Impact Assessment of Land-Use Changes on Nutrient Load in Song Cau Watershed Using Soil and Water Assessment Tool （SWAT） Model

The objective of this paper is to implement ＂Soil and Water Assessment Tool （SWAT）＂ model to assess the possible impact of land-use changes on nutrient yields from Song Cau watershed located in Northern Viet Nam. Organic nitrogen （N） as well as phosphorus （P） output due to nonpoint source erosion was estimated through SWAT. Parameters governing the mechanics of streamflow discharge, sediment yield, nitrogen, and phosphorus output in SWAT were calibrated in a distributed fashion. A five-year period of record for nutrient was used for model calibration, while a four-year period was used for model validation. Comparing measured versus simulated average monthly total N, and P loads for the calibration and validation periods; respectively, we found that SWAT model performed reasonably well for Song Cau watershed. Simulation results showed that monthly Nash-Sutcliffe coefficient of Efficiency （NSE） ranged from 0.65 to 0.83, observation＇s standard deviation ratio （RSR） and percent bias （PBIAS） ranged from 0.41 to 0.58 and -36.12 to 2.78, respectively. Additionally, SWAT simulation results also showed that land-use changes caused significant percentage of changes in sediment yield, total N, and P loads within Song Cau watershed.

Defining Soil and Water Assessment Tool(SWAT)hydrologic responseunits(HRUs)by field boundaries

The Soil and Water Assessment Tool(SWAT)is widely used to relate farm management practices to their impacts on surface waters at the watershed scale,yet its smallest spatial unit is not generally defined by physically meaningful boundaries.The hydrologic response unit(HRU)is the smallest spatial unit of the model,and the standard HRU definition approach lumps all similar land uses,soils,and slopes within a subbasin based upon user-defined thresholds.This standard method provides an efficient way to discretize large watersheds where simulation at the field scale may not be computationally feasible.In relatively smaller watersheds,however,defining HRUs to specific spatial locations bounded by property lines or field borders would often be advantageous,yet this is not currently possible within the ArcSWAT interface.In this study,a simple approach is demonstrated that defines HRUs by field boundaries through addition of uniquely named soils to the SWAT user soil database and creation of a field boundary layer with majority land use and soil attributes.Predictions of nitrogen,phosphorus,and sediment losses were compared in a case study watershed where SWAT was set up using both the standard HRU definition and field boundary approach.Watershed-scale results were reasonable and similar for both methods,but aggregating fields by majority soil type masked extremely high soil erosion predicted for a few soils.Results from field-based HRU delineation may be quite different from the standard approach due to choosing a majority soil type in each farm field.This approach is flexible such that any land use and soil data prepared for SWAT can be used and any shapefile boundary can divide HRUs.

Integrated Hydrological Modeling of the Godavari River Basin in Maharashtra Using the SWAT Model: Streamflow Simulation and Analysis

Hydrological modeling plays a crucial role in efficiently managing water resources and understanding the hydrologic behavior of watersheds. This study aims to simulate daily streamflow in the Godavari River Basin in Maharashtra using the Soil and Water Assessment Tool (SWAT). SWAT is a process-based hydrological model used to predict water balance components, sediment levels, and nutrient contamination. In this research, we used integrated remote sensing and GIS data, including Digital Elevation Models (DEM), land use and land cover (LULC) maps, soil maps, and observed precipitation and temperature data, as input for developing the SWAT model to assess surface runoff in this large river basin. The Godavari River Basin under study was divided into 25 sub-basins, comprising 151 hydrological response units categorized by unique land cover, soil, and slope characteristics using the SWAT model. The model was calibrated and validated against observed runoff data for two time periods: 2003-2006 and 2007-2010 respectively. Model performance was assessed using the Nash-Sutcliffe efficiency (NSE) and the coefficient of determination (R2). The results show the effectiveness of the SWAT2012 model, with R2 value of 0.84 during calibration and 0.86 during validation. NSE values also ranged from 0.84 during calibration to 0.85 during validation. These findings enhance our understanding of surface runoff dynamics in the Godavari River Basin under study and highlight the suit-ability of the SWAT model for this region.

