Eficiencia en el uso del agua: uso en conjunto del análisis de ciclo de vida y optimización multiperíodo.

dc.contributor.advisorRivera Salazar, Diegoes
dc.contributor.advisorHolzapfel Hoces, Eduardoes
dc.contributor.authorKuschel Otarola, Mathias Nicholases
dc.date.accessioned2020-10-27T01:45:55Z
dc.date.accessioned2024-05-13T17:20:26Z
dc.date.accessioned2024-08-29T18:33:30Z
dc.date.available2020-10-27T01:45:55Z
dc.date.available2024-05-13T17:20:26Z
dc.date.available2024-08-29T18:33:30Z
dc.date.issued2019
dc.descriptionTesis presentada para optar al grado de Doctor en Ingeniería Agrícola con mención en Recursos Hídricos en la Agriculturaes
dc.description.abstractWith the need to feed an increasing population, the worldwide irrigated area should increase in 30 M ha demanding 40% more water and energy for the next 20 years. Agriculture, however, has contributed to water scarcity. Among different proposed solutions, optimisation has includedin this thesis, which aims to assign resources among competitive activities, subject to some restrictions and solved through mathematical algorithms. A key part of the optimisation model is a crop production function, which relates the yield reduction as a result of the relative loss in evapotranspiration. In the literature, most of the researches are based at a seasonal timescale, i.e., they do not account for intraseasonal changes. Therefore, the motivation was to develop in Chapter 1, a monthly crop yield function based on crop features (yield response factor for each growth stage and its duration in days) and sowing dates. This approach presented low values of RMSE and RD (below to 0.03 and 6.75%, respectively) when was compared to the daily approach proposed by Raes et al. (2006). Once the monthly crop yield function was developed, it was included in a monthly optimisation model to obtain an optimum cropping pattern and monthly water allocation for irrigated agriculture to obtain maximum profits (Chapter 2). The model included improvements in water resource management such as water storage and water transactions, being the latter a monthly decision variable that can increase farmer’s profits. Results showed that the model not only attains higher profits but also decreases uncertainty and improves risk management. With respect to the monthly crop yield function developed in Chapter 1, the yield response factors proposed by Doorenbos and Kassam (1979) and FAO (2017), are not specific for a particular soil type or management. Therefore in Chapter 3 was included AquaCrop-OS (Foster et al., 2017), an open source code version of AquaCrop (Steduto et al., 2009) which was written in MATLAB. AquaCrop simulates attainable yields of crops as a function of water consumption under rainfed, supplemental, deficit and full irrigation conditions and has been used to determine accurately crop yield in some crops. The objective was to estimate the yield response factor (slope of the crop yield function) under local conditions for a given crop, soil, weather, sowing date and management and for each growth stage which depends on the growing degree days (GDD) instead of days. Results showed that there was a good agreement in the proposed methodology (over 85% of the results for each crop presented NRMSE values below to 20%).en
dc.description.campusChillánes
dc.description.departamentoDepartamento de Recursos Hídricoses
dc.description.facultadFacultad de Ingeniería Agrícolaes
dc.identifier.urihttps://repositorio.udec.cl/handle/11594/953
dc.language.isoeses
dc.publisherUniversidad de Concepciónes
dc.rightsCC BY-NC-ND 4.0 DEED Attribution-NonCommercial-NoDerivs 4.0 Internationalen
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectEficiencia del Uso del Aguaes
dc.subjectEficiencia del Riegoes
dc.subjectAgua de Riegoes
dc.subjectOptimización - Matemáticaes
dc.subjectAgua Limpia y Saneamientoes
dc.titleEficiencia en el uso del agua: uso en conjunto del análisis de ciclo de vida y optimización multiperíodo.es
dc.title.alternativeWater use efficiency: Joint use of life cycle assessment and multiperiod optimisation.en
dc.typeTesises

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