基于二元水循环的水量-水质-水效联合调控模型开发与应用

为将我国最严格水资源管理制度的实践与二元水循环理论相结合，提高“三条红线”控制指标的科学性与合理性，本文以SWAT模型为基础，通过改进子流域划分方法、添加经济社会模块和人工用水模块，对其人工侧支循环模拟进行了系统的完善，开发了基于SWAT的水量-水质-水效联合调控模型SWAT_WAQER。以广西南流江流域为例，从国民经济用水量、河道径流与水质等方面对模型进行校验，并在此基础上划分了2030年“三条红线”控制指标。结果表明：该模型性能良好，能够用于不同节水情景下的国民经济用水量、污染物排放量、水功能区水质达标结果分析，可以作为科学制定“三条红线”控制指标的有力支撑工具。     

Assessment of the different sources of uncertainty in a SWAT model of the River Senne (Belgium)

Although rainfall input uncertainties are widely identified as being a key factor in hydrological models, the rainfall uncertainty is typically not included in the parameter identification and model output uncertainty analysis of complex distributed models such as SWAT and in maritime climate zones. This paper presents a methodology to assess the uncertainty of semi-distributed hydrological models by including, in addition to a list of model parameters, additional unknown factors in the calibration algorithm to account for the rainfall uncertainty (using multiplication factors for each separately identified rainfall event) and for the heteroscedastic nature of the errors of the stream flow. We used the Differential Evolution Adaptive Metropolis algorithm (DREAM_(zs)) to infer the parameter posterior distributions and the output uncertainties of a SWAT model of the River Senne (Belgium). Explicitly considering heteroscedasticity and rainfall uncertainty leads to more realistic parameter values, better representation of water balance components and prediction uncertainty intervals.     

变化环境下由设计暴雨推求设计洪水方法研究

为推求变化环境下的设计洪水,以黄河上游唐乃亥站以上流域1967~2006年的年最大15d降雨量系列为例,基于设计暴雨与SWAT模型相结合的方法,首先构建变参数概率分布函数模型描述变化环境下非一致性暴雨极值系列的分布规律,随后基于等可靠度方法推求给定重现期条件下的设计暴雨值,再结合SWAT水文模型推求设计洪水。结果表明,变化环境下唐乃亥站以上流域各设计频率(P=10%、5%、2%、1%)的设计暴雨值随工程设计寿命(20、30、50、80、100年)的增大而减小,百年一遇设计洪峰从3 292m^3/s降至3 023m^3/s,洪量从29.9×10^8 m^3降至27.4×10^8 m^3。实例应用验证了该方法的可行性,可为变化环境下的设计洪水计算提供参考。     

Uncertainty analysis of parameters in non‐point source pollution simulation: case study of the application of the Soil and Water Assessment Tool model to Yitong River watershed in northeast China

Uncertainty analysis of the model parameters in non‐point source pollution (NPSP) simulation is important because of its great effects on predictions and decision‐making. Understanding the main parameters that effect the uncertainty of NPSP is necessary to provide the basis for formulating control measures. In this study, two methods were applied to conduct parameter uncertainty analysis for Soil and Water Assessment Tool (SWAT). Sobol’ method was used to screen out the model parameters with great effects on the runoff, sediment, total nitrogen (TN) and total phosphorus (TP). The results obtained by sensitivity analysis were used subsequent model calibration and further uncertainty analysis. Monte Carlo (MC) method was employed to analyse the effects of parameter uncertainty on the model outputs. However, such problems are time‐consuming because the MC method required to invoke simulation model thousands of times. To address this challenge, a kriging surrogate model was developed to improve the overall calculation efficiency. The results obtained by sensitivity analysis showed that curve number value (CN2), soil evaporation compensation factor (ESCO), universal soil loss equation support practice factor (USLE_P) and initial organic nitrogen concentration in soil layer (SOL_ORGN) had significant effects on the SWAT outputs. The uncertainty analysis results showed that the uncertainty of runoff is the lowest, followed by TP and TN, and the uncertainty of sediment was the greatest. The kriging surrogate model has the ability to solve this time‐consuming problem rapidly with a high degree of accuracy, and thus it is very robust.     

A comparison of SWAT, HSPF and SHETRAN/GOPC for modelling phosphorus export from three catchments in Ireland

Recent extensive water quality surveys in Ireland revealed that diffuse phosphorus (P) pollution originating from agricultural land and transported by runoff and subsurface flows is the primary cause of the deterioration of surface water quality. P transport from land to water can be described by mathematical models that vary in modelling approach, complexity and scale (plot, field and catchment). Here, three mathematical models (soil water and analysis tools (SWAT), hydrological simulation program-FORTRAN (HSPF) and système hydrologique Européen TRANsport (SHETRAN)/grid oriented phosphorus component (GOPC)) of diffuse P pollution have been tested in three Irish catchments to explore their suitability in Irish conditions for future use in implementing the European Water Framework Directive. After calibrating the models, their daily flows and total phosphorus (TP) exports are compared and assessed. The HSPF model was the best at simulating the mean daily discharge while SWAT gave the best calibration results for daily TP loads. Annual TP exports for the three models and for two empirical models were compared with measured data. No single model is consistently better in estimating the annual TP export for all three catchments.     

