Geospatial data resampling and resolution effects on watershed modeling: A case study using the agricultural non-point source pollution model
Geospatial data resampling and resolution effects on watershed modeling: A case study using the agricultural non-point source pollution model
复制标题
地理空间数据重采样和分辨率对流域建模的影响：使用农业面源污染模型的案例研究
DOI：
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发表时间：
2004
影响因子：
2.9
通讯作者：
M. Bearden
中科院分区：
文献类型：
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作者：
E. L. Usery;Michael P. Finn;D. Scheidt;S. Ruhl;Thomas Beard;M. Bearden
摘要：多年来，研究人员一直将地理信息系统（GIS）的数据处理能力与流域和水质模型相结合。这种能力适合于开发适合水模型的数据库。然而，地理信息系统很少为模型提供直接投入。为了说明耦合GIS进行模型参数提取的逻辑过程，我们选择了农业非点源污染模型。调查人员可以生成各种分辨率的数据层，并重新采样到像素大小，以支持特定尺度的模型。我们在四个流域开发了不同分辨率的海拔、土地覆盖和土壤数据库。使用多分辨率数据库生成模型参数的能力对于基于网格的模型是有问题的。我们使用的数据库开发程序，并观察分辨率和rescue对GIS输入数据集和参数产生的影响，从这些输入AGESTOS。结果表明，在特定点的高程值比较有利的3和30米的光栅数据集。分类数据分析表明，土地覆被类别差异很大。派生参数与基本GIS数据集的结果并行。从30米到60，120，210，240，480，960和1920米像素重采样的数据分析表明，随着分辨率的降低，海拔和土地覆盖的相关性普遍下降。可溶性氮和磷的模型输出值的初步评价表明，类似的降解与分辨率。
Abstract.Researchers have been coupling geographic information systems (GIS) data handling and processing capability to watershed and water-quality models for many years. This capability is suited for the development of databases appropriate for water modeling. However, it is rare for GIS to provide direct inputs to the models. To demonstrate the logical procedure of coupling GIS for model parameter extraction, we selected the Agricultural Non-Point Source (AGNPS) pollution model. Investigators can generate data layers at various resolutions and resample to pixel sizes to support models at particular scales. We developed databases of elevation, land cover, and soils at various resolutions in four watersheds. The ability to use multiresolution databases for the generation of model parameters is problematic for grid-based models. We used database development procedures and observed the effects of resolution and resampling on GIS input datasets and parameters generated from those inputs for AGNPS. Results indicate that elevation values at specific points compare favorably between 3- and 30-m raster datasets. Categorical data analysis indicates that land cover classes vary significantly. Derived parameters parallel the results of the base GIS datasets. Analysis of data resampled from 30-m to 60-, 120-, 210-, 240-, 480-, 960-, and 1920-m pixels indicates a general degradation of both elevation and land cover correlations as resolution decreases. Initial evaluation of model output values for soluble nitrogen and phosphorous indicates similar degradation with resolution.