Simulating Crop Phenological Responses to Water Stress Using the PhenologyMMS Software Program

McMaster, Gregory S.; Ascough, J. C.; Edmunds, Debora A.; Nielsen, D. G.; Prasad, Priyanka

doi:10.13031/2013.42654

Cited by 15 publications

(9 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Implementing the water stress function into a model can be done in several ways. As currently implemented in AgES, we used the PhenologyMMS approach (McMaster et al, 2013), where the GDD required to reach the next stage is estimated daily using a linear regression to interpolate between the No-Stress and Stressed values. Sudden shifts in the environment (e.g., a significant rainstorm or an irrigation event) could reset the value to no-Stress even if drought was severe during the interval and near the Stressed value.…”

Section: Discussionmentioning

confidence: 99%

“…The WEPS plant growth component was restructured into FORTRAN 90/95 and was used as the platform for building the UPGM plant growth component (McMaster et al, 2014). Seedling emergence, canopy height, and phenology algorithms that responded to varying amounts of water stress from PhenologyMMS (McMaster et al, 2011(McMaster et al, , 2013 and SHOOTGRO (McMaster et al, 1992;Wilhelm et al, 1993;Zalud et al, 2003) were incorporated into the UPGM. The FORTRAN 90/95 WEPS and UPGM plant growth components were incorporated into the Java-based AgES model, and the user selects the plant growth component to use in simulations.…”

Section: Model and Component Overviewsmentioning

confidence: 99%

“…We tested the UPGM for optimum/no-stress conditions for corn (McMaster et al, 2014) but not for conditions that were less than optimum. A water stress response curve from PhenologyMMS (McMaster et al, 2013) was used to adjust for varying water deficits ( Fig. 3).…”

Section: Model and Component Overviewsmentioning

confidence: 99%

See 2 more Smart Citations

Winter Wheat Phenology Simulations Improve when Adding Responses to Water Stress

et al. 2019

View full text Add to dashboard Cite

Phenology is critical in simulating crop production and hydrology and must be sufficiently robust to respond to varying environments, soils, and management practices. Phenological algorithms typically focus on the air temperature response function and rarely quantify the phenological responses to varying water deficits, particularly for versions of the Environmental Policy Integrated Climate model (EPIC)‐based plant growth component used in many agroecosystem models. Three EPIC‐based plant growth components (Soil Water Assessment Tool [SWAT], Wind Erosion Prediction System [WEPS], and the Unified Plant Growth Model [UPGM]) have been incorporated into the spatially distributed Agricultural Ecosystems Services model [AgES], and only the UPGM includes a phenological response to varying water deficits. These three plant components were used to evaluate the phenological responses of winter wheat (Triticum aestivum L.) to varying water deficits and whether having a water stress factor in UPGM improves the simulation of phenology. A 3‐yr irrigation study and a 4‐yr study across a rainfed landscape were used in the evaluation. Only the UPGM simulated all five of the developmental stagesmeasured. The UPGM was the only component that simulated a phenological response to variable water deficits, resulting in better prediction of phenology. For example, the RMSE (days) and relative error (RE, days) decreased and index of agreement (d) increased in predicting maturity from SWAT (RMSE = 18.4; RE = 9.2; d = 0.34) to WEPS (RMSE = 6.2; RE = 1.0, d = 0.63) to the UPGM (RMSE = 6.1; RE = 0.1; d = 0.70). Incorporating phenological responses to varying water deficits improves the accuracy and robustness of predicting phenology, which is particularly important in spatially distributed agroecosystem models. Core Ideas Phenology is critical in accurately simulating crop production and hydrology. The AgES watershed model evaluated three EPIC‐based plant growth components. Only UPGM was able to simulate phenological responses to varying water deficits. The results promote more robust simulation of phenology in varying environments.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Model and Component Overviewsmentioning

confidence: 99%

See 1 more Smart Citation

Winter Wheat Phenology Simulations Improve when Adding Responses to Water Stress

et al. 2019

View full text Add to dashboard Cite

show abstract

“…This relationship was updated for the High Plains by Kamble et al (2013) and Campos et al (2017). Fine-resolution remote sensing data are now integrated into programs to simulate crop development (phenology) over large Great Plains areas and to follow regional crop rotations (Kipka et al, 2015;McMaster et al, 2013McMaster et al, , 2014. Ongoing research in Nebraska is using this remotesensing-based approach to estimate crop yield and CWP as well as ET (Campos et al, 2018).…”

