Simulating change in surface runoff depth due to LULC change using soil and water assessment tool for flash floods prediction

IF 0.3 Q4 REMOTE SENSING South African Journal of Geomatics Pub Date : 2022-09-07 DOI:10.4314/sajg.v9i2.19
T. Mawasha, W. Britz
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引用次数: 1

Abstract

Accurate documentation of land-use/land-cover (LULC) change and evaluating its hydrological impact are of great interest for catchment hydrological management. Jukskei River catchment has undergone a rapid infrastructural and residential development which had an influence on runoff depth. The objective of the study is to integrate Geographical Information System (GIS) and remote sensing (RS) techniques with Soil and Water Assessment Tool (SWAT) model to quantify the spatial and temporal changes in surface runoff depth resulting from LULC change. Landsat images of 1987 MSS, 2001 TM and 2015 OLI were pre-processed and classified using a supervised classification method with maximum likelihood. Results indicated that, there was a significant increase in built-up area from 28700.4ha in 1987 LULC to 36313.6ha in 2001 and 42713.1ha in 2015 at the expense of bare surface, intact vegetation and sparsed vegetation. However, during hydrological modelling, soil, DEM and climatic data were kept constant except LULC images which were interchanged during each simulation phase. Calibrated with observed hydrological data at the catchment outlets, SWAT model was used to evaluate the effect of LULC change on surface runoff depth. The analysis of SWAT model showed increases surface runoff depth from 70.5mm in 1987 LULC to 134.2mm in 2001 and 199.3mm in 2015 LULC. The SWAT model indicated satisfactorily results based on model calibration and validation results. Therefore, this study concluded that, integration of GIS and RS techniques with SWAT model can help in formulating policy guidelines for land-use practices thereby reducing hydrological impacts associated with LULC changes.
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利用土壤和水评估工具模拟LULC变化引起的地表径流深度变化,用于山洪预测
准确记录土地利用/土地覆盖变化及其水文影响对流域水文管理具有重要意义。Jukskei河流域经过了快速的基础设施和住宅开发,对径流深度产生了影响。本研究的目的是将地理信息系统(GIS)和遥感(RS)技术与土壤和水评估工具(SWAT)模型相结合,以量化LULC变化引起的地表径流深度的空间和时间变化。采用最大似然监督分类方法对1987年MSS、2001年TM和2015年OLI的陆地卫星图像进行了预处理和分类。结果表明,建成区面积从1987年的28700.4公顷显著增加到2001年的36313.6公顷和2015年的42713.1公顷,但代价是地表裸露、植被完整和稀疏。然而,在水文建模过程中,除了在每个模拟阶段交换的LULC图像外,土壤、DEM和气候数据保持不变。SWAT模型利用集水区出口的观测水文数据进行校准,用于评估LULC变化对地表径流深度的影响。SWAT模型分析表明,地表径流深度从1987年LULC的70.5mm增加到2001年的134.2mm和2015年的199.3mm。SWAT模型在模型校准和验证结果的基础上显示出令人满意的结果。因此,本研究得出结论,将地理信息系统和遥感技术与SWAT模型相结合,有助于制定土地利用实践的政策指南,从而减少与LULC变化相关的水文影响。
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