Using a parallelized MCMC algorithm in R to identify appropriate likelihood functions for SWAT

Markov Chain Monte Carlo (MCMC) algorithms allow the analysis of parameter uncertainty. This analysis can inform the choice of appropriate likelihood functions, thereby advancing hydrologic modeling with improved parameter and quantity estimates and more reliable assessment of uncertainty. For long-running models, the Differential Evolution Adaptive Metropolis (DREAM) algorithm offers spectacular reductions in time required for MCMC analysis. This is partly due to multiple parameter sets being evaluated simultaneously. The ability to use this feature is hindered in models that have a large number of input files, such as SWAT. A conceptually simple, robust method for applying DREAM to SWAT in R is provided. The general approach is transferrable to any executable that reads input files. We provide this approach to reduce barriers to the use of MCMC algorithms and to promote the development of appropriate likelihood functions.     

基于SWAT模型的东江流域蓝水、绿水时空分布特征研究

基于SWAT(soil and water assessment tool)模型,对东江流域天然状态下的降雨径流过程进行模拟,进而评估流域蓝水、绿水的时空分布特征。结果表明:东江流域蓝水、绿水资源量都非常丰富,多年平均蓝水资源量274.67×108m3,绿水资源量178.72×108m3(主要以绿水流为主),蓝水资源是绿水资源的1.54倍。东江流域以蓝水为主的水资源构成体系主要是由流域湿热多雨的气候条件决定的。从时间变化来看,近年来东江流域蓝水资源、绿水资源、绿水流、绿水储皆无显著增加或降低趋势。从空间分布上来看,蓝水资源格局主要受降雨格局控制,而绿水资源不但受气候条件影响,还受流域下垫面的自然属性以及人类活动干扰,如土地利用方式、土壤类型等,分布格局较为复杂。     

基于分项调查法和SWAT模型的水资源评价方法

现状下垫面条件下长系列天然径流资料是水资源评价的基础,但下垫面变化以及人类活动常常改变了水文循环过程,给水资源评价带来系统性偏差与较大的不确定性。以浠水流域为实例,提出将分项调查法和SWAT模型相结合的水资源评价方法,即根据水文站与水库位置关系建立不同水量平衡方程进行径流还原,利用与现状下垫面条件相近年份的还原后的径流数据进行参数率定与验证,并将构建的模型应用于长系列天然径流过程模拟计算。结果表明：仅采用分项调查法还原后的水文站降水-径流关系的一致性存在明显偏差;而通过构建基于现状下垫面条件下的SWAT模型,各水文站径流模拟值的降水-径流相关性优于还原值,且不同时期降水-径流关系一致性得到显著改善,表明该方法能够有效修正下垫面变化对径流的影响,有助于进一步开展水资源规划、水旱灾害风险评估等工作。     

基于EnKS和SWAT模型的闽江流域径流数据同化

地表水文过程中观测变量对状态变量的响应存在时间滞后性,为提高径流数据同化的精度,以闽江流域为研究区,基于集合卡尔曼平滑器（EnKS）和SWAT模型,构建径流数据同化方案,并与集合卡尔曼滤波（EnKF）方法进行对比,评价不同同化模型的精度,分析数据同化对不同径流分量的影响。结果表明：EnKS最优时间窗口长度在不同水文周期、流域存在差异;考虑水文模型的时间滞后性可以有效提高模型的同化精度,对比EnKF方法,EnKS方法的纳什效率系数(NSE)在七里街、沙县、竹岐3个站点上分别提升了0.03、0.12、0.03,均方根误差(RMSE)分别减小了7.43%、26.81%、4.25%;数据同化方法对不同径流分量的改进程度存在空间异质性和时间异质性,在高渗透率土壤和陡坡区域EnKS方法能使壤中流获得更显著的改进,丰水期EnKS方法对地表径流的改进较枯水期更明显。     

DEM和土地利用分辨率对SWAT水沙模拟效果的影响——以泾河流域为例

DEM和土地利用的数据精度影响水文模型的模拟效果。以泾河流域为对象,选取毛家河、杨家坪和张家山3个水文站作为控制站,分别利用9组不同分辨率的DEM和土地利用数据（分辨率范围均为30～3 000 m）构建了100个SWAT模型,探究输入数据精度对水沙模拟效果的影响,并采用TOPSIS理论方法对模型进行综合评价。研究表明：DEM分辨率会影响流域的边界和河网提取,且流域特征信息会随分辨率的降低而发生丢失;当DEM分辨率低于1 000 m时,需使用SWAT中的Burn in工具,才能完成流域边界与河网的准确提取;HRU的数量随DEM分辨率的下降而减少,而土地利用分辨率对HRU数量的影响不显著;当分辨率变化较大时,DEM对参数敏感性造成的影响要大于土地利用;在构建的毛家河、杨家坪和张家山3个站点的模型中,DEM和土地利用分辨率的最优组合分别为750和300 m、30和90 m以及150和3 000 m。该研究可为流域水沙模型构建与模拟精度提升提供方法与技术参考。