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Agent-Based Modeling for Identifying Water Conflicts in Farmer Water User Organizations: A Socio-Hydrological Approach
(ACM, 2024-11-11)
Mario Lillo Saavedra
;
Pablo Velásquez
;
Marcela Salgado
;
Ángel García-Pedrero
;
Consuelo Gonzalo-Martín
3
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Socio-Hydrological Agent-Based Modeling as a Framework for Analyzing Conflicts Within Water User Organizations
(2024)
Mario Lillo-Saavedra
;
Pablo Velásquez-Cisterna
;
Ángel García-Pedrero
;
Marcela Salgado-Vargas
;
RIVERA SALAZAR, DIEGO ANDRÉS
Water resource management in agriculture faces complex challenges due to increasing scarcity, exacerbated by climate change, and the intensification of conflicts among various user groups. This study addresses the issue of predicting and managing these conflicts in the Longaví River Basin, Chile, by considering the intricate interactions between hydrological, social, and economic factors. A socio-hydrological agent-based model (SHABM) was developed, integrating hydrological, economic, and behavioral data. The methodology combined fieldwork with computational modeling, characterizing three types of agents (selfish, neutral, and cooperative) and simulating scenarios with varying levels of water availability and oversight across three water user organizations (WUOs). The key findings revealed that (1) selfish agents are more likely to disregard irrigation schedules under conditions of scarcity and low supervision; (2) high supervision (90%) significantly reduces conflicts; (3) water scarcity exacerbates non-cooperative behaviors; (4) high-risk conflict areas can be identified; and (5) behavioral patterns stabilize after the third year of simulation. This work demonstrates the potential of SHABM as a decision-making tool in water management, enabling the proactive identification of conflict-prone areas and the evaluation of management strategies.
7Scopus© Citations 5
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A satellite-based ex post analysis of water management in a blueberry orchard
(2020)
Eduardo Holzapfel
;
Mario Lillo-Saavedra
;
RIVERA SALAZAR, DIEGO ANDRÉS
;
Viviana Gavilán
;
Angel García-Pedrero
1Scopus© Citations 6 2
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Early Estimation of Tomato Yield by Decision Tree Ensembles
(2022)
Mario Lillo-Saavedra
;
Alberto Espinoza-Salgado
;
Angel García-Pedrero
;
Camilo Souto
;
Eduardo Holzapfel
Crop yield forecasting allows farmers to make decisions in advance to improve farm management and logistics during and after harvest. In this sense, crop yield potential maps are an asset for farmers making decisions about farm management and planning. Although scientific efforts have been made to determine crop yields from in situ information and through remote sensing, most studies are limited to evaluating data from a single date just before harvest. This has a direct negative impact on the quality and predictability of these estimates, especially for logistics. This study proposes a methodology for the early prediction of tomato yield using decision tree ensembles, vegetation spectral indices, and shape factors from images captured by multispectral sensors on board an unmanned aerial vehicle (UAV) during different phenological stages of crop development. With the predictive model developed and based on the collection of training characteristics for 6 weeks before harvest, the tomato yield was estimated for a 0.4 ha plot, obtaining an error rate of 9.28%.
1Scopus© Citations 8 1
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Legal disputes as a proxy for regional conflicts over water rights in Chile
(2016)
Diego Rivera Salazar
;
GODOY FAUNDEZ, ALEX ORIEL
;
Mario Lillo
;
Amaya Alvez
;
Verónica Delgado
1Scopus© Citations 64 1
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Ex Post Analysis of Water Supply Demand in an Agricultural Basin by Multi-Source Data Integration
(2021)
Mario Lillo-Saavedra
;
Viviana Gavilán
;
Angel García-Pedrero
;
Consuelo Gonzalo-Martín
;
Felipe de la Hoz
In this work, we present a new methodology integrating data from multiple sources, such as observations from the Landsat-8 (L8) and Sentinel-2 (S2) satellites, with information gathered in field campaigns and information derived from different public databases, in order to characterize the water demand of crops (potential and estimated) in a spatially and temporally distributed manner. This methodology is applied to a case study corresponding to the basin of the Longaví River, located in south-central Chile. Potential and estimated demands, aggregated at different spatio-temporal scales, are compared to the streamflow of the Longaví River, as well as extractions from the groundwater system. The results obtained allow us to conclude that the availability of spatio-temporal information on the water availability and demand pairing allows us to close the water gap—i.e., the difference between supply and demand—allowing for better management of water resources in a watershed.
1Scopus© Citations 5 2

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