Modeling And Prediction Of Water Quality In Headwater Area Of Reservoir And Uncertainty Analysis

Water is the material foundation of mankind's survival and development, and thesafety of drinking water is even more important to people's health and livelihood. Insouthern China, with rapid socio-economic development and urbanization, water inthe middle and lower reaches of many rivers has lost its function for drinking due toincreasing point-source pollution and non-point-source (NPS) pollution, andreservoirs became the most important municipal centralized water supply sources.Therefore, systematically research on protection of headwater area of reservoir hasprofound and significant meanings.Variation of water quality is the foundation for the water quality protection inheadwater area of reservoir. Modeling and prediction of water quality is key approachfor the protection research, and the predicted results are also the main theoretical basisfor creating scientific and reasonable emission control project. The aims of the presentstudy were to establish a methodological and technical system for modeling andprediction of water quality in headwater area of Laohutan reservoir watershed inHuzhou, Zhejiang Province, Southern China. Water quality throughout the Laohutanreservoir watershed were monthly measured continuously for the whole year, whichcombined with investigation of natural, social and economic conditions. Based on theanalysis of overall datum, water environmental quality in Laohutan reservoirwatershed was evaluated in each reach and period, and spatio-temporal variations andthe composition analysis of main pollutants were also studied. Sub-watersheds wereseparated by means of SWAT2002 in Laohutan reservoir, and each produce flux ofmain pollutant were gained in each sub-watershed. Based on integrative considerationof the effects of point-source pollution, NPS pollution and environmental backgroundvalues on river water quality in headwater area, and one-dimensional river waterquality model for headwater area (1-D RWQHA model) was founded, and the keycoefficient (export coefficient of NPS pollution) in the model was calibrated usingmulti-objective genetic algorithm (MOGA) based on NSGA-â…¡. As a case study, 1-DRWQHA model, Vollenweider model and Dillon model were used to predict the variations of water quality in the river-reservoir system in Laohutan reservoirwatershed. Finally, based on the response relations between input parameters andoutputs, uncertainty and sensitivity on 1-D RWQHA mode was analyzed by usingMonte-Carlo method, and the main uncertainty factors were identified.The main conclusions of the dissertation included:1) Water quality at 12 sampling sites throughout the Laohutan reservoir watershedwere monthly measured continuously for the whole year from Jan 2007 to Dec 2007,which combined with investigation of natural, social and economic conditions. Basedon single index method and fuzzy synthetic method, river water quality wereevaluated, and the results showed that the water quality in all sampling sites were orbetter than Gradeâ…¢I.2) Total nitrogen (TN), total phosphorus (TP), ammonia-nitrogen (NH₃-N) andCOD_Mn were the main pollution factors in this watershed, and organic and nutrientpollution was the main pollution problem in this headwaters area. Pollutant produceflux from NPS pollution (rural domestic waste pollution, livestock-poultry wastepollution, agricultural NPS pollution) was the main pollution source, and the produceflux from NPS pollution occupied above 95% in total amount. In all pollution sources,agricultural NPS pollution and livestock- poultry waste pollution were the mainsources of TN and TP, which occupied 80% of total produce flux of TN and TP.Livestock- poultry waste pollution and rural domestic waste pollution were the mainsources of NH₃-N, which occupied 45.52%, 30.70% of total produce flux of NH₃-N,respectively. Livestock-poultry waste pollution and agricultural non-point pollutionwere the main sources of organic matter, which occupied 36.57%, 34.98% of totalproduce flux of organic matter, respectively.3) According to the pollution characteristics and river feature in headwater area ofreservoir, 1-D RWQHA model was founded. The model integrative considered theeffects of point-source pollution, NPS pollution, and environmental backgroundvalues on river water quality. The denotation of 1-D RWQHA model as follow: 4) Pollutant degradation coefficients, pollutant environmental background values,and the distribution of monthly pollutant export amount from different pollutionsources were calibrated and validated. Multi-objective optimization model wasestablished to solve export coefficient in each sub-watershed based on 1-D RWQHAmodel. Using Matlab the Pareto solution