Combining CLUE-S and SWAT Models to Forecast Land Use Change and Non-point Source Pollution Impact at a Watershed Scale in Liaoning Province, China

Non-point source(NPS) pollution has become a major source of water pollution. A combination of models would provide the necessary direction and approaches designed to control NPS pollution through land use planning. In this study, NPS pollution load was simulated in urban planning, historic trends and ecological protection land use scenarios based on the Conversion of Land Use and its Effect at Small regional extent(CLUE-S) and Soil and Water Assessment Tool(SWAT) models applied to Hunhe-Taizi River Watershed, Liaoning Province, China. Total nitrogen(TN) and total phosphorus(TP) were chosen as NPS pollution indices. The results of models validation showed that CLUE-S and SWAT models were suitable in the study area. NPS pollution mainly came from dry farmland, paddy, rural and urban areas. The spatial distribution of TN and TP exhibited the same trend in 57 sub-catchments. The TN and TP had the highest NPS pollution load in the western and central plains, which concentrated the urban area and farm land. The NPS pollution load would increase in the urban planning and historic trends scenarios, and would be even higher in the urban planning scenario. However, the NPS pollution load decreased in the ecological protection scenario. The differences observed in the three scenarios indicated that land use had a degree of impact on NPS pollution, which showed that scientific and ecologically sound construction could effectively reduce the NPS pollution load in a watershed. This study provides a scientific method for conducting NPS pollution research at the watershed scale, a scientific basis for non-point source pollution control, and a reference for related policy making.

Simulation of hydrological processes of mountainous watersheds in inland river basins: taking the Heihe Mainstream River as an example

The hydrological processes of mountainous watersheds in inland river basins are complicated.It is absolutely significant to quantify mountainous runoff for social,economic and ecological purposes.This paper takes the mountainous watershed of the Heihe Mainstream River as a study area to simulate the hydrological processes of mountainous watersheds in inland river basins by using the soil and water assessment tool(SWAT)model.SWAT simulation results show that both the Nash–Sutcliffe efficiency and the determination coefficient values of the calibration period(January 1995 to December 2002)and validation period(January 2002 to December 2009)are higher than 0.90,and the percent bias is controlled within±5%,indicating that the simulation results are satisfactory.According to the SWAT performance,we discussed the yearly and monthly variation trends of the mountainous runoff and the runoff components.The results show that from 1996 to 2009,an indistinctive rising trend was observed for the yearly mountainous runoff,which is mainly recharged by lateral flow,and followed by shallow groundwater runoff and surface runoff.The monthly variation demonstrates that the mountainous runoff decreases slightly from May to July,contrary to other months.The mountainous runoff is mainly recharged by shallow groundwater runoff in January,February,and from October to December,by surface runoff in March and April,and by lateral flow from May to September.

Impacts of Land Cover Changes on Runoff and Sediment in the Cedar Creek Watershed,St.Joseph River,Indiana,United States

The relation between runoff and sediment and land cover is investigated in the Cedar Creek Watershed （CCW）, located in Northeastern Indiana, United States. The major land cover types in this watershed are cultivated land, woodland and pasture /Conservation Reserve Program （CRP）, which account for approximate 90 % of the total area in the region. Moreover, land use was changed tremendously from aooo to 9004, even without regarding the effect of the crop rotation system （corn ＆ soybean）. At least 49 % of land cover types were changed into other types in this period. The land cover types, ranking by changing area from high to low series, are rye, soybean, corn, woodland and pasture/CRP. The CCW is divided into 21 subwatersheds, and soil and water loss in each sub-watershed is computed by using Soil and Water Assessment Tool （SWAT）. The results indicate that the variations in runoff and sediment have positive relation to the area of crops （especially corn and soybean）; sediment is more sensitive to land cover changes than runoff; more heavy rainfall does not always mean more runoff because the combination of different land cover types always modify runoff coefficient; and rye, soybean and corn are the key land cover types, which affected the variation in runoff and sediment in the CCW.

