Dresden University of Technology Faculty of Forest, Geo and Hydro Sciences Quantification of water and nutrient flows on a river catchment scale under scarce data conditions (A case study of Western Bug river basin, Ukraine) By Tatyana Terekhanova Thesis is submitted in partial fulfillment of the examination requirements for the academic degree of Master of Science in Hydro Science and Engineering (MSc. HS & E.) Supervisors: Dr.-Ing. Jens Tränckner Dipl.-Ing. Björn Helm Institute of Urban Water Management TU-Dresden, Germany Responsible Professor: Prof. Dr. Sc.techn. Peter Krebs Institute of Urban Water Management TU-Dresden, Germany Lending admitted/ not admitted TU-Dresden, Germany Chairman of Examination Commission Dresden, November 2009 Declaration This is my original work and has not been submitted for a degree award in any other University. ___________________________ Tatyana Terekhanova Born: 9th August 1984 This thesis has been submitted for examination with our approval as the University Supervisors ____________________________ Dipl.-Ing. Björn Helm ____________________________ Dr.-Ing. Jens Tränckner ____________________________ Prof. Dr. Sc.techn. Peter Krebs Acknowledgement Herewith I would like to thank the German Academic Exchange Service (DAAD) for the support of my study in Germany through a generous two year scholarship. This study opened for me new horizons in my subject and gave the chance to get to know many highly-qualified and experienced colleagues in Hydro sciences from all over the world. I am very grateful to Prof.Dr.Peter Krebs for having accepted me as his student. I appreciate very much Dr. Jens Tränckner for his comprehensive support, advices and inspiration given to me while the compilation of this thesis. My deepest gratitude goes to Björn Helm for his encyclopedic help in process of data acquisition, organizational issues and readiness to reply to my questions. I thank very much the staff members of the German Leibniz-Institute of Freshwater Ecology and Inland Fisheries, in particularly, Dr.Markus Venohr and Dipl.Phys. Dietmar Opitz for the cooperation in set up of the model. I am also very grateful to the IWAS-Ukraine project team and their Ukrainian partners for the help in data acquisition. For the opportunity to study, permanent support and encouragement I am deeply thankful to my great parents. Abstract This thesis describes the set-up of mass flow analysis on river basin scale. The water and nutrient matter flows were estimated for the W.Bug basin (Ukraine) with the application of the evaluation tool MONERIS. The model was chosen due to such criteria as medium complexity of the processes description and low input data requirements. In order to estimate the influence of the data availability on the MFA set up with MONERIS two data sets were applied, which differed in accuracy of such input data as land cover, amount of precipitations, N-surplus and P- accumulation in agricultural areas, river network length. One set of data is characterized as “local” and another is “remote” due to origin from Ukrainian and other information sources correspondingly. The model was run in annual time resolution for a watershed W.Bug – Kamianka-Bugska, which was divided into 16 sub-catchments. The modeling period corresponds to 1995 – 1998, for which the model validation data were available. Additionally, the option of MONERIS to calculate nutrient loads for design years (“long-term”, dry and wet year) was used. The validation of the modeling results has shown better fit of the water and matter flows estimated with “local” data set for the “long-term” design year with reference “long-term” load values. The major part of the estimated nitrogen loads is originated from agricultural areas and is delivered with groundwater pathway. In contrast, the phosphorous load is coming mainly from the communal WWTP and delivered accordingly with point sources. Comparison of the modeling results performed with two data sets has shown strong dependence of the model on the accuracy of land cover information, especially nitrogen load estimations in comparison to phosphorous loads, which calculation approach is strongly parameterized in the model. The evaluation of sensitivity and uncertainty of the modeling results was performed qualitatively due to the fact that the model was not available for additional runs. For the estimation of parameter sensitivity of the Urban system pathway of MONERIS, the pathway was reproduced after MONERIS approach description. Such issues as influence of different input data on modeling results, modeling results of MONERIS, application of the quantification tool on W.Bug basin conditions, possible remediation measures are discussed. Recommendations for further model development, data acquisition in the W.Bug basin and remediation of the nutrient loads are given. The thesis includes 80 pages with 18 tables, 54 figures, 63 references In Annexes - 2 figures - 10 tables Table of content Abbreviations and Acronyms……………………………………………………………… ii List of figures………………………………………………………………………………. iv List of tables………………………………………………………………………………... v 1. Introduction……………………………………………………………………………… 1 1.1. Problem description……………………………………………………………. 