Evaluating Land Degradation Vulnerability Using Analytical Hierarchy Process (AHP) And Geo-Spatial Techniques In The Mashi Dam Command Area, Rajasthan (India)

Main Article Content

Brijmohan Bairwa, Rashmi Sharma

Abstract

Land degradation stands as a primary environmental calamity caused by combination of human activities and natural factors, affecting the sustainability of soil and ecosystems in arid and semi-arid regions globally. This issue underscores the necessity for identifying and planning vulnerability zones of land degradation at various scales, ranging from regional to micro levels. In this research work, rainfall, potential evapotranspiration (PET), data were extracted from Terra climate, while land surface temperature (LST) were extracted from Landsat series using the Climate Engine platform. Additionally, the study incorporated land-use/land-cover (LULC) information derived from Sentinel-2A imagery, as well as data on drainage and canal systems, elevation, slope, and key soil properties like electrical conductivity (EC) and exchangeable sodium percentage (ESP). Among these parameters, EC, ESP, LULC, PET and canal system were determined to be the most significant factors, followed by elevation, slope, LST, drainage and precipitation. Geospatial techniques derived products, and the analytical hierarchy process (AHP) were employed to model the land degradation vulnerability index (LDVI). The LDVI was classified into three classes: highly vulnerable (7.63%), moderately vulnerable (52.12%), and slightly vulnerable (40.26%) to viewing the affected fields due to the land degradation factors. The typically western part of the main canal of the study area, characterized by low precipitation rates vulnerable to evaporation under high temperatures, was identified as highly vulnerable to land degradation (LD), while the eastern part of the study area exhibited the opposite trend. The model's applicability was validated using high resolution dataset (Google Earth), demonstrating its effectiveness in the study. Furthermore, the validation using the Receiver Operating Characteristic (ROC) curve analysis yielded an area under curve (AUC) value of 80.6%, affirming the AHP method's accuracy in predicting LD vulnerability fields in the study area. This study significantly contributes to understanding the impact of land degradation on sustainable agriculture management and development in the Mashi Dam Command Area (MDCA), Rajasthan (India).

Article Details

Section
Articles