A Modified Groundwater Module in SWAT for Improved Streamflow Simulation in a Large, Arid Endorheic River Watershed in Northwest China

Interactions between surface water and groundwater are dynamic and complex in large endorheic river watersheds in Northwest China due to the influence of both irrigation practices and the local terrain. These interactions interchange numerous times throughout the middle reaches, making streamflow simulation a challenge in endorheic river watersheds. In this study, we modified the linear-reservoir groundwater module in SWAT(Soil and Water Assessment Tools, a widely used hydrological model) with a new nonlinear relationship to better represent groundwater processes; we then applied the original SWAT and modified SWAT to the Heihe River Watershed, the second largest endorheic river watershed in Northwest China, to simulate streamflow. After calibrating both the original SWAT model and the modified SWAT model, we analyzed model performance during two periods: an irrigation period and a non-irrigation period. Our results show that the modified SWAT model with the nonlinear groundwater module performed significantly better during both the irrigation and non-irrigation periods. Moreover, after comparing different runoff components simulated by the two models, the results show that, after the implementation of the new nonlinear groundwater module in SWAT, proportions of runoff components changed-and the groundwater flow had significantly increased, dominating the discharge season. Therefore, SWAT coupled with the non-linear groundwater module represents the complex hydrological process in the study area more realistically. Moreover, the results for various runoff components simulated by the modified SWAT models can be used to describe the hydrological characteristics of lowland areas. This indicates that the modified SWAT model is applicable to simulate complex hydrological process of arid endorheic rivers.

Effect of Land Use Change on Runoff and Sediment Yield in Da River Basin of Hoa Binh province, Northwest Vietnam

The objective of this study was to assess runoff discharge and sediment yield from Da River Basin in the Northwest of Vietnam using Soil and Water Assessment Tools(SWAT) model.The SWAT model was calibrated and validated using the observed monthly stream flows and sediment yield at selected gauging stations.The results indicated that SWAT generally performs well in simulating runoff and sediment yield according to Nash-Sutcliffe efficiency(NSE), Observation's standard deviation ratio(RSR), and percent bias(PBIAS) values.For runoff, the values of NSE, RSR, and PBIAS were 0.98,0.02, and 3.69 during calibration period and 0.99,0.01, and 1.56 during validation period, respectively.For sediment yield, the efficiency was lower than the value of NSE, RSR, and PBIAS during calibration period were 0.81, 0.19, and-4.14 and 0.84, 0.16, and-2.56 during validation period, respectively.The results of the study indicated that the vegetation status has a significant impact on runoff and sediment yield.Changes in land use type between 1995 and2005 from forest to field crop and urban strongly contributed to increasing the average annual runoff from 182.5 to 342.7 mm and sediment yield from101.3 to 148.1 ton-1 ha.Between 2005 and 2010, adecrease of both runoff(from 342.7 to 167.6 mm) and sediment yield(from 148.1 to 74.0 ton-1 ha) was due to the expansion of forested area and application of soil conservation practices.The results of this study are important for developing soil and water conservation programs, extending future SWAT modelling studies and disseminating these results to other regions in Vietnam.

Hydrological Impacts of Climate Change on Streamflow of Dongliao River Watershed in Jilin Province,China

The impacts of future climate change on streamflow of the Dongliao River Watershed located in Jilin Prov-ince, China have been evaluated quantitatively by using a general circulation model （HadCM3） coupled with the Soil and Water Assessment Tool （SWAT） hydrological model. The model was calibrated and validated against the historical monitored data from 2005 to 2009. The streamflow was estimated by downscaling HadCM3 outputs to the daily mean temperature and precipitation series, derived for three 30-year time slices, 2020s, 2050s and 2080s. Results suggest that daily mean temperature increases with a changing rate of 0.435~C per decade, and precipitation decreases with a changing rate of 0.761 mm per decade. Compared with other seasons, the precipitation in summer shows significant downward trend, while a significant upward trend in autumn. The annual streamflow demonstrates a general down-ward trend with a decreasing rate of 0.405 m^3/s per decade. The streamflow shows significant downward and upward trends in summer and in autumn, respectively. The decreasing rate of streamflow in summer reaches 1.97 m^3/s per decade, which contributes primarily to the decrease of streamflow. The results of this work would be of great benifit to the design of economic and social development planning in the study area.

