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        Quantifying energy consumption by groundwater pumping for irrigation in the Netherlands

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        Thesis_Tom_de_Boer_5999529_def.pdf (7.289Mb)
        Publication date
        2024
        Author
        Boer, Tom de
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        Summary
        Groundwater is a vital resource for agricultural production, especially in regions where surface water is limited. However, extracting groundwater is highly energy-intensive, making it a key contributor to energy consumption in the agricultural sector and an important component of the water-energy nexus. Understanding the energy demand for groundwater pumping is essential for developing sustainable water and energy management strategies, particularly in the context of climate change and groundwater depletion. The goal of this study was to quantify the energy consumption for groundwater pumping for irrigation in the Netherlands from 1980 to 2015. Two models were used to achieve this: the GLOBGM v1.0 model to simulate groundwater levels and the PCR-GLOBWB 2.0 model to estimate water withdrawals. Data collection for validation included groundwater level observations, which were used to evaluate the models using the Kling-Gupta Efficiency (KGE) metric. The KGE analysis showed that approximately 68% of the analyzed pixels performed better than a simple mean-flow benchmark, indicating reasonable model performance for general trends. The energy consumption was estimated at an average of 530 MWh per year for 40% pump efficiency. During dry years, the energy demand increased significantly compared to wet or average years, highlighting the strong dependency of energy consumption on annual precipitation patterns. Overall, the results show that observed data provided more reliable estimates, ranging from 0.0004% to 0.002% of the total electricity consumption in the Netherlands, whereas the modelbased approach consistently underestimated the energy use. These findings emphasize the need for integrating high-resolution models and detailed data to enhance accuracy. Future research should focus on refining model parameters and improving data quality to expand this approach to regions with complex hydrogeological settings, contributing to a better understanding of the global water-energy nexus.
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        https://studenttheses.uu.nl/handle/20.500.12932/48072
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