降水空间异质性对非点源关键源区识别面积变化的影响

针对地形起伏和降水空间差异较大的农业区非点源污染问题,基于SWAT模型评估了阿什河流域在异质性降水和均匀降水两种情景下总氮、总磷关键源区空间变化规律,统计了两种情景下识别的关键源区面积变化,并分析其与降水特征参数的关系.结果表明,降水量一定时,两种情景下识别的总氮、总磷关键源区面积变化趋势大致相同,且总磷关键源区面积不易受降水空间异质性的影响,但总氮关键源区面积却明显受到其影响.对各年份总氮和总磷关键源区面积与降水特征参数的相关分析表明,总磷关键源区面积与当年降水量呈显著正相关,而总氮关键源区面积却与前一年降水量呈显著正相关.研究结果对进一步探讨降水这一重要驱动因子的不确定性对非点源污染关键源区的影响,以及农业非点源污染的治理具有重要意义.     

Modeling of non-point source pollution in a Mediterranean drainage basin

SWAT ver. 2000 was used to predict hydrographs, and sediment, nitrate and total phosphorus loadings from a 1349 km² mountainous/agricultural watershed in Northern Greece. The model was calibrated and verified using continuous meteorological data from eight stations within the drainage area, and runoff, sediment and nutrient concentrations measured at nine stations located within the main tributaries of the watershed, for the time period from May 1st, 1998 to January 31st, 2000. Model validation methodology and resulting input parameters appropriate for Mediterranean drainage basins are presented. Predicted by the model hydrographs, sedimentographs and pollutographs are plotted against observed values and show good agreement. Model performance is evaluated using the root mean square error computation and scattergrams of predicted versus observed data. The validated model is also used to test the effectiveness of three alternative cropping scenarios in reducing nutrient loadings from the agricultural part of the watershed. The study showed that this model, if properly validated, can be used effectively in testing management scenarios in Mediterranean drainage basins.     

基于WARMF模型的杭埠-丰乐河流域水文模拟研究

研究了WARMF模型在杭埠-丰乐河流域(巢湖流域最大支流)的水文模拟适应性能并进行了流域水文系统分析.利用AVSWAT2000模型将流域划分为37个子流域,利用流域地貌-土壤分布对应关系、土壤剖面结构、地下水位埋深等条件,确定了子流域的平面分组与剖面土层结构,较大程度上降低了流域模型参数校准的难度与不确定性.利用2000～2003年的水文观测数据,在参数灵敏度分析基础上,对模型水文参数进行了校准与检验.结果表明,WARMF在研究区具有较好的适应性能.WARMF模型与AVSWAT2000模型的水文模拟结果对比表明,WARMF模型具有更好的日拟合性能.基于模型的模拟结果,在空间尺度上定量分析了流域从降水开始到入湖的水循环过程,在时间尺度上分析了年内降雨、径流的分布及其对应关系.流域概化、模型的校准与检验以及流域水文时空变化的系统分析方法等对流域水文、环境的模拟研究与系统分析具有探索意义.     

How effective are River Basin Management Plans in reaching the nutrient load reduction targets?

Riverine nutrient loads are among the major causes of eutrophication of the Baltic Sea. This study applied the Soil & Water Assessment Tool (SWAT) in three catchments flowing to the Baltic Sea, namely Vantaanjoki (Finland), Fyrisån (Sweden), and Słupia (Poland), to simulate the effectiveness of nutrient control measures included in the EU’s Water Framework Directive River Basin Management Plans (RBMPs). Moreover, we identified similar, coastal, middle-sized catchments to which conclusions from this study could be applicable. The first modelling scenario based on extrapolation of the existing trends affected the modelled nutrient loads by less than 5%. In the second scenario, measures included in RBMPs showed variable effectiveness, ranging from negligible for Słupia to 28% total P load reduction in Vantaanjoki. Adding spatially targeted measures to RBMPs (third scenario) would considerably improve their effectiveness in all three catchments for both total N and P, suggesting a need to adopt targeting more widely in the Baltic Sea countries.Electronic supplementary materialThe online version of this article (10.1007/s13280-020-01393-x) contains supplementary material, which is available to authorized users.     

