Report
Reference
Database of useful data for SWAT modelling and report on data availability and quality for hydrological modelling and water quality
modeling in the Black Sea Catchments
HANGANU, Jenica, et al.
Abstract
This document reports on data availability and quality for hydrological modeling and water quality modeling in the Black Sea Catchments. The report gives an overview of different hydrological models such as Soil Water Assessment Tool (SWAT) that is our selected tool for hydrological modeling and water quality modeling in the Black Sea Catchments, followed by Delft3D a 2D/3D modeling program, SOBEK, MONERIS, and Qualitative Reasoning (QR) models. The main hydrological projects developed in the regions are also described in order to benefit from existing modeling data suitable also for SWAT model. In the partners' contribution chapter, each partner gives an overview of meteorological, hydrological and other SWAT data it can contribute or may be collected from the official owners. It is concluded that Ukraine, Romania and Hungary territory is well covered with SWAT needed data from enviroGRIDS partners, other data for the rest of the area as upstream of Danube Catchments are mostly available through ICPDR or at Global, European and regional database repositories.
HANGANU, Jenica, et al. Database of useful data for SWAT modelling and report on data availability and quality for hydrological modelling and water quality modeling in the Black Sea Catchments. 2010, 47 p.
Available at:
http://archive-ouverte.unige.ch/unige:79003
Disclaimer: layout of this document may differ from the published version.
Database of useful data for SWAT modelling and report on data availability and quality for hydrological modelling and water quality modeling in the Black Sea Catchments
Title Database of useful data for SWAT modeling and report on data availability and quality for hydrological modeling and water quality modeling in the Black Sea Catchments
Creator Jenica Hanganu (DDNI), Anthony Lehmann (UNIGE), Yevgen Makarovskiy (USRIEP), Mikhail Kornilov (DHMO), Ann van Griensven (UNESCO-IHE), Volodymyr Medinets (ONU),
Zsolt Mattányi (VITUKI), Viorel Chendes (INHGA) Creation date 01.07.2010
Date of last revision 30.11.2010
Subject Data available for SWAT modeling, data quality, data access
Status Validated
Type Word document
Description Report on data availability and quality for hydrological modeling and water quality modeling in the Black Sea Catchment hydrological modeling.
Contributor(s) DDNI, EAWAG, DHMO, IHE, USRIEP, ONU, VITUKI, NIMH, UNIGE, INHGA.
Rights Restricted to other programme participants (including the Commission Services)
Identifier enviroGRIDS_D41
Language English
Relation 1. EnviroGRIDS Gap analysis repot (D2.6)
2. EnviroGRIDS Existing scenarios and data compilation (D3.4) 3. EnviroGRIDS Report from survey on GEO BSC OS (D6.2) 4. Data use and integration guideline (D2.3)
5. EnviroGRIDS remote sensing data use and integration guideline (D2.4)
ABBREVIATIONS AND ACRONYMS
BASHYT Basin Scale Hydrologic Toolkit
BS Black Sea
BSC-OS Black Sea Catchment – Observation System
DDNI Danube Delta National Institute for Research & Development
DEM Digital Elevation Model
DHMO Danube Hydrometeorological Observatory, Ukraine
EAWAG Swiss Federal Institute of Aquatic Science and Technology
EG enviroGRIDS project
EGEE network Enabling Grids for E-science network
EO Earth Observation
GEO Group on Earth Observation
GEOSS Global Earth Observation System of Systems
GDP Gross Domestic Product
GIS Geographic Information System
GRDC Global Runoff Database Centre
ICPDR International Commission for the Protection of the Danube River
IHE Institute for Water Education
IHP International Hydrological Programme
INHGA National Institute of Hydrology and Water INSPIRE Infrastructure for Spatial Information in Europe
NIMH National Institute of Meteorology and Hydrology, Sofia (Bulgaria
OGC Open Geospatial Consortium
ONU Odessa National I.I. Mechnikov University
RBIS River Basin Information System
SDI Spatial Data Infrastructure
SEE programme South East Europe
SWAT Soil and Water Assessment Tool
UNIGE University of Geneva, Switzerland
USRIEP Ukrainian Scientific and Research Institute of Ecological Problems VITUKI Environmental Protection and Water Management
QR model Qualitative Reasoning
WMO World Meteorological Organization
ABSTRACT:
This document reports on data availability and quality for hydrological modeling and water quality modeling in the Black Sea Catchments. The report gives an overview of different hydrological models such as Soil Water Assessment Tool (SWAT) that is our selected tool for hydrological modeling and water quality modeling in the Black Sea Catchments, followed by Delft3D a 2D/3D modeling program, SOBEK, MONERIS, and Qualitative Reasoning (QR) models. The main hydrological projects developed in the regions are also described in order to benefit from existing modeling data suitable also for SWAT model. In the partners’ contribution chapter, each partner gives an overview of meteorological, hydrological and other SWAT data it can contribute or may be collected from the official owners. It is concluded that Ukraine, Romania and Hungary territory is well covered with SWAT needed data from enviroGRIDS partners, other data for the rest of the area as upstream of Danube Catchments are mostly available through ICPDR or at Global, European and regional database repositories.
EXECUTIVE SUMMARY
EnviroGRIDS (Building Capacity for a Black Sea Catchment Observation and Assessment System Supporting Sustainable Development) is a 4 years project funded under the EC Seventh Framework Programme, aiming to address the subjects of ecologically unsustainable development and inadequate resource management in the Black Sea Catchment area.
The EnviroGRIDS project is organized into several Work Packages (WPs). The WP 4 Catchment Hydrological Models is aiming to make predictions of hydrological models under different scenarios and the high-resolution calibrated SWAT model was selected to predict water quality and quantity in the Black Sea Catchment. The objective of this WP is to gather, format and bring into ArcGIS the necessary data for the Soil Water Assessment Tool (SWAT) in order to model the spatial distribution of water quantity and quality, to calibrated and validate the obtained hydrological models, and to perform uncertainty analyses. The hydrological model will be processed using GRID technologies for distributed computations that should allow to run land use/cover and climate change scenarios on a large dataset.
The scope of this deliverable is to report on availability of meteorological, hydrological, water quality and soil databases useful for SWAT modeling in the BSC. The document is presenting the purpose and scope of the project, is giving an overview of the hydrological models, the main hydrological projects in the region, data requirements for SWAT modeling and Geographical Information System (GIS) layers for SWAT, an overview of meteorological, hydrological and GIS data available from selected partners, gap analyses and new partners, and conclusions and recommendations.
