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Morphometric analysis for soil erosion susceptibility mapping using novel gis-based ensemble model

Arabameri A. Department of Geomorphology, Tarbiat Modares University, Tehran, 14117-13116, Iran|
Bui D.T. Department of Energy and Mineral Resources Engineering, Sejong University, Choongmu-gwan, 209 Neungdong-ro, Gwangjin-gu, Seoul, 05006, South Korea| Pradhan B. Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), School of Information, University of Technology Sydney, Sydney, NSW 2007, Australia| Blaschke T. Department of Geoinformatics-Z-GIS, University of Salzburg, Salzburg, 5020, Austria| Tiefenbacher J.P. Department of Geography, Texas State University, San Marcos, TX 78666, United States|

Remote Sensing Số 5, năm 2020 (Tập 12, trang -)

DOI: 10.3390/rs12050874

Tài liệu thuộc danh mục: ISI, Scopus

English

English

Từ khóa: Agronomy; Decision making; Drainage; Erosion; Geographic information systems; Geomorphology; Hierarchical systems; Lithology; Remote sensing; Sensitivity analysis; Soils; Surveying; Synthetic aperture radar; Tectonics; Textures; Drainage networks; Ensemble techniques; Kalvari basin; Morphometry; Soil erosion; Catchments
Tóm tắt tiếng anh
The morphometric characteristics of the Kalvari basin were analyzed to prioritize sub-basins based on their susceptibility to erosion by water using a remote sensing-based data and a GIS. The morphometric parameters (MPs)-linear, relief, and shape-of the drainage network were calculated using data from the Advanced Land-observing Satellite (ALOS) phased-array L-type synthetic-aperture radar (PALSAR) digital elevation model (DEM) with a spatial resolution of 12.5 m. Interferometric synthetic aperture radar (InSAR) was used to generate the DEM. These parameters revealed the network's texture, morpho-tectonics, geometry, and relief characteristics. A complex proportional assessment of alternatives (COPRAS)-analytical hierarchy process (AHP) novel-ensemble multiple-criteria decision-making (MCDM) model was used to rank sub-basins and to identify the major MPs that significantly influence erosion landforms of the Kalvari drainage basin. The results show that in evolutionary terms this is a youthful landscape. Rejuvenation has influenced the erosional development of the basin, but lithology and relief, structure, and tectonics have determined the drainage patterns of the catchment. Results of the AHP model indicate that slope and drainage density influence erosion in the study area. The COPRAS-AHP ensemble model results reveal that sub-basin 1 is the most susceptible to soil erosion (SE) and that sub-basin 5 is least susceptible. The ensemble model was compared to the two individual models using the Spearman correlation coefficient test (SCCT) and the Kendall Tau correlation coefficient test (KTCCT). To evaluate the prediction accuracy of the ensemble model, its results were compared to results generated by the modified Pacific Southwest Inter-Agency Committee (MPSIAC) model in each sub-basin. Based on SCCT and KTCCT, the ensemble model was better at ranking sub-basins than the MPSIAC model, which indicated that sub-basins 1 and 4, with mean sediment yields of 943.7 and 456.3m3km-2 year-1, respectively, have the highest and lowest SE susceptibility in the study area. The sensitivity analysis revealed that the most sensitive parameters of the MPSIAC model are slope (R2 = 0.96), followed by runoff (R2 = 0.95). The MPSIAC shows that the ensemble model has a high prediction accuracy. The method tested here has been shown to be an effective tool to improve sustainable soil management. � 2020 by the author. Licensee MDPI, Basel, Switzerland.

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