set of multi-objective optimization modelwas solved by means of NSGA-â…¡. According to the difference of sub-watershedcharacteristics and the pollution sources feature, proper export coefficients were chosein the Pareto solution set.5) After the calibration of all parameters and input data of 1-D RWQHA model,the model was validated. The validation result showed that the predicted valuesagreed well with the measured values, and the average errors basically within±20%.6) Combining with 1-D RWQHA model, Vollenweider model and Dillon model,water quality of river-reservoir system was synchronized predicted under differenthydrology and emission conditions. The results showed that, in current emissioncondition, the predicted concentrations of NH₃-N and COD_Mn in rivers and reservoirwere all between gradeâ… -â…¡water quality levels. If the emission of point-sourcepollution and NPS pollution were doubled, the predicted concentrations of COD_Mnwere in gradeâ…£water quality for some tributaries in dry hydrologic year, theremainders were in gradeâ… -â…¢water quality, while the predicted concentrations ofNH₃-N and COD_Mn in reservoir maintained gradeâ… -â…¡water quality. In currentemission condition, the predicted concentrations of TP in river s were in gradeâ…¡-â…¢water quality, and the predicted concentrations of TN and TP in reservoir would be ingradeâ…¢in flooding and average hydrologic year, but would be in gradeâ…£in dryhydrologic year due to the water quality standard of nutrient in reservoir is morerigorous than that in river. If 50% point-source pollution emission and 26% NPSpollution emission were reduced, the predicted concentrations of TN and TP inreservoir would or better than gradeâ…¢water quality in all hydrologic years.7) Uncertainty on predicted concentrations of TN in Daixi river in each hydrologic period in 2007 was analyzed by using Monte-Carlo method based on 1-D RWQHAmodel. The results showed that the effects of degradation coefficient k andpoint-source pollution load q_i on model's outputs were minor, the effects of river flowQ_e and environmental background value C_b on model's outputs were medium, and theeffect of structural uncertainty on model's outputs was major. Thus, to diminish theuncertainty of 1-D RWQHA model's outputs, the research about allocation of monthlynon-point transport flux should strengthen. In current condition, the predicted valuesshowed normal distribution, and the approximately 90% of values within the range of±20% of mean value. The model's output uncertainty could diminish via decreasedthe uncertainty of model's uncertainty sources. If the uncertainty of each sourcedecreased 50%, the approximately 90% of values would within the range of±10% ofmean value.The innovated progress of this dissertation included:1) The concept of "entropy" in informatics was applied in the determination of theweight for evaluating indicators in fuzzy synthetic water quality evaluation. Usingfuzzy synthetic evaluation based on entropy not only avoided the one-sidedness ofsingle index method, but also considered the correlation of different evaluatedsubjects. Thus, the results of fuzzy synthetic evaluation based on entropy were morescientific and reasonable.2) According to the pollution characteristics and river feature in headwater area ofreservoir, and combined with current studies about river water quality model and NPSpollution, 1-D RWQHA model integrative considered the effects of point-sourcepollution, NPS pollution, and environmental background values on river water qualitywas founded. Thus, a methodological and technical system for modeling andprediction of river water quality in headwater area of reservoir which dominated byNPS pollution was created.3) Multi-objective optimization model was created to solve export coefficients ineach sub-watershed, and solved by MOGA based on NSGA-â…¡. Proper exportcoefficients were solved according to the difference of sub-watershed characteristic and the pollution sources feature. The export coefficients identification methodprovided new idea and new approach for NPS pollution research.4) Combining with 1-D RWQHA model, Vollenweider model and Dillon model,water quality of river-reservoir system was synchronized predicted under differenthydrology and emission conditions, and reasonable emission control project for wholewatershed was founded.5) Sources of model uncertainty include parameter uncertainty, input datauncertainty and structural uncertainty, and the uncertainty of 1-D RWQHA model wasstudied by using Monte-Carlo method. The range and distribution of outputs wereanalyzed, and the main uncertainty factors were identified using "tornado graphs".The results of uncertainty analysis provided theoretical basis for model furtherimprovement.