It starts with an overview of hydrological models showing their suitability for modeling large scale areas such as SWAT, or more suitable for simulations of water flow, sediment transports, waves, water quality, morphological developments and ecology in river, coastal, and estuarine areas such as Delft3D model and other models like MONERIS, which is more suitable for the quantification of nutrient emissions from point and diffuse sources in river catchments.
Main hydrological projects in the regions are described in the next chapter in order to gain knowledge and take advantage of existing modeling data suitable also for SWAT model. Most of the data used in the regional models refer to Danube River and catchment, Danube delta except SCENES project that is modeling the water quality scenarios for pan-Europe.
An important inventory on data availability for SWAT is in the partners’
contribution chapter. Each partner give an overview of meteorological, hydrological and other SWAT data they can contribute or may be collected from the official owners. It seems that Ukraine, Romania and Hungary territory are well covered with SWAT needed data. Other data not shown here are available in Bulgaria, while for the upstream area of the Danube Catchment, data are available at ICPDR or in the European database repositories.
Contents
1 INTRODUCTION ... 8
1.1 PURPOSE AND SCOPE ... 8
1.2 DOCUMENT STRUCTURE ... 9
2 OVERVIEWOFHYDROLOGICALMODELS ... 9
2.1 SOIL AND WATER ASSESSMENT TOOL (SWAT) ... 10
2.2 DELFT3D ... 10
2.3 SOBEK ... 11
2.4 MONERIS ... 12
2.5 QUALITATIVEREASONINGMODEL(QR) ... 13
3. MAINHYDROLOGICALPROJECTSINTHEREGION ... 13
3.1 DANUBE FLOOD RISK PROJECT ... 14
3.2. MORFDD PROJECT ... 14
3.3. NATURNET-REDIME PROJECT ... 15
3.4 FORECASTER PROJECT ... 15
3.6 DANUBE DELTA BIOSPHERE RESERVE HYDROLOGY DATABASES ... 16
3.7 DANUBE DELTA BIOSPHERE RESERVE WATER CHEMISTRY DATABASE ... 18
3.8 DANUBS PROJECT ... 19
4. DATAREQUIREMENTSFORSWATMODELING ... 19
4.1 METEOROLOGICAL AND HYDROLOGICAL DATA FOR SWAT ... 20
4.2 GIS DATA LAYERS FOR SWAT ... 22
5. CONTRIBUTIONSFROMENVIROGRIDSPARTNERS ... 23
5.1 INHGA ... 23
5.2 DANUBE DELTA NATIONAL INSTITUTE (DDNI) ... 27
5.3 DHMO ... 30
5.4 USRIEP ... 32
5.6 VITUKI ... 42
6. GAPANALYSISANDNEWPARTNERS ... 45
6.1 MAIN RECOMMENDATIONS FROM GAP ANALYSIS ... 45
6.2 CALL FOR NEW PARTNERS ... 45
7. CONCLUSIONSANDRECOMMENDATIONS ... 45
7.1 CONCLUSIONS ... ERROR!BOOKMARK NOT DEFINED. 7.2 RECOMMENDATIONS ... ERROR!BOOKMARK NOT DEFINED.
List of Figures
Figure 1 - Hydrometric stations for hydrology regime study within the DDBR hydrographic network.
Figure 2 - Danube Delta Biosphere Reserve area – sampling points for water and sediment chemistry study
Figure 3 - Distribution of weather stations in Romania
Figure 4 - Location of hydrometric stations at outlet of Romanian river basins Figure 5 - Arges – Vedea hydrographic district
Figure 6 - Buzau river basin - area covered by SWAT modeling data Figure 7a – Overall view of hydrometric stations along Danube’s arms and inner channels /canals
Figure 7b - Position of hydrometric stations along Danube River (Romanian sector) Figure 8 - Land and river /channels /lakes bottom elevation data
(including numerical map /shape with these data) Figure 9 - Location of the hydrometric stations Figure 10 - Location of the water quality stations
Figure 11 - Digital elevation map (DEM) of the investigation region
Figure 12 - Location of hydro chemical control stations of Ukrainian State Hydro meteorological Service
Figure 13 - Location of hydro chemical control stations of Ukrainian State Ecological Inspection
Figure 14 - Location of hydro chemical control stations of Ukrainian State Water Economy Committee
Figure 15 - Location of meteorological stations in Ukraine Figure 16 - Position of the 11 Hungarian meteorological stations
Figure 17 - Interpolated meteorological parameters on the Danube catchment down to the Tisza mouth (resolution 0.1 degree)
Figure 18 - Position of the 187 gauging stations
1 INTRODUCTION
1.1 Purpose and Scope
The main objectives of WP 4 – Hydrological catchment models is to gather, format and bring into ArcGIS the necessary data for the application Soil Water Assessment Tool (SWAT) in order to model the spatial distribution of water quantity and water quality in the Black Sea Catchment, to calibrate and validate hydrological models, and to perform uncertainty analyses using GRID network for distributed computations, as well as land use/cover and climate change scenarios generated in WP3. The scope of this deliverable is to report on data availability and quality for hydrological modeling and water quality modeling in the Black Sea Catchment.
New advances in computing technology plus data availability from the Internet have made high resolution modeling of distributed hydrologic processes possible.
Using the program Soil Water Assessment Tool1 (Arnold et al., 1998), in this WP a high-resolution (sub-catchment spatial and daily temporal resolution) water balance model of the entire Black Sea Catchment (BSC) will be built. The BSC model will be calibrated and validated using river discharge data, river water quality data and crop yield data.
For the simulation of the BSC, SWAT requires data on elevation, soil, land cover, and climate for model setup, on river discharges and water quality, and on crop yield (as available) for calibration and uncertainty analysis.
Most of this data is available and can be obtained from the Internet and in collaboration with WP2 from remote Sensing. The United Nations Water programme is currently collecting global data on water resources and reporting on the state of this resource at the global and regional levels every 3 years (UN 2006). UN-Water is responsible for assessing the status and trends in freshwater at the global and regional levels through the World Water Development Report, which is a comprehensive and authoritative review of the state of the world's freshwater resources. UN-water has also published papers on the risks associated with changes in water resources (UN-Water 2005). The United Nations Environment Programme is active in several projects linking water and environment. First, the UNEP GEMS/Water Programme provides data and information on the state and trends of global inland water quality (GEMS/Water 2007).
Another initiative that has been supported by UNEP is the River Basin Information System (RBIS) that provides valuable hydrological statistics per watershed and is now expanding worldwide (Global-RIMS). The Global International Water Assessment (GIWA) is another initiative that was supported by UNEP/GEF and produced regional reports on the state of water resources in several regions of the world comprising the Black Sea (GIWA 2005 a, b).