基于SWAT模型的三峡库区香溪河非点源氮磷负荷模拟

三峡水库蓄水后,水动力条件改变下营养盐的过量输入导致部分支流库湾水华现象及水体富营养化问题严重.本文以香溪河为研究示范区,基于GIS平台建立流域下垫面空间数据库,以氮磷为研究对象,应用SWAT模型对流域三大主要水系及涉及35个子流域进行2000-2009年径流、营养盐输出模拟研究,并对实测数据和模拟结果进行分析,结果表明:径流模拟结果校验阶段的效率系数0.65和0.86,确定系数是0.78和0.91,模拟效果较好,径流和营养盐负荷受降雨影响呈正相关关系,在丰水年和丰水季节较大,2000-2009年期间TN和TP年均负荷分别是2640.64和300.01 t,在2007年达到最大值,分别是3475.96和399.20 t,在2005年为最小值,分别是2036.72和226.44 t,TN和TP负荷的贡献率高岚水系＞古夫水系＞南阳水系,支流TN和TP输出强度空间差异较大,空间分布差异系数分别是0.34和0.58,TN最大值和最小值是29.39 kg·hm-2·a-1和3.86 kg·hm-2·a-1,TP最大值和最小值分别是4.90 kg·hm-2·a-1和0.54 kg·hm-2·a-1.     

COMPARISON OF PROCESS‐BASED AND ARTIFICIAL NEURAL NETWORK APPROACHES FOR STREAMFLOW MODELING IN AN AGRICULTURAL WATERSHED1

ABSTRACT: The performance of the Soil and Water Assessment Tool (SWAT) and artificial neural network (ANN) models in simulating hydrologic response was assessed in an agricultural watershed in southeastern Pennsylvania. All of the performance evaluation measures including Nash‐Sutcliffe coefficient of efficiency (E) and coefficient of determination (R²) suggest that the ANN monthly predictions were closer to the observed flows than the monthly predictions from the SWAT model. More specifically, monthly streamflow E and R² were 0.54 and 0.57, respectively, for the SWAT model calibration period, and 0.71 and 0.75, respectively, for the ANN model training period. For the validation period, these values were ?0.17 and 0.34 for the SWAT and 0.43 and 0.45 for the ANN model. SWAT model performance was affected by snowmelt events during winter months and by the model's inability to adequately simulate base flows. Even though this and other studies using ANN models suggest that these models provide a viable alternative approach for hydrologic and water quality modeling, ANN models in their current form are not spatially distributed watershed modeling systems. However, considering the promising performance of the simple ANN model, this study suggests that the ANN approach warrants further development to explicitly address the spatial distribution of hydrologic/water quality processes within watersheds.     

EFFECTS OF STATSGO AND SSURGO AS INPUTS ON SWAT MODEL'S SNOWMELT SIMULATION1

ABSTRACT: Soil data comprise a basic input of SWAT (Soil and Water Assessment Tool) for a watershed application. For watersheds where site specific soil data are unavailable, the two U.S. Department of Agriculture (USDA) soil databases, the State Soil Geographic (STATSGO) and Soil Survey Geographic (SSURGO) databases, may be the best alternatives. Although it has been noted that SWAT models using the STATSGO and SSURGO data may give different simulation results for water, sediment, and agricultural chemical yields, information is scarce on the effects of using these two databases in predicting streamflows that are predominantly generated from melting snow in spring. The objective of this study was to assess the effects of using STATSGO versus SSURGO as an input for the SWAT model's simulation of the streamflows in the upper 45 percent of the Elm River watershed in eastern North Dakota. Designating the model as SWAT‐STATSGO when the STATSGO data were used and SWAT‐SSURGO when the SSURGO data were used, SWAT‐STATSGO and SWAT‐SSURGO were separately calibrated and validated using the observed daily streamflows. The results indicated that SWAT‐SSURGO provided an overall better prediction of the discharges than SWAT‐STATSGO, although both did a good and comparable job of predicting the high streamflows. However, SWAT‐STATSGO predicted the low streamflows more accurately and had a slightly better performance during the validation period. In addition, the discrepancies between the discharges predicted by these two SWAT models tended to be larger at upstream locations than at those farther downstream within the study area.     

