Universidad del Desarrollo

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Optimization of Water and Land Allocation in Fruit Orchards over a 20-Year Period
(MDPI AG, 2024-12-24)
Luciano Quezada
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Eduardo Holzapfel
;
Mathias Kuschel-Otárola
;
Mario Lillo-Saavedra
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RIVERA SALAZAR, DIEGO ANDRÉS
<jats:p>This study proposes a nonlinear programming model for the optimization of water and land allocation in a 1000 ha orchard over a 20-year period to maximize farmers’ net profits. Different scenarios were evaluated, including equitable and unrestricted land allocation, and the risks associated with fruit production were considered. Additionally, a sensitivity analysis that focused on the variability of labor and water availability was conducted. The results reveal that with equitable land allocations and no constraints on the cultivated area, cherry emerges as the most profitable crop, although there are large risks associated with its price volatility. The introduction of risk and land allocation constraints highlights the importance of crop diversification in mitigating economic risks. A sensitivity analysis indicated that reductions in water and labor availability significantly affect the optimal cropping pattern of an orchard, suggesting that the efficient and adaptive management of resources is required. The proposed optimal cropping pattern maintains the economic viability of the orchard even with 70% and 24% reductions in water and labor, respectively. This approach underscores the importance of implementing resilient and sustainable agricultural strategies to ensure food security and increase economic stability in the face of changing climatic and labor conditions.</jats:p>
Scopus© Citations 5 2
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Decadal Variability of Dry Days in Central Chile
(2024)
Daniela Latoja
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Mario Lillo-Saavedra
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Consuelo Gonzalo-Martin
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GODOY FAUNDEZ, ALEX ORIEL
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Marcelo Somos-Valenzuela
<jats:title>Abstract</jats:title><jats:p>Dry days are crucial in precipitation variability and water scarcity, particularly in Mediterranean regions facing increasing aridity. Despite their importance, most research focuses on precipitation amounts and temporal dynamics. This study addresses this gap by analyzing dry days’ temporal and spatial variability in central Chile (32–40 S), a region experiencing prolonged drought. We examined dry day patterns from 1960 to 2021 using high-resolution gridded precipitation data, defining dry days with five precipitation thresholds (0.10, 1, 2.5, 5, and 10 mm/day). Principal component and trend analyses were employed to characterize spatial and temporal variability. Results reveal a spatial pattern of dry days closely following precipitation patterns, with more dry days in northern and coastal areas. The first principal component explains 70–80% of the variance, and clustering methods allowed the definition of five homogeneous regions with distinct monthly dry-day characteristics. Long-term trends show a significant increase in annual dry days south of 38°S, while trends are weaker and non-significant further north. Notably, trend direction is highly sensitive to the analysis period, with some regions showing opposing trends before and after 1982. The 2010–2019 megadrought is detectable in decadal anomalies. We found links between dry day anomalies and large-scale climate patterns, suggesting modulation by changes in subtropical and extratropical atmospheric circulation. This comprehensive characterization of dry day climatology and variability provides crucial insights for water resource management and climate change adaptation in central Chile and similar Mediterranean regions worldwide. Our findings highlight the importance of considering dry day frequency in drought assessment and water planning, contributing to a more nuanced understanding of precipitation patterns in Mediterranean climates.</jats:p>
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A satellite-based ex post analysis of water management in a blueberry orchard
(2020)
Eduardo Holzapfel
;
Mario Lillo-Saavedra
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RIVERA SALAZAR, DIEGO ANDRÉS
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Viviana Gavilán
;
Angel García-Pedrero
1Scopus© Citations 6 2
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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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