1 http://www.brc.tamus.edu/swat/
The International Hydrological Programme (IHP) of UNESCO is a scientific programme in water research, water resources management, education and capacity- building. Its first aim is on the impact of climate and human-induced changes on water resources. It is asking questions such as how, when and where human induced changes, together with weather and climatic extremes are influencing water resources and its sustainability. As these questions are very complex they require improved analytical techniques. Finally, the United Nations are also active in the hydrological fields through the World Meteorological Organization (WMO) and the Global Runoff Database Centre (GRDC) that is a world-wide depository of discharge data and metadata. GRDC is a facilitator between data providers and data users. GRDC is also developing the Global Terrestrial Network for River Discharge (GTN-R) that is a near real-time river discharge data base comprising 400 gauging stations around the world, which accounts for a massive proportion of freshwater fluxes into the oceans.
These European and United Nations initiatives are fully compatible with national and sub-national projects that are needed to address locally the important issues of water resource sustainability and vulnerability.
1.2 Document Structure
This document is structured in eight chapters. Chapter 1 is presenting the purpose and scope of the project, chapter 2 is giving an overview of the hydrological models, chapter 3 is presenting the main hydrological projects in the region, chapter 4 is presenting data requirements for SWAT modeling and GIS layers for SWAT. Chapter 5 is presenting an overview of meteorological, hydrological and GIS data available from project partners as input to SWAT database. Results from a gap analyses and new partners are shown in chapter 6. Conclusion, and recommendations are presented in chapter 7.
2 OVERVIEW OF HYDROLOGICAL MODELS
This chapter is giving an overview of the hydrological models starting with the Soil and Water Assessment Tool (SWAT) that is our selected tool for hydrological modeling and water quality modeling in the Black Sea Catchments followed by Delft3D a 2D/3D modeling program suite for simulations of water flow, sediment transports, waves, water quality, morphological developments and ecology in river, coastal and estuarine areas, SOBEK 1D/2D hydraulic model for the integral simulation of processes for flood forecasting, optimization of drainage systems, control of irrigation systems, sewer overflow design, ground-water level control, river morphology, salt intrusion and water quality, and MONERIS (Modelling Nutrient Emissions in River Systems) a semi-empirical, conceptual model for the quantification of nutrient emissions from point and diffuse sources in river catchments.
2.1 Soil and Water Assessment Tool (SWAT)
Soil Water Assessment Tool (SWAT: http://swatmodel.tamu.edu) is a hydrologic program used for large scale simulations. This watershed-scale program performs simulations that integrate various processes such as hydrology, climate, chemical transport, soil erosion, pesticide dynamics and agricultural management. SWAT accounts for variable soil and land cover conditions by subdividing the simulated catchment into sub-areas. The model uses a daily to sub-hourly time step and can perform continuous simulation for a 1 to 100 year period. SWAT has an ArcGIS interface, which takes layers of information such as soil, land cover, elevation and management and calculates hydrology, erosion and chemical transport both inland and along streams. About 50 peer- reviewed papers discussed the application of SWAT on pollution loss studies for a wide range of small and large river catchments (Gassman et al., 2005).
SWAT was already used to simulate the continent of Africa (Schuol et al., 2007) and in the “Hydrologic Unit Model for the United States” (HUMUS) (Arnold et al., 1999), where the entire U.S. was simulated with good results for river discharges at around 6000 gauging stations. This study is now extended within the national assessment of the USDA Conservation Effects Assessment Project (CEAP 21). Other large scale SWAT application included the work of Gosain et al. (2006) where twelve large river catchments in India were modeled with the purpose of quantifying the climate change impact on hydrology. SWAT is recognized by the U.S. Environmental Protection Agency (EPA) and has been incorporated into the EPA’s BASINS (Better Assessment Science Integrating Point and Non-point Sources). For the simulation of SBS, SWAT requires data on DEM, soil, land cover and climate for model setup and river discharges, river water quality and crop yield (as available) for calibration and uncertainty analysis. Most of this data is available and can be obtained from the Internet and in collaboration with WP2 from remote sensing.
2.2 Delft3D
The Delft3D is a 2D/3D modeling program developed by the DELTARES – Delft Hydraulic Institute, The Netherlands. It is a fully integrated computer software suite for simulations of water flow, sediment transports, waves, water quality, morphological developments and ecology, in river, coastal and estuarine areas.
It is composed of 6 modules which cover certain aspects of a research or engineering problem, such as: stratified and density driven flows, river flow simulations, simulations in deep lakes and reservoirs, fresh-water river discharges in bays, salt intrusion, thermal stratification in lakes, seas and reservoirs, cooling water intakes and waste water outlets, transport of dissolved material and pollutants, online sediment transport and morphology, wave-driven currents, non-hydrostatic flows.
The central module is Delft3D-FLOW: a multi-dimensional (2D or 3D) hydrodynamic simulation program. It solves the Navier-Stokes hydraulic fundamental equations for non-
steady water flow and transport phenomena on a rectilinear or curvilinear, boundary fitted grid.
The hydrodynamic conditions (velocities, water elevations, density, salinity, vertical eddy viscosity and vertical eddy diffusivity), calculated in the Delft3D-FLOW module are used as input to the other modules of Delft3D. The modules interact with one another by means of a so-called communication file.
These modules are:
- Delft3D-WAVE: short wave propagation - Delft3D-WAQ: far-field water quality
- Delft3D-PART: mid-field water quality and particle tracking - Delft3D-ECO: ecological modeling
- Delft3D-SED: cohesive and non-cohesive sediment transport
Inputs are geospatial data. Thus, all studies and field measurements to collect data and data processing should be compatible with GIS.
2.3 SOBEK
SOBEK is a 1D /2D hydraulic model for the integral simulation of processes in one dimension (i.e. in a river, an estuary, a canal or in a sewer network), for flood forecasting, optimization of drainage systems, control of irrigation systems, sewer overflow design, ground-water level control, river morphology, salt intrusion and water quality. It has been developed, and is being further developed, jointly with the Netherlands public institutes and private consultants.
SOBEK has three basic product lines covering any fresh water management situation in River, Rural and Urban systems alike. Each product line consists of different modules to simulate particular aspects of the water system. These modules can be operated separately or in combination. The data transfer between the modules is fully automatic and modules can be run in sequence or simultaneously to facilitate the physical interaction.
All product lines use the same interface components. The interfaces of the urban and rural product lines are fully integrated. The user interface is used to prepare your schematization, control your input data, check for possible schematization errors, and helps you to analyze both input data and all computed parameters.
