Toward improved calibration of watershed models: Multisite multiobjective measures of information

This paper presents a computational framework for incorporation of disparate information from observed hydrologic responses at multiple locations into the calibration of watershed models. The framework consists of three components: 1) an a-priori characterization of system behavior; 2) a formal and statistically valid formulation of objective function(s) of model errors; and 3) an optimization engine to determine the Pareto-optimal front for the selected objectives. The proposed framework was applied for calibration of the Soil and Water Assessment Tool (SWAT) in the Eagle Creek Watershed, Indiana, USA using three single objective optimization methods [Shuffled Complex Evolution (SCE), Dynamically Dimensioned Search (DDS), and DiffeRential Evolution Adaptive Metropolis (DREAM)], and one multiobjective optimization method. Solutions were classified into behavioral and non-behavioral using percent bias and Nash–Sutcliffe model efficiency coefficient. The results showed that aggregation of streamflow and NO_x (NO₃-N + NO₂-N) information measured at multiple locations within the watershed into a single measure of weighted errors resulted in faster convergence to a solution with a lower overall objective function value than using multiple measures of information. However, the DREAM method solution was the only one among the three single objective optimization methods considered in this study that satisfied the conditions defined for characterizing system behavior. In particular, aggregation of streamflow and NO_x responses undermined finding “very good” behavioral solutions for NO_x, primarily because of the significantly larger number of observations for streamflow. Aggregation of only NO_x responses into a single measure expedited finding better solutions although aggregation of data from nested sites appeared to be inappropriate because of correlated errors. This study demonstrates the importance of hydrologic and water quality data availability at multiple locations, and also highlights the use of multiobjective approaches for proper calibration of watershed models that are used for pollutant source identification and watershed management.     

基于SWAT模型的小清河流域总氮输出模拟研究

小清河流域工业和农业发达,点源和非点源污染均比较严重,致使河流总氮含量严重超标,对下游河口及莱州湾的水生态与环境产生了深刻影响。本文基于实测径流和总氮资料,对小清河流域SWAT模型进行了校准和验证,在此基础上,模拟和分析了流域2008-2013年总氮负荷的时空特征,并对其污染来源进行了甄别。研究结果表明:小清河流域总氮的年输出量与年径流量趋势总体一致,表现出明显的年际特征,总氮负荷多年均值为38.0×103t。空间上,各子流域的总氮输出量均较高,其中,位于农业发达的寿光市和章丘市、工企业较多的邹平县、人口密度大的济南市区等区域的子流域总氮输出量最高。流域总氮负荷主要来自非点源污染源,其中,农业施肥引起的氮素流失和畜禽养殖的污水排放对流域总氮输出的贡献分别为32.5%和29.5%,另外,工业和城镇污水的氮排放量也较高,分别占流域总氮输出量的19.4%和16.5%。为此,须结合点源和非点源污染源对小清河流域氮污染物进行总量控制和削减。     

土地利用变化对牤牛河流域径流的影响

土地利用变化对流域水资源配置及其循环过程有显著的影响,了解土地利用与径流的关系是流域水文学研究的重要内容。以牤牛河流域为研究区,基于SWAT分布式水文模型,利用流域DEM、土地利用、土壤、气象等数据,结合GIS和RS技术,并采用极端土地利用分析方法,对流域土地利用变化的径流响应进行定量研究与分析。结果表明:流域内1998年与2009年土地均以耕地、林地、未使用地为主,约占总面积的90%;相同的气象条件下,两期土地利用情景下年、月均径流量变化趋势一致,2009年土地利用情景下的年、月径流量较1998年略小,年均径流量减少605.5万m3;7,8月份月径流模拟减少量明显;土地植被覆盖度增大径流量减小,反之则增大;在极端土地利用情景下,径流量将发生剧烈变化。因此,在不考虑研究期间内气候变化等因素的条件下,土地利用变化是影响流域径流变化的主要因素。     

SWAT模型在天山西部山区的应用

以伊犁喀什河流域为研究对象,采用分布式流域水文物理模型SWAT对喀什河流域进行径流模拟,并建立模型所需的土壤、土地利用、气象数据库。应用1990-1996年的月径流资料进行模型参数的率定;1997-2000年月径流资料进行模型的验证,评估了模型在天山西部山区的适用性。模型经过多次的参数率定后,能较好地模拟新疆山区水文过程。结果表明:率定期的径流相对误差RE为8.6%,Nash-Sutcliffe效率系数为0.8,模拟值与实测值之间的拟合程度较好。融雪是新疆径流形成的重要环节,模型中的融雪参数对模拟径流结果的影响较大,适当的调整融雪参数值,可提高模拟精度。     

基于SWAT模型的水资源与水环境综合管理规划研究——以临漳县为例

分析SWAT模型在临漳县的水资源与水环境综合管理规划中的运用.通过对模型参数的率定,结合临漳县实际的种植情况和遥感监测的ET,进行了临漳县水量组合方案的制定与情景模拟,并由此提出临漳水资源与水环境综合管理的优选方案.     

