Effects of land-use land-cover data resolution and classification methods on SWAT model flow predictive reliability

被引：7

作者：

Asante K. ^{[1
]}

Leh M.D. ^{[2
]}

Cothren J.D. ^{[3
]}

Di Luzio M. ^{[4
]}

Van Brahana J. ^{[5
]}

机构：

[1] Environmental Systems Research Institute (ESRI), 3325 Springbank Ln # 200, Charlotte, 28226, NC

[2] Department of Biological and Agricultural Engineering, University of Arkansas, Fayetteville, 72701, AR

[3] Center for Advanced Spatial Technologies (CAST), University of Arkansas, 304 JBHT, Fayetteville, 72701, AR

[4] Blackland Texas AgriLifeResearch and Extension Center, 720 Blackland Rd, Temple, 76502, TX

[5] University of Arkansas, 346 Arkansas Avenue, Fayetteville, 72701, AR

来源：

International Journal of Hydrology Science and Technology | 2017年 / 7卷 / 01期

关键词：

High and low-resolution; Land-use land-cover; LULC; Remote sensing; SWAT stream-flow modeling;

D O I：

10.1504/IJHST.2017.080956

中图分类号：

学科分类号：

摘要：

The aim of this study is to evaluate the predictive reliability of the soil and water assessment tool (SWAT) model based on LULC data spatial resolution and image classification methods. The predictive reliability of the model is primarily evaluated with two descriptive statistics; the p-factor and the r-factor. The p-factor quantifies the percentage of the observed data that a calibrated model captures whereas the r-factor quantifies the level of uncertainty associated with the calibrated model. The hypothesis is that a combination of GIS-based hydrologic modelling and the promise of high-resolution LULC data obtained through object-oriented image analysis (OOIA) significantly improves SWAT flow predictive reliability. Two SWAT models were setup and calibrated at a gauging station located within the study area. After both manual and auto-calibration, results showed that the low-resolution model had a slightly better predictive reliability. The impact of the classification methods is however unclear. © Copyright 2017 Inderscience Enterprises Ltd.

引用

页码：39 / 62

页数：23

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