2026
1.
Abid Sarwar; Josué Medellín-Azuara; John T. Abatzoglou; Joshua H. Viers
In: PLOS Water, vol. 5, no. 7, pp. e0000416, 2026, ISSN: 2767-3219.
Abstract | Links | BibTeX | Tags: Agricultural irrigation, Crop management, Crops, Remote Sensing, Seasons, Valleys, Vegetables, Water management
@article{sarwar_identifying_2026,
title = {Identifying agricultural consumptive-use patterns to support adaptive water management in California’s Santa Clara Valley via remote sensing and machine learning},
author = {Abid Sarwar and Josu\'{e} Medell\'{i}n-Azuara and John T. Abatzoglou and Joshua H. Viers},
url = {https://journals.plos.org/water/article?id=10.1371/journal.pwat.0000416},
doi = {10.1371/journal.pwat.0000416},
issn = {2767-3219},
year = {2026},
date = {2026-07-01},
urldate = {2026-07-01},
journal = {PLOS Water},
volume = {5},
number = {7},
pages = {e0000416},
publisher = {Public Library of Science},
abstract = {Site-specific agricultural water management is particularly important in highly productive and diverse agricultural regions such as California’s Santa Clara Valley (SCV), where broad crop categories can obscure substantial parcel-scale differences in consumptive use. This study used unsupervised machine learning on remotely sensed data from 2019-2023 to develop operationally distinct, agricultural consumptive-use groups for major crop types. Time series of Sentinel-2 normalized difference vegetation index (NDVI), OpenET ensemble actual evapotranspiration (ETa, used as a proxy for consumptive use), and PRISM precipitation were analyzed at the parcel level for truck crops, vineyards, and hay crops. Across 2,189 parcels (textasciitilde7,483 ha), the only-NDVI and NDVI+ETa clustering approaches identified 13 consumptive-use clusters and revealed substantial within-crop heterogeneity hidden by conventional crop averages. Six clusters were detected in truck crops (TC), four in vineyards (VC), and three in hay crops (HC). Adding ETa magnitude and trend information generally reduced average within-cluster coefficient of variation (CV) relative to only-NDVI clustering and increased separation among cluster means. The ratios of between-cluster to mean within-cluster CV were lower under only-NDVI (TC = 0.30},
keywords = {Agricultural irrigation, Crop management, Crops, Remote Sensing, Seasons, Valleys, Vegetables, Water management},
pubstate = {published},
tppubtype = {article}
}
Site-specific agricultural water management is particularly important in highly productive and diverse agricultural regions such as California’s Santa Clara Valley (SCV), where broad crop categories can obscure substantial parcel-scale differences in consumptive use. This study used unsupervised machine learning on remotely sensed data from 2019-2023 to develop operationally distinct, agricultural consumptive-use groups for major crop types. Time series of Sentinel-2 normalized difference vegetation index (NDVI), OpenET ensemble actual evapotranspiration (ETa, used as a proxy for consumptive use), and PRISM precipitation were analyzed at the parcel level for truck crops, vineyards, and hay crops. Across 2,189 parcels (textasciitilde7,483 ha), the only-NDVI and NDVI+ETa clustering approaches identified 13 consumptive-use clusters and revealed substantial within-crop heterogeneity hidden by conventional crop averages. Six clusters were detected in truck crops (TC), four in vineyards (VC), and three in hay crops (HC). Adding ETa magnitude and trend information generally reduced average within-cluster coefficient of variation (CV) relative to only-NDVI clustering and increased separation among cluster means. The ratios of between-cluster to mean within-cluster CV were lower under only-NDVI (TC = 0.30
2024
2.
Basavaraj R. Amogi; Lav R. Khot; Bernardita V. Sallato
Localized Crop Physiology Sensing System Driven Apple Fruit Color Progression Monitoring Proceedings Article
In: 2024 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor), pp. 232–236, 2024.
Abstract | Links | BibTeX | Tags: Biomedical monitoring, Crops, cyber physical system, fruit color, hue, Image color analysis, Monitoring, Prevention and mitigation, Real-time systems, Sensors, Solar heating, Solar radiation, Stress
@inproceedings{amogi_localized_2024,
title = {Localized Crop Physiology Sensing System Driven Apple Fruit Color Progression Monitoring},
author = {Basavaraj R. Amogi and Lav R. Khot and Bernardita V. Sallato},
url = {https://ieeexplore.ieee.org/document/10948846},
doi = {10.1109/MetroAgriFor63043.2024.10948846},
year = {2024},
date = {2024-10-01},
urldate = {2024-10-01},
booktitle = {2024 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)},
pages = {232\textendash236},
abstract = {Fruit color is a critical quality attribute that significantly affects the commercial value of apples. Elevated air temperatures and solar radiation during heat waves can substantially impact fruit coloration, while mitigation techniques such as netting can further compromise fruit color development by trapping heat. Continuous monitoring of fruit color throughout the growing season, particularly under heat stress conditions, is thus essential for informed grower decision-making. This study leverages a previously developed localized crop physiology sensing system (CPSS) to enable real time monitoring of apple fruit color progression. Using visible imagery captured by the CPSS, apple fruit color was quantified by extracting the hue angle (ˆtextbackslashcirctextbackslashmathbfh). The results showed that, the influence of sunlight on measured color accuracy (ΔE) is lower and more stable during mid-day hours (1000 h − 1300 h), whereas notable variations were observed during early morning and late afternoon periods. The ˆtextbackslashcirctextbackslashmathbfh hence calculated for RGB images captured around 1200 h was utilized to track fruit color progression. Its monitoring over the summer 2022 growing season showed variations as an effect of environmental stressors, especially in response to heat wave. The developed approach offers a tool for growers to adjust different heat mitigation techniques during heat wave/events to mitigate any negative implication on fruit coloration.},
keywords = {Biomedical monitoring, Crops, cyber physical system, fruit color, hue, Image color analysis, Monitoring, Prevention and mitigation, Real-time systems, Sensors, Solar heating, Solar radiation, Stress},
pubstate = {published},
tppubtype = {inproceedings}
