An Extensive Review of Leaching Models for the Forecasting and Integrated Management of Surface and Groundwater Quality

The present study reviews leachate models useful for proactive and rehab actions to safeguard surface and subsurface soft water, which have become even more scarce. Integrated management plans of water basins are of crucial importance since intensively cultivated areas are adding huge quantities of fertilizers to the soil, affecting surface water basins and groundwater. Aquifers are progressively being nitrified on account of the nitrogen-based fertilizer surplus, rendering water for human consumption not potable. Well-tested solute leaching models, standalone or part of a model package, provide rapid site-specific estimates of the leaching potential of chemical agents, mostly nitrates, below the root zone of crops and the impact of leaching toward groundwater. Most of the models examined were process-based or conceptual approaches. Nonetheless, empirical prediction models, though rather simplistic and therefore not preferrable, demonstrate certain advantages, such as less demanding extensive calibration database information requirements, which in many cases are unavailable, not to mention a stochastic approach and the involvement of artificial intelligence (AI). Models were categorized according to the porous medium and agents to be monitored. Integrated packages of nutrient models are irreplaceable elements for extensive catchments to monitor the terrestrial nitrogen-balanced cycle and to contribute to policy making as regards soft water management.

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Publication Details

Journal
Water
Published
2024-11-21
DOI
https://doi.org/10.3390/w16233348
Citations
9
Primary Topic
Hydrology and Watershed Management Studies
Type
article
Field-Weighted Citation Impact
1.81
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article

An Extensive Review of Leaching Models for the Forecasting and Integrated Management of Surface and Groundwater Quality

Christina G. Siontorou, D.K. Sidiras, Stephanos D. V. Giakoumatos
9 citations
Water
Hydrology and Watershed Management Studies
1.81
article

An Extensive Review of Leaching Models for the Forecasting and Integrated Management of Surface and Groundwater Quality

Christina G. Siontorou, D.K. Sidiras, Stephanos D. V. Giakoumatos
article en
9 citations

Abstract

The present study reviews leachate models useful for proactive and rehab actions to safeguard surface and subsurface soft water, which have become even more scarce. Integrated management plans of water basins are of crucial importance since intensively cultivated areas are adding huge quantities of fertilizers to the soil, affecting surface water basins and groundwater. Aquifers are progressively being nitrified on account of the nitrogen-based fertilizer surplus, rendering water for human consumption not potable. Well-tested solute leaching models, standalone or part of a model package, provide rapid site-specific estimates of the leaching potential of chemical agents, mostly nitrates, below the root zone of crops and the impact of leaching toward groundwater. Most of the models examined were process-based or conceptual approaches. Nonetheless, empirical prediction models, though rather simplistic and therefore not preferrable, demonstrate certain advantages, such as less demanding extensive calibration database information requirements, which in many cases are unavailable, not to mention a stochastic approach and the involvement of artificial intelligence (AI). Models were categorized according to the porous medium and agents to be monitored. Integrated packages of nutrient models are irreplaceable elements for extensive catchments to monitor the terrestrial nitrogen-balanced cycle and to contribute to policy making as regards soft water management.

WaterVol. 16(23)
University of Piraeus (GR)
Clean water and sanitation
Openalex Percentile: Top 16%
Hydrology and Watershed Management Studies
1.81
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An Extensive Review of Leaching Models for the Forecasting and Integrated Management of Surface and Groundwater Quality — Christina G. Siontorou, D.K. Sidiras, et al. · Water (2024) | TGRS Research Map | TGRS