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Titlebook: Distributed Hydrologic Modeling Using GIS; Baxter E. Vieux Book 20011st edition Springer Science+Business Media B.V. 2001 Infiltration.agr

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書目名稱Distributed Hydrologic Modeling Using GIS
編輯Baxter E. Vieux
視頻videohttp://file.papertrans.cn/282/281905/281905.mp4
叢書名稱Water Science and Technology Library
圖書封面Titlebook: Distributed Hydrologic Modeling Using GIS;  Baxter E. Vieux Book 20011st edition Springer Science+Business Media B.V. 2001 Infiltration.agr
描述During ten years serving with the USDA Soil Conservation Service (SCS), now known as the Natural Resources Conservation Service (NRCS), I became amazed at how millions of dollars in contract monies were spent based on simplistic hydrologic models. As project engineer in western Kansas, I was responsible for building flood control dams (authorized under Public Law 566) in the Wet Walnut River watershed. This watershed is within the Arkansas-Red River basin, as is the Illinois River basin referred to extensively in this book. After building nearly 18 of these structures, I became Assistant State Engineer in Michigan and, for a short time, State Engineer for NRCS. Again, we based our entire design and construction program on simplified relationships variously referred to as the SCS method. I recall announcing that I was going to pursue a doctoral degree and develop a new hydrologic model. One of my agency‘s chief engineers remarked, "Oh no, not another model!" Since then, I hope that I have not built just another model but have significantly advanced the state of hydrologic modeling for both researchers and practitioners. Using distributed hydrologic techniques described in this book,
出版日期Book 20011st edition
關(guān)鍵詞Infiltration; agriculture; simulation; soil; water; hydrogeology
版次1
doihttps://doi.org/10.1007/978-94-015-9710-4
isbn_ebook978-94-015-9710-4Series ISSN 0921-092X Series E-ISSN 1872-4663
issn_series 0921-092X
copyrightSpringer Science+Business Media B.V. 2001
The information of publication is updating

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Surface Generation,eration of raster surfaces from data points. Given the many surface generation utilities available within general purpose GIS packages such as ArcView or GRASS, it is important to understand how these surfaces are generated and some of the pitfalls. Figure 3.1 shows the hillslope shaded image of the
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Information Content and Spatial Variability,ufficient to capture spatial information. In the following sections we first examine the background and theory of informational entropy; how this statistic serves as a measure of spatial variability; and an application showing the effects of resolution on slope derived from a raster DEM. Using infor
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Infiltration,gure 5.1 shows an eroded ski slope in Kalkaskia County, Michigan. The Kalkaskia soil is of glacial origin with permeability in excess of 24 cm/hr. Surface runoff and subsequent erosion was possible only because surface vegetation had been removed for construction and raindrop impact caused surface s
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Precipitation,igure 8.2. Reflectivity depends on the distribution of raindrop sizes with higher reflectivity (>35 dBZ) shown in black representing more intense rainfall. Radar is an important source of spatially and temporally distributed rainfall data for hydrologic modeling. This chapter deals with the use of w
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Calibration,ion considered, the equation modeled, and the associated data sets. The often-stated advantage of physics-based or deterministic representation of distributed hydrologic processes is that parameters having physical significance are properties of the media. Under this tenant, hydraulic roughness is a
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