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Author: search.filters.author.Gupta, NiteshStart date: 2025

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    Drought vulnerability assessment using morphometric features and extreme precipitation indicators to prioritize sub-basins: AI-based Fuzzy Logic approach
    (2026-03-01)
    Nigam, Utkarsh
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    Patel, Vinodkumar M.
    ;
    Patel, Dhruvesh P.
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    Jodhani, Keval H.
    ;
    Gupta, Nitesh
    The identification of watersheds and extraction of drainage networks are essential for effective hydrological and geomorphological modelling. This study investigates the influence of morphometric factors and extreme precipitation events on the hydrological responses of the Sabarmati River Basin (SRB), India, to identify the drought-vulnerable sub-basins. Watershed prioritization was carried out using satellite remote sensing, GIS, and secondary data, including topographic sheets and ASTER DEM with a spatial resolution of 90 m. The SRB was divided into nine sub-watersheds, and 28 morphometric parameters were evaluated, comprising 07 linear, 15 areal, and 06 relief parameters. A compound factor (CF) was derived using multi-criteria decision-making techniques such as Weighted Sum Analysis (WSA), Principal Component Analysis (PCA), Analytic Hierarchy Process (AHP), Fuzzy-AHP (FAHP), and TOPSIS. Sub-watersheds were ranked based on CF value, where a lower CF indicated higher priority for runoff management strategies. Additionally, 42 years of precipitation data were analysed using the Standardized Precipitation Index (SPI) at timescales ranging from 3 to 24 months to assess trends in drought and extreme precipitation events. The analysis indicate decline in runoff potential in several sub-basins, however others (e.g., SB2, SB3, SB4, SB5) exhibit positive precipitation trends, making them suitable for runoff enhancement. This integrated methodology offers a comprehensive framework for managing sub-basins, optimizing runoff potential, and supporting sustainable water conservation. The results provide actionable insights for policymakers and planners to better utilize the SRB water resources based on its geomorphological and climatic characteristics.
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    Sustainable groundwater management through water quality index and geochemical insights in Valsad India
    (2025-12-01)
    Jodhani, Keval H.
    ;
    Gupta, Nitesh
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    Dadia, Sanidhya
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    Patel, Harsh
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    Patel, Dhruvesh
    Groundwater quality assessment is crucial for sustainable water resource management and public health protection. This study evaluated the Water Quality Index (WQI) of groundwater in the southern part of Gujarat focusing on the Valsad District. Groundwater in this region occurs in porous, unconsolidated formations and fracture formations, both under groundwater table conditions and confined aquifers. Various parameters including Nitrate (NO<inf>3</inf>¯), pH, Calcium (Ca<sup>2+</sup>), Electrical Conductivity (EC), Total Hardness (TH), Magnesium (Mg<sup>2+</sup>), Total Dissolved Solids (TDS), Potassium (K<sup>+</sup>), Sodium (Na<sup>+</sup>), Sulphate (SO<inf>4</inf><sup>2−</sup>), Chloride (Cl¯), Bicarbonate (HCO<inf>3</inf>¯), Silicate (SiO<inf>4</inf><sup>4−</sup>), and Fluoride (F¯) were analyzed to assess groundwater quality. Results indicate that most of the parameters fell within acceptable permissible limits for drinking water, except for Muli and Nanaponda villages with the parameters Cl¯, EC, and TDS exceeding the permissible limit. The WQI analysis revealed that 31.25% of water samples from different villages were found in the excellent category (WQI < 25). About 68.75% of samples from 16 villages were classified as good quality category (WQI ∼ 25–50). Overall, the WQI ranged from 14.20 to 41.98, suggesting that groundwater in the Valsad district is suitable for drinking. The Piper diagram analysis of water samples collected from the field indicated unique geochemical compositions and good water. The diagram revealed that the Ca<sup>2+</sup> was the predominant cation, followed by K<sup>+</sup>, Na<sup>+</sup>, and Mg<sup>2+</sup>. Among the anions, the HCO<inf>3</inf><sup>−</sup> showed the highest concentrations, followed by SO<inf>4</inf><sup>2−</sup>, NO<inf>3</inf><sup>−</sup>, and Cl<sup>−</sup>. This dominance pattern demonstrated that the weathering of minerals significantly influenced the groundwater. This study recommends remediation for areas with reduced water quality to address geogenic and anthropogenic contamination.