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Globally, soil erosion is a significant problem contributing to nutrient loss, water quality degradation, and sand accumulation in water bodies. Currently, various climate factors are affecting the natural resources entire worldwide. Agricultural intensification, soil degradation, and some other human impacts all contribute to soil erosion, which is a significant issue. Management and conservation efforts in a watershed can benefit from a soil erosion study. Modeling can establish a scientific and accurate method to calculate sediment output and soil erosion below a variety of circumstances. The measured soil loss tolerance was compared to the risk of soil erosion (T value).In this study, GIS and remote sensing techniques have been integrated with the Revised Universal Soil Loss Equation (RUSLE) model to estimate soil loss in the Mayurakshi river basin of eastern India. To determine soil erosion-prone areas, rainfall, land use, and land cover maps, as well as a digital elevation model (DEM), were used as input. The annual soil loss in the basin area is estimated to be 4,629,714.8 tons. Accordingly, the study basin was categorized into five soil loss severity classes: very low (40.92%), low (49%), moderate (6.5%), high (2.4%) and very high (1.18%) risk classes. Soil erosion rates ranged from very slight to slight throughout the majority of the region. The section of the basin's lower plain has been discovered to be least affected by soil loss. The results of study area can be helpful to conservation of soil management practices and watershed development program in the basin area. [ABSTRACT FROM AUTHOR]

Renewable energy is considered to be one of the viable options in consideration of intense economic development and increasing energy consumption. With maturity of advanced technologies, economical viable and environmental friendly, wind energy has become one of the fastest growing sources of renewable energy in the world. This study focuses on the combined use of geographic information systems (GIS) and spatial multi-criteria decision analysis for selecting the most appropriate sites for wind-farm development projects. This paper utilized wind speed data over a period of almost 20 years between 1991 and 2010 from different stations to assess the wind power potential sites. The wind energy potential zones were grouped into four categories as “high suitable”, “moderate suitable”, “low suitable” and “not suitable”. The results show that the study area has 12.20% (2787.78 km 2 ) as high suitable, 17.06% (3899.78 km 2 ) as moderate suitable and 11.06% (2528.61 km 2 ) as low suitable. The most potential suitable sites were located in the northwestern (along Osian, Shergargh, Dechu, and Shaitrawa, Phalodi) of Jodhpur district, India. This scientific approach will enable resource managers during planning process to make informed decisions. [ABSTRACT FROM AUTHOR]