Katherine Osorio-Diaz
Utah State University | Graduate Research Assistant
| Subject Areas: | Hydrology, remotesensing, watermanagement, climate, engineering |
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ABSTRACT:
This dataset supports Chapter III of the Ph.D. dissertation titled “Irrigation Canal Companies remote sensing-based water balance and agricultural water management assessment under different Utah climate regions.” This dataset represents the thesis version of the study and may be updated later to correspond to the journal article version currently under review in Irrigation Science Journal. The dataset folder contains two main subfolders: “Raw,” which includes data downloaded from the original sources, and “Processed,” which includes the GIS, raster, and tabular datasets generated during the study.
The study applied an existing remote sensing-based agricultural water balance approach previously developed for Utah irrigation canal companies (https://doi.org/10.1007/s00271-026-01172-8) to evaluate water balance behavior and agricultural water management performance across ICCs located in contrasting Utah climate regions. Historical remote-sensing data from OpenET and gridMET were integrated with Geographic Information Systems datasets, including agricultural field information, canal distribution data, and agricultural water diversion records, to model monthly water balances during 2020–2023 in three major basins: the Bear River Basin, Upper Colorado River Basin, and Sevier River Basin.
The water balance evaluated precipitation, irrigation, actual crop evapotranspiration (ETc act), capillary rise from groundwater (CR), runoff, deep percolation (DP), and change of water depletion in the root zone (∆Dr). CR, runoff, DP, and other unresolved hydrologic contributions and uncertainty were represented through the Water Balance Residual (WBR). Based on the estimated water balance components, agricultural water management performance metrics were also evaluated to compare patterns among ICCs under different climatic and agricultural water diversion conditions.
Seasonally, WBR represented approximately 5–29%, 3–33%, and 1–35% of the sum of all water balance components in the Bear River, Upper Colorado River, and Sevier River Basins, respectively. Seasonal agricultural water management performance metrics ranged from 25–156%, 28–117%, and 28–129% across the same basins, respectively. These values should be interpreted as illustrative screening ranges rather than direct measures of irrigation efficiency, water savings, or recoverable water volumes.
Overall, the dataset supports comparison of ICC-scale agricultural water-balance behavior and management indicators under contrasting geographic and climatic conditions and can help identify areas where additional investigation of agricultural water management may be warranted.
ABSTRACT:
This dataset supports the paper titled “Agricultural water balance and variability in Utah irrigation canal companies with OpenET products and spatial data” associated with https://doi.org/10.1007/s00271-026-01172-8. The dataset folder "Torres_MeasurementRT4Utah_Paper1Data", was originally organized for the USDA Secure Water Future project repository. It contains two main subfolders: “Raw” which includes data downloaded from the original sources, and “Processed,” which includes the GIS, raster, and tabular datasets generated during the study.
The study coupled historical remote sensing data from OpenET and gridMET with GIS datasets, including field boundaries, canal distribution information, and agricultural water diversion records, to implement a monthly water balance model for three irrigation canal companies (ICCs) in Northern Utah. The water balance model evaluated precipitation, irrigation, capillary rise from groundwater (CR), actual crop evapotranspiration (ETc act), runoff, deep percolation (DP), and change of water depletion at the root zone (∆Dr). The water balance residual (WBR) was calculated as the unresolved portion of the balance and may reflect runoff, DP, other unquantified hydrologic exchanges, and uncertainty (CR was considered only where supported by site conditions). The spatial distribution of ∆Dr was estimated using a Random Forest model based on local observed data such ETc act, and soil water content. Monthly WBR values were highest during the peak irrigation season (July–August). Seasonally, from April to October, WBR represented approximately 5–29% of the sum of all water balance components across the studied ICCs. These values should be interpreted as illustrative screening ranges rather than measured water savings or directly recoverable water volumes.
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Created: Aug. 17, 2026, 6:43 p.m.
