrakirovo 146 3,080 3,080 N/A 0.0 8,500 0 0 0 0 0 0 1 4 0 0 0 36,000 242,576 278,576 12,700 0 291,276 72,819 364,095 Sandanski Strumeshnitsa 147 12,733 7,500 Water intake Petrich MIC 1.5 14,608 0 0 0 0 9 0 1 4 8 0 0 165,000 577,596 742,596 20,450 0 763,046 190,762 953,808 Sub Total 177,306 141,179 Sub Total 33.7 363,357 7 11,615 10 6,055 625 0 47 20 19 120,000 181,275 3,173,900 11,754,270 15,229,445 669,250 432,500 16,331,195 4,082,799 20,413,994 Blazhievski IC water itnake, Usoyski IC water intake, Polski reservoir IC water Dupnitsa Boboshevo 61 15,873 12,574 intake, Buranovo PS water intake, 3.1 35,710 0 0 3 1,450 127 0 6 2 8 42,000 52,000 373,000 853,719 1,320,719 28,000 0 1,348,719 337,180 1,685,899 Mursalevo PS water intake Gl. Rilski IC water intake, Drachka ditch IC Dupnitsa Rila 62 27,330 23,614 water intake, Glaven Porominovski IC 3.5 43,106 0 0 0 0 98 0 12 13 12 82,000 10,000 314,000 1,405,913 1,811,913 0 0 1,811,913 452,978 2,264,891 water intake Arakchiyski IC water intake, Glaven Dupnitsa Dupnitsa 60 26,526 16,807 1.2 35,226 0 0 0 0 71 1 8 17 4 76,000 2,500 216,000 759,748 1,054,248 0 0 1,054,248 263,562 1,317,810 Gyurgevski IC water intake Bistritsa derivation water intake, Otovitsa Dupnitsa Dyakovo reservoir 59 18,234 18,234 3.4 36,955 1 35,400 0 0 4 4 5 8 6 0 20,000 515,000 250,636 785,636 69,000 0 854,636 213,659 1,068,295 2 river intake Lyav Blagoevgrad MIC water intake, Tuhlarska ditch IC water intake, Tsentralna Dupnitsa Blagoevgrad 63 16,029 15,129 ditch IC water intake, Water intake to Belo 2.3 22,500 0 0 4 2,155 27 0 2 0 3 190,000 25,500 99,000 499,902 814,402 11,840 2,500 828,742 207,186 1,035,928 pole PS , Zelen dol PS water intake, Gotse Delcev Razlog 58 28,692 18,428 N/A 4.6 24,290 1 110 0 0 92 0 4 0 0 0 0 202,000 629,365 831,365 2,000 0 833,365 208,341 1,041,706 Sandanski Pirinska Bistritsa 150 38,721 38,721 MIC Pirinska Bistritsa water intake 0.0 73,433 0 0 1 700 174 0 15 4 23 0 14,600 914,380 2,978,351 3,907,331 62,000 0 3,969,331 992,333 4,961,664 Sandanski Kozhuh 145 16,128 14,000 N/A 0.0 9,800 0 0 1 1,400 11 0 1 0 0 0 0 72,100 399,489 471,589 13,500 1,600 486,689 121,672 608,361 Sandanski Valtata 148 4,738 4,738 N/A 0.0 0 1 900 0 0 0 0 0 0 0 0 0 14,000 0 14,000 14,000 0 28,000 7,000 35,000 Sandanski Svoboda 144 10,100 10,100 N/A 0.0 9,460 0 0 1 2,000 0 0 2 1 10 0 0 81,600 227,678 309,278 17,300 0 326,578 81,645 408,223 Sub Total 202,371 172,345 Sub Total 18.0 290,480 3 36,410 10 7,705 604 5 55 45 66 390,000 124,600 2,801,080 8,004,801 11,320,481 217,640 4,100 11,542,221 2,885,555 14,427,776 Dupnitsa Leshko 64 31,825 28,512 N/A 0.0 9,050 0 0 0 0 3 0 4 0 0 0 0 65,000 426,385 491,385 300 0 491,685 122,921 614,606 Gotse Delcev Ablanitsa 57 2,500 1,950 N/A 0.4 0 0 0 1 350 0 0 0 0 0 0 0 30,000 0 30,000 0 30,000 60,000 15,000 75,000 Pernik Begunovtsi IA 109 3,000 3,000 Begunovtsi reservoir water intake 0.4 1,658 2 1,554 0 0 0 0 2 0 0 0 19,500 14,500 37,307 71,307 0 0 71,307 17,827 89,134 Pernik Dolna Dikanya 76 27,379 25,879 N/A 0.0 4,000 1 7 0 0 0 0 1 0 0 0 3,000 176,500 128,960 308,460 0 0 308,460 77,115 385,575 Pernik Izvor 77 18,917 17,817 Izvor reservoir water intake 0.0 10,700 1 7 0 0 14 0 0 0 0 0 10,000 288,000 354,642 652,642 3,000 0 655,642 163,911 819,553 3 Pernik Pchelina 79 18,167 18,167 N/A 0.0 24,761 2 55,325 1 4,125 0 0 11 2 2 0 1,000 385,000 1,631,556 2,028,806 0 0 2,028,806 507,202 2,536,008 Pernik Yardzhilovtsi 78 8,003 8,003 Yardzhilovtsi water intake 0.8 0 1 1 1 786 0 0 0 0 0 0 3,000 19,000 0 22,000 0 0 22,000 5,500 27,500 Sandanski Ograzhden 153 4,360 4,360 N/A 0.0 19,960 0 0 1 200 40 0 17 0 0 0 0 250,000 692,016 942,016 10,000 0 952,016 238,004 1,190,020 Sandanski Asen Itov 152 13,555 13,555 N/A 0.0 29,540 0 0 2 1,700 35 0 10 3 4 0 11,020 214,000 899,907 1,124,927 61,000 0 1,185,927 296,482 1,482,409 Sub Total 127,706 121,243 Sub Total 1.5 99,669 7 56,895 6 7,161 92 0 45 5 6 0 47,520 1,442,000 4,170,773 5,671,543 74,300 30,000 5,775,843 1,443,961 7,219,804 Total 507,383 434,767 Total 53.2 753,506 17 104,919 26 20,921 1,321 5 147 70 91 510,000 353,395 7,416,980 23,929,844 32,221,469 961,190 466,600 33,649,259 8,412,315 42,061,574

