The Murredu watershed in Telangana State was chosen for the morphometric and land use/land cover (LULC) analysis in this current study. Geographical information system (GIS) and remote sensing (RS) techniques can estimate the morphometric features and LULC analysis of a catchment. A total of fourteen sub-watersheds (SWs) were created from the watershed (SW 1 to SW 14), and sub-watersheds were prioritized based on morphometric and LULC features. Evaluation of various morphometric characteristics such as linear aspects, relief aspects, and aerial aspects has been carried out for every sub-watershed to prefer ranking. Four parameters were utilized for the LULC analysis to rank and prioritize sub-watersheds. The sub-watersheds were categorized into three groups as low, medium, and high, for soil and water conservation priority based on morphometric and LULC analysis. Using morphometric analysis, higher priorities have been assigned to SW 12 and SW 1, while using LULC analysis, higher priorities have been assigned to SW 9 and SW 11. SW 10 and SW 13 are the most common sub-watersheds that fall within the same priority while using morphometric and LULC analysis. The coefficient of regression results reveals that stream length and stream order, and also stream number and stream order, have a strong association. The deployment of soil and water conservation measures may be conducted in the high-priority sub-watersheds.

Urban development has consequently given rise to the empirically observed phenomenon of the urban heat island (UHI). The article aims to determine the change in land surface temperature (LST) over Jaipur study area during the period from 2008 to 2011 and analyzes the spatial variation of LST in the context of changes in land use/land cover (LU-LC). The LST has been retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) images for the years 2008 and 2011 to find the variation of LST as per the LU-LC classes. Results show a significant rise in temperature for all LU-LC categories during the study period. The percentage impervious surface area (ISA) pattern of these classes has also been analyzed for both the years, and a rising trend in ISA for different LU-LC categories has been observed; showing that Jaipur city has witnessed substantial growth in built-up area at the cost of greener patches and open land at a fast pace having a clear impact on LST variation. The average rise in temperature during winter season was found to be around 2.6 °C while 1.47 °C rise was observed during summers. Inter-seasonal variations of LST on different LU-LC over Jaipur have been analyzed.

Water resource management is critical in the face of climate change to reduce water scarcity and meet the demands of an expanding population. Prioritization of watersheds has gained significance in natural resource management, particularly in the context of watershed management. This study prioritizes sub-watersheds for the Peddavagu basin using five methods. The four methods mentioned above can be estimated utilizing remote sensing (RS) and geographic information system (GIS) approaches, while linear discriminant analysis (LDA) is estimated using machine learning techniques. The catchment resulted in the formation of 13 sub-watersheds. The quantitative measurements of morphometric analysis, including linear, relief, and areal, were considered, and 18 morphometric characteristics were chosen to rank and prioritize sub-watersheds. Principal component analysis (PCA) was used to rank and prioritize sub-watersheds based on four highly correlated morphometric parameters. The land use/land cover (LULC) analysis used four features to prioritize sub-watersheds. The LDA analysis used two features to prioritize sub-watersheds. Using hypsometric integral (HI) values, prioritization has been done. Sub-watersheds were prioritized. Based on five methods, the sub-watersheds were classified as low, medium, and high. Among the sub-watersheds identified as high priority, immediate priority is assigned to SW10. Decision-makers in the research region can use the findings to plan and implement watershed management techniques.

The sustainable management of groundwater resources is crucial for ecological diversity, human health, and economic growth. This study employs scientific concepts and advanced techniques, including the analytic hierarchy process (AHP) and Fuzzy-AHP, to identify groundwater potential zones (GWPZs). Thematic maps representing drainage density, elevation, soil, geomorphology, slope, land use and land cover, and rainfall are used to delineate the GWPZs. Both techniques are employed to assign weights to these thematic maps based on their characteristics and water potential. The study revealed that in the investigated area, 17.76 and 18.27% of the final GWPZs (AHP and Fuzzy-AHP) can be classified as having poor potential, while 72.79 and 71.07% are categorized as having moderate potential. Moreover, 9.45 and 10.69% of the final GWPZs are identified as having high potential using the AHP and Fuzzy-AHP models, respectively. Receiver operating characteristics (ROCs) analysis is employed to validate these findings, demonstrating that the Fuzzy-AHP technique achieves an accuracy of 74% in identifying GWPZs in the region. This study utilizes the best method derived from both models to identify 26 suitable locations for artificial recharge sites. The reliable findings of this research offer valuable insights into decision-makers and water users in the Kinnerasani Watershed.