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An integrated modeling process to assess water quality for watersheds.

机译:用于评估流域水质的集成建模过程。

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An integrated modeling process has been developed that combines remote sensing, Geographic Information Systems (GIS), and the Agricultural NonPoint Source Pollution (AGNPS) hydrologic model to assess water quality of a watershed. Remotely sensed Landsat Thematic Mapper (TM) images were used to obtain various land cover information of a watershed including sub-classes of rangeland and wheat land based on the estimates of vegetative cover and crop residue, respectively. AGNPS model input parameters including Universal Soil Loss Equation's (USLE) cropping factors (C-factors) were assigned to the landcover classes. The AGNPS-ARC INFO interface was used to extract input parameters from several GIS layers for the AGNPS model during several selected storm events for the sub-watersheds. Measured surface water quantity and quality data for these storm events were obtained from U.S. Geological Survey (USGS) gaging stations. Base flow separation was done to remove the base flow fraction of water and total suspended sediment (TSS), total nitrogen (total-N), and total phosphorous (total-P) from the total stream flow. Continuous antecedent moisture content ratios were developed for the sub-watersheds during the storm events and were used to adjust the Soil Conservation Service-Curve Numbers (SCS-CN) of various landcovers. A relationship was developed between storm amounts and estimated energy intensity (EI) values using a probability method (Koelliker and Humbert, 1989), and the EI values were used in running the AGNPS model input files. Several model parameters were calibrated against the measured water quality data and then the model was run on different sub-watersheds to evaluate the modeling process. This modeling process was found to be effective for smaller sub-watersheds having adequate rainfall data. However, in the case of large sub-watersheds with substantial variations of rainfall and landcover, this process was less satisfactory. This integrated modeling process will be useful for the resource managers to assess the water quality of sub-watersheds and identify areas within a watershed for which to develop action plans for land use decisions such as adoption of best management practices (BMPs) to improve water quality.*; *This dissertation includes a CD that is compound (contains both a paper copy and a CD as part of the dissertation). The CD requires the following applications: Microsoft Excel; AGNPS ARC INFO (program included); NDVI Estimation (included) for ERDAS IMAGINE software (not included); Winzip; Real Jukebox.
机译:已开发出一种集成的建模过程,该过程结合了遥感,地理信息系统(GIS)和农业面源污染(AGNPS)水文模型来评估流域的水质。遥感Landsat Thematic Mapper(TM)图像用于分别基于植物的植被覆盖度和农作物残渣的估计值来获取流域的各种土地覆盖信息,包括牧场和小麦土地的子类。 AGNPS模型输入参数(包括通用土壤流失方程(USLE)种植因子(C因子))已分配给土地覆被类别。在子流域的几次选定暴风雨事件中,使用AGNPS-ARC INFO界面从AGNPS模型的几个GIS层提取输入参数。这些风暴事件的地表水量和水质数据是从美国地质调查局(USGS)的测量站获得的。进行基本流分离以从总流中除去水和总悬浮沉积物(TSS),总氮(总N)和总磷(总P)的基本流量分数。在暴风雨期间,为小流域制定了连续的前期含水量比率,并将其用于调整各种土地覆被的土壤保护服务曲线数(SCS-CN)。使用概率方法(Koelliker和Humbert,1989)在风暴量和估计的能量强度(EI)值之间建立了一种关系,并且EI值用于运行AGNPS模型输入文件。针对测得的水质数据校准了几个模型参数,然后在不同的子流域上运行模型以评估建模过程。发现该建模过程对于具有足够降雨数据的较小子流域有效。但是,在大的分流域,降雨和土地覆盖变化很大的情况下,这一过程不太令人满意。这种集成的建模过程对于资源管理者评估子集水区的水质并确定集水区中的区域非常有用,这些区域将为土地使用决策制定行动计划,例如采用最佳管理实践(BMP)来改善水质。 。*; *本论文包括一张复合CD(该论文既包含纸质副本,又包含CD)。该CD需要以下应用程序:Microsoft Excel; AGNPS ARC INFO(包括程序);用于ERDAS IMAGINE软件的NDVI估计(包括在内)(不包括在内); Winzip;真正的自动点唱机。

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