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    Development of the Diversion Runoff Calculator to Estimate Agricultural Water Consumption and Irrigation Diversions at the Field- to Basin-Scale in Northeastern Utah

    Source: Journal of Irrigation and Drainage Engineering:;2025:;Volume ( 151 ):;issue: 002::page 04025004-1
    Author:
    Michael Follum
    ,
    Betsy Morgan
    ,
    Leland Dorchester
    ,
    Adolph “Shane” Coors
    ,
    Anthony Powell
    ,
    Bart Leeflang
    ,
    Mark Wahl
    ,
    Joshua Rayes
    DOI: 10.1061/JIDEDH.IRENG-10452
    Publisher: American Society of Civil Engineers
    Abstract: With the western United States experiencing aridification and prolonged drought, there is a need for improved water management to understand irrigation water requirements and to forecast how drought mitigation efforts may affect irrigation operations at the field-, canal-, and basin-scale. This paper presents the Diversion Runoff Calculator (DRC), which uses geospatial and field-scale data sets (monthly evapotranspiration estimates from OpenET and effective precipitation estimates from the ET Demands model) to estimate irrigation requirements, field runoff, and canal seepage at the field-, canal-, and basin-scale. Because the geospatial data sets characterize field-scale attributes (irrigation method, canal lining, etc.), changes to these attributes can be made to reflect potential drought mitigation strategies and processed using the DRC. The effects of drought mitigation strategies are realized through changes in irrigation demands. The DRC is tested on irrigated lands along the Duchesne River in northeast Utah. At the field scale, the study finds that the consumptive use values calculated using OpenET data and the ET Demands model match well with the irrigation requirement tables typically used by water managers. The field-scale consumptive use data are aggregated to the canal-scale and a transit loss within the canal is calculated, resulting in an estimated diversion flow requirement at the headgate of each canal, which is subsequently aggregated to the basin scale. The canal- and basin-scale diversion estimates reasonably replicate observed diverted flows, with basin-scale Nash–Sutcliffe Efficiency of 0.74. Two test cases are presented that demonstrate how the DRC can be used to evaluate drought mitigation strategies. The first considers lining all the earthen canals, which results in a 5.0% reduction in diverted flows. The second considers converting all flood-irrigated fields to sprinkler-irrigated fields, which results in a 4.4% reduction in diverted flows. Although the geospatial data sets used are Utah-specific, avenues for applying the DRC in other western states are discussed.
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      Development of the Diversion Runoff Calculator to Estimate Agricultural Water Consumption and Irrigation Diversions at the Field- to Basin-Scale in Northeastern Utah

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    contributor authorMichael Follum
    contributor authorBetsy Morgan
    contributor authorLeland Dorchester
    contributor authorAdolph “Shane” Coors
    contributor authorAnthony Powell
    contributor authorBart Leeflang
    contributor authorMark Wahl
    contributor authorJoshua Rayes
    date accessioned2025-04-20T10:15:48Z
    date available2025-04-20T10:15:48Z
    date copyright1/20/2025 12:00:00 AM
    date issued2025
    identifier otherJIDEDH.IRENG-10452.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4304341
    description abstractWith the western United States experiencing aridification and prolonged drought, there is a need for improved water management to understand irrigation water requirements and to forecast how drought mitigation efforts may affect irrigation operations at the field-, canal-, and basin-scale. This paper presents the Diversion Runoff Calculator (DRC), which uses geospatial and field-scale data sets (monthly evapotranspiration estimates from OpenET and effective precipitation estimates from the ET Demands model) to estimate irrigation requirements, field runoff, and canal seepage at the field-, canal-, and basin-scale. Because the geospatial data sets characterize field-scale attributes (irrigation method, canal lining, etc.), changes to these attributes can be made to reflect potential drought mitigation strategies and processed using the DRC. The effects of drought mitigation strategies are realized through changes in irrigation demands. The DRC is tested on irrigated lands along the Duchesne River in northeast Utah. At the field scale, the study finds that the consumptive use values calculated using OpenET data and the ET Demands model match well with the irrigation requirement tables typically used by water managers. The field-scale consumptive use data are aggregated to the canal-scale and a transit loss within the canal is calculated, resulting in an estimated diversion flow requirement at the headgate of each canal, which is subsequently aggregated to the basin scale. The canal- and basin-scale diversion estimates reasonably replicate observed diverted flows, with basin-scale Nash–Sutcliffe Efficiency of 0.74. Two test cases are presented that demonstrate how the DRC can be used to evaluate drought mitigation strategies. The first considers lining all the earthen canals, which results in a 5.0% reduction in diverted flows. The second considers converting all flood-irrigated fields to sprinkler-irrigated fields, which results in a 4.4% reduction in diverted flows. Although the geospatial data sets used are Utah-specific, avenues for applying the DRC in other western states are discussed.
    publisherAmerican Society of Civil Engineers
    titleDevelopment of the Diversion Runoff Calculator to Estimate Agricultural Water Consumption and Irrigation Diversions at the Field- to Basin-Scale in Northeastern Utah
    typeJournal Article
    journal volume151
    journal issue2
    journal titleJournal of Irrigation and Drainage Engineering
    identifier doi10.1061/JIDEDH.IRENG-10452
    journal fristpage04025004-1
    journal lastpage04025004-14
    page14
    treeJournal of Irrigation and Drainage Engineering:;2025:;Volume ( 151 ):;issue: 002
    contenttypeFulltext
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