土壤数据精度对灌溉调度工具输出的影响

IF 1.2 4区 农林科学 Q3 AGRICULTURAL ENGINEERING
Mukesh Mehata, S. Datta, S. Taghvaeian, A. Mirchi, D. Moriasi
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引用次数: 0

摘要

重点研究了土壤数据精度对灌溉调度模型估算水通量的影响。免费和常用的网式土壤调查(WSS)土壤质地数据低估了89%的沙粒。根据WSS和实测土壤数据估算的季节性灌溉差异中,49%在±25毫米范围内。在大多数情况下,与基于测量土壤数据的数据相比,使用WSS数据导致了更大的蒸发、更小的深渗和更大的径流。摘要一种广泛使用的灌溉调度方法是基于土壤水分平衡建模,该方法需要几个关键的输入,包括土壤数据。使用这种方法开发的许多调度工具依赖于公开可用的土壤数据,例如美国农业部的网络土壤调查(WSS)。虽然土壤调查数据在大尺度上是一般农场和自然资源规划和管理的宝贵信息来源,但在田间和子田间尺度上土壤条件的不准确可能妨碍通过灌溉调度工具进行有效的农业用水管理。为了阐明局部不准确的含义,本研究通过与原位采样(ISS)数据的比较,估计了俄克拉何马州西部三个地区18个站点的WSS土壤质地数据的误差。还研究了15年(2006-2020年)期间每个地区主要作物的误差对估计水通量的影响。结果表明,在大多数地点和土层上,WSS土壤质地比ISS更细,因此根区总有效水分估计值通常更高。当使用WSS数据而不是ISS数据时,季节性灌溉需求估计值的差异在一个站点达到20%,而在区域之间则在±9%以内。所有地点、年份和作物的估计季节灌溉差异中有一半在±25毫米范围内。土壤数据源也会影响土壤蒸发、深层渗流和径流通量,尽管影响程度小于灌溉,但其水平和方向(高估或低估)取决于WSS误差的符号和大小,以及降水量和时间。总的来说,WSS数据的误差在区域尺度上可能不会产生重大影响,但对个别灌溉农场的影响可能很严重,这取决于WSS数据与真实土壤条件之间差异的大小。关键词:灌溉需求;土壤水分平衡;SSURGO;
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effects of Soil Data Accuracy on Outputs of Irrigation Scheduling Tools
Highlights The effects of soil data accuracy on estimated water fluxes by an irrigation scheduling model were investigated. Free and frequently used web soil survey (WSS) soil textural data underestimated sand particles in 89% of cases. Forty-nine percent of the estimated differences in seasonal irrigation based on WSS and measured soil data were within ±25 mm. In most cases, use of WSS data resulted in larger evaporation, smaller deep percolation, and larger runoff compared to those based on measured soil data. Abstract. A widely used irrigation scheduling method is based on modeling soil water balance, which requires several key inputs, including soil data. Many scheduling tools developed using this method rely on publicly available soil data, such as the United States Department of Agriculture's Web Soil Survey (WSS). While soil survey data are a valuable source of information for general farm and natural resource planning and management at large scales, inaccuracies in soil conditions at field and subfield scales can hamper efficient agricultural water management through irrigation scheduling tools. To illuminate the implications of the localized inaccuracies, this study estimated the errors in WSS soil textural data at 18 sites in three regions of western Oklahoma through comparison with in-situ sampling (ISS) data. The effects of errors on estimated water fluxes were also investigated for dominant crops of each region over a 15-year (2006-2020) period. The findings demonstrated that WSS soil textures were finer than ISS at most sites and soil layers, resulting in generally greater root zone total available water estimates. Differences in seasonal irrigation demand estimates when WSS data were used instead of ISS reached 20% at one site but were within ±9% among the regions. Half of the estimated seasonal irrigation differences for all sites, years, and crops were within ±25 mm. Soil evaporation, deep percolation, and runoff fluxes were also impacted by soil data source, albeit to a smaller degree than irrigation, at levels and directions (over or underestimation) that were dependent on the sign and magnitude of WSS errors, as well as precipitation amounts and timing. Overall, errors in WSS data may not have a major impact at regional scales, but the effects on individual irrigated farms may be severe depending on the magnitude of difference between WSS data and true soil conditions. Keywords: Irrigation demand, Soil water balance, SSURGO, Water fluxes, Web soil survey.
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