Analysis of the Relationship between Landuse and Non-point Source Pollution in Ashi River Basin

Landuse is one of the most influential factors of non-point source pollution. Based on the three-year landuse data( 2000,2005 and 2008),Arc GIS and Fragstat were used to analyze the landuse type and the change of landscape pattern. The relationships between landuse and non-point source-total nitrogen( NPS-TN) and nonpoint source-total phosphorus( NPS-TP) were discussed with the methods of spatially statistical analysis,landscape pattern analysis and principal component analysis. The study results conveyed that agricultural land and forestland,which accounted for over 92% of the study area,were the major landuse type of Ashi River Basin.Meanwhile,the NPS pollution had close connections with landuse type and landscape pattern. When it comes to landuse type,the export risks of NPS-TN and NPS-TP were agricultural land > urban land > grassland > forestland. As for landscape pattern,NPS-TN and NPS-TP were positively related to SHDI and SHEI, while negatively connected with LPI,AI and COHESION. Therefore,the study could reach the conclusion that the more fragmented and complicated the landscape patterns were,the more serious the NPS pollution was.

A Comparison of SWAT Model Calibration Techniques for Hydrological Modeling in the Ganga River Watershed

The Ganga River, the longest river in India, is stressed by extreme anthropogenic activity and climate change, particularly in the Varanasi region. Anticipated climate changes and an expanding populace are expected to further impede the efficient use of water. In this study, hydrological modeling was applied to Soil and Water Assessment Tool （SWAT） modeling in the Ganga catchment, over a region of 15 621.612 km2 in the southern part of Uttar Pradesh. The primary goals of this study are： ① To test the execution and applicability of the SWAT model in anticipating runoff and sediment yield; and ② to compare and determine the best calibration algorithm among three popular algorithms-sequential uncertainty fitting version 2 （SUFI-2）, the generalized likelihood uncertainty estimation （GLUE）, and par-allel solution （ParaSol）. The input data used in the SWAT were the Shuttle Radar Topography Mission （SRTM） digital elevation model （DEM）, Landsat-8 satellite imagery, soil data, and daily meteorological data. The watershed of the study area was delineated into 46 sub-watersheds, and a land use/land cover （LULC） map and soil map were used to create hydrological response units （HRUs）. Models utilizing SUFI- 2, GLUE, and ParaSol methods were constructed, and these algorithms were compared based on five cat-egories： their objective functions, the concepts used, their performances, the values of P-factors, and the values of R-factors. As a result, it was observed that SUFI-2 is a better performer than the other two algo-rithms for use in calibrating Indian watersheds, as this method requires fewer runs for a computational model and yields the best results among the three algorithms. ParaSol is the worst performer among the three algorithms. After calibrating using SUFI-2, five parameters including the effective channel hydraulic conductivity （CH_K2）, the universal soil-loss equation （USLE） support parameter （USLE_P）, Manning＇s n value for the main channel （CH_N2）, the surface runoff lag time （SURLAG）, and the available water capac-ity of the soil layer （SOL_AWC） were observed to be the most sensitive parameters for modeling the pre-sent watershed. It was also found that the maximum runoff occurred in sub-watershed number 40 （SW#40）, while the maximum sediment yield was 50 t.a ^1 for SW#36, which comprised barren land. The average evapotranspiration for the basin was 411.55 mm.a ^1. The calibrated model can be utilized in future to facilitate investigation of the impacts of LULC, climate change, and soil erosion.

Predictive simulation and optimal allocation of surface water resources in reservoir basins under climate change

Predicting and allocating surface water resources are becoming increasingly important tasks for addressing the risk of water shortages and challenges of climate change,especially in reservoir basins.However,surface water resource management includes many systematic uncertainties and complexities that are difficult to address.Thus,advanced models must be developed to support predictive simulations and optimal allocations of surface water resources,which are urgently required to ensure regional water supply security and sustainable socioeconomic development.In this study,a soil and water assessment tool-based interval linear multi-objective programming(SWAT-ILMP)model was developed and integrated with climate change scenarios,SWAT,interval parameter programming,and multi-objective programming.The developed model was applied to the Xinfengjiang Reservoir basin in South China and was able to identify optimal allocation schemes for water resources under different climate change scenarios.In the forecast year 2025,the optimal water quantity for power generation would be the highest and account for∼60%of all water resources,the optimal water quantity for water supply would account for∼35%,while the optimal surplus water released from the reservoir would be the lowest at≤5%.In addition,climate change and reservoir initial storage would greatly affect the surplus water quantity but not the power generation or water supply quantity.In general,the SWAT-ILMP model is applicable and effective for water resource prediction and management systems.The results from different scenarios can provide multiple alternatives to support rational water resource allocation in the study area.