SOBEK has a unique interface concept where the same set of interface tools is used for all product lines and all SOBEK modules. Examples of these interface tools are the Case Manager, the Case Analysis Tool and the GIS network editor NETTER.
SOBEK offers two GIS solutions:
• The OpenGIS environment NETTER. This environment is free of charge. It allows for the import and export of a range of GIS formats. The NETTER layers provide an extremely fast data access while performing map based input data editing and post processing of results.
• A Map Front End approach to plug in SOBEK components into GIS environments such as ArcGIS.
SOBEK reads all standard GIS formats and thus allow you to link your GIS database system with your SOBEK model. Layered maps can be imported and all objects and their ID's can be used directly. SOBEK even allows generating a complete SOBEK network schematization on basis of a vector layer. It is also possible to define your SOBEK schematization in your GIS environment and export it to SOBEK.
2.4 MONERIS
MONERIS (Modeling Nutrient Emissions in River Systems) is a semi-empirical, conceptual model for the quantification of nutrient emissions from point and diffuse sources in river catchments (Behrendt et al., 2000; 2002a; 2002b). It is developed by the Department of Limnology of Shallow Lakes and Lowland Rivers, at the Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany (IGB-Berlin). Since its inception in 1999 MONERIS has been applied to numerous European river systems (for example the Axios, Danube, Daugava, Elbe, Odra, Po, Rhine, Vistula, see Behrendt et al., 1999; 2003a; 2003b; Schreiber et al., 2005a; Behrendt & Dannowski, 2005), the whole of Germany (Behrendt et al., 2000; Venohr et al., 2008 a, b), and river catchments in Canada, Brazil (Von Sperling & Behrendt, 2007) and China (Xu Pengzu, 2004).
MONERIS has a model surface programmed in VBA, implemented in 2008. In MONERIS results are presented for total nitrogen (TN), total phosphorus (TP) and dissolved silicium (Si). Furthermore, a scenario manager has been developed to calculate the effects of measures on the nutrient emissions for different pathways and spatial units.
The model is based on data for runoff and water quality for the study area along with a Geographical Information System (GIS), thus bringing together digital maps as well as statistical information for different administrative levels. Point data (e.g. waste water treatment plants), area information (e.g. soil data) and administrative information (like statistical data for districts) are integrated. The application of MONERIS allows regionally differentiated quantification of nutrient emissions into a river system on the level of an analytical unit. The results can be visualized in GIS generated maps. The MONERIS approach provides an assignment of the measures applied to the analytical units. In the model, suitable measures are pre-defined which can be implemented by the user, either as single or combined measures. The measures can be based on analytical units or cover larger areas. Therewith, the resulting effect of measures on loads in the catchments can be tested. Modeling scenarios allows calculation of the efficiency of management measures for reaching prescribed water quality standards (such as target concentrations of surface water quality).
2.5 QUALITATIVE REASONING MODEL (QR)
Qualitative Reasoning (QR) model is an innovative technique, originating from Artificial Intelligence (AI) that involves non-numerical description of systems and their behavior, preserving all the important behavioral properties and distinctions.
The main data sources for QR models are data containing the modeled system components and the causal (cause-effect) relationships among them.
QR technology is of great importance for developing, strengthening and further improving education and training on topics dealing with systems (social, economic, environment, and culture) and their behaviors. That is, being able to distinguish a system from the environment in which it operates to identify the parts that it is made of and to predict or explain its behaviors. Research in the cognitive sciences has shown that when learners have a causal model of system behavior they are better able to apply their knowledge to new situations (Schumacher and Gentner, 1988; Bredeweg & Winkels, 1998). QR models are a way to develop such causal models because they capture the fundamental aspects of a system or mechanism while suppressing much of the irrelevant detail. This approach makes expert knowledge available to non-experts for direct use in educational and applied contexts. An important advantage of QR over other techniques like expert or knowledge-based systems is that QR transfers not just predictions based on expert knowledge, but also makes this knowledge explicit, allowing its transfer to others.
3. MAIN HYDROLOGICAL PROJECTS IN THE REGION
This chapter presents the main hydrological projects in the region:
- “Danube Flood risk” project that is focused on flood risk reduction, risk assessment, risk mapping, and risk reduction in the lower Danube river area,
- MORFDD project that models hydro-morphologic changes and the ways these affect the water quality and implicitly the biodiversity within Danube Delta wetlands,
- NaturNet-Redime project to support sustainable development via Qualitative reasoning (QR) model web tools aiming to contribute to the implementation of the EU Strategy on Sustainable Development,
- FORECASTER project (Facilitating the application of Output from REsearch and CAse STudies on Ecological Responses to hydro-morphological degradation and rehabilitation),
- SCENES project 'Water Scenarios for Europe and for Neighbouring States aiming to develop and analyze a set of comprehensive scenarios of Europe’s freshwater futures up to 2025,
- other two building database projects first one aiming to Build Danube Delta Biosphere Reserve Hydrology databases and the second one Danube Delta Biosphere Reserve water chemistry database and the DANUBS project (Nutrient Management in the Danube Basin and its Impact on the Black Sea).
3.1 Danube Flood risk project
The Danube River is one of the most important natural axes in South-East-Europe.
It links most of the countries in the SEE area. Thus the improvement and good examples of transnational cooperation of all countries will be a brilliant signal for the whole region.
This project has a far reaching strategic focus beyond risk management and could become a flagship project for the SEE programme. It will improve safer sustainable conditions for living environment and economy in the Danube floodplains. It integrates stakeholders and different acting groups and disciplines.
Flood risk increases with ongoing climate change. Risk reduction in large international river basins can only be achieved through transnational, interdisciplinary and stakeholder oriented approaches within the framework of a joint transnational project.
Practice has shown that starting this kind of cooperation is extremely difficult, due to practical, political and financial reasons. If incentives exist like the transnational cooperation programme, the start up can be successful. The long term process will be self-running after the starting phase.
The Danube Flood risk project focuses on the most cost-effective measures for flood risk reduction: risk assessment, risk mapping, involvement of stakeholders and risk reduction by adequate spatial planning.
The project will bring together scientists, public servants, NGOs and stakeholders who develop jointly a scalable system of flood risk maps for the Danube River floodplains.
Transnational methodology and models will be defined and implemented for flood risk assessment and mapping. This results in proposals for flood mitigation measures, adjustments of spatial development plans, assessment tools for economic development in flood plains and raised awareness of flood risk of stakeholders, politicians, planners and the public. Infrastructures at risk like industry, power stations and supply infrastructure will be considered in the project.
