A web application for cotton irrigation management on the U.S. Southern High Plains. Part I: Crop yield modeling and profit analysis

Mauget, Steven A.; Leiker, Gary; Nair, Shyam

doi:10.1016/j.compag.2013.10.003

Cited by 18 publications

(12 citation statements)

References 17 publications

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“…Given this depletion rate, scientists have predicted that 35% of the Southern High Plains will not be able to support irrigation in 30 years. Many other water resources in the world are depleting rapidly in recent years with negligible recharge, indicating the need for water conservation solutions in agriculture [4,5]. More effective and efficient management of water is required to better conserve water and improve water use efficiency for sustainable crop production.…”

Section: Introductionmentioning

confidence: 99%

“…Today, site-specific water management has been made easier with several precision agriculture tools, such as GNSS, GIS, yield mapping, soil survey and remote sensing [26]. Several decision support tools and strategies to reduce groundwater withdrawal without reductions in irrigated land area or crop productivity have been developed [4]. The measures to optimize the use of irrigation water in the fields include increasing weather-based irrigation scheduling, converting gravity-based irrigation to center pivot irrigation, subsurface drip irrigation, replacing high water to low water demand crops, and deficit irrigation based on evapotranspiration replacement using various water-balance models [27].…”

Section: Introductionmentioning

confidence: 99%

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Agronomic Basis and Strategies for Precision Water Management: A Review

2019

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Agriculture faces the challenge of feeding a growing population with limited or depleting fresh water resources. Advances in irrigation systems and technologies allow site-specific application of irrigation water within the field to improve water use efficiency or reduce water usage for sustainable crop production, especially in arid and semi-arid regions. This paper discusses recent development of variable-rate irrigation (VRI) technologies, data and information for VRI application, and impacts of VRI, including profitability using this technology, with a focus on agronomic factors in precision water management. The development in sprinkler systems enabled irrigation application with greater precision at the scale of individual nozzle control. Further research is required to evaluate VRI prescription maps integrating different soil and crop characteristics in different environments. On-farm trials and whole-field studies are needed to provide support information for practical VRI applications. Future research also needs to address the adjustment of the spatial distribution of prescription zones in response to temporal variability in soil water status and crop growing conditions, which can be evaluated by incorporating remote and proximal sensing data. Comprehensive decision support tools are required to help the user decide where to apply how much irrigation water at different crop growth stages to optimize water use and crop production based on the regional climate conditions and cropping systems.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Agronomic Basis and Strategies for Precision Water Management: A Review

2019

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“…Without irrigation, SHP summers are generally dry relative to conditions that maximize yield. During 1974During -2005, the region's median May-Sept. rainfall was 29.2 cm (Mauget et al, 2013), which is less than half of the 74.0 cm estimated by Wanjura et al (2002) to achieve maximum SHP lint yield. In addition, summer temperatures are generally considered to be cool relative to the requirements for cotton growth (Morrow and Kreig, 1990;Howell et al, 2004;Tolk and Howell, 2010).…”

Section: Introductionmentioning

confidence: 71%

“…An alternative approach is to simulate dryland production with crop models. As in M17 and earlier work (Mauget et al, 2009(Mauget et al, , 2013, driving a crop model with weather inputs from numerous weather stations and then aggregating the resulting yields into distributions is a central feature of the MtC simulation approach used here. To broadly sample current summer rainfall outcomes over the SHP production region (Figure 1), weather inputs to the DSSAT CROPGRO-Cotton model were derived from 21 stations within Texas Tech University's West Texas Mesonet (WTM) network (Schroeder et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

Optimizing Dryland Crop Management to Regional Climate via Simulation. Part I: U.S. Southern High Plains Cotton Production

Mauget

Marek

Adhikari

et al. 2020

Front. Sustain. Food Syst.

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Over semi-arid agricultural regions such as the U.S. Southern High Plains (SHP) producers of dryland crops need to know which management practices increase yields and decrease production risk. Here, a modeling approach is used to explore management options (MO) that increase dryland cotton yields and estimate those practice's yield risk effects under current SHP climate conditions. To simulate current dryland yield variability, dense distributions of lint yield outcomes were generated using the CROPGRO-Cotton crop model driven by weather inputs from 21 SHP weather stations during 2005-2016. Management effects were explored by repeating simulations over 32 MOs defined by 4 planting dates, 4 planting densities, and applying or not applying nitrogen. Both earlier planting date and decreased plant density increased median simulated yields, with earlier planting having the greatest positive yield effects. The simulated MO that produced the highest median lint yields planted on the earliest planting date (May 15), at the lowest density (3 plants m −1), and applied no nitrogen. Recent SHP field studies generally confirm the earlier planting date effect, but suggest insignificant yield effects for different seeding rates. Even so, negligible yield effects and lower input costs favor lower seeding densities from a profit standpoint. These crop simulations demonstrate a modeling-based method for climate-related agricultural risk management, and suggest mid-May planting dates and low plant densities as part of management practices that increase yields and profits in dryland SHP cotton production.

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“…5b) provides links to other web-based climate and crop management resources including the U.S. Drought Monitor, the U.S. Climate Prediction Center, a JavaScript tool for West Texas cotton irrigation management (Mauget et al, 2013a(Mauget et al, , 2013b, and the Visual Basic Ogallala Agro-Climate Tool.…”

Section: Graphical User Interface Descriptionmentioning

confidence: 99%

A Web Application for Managing Regional Crop Production: The West Texas Mesonet Agro‐Climate Monitor

Mauget

Leiker

Schroeder³

et al. 2017

Agronomy Journal

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Although dependent on rainfall and other climate factors to produce crops, West Texas crop consultants, extension agents, and agricultural producers have few tools that allow them to track the current growing season's climate conditions and determine how current conditions compare with those of past years. Th e West Texas Mesonet Agro-Climate Monitor (ACM), a JavaScript web application based on daily data from Texas Tech University's mesonet weather station network, was designed to meet this need. By displaying continuously updated information on variables such as soil temperature, cumulative growing degree days (GDD), cumulative precipitation, and fi rst freeze dates, the ACM allows producers to monitor planting conditions, track crop development, and compare current conditions with those during the previous 10 yr's growing seasons. In illustrating how mesonet data might be used as an operational climate data resource, the ACM might also serve as a conceptual model for other high resolution climate tools that estimate measures of current climate using continuously updated daily data sets.

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A web application for cotton irrigation management on the U.S. Southern High Plains. Part I: Crop yield modeling and profit analysis

Cited by 18 publications

References 17 publications

Agronomic Basis and Strategies for Precision Water Management: A Review

Agronomic Basis and Strategies for Precision Water Management: A Review

Optimizing Dryland Crop Management to Regional Climate via Simulation. Part I: U.S. Southern High Plains Cotton Production

A Web Application for Managing Regional Crop Production: The West Texas Mesonet Agro‐Climate Monitor

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