lash drought is generally understood to be the rapid onset or intensification of relatively short-term agricultural drought. It occurs because of lower-than-normal rates of precipitation accompanied by abnormally high temperatures, winds and solar radiation. Together, these changes increase evapotranspiration and rapidly lower soil moisture. In sandy soils with low water-holding capacity, flash drought may quickly result in crop water stress and, depending on crop growth stage, significant yield losses to rainfed crops. The U.S. Drought Monitor, which is often used to justify federal assistance for crop damage resulting from drought, may not always identify localized flash droughts.
An ongoing study funded by the National Oceanic and Atmospheric Administration that is being conducted by the University of Alabama-Huntsville, the University of Florida and the University of Georgia is developing methods for identifying and quantifying the effect of flash drought with each university focusing on different strategies. UGA is focusing on using a mathematical modeling approach to address this problem.
Building a model
Over the past few years, UGA and UF have worked together to develop a suite of smartphone-based irrigation scheduling apps called the SmartIrrigation apps. Among other crops, these apps are available for corn, cotton and soybeans. Apps for peanuts and forages are under development. The apps use weather data to estimate daily crop water use and utilize this information to calculate the amount of plant available water available in the soil profile. They have been extensively tested in southern Georgia and northern Florida and perform as well as soil moisture sensors in scheduling irrigation.
For this project, the cotton, corn and forages SmartIrrigation apps are being used to identify periods when soil moisture becomes dangerously low under rainfed conditions.
In most situations, we irrigate crops when plant available soil moisture drops below 50%. We trigger irrigation at this level to ensure that we have a time buffer in which to apply water before the crops begin to experience water stress. When plant-available soil water drops below 30%, the remaining soil water can be rapidly used by crops, especially in sandy soils, and result in crop water stress. This level is also referred to as a 70% soil water deficit.
Drought effects
Based on evaluations with a sophisticated crop growth model described below, we defined flash drought as seven or more days during which plant-available soil water, as determined by the apps, is continuously less than 30%. We ran the corn, cotton and forages apps for virtual rainfed fields of each crop at the 42 UF and 88 UGA weather station locations for the past five years and identified periods of flash drought based on our definition.
Figure 1 shows a period of flash drought identified by the corn app for the Tifton, Georgia, weather station virtual field between May 23 and June 7, 2021. During this period, the soil water deficit exceeded 80% for 16 days and reached 100% (no plant-available soil water) for 10 days. Although this condition does not occur every year, it does occur occasionally.
Figure 2 shows that the U.S. Drought Monitor did not recognize the occurrence of drought in Tift County (where Tifton is located) during this period, primarily because the drought monitor is not designed to take into account the crop water use of specific crops.
To assess the effect of this duration of flash drought on crop yield, we used the Decision Support System for Agrotechnology Transfer Ceres-Maize corn simulation model. This is a widely used model that can quantify the crop’s physiological stress as well as predict yields under a variety of growing conditions. In our case, we calibrated the model using experimental data from Tifton and then simulated the growth of a rainfed corn crop for each of the 30 years for which we had data from the Tifton UGA weather station. The predicted average rainfed yield for the 30 years of simulation was 83 bushels per acre.
To simulate the effect of flash drought on yield, we artificially suppressed rain for two-week periods in each of the simulation years. For example, we did not allow any rain for the period of May 1 to May 15 for each of the simulated 30 years. Then we ran the model again and did not allow any rain from May 16 to May 30, and so on. Crops are generally most sensitive to water stress during the reproductive phase because water stress during this phase can negatively affect yield potential. In southern Georgia, corn is typically planted in late March, and it is in its reproductive phase from mid-May through the end of June.
Figure 3 shows the percent reduction in yield compared to the 30-year rainfed average if flash drought occurs for the given two-week periods during corn’s reproductive phase. For Tifton, Georgia, the most sensitive two-week period is between June 1 and June 15, during which flash drought in rainfed corn results in yield reductions as high as 60%. This is the predicted average reduction for the 30-year simulation period. Consequently, the timing of flash drought is as important as its duration in determining yield losses.
Figure 4 shows the simulation results for Quincy, Florida, where the 30-year rainfed average corn yield is 125 bushels per acre. Again, the most sensitive period is between June 1 to June 15, during which flash drought in rainfed corn results in yield reductions larger than 40%.
The deliverable of this project is to develop a database showing the expected yield losses from flash drought for corn, cotton and forages in southern Alabama, southern Georgia and northern Florida. Another goal is to use the SmartIrrigation apps as sentinels to warn growers that their crops are experiencing yield-damaging periods of flash drought.
Armed with this information, growers may be able to seek federal assistance for rainfed crop damage resulting from flash drought. The information is also useful for irrigated crop growers to reference flash drought impact. The SmartIrrigation apps are available to all growers at no cost.