西南岩溶灌区水文特性及其模拟模型的构建

从岩溶水文和灌区水文两方面分析了西南岩溶灌区水文的特殊性和脆弱性。针对西南岩溶灌区水文特点,在对自然流域水文模型SWAT改进的基础上,构建岩溶灌区分布式水文模型。建立的岩溶灌区分布式水文模型主要添加了表层岩溶带水循环模块、岩溶地下河汇流过程,改进浅层岩溶水计算方法、稻田水分循环模块、渠系渗漏计算模块,增加塘堰的灌溉功能等,并介绍了模型的流域离散方法和水循环结构。岩溶灌区分布式水文模型的构建可为西南岩溶灌区水文特性及其对变化环境的响应等研究提供有效的工具和手段。     

环境变化对汉江上游径流影响的定量分析

气候和土地利用等环境变化的水文响应研究对流域水资源利用具有重要价值。以汉江石泉水文站上游为研究区,采用7种基于Budyko理论的弹性系数法和SWAT模型定量分析了气候变化和人类活动对径流变化的贡献率,设置多种气候变化和土地利用变化情景,分析其对径流的影响。结果表明,石泉水文站年径流呈减少趋势,气候变化对径流减少的贡献率为65.3% ~ 68.1%,人类活动的贡献率为31.9% ~ 34.7%,气候变化是近56年径流减少的主要原因。气候变化情景的模拟显示径流变化主要由降水变化主导。土地利用自然增长情景和极端草地情景使石泉水文站年径流量增加,而退耕还林、极端耕地和极端林地情景使年径流量减少。     

Comparison of variance-based and moment-independent global sensitivity analysis approaches by application to the SWAT model

Global Sensitivity Analysis (GSA) is an essential technique to support the calibration of environmental models by identifying the influential parameters (screening) and ranking them.In this paper, the widely-used variance-based method (Sobol') and the recently proposed moment-independent PAWN method for GSA are applied to the Soil and Water Assessment Tool (SWAT), and compared in terms of ranking and screening results of 26 SWAT parameters. In order to set a threshold for parameter screening, we propose the use of a “dummy parameter”, which has no influence on the model output. The sensitivity index of the dummy parameter is calculated from sampled data, without changing the model equations. We find that Sobol' and PAWN identify the same 12 influential parameters but rank them differently, and discuss how this result may be related to the limitations of the Sobol' method when the output distribution is asymmetric.     

Modelling the impacts of grassland to cropland conversion on river flow regimes in Skunk Creek watershed,Upper Midwest United States

Conversion of grassland to cultivated cropland has been linked to downstream alteration of flow regimes. This study used the Soil and Water Assessment Tool (SWAT) to construct seven “what if” scenarios for quantifying the impacts of grassland to cropland and vice versa conversion (i.e., replacement of grassland with selected agricultural crops) on river flow regimes in Skunk Creek watershed. The Cropland Data Layer for the year 2011 in conjunction with historical climate data was used to create SWAT models for scenario simulations over 19 years, from 1996 to 2014. The model developed for the historical climate records (baseline) was compared with the scenarios examined using stream flow metrics for a range of flow regimes, including magnitude, duration, frequency, and timing of annual low‐ and high‐flow conditions. The simulation results suggest that grassland conversion to cultivated cropland would generally increase river flows compared with conversion of cultivated cropland to grassland, which may reduce flows in the watershed. Low and moderate flows increased by 2–8% from the baseline scenario with conversion of grass crop and by 1–20% decreases with crop–grass conversion. High flows increased by 3–7% and decreased by 1–18% when grass is converted to crop and crop to grass, respectively. The analysis also suggests that grassland establishment may attenuate the peaks of prolonged small floods and shorter but earlier large floods.     

Spatio-temporal effect of climate and land-use change on water balance of the Ganga river basin

The assessment of climate and land-use transformations upon the hydrologic response is crucial for decision-makers to accomplish various adaptation strategies. The Regional Climate Models (RCMs) have been extensively employed to study the impact of climate change on various hydrologic components. However, these climate models are subjected to a large number of uncertainties, which demands a careful selection of an appropriate climate model. To rationalize such uncertainties and select suitable models, a multi-criteria ranking technique has been employed. Ranking of RCMs has been done on its capability to simulate hydrologic components, i.e., simulations of the surface runoff by employing Soil Water Assessment Tool (SWAT), exercising Entropy, and PROMETHEE-2 approach. The spatial extent of changes in the hydrologic components is examined over the Ganga river basin, using the top three ranked RCMs, for a period from January 2021-December 2100. For the monsoon months (June-September), the future annual mean surface runoff will decrease substantially (−50% to −10%), while the flows for post-monsoon months (October-December) are projected to increase (10–20%). Extremes are noted to increase during the non-monsoon months, while a substantial decrease in medium events is also highlighted. Snow-melt is projected to increase during the months of November-March (50% to 400%). Major loss of recharge is expected to occur in the central part of the basin. The investigation presents not only a reliable impact assessment but also the valuation of future alterations in individual hydrological components and will furnish the administrators with substantive information, a prerequisite to formulating ameliorative policies.