Comparison and Evaluation of Gridded Precipitation Datasets in a Kansas Agricultural Watershed Using SWAT

Gridded precipitation datasets are becoming a convenient substitute for gauge measurements in hydrological modeling; however, these data have not been fully evaluated across a range of conditions. We compared four gridded datasets (Daily Surface Weather and Climatological Summaries [DAYMET], North American Land Data Assimilation System [NLDAS], Global Land Data Assimilation System [GLDAS], and Parameter‐elevation Regressions on Independent Slopes Model [PRISM]) as precipitation data sources and evaluated how they affected hydrologic model performance when compared with a gauged dataset, Global Historical Climatology Network‐Daily (GHCN‐D). Analyses were performed for the Delaware Watershed at Perry Lake in eastern Kansas. Precipitation indices for DAYMET and PRISM precipitation closely matched GHCN‐D, whereas NLDAS and GLDAS showed weaker correlations. We also used these precipitation data as input to the Soil and Water Assessment Tool (SWAT) model that confirmed similar trends in streamflow simulation. For stations with complete data, GHCN‐D based SWAT‐simulated streamflow variability better than gridded precipitation data. During low flow periods we found PRISM performed better, whereas both DAYMET and NLDAS performed better in high flow years. Our results demonstrate that combining gridded precipitation sources with gauge‐based measurements can improve hydrologic model performance, especially for extreme events.     

基于GLUE法的多指标水质模型参数率定方法

目前对水质模型进行参数率定通常利用计算机算法来实现,但由于水质模型日趋复杂的非线性结构往往会导致"异参同效"现象,无法通过单个似然度判断参数的取值是否能够取得真值.为避免这一情况,本文提出了一套基于GLUE法的多目标模型参数率定方法,并以WASP水质模型的应用为例,通过Sobol方法确定模型的敏感参数,并利用DO、CBOD、氨氮、硝态氮4项指标的似然函数对参数同时进行率定.结果表明,该方法既可以有效地避免因追求"过拟合"而造成模型参数取值不当,也可以减小模型参数的不确定性,为具有"异参同效"现象的复杂模型的参数率定工作提供了一个更为可靠的方法.     

气相分子吸收光谱法测定氨氮校准曲线斜率、截距参考值研究

主要阐述了气相分子吸收光谱法测定氨氮的校准曲线斜率、截距参考值的分析.文章收集了临安市环境监测站实验室自2012年以来气相分子吸收光谱法氨氮校准曲线制作的一系列原始数据,并通过数理统计方法对校准曲线、残余标准偏差、斜率扩展不确定度、截距扩展不确定度开展了详细讨论,得出气相分子吸收光谱法氨氮校准曲线截距a值、斜率b值实验室参考值.此结果对实验室分析人员判定氨氮项目校准曲线制作是否合格具有一定的参考价值.     

Calibrating a Basin‐Scale Groundwater Model to Remotely Sensed Estimates of Groundwater Evapotranspiration

Remotely sensed vegetation indices correspond to canopy vigor and cover and have been successfully used to estimate groundwater evapotranspiration (ET_g) over large spatial and temporal scales. However, these data do not provide information on depth to groundwater (dtgw) necessary for groundwater models (GWM) to calculate ET_g. An iterative approach is provided that calibrates GWM to ET_g derived from Landsat estimates of the Enhanced Vegetation Index (EVI). The approach is applied to different vegetation groups in Mason Valley, Nevada over an 11‐year time span. An uncertainty analysis is done to estimate the resulting mean and 90% confidence intervals in ET_g to dtgw relationships to quantify errors associated with plant physiologic complexity, species variability, and parameter smoothing to the 100 m GWM‐grid, temporal variability in soil moisture and nonuniqueness in the solution. Additionally, a first‐order second moment analysis shows ET_g to dtgw relationships are almost exclusively sensitive to estimated land surface, or maximum, ET_g despite relatively large uncertainty in extinction depths and hydraulic conductivity. The EVI method of estimating ET_g appears to bias ET_g during years with exceptionally wet spring/summer conditions. Excluding these years improves model performance significantly but highlights the need to develop a methodology that accounts not only on quantity but timing of annual precipitation on phreatophyte greenness.     

Calibration and Verification of SWMM for Low Impact Development

The Storm Water Management Model was used to simulate runoff and nutrient export from a low impact development (LID) watershed and a watershed using traditional runoff controls. Predictions were compared to observed values. Uncalibrated simulations underpredicted weekly runoff volume and average peak flow rates from the multiple subcatchment LID watershed by over 80%; the single subcatchment traditional watershed had better predictions. Saturated hydraulic conductivity, Manning's n for swales, and initial soil moisture deficit were sensitive parameters. After calibration, prediction of total weekly runoff volume for the LID and traditional watersheds improved to within 12 and 5% of observed values, respectively. For the validation period, predicted total weekly runoff volumes for the LID and traditional watersheds were within 6 and 2% of observed values, respectively. Water quality simulation was less successful, Nash–Sutcliffe coefficients >0.5 for both calibration and validation periods were only achieved for prediction of total nitrogen export from the LID watershed. Simulation of a 100‐year, 24‐h storm resulted in a runoff coefficient of 0.46 for the LID watershed and 0.59 for the traditional watershed. Results suggest either calibration is needed to improve predictions for LID watersheds or expanded look‐up tables for Green–Ampt infiltration parameter values that account for compaction of urban soil and antecedent conditions are needed.     

