基于SWAT分布式流域水文模型的下垫面变化和水利工程对径流影响分析

近年来随着人类活动的加剧,兴建了许多中、小型水利和水土保持工程,迅速改变着流域的自然面貌,因而改变了径流的原有规律。选取1960以前水利工程较少的时期作为人类活动不明显期来率定SWAT模型参数,对于1990以后人类活动稳定期的径流分别设置3个情景:应用原SWAT模型、应用只考虑下垫面变化的SWAT模型和应用考虑下垫面变化和水利工程影响的SWAT模型分别进行模拟。对于五道沟以上流域和流域内东丰、磐石、样子哨3个子流域模拟结果显示:考虑下垫面变化和水利工程影响后的径流模拟相关系数R2和纳什效率系数NSE分别从0.82、0.56提高到0.91、0.79,分别提高了11.0%和41.1%。其中模拟精度的提高量中91.3%是由于考虑水利工程作用所引起的,剩余部分是由考虑下垫面变化引起的。相比下垫面变化,水利工程运行对该流域径流变化占据主导作用。     

基于高性能计算的SWAT参数敏感度分析并行框架

随着大规模水文模拟需求的不断提高,如何解决计算需求问题逐渐成为水文研究的一个热点.SWAT(soil and water assessment tool)模型在进行大规模水文模拟时有着良好的适应性与准确度,但其敏感度分析模块由于计算量过高,计算时长往往长达数月之久.为了加快SWAT敏感度分析的运行速度,针对SWAT敏感度分析模块的特点,基于MPI提出了一种高效的主—从式并行计算框架,并在此框架的基础上,通过将正演过程并行化,在敏感度分析的主—从并行框架中引入通信子空间的操作,将并行化的正演与主—从式的外层并行框架相结合,得到一种混合式的敏感度分析并行框架,大大提高了对参数集合的敏感度分析速度,将SWAT敏感度分析模块使用的处理器数量从原始的单核串行一跃提升到百核的数量级.最后通过天山北坡流域的模拟验证了此并行框架的可行性.     

Design and implementation of a general software library for using NSGA-II with SWAT for multi-objective model calibration

Calibrating watershed-scale hydrologic models remains a critical but challenging step in the modeling process. The Soil and Water Assessment Tool (SWAT) is one example of a widely used watershed-scale hydrologic model that requires calibration. The calibration algorithms currently available to SWAT modelers through freely available and open source software, however, are limited and do not include many multi-objective genetic algorithms (MOGAs). The Non-Dominated Sorting Genetic Algorithm II (NSGA-II) has been shown to be an effective and efficient MOGA calibration algorithm for a wide variety of applications including for SWAT model calibration. Therefore, the objective of this study was to create an open source software library for multi-objective calibration of SWAT models using NSGA-II. The design and implementation of the library are presented, followed by a demonstration of the library through a test case for the Upper Neuse Watershed in North Carolina, USA using six objective functions in the model calibration.     

Multi-objective model auto-calibration and reduced parameterization: Exploiting gradient-based optimization tool for a hydrologic model

Multi-objective model optimization methods have been extensively studied based on evolutionary algorithms, but less on gradient-based algorithms. This study demonstrates a framework for multi-objective model calibration/optimization using gradient-based optimization tools. Model-independent software Parameter ESTimation (PEST) was used to auto-calibrate ISWAT, a modified version of the distributed hydrologic model Soil and Water Assessment Tool (SWAT2005), in the Shenandoah River watershed. The time-series processor TSPROC was used to combine multiple objectives into the auto-calibration process. Two sets of roughness coefficients for main channels, one assigned and calibrated according on soil types and one determined via empirical equations, were examined for stream discharge simulation. Five different weighting alternatives were investigated for their effects on ISWAT calibrations. Results showed that using Manning's roughness coefficients obtained from empirical equations improves simulation results and calibration efficiency. Applying a two-step weighting alternative to different observation groups would provide the best calibration results.     