Authors: Osorio-Diaz, Katherine · Torres-Rua, Alfonso Faustino · Yost, Matt · Lawrence Hipps
ABSTRACT:
This dataset supports the paper titled “Agricultural water balance and variability in Utah irrigation canal companies with OpenET products and spatial data” associated with https://doi.org/10.1007/s00271-026-01172-8. The dataset folder "Torres_MeasurementRT4Utah_Paper1Data", was originally organized for the USDA Secure Water Future project repository. It contains two main subfolders: “Raw” which includes data downloaded from the original sources, and “Processed,” which includes the GIS, raster, and tabular datasets generated during the study.
The study coupled historical remote sensing data from OpenET and gridMET with GIS datasets, including field boundaries, canal distribution information, and agricultural water diversion records, to implement a monthly water balance model for three irrigation canal companies (ICCs) in Northern Utah. The water balance model evaluated precipitation, irrigation, capillary rise from groundwater (CR), actual crop evapotranspiration (ETc act), runoff, deep percolation (DP), and change of water depletion at the root zone (∆Dr). The water balance residual (WBR) was calculated as the unresolved portion of the balance and may reflect runoff, DP, other unquantified hydrologic exchanges, and uncertainty (CR was considered only where supported by site conditions). The spatial distribution of ∆Dr was estimated using a Random Forest model based on local observed data such ETc act, and soil water content. Monthly WBR values were highest during the peak irrigation season (July–August). Seasonally, from April to October, WBR represented approximately 5–29% of the sum of all water balance components across the studied ICCs. These values should be interpreted as illustrative screening ranges rather than measured water savings or directly recoverable water volumes.
Created: Nov. 12, 2026, 11:45 p.m.
Authors: Osorio-Diaz, Katherine · Torres-Rua, Alfonso Faustino
ABSTRACT:
This dataset supports Chapter III of the Ph.D. dissertation titled “Irrigation Canal Companies remote sensing-based water balance and agricultural water management assessment under different Utah climate regions.” This dataset represents the thesis version of the study and may be updated later to correspond to the journal article version currently under review in Irrigation Science Journal. The dataset folder contains two main subfolders: “Raw,” which includes data downloaded from the original sources, and “Processed,” which includes the GIS, raster, and tabular datasets generated during the study.
The study applied an existing remote sensing-based agricultural water balance approach previously developed for Utah irrigation canal companies (https://doi.org/10.1007/s00271-026-01172-8) to evaluate water balance behavior and agricultural water management performance across ICCs located in contrasting Utah climate regions. Historical remote-sensing data from OpenET and gridMET were integrated with Geographic Information Systems datasets, including agricultural field information, canal distribution data, and agricultural water diversion records, to model monthly water balances during 2020–2023 in three major basins: the Bear River Basin, Upper Colorado River Basin, and Sevier River Basin.
The water balance evaluated precipitation, irrigation, actual crop evapotranspiration (ETc act), capillary rise from groundwater (CR), runoff, deep percolation (DP), and change of water depletion in the root zone (∆Dr). CR, runoff, DP, and other unresolved hydrologic contributions and uncertainty were represented through the Water Balance Residual (WBR). Based on the estimated water balance components, agricultural water management performance metrics were also evaluated to compare patterns among ICCs under different climatic and agricultural water diversion conditions.
Seasonally, WBR represented approximately 5–29%, 3–33%, and 1–35% of the sum of all water balance components in the Bear River, Upper Colorado River, and Sevier River Basins, respectively. Seasonal agricultural water management performance metrics ranged from 25–156%, 28–117%, and 28–129% across the same basins, respectively. These values should be interpreted as illustrative screening ranges rather than direct measures of irrigation efficiency, water savings, or recoverable water volumes.
Overall, the dataset supports comparison of ICC-scale agricultural water-balance behavior and management indicators under contrasting geographic and climatic conditions and can help identify areas where additional investigation of agricultural water management may be warranted.