Modeling farmer responses to reservoir operation policies using agent based analysis of risk behavior and irrigation adoption

Abstract Understanding farmers’ responses to reservoir operation policies is crucial for water resources management. This study employs an Agent-Based model with established socio-hydrological rules to simulate farmers’ decision-making. Operator agents utilize either the Standard Operation Policy (S...

Full description

Saved in:
Bibliographic Details
Main Authors: Ehsan Ebrahimi, Mojtaba Shourian
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Online Access:https://doi.org/10.1038/s41598-025-11908-9
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849387880900722688
author Ehsan Ebrahimi
Mojtaba Shourian
author_facet Ehsan Ebrahimi
Mojtaba Shourian
author_sort Ehsan Ebrahimi
collection DOAJ
description Abstract Understanding farmers’ responses to reservoir operation policies is crucial for water resources management. This study employs an Agent-Based model with established socio-hydrological rules to simulate farmers’ decision-making. Operator agents utilize either the Standard Operation Policy (SOP), a hedging rule (strategies to balance water shortages over time), or a dynamic informed hedging rule for reservoir operation. Farmer agents annually decide on land cultivation and the potential adoption of modern irrigation systems based on socioeconomic characteristics and water availability. The study focuses on Iran’s Borkhar Plain, modeling operator and farmer agents within MODSIM, a decision-support system used for water allocation and reservoir operations. Results indicate that high-risk-taking farmers tend to cultivate more land, particularly under SOP averaging 69.6%, while under the hedging rule, farmers’ decisions became more predictable, with reduced land use averaging 63.6% and retaining profitability. The dynamic informed hedging rule scheme, however, resulted in the most synchronized farmer behavior, with land use decreasing further to 54% without a significant decrease in profitability. Adoption of modern irrigation systems was significantly influenced by education levels and risk-taking behavior. Adoption rates increased across policies, from 37.5% under SOP to 45.83% under the hedging rule, and peaked at 62.5% under the informed hedging rule scheme.
format Article
id doaj-art-ebc40e097f484f18918c4656a1250c28
institution Kabale University
issn 2045-2322
language English
publishDate 2025-07-01
publisher Nature Portfolio
record_format Article
series Scientific Reports
spelling doaj-art-ebc40e097f484f18918c4656a1250c282025-08-20T03:42:28ZengNature PortfolioScientific Reports2045-23222025-07-0115111810.1038/s41598-025-11908-9Modeling farmer responses to reservoir operation policies using agent based analysis of risk behavior and irrigation adoptionEhsan Ebrahimi0Mojtaba Shourian1Department of Civil and Environmental Engineering, Utah Water Research Laboratory, Utah State UniversityFaculty of Civil, Water and Environmental Engineering, Shahid Beheshti UniversityAbstract Understanding farmers’ responses to reservoir operation policies is crucial for water resources management. This study employs an Agent-Based model with established socio-hydrological rules to simulate farmers’ decision-making. Operator agents utilize either the Standard Operation Policy (SOP), a hedging rule (strategies to balance water shortages over time), or a dynamic informed hedging rule for reservoir operation. Farmer agents annually decide on land cultivation and the potential adoption of modern irrigation systems based on socioeconomic characteristics and water availability. The study focuses on Iran’s Borkhar Plain, modeling operator and farmer agents within MODSIM, a decision-support system used for water allocation and reservoir operations. Results indicate that high-risk-taking farmers tend to cultivate more land, particularly under SOP averaging 69.6%, while under the hedging rule, farmers’ decisions became more predictable, with reduced land use averaging 63.6% and retaining profitability. The dynamic informed hedging rule scheme, however, resulted in the most synchronized farmer behavior, with land use decreasing further to 54% without a significant decrease in profitability. Adoption of modern irrigation systems was significantly influenced by education levels and risk-taking behavior. Adoption rates increased across policies, from 37.5% under SOP to 45.83% under the hedging rule, and peaked at 62.5% under the informed hedging rule scheme.https://doi.org/10.1038/s41598-025-11908-9Reservoir operationSOPHedgingWater allocationAgent-Based modeling
spellingShingle Ehsan Ebrahimi
Mojtaba Shourian
Modeling farmer responses to reservoir operation policies using agent based analysis of risk behavior and irrigation adoption
Scientific Reports
Reservoir operation
SOP
Hedging
Water allocation
Agent-Based modeling
title Modeling farmer responses to reservoir operation policies using agent based analysis of risk behavior and irrigation adoption
title_full Modeling farmer responses to reservoir operation policies using agent based analysis of risk behavior and irrigation adoption
title_fullStr Modeling farmer responses to reservoir operation policies using agent based analysis of risk behavior and irrigation adoption
title_full_unstemmed Modeling farmer responses to reservoir operation policies using agent based analysis of risk behavior and irrigation adoption
title_short Modeling farmer responses to reservoir operation policies using agent based analysis of risk behavior and irrigation adoption
title_sort modeling farmer responses to reservoir operation policies using agent based analysis of risk behavior and irrigation adoption
topic Reservoir operation
SOP
Hedging
Water allocation
Agent-Based modeling
url https://doi.org/10.1038/s41598-025-11908-9
work_keys_str_mv AT ehsanebrahimi modelingfarmerresponsestoreservoiroperationpoliciesusingagentbasedanalysisofriskbehaviorandirrigationadoption
AT mojtabashourian modelingfarmerresponsestoreservoiroperationpoliciesusingagentbasedanalysisofriskbehaviorandirrigationadoption