The main data sources for flood risk maps are digital terrain data, land use information, hydraulic data and for the damage assessment also statistics. Especially linear structures need to be considered as they have high impacts on the simulation.
3.2. MORFDD project
This project is funded by the Romanian Education and Research Ministry in the framework of the National Plan of Research, Development, and Innovation and is running within 2007-2010. Danube Delta National Institute for research and Development, Tulcea, Romania, is this project’s coordinator.
The MORFDD project develops a model to investigate the environment factors, mainly of water regime as result of hydro-morphologic changes and the ways these affect the water quality and implicitly, the biodiversity within wetlands. The project purpose is to create a scientific knowledge base of an environment system functioning mode. It helps
to scientifically justify the decisions made on protection and ecological reconstruction of wetlands and preservation of protected areas. MORFDD model is constructed using as Delft3D hydraulic program specialized in numerical modeling of hydro-morphology changes and water quality. Inputs are geospatial data.
Thus, all field measurements and data processing are carried out using equipments and computational techniques of high performance compatible with GIS. The project case study is the Danube Delta Biosphere Reserve (DDBR) aquatic ecosystem. DDBR is one of the main components within the Danube River-Danube Delta-Black Sea geo- ecosystem. It is formed by the Danube Delta territory, the Razim-Sinoie lake complex and the north-western coastal zone of Black Sea up to the isobaths of 20 m depth. For this type of system, the management issues are related to rehabilitation/improvement of ecological factors through a sustainable management of wetland hydrographic network.
The main objective is to improve the hydrologic regime – premise for life conditions for establishing an ecological equilibrium which ensures protection and preservation for biological diversity.
3.3. NaturNet-Redime project
This is a FP6 project funded by the European Commission for Research and Development. The general objective of NaturNet-Redime2 is to support sustainable development by improving knowledge about all aspects of sustainability and provide education mainly about social, economic and environmental tools for the implementation of the EU Strategy on Sustainable Development at both EU and international levels.
There are two main approaches of the NaturNet-Redime project. The first is the NaturNet - Redime portal which focuses on innovative presentation of different tools and data sources for learning about sustainability. The second is learning through modeling where learners develop deep understanding of causes and effects by developing their own models of particular systems - using Qualitative Reasoning (QR). In the framework of this project, the Redime part deals with Qualitative Reasoning (QR) model.
The Danube Delta Biosphere Reserve aquatic and terrestrial ecosystem components were qualitatively modeled, using QR software, from their physical, chemical and biological behavior point of view. Components and their causal relationships were used to construct the model structure. They include the water chemistry / pollution elements, flora and fauna species relationship (in the framework of the Functional Feeding Groups) up to the human beings health, in the context of a low /medium / high water pollution level.
3.4 FORECASTER project
The Forecaster project (Facilitating the application of Output from REsearch and CAse STudies on Ecological Responses to hydro-morphological degradation and rehabilitation) is a EU project funded by the IWRM-Net. The project aims at linking
2 http://www.naturnet.org/
science with practical implementation of robust, cost efficient rehabilitation strategies for improving rivers and standing waters. The main objective of the project is assessing research outputs (both national, European and North American) and case studies concerning the ecological effects of hydro-morphological degradation, in order to position hydro-morphology in river rehabilitation strategies.
The focus is on rivers and fish, but invertebrates and lakes are also considered.
Mechanism for achieving good ecological potential in heavily modified and artificial water bodies is included, an aspect that has yet to be realized widely across Europe. A common website using Google maps and Wiki type information on the implemented restoration projects in the partner countries was set up (www.hull.ac.uk/comp). Romanian case studies are in Babina, Cernovca, Holbina-Dunavat, Fortuna, and Popina. The access is open to public including new case studies, but the data base can be change by partners only.
3.5 SCENES project
The SCENES project 'Water Scenarios for Europe and for Neighboring States”
('http://www.environment.fi) aims at developing and analyzing a set of comprehensive scenarios of Europe’s freshwater futures up to 2025. The project covers four different geopolitical settings which will have an important effect on water availability and use of these regions in the future: Baltic, Mediterranean, Lower Danube and Black Sea. There are 10 Pilot areas: Lake Peipsi, Narew, Lower Don, Crimea, Danube Delta, Tisza, Candeliaro, Garonne, Guadianna, Seyhan. The Scenes scenarios will provide a reference point for long-term strategic planning of European water resource development, alert policymakers and stakeholders about emerging problems, allow river basin managers to test regional and local water plans against uncertainties and surprises. The water quality modeling of Scenes scenarios for pan-Europe is using point source loadings for domestic, industrial and urban runoff - Biological Oxygen Demand (BOD). The main drivers for the scenario analysis of point loads are "connectivity to sewage networks" and the "level of treatment", also changes in population, GDP and emission factors (currently only for phosphorus) play a role. In SCENES a continental-scale model of surface water quality (WorldQual) is currently being developed. The aim is to have a system to predict water quality in river and lakes across pan-Europe for the 2025s and 2050s which is consistent with SCENES scenarios. The starting point was to construct the model for baseline conditions, in year 2000.
3.6 Danube Delta Biosphere Reserve Hydrology databases
The hydrological database for long study interval contains data for a number of 68 hydrology measurement points / hydrometric stations (Figure1), as follows:
- water level;
- currents;
- water depth;
- cross-section area;
- water discharge;
- suspended solid discharge;
- water turbulence;
- bottom sediment;
- sand /mud sediment fractions /percentage.
Figure 1 - Hydrometric stations for hydrology regime study within the DDBR hydrographic network.
The above database is managed by the National Institute of Hydrology and Water Management, Bucharest, Romania, and National Institute of Research and Development for Geology and Geoecology (Bucharest, Romania) as partners in MORFDD project3.
Bathymetric and topo-hydrographic data: bottom elevation data of the Danube Delta Biosphere Reserve hydrographic network (channels /canals / lakes /western Black Sea coastal zone is managed by the Danube Delta National Institute for Research and Development (Tulcea, Romania) as coordinator of the MORFDD project.
3 http://www.indd.tim.ro/morfdd
3.7 Danube Delta Biosphere Reserve water chemistry database
Since 1996, with a monthly frequency, the DDBR aquatic ecosystems water chemistry study is carried out for Danube River, Danube’s arms, canals and lakes they connect in a number of 25 sampling points. The 25 sampling points for water quality study are located as shown in Figure2.
