High-resolution model for estimating the economic and policy implications of agricultural soil salinization in California
High-resolution model for estimating the economic and policy implications of agricultural soil salinization in California
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DOI：
10.1088/1748-9326/aa848e
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发表时间：
2017-09-01
影响因子：
6.7
通讯作者：
Mauter, Meagan S.
中科院分区：
文献类型：
--
作者：
Welle, Paul D.;Mauter, Meagan S.
这项工作介绍了一种估算土壤盐碱化造成的农田尺度农业产量损失的通用方法。当与作物产量和价格的区域数据结合在一起时，该模型提供了对大片农业区收入损失的高分辨率估计。这些方法解释了来自卫星的模型输入、实验场数据和解释的模型结果所固有的不确定性。应用该方法估算了土壤盐分对加州农业产出的影响，并利用高分辨率(即田间尺度)和低分辨率(即县域尺度)数据源进行了分析，以突出空间分辨率在农业分析中的重要性。我们估计，土壤盐碱化导致2014年农业收入减少37亿美元(17亿至70亿美元)，相当于土壤盐碱度低于作物特定阈值造成800万吨产量损失。当使用低分辨率数据源时，我们发现盐碱化的成本被低估了三倍。这些结果突出了在农业环境评估中对高分辨率数据的需要以及与整合这些数据相关的挑战。
This work introduces a generalizable approach for estimating the field-scale agricultural yield losses due to soil salinization. When integrated with regional data on crop yields and prices, this model provides high-resolution estimates for revenue losses over large agricultural regions. These methods account for the uncertainty inherent in model inputs derived from satellites, experimental field data, and interpreted model results. We apply this method to estimate the effect of soil salinity on agricultural outputs in California, performing the analysis with both high-resolution (i.e. field scale) and low-resolution (i.e. county-scale) data sources to highlight the importance of spatial resolution in agricultural analysis. We estimate that soil salinity reduced agricultural revenues by $3.7 billion ($1.7-$7.0 billion) in 2014, amounting to 8.0 million tons of lost production relative to soil salinities below the crop-specific thresholds. When using low-resolution data sources, we find that the costs of salinization are underestimated by a factor of three. These results highlight the need for high-resolution data in agro-environmental assessment as well as the challenges associated with their integration.