Inference of hydrological modelling and field-based monitoring on dynamics of heavy metals in water of Hindon Basin

Study region: The Hindon basin, crucial for agriculture, faces pollution from industry and farming, affecting the water quality and ecosystems. Study focus: This research unravels heavy metal dynamics in uncertain pathways, varying hydrological conditions, and data-restricted basins by integrating a...

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Main Authors: Prabhat Dwivedi, Brijesh Kumar Yadav
Format: Article
Language:English
Published: Elsevier 2025-08-01
Series:Journal of Hydrology: Regional Studies
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2214581825003131
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author Prabhat Dwivedi
Brijesh Kumar Yadav
author_facet Prabhat Dwivedi
Brijesh Kumar Yadav
author_sort Prabhat Dwivedi
collection DOAJ
description Study region: The Hindon basin, crucial for agriculture, faces pollution from industry and farming, affecting the water quality and ecosystems. Study focus: This research unravels heavy metal dynamics in uncertain pathways, varying hydrological conditions, and data-restricted basins by integrating a hydrological model with heavy metal mass budgeting. Initially, spatiotemporal meteorological data and landscape properties were utilized to develop a monthly-scale hydrological model for 12 years (2010–2022). Subsequently, heavy metal concentrations were measured in 2023 from rivers, canals, and wastewater drains across the basin. The river flows predicted by the hydrological model were then used to estimate seasonal heavy metal loads based on observed concentrations. New hydrological insights: The hydrological activity in the region displayed drier conditions from 2010 to 2023, with declining post-monsoon water balance components in the lower and middle regions. However, in 2023, enhanced monsoon rainfall reversed this trend, improving surface water availability, increasing flow rates, and altering heavy metal dynamics during the post-monsoon season. This shift underscores the role of hydrological uncertainty in heavy metal loads across all surface water bodies. River water contributed the largest share of heavy metal loads (52 %) in both seasons, followed by wastewater (26 %) and canal water (22 %). These findings emphasize the influence of changing hydrological conditions on heavy metal contributions from surface water sources, reducing reliance on direct flow measurements in challenging field environments.
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spelling doaj-art-2f8612e4b98342e5baa0f1869713bb202025-08-20T02:48:34ZengElsevierJournal of Hydrology: Regional Studies2214-58182025-08-016010248810.1016/j.ejrh.2025.102488Inference of hydrological modelling and field-based monitoring on dynamics of heavy metals in water of Hindon BasinPrabhat Dwivedi0Brijesh Kumar Yadav1Department of Hydrology, Indian Institute of Technology Roorkee, Roorkee 247667, IndiaCorresponding author.; Department of Hydrology, Indian Institute of Technology Roorkee, Roorkee 247667, IndiaStudy region: The Hindon basin, crucial for agriculture, faces pollution from industry and farming, affecting the water quality and ecosystems. Study focus: This research unravels heavy metal dynamics in uncertain pathways, varying hydrological conditions, and data-restricted basins by integrating a hydrological model with heavy metal mass budgeting. Initially, spatiotemporal meteorological data and landscape properties were utilized to develop a monthly-scale hydrological model for 12 years (2010–2022). Subsequently, heavy metal concentrations were measured in 2023 from rivers, canals, and wastewater drains across the basin. The river flows predicted by the hydrological model were then used to estimate seasonal heavy metal loads based on observed concentrations. New hydrological insights: The hydrological activity in the region displayed drier conditions from 2010 to 2023, with declining post-monsoon water balance components in the lower and middle regions. However, in 2023, enhanced monsoon rainfall reversed this trend, improving surface water availability, increasing flow rates, and altering heavy metal dynamics during the post-monsoon season. This shift underscores the role of hydrological uncertainty in heavy metal loads across all surface water bodies. River water contributed the largest share of heavy metal loads (52 %) in both seasons, followed by wastewater (26 %) and canal water (22 %). These findings emphasize the influence of changing hydrological conditions on heavy metal contributions from surface water sources, reducing reliance on direct flow measurements in challenging field environments.http://www.sciencedirect.com/science/article/pii/S2214581825003131Hydrological modelSurface waterRiver flowsHeavy metal loadHeavy metal dynamicsHindon basin
spellingShingle Prabhat Dwivedi
Brijesh Kumar Yadav
Inference of hydrological modelling and field-based monitoring on dynamics of heavy metals in water of Hindon Basin
Journal of Hydrology: Regional Studies
Hydrological model
Surface water
River flows
Heavy metal load
Heavy metal dynamics
Hindon basin
title Inference of hydrological modelling and field-based monitoring on dynamics of heavy metals in water of Hindon Basin
title_full Inference of hydrological modelling and field-based monitoring on dynamics of heavy metals in water of Hindon Basin
title_fullStr Inference of hydrological modelling and field-based monitoring on dynamics of heavy metals in water of Hindon Basin
title_full_unstemmed Inference of hydrological modelling and field-based monitoring on dynamics of heavy metals in water of Hindon Basin
title_short Inference of hydrological modelling and field-based monitoring on dynamics of heavy metals in water of Hindon Basin
title_sort inference of hydrological modelling and field based monitoring on dynamics of heavy metals in water of hindon basin
topic Hydrological model
Surface water
River flows
Heavy metal load
Heavy metal dynamics
Hindon basin
url http://www.sciencedirect.com/science/article/pii/S2214581825003131
work_keys_str_mv AT prabhatdwivedi inferenceofhydrologicalmodellingandfieldbasedmonitoringondynamicsofheavymetalsinwaterofhindonbasin
AT brijeshkumaryadav inferenceofhydrologicalmodellingandfieldbasedmonitoringondynamicsofheavymetalsinwaterofhindonbasin