Development of an Optimal Water Allocation Decision Tool for the Major Crops During the Water Deficit Period in the Southeast United States

Paudel, Krishna P.; Limaye, Ashutosh; Hatch, L. Upton; Cruise, J. F.; Musleh, Fuad

doi:10.1111/j.1939-7445.2005.tb00159.x

Cited by 4 publications

(4 citation statements)

References 10 publications

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“…Alabama is a subtropical, humid region in the Southeastern United States and receives over 1400 mm of precipitation annually [30]. However, less than 300 mm of precipitation occurs during the growing season, on average, and thus, water-intensive crops, such as corn, can benefit greatly from supplemental irrigation [48]. The field covers 30.5 ha (75.5 ac) comprised of six different soil types.…”

Section: Study Areamentioning

confidence: 99%

Modeling Soil Moisture Profiles in Irrigated Fields by the Principle of Maximum Entropy

Mishra

Ellenburg

Al‐Hamdan

et al. 2015

Entropy

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Vertical soil moisture profiles based on the principle of maximum entropy (POME) were validated using field and model data and applied to guide an irrigation cycle over a maize field in north central Alabama (USA). The results demonstrate that a simple two-constraint entropy model under the assumption of a uniform initial soil moisture distribution can simulate most soil moisture profiles that occur in the particular soil and climate regime that prevails in the study area. The results of the irrigation simulation demonstrated that the POME model produced a very efficient irrigation strategy with minimal losses (about 1.9% of total applied water). However, the results for finely-textured (silty clay) soils were problematic in that some plant stress did develop due to insufficient applied water. Soil moisture states in these soils fell to around 31% of available moisture content, but only on the last day of the drying side of the irrigation cycle. Overall, the POME approach showed promise as a general strategy to guide irrigation in humid environments, such as the Southeastern United States.

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Section: Study Areamentioning

confidence: 99%

Modeling Soil Moisture Profiles in Irrigated Fields by the Principle of Maximum Entropy

Mishra

Ellenburg

Al‐Hamdan

et al. 2015

Entropy

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“…Although ALEXI data were available at irregular intervals due to cloud constraints, which also led to occasional spurious readings, the results indicate that the data were available at sufficient temporal resolution to drive the crop model in a realistic manner when compared to both the rainfed model and observed corn yields (RMSE 28% of mean observed values; bias 4.7%). This result is particularly significant in that corn is the most water intensive crop grown in the Southeastern United States [72]. The comparison of ALEXI driven yields to observed yields also illustrates that the ALEXI signal did possess the fidelity to drive the crop model in a manner that was representative of the regional crop response.…”

Section: Discussionmentioning

confidence: 80%

A Remote-Sensing Driven Tool for Estimating Crop Stress and Yields

et al. 2013

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Biophysical crop simulation models are normally forced with precipitation data recorded with either gauges or ground-based radar. However, ground-based recording networks are not available at spatial and temporal scales needed to drive the models at many critical places on earth. An alternative would be to employ satellite-based observations of either precipitation or soil moisture. Satellite observations of precipitation are currently not considered capable of forcing the models with sufficient accuracy for crop yield predictions. However, deduction of soil moisture from space-based platforms is in a more advanced state than are precipitation estimates so that these data may be capable of forcing the models with better accuracy. In this study, a mature two-source energy balance model, the Atmosphere Land Exchange Inverse (ALEXI) model, was used to deduce root zone soil moisture for an area of North Alabama, USA. The soil moisture estimates were used in turn to force the state-of-the-art Decision Support System for Agrotechnology Transfer (DSSAT) crop simulation model. The study area consisted of a mixture of rainfed and irrigated cornfields. The results indicate that the model forced with the ALEXI moisture estimates produced yield simulations that compared favorably with observed yields and with the rainfed model. 3332The data appear to indicate that the ALEXI model did detect the soil moisture signal from the mixed rainfed/irrigation corn fields and this signal was of sufficient strength to produce adequate simulations of recorded yields over a 10 year period.

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“…In the Eastern United States-where water is relatively less scarce-the use of on-farm surface water (e.g., on-farm irrigation ponds and surface water diversions) is more common, given lesser public and private incentives to invest in costly water conveyance infrastructure. A notable exception is in the Southeastern United States, where severe drought in the 1950s led to more widespread use of on-and off-farm irrigation ponds (Barber and Stamey, 2000;Paudel et al, 2005). In the Western United States, irrigators are much more reliant on off-farm surface water deliveries from publicly financed water projects.…”

Section: Water Sourcesmentioning

confidence: 99%

Trends in U.S. Irrigated Agriculture: Increasing Resilience Under Water Supply Scarcity

Hrozencik

2021

SSRN Journal

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Irrigation contributes significantly to U.S. agricultural output and production value. In 2017, irrigated farms accounted for more than 54 percent of the total value of crop sales. Irrigation allows for agricultural production in arid regions where precipitation is insufficient to meet crop water requirements. In more humid regions with variable rainfall, irrigation supplements available soil moisture and provides a critical buffer against periodic drought during the crop growing season. However, surface water supply shortfalls during prolonged drought are increasingly taxing the ability of regional water systems to meet the demands of the irrigation sector-as well as industry, municipal use, recreation, and environmental needs. The irrigation sector responded by increasing its reliance on groundwater. This response raises sustainability concerns, as groundwater levels in many major aquifers supporting irrigated agriculture are in decline across the United States. The resiliency of irrigated agriculture under projected climate change will depend on how the sector-and the institutions that influence water supply and use-adapts to increasing water scarcity. Regional adaptation to increasingly limited water supplies may involve a combination of measures. These measures include: continued shifts in area irrigated, increased irrigation efficiency through system upgrades, enhanced water management practices, changes in regional cropping patterns, and shifts in water supply sources, including potentially novel sources of irrigation water such as recycled or reclaimed water.

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Development of an Optimal Water Allocation Decision Tool for the Major Crops During the Water Deficit Period in the Southeast United States

Cited by 4 publications

References 10 publications

Modeling Soil Moisture Profiles in Irrigated Fields by the Principle of Maximum Entropy

Modeling Soil Moisture Profiles in Irrigated Fields by the Principle of Maximum Entropy

A Remote-Sensing Driven Tool for Estimating Crop Stress and Yields

Trends in U.S. Irrigated Agriculture: Increasing Resilience Under Water Supply Scarcity

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