Application of the Soil and Water Assessment Tool for six watersheds of Lake Erie: Model parameterization and calibration

The Soil and Water Assessment Tool (SWAT), a physically-based watershed-scale model, holds promise as a means to predict tributary sediment and nutrient loads to the Laurentian Great Lakes. In the present study, model performance is compared across six watersheds draining into Lake Erie to determine the applicability of SWAT to watersheds of differing characteristics. After initial model parameterization, the Huron, Raisin, Maumee, Sandusky, Cuyahoga, and Grand SWAT models were calibrated (1998-2001) and confirmed, or validated (2002-2005), individually for stream water discharge, sediment loads, and nutrient loads (total P, soluble reactive P, total N, and nitrate) based on available datasets. SWAT effectively predicted hydrology and sediments across a range of watershed characteristics. SWAT estimation of nutrient loads was weaker although still satisfactory at least two-thirds of the time across all nutrient parameters and watersheds. SWAT model performance was most satisfactory in agricultural and forested watersheds, and was less so in urbanized settings. Model performance was influenced by the availability of observational data with high sampling frequency and long duration for calibration and confirmation evaluation. In some instances, it appeared that parameter adjustments that improved calibration of hydrology negatively affected subsequent sediment and nutrient calibration, suggesting trade-offs in calibrating for hydrologic vs. water quality model performance. Despite these considerations, SWAT accurately predicted average stream discharge, sediment loads, and nutrient loads for the Raisin, Maumee, Sandusky, and Grand watersheds such that future use of these SWAT models for various scenario testing is reasonable and warranted.     

基于SWAT 模型的区域蒸散发模拟及遥感验证

应用分布式水文模型进行灌区用水效率多尺度评价,可为灌区节水改造提供技术支持,本文运用SCE-UA算法在大兴试验站对分布式水文模型（SWAT）中的夏玉米-冬小麦轮作作物参数进行率定,对SWAT模型中蒸散发相关参数进行了敏感性分析,综合考虑农业灌溉措施和施肥措施,将模型模拟ET与遥感监测值进行对比验证.结果表明,SWAT模型模拟ET与遥感监测ET的确定性系数和Nash效率系数分别达到了0.91和0.90,模拟精度较高;不同的土地利用形式下,蒸散发变化显著,平均误差为6.9％.利用遥感监测ET数据有助于蒸散发的正确模拟,从而有效地提高水文过程的模拟精度.     

A SWAT evaluation of the effect of climate change on the hydrology of the Volta River basin

The SWAT (Soil and Water Assessment Tool) was used to evaluate the impacts of a climate scenario based on IPCC A1B emissions on flows in the Volta River basin in West Africa for 2021–2050 and 2071–2100, using 1983–2012 as the reference period. Overall, the simulation indicates increased variability and a decrease of up to 40% in river flow as a consequence of decreasing rainfall and increasing temperature. In particular, the analysis shows smaller absolute but greater relative changes in the hydrology of the northern (upper) part of the basin, particularly at the end of the century.     

灌区地表水—地下水耦合模型的构建

为了定量描述灌区水平衡要素及其转化关系,构建了灌区地表水-地下水分布式模拟耦合模型。通过改进SWAT模型的稻田及旱作物水分循环、蒸发蒸腾量和渠系渗漏计算等模块,建立了灌区地表水分布式模拟模型;以SWAT模型中的水文响应单元(HRU)和MODFLOW模型中的有限差分网格(cells)作为基本交换单元,将改进SWAT模型的地下水补给量计算值加载到MODFLOW模型的地下水补给模块,实现了灌区地表水-地下水分布式模拟模型的耦合。耦合模型在柳园口灌区的应用结果表明,该模型能够准确模拟和预测灌区地表水和地下水的动态变化,为灌区水管理提供了科学依据。     

基于GIS的潘家口水库面源污染负荷计算

潘家口水库是海河流域的重要水源地，在水资源匮乏的北方地区，水源地的保护有非常重要的意义。本文内容是海河流域重要水源地富营养化防治研究的一部分，利用SWAT模型研究了潘家口水库上游地区面源污染负荷和产出特征。SWAT模型是一个物理分布式的流域面源污染计算模型，AvSwat是ArcView软件的一个扩展模块，可以处理SWAT模型需要的GIS数据。文中利用实测数据对模型进行了参数率定，对不同水平年进行了面源污染负荷计算，并分析了施肥对于面源污染负荷的影响。     

赣江流域气候和土地利用变化对蓝绿水的影响

采用标准化降水指数(SPI)确定赣江流域的典型年,基于SWAT模型,对典型年份赣江流域蓝绿水的时空分布进行了分析;设置多种气候与土地利用情景,定量分析了气候和土地利用变化对流域内蓝绿水的影响。结果表明:1972年、1998年和2014年分别为赣江流域的干旱年、湿润年和正常年;湿润年的蓝水量最为丰富,是干旱年的2.01倍,绿水量的变化相对稳定,干旱年绿水系数最高,是湿润年的1.44倍;土地利用变化对蓝绿水的时空分布影响较小;气候变化情景下蓝水量、绿水量分别增加了75.52mm和30.65mm,绿水系数减小了2.33%,共同变化情景下蓝绿水变化趋势与气候变化情景大致相同,表明气候变化对流域蓝绿水的影响较大。