Figure 2 - Danube Delta Biosphere Reserve area – sampling points for water and sediment chemistry study
Database for water quality as collected between 1997-2010 contains the following quality characteristic indicators:
1. For channels /canals network:
- Chemical and physical-chemical indicators: water temperature, pH, dissolved oxygen, oxygen chemical consumption;
- [CCO-Mn], salts, nutrients (N-NH4, N-NO2, N-NO3, Ntotal, P-PO4, Ptotal);
- Water pollution indicator: Heavy metals: Fe, Cd, Zn, Cu, Mn, Pb, Ni.;
- Physical indicators: solid suspensions;
- Eutrophication indicators: Ntotal si Ptotal.
2. For lakes:
- Chemical and physical-chemical indicators: water temperature, pH, dissolved oxygen, oxygen chemical consumption, [CCO-Mn], salts, nutrients (N-NH4, N- NO2, N-NO3, Ntotal, P-PO4, Ptotal), and Chlorophyll “a”;
- Water pollution indicator: Heavy metals: Fe, Cd, Zn, Cu, Mn, Pb, Ni.;
- Physical indicators: solid suspensions;
- Eutrophication indicators: Ntotal si Ptotal ;
3. For Western Black Sea coastal waters: water salinity and pH.
3.8 DANUBS project
The DANUBS project is investigating the nutrient balance in the Danube river catchment with main emphasis on diffuse pollution (e.g. agriculture, air pollution), the transport, retention and losses of nutrients in the catchment (nutrient balances in case study regions) and silica along the Danube River and the functioning of the Western Black Sea ecosystem concerning the direct influence of riverine nutrient and silica discharges.
The mathematical models used in the DANUBS project are MONERIS-emission model; Danube Water Quality Model (DWQM) for the description of the transport and transformation processes in the river system, Danube Delta Model (DDM) for the quantification of nutrient transport in the Danube Delta and Shelf Model for modeling the impact of the Danube load on the Western Black Sea. Based on these models the whole system can be considered as a complex unit and scenarios can be developed as a basis for scenario evaluation.
4. DATA REQUIREMENTS FOR SWAT MODELING
All the tasks related to data collection for SWAT, hydrological model building, calibration, validation, assessment of uncertainties, as well as driving model under different scenarios, belongs to WP4. For the simulation of processes at catchment level, SWAT requires data on DEM, soil, land cover, and climate for model setup, and river discharges, river water quality, and crop yield (as available) for calibration and uncertainty analysis. Most of this data is available from the Internet including the remote sensing data, which shall be obtained in collaboration with WP2.
4.1 Meteorological and hydrological data for SWAT
4.1.1 SWAT meteorological and hydrological data requirement
Data name Required information
Stream network map
River names are also required
Climate data
- Daily precipitation (mm)
- Daily Max temperature (degree C.) - Daily Min temperature (degree C.)
- Location (lat, long, elevation) of the climate stations - Wind speed (m/s) (if available)
- Relative humidity (if available)
- Solar radiation (MJ/m2/day) (if available)
Reservoir operation information
- Month the reservoir became operational (0-12)
- Reservoir surface area when the reservoir is filled to the emergency spillway (ha)
- Volume of water needed to fill the reservoir to the emergency spillway (104 m3)
- Reservoir surface area when the reservoir is filled to the principal spillway (ha)
- Volume of water needed to fill the reservoir to the principal spillway (104 m3)
- Initial reservoir volume.
- Initial sediment concentration in the reservoir (mg/L) - Equilibrium sediment concentration in the reservoir (mg/L) - Hydraulic conductivity of the reservoir bottom (mm/hr) - Daily reservoir outflow (m3/s).
Inlet
- Lat and long for any inlet to the watershed is required - Daily data for any inlet (optional)
Data name Required information Water
management
- Water transfer information, water use from shallow and deep aquifer, river, and ponds
River discharge data at hydrometric
stations
- Daily river discharge (m3/s)
- River water quality data (see below) - Lat and long of the stations
- The river names where the stations are located
Water quality at hydrometric
stations
- Sediment load transported by the river (daily, or monthly) (tn), or - River sediment concentration (mg/l)
- Nitrate load transported by the river (kg N) - Phosphorus load transported by the river (Kg P) - Dissolved oxygen transported by the river (kg O2) - Algal biomass transported by river (kg)
- Other chemicals such as: NH4, NO2, Mineral P, organic P, Organic N, CBOD are also considered by SWAT
Point sources
- Input from water treatment plants (quantity and quality of water, and Lat- Long location)
- Springs (quantity and quality, and Lat-Long location)
4.2 GIS data layers for SWAT
All maps should be in WGS84 projection
Data name Required information
DEM map
- Resolution of 90m x 90m exists, which is sufficient for the entire Basin, but for smaller projects higher resolution would be required.
Land use map
SWAT has a large landuse database for various landuses which must be linked to the landuse map. The landuse map must be accompanied with a database that describes the map units.
Soil map
An accompanying soil database is needed with the following parameters:
- Number of soil layers up to 10 may be specified - Soil Hydrologic group (A, B, C, or D)
- Maximum rooting depth (mm) - Textural class of first soil layer
- Depth from soil surface to bottom of each layer (mm) - Moist bulk density (g/cm3)
- Available water capacity (mm H2O/mm soil) - Saturated hydraulic conductivity (mm/hr) - Organic carbon content (% soil weight) - Clay content (% soil weight)
- Silt content (% soil weight) - Sand content (% soil weight)
- Rock fragment content (% total weight) - Moist soil albedo
- Soil erodibility factor, K, in USLE equation
Agricultural management
data
- Planting and harvest dates
- Fertilization information (when, where, how much) - Tillage operation (method, date)
- Irrigation (source, date, amount) - Grazing
- Tile drains (exits or not, if yes, at what depth) - Pesticide application
- Crop rotation Crop yield
data
- Annual yield for major crops in the region
5. CONTRIBUTIONS FROM ENVIROGRIDS PARTNERS
The main enviroGRIDS partners contributing to this report on data useful for SWAT are DDNI, INHGA, EAWAG, DHMO, IHE, USRIEP, ONU, VITUKI, NIMH, UNIGE.
The partners were requested to report on SWAT data owner in their respective countries such as official meteorological and hydrological data centers. Partners were asked which meteorological data, hydrological data and GIS data they could provide to the enviroGRIDS project and at which conditions.
An overview of SWAT data availability per institutions is given below:
5.1 INHGA
5.1.1 Meteorological data
The Romanian National Institute of Meteorology and Hydrology (Bucharest) is regularly reporting basic climatic data from 30 weather stations (Figure 3) to the European Climate Assessment & Dataset (http://eca.knmi.nl/dailydata/index.php).