1 1.2. Objectives……………………………………………………………………… 3 2. Mass Flow Analysis on river basin scale: literature review……………………………... 4 2.1. General concept of MFA…………………………………………………………. 4 2.2. MFA for river basin scale………………………………………………………... 5 2.2.1. Specific properties of matter flows in river basin………………………. 5 2.2.2. Nutrients: sources, transformation processes and sinks…………………. 8 2.2.2.1. Cycling of Nitrogen…………………………………………….. 8 2.2.2.2. Cycling of Phosphorous………………………………………... 11 2.3. Available models and tools for Nutrients Flow Analysis on river basin scale…... 13 2.3.1. Types of models…………………………………………………………. 13 2.3.2. Existing mass balance models and tools for river basin scale and their evaluation………………………………………………………………………. 15 2.3.3. MONERIS (Modeling of Nutrient Emissions in River System)………… 19 3. Methodology…………………………………………………………………………….. 23 3.1. Study case: Western Bug river basin…………………………………………….. 23 3.2. Model set up……………………………………………………………………… 30 3.3. Data acquisition and related calculations………………………………………… 31 3.3.1 Basic information………………………………………………………… 32 3.3.2. Time series data (“Periodical data”)…………………………………….. 43 3.3.3. Individual WWTPs……………………………………………………… 47 3.3.4. Country data……………………………………………………………... 47 3.3.5. Measured runoff and nutrient loads……………………………………... 48 3.4. Validation of the model results…………………………………………………... 49 3.4.1. Model precision…………………………………………………………. 49 3.4.2. Model accuracy………………………………………………………….. 51 3.5. Sensitivity analysis……………………………………………………………….. 52 3.5.1. Response of the model on “local” and “remote” data sets………………. 52 3.5.2. MONERIS - Urban System……………………………………………… 56 3.6. Uncertainty analysis……………………………………………………………… 60 3.6.1. Uncertainty in input data………………………………………………… 61 3.6.2. Uncertainty in modeling…………………………………………………. 62 4. Results and Discussion…………………………………………………………………... 64 4.1. Evaluation of modeling Results………………………………………………... 64 4.2. Application of scenarios……………………………………………………….. 70 4.3. Discussion……………………………………………………………………… 71 5. Conclusions and Recommendations……………………………………………………... 74 5.1. Conclusions…………………………………………………………………….. 74 5.2. Recommendations……………………………………………………………… 75 References………………………………………………………………………………….. 76 Annexes…………………………………………………………………………………….. 81 i Abbreviations and Acronyms Description Unit a Substance in input good ABAG General Soil Losses Equation (Algemeine Boden Abtrag Gleichnung) ADdir_prec Runoff from precipitation falling directly on surface runoff [m3/s] Aopm Areas with open mining [km2] ASR_snow Snow covered area [km2] ATD Tile drained areas [km2] AtotalAU Total area of sub-basin [m3/s] ATV - DVWK Abwassertechnische Vereinigung fuer Wasserwirtschaft, Abwasser und Abfall b Substance in output good BOD5 Biological Oxygen Demand within 5 days BSDB Baltic Sea Drainage basin c Concentration [kg/m3] CLC CORINE land cover COD Chemical Oxygen Demand CORINE Coordination on Information on the Environment CSO Combined Sewer Overflow DEM Digital Elevation Model DIN Dissolved Inorganic Nitrogen DWD German Weather Service ECA European Climate Assessment ESRI Environmental System Research Institute EU European Union EUROHARP Project “Towards European Harmonized Procedures for Quantification of Nutrient Losses from Diffuse Sources EWFD European Water Framework Directive FAO-UNO/FAO Food and Agricultural Organization of the United Nations GIS Geographical information system GPCC The Global Precipitation Climatology Centre IDW Inverse Distance weighted interpolation IGB German Leibniz-Institute of Freshwater Ecology and Inland Fisheries IHM TUD Institute for Hydrology and Meteorology of the Dresden University of Technology ISI TUD Institute for industrial and urban water management of the Dresden University of Technology IWAS - Ukraine International Water Alliance Saxony, model region Ukraine IWRM Integrated Water Resources Management KGWRA1 Area of groundwater renewal [km2] ki Transfer coefficient L Matter load [kg] MFA Material Flow Analysis MONERIS Modeling of Nutrient Emissions in River system N Nitrogen NASA-SRTM National Aeronautics and Space Administration - Shuttle Radar Topography Mission ii NM Nutrient matter NOAA National Oceanic and Atmospheric Administration Ntotal Total nitrogen P Phosphorous PELCOM Pan-European Land Cover Monitoring Q Water discharge [m3/s] QGW Ground water