Estimation of Pollutant Loads in Ardila Watershed Using the SWAT Model

Abstract： Excess of organic matter and nutrients in water promotes eutrophication process observed in the Ardila River. It was classified as much polluted being critical for Alqueva-Pedrogāo System. The aim of this study was to estimate the transported nutrients loads in a transboundary watershed using the SWAT （soil and water assessment tool） model and to determine the contribution of nutrients load in the entire watershed. Ardila watershed is about 3,711 km^2 extended from Spain （78%） to the eastern part of Portugal （22%）. It was discretized into 32 sub-basins using automated delineation routine, and 174 hydrologic response units. Monthly average meteorological data （from 1947 to 1998） were used to generate daily values through the weather generator Model incorporated in SWAT. Real daily precipitation （from 1931 to 2003） was introduced. The model was calibrated and verified for flow （from 1950 to 2000） and nutrients （from 1981 to 1999）. Model performance was evaluated using statistical parameters, such as NSE （Nash-Sutcliffe efficiency） and root mean square error （R2）. Calibration and verification flow results showed a satisfactory agreement between simulated and measured monthly date from 1962 to 1972 （NSE = 0.8; R^2 = 0.9）. The results showed that the most important diffuse pollution comes from the two the main tributary （Spain）. The estimated nitrogen and phosphorous loads contribution per year was respectively 72% and 59% in Spain and 28% and 41% in Portugal. The SWAT model was revealed to be a useful tool for an integrated water management approach that might be improved taking into count the WFD （water framework directive）.

Runoff Modeling in Ungauged Catchments Using Machine Learning Algorithm-Based Model Parameters Regionalization Methodology

Model parameters estimation is a pivotal issue for runoff modeling in ungauged catchments.The nonlinear relationship between model parameters and catchment descriptors is a major obstacle for parameter regionalization,which is the most widely used approach.Runoff modeling was studied in 38 catchments located in the Yellow–Huai–Hai River Basin(YHHRB).The values of the Nash–Sutcliffe efficiency coefficient(NSE),coefficient of determination(R2),and percent bias(PBIAS)indicated the acceptable performance of the soil and water assessment tool(SWAT)model in the YHHRB.Nine descriptors belonging to the categories of climate,soil,vegetation,and topography were used to express the catchment characteristics related to the hydrological processes.The quantitative relationships between the parameters of the SWAT model and the catchment descriptors were analyzed by six regression-based models,including linear regression(LR)equations,support vector regression(SVR),random forest(RF),k-nearest neighbor(kNN),decision tree(DT),and radial basis function(RBF).Each of the 38 catchments was assumed to be an ungauged catchment in turn.Then,the parameters in each target catchment were estimated by the constructed regression models based on the remaining 37 donor catchments.Furthermore,the similaritybased regionalization scheme was used for comparison with the regression-based approach.The results indicated that the runoff with the highest accuracy was modeled by the SVR-based scheme in ungauged catchments.Compared with the traditional LR-based approach,the accuracy of the runoff modeling in ungauged catchments was improved by the machine learning algorithms because of the outstanding capability to deal with nonlinear relationships.The performances of different approaches were similar in humid regions,while the advantages of the machine learning techniques were more evident in arid regions.When the study area contained nested catchments,the best result was calculated with the similarity-based parameter regionalization scheme because of the high catchment density and short spatial distance.The new findings could improve flood forecasting and water resources planning in regions that lack observed data.

A comparison of single- and multi-site calibration and validation： a case study of SWAT in the Miyun Reservoir watershed, China

An essential task in evaluating global water resource and pollution problems is to obtain the optimum set of parameters in hydrological models through calibra- tion and validation. For a large-scale watershed, single-site calibration and validation may ignore spatial heterogeneity and may not meet the needs of the entire watershed. The goal of this study is to apply a multi-site calibration and validation of the Soil and Water Assessment Tool （SWAT）, using the observed flow data at three monitoring sites within the Baihe watershed of the Miyun Reservoir watershed, China. Our results indicate that the multi-site calibration parameter values are more reasonable than those obtained from single-site calibrations. These results are mainly due to significant differences in the topographic factors over the large-scale area, human activities and climate variability. The multi-site method involves the division of the large watershed into smaller watersheds, and applying the calibrated parameters of the multi-site calibration to the entire watershed. It was anticipated that this case study could provide experience of multi-site calibration in a large-scale basin, and provide a good foundation for the simulation of other pollutants in follow- up work in the Miyun Reservoir watershed and other similar large areas.