Augmenting Watershed Model Calibration with Incorporation of Ancillary Data Sources and Qualitative Soft Data Sources

Watershed simulation models such as the Soil & Water Assessment Tool (SWAT) can be calibrated using “hard data” such as temporal streamflow observations; however, users may find upon examination of model outputs, that the calibrated models may not reflect actual watershed behavior. Thus, it is often advantageous to use “soft data” (i.e., qualitative knowledge such as expected denitrification rates that observed time series do not typically exist) to ensure that the calibrated model is representative of the real world. The primary objective of this study is to evaluate the efficacy of coupling SWAT‐Check (a post‐evaluation framework for SWAT outputs) and IPEAT‐SD (Integrated Parameter Estimation and Uncertainty Analysis Tool‐Soft & hard Data evaluation) to constrain the bounds of soft data during SWAT auto‐calibration. IPEAT‐SD integrates 59 soft data variables to ensure SWAT does not violate physical processes known to occur in watersheds. IPEAT‐SD was evaluated for two case studies where soft data such as denitrification rate, nitrate attributed from subsurface flow to total discharge ratio, and total sediment loading were used to conduct model calibration. Results indicated that SWAT model outputs may not satisfy reasonable soft data responses without providing pre‐defined bounds. IPEAT‐SD provides an efficient and rigorous framework for users to conduct future studies while considering both soft data and traditional hard information measures in watershed modeling.     

How to Constrain Multi‐Objective Calibrations of the SWAT Model Using Water Balance Components

Accurate discharge simulation is one of the most common objectives of hydrological modeling studies. However, a good simulation of discharge is not necessarily the result of a realistic simulation of hydrological processes within the catchment. We propose an evaluation framework that considers both discharge and water balance components as evaluation criteria for calibration of the Soil and Water Assessment Tool (SWAT). In this study, we integrated average annual values of surface runoff, groundwater flow, and evapotranspiration in the model evaluation procedure to constrain the selection of good model runs for the Little River Experimental Watershed in Georgia, United States. For evaluating water balance and discharge dynamics, the Nash‐Sutcliffe efficiency (NSE) and percent bias (PBIAS) were used. In addition, the ratio of root mean square error and standard deviation of measured data (RSR) was calculated for individual segments of the flow duration curve to identify the best model runs in terms of discharge magnitude. Our results indicate that good statistics for discharge do not guarantee realistic simulations of individual water balance components. Therefore, we recommend constraining the ranges of water balance components to achieve a more realistic simulation of the entire hydrological system, even if tradeoffs between good statistics for discharge simulations and reasonable amounts of the water balance components are unavoidable. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

不同来源废水COD、TOC与Cl-的关系

通过对含盐化工废水(A)、受潮汐影响的河流水(B)、城市生活污水处理厂排水(C)、采油废水(D)4种不同来源废水进行为期15 d的采样监测,测定了其COD、TOC和Cl-浓度,分析比较了3种废水指标之间的关系,其中COD分别使用重铬酸钾法、氯气校正法和碘化钾碱性高锰酸钾法3种方法进行测定.实验结果表明,4种废水Cl-浓...     

经口摄入土壤多溴联苯醚生物可给性变化及影响因素的体外消化模拟

误食土壤是污染物(如多溴联苯醚)人体(主要是儿童)暴露的重要途径,人体消化道内污染物吸收的生物可给性是针对此种暴露方式进行定量风险评估的有效途径之一.本研究采用体外消化实验模拟3种不同有机碳含量的天然土壤中典型多溴联苯醚(BDE-28、BDE-47、BDE-99和BDE-153)在胃和小肠消化液中的释放,验证部分消化释放的多溴联苯醚因消化残留固相表面的再吸附造成低估实际生物可给性,并通过不同水土比的拟合计算予以校正.结果表明,校正后的消化率普遍高于校正前;就不同土样而言,BDE-28、BDE-47、BDE-99和BDE-153在不同初始暴露浓度条件下平均提升比例范围分别为14.3%~42.3%、11.1%~32.1%、4.9%~12.3%和0.0%~7.7%.因此,未经校正的消化率会显著低估PBDEs消化道内的生物可给性,尤其是低溴代组分及PBDEs初始浓度较高或高TOC含量的土样.校正后BDE-28、BDE-47、BDE-99和BDE-153的消化率分别维持在21.9%~54.7%、18.8%~43.1%、13.4%~27.2%和9.3%~19.9%.此外,PBDEs的消化率与其辛醇-水分配系数的对数lg KOW呈显著负相关;而与土壤TOC含量及PBDEs初始暴露浓度的相关性并不显著,尤其是高溴代组分.     

Local calibration of coliforms parameters of water quality problem at Igapó I Lake, Londrina, Paraná, Brazil

This article presents results concerning the local calibration of the transport parameters (longitudinal and transversal diffusions and decay coefficient) for a two-dimensional problem of water quality at Igapó I Lake, located in Londrina, Paraná, Brazil, using fecal coliforms as an indicator of water quality. The simulation of fecal coliforms concentrations all over the water body is conducted by means of a structured discretization of the geometry of Igapó I Lake, together with the finite difference and finite element methods. By using the velocity field, modeled by the Navier-Stokes and Poisson equations, the flow of fecal coliforms is described by means of a transport model, which considers advective and diffusive processes, as well as a process of fecal coliforms decay. In the checkpoint, the longitudinal and transversal diffusion coefficients and the coliforms decay coefficient that best fitted the value of the fecal coliforms concentration were D_x = D_y = 0.001 m²/h and k = 0.5 d⁻¹ = 0.02083 h⁻¹. A qualitative and quantitative analysis of the numerical simulations conducted in function of the diffusion coefficients and of the coliforms decay parameter provided a better understanding of the local water quality at Igapó I Lake.