Figure 3 - Distribution of weather stations in Romania
5.1.2 Hydrological data
The INHGA is reporting on hydrological data from 18 Hydrometric stations ( Figure 4, Table 1), 14 on Romanian rivers and 4 on Danube river they are the owners of SWAT level data for some rivers hydrographic districts as Arges - Vedea (Figure 5) and historical Danube water discharges (Table 2) from 1979 to 2008. The river water quality data are recorded monthly from the period 1998 – 2008.
Figure 4 - Location of hydrometric stations at outlet of Romanian river basins Table 1 - Hydrometric stations
Nr.
crt. River
Selected Hydrometric
monitoring station
River basin
Coordinates
Area (sq.km)
Mean elevation Latitude Longitude (m)
1 TISA SIGHETU
MARMATIEI TISA 47:56:21.62 23:52:34.21 1633,2 984,9 2 SOMES SATU - MARE SOMES 47:47:13.33 22:52:31.68 15364,1 527,6 3 CRISUL
REPEDE ORADEA CRISURI 47:03:25.92 21:55:40.70 2169,5 637,7 4 CRISUL
NEGRU ZERIND CRISURI 46:37:41.27 21:30:59.63 3801,1 325,3 5 CRISUL
ALB CHISINAU
CRIS CRISURI 46:31:09.93 21:30:37.98 3478,7 374,5 6 MURES ARAD MURES 46:09:38.34 21:19:13.13 27246,3 624,1 7 TIMIS SAG TIMIS 45:38:44.23 21:10:31.75 4564,8 471,0 8 CARAS VARADIA CARAS 45:05:01.08 21:32:59.21 759,5 359,0 9 JIU ZAVAL JIU 43:50:30.37 23:50:43.81 10119,5 441,1 10 OLT CORNET OLT 45:23:05.83 24:17:52.84 13775,5 764,8 11 ARGES BUDESTI ARGES 44:13:28.77 26:27:02.68 9309,8 387,9 12 IALOMITA SLOBOZIA IALOMITA 44:33:48.48 27:22:57.02 9238,0 360,2 13 SIRET LUNGOCI SIRET 45:33:30.76 27:30:25.21 36291,7 539,6 14 PRUT OANCEA PRUT 45:55:02.33 28:07:12.52 26618,1 269,7 15 DUNARE BAZIAS DUNARE 44:48:30.38 21:23:05.76
16 DUNARE ZIMNICEA DUNARE 43:37:32.48 25:21:30.46 17 DUNARE HARSOVA DUNARE 44:40:39.15 27:56:39.14 18 DUNARE CEATAL
IZMAIL DUNARE 45:13:17.33 28:44:43.45
Figure 5 - Arges – Vedea hydrographic district
Table 2 - The Danube river average daily water discharge (m3/s) during 30 years, from 1979 to 2008
Measurement data River / measuring
section
BAZIAS Km 1072,5
ZIMNICEA Km 553,23
HARSOVA Km 248,0
CEATAL
IZMAIL Km 80,5
01.01.1979 5.120 4.600 - 6.170
01.02.1979 5.600 4.580 - 5.920
01.03.1979 6.270 4.580 - 5.580
01.01.1984 4.360 4.370 1.460 3.650
01.02.1984 4.250 4.450 1.530 3.760
01.03.1984 3.960 4.370 1.500 3.950
29.12.2008 7.190 7.750 2.480 7.220
30.12.2008 7.410 7.760 2.580 7.340
31.12.2008 7.530 7.520 2.660 7.450
For some areas as the Buzau river basin, the area has detailed SWAT hydrologic data for modelling and calibration scenarios (Figure 6).
Figure 6 - Buzau river basin - area covered by SWAT modeling data
5.1.3 Soils data and maps
Soils data and maps for the Romanian territory are available at the Research Institute for Soil Science and Agrochemistry, Bucharest.
Soil data and map:
- Soil class and type;
- Soil hydrologic group;
- Rooting depth (mm);
- Textural class of first soil layer;
- Moist bulk density (g/cm3);
- Organic carbon content (% soil weight);
- Available maximum water content at root length (mm H2O);
- Total water content at root length (cm);
- Soil erodability factor K, in USE equation.
5.2 Danube Delta National Institute (DDNI)
Hydrological data which DDNI can provide are related to the Danube River basins and Danube Delta Biosphere Reserve (DDBR) area hydrographic network: Danube’s arms, inner channels/canals and the lakes they connect, and the Black Sea coastal waters area up to the 20m isobaths. These data are as follows:
a) Hydrometric stations names and their geographical positions along Danube’s arms and inner channels /canals (Figure 7a, b).
Figure 7a – Overall view of hydrometric stations along Danube’s arms and inner channels /canals
Figure 7b - Position of hydrometric stations along Danube River (Romanian sector)
Table 3 - Name and coordinates of hydrometric stations
Station X Y
Gruia 2.268.574 4.426.718 Calafat 2.292.260 4.399.796 Bechet 2.394.868 4.374.652 Corabia 2.450.696 4.376.469 Tr.Magurele 2.487.179 4.370.704 Zimnicea 2.535.842 4.362.639 Giurgiu 2.599.226 4.388.075 Oltenita 2.663.749 4.405.941 Calarasi 2.732.413 4.414.013 Harsova 2.794.292 4.467.824 Vadu Oii 2.787.412 4.474.218 Gropeni 2.794.292 4.467.824 Braila 2.798.356 4.526.805 Galati 2.807.809 4.543.562 Grindu 2.819.182 4.541.453 Isaccea 2.846.827 4.528.382 Ceatal Ismail 2.873.679 4.522.886
b) Land and river/channels/lakes bottom elevation data - including numerical map/
shape with these data (Figure 8).
Figure 8 - Land and river /channels /lakes bottom elevation data (including numerical map /shape with these data) c) Danube river hydrological data:
• Water level recorded within 1858 – 2010 for the main hydrometric stations along the Danube’s arms: monthly values (maximum, average, and minimum);
• Water discharge /water flow hydraulic parameters for the entire water level span;
• Water quality within 1997-2010: monthly values at 25 stations (geographically positioned) for next parameters:
- River sediment concentration (mg/l);
- Nitrate load transported by the river (kg N);
- Phosphorus load transported by the river (Kg P);
- Dissolved oxygen transported by the river (kg O2);
- Algal biomass transported by river (kg);
- NH4, NO2, Mineral P, organic P, Organic N, and CBOD.
5.3 DHMO
Official data center for hydrological and meteorological data in Ukraine is the State Hydro meteorological Service. The data are stored in the central archive of the Service at Regional Centers.
The Danube Hydro-Meteorological Observatory is the structural unit of State HM Service that collects process and stores the data for the Danube estuary area and the adjacent part of the Black Sea (Figure 9, 10).