6.4

6.5

6.6

6.7

6.8

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Table 6.8.1 Summary of the Proposed Programme of Measures for Water Quality

and Water Quantity Improvement and Management

Measures

To ensure stable monitoring, selection of Key Key of selection monitoring, stable ensure To and Stations / Zones Monitoring Important and with measure municipalities. stage-wise and building Capacity monitoring new the of implementation program. Quality control program to be formulated and implemented. From Industries andAnimal Big Breeding Firms. pilot some start from to Recommendable works. municipalities for monitoring

• • • • • Review and improvement of water use permission permission use water of improvement and Review for optimum wateruse. volume. intake water of Monitoring/measurement water for required data of quality of Improvement management. Improvement of surface monitoring system system for of surfacewater monitoring Improvement quality. quality water for municipality with Cooperation management. Strengthening of regulation for wastewater discharge.

1) 2) 3) 3) 1) 2)

mil. 3towns 4towns 6 towns 609 17 towns EUR 72 mil. EUR EUR. 20 mil. mil. 20 EUR. EUR. 84 mil. mil. 84 EUR. EUR 206 mil. mil. 206 EUR

537 EUR. mil. EUR. 1834 mil. mil. 1834 EUR. EUR. 1628 mil. mil. 1628 EUR. of Measures for Water Quality and Water Quality and Water Water for of Measures Year 2011 to 2018 2018 to 2011 Year 2018 to 2011 Year

about m 62,288, 000

million 11,809 EUR about

Measures Non-structural

and Management Quantity Improvement Sub-total: EUR. Sub-total:

5 Irrigation Systems in 3 Irrigation Branches. Cost: Construction WWTPs (New & Renovation):WWTPs (New Networks: Sewer WWTPs (new & renovation): & renovation): (new WWTPs networks: Sewer Whole Bulgaria:Whole cost: Total 5 Irrigation Systems in 3 Irrigation Branches. Cost: Construction Construction Cost Cost Construction Improve. / Expansion / New Sewer Networks: Sewer / /New Improve. Expansion 9 towns Construction cost cost Construction WWTPs:New Renovationthe of existingWWTPs: Improve. / expansion / new sewer networks: 22 towns New WWTPs:New Renovationthe of existingWWTPs: WABD EABD WABD high priority towns towns priority high WABD EABD high priority towns towns priority high EABD Replacement of water supply pipes

• • • • • • • • • • • • • •

3) 3) schedule: Implementation 2) 3) 3) schedule: Implementation 2) 2) Long-term and to be started as soon as possible. possible. 2) as soon as started be to and Long-term 1) 1) facilities: distribution and transfer water intake, of Improvement 1)

Programme 6.8.1 Summary of the Proposed

Table

Structural Category

Systems Systems Systems

and Management and Management

1. Improvement Quality Water Improvement Quantity 2. Water 2.1 Supply Water of Improvement Irrigation of Improvement 2.2

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