}
Fruit color is a critical quality attribute that significantly affects the commercial value of apples. Elevated air temperatures and solar radiation during heat waves can substantially impact fruit coloration, while mitigation techniques such as netting can further compromise fruit color development by trapping heat. Continuous monitoring of fruit color throughout the growing season, particularly under heat stress conditions, is thus essential for informed grower decision-making. This study leverages a previously developed localized crop physiology sensing system (CPSS) to enable real time monitoring of apple fruit color progression. Using visible imagery captured by the CPSS, apple fruit color was quantified by extracting the hue angle (ˆtextbackslashcirctextbackslashmathbfh). The results showed that, the influence of sunlight on measured color accuracy (ΔE) is lower and more stable during mid-day hours (1000 h − 1300 h), whereas notable variations were observed during early morning and late afternoon periods. The ˆtextbackslashcirctextbackslashmathbfh hence calculated for RGB images captured around 1200 h was utilized to track fruit color progression. Its monitoring over the summer 2022 growing season showed variations as an effect of environmental stressors, especially in response to heat wave. The developed approach offers a tool for growers to adjust different heat mitigation techniques during heat wave/events to mitigate any negative implication on fruit coloration.
3.
Vicky Espinoza; Joshua H. Viers
The paradox of production: Surface water supply drives agricultural productivity but not prosperity in California’s San Joaquin Valley Journal Article
In: PLOS Water, vol. 3, no. 6, pp. e0000192, 2024, ISSN: 2767-3219.
Abstract | Links | BibTeX | Tags: Agricultural irrigation, Climate change, Crops, Surface irrigation, Surface water, Valleys, Water management, Water resources
@article{espinoza_paradox_2024,
title = {The paradox of production: Surface water supply drives agricultural productivity but not prosperity in California’s San Joaquin Valley},
author = {Vicky Espinoza and Joshua H. Viers},
url = {https://journals.plos.org/water/article?id=10.1371/journal.pwat.0000192},
doi = {10.1371/journal.pwat.0000192},
issn = {2767-3219},
year = {2024},
date = {2024-06-01},
urldate = {2024-06-01},
journal = {PLOS Water},
volume = {3},
number = {6},
pages = {e0000192},
publisher = {Public Library of Science},
abstract = {Societies globally are struggling to meet freshwater demands while agencies attempt to address water access inequities under a rapidly changing climate and growing population. An understanding of dynamic interactions between people and water, known as sociohydrology, regionally could provide approaches to addressing local water mismanagement and water access inequity. In semi-arid California, local water agencies, primarily agricultural irrigation districts, are at the intersection of rethinking approaches to balance freshwater demands. More than 150 years of complex water governance and management have defined San Joaquin Valley irrigation districts and the region’s water access inequities and sociohydrologic instability. Older irrigation districts have higher surface water allocations and less groundwater dependence. About 60% of irrigation districts with pre-1914 water rights have twice the crop water demand in surface water allocations. In contrast, 86% of irrigation districts depend on groundwater, of which 12% rely exclusively on groundwater to supply irrigation demands. This study found that disadvantaged communities within irrigation districts do not have increased water access or better environmental conditions than those outside irrigation district boundaries, which underscores the need for inclusive water management structures to address the multifaceted water and environmental inequities. Groundwater overdependence across irrigation districts shows that imbalanced surface water allocations and inflexible crops could imperil agriculture and impact agricultural disadvantaged communities, especially under California’s SGMA and prolonged drought events. It is imperative that underserved communities are prioritized communities in achieving equitable water rebalance in California in addition to developing and implementing essential infrastructure and policy changes.},
keywords = {Agricultural irrigation, Climate change, Crops, Surface irrigation, Surface water, Valleys, Water management, Water resources},
pubstate = {published},
tppubtype = {article}
}
Societies globally are struggling to meet freshwater demands while agencies attempt to address water access inequities under a rapidly changing climate and growing population. An understanding of dynamic interactions between people and water, known as sociohydrology, regionally could provide approaches to addressing local water mismanagement and water access inequity. In semi-arid California, local water agencies, primarily agricultural irrigation districts, are at the intersection of rethinking approaches to balance freshwater demands. More than 150 years of complex water governance and management have defined San Joaquin Valley irrigation districts and the region’s water access inequities and sociohydrologic instability. Older irrigation districts have higher surface water allocations and less groundwater dependence. About 60% of irrigation districts with pre-1914 water rights have twice the crop water demand in surface water allocations. In contrast, 86% of irrigation districts depend on groundwater, of which 12% rely exclusively on groundwater to supply irrigation demands. This study found that disadvantaged communities within irrigation districts do not have increased water access or better environmental conditions than those outside irrigation district boundaries, which underscores the need for inclusive water management structures to address the multifaceted water and environmental inequities. Groundwater overdependence across irrigation districts shows that imbalanced surface water allocations and inflexible crops could imperil agriculture and impact agricultural disadvantaged communities, especially under California’s SGMA and prolonged drought events. It is imperative that underserved communities are prioritized communities in achieving equitable water rebalance in California in addition to developing and implementing essential infrastructure and policy changes.