Figure 9 - Location of the hydrometric stations Summary of metadata (hydrology):
Data source DHMO
File format xls timeseries
Attributes Station name, latitude, lonitude, coordinates WGS1984 Data use is limited or commercial in general, but free to use for project purposes.
The parameters recorded are daily min, max temperature, daily precipitation (For all 5 stations). Daily evaporation for 2 stations. Wind direction and velocity for 2 stations.
Time span is from 01.01.1980 to 31.12.2009.
Data are allocated on DHMO FTP-server with limited access, login and password was set and sent to coordinator of WP4
Figure 10 - Location of the water quality stations
Summary of metadata (water quality):
Data source DHMO
File format xls timeseries
Attributes Station name, lat, lon, coordinates WGS1984 Data use is limited or commercial in general, but free to use for project purposes.
The parameters are daily water discharge, turbidity, sediments discharge, and water temperature. Time span is from 01.01.1980 to 31.12.2009.
Water discharge data are allocated on DHMO FTP-server with limited access, login and password was set and sent to coordinator of WP4.
Water quality data on dissolved oxygen, mineralization, BOD5, nutrients etc. are available on the same conditions but still in digitalization/formatting/checking stage, should be added until December 2010.
5.4 USRIEP
The USRIEP team has began work on SWAT modeling of Seversky Donets river basin that is located in North-Eastern part of Ukraine and it is a major surface water body in the region. Using DEM map, European land-use map and soil map for Seversky Donets river basin there were marked out the borders of sub basins and defined their characteristics (within Kharkiv, Lugansk and Donetsk regions). There were sorted out hydrologic similar units and calculated their characteristics (HRU Analysis - Land use, Soil and Slope Definition). Source data is collecting for calculations of hydrological discharge and water quality of Seversky Donets River and also for model calibration.
After adaptation of SWAT program to Seversky Donets river basin, USRIEP team is planning to adapt SWAT model to Ukrainian part of Black Sea basin in cooperation with other Ukrainian WP4 participants for such regions as Crimea, Odessa, Nikolaev, Herson, Zaporozhie, Donetsk, Dnepropetrovsk.
Within the work on task 4.1 USRIEP team has provided following SWAT data:
a) DEM map of 90 m x 90 m of Ukraine (Grid format, Fig.1);
b) Soil map of Ukraine on a scale of М 1: 1 500 000 (hard copy);
c) European soil map of Ukraine on a scale of 1:5 000 m (Grid format);
d) European land-use map of Ukraine on a scale of 1:5 000 m (Grid format);
e) Digital map with indications of the hydro chemical control stations (monitoring stations) on a scale of 1: 500 000 (Shape format);
f) Digital map with indications of the meteorological stations on a scale of 1: 500 000 (Shape format);
g) Water quality data including information on:
- Suspended sediments transport, concentration of suspended solids, nitrates and phosphates transport with the river flow (kg N, kg. P), dissolved oxygen transport (kg O2), data on concentration of chemicals such as: ammonium (NH4), nitrites (NO2), mineral P (for the period from 1980 to 1992 – hard copy);
- Concentration of suspended solids; nitrates and phosphates transport with the river flow (kg N, kg. P), dissolved oxygen transport (kg O2), data on concentration of chemicals such as: ammonium (NH4), nitrites (NO2), mineral P (collected in outfall stations of the major rivers for the period from 1995 to 2008 e-form, Excel);
- River water quality data: concentration of suspended solids, nitrates and phosphates with the river flows (mg/liter N, Р), dissolved oxygen (mg/liter O2), data on concentration of chemicals such as ammonium (NH4), nitrites (NO2), mineral P for the period from 2006 to 2009 – e-form, Excel.
h) Temperature data (daily average– daytime and nighttime temperatures, atmospheric pressure) for the period from 1997 to 2010 (e-form);
i) Digital maps with indications of the location of major surface water intake points and wastes discharge from point-sources in Lugansk and Kharkov regions (Shape format);
j) Digital soil maps of Lugansk and Kharkov regions (Shape format).
The official meteorological and hydrological data centers in Ukraine are as shown in Table 4.
Table 4 - Official meteorological and hydrological data centers in Ukraine:
Name of hydrological data center (HDC) Location (city)
HDC in Crimea Simferopol
Vinnitsa HDC Vinnitsa
Volhynia HDC Lutsk
Dnepropetrovsk HDC Dnepropetrovsk
Donetsk HDC Donetsk
Zhitomir HDC Zhitomir
Transcarpathian HDC Uzgorod
Zaporoje HDC Zaporoje
Ivano-Frankovsk HDC Ivano-Frankovsk
Kirovograd HDC Kirovograd
Lugansk HDC Lugansk
Lvov HDC Lvov
Nikolaev HDC Nikolaev
Black and Azov Seas HDC Odessa
Poltava HDC Poltava
Rovno HDC Rovno
Sumy HDC Sumy
Ternopol HDC Ternopol
Kharkov HDC Kharkov
Herson HDC Herson
Hmelnitskiy HDC Hmelnitskiy
Chernovtsy HDC Chernovtsy
Cherkassy HDC Cherkassy
Chernigov HDC Chernigov
Ukrainian hydrological data center Kyiv
Central geophysical observatory Kyiv
At present, the following SWAT data are available:
a) Meteorological data
− Meteorological stations. Names and geographical positions – digital maps.
− Data on daily minimal and maximal temperature (text files for the period from 1997 -2010).
− Data on daily rainfall. We can obtain them after turning to relevant HDC.
b) Hydrological data
− Water quantity (for the period from 1980-1992, Excel format);
− Water quality (for the period from 1980-1992, 2009-2010, Excel format);
− Hydrological stations. Names and geographical positions – digital maps (Shape format);
− Outfall stations of rivers such as Dunaj, Dnieper, Juznyj Bug – data on water quality (for the period from 1992-2008, Excel format).
c) GIS data
− DEM map of 90m х 90m for whole research area - Figure 11(Grid format).
Figure 11 - Digital elevation map (DEM) of the investigation region
− Digital map with indications of the hydro chemical control stations (monitoring stations) on a scale of 1: 500 000 - Shape format (Figure 12, 13, 14);
Figure 12 - Location of hydro chemical control stations of Ukrainian State Hydro meteorological Service
Figure 13 - Location of hydro chemical control stations of Ukrainian State Ecological Inspection
Figure 14 - Location of hydro chemical control stations of Ukrainian State Water Economy Committee
− Digital map with indications of the meteorological stations on a scale of 1: 500 000 - Shape format (Figure 15).
Figure 15 - Location of meteorological stations in Ukraine