WATER QUALITY MODELING OF ALTERNATIVE AGRICULTURAL SCENARIOS IN THE U.S. CORN BELT1

ABSTRACT: Simulated water quality resulting from three alternative future land‐use scenarios for two agricultural watersheds in central Iowa was compared to water quality under current and historic land use/land cover to explore both the potential water quality impact of perpetuating current trends and potential benefits of major changes in agricultural practices in the U.S. Corn Belt. The Soil Water Assessment Tool (SWAT) was applied to evaluate the effect of management practices on surface water discharge and annual loads of sediment and nitrate in these watersheds. The agricultural practices comprising Scenario 1, which assumes perpetuation of current trends (conversion to conservation tillage, increase in farm size and land in production, use of currently‐employed Best Management Practices (BMPs)) result in simulated increased export of nitrate and decreased export of sediment relative to the present. However, simulations indicate that the substantial changes in agricultural practices envisioned in Scenarios 2 and 3 (conversion to conservation tillage, strip intercropping, rotational grazing, conservation set‐asides and greatly extended use of best management practices (BMPs) such as riparian buffers, engineered wetlands, grassed waterways, filter strips and field borders) could potentially reduce current loadings of sediment by 37 to 67 percent and nutrients by 54 to 75 percent. Results from the study indicate that major improvements in water quality in these agricultural watersheds could be achieved if such environmentally‐targeted agricultural practices were employed. Traditional approaches to water quality improvement through application of traditional BMPs will result in little or no change in nutrient export and minor decreases in sediment export from Corn Belt watersheds.     

Water Supply Planning Considering Uncertainties in Future Water Demand and Climate: A Case Study in an Illinois Watershed

Ensuring an adequate, reliable, clean, and affordable water supply for citizens and industries requires informed, long-range water supply planning, which is critically important for water security. A balance between water supply and demand must be considered for a long-term plan. However, water demand projections are often highly uncertain. Climate change could impact the hydrologic processes, and consequently, threaten water supply. Thus, understanding the uncertainties in future water demand and climate is critical for developing a sound water supply plan. In Illinois, regional water supply planning attempts to explore the impacts of future water demand and climate on water supply using scenario analyses and hydrologic modeling. This study is aimed at developing a water supply planning framework that considers both future water demand and climate change impacts. This framework is based on the Soil and Water Assessment Tool to simulate the watershed hydrology and conduct scenario analyses that consider the uncertainties in both future water demand and climate as well as their impacts on water supply. The framework was applied to water supply planning efforts in the Kankakee River watershed. The Kankakee River watershed model was calibrated and validated to observed streamflow records at four long-term United States Geological Survey streamflow gages. Because of the many model parameters involved, the calibration process was automated and was followed by a manual refinement, resulting in good model performance. Long-range water demand projections were prepared by the Illinois State Water Survey. Six future water demand scenarios were established based on a suite of assumptions. Climate scenarios were obtained from the Coupled Model Intercomparison Projection Phase 5 datasets. Three representative concentration pathways (RCPs), RCP2.6, RCP4.5, and RCP8.5, are used in the study. The scenario simulation results demonstrated that climate change appears to have a greater impact on water availability in the study area than water demand. The framework developed in this study can also be used to explore the impacts of uncertainties of water demand and climate on water supply and can be extended to other regions and watersheds.     

SWAT模型在茫溪河流域非点源污染研究中的应用

本研究采用美国农业部农业研究所开发的SWAT模型(Soil and Water Assessment Tool)对茫溪河流域非点源污染进行了模拟研究,构建了适用于茫溪河流域的非点源污染模型,对流域的非点源污染进行了模拟和分析。模拟结果显示:茫溪河流域污染特征以非点源污染为主;东茫溪河水系的泥沙、氮、磷等负荷均大于西茫溪河水系;单位泥沙负荷最大的区域为流域东北部、东部和东南部一带的深丘地区,是茫溪河流域的主要泥沙输出区;氮、磷负荷最大的区域为茫溪河中下游一带的平坝、浅丘地区,是茫溪河流域的主要氮、磷输出区;研究区内泥沙、营养物质的输出具有很强的时间规律,有机氮、有机磷的输出在雨季(6月~9月)会出现高峰,因此雨季是流域内非点源污染源输出的重点时段。