Application of Spatially Distributed Calibrated Hydrological Model in Evapotranspiration Simulation of Three Gorges Reservoir Area of China:A Case Study in the Madu River Basin

Evapotranspiration(ET)is the key to the water cycle process and an important factor for studying near-surface water and heat balance.Accurately estimating ET is significant for hydrology,meteorology,ecology,agriculture,etc..This paper simulates ET in the Madu River Basin of Three Gorges Reservoir Area of China during 2009-2018 based on the Soil and Water Assessment Tool(SWAT)model,which was calibrated and validated using the MODIS(Moderate-resolution Imaging Spectroradiometer)/Terra Net ET 8-Day L4 Global 500 m SIN Grid(MOD16A2)dataset and measured ET.Two calibration strategies(lumped calibration(LC)and spatially distributed calibration(SDC))were used.The basin was divided into 34 sub-basins,and the coefficient of determination(R^(2))and NashSutcliffe efficiency coefficient(NSE)of each sub-basin were greater than 0.6 in both the calibration and validation periods.The R2 and NSE were higher in the validation period than those in the calibration period.Compared with the measured ET,the accuracy of the model on the daily scale is:R^(2)=0.704 and NSE=0.759(SDC results).The model simulation accuracy of LC and SDC for the sub-basin scale was R^(2)=0.857,R^(2)=0.862(monthly)and R^(2)=0.227,R^(2)=0.404(annually),respectively;for the whole basin scale was R^(2)=0.902,R^(2)=0.900(monthly)and R^(2)=0.507 and R^(2)=0.519(annually),respectively.The model performed acceptably,and SDC performed the best,indicating that remote sensing data can be used for SWAT model calibration.During 2009-2018,ET generally increased in the Madu River Basin(SDC results,7.21 mm/yr),with a multiyear average value of 734.37 mm/yr.The annual ET change rate for the sub-basin was relatively low upstream and downstream.The linear correlation analysis between ET and meteorological factors shows that on the monthly scale,precipitation,solar radiation and daily maximum and minimum temperature were significantly correlated with ET;annually,solar radiation and wind speed had a moderate correlation with ET.The correlation between maximum temperature and ET is best on the monthly scale(Pearson correlation coefficient R=0.945),which may means that the increasing ET originating from increasing temperature(global warming).However,the sub-basins near Shennongjia Nature Reserve that are in upstream have a negative ET change rate,which means that ET decreases in these sub-basins,indicating that the’Evaporation Paradox’exists in these sub-basins.This study explored the potential of remote-sensing-based ET data for hydrological model calibration and provides a decision-making reference for water resource management in the Madu River Basin.

Calibration of Hydrological Streamflow Modeling Using MODIS

LULC （land use and land cover） plays an important role in mathematical hydrological modeling. As many countries, available LULC are not always updated to reflect the most current situation. In this regard, the objective of this study was to investigate the potential capability of moderate resolution satellite imagery such as MODIS （Moderate Resolution Imaging Spectroradiometer）, acquired in 2010 for updated LULC. This issue was illustrated through the application of the most current LULC as one of the data inputs of the SWAT （Soil and Water Assessment Tool） model in the Tonle Sap Lake Basin, a sub-basin of the Mekong River. The streamflow was tested using moderate resolution LULC of 500 meters. The statistical evaluation results at a monitoring station for model calibration and validation showed that the R2 for daily and monthly values range from 0.76 to 0.88 and 0.86 to 0.89 respectively, whereas the Nash-Sutcliffe efficiency daily and monthly values range between 0.75 to 0.85 and 0.76 to 0.87 respectively. The simulation result based on MODIS imagery demonstrates LULC at moderate resolution holds considerable potential as an effective hydrological modeling tool. An additional level of confidence is provided by the notion that the methods described here could be applied in similar watershed conditions.

