Quantifying and valuing irrigation in energy and water limited agroecosystems

IF 3.1 Q2 GEOSCIENCES, MULTIDISCIPLINARY
Mehmet Evren Soylu , Rafael L. Bras
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引用次数: 0

Abstract

Agriculture in regions with limited water availability is possible because of irrigation. Irrigated croplands are expanding, and irrigation water demand is increasing. Nevertheless, there is a limited understanding of how much water is consumed for irrigation and how effective irrigation increases crop productivity in various climates. In this study, we aim to understand how irrigation water affects crop productivity in different climates. To achieve this goal, we developed a simple approach to quantify irrigation quantities from SMAP satellite soil moisture observations based on a zero-dimensional bucket-type hydrology model. The central assumption is that irrigation quantities can be estimated from the gap between the modeled and observed soil moisture by iteratively providing irrigation as a model input until the soil moisture simulations agree well with the observations. We then used the estimated amount of irrigation to simulate water, energy, and carbon fluxes at two agricultural sites on the west coast of the US: one that was water-limited (Central Valley, CA) and one that was energy-limited (Eugene, OR). An agroecosystem model, AgroIBIS-VSF, was used to conduct simulations. To verify our simulations, we used data from two AmeriFlux Eddy covariance towers at each site. We found that incorporating estimated irrigation amounts into our simulations improved the accuracy of energy balance components and soil moisture predictions, reducing the root-mean-square error of soil moisture predictions by up to 22%. We also discovered that the irrigation value, in terms of increased productivity of actual irrigation water used, is more than five times more valuable at the energy-limited site than at the water-limited site. Soil hydraulic properties have a strong influence on irrigation water valuation. Our study highlights the potential of satellite soil moisture observations to improve our understanding of water productivity in different climates. By better understanding the efficiency of resources used for crop production, we can ensure the sustainability and resilience of agricultural systems, leading to better management practices.

对能源和水资源有限的农业生态系统中的灌溉进行量化和估价
有了灌溉,才有可能在水资源有限的地区进行农业生产。灌溉农田不断扩大,灌溉用水需求也在增加。然而,人们对不同气候条件下灌溉耗水量以及灌溉如何有效提高作物产量的了解还很有限。本研究旨在了解灌溉用水如何影响不同气候条件下的作物生产力。为实现这一目标,我们开发了一种简单的方法,基于零维水桶型水文模型,从 SMAP 卫星土壤水分观测数据中量化灌溉量。其核心假设是,可以根据模型和观测土壤水分之间的差距估算灌溉量,方法是反复提供灌溉作为模型输入,直到土壤水分模拟与观测结果完全一致。然后,我们利用估算的灌溉量来模拟美国西海岸两个农业区的水、能量和碳通量:一个是限水区(加利福尼亚州中央山谷),另一个是限能区(俄勒冈州尤金)。我们使用农业生态系统模型 AgroIBIS-VSF 进行了模拟。为了验证模拟结果,我们在每个地点使用了两个 AmeriFlux 涡协方差塔的数据。我们发现,将估算的灌溉量纳入模拟可提高能量平衡成分和土壤水分预测的准确性,使土壤水分预测的均方根误差减少达 22%。我们还发现,就实际灌溉用水所提高的生产率而言,限能区的灌溉价值是限水区的五倍以上。土壤水力特性对灌溉水价值有很大影响。我们的研究强调了卫星土壤水分观测在提高我们对不同气候条件下水生产率的认识方面所具有的潜力。通过更好地了解用于作物生产的资源的效率,我们可以确保农业系统的可持续性和恢复力,从而改进管理方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Hydrology X
Journal of Hydrology X Environmental Science-Water Science and Technology
CiteScore
7.00
自引率
2.50%
发文量
20
审稿时长
25 weeks
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