Mukesh Mehata, S. Datta, S. Taghvaeian, A. Mirchi, D. Moriasi
{"title":"土壤数据精度对灌溉调度工具输出的影响","authors":"Mukesh Mehata, S. Datta, S. Taghvaeian, A. Mirchi, D. Moriasi","doi":"10.13031/ja.15323","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":29714,"journal":{"name":"Journal of the ASABE","volume":null,"pages":null},"PeriodicalIF":1.2000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Effects of Soil Data Accuracy on Outputs of Irrigation Scheduling Tools\",\"authors\":\"Mukesh Mehata, S. Datta, S. Taghvaeian, A. Mirchi, D. Moriasi\",\"doi\":\"10.13031/ja.15323\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":29714,\"journal\":{\"name\":\"Journal of the ASABE\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the ASABE\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.13031/ja.15323\",\"RegionNum\":4,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"AGRICULTURAL ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the ASABE","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.13031/ja.15323","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AGRICULTURAL ENGINEERING","Score":null,"Total":0}
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.