Evaluation of non-point source pollution reduction by applying Best Management Practices using a SWAT model and QuickBird high resolution satellite imagery

This study evaluated the reduction effect of non-point source pollution by applying best management practices （BMPs） to a 1.21 km^2 small agricultural watershed using a SWAT （Soil and Water Assessment Tool） model. Two meter QuickBird land use data were prepared for the watershed. The SWAT was calibrated and validated using dally streamflow and monthly water quality （total phosphorus （TP）, total nitrogen （TN）, and suspended solids （SS）） records from 1999 to 2000 and from 2001 to 2002. The average Nash and Sutcliffe model efficiency was 0.63 for the streamflow and the coefficients of determination were 0.88, 0.72, and 0.68 for SS, TN, and TP, respectively. Four BMP scenarios viz. the application of vegetation filter strip and riparian buffer system, the regulation of Universal Soil Loss Equation P factor, and the fertilizing control amount for crops were applied and analyzed.

Runoff variation and its response to climate change in the Three Rivers Source Region

Runoff at the three time scales （non-flooding season, flooding season and annual period） was simulated and tested from 1958 to 2005 at Tangnaihai （Yellow River Source Region： YeSR）, Zhimenda （Yangtze River Source Region： YaSR） and Changdu （Lancang River Source Region： LcSR） by hydrological modeling, trend detection and comparative analysis. Also, future runoff variations from 2010 to 2039 at the three outlets were analyzed in A1B and B1 scenarios of CSIRO and NCAR climate model and the impact of climate change was tested. The results showed that the annual and non-flooding season runoff decreased significantly in YeSR, which decreased the water discharge to the midstream and down- stream of the Yellow River, and intensified the water shortage in the Yellow River Basin, but the other two regions were not statistically significant in the last 48 years. Compared with the runoff in baseline （1990s）, the runoff in YeSR would decrease in the following 30 years （2010-2039）, especially in the non-flooding season. Thus the water shortage in the mid- stream and downstream of the Yellow River Basin would be serious continuously. The runoff in YaSR would increase, especially in the flooding season, thus the flood control situation would be severe. The runoff in LcSR would also be greater than the current runoff, and the annual and flooding season runoff would not change significantly, while the runoff variation in the non-flooding season is uncertain. It would increase significantly in the B1 scenario of CSIRO model but decrease significantly in B1 scenario of NCAR model. Furlhermore, the most sensitive region to climate change is YaSR, followed by YeSR and LcSR.

Uncertainty analysis of hydrological model parameters based on the bootstrap method:A case study of the SWAT model applied to the Dongliao River Watershed,Jilin Province,Northeastern China

As an important tool for the description and analysis of hydrological processes,the watershed hydrological model has been increasingly applied to watershed hydrological simulations and water resource management.However,in most cases,model parameters are only determined in a calibration scheme which fits the modeled data to observations,thus significant uncertainties exist in the model parameters.How to quantitatively evaluate the uncertainties in model parameters and the resulting uncertainty impacts on model simulations has always been a question which has attracted much attention.In this study,two methods based on the bootstrap method(specifically,the model-based bootstrap and block bootstrap)are used to analyze the parameter uncertainties in the case of the SWAT(Soil and Water Assessment Tool)model applied to a hydrological simulation of the Dongliao River Watershed.Then,the uncertainty ranges of five sensitivity parameters are obtained.The calculated variation coefficients and the variable parameter contributions show that,among the five parameters,ESCO and CN2 have relatively high uncertainties:the variation coefficients and contribution rates are 23.98 and 70%,14.43 and 18%,respectively.The three remaining parameters have relatively low uncertainties.We compare the two uncertainty ranges of parameters acquired by the two bootstrap methods,and find that the uncertainty ranges of parameters acquired by the block bootstrap are narrower than those acquired by the model-based bootstrap.Further analysis of the effects of parameter uncertainties on the model simulation reveals that the parameter uncertainties have great impacts on results of the model simulation,and in the model calibration stage 60%70%of runoff observations were within the corresponding 95%confidence interval.The uncertainty in the model simulation during the flood season(i.e.the wet period)is relatively higher than that during the dry season.