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Record W4411329666 · doi:10.1016/j.watres.2025.124040

Surface-water-irrigation return flow dominates groundwater recharge, groundwater age and nitrate dynamics in an alluvial basin aquifer

2025· article· en· W4411329666 on OpenAlexaff
Mariachiara Caschetto, Elisa Sacchi, Daniele L. Pinti, Carlo Riparbelli, S. Bruno, Chiara Zanotti, Tullia Bonomi, Marco Rotiroti

Bibliographic record

VenueWater Research · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGroundwater and Isotope Geochemistry
Canadian institutionsUniversité du Québec à Montréal
FundersUniversità degli Studi di Milano-BicoccaFondazione Cariplo
KeywordsGroundwater rechargeGroundwaterHydrology (agriculture)AquiferDepression-focused rechargeStructural basinSurface waterGroundwater modelIrrigationGeologyGroundwater flowAlluviumGroundwater dischargeReturn flowEnvironmental scienceFlow (mathematics)GeomorphologyEnvironmental engineeringGeotechnical engineering

Abstract

fetched live from OpenAlex

In agricultural regions where crop water demand is met by surface-water irrigation, excess irrigation water can play a fundamental role in aquifer recharge and contaminant mobilization. Despite much research, the role of surface-water-irrigation return flow in groundwater recharge, flow processes and nitrate pollution is not yet fully understood. It is therefore addressed here using the case of the Po Plain in northern Italy. Tracers of groundwater recharge (stable isotopes in water and Cl/Br ratio), age tracers (CFCs, SF 6 , 3 H- 3 He, noble gases) and long-term average nitrate concentrations measured/calculated from a 64-point monitoring network revealed the dominant role of surface-water-irrigation return flow in recharging the aquifer (median contribution of 64.4% to total recharge in irrigated areas), with effects even on groundwater apparent ages and nitrate concentrations. Regional groundwater flow from north to south gradually mixes with a vertical inflow of younger water from excess irrigation, inducing a renewal effect that rejuvenates groundwater ages and even reverses the typical increasing age trend along a flowpath. The median apparent age of 39 years in areas with no or non-intensive irrigation (i.e., recharge by surface-water-irrigation return flow <60%) decreases to 27 years where intensive irrigation (recharge by surface-water-irrigation return flow >60%) is practiced. At the same time, groundwater nitrate concentration increases progressively with increasing recharge by surface-water-irrigation return flow up to 60%. Then it decreases in intensively irrigated areas with a decrease rate of 7.2 mg/L of nitrate for a 10% increase in recharge by surface-water-irrigation return flow. This decrease in nitrate is due to dilution and flushing promoted by the greater volume of water infiltrating the soil under intensive irrigation. However, under non-intensive irrigation, nitrate leaching from fertilized soils still dominates and causes an increase in groundwater nitrate concentration. These results show that groundwater nitrate concentration is mainly controlled by hydrogeological processes such as dilution and flushing on a short-time scale rather than by reduction of nitrate sources, which can certainly abate nitrate concentrations in groundwater but on a long-time scale. These findings could serve as a valuable reference for other surface-water-irrigated areas worldwide with similar hydrogeological settings, highlighting critical aspects for sustainable management of water resources.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.034
GPT teacher head0.286
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2025
Admission routes1
Has abstractno

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