Chaitanya B. Pande

Integration of remote sensing (RS) and GIS methods has allowed for the identification of potential water resource zones. Here, climatic, ecological, hydrologic, and topographic data have been integrated with microwave and multispectral data. Sentinel-2, SRTM, and TRMM data were developed to characterize the climatic, hydrologic, and topographic landscapes of Wadi Fatima, a portion of western Saudi Arabia that drains to the Red Sea. The physical characteristics of Wadi Fatima’s catchment area that are essential for mapping groundwater potential zones were derived from topographic data, rainfall zones, lineaments, and soil maps through RS data and GIS techniques. Twelve thematic factors were merged with a GIS-based knowledge-driven approach after providing a weight for every factor. Processing of recent Sentinel-2 data acquired on 4 August 2023 verified the existence of a zone of vegetation belonging to promising areas of groundwater potential zones (GPZs). The output map is categorized into six zones: excellent (10.98%), very high (21.98%), high (24.99%), moderate (21.44%), low (14.70%), and very low (5.91%). SAR CCD derived from Sentinel-1 from 2022 to 2023 showed that the parts of no unity are in high-activity areas in agricultural and anthropogenic activities. The model predictions were proven with the ROC curves with ground data, existing wells’ locations, and the water-bearing formations’ thickness inferred from geophysical data. Their performance was accepted (AUC: 0.73). The outcomes of the applied methodologies were excellent and important for exploring, planning, managing, and sustainable development of resources of water in desert areas. The present study successfully provided insights into the watershed’s hydrologic, climatic, vegetated variation, and terrain database information using radar, optical, and multi-temporal InSAR data. Furthermore, the applied multi-criteria overlay technique revealed promising areas for groundwater abstraction, which can be applied elsewhere in various environmental situations.

Currently, natural hazards are a significant concern as they contribute to increased vulnerability, environmental degradation, and loss of life, among other consequences. Climate change and human activities are key factors that contribute to various natural hazards such as floods, landslides, droughts, and deforestation. Assam state in India experiences annual floods that significantly impact the local environment. In 2022, the flooding affected approximately 1.9 million people and 2930 villages, resulting in the loss of 54 lives. This study utilized the Google Earth Engine (GEE) cloud-computing platform to investigate the extent of flood inundation and deforestation, analyzing pre-flood and post-flood C band Sentinel-1 GRD datasets. Identifying pre- and post-flood areas was conducted using Landsat 8–9 OLI/TIRS datasets and the modified and normalized difference water index (MNDWI). The districts of Cachar, Kokrajhar, Jorhat, Kamrup, and Dhubri were the most affected by floods and deforestation. The 2022 Assam flood encompassed approximately 24,507.27 km2 of vegetation loss and 33,902.49 km2 of flood inundation out of a total area of 78,438 km2. The most affected areas were the riverine regions, the capital city Dispur, Guwahati, southern parts of Assam, and certain eastern regions. Flood hazards exacerbate environmental degradation and deforestation, making satellite-based information crucial for hazard and disaster management solutions. The findings of this research can contribute to raising awareness, planning, and implementing future disaster management strategies to protect both the environment and human life.

Wetland ecosystems are essential for maintaining biological diversity and are significant elements of the global landscape. However, the biodiversity of wetlands has been significantly reduced by more than 50% worldwide due to the rapid expansion of urban areas and other human activities. The aforementioned factors have resulted in drastic antagonistic effects on species composition, particularly aquatic avifauna. The decline in wetland avifauna, which can be attributed to changes in water quality that impact aquatic habitats, is a major concern. In this study, we evaluated the impact of physicochemical parameters on aquatic avifauna in India’s first Conservation Reserve, a Ramsar site and an Important Bird Area. Water samples were collected on a monthly basis across nine different sites and various parameters, such as temperature, electrical conductivity, pH, biological oxygen demand, dissolved oxygen, total dissolved solids and salinity, were analyzed for pre-monsoon and post-monsoon seasons, while point count surveys were conducted to assess species richness and the density of waterbirds. Our findings show a positive correlation of species density with water temperature (r = 0.57), total dissolved solids (r = 0.56) and dissolved oxygen (r = 0.6) for pre-monsoon season and a negative correlation for dissolved oxygen (r = −0.62) and biological oxygen demand (r = −0.69) for post-monsoon season. We suggest that a synergistic effect of pH, salinity, biological oxygen demand and total dissolved solids may affect aquatic bird populations in Asan Conservation Reserve. Poor water quality was observed in a few sampling sites, which may negatively affect the number and density of waterbirds present. The findings of this study emphasize the importance of water quality in wetland conservation, particularly for aquatic avifauna.