Drought on the Southern High Plains
Figure 1: Satellite imagery of Dawson County, located in the Southern High Plains of Texas. Located in the center of the county is the Agricultural Complex for Advanced Research and Extension Systems (AG-CARES) farm where we are able to conduct a variety of agricultural research experiments in semi-arid Amarillo fine sandy loam soils. All images were obtained through Sentinel-Hub.
The semi-arid southern portion of the Great Plains, the Southern High Plains (SHP), produces an estimated 30% of the U.S. annual cotton production and receives approximately 90% of its irrigation demand from the Ogallala Aquifer (Colaizzi et