<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Gullies and other forms of erosion have been the greatest environmental problem and catastrophe in most high- and low-income countries. The challenge posed by soil erosion has compromised agricultural productivity, environmental biodiversity and food safety for the world's population. It is important to identify vulnerable areas to soil erosion in each region to initiate remedial measures. This study demonstrates the use of watershed morphometry coupled with weighted sum analysis (WSA) to estimate the soil erosion susceptibility of the Imo River Basin sub-watersheds (SWs) in South-Eastern Nigeria using satellite remote-sensing data and geographic information system (GIS) analysis. To this end, Shuttle Radar Topography Mission (SRTM), a Digital Elevation Model (DEM) with 30 m spatial resolution was used to extract and analyse 18 morphometric parameters including basic, linear, shape and relief. The method of receiver operating characteristics (ROC) curves was used to validate the model's prediction accuracy. This morphometry-based analysis resulted in the SWs being classified into zones of low, medium, high and very high erosion susceptibility. With regard to erosion susceptibility, 41.51% of the basin (2494.68 km<sup>2</sup>) is in the very high priority zone; while 10.50%, 44.33% and 3.66% of the basin are in the high, medium and low priority zones respectively. Validation of the final erosion susceptibility map showed a prediction accuracy of 81%. The use of satellite imagery and morphometric analysis in this study was cost- and time-effective for identifying areas susceptible to soil erosion.</p>
</abstract>

Gullies and other forms of erosion have been the greatest environmental problem and catastrophe in most high- and low-income countries. The challenge posed by soil erosion has compromised agricultural productivity, environmental biodiversity and food safety for the world's population. It is important to identify vulnerable areas to soil erosion in each region to initiate remedial measures. This study demonstrates the use of watershed morphometry coupled with weighted sum analysis (WSA) to estimate the soil erosion susceptibility of the Imo River Basin sub-watersheds (SWs) in South-Eastern Nigeria using satellite remote-sensing data and geographic information system (GIS) analysis. To this end, Shuttle Radar Topography Mission (SRTM), a Digital Elevation Model (DEM) with 30 m spatial resolution was used to extract and analyse 18 morphometric parameters including basic, linear, shape and relief. The method of receiver operating characteristics (ROC) curves was used to validate the model's prediction accuracy. This morphometry-based analysis resulted in the SWs being classified into zones of low, medium, high and very high erosion susceptibility. With regard to erosion susceptibility, 41.51% of the basin (2494.68 km2) is in the very high priority zone; while 10.50%, 44.33% and 3.66% of the basin are in the high, medium and low priority zones respectively. Validation of the final erosion susceptibility map showed a prediction accuracy of 81%. The use of satellite imagery and morphometric analysis in this study was cost- and time-effective for identifying areas susceptible to soil erosion.

Soil Erosion Susceptibility Mapping of Imo River Basin Using Modified Geomorphometric Prioritisation Method

Department of Surveying and Geoinformatics

Quaestiones Geographicae

This work is licensed under the Creative Commons Attribution 4.0 International License.

Gullies and other forms of erosion have been the greatest environmental problem and catastrophe in most high- and low-income countries. The challenge posed by...

Soil Erosion Susceptibility Mapping of Imo River Basin Using Modified Geomorphometric Prioritisation Method

Online veröffentlicht: 30. Sept. 2021

Seitenbereich: 143 - 162

Eingereicht: 24. März 2021

DOI: https://doi.org/10.2478/quageo-2021-0029

Schlüsselwörter
morphometry, weighted sum analysis, soil erosion susceptibility, SRTM, remote sensing, GIS, Imo River Basin

© 2021 Peter C. Nwilo et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Soil Erosion Susceptibility Mapping of Imo River Basin Using Modified Geomorphometric Prioritisation Method

Online veröffentlicht: 30. Sept. 2021

Seitenbereich: 143 - 162

Eingereicht: 24. März 2021

DOI: https://doi.org/10.2478/quageo-2021-0029

Schlüsselwörtermorphometry, weighted sum analysis, soil erosion susceptibility, SRTM, remote sensing, GIS, Imo River Basin

© 2021 Peter C. Nwilo et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
morphometry, weighted sum analysis, soil erosion susceptibility, SRTM, remote sensing, GIS, Imo River Basin