Soil erosion is becoming a major concern at the watershed scale for the environment, natural resources, and sustainable resource management. Therefore, the estimation of soil loss through this phenomenon and the identification of critical soil erosion-prone areas are considered to be key tasks in the soil conservation programme for the design and implementation of best management practices for specific regions or areas. In the present study, revised universal soil loss equation (RUSLE) modelling is combined with remote sensing (RS) and geographical information system (GIS) techniques and used to predict soil erosion and the prioritization of watersheds in Nainital district Uttarakhand, India. For the estimation of soil loss, different factors, namely, rainfall-runoff erosivity (R) factor, soil erodability (K) factor, slope length steepness (LS) factor, cover management (C) factor, and the erosion control practices (P) factor were computed. The data on various other aspects such as land use/land cover (LU/LC), the digital elevation model (DEM), slope, contours, drainage network, soil texture, organic matter, and rainfall were integrated to prepare a database for the RUSLE equation by employing ENVI & QGIS software. The results showed that a major portion (70.26%) of Nainital district is covered with forest, followed by area under fallow and agricultural land. Annual average soil loss ranged between 20 to 80 t ha⁻¹ yr⁻¹ in the study area. Out of 50 watersheds in the study area, 7 watersheds were given top priority for conserving natural resources, while 11 watersheds, mostly in the east-central part of Nainital, were kept under the next priority category. Only 4 watersheds of the total were given lowest priority. Moreover, it was concluded that major portions of Nainital district were in a severely prone category of soil erosion, and therefore required immediate action plans to check soil erosion and evade the possibility of landslides.

The study aimed to assess the dynamic behavior of groundwater levels in the southwestern districts of Indian Punjab, focusing on the spatial and temporal distribution of waterlogged and overexploited areas before and after the monsoon season. The study utilized groundwater level data spanning 48 years (1973 -2020), using GIS to map groundwater levels and visualize fluctuations throughout the study area. The findings revealed significant variations in groundwater levels within the southwestern district of Punjab during different seasons. The maximum waterlogged areas were found to be 97,350 ha (1973, Faridkot), 56,080 ha (1981, Ferozepur), 21,730 ha (1991, Sri Muktsar Sahib), 52,790 ha (2000, Sri Muktsar Sahib), 6,760 ha (2010, Sri Muktsar Sahib), and 2,910 ha (2020, Fazilka). However, the waterlogged and potential waterlogging area observed in Fazilka district covered about one-third (32.52%) of the district during 2020. The study identified that 45% of the study area faced the risk of overexploitation, 46% was considered safe, and 9% was either waterlogged or at risk of waterlogging. Over the 48 years, the study demonstrated the dynamic nature of waterlogged areas in the southwestern districts of Punjab, including Ferozepur to Fazilka via Faridkot and Sri Muktsar Sahib districts.

Semi-arid region can benefit greatly from surface and subsurface drip irrigation techniques in overcoming the problem of water scarcity. Therefore, a field study was carried out at the research farm of CCS Haryana Agricultural University, Hisar, Haryana during winter (rabi) season 2019–20 and 2020–21 to investigate the effectiveness of surface and subsurface drip irrigation on growth and yield of broccoli (Brassica oleracia L.). Subsurface drip irrigation shows higher moisture content than surface drip irrigation at vertical as well as radial distance. The growth parameters were found highest in the treatment irrigation after one day under subsurface drip irrigation. The average highest (14610 kg/ha in 2019–20 and 14740 kg/ha in 2020–21) and lowest (12920 kg/ha in 2019–20 and 13030 kg/ha in 2020–21) total yield was recorded under irrigation after one day in subsurface drip irrigation and irrigation after three days in surface drip irrigation treatments, respectively. It is concluded that alternate days irrigation with subsurface drip irrigation gives better performance to obtain the maximum yield of broccoli grown in the semi-arid region of India.

This research explores the intricate dynamics of cropping patterns and their influence on waterlogging and salinity in the semi–arid region of Indian Punjab. Examining the timeframe from 1991–92 to 2020–21 in the southwestern districts of Punjab, the study identifies notable shifts in the cultivation areas of major crops. There is an increase in the cultivation of rice, wheat, and vegetables, while cotton, fruits, oilseeds, and pulses experience declining trends. From 1991–92 to 2020–21, the area under rice cultivation increased by 41.05% in Bathinda, 53.27% in Faridkot, 39.52% in Ferozepur, and 4.21% in Fazilka, while cotton cultivation declined by 23.45%, 36.70%, 27.17%, and 2.13%, respectively. The expansion of irrigated areas, driven by both canal and tubewell irrigation, accompanies these shifts. However, the intensified irrigation and cultivation of high water requirement crops contributes to a rise in the water table, resulting in increased waterlogging and salinity in Fazilka, Sri Muktsar Sahib, and Faridkot districts, posing threats to soil health and crop yields. Correlation analysis indicates a significant positive correlation between rice, wheat, and vegetable cultivation and salt–affected waterlogged areas, exacerbating waterlogging and salinity due to the high water requirements of these crops. In contrast, cotton and fruit cultivation display a significant negative correlation with waterlogged areas. This thorough analysis underscores the urgency of adopting sustainable agricultural practices and collaborative irrigation management to effectively address waterlogging and salinity challenges. A joint effort involving farmers and policymakers is imperative to promote sustainable agriculture and enhance crop productivity in the region.