Groundwater is a natural resource used for drinking, agriculture, and industry, apart from surface water. Its quality should be assessed regularly, and the condition of water resources should be maintained accordingly. The most common analytical method for describing and assessing the general water quality is the Water Quality Index (WQI). This study aims to assess the South Gujarat Region’s groundwater quality using the WQI. Various physicochemical parameters like pH, turbidity, total dissolved solids, total hardness, calcium, magnesium, chloride, sulphate, nitrate, fluorides, and total alkalinity are considered for the present study. The data period from 2018 to 2022 is considered for the same. The Weighted Arithmetic Water Quality Index Technique is used to evaluate these data. For checking the potability of the parameters within the acceptable limit, the Indian Standard Drinking Water Specification code (IS: 10050-2012) is adopted. According to the study mentioned above, a few wells’ groundwater quality has been found to be higher than the WQI value. It is also observed that four wells were found unsuitable for drinking purposes in 2018. It is noted that if the WQI value of groundwater is above 51, it is considered harmful to human health; therefore, it requires some kind of processing before use. This study will be beneficial to the policymakers for identifying and providing details about groundwater quality in the form of a specific value, i.e., WQI.

This research work aimed to project and analyze climatic variability using GCMs and RCMs in the Hathmati River Basin, which happens to be one of the most important tributaries of Western India. The analysis included a baseline period from 1980 to 2014 and a future scenario (2050s) under a representative concentration pathway (RCP4.5). Following the evaluation of bias correction methods, distribution mapping and power transformation were used for temperature and precipitation projection, respectively. The 2050 s RCP4.5 simulations showed an increase in precipitation to 1,015.54 mm from 936.91 mm giving around a 8.45% increase in average precipitation. For temperature, the maximum temperature was around a 7.05% increase taking the average temperature to 34.21 from 33.97. The minimum temperature was 20.24 from 20.41 showing a positive change of around 8.4%. The future precipitation and temperature change projected might worsen the water stress and increase the probability of the occurrence of severe events, and hence mitigation strategies and management options to reduce this negative impact should be encouraged.

Landcover is important for examining land use patterns and helping in the prediction of future sustainable land management and environment conservation. This land use patterns shows more turbulence in urban areas where activities like the human influences and deforestation which affects the environment severely, are more frequent. This study takes up one of such area named Ahmedabad district that is situated in Gujarat, India. The land use and land cover (LULC) of Ahmedabad has changed in many ways. In this investigation, LULC variations were identified and measured using remote sensing (RS). These changes have been considered over thirty years of period. The Landsat 7 Enhanced Thematic Mapper (ETM+) and Landsat 8 Operational Land Imager (OLI) images are used as the sources. The supervised classification method using Maximum Likelihood Classification is used to classify LULC types. The study shows that area of built-up land, Fallow land, Shrub land, Water bodies increased by 1.7%,13%,0.8%,0.4% respectively and area of Cropland, Waste-land decreased by 15.6% and 0.1% respectively. The LULC changes in the study area were subjected to urbanization, population growth, social economic growth and climate change. The results clearly shows that the influence of landuse change is not in the favour of environment and vegetation. These variations were ascribed to factors such as urbanization, the population increase, social-economic expansion and environment disbalance.

In recent development, scientists have shown increasing interest in applying geographic information systems (GIS) and satellite-based remote sensing (RS) techniques to the hydrological modelling. T...

The study is conducted on the Hathmati River, which is the principal tributary of the Sabarmati River, one of Gujarat's biggest rivers. Indicators of water quality such organic N, organic P, NO3, NH4, NO2, total N, and total P were compared between the observed values in the watershed and the streamflow models. For monthly streamflow and monthly nitrate during the calibration period of 1999–2012, and for 0.87 and 0.56 for the validation period of 2013–2020, respectively, the Nash–Sutcliffe efficiency was 0.89 and 0.79. The measured water quality data at three locations in the watershed were largely compatible with their corresponding modeled values, while the agreement varied by nutrients. Using the parameters used to forecast the hydrological and water quality responses in the watershed region, the Soil and Water Assessment Tool model faithfully duplicated the hydrological and water quality conditions in this agricultural watershed. The results of the modeling indicated that nutrients are one of the key determinants with regard to the quality of the water, in accordance with the current land use and management practices in the watershed. Management practices should be implemented in order to reduce the nutrient load and meet the watershed's requisite water quality standards.

The researchers and scientists have realized that this is the high time to act in accordance to the impact of change of climate. Because of climate change problem, various effects occur, one of them is hydrological extremes. This leads to the emergence of hot-spots and vulnerable areas causing difficult adaptation. The current analysis intends to estimate the influence of change in climate on the hydrological parameter on one of the most important tributaries of Saurashtra region of Gujarat, Western India. Out of number of methods available to perform this task, simulation (hydrological modelling) which is the most widely used techniques available at this time, has been adopted. Here in this research the SWAT (Soil and Water Assessment Tool) model which happens to be a semi-distributed model and integrates the GIS information with the attribute database of the River has been utilized. The watershed delineation has been done using AWD (Automatic Watershed Delineation) which is available as a plugin in ArcSWAT. It has classified the catchment into 28 subbasins. From Esri Sentinel-2 landuse map has been used and the soil map is extracted from FAO Raster world soil map. Moreover, we can classify the sub basins into 173 HRUs (Hydrological Response Unit) by the model. The weather files from 1982 to 2019 has been used from the global weather source as a seed to the model. The successful run of the model gives elucidate fluctuating runoff volumes over time, spanning from a lowest of 2.56 mm to a extreme of 503.78mm. Notably, the annual average runoff stands at 190.82 mm, representing approximately 28.34% of the cumulative rainfall experienced within the river basin. The estimation of runoff is helpful in allocating water for agriculture, household demands, and industrial requirements.