Section: Future Perspectives Irrigation Technology For Improving Prodmentioning

confidence: 99%

Past, Present, and Future of Irrigation on the U.S. Great Plains

Evett¹,

Colaizzi²,

Lamm

et al. 2020

Transactions of the ASABE

View full text Add to dashboard Cite

Highlights Irrigation is key to the productivity of Great Plains agriculture but is threatened by water scarcity. The irrigated area grew to >9 million ha since 1870, mostly since 1950, but is likely to decline. Changes in climate, water availability, irrigated area, and policy will affect productivity. Adaptation and innovation, hallmarks of Great Plains populations, will ensure future success. Abstract. Motivated by the need for sustainable water management and technology for next-generation crop production, the future of irrigation on the U.S. Great Plains was examined through the lenses of past changes in water supply, historical changes in irrigated area, and innovations in irrigation technology, management, and agronomy. We analyzed the history of irrigated agriculture through the 1900s to the present day. We focused particularly on the efficiency and water productivity of irrigation systems (application efficiency, crop water productivity, and irrigation water use productivity) as a connection between water resource management and agricultural production. Technology innovations have greatly increased the efficiency of water application, the productivity of water use, and the agricultural productivity of the Great Plains. We also examined the changes in water stored in the High Plains aquifer, which is the region’s principle supply for irrigation water. Relative to other states, the aquifer has been less impacted in Nebraska, despite large increases in irrigated area. Greatly increased irrigation efficiency has played a role in this, but so have regulations and the recharge to the aquifer from the Nebraska Sand Hills and from rivers crossing the state. The outlook for irrigation is less positive in western Kansas, eastern Colorado, and the Oklahoma and Texas Panhandles. The aquifer in these regions is recharged at rates much less than current pumping, and the aquifer is declining as a result. Improvements in irrigation technology and management plus changes in crops grown have made irrigation ever more efficient and allowed irrigation to continue. There is good reason to expect that future research and development efforts by federal and state researchers, extension specialists, and industry, often in concert, will continue to improve the efficiency and productivity of irrigated agriculture. Public policy changes will also play a role in regulating consumption and motivating on-farm efficiency improvements. Water supplies, while finite, will be stretched much further than projected by some who look only at past rates of consumption. Thus, irrigation will continue to be important economically for an extended period. Sustaining irrigation is crucial to sustained productivity of the Great Plains “bread basket” because on average irrigation doubles the efficiency with which water is turned into crop yields compared with what can be attained in this region with precipitation alone. Lessons learned from the Great Plains are relevant to irrigation in semi-arid and subhumid areas worldwide. Keywords: Center pivot, Crop water productivity, History, Sprinkler irrigation, Subsurface drip irrigation, Water use efficiency.

show abstract

“…The objectives of PhenologyMMS are to (1) provide a relatively easy tool to producers, consultants, and scientists to predict crop developmental stages and provide information about crop phenology; and (2) develop seedling emergence and crop phenology science simulation components that could be inserted into other crop simulation models. Additional details on PhenologyMMS not covered below can be found in [19,[28][29][30], and PhenologyMMS can be downloaded at ARS Agricultural Software Download and Applications website [31].…”

Section: Phenologymms Decision Support Tool Overview and Default Paramentioning

confidence: 99%

Simulating the Probability of Grain Sorghum Maturity before the First Frost in Northeastern Colorado

et al. 2016

View full text Add to dashboard Cite

Expanding grain sorghum [Sorghum bicolor (L.) Moench] production northward from southeastern Colorado is thought to be limited by shorter growing seasons due to lower temperatures and earlier frost dates. This study used a simulation model for predicting crop phenology (PhenologyMMS) to estimate the probability of reaching physiological maturity before the first fall frost for a variety of agronomic practices in northeastern Colorado. Physiological maturity for seven planting dates (1 May to 12 June), four seedbed moisture conditions affecting seedling emergence (from Optimum to Planted in Dust), and three maturity classes (Early, Medium, and Late) were simulated using historical weather data from nine locations for both irrigated and dryland phenological parameters. The probability of reaching maturity before the first frost was slightly higher under dryland conditions, decreased as latitude, longitude, and elevation increased, planting date was delayed, and for later maturity classes. The results provide producers with estimates of the reliability of growing grain sorghum in northeastern Colorado.

show abstract

Simulating Crop Phenological Responses to Water Stress Using the PhenologyMMS Software Program

Cited by 15 publications

References 0 publications

Winter Wheat Phenology Simulations Improve when Adding Responses to Water Stress

Winter Wheat Phenology Simulations Improve when Adding Responses to Water Stress

Past, Present, and Future of Irrigation on the U.S. Great Plains

Simulating the Probability of Grain Sorghum Maturity before the First Frost in Northeastern Colorado

Contact Info

Product

Resources

About