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Soil erosion is one of the major environmental concerns, causing a reduction in soil carbon stock and soil fertility. It is generally difficult to estimate soil erosion in hilly terrains. To overcome this, different types of erodibility indices are developed and used to describe the intensity of soil erosion. The present study was conducted in Nagaland state of northeast India, where clay ratio (CR), modified clay ratio (MCR), critical level of organic matter (CLOM) and erodibility factor (K) were used to assess the severity of soil erosion under different land uses. To study these, soil samples from forest, jhum, fallow jhum and tea gardens were collected from 0 to 30 cm soil depth. The results showed that sand and clay content were significantly different under different land uses, while soil organic carbon (SOC) and stocks followed the same trend, with maximum and minimum values under tea (60.55 t C ha–1 ) and jhum lands (40.74 t C ha–1 ) respectively. Among the different erodibility indices, only CR and MCR values were found to be significantly different from each other. Higher values of CR and MCR under jhum and fallow jhum lands indicate that these land uses are more prone to erosion. The present study provides a picture of severity of soil erosion under different land uses in Nagaland and recommends that CR and MCR can be used to evaluate soil erosion in hilly terrain areas. [ABSTRACT FROM AUTHOR]

Land surface temperature (LST) and its interaction with normalized difference vegetation index (NDVI) are crucial for better understanding of environmental changes in current scenario. Therefore, the purpose of conducting this study was to examine, how LST and NDVI change as a function of elevation in Rajasthan. In present study, MODIS derived NDVI and LST and digital elevation model (DEM) from shuttle radar topography mission (SRTM) have been used. Results revealed that the LST and NDVI both were significantly influenced by elevation. Elevation, NDVI and LST varied from -6 to 1698 m, -0.09 to 0.65 and 24 to 45°C throughout the study region. In contrast to LST, which has a decreasing gradient from western to eastern portions, the spatial variability of NDVI has decreasing gradients from southern and eastern to western regions. The highest mean LST value (39.76 ± 0.2.9 0C) was obtained in elevation range of -6 to 168 m, whereas NDVI value (0.38 ± 0.06) in elevation ranges of 589 - 1698 m. The elevation has strong positive correlation with NDVI (R² = 0.26) and negative correlation with LST (R² = 0.28). Findings from this research can be utilized as a platform for environmental and land use planning for sustainable ecosystem management. [ABSTRACT FROM AUTHOR]

Wind erosion is a major natural disaster worldwide, and it is a key problem in western Rajasthan in India. The Analytical Hierarchy Process (AHP), the Geographic Information System (GIS), and remote sensing satellite images are effective tools for modeling and risk assessment of land degradation. The present study aimed to assess and model the land degradation vulnerable (LDV) zones based on the AHP and geospatial techniques in the Luni River basin in Rajasthan, India. This study was carried out by examining important thematic layers, such as vegetation parameters (normalized difference vegetation index and land use/land cover), a terrain parameter (slope), climatic parameters (mean annual rainfall and land surface temperature), and soil parameters (soil organic carbon, soil erosion, soil texture, and soil depth), using the Analytical Hierarchical Process (AHP) and geospatial techniques in the Luni River basin in Rajasthan, India. The weights derived for the thematic layers using AHP were as follows: NDVI (0.27) > MAR (0.22) > LST (0.15) > soil erosion (0.12) > slope (0.08) > LULC (0.06) > SOC (0.04) > soil texture (0.03) > soil depth (0.02). The result indicates that nearly 21.4 % of the total area is prone to very high degradation risks; 12.3% is prone to high risks; and 16%, 24.3%, and 26% are prone to moderate, low, and very low risks, respectively. The validation of LDV was carried out using high-resolution Google Earth images and field photographs. Additionally, the Receiver Operating Characteristic (ROC) curve found an area under the curve (AUC) value of 82%, approving the prediction accuracy of the AHP technique in the study area. This study contributes by providing a better understanding of land degradation neutrality and sustainable soil and water management practices in the river basin. [ABSTRACT FROM AUTHOR]

This study aims to identify soil quality indicators, assess soil quality index (SQI), and validate them with crop yield for India's two contrasting Agro-ecological Sub-Regions (AESRs). For this, 340 and 85 soil samples (0–15 cm) from AESRs 6.1 (semi-arid dry) and 18.4 (sub-humid dry) were analysed for 26 soil physical, chemical, and biological properties. Principal component analysis (PCA) was used to identify soil quality indicators, and the SQI and relative SQI (RSQI) were calculated using the weighted index method. We identified soil pH, active carbon pool (ACP), and available Zn as common indicators for both the AESRs apart from specific indicators. The SQI of AESR 6.1 soils under cotton and sugarcane were higher (0.48–0.75) than the AESR 18.4 soils under rice (0.26–0.70). Among the indicators, EC (35%), CEC (24%), pH (23%), clay (17%), and ACP (14%) significantly contributed to the SQI. The strong relationship of RSQI with the yield of cotton (R2 = 0.52), sugarcane (R2 = 0.68), and rice (R2 = 0.64) indicated that the selected indicators are representative to measure soil quality. We conclude that AESR specific soil quality indicators are appropriate for the evaluation and monitoring of agroecosystem functions. [ABSTRACT FROM AUTHOR]