A new vector-based framework combining AquaCrop, CROPWAT, WEAP, and multi-objective programming for optimizing crop allocation under water scarcity

Effective crop land-use allocation requires evaluating both the potential of land units and the demand for various crops to identify optimal strategies. This paper presents a new vector-based framework that combines AquaCrop for crop-water requirement estimation, CROPWAT for reference evapotranspiration, GAMS for multi-objective optimization, and WEAP for basin-level water allocation. The model operates directly on agricultural-plot polygons to enable spatially explicit optimization that balances agricultural income and production costs. The model’s plausibility for real-world planning was validated by comparing simulated cultivated areas against official statistics, showing a close agreement with a total difference of only 0.2%. Application of the framework to the water-scarce Borkhar & Meymeh district in Isfahan Province, Iran, uncovered a severe baseline water deficit where a substantial portion of the crop water requirements remained unmet. To address this, the model evaluated management scenarios and identified that a 45% reduction in total cultivation area—when spatially optimized alongside crop suitability—could be effective. This strategy significantly improved system performance by reducing the unmet water requirement from 45.8% in the baseline to 26.5% in the most restrictive scenario. Overall, this spatial optimization resulted in a 19.3% improvement in system-wide water reliability compared to existing conditions. The proposed model provides a robust decision-support framework for improving agricultural productivity and designing adaptive management strategies in water-scarce regions.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-04-17
DOI
https://doi.org/10.1038/s41598-026-44171-7
Primary Topic
Climate change impacts on agriculture
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A new vector-based framework combining AquaCrop, CROPWAT, WEAP, and multi-objective programming for optimizing crop allocation under water scarcity

Parastoo Pilehforooshha, Mohammad Ahmadlou, Mohammad Karimi, Mohsen Mousavi et al.
Scientific Reports
Climate change impacts on agriculture
article

A new vector-based framework combining AquaCrop, CROPWAT, WEAP, and multi-objective programming for optimizing crop allocation under water scarcity

Parastoo Pilehforooshha, Mohammad Ahmadlou, Mohammad Karimi, Mohsen Mousavi, Bahman Farhadi-Bansouleh
article en

Abstract

Effective crop land-use allocation requires evaluating both the potential of land units and the demand for various crops to identify optimal strategies. This paper presents a new vector-based framework that combines AquaCrop for crop-water requirement estimation, CROPWAT for reference evapotranspiration, GAMS for multi-objective optimization, and WEAP for basin-level water allocation. The model operates directly on agricultural-plot polygons to enable spatially explicit optimization that balances agricultural income and production costs. The model’s plausibility for real-world planning was validated by comparing simulated cultivated areas against official statistics, showing a close agreement with a total difference of only 0.2%. Application of the framework to the water-scarce Borkhar & Meymeh district in Isfahan Province, Iran, uncovered a severe baseline water deficit where a substantial portion of the crop water requirements remained unmet. To address this, the model evaluated management scenarios and identified that a 45% reduction in total cultivation area—when spatially optimized alongside crop suitability—could be effective. This strategy significantly improved system performance by reducing the unmet water requirement from 45.8% in the baseline to 26.5% in the most restrictive scenario. Overall, this spatial optimization resulted in a 19.3% improvement in system-wide water reliability compared to existing conditions. The proposed model provides a robust decision-support framework for improving agricultural productivity and designing adaptive management strategies in water-scarce regions.

Scientific Reports
Razi University (IR), Duy Tan University (VN), K. N. Toosi University of Technology (IR)
Zero hunger
Openalex Percentile: Top 4%
Climate change impacts on agriculture
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.