{"title":"Simulating change in surface runoff depth due to LULC change using soil and water assessment tool for flash floods prediction","authors":"T. Mawasha, W. Britz","doi":"10.4314/sajg.v9i2.19","DOIUrl":null,"url":null,"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.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.3000,"publicationDate":"2022-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"South African Journal of Geomatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4314/sajg.v9i2.19","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"REMOTE SENSING","Score":null,"Total":0}
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.