Functions to Predict Optimal Irrigation Programs

Stewart, John; Hagan, Robert M.; Pruitt, William O.

doi:10.1061/jrcea4.0000976

Cited by 35 publications

(1 citation statement)

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“…For grain crops, this minimum ET is typically 20 to 50% of ET p . Many published studies propose that both biomass and grain yield increase linearly between this ET intercept and ET p (Cakir, 2004;Doorenbos and Kassam, 1979;Hanks, 1983;Stewart et al, 1974).…”

Section: Water Production Functionmentioning

confidence: 99%

An Economic and Biophysical Model of Deficit Irrigation

Trout

Manning

2019

Agronomy Journal

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Competition for scarce water resources may lead to high water prices. Agricultural producers can adapt to increasing water price by adjusting irrigation management strategies. When water prices are high, deficit irrigation, the purposeful reduction of irrigation to reduce water use while accepting reduced yield, may increase net income. Deficit irrigation decisions depend on economic, biological, and physical conditions. A model based on relationships among the amount and cost of irrigation water applied, water productivity, and the value of water saved and crop yield was developed to assist farmers making deficit irrigation decisions. A model application for irrigated maize (Zia mays L.) production in northeast Colorado illustrates conditions under which deficit irrigation increases net income. High water costs and low crop prices favor deficit irrigation. When water has value for leasing, the combination of deficit irrigation production to reduce water use and water leasing may increase net income. Sufficiently high lease prices and low commodity prices favor rainfed production or fallowing. Core Ideas Deficit irrigation may increase net farm income. Expensive water, low crop prices, and high elasticity of water productivity favor deficit irrigation. Combining economic with biophysical models improves applicability.

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Section: Water Production Functionmentioning

confidence: 99%

An Economic and Biophysical Model of Deficit Irrigation

Trout

Manning

2019

Agronomy Journal

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Concepts and Applications of AquaCrop: The FAO Crop Water Productivity Model

Steduto¹,

Raes

Hsiao

et al. 2009

Crop Modeling and Decision Support

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Predicting attainable yield under water-limiting conditions is an important goal in arid, semi-arid and drought-prone environments. To address this task, FAO has developed a model, AquaCrop, which simulates attainable yields of the major herbaceous crops in response to water. Compared to other models, AquaCrop has a significantly smaller number of parameters and attempts to strike a balance between simplicity, accuracy, and robustness. Root zone water content is simulated by keeping track of incoming and outgoing water fluxes. Instead of leaf area index, AquaCrop uses canopy ground cover. Canopy expansion, stomatal conductance, canopy senescence, and harvest index are the key physiological processes which respond to water stress. Low and high temperature stresses on pollination and harvestable yield are considered, as is cold temperature stress on biomass production. Evapotranspiration is simulated separately as crop transpiration and soil evaporation and the daily transpiration is used to calculate the biomass gain via the normalized biomass water productivity. The normalization is for atmospheric evaporative demand and carbon dioxide concentration, to make the model applicable to diverse locations and seasons, including future climate scenarios. AquaCrop accommodates fertility levels and water management systems, including rainfed, supplemental, deficit, and full irrigation. Simulations are routinely in thermal time, but can be carried out in calendar time. Future versions will incorporate salt balance and capillary raise. AquaCrop is aimed at users in extension services, consulting firms, governmental agencies, NGOs, farmers associations and irrigation districts, as well as economists and policy analysts in need of crop models for planning and assessing water needs and use of projects and regions.

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Crop Water Management to Optimize Growth and Yield

Hake¹,

Grimes²

2010

Physiology of Cotton

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Functions to Predict Optimal Irrigation Programs

Cited by 35 publications

References 0 publications

An Economic and Biophysical Model of Deficit Irrigation

An Economic and Biophysical Model of Deficit Irrigation

Concepts and Applications of AquaCrop: The FAO Crop Water Productivity Model

Crop Water Management to Optimize Growth and Yield

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