Basant Yadav

Agriculture accounts for the majority of global freshwater consumption, underscoring the importance of accurate crop water footprint (WF) estimation to ensure sustainable water use and secure food supplies. Given agriculture’s extensive reliance on freshwater resources, precise WF assessments are crucial for effective resource management and policy-making. Variations in crop WF estimates arise across fields, basins, regions, and countries due to differing methodologies, agro-climatic conditions, regional agricultural practices, and data availability. Most studies have focused on estimating only green and blue WF, often overlooking the water quality dimension (grey WF) and the distinctions among the individual footprints (green, blue, and grey). These variations are critical for understanding diverse water uses and their impacts on both water quantity and quality. This study assessed the variation in all three WFs and measures to address this variability under different WF estimation approaches and scales. Five significant WF estimation approaches were considered: field crop water requirement (FCWR), field soil water balance (FSWB), regional water balance (RWB), remote sensing (RS), and field measured water balance (FMWB). The WF variation for wheat, rice, maize, potato, and sugarcane was assessed from 2002 to 2023. The analysis suggests that the FSWB approach has less variability in WF estimation than the FCWR approach, with the coefficient of variation (CV) for rice, wheat, and maize under the FSWB approach being 45.25%, 61.16%, and 86.21%, respectively. RWB and RS approaches show higher accuracy and feasibility at regional, basin, and country scales. The FMWB approach is the most accurate at the field scale and exhibits the lowest variation in WF estimate, with CVs of 32.23% for rice and 24.49% for wheat. Additionally, the FMWB approach can be used to calibrate and validate other large-scale approaches due to its limitation of upscaling and advantage of higher accuracy. A case study was also performed to estimate WF using the FCWR approach for sugarcane and wheat crops in the Hindon River basin in India to assess the variability in WF estimation. The total WF of sugarcane and wheat was 266.93 m³/t and 1506 m³/t, respectively, showing variation as these values are nearly equal to, more than, or less than many national and international studies. This variation could be due to scale, data availability, methodology, agro-climatic conditions, and regional agricultural practices. It is recommended that the effects of scale, data accuracy, and suitability of WF estimation approaches for specific crops be considered when making regional water policies based on WF estimation.Keywords: Water Footprint, Methodology, Scale variability, Crop, Sustainable Agriculture

Nitrogen and water availability are the primary environmental factors limiting crop productivity on a global scale. Nitrogen behaviour in the subsurface is influenced by multiple factors, including continuous wetting, wetting/drying cycles, temperature, system design, and TWW quality, which are often challenging to quantify. This study examined these dynamics using batch adsorption and a laboratory-scale soil aquifer treatment system, simulated in a glass column filled with agricultural soil, to investigate the effects of synthetic ammonium solution under alternating wet and dry cycles. The study focused on ammonium removal and transformation, specifically ammonium and nitrate, under varying wetting and drying phases. Constant-concentration synthetic wastewater was introduced, allowing analysis of how soil water content, pH, dissolved oxygen, and nitrogen concentrations impacted the geochemical properties of the soil medium. Batch adsorption experiments indicated strong alignment with Freundlich and Temkin isotherm models, suggesting heterogeneous adsorption sites and varying affinities. pH-edge experiments further revealed that ammonium adsorption was greater in alkaline conditions, indicating a pH-dependent mechanism. The column experiment continued for 52 days, studying three scenarios: (1) continuous flow, (2) alternate day wetting and drying, and (3) three days of drying followed by one day of wetting. Under drier conditions, increased ammonium transformation and sorption occur due to the formation of anoxic zones. Therefore, in the third scenario, anoxic conditions are formed, leading to a greater reduction in hydraulic conductivity. This study offers valuable insights and a strong scientific basis for the protection and management of groundwater and soil quality in agricultural areas.

Lentic Small Water Bodies (LSWBs), including ponds, lakes, and reservoirs, are crucial for ecological balance,biodiversity, and ecosystem services. However, their seasonal dynamics, nutrient cycling, and the influenceof surrounding land use and landscape patterns are often under-studied. Using integrated machinelearning and remote sensing tools, this study mapped LSWBs across India and analyzed their socioeconomic and environmental impacts in four states. Land use changes, especially urban expansion, causedLWB degradation nationwide. Socioeconomic factors revealed disparities in development and LWBs acrossstates, emphasizing the need for tailored regional management strategies. Strategies proposed includetargeted pollution control in urban areas and incentives for sustainable agricultural practices to reducedetrimental agricultural runoff.Further, to understand the physio-chemical dynamics of LSWBs, this study examined seasonal patterns,vertical stratification, and the trophic level index (TLI) in Haridwar district, northern India. Analysis indicatedthat nutrient concentrations rose at inlets during the monsoon, and Chl-a levels increased near LSWBedges, showing significant seasonal variations. Pre-monsoon, vertical stratification of pH, temperature, andTN was observed but decreased during monsoon mixing. The TLI revealed a shift from oligotrophic (0 to 30)to hypereutrophic (70 to 100) states, mainly due to agricultural runoff. The TN: TP ratio (< 10) suggestsnitrogen limitation drives algal blooms during monsoons, worsening water quality.In conclusion, effective management strategies must address nutrient dynamics, stratification, andeutrophication while considering environmental and socioeconomic factors. Additionally, long-termmonitoring and adaptive management strategies are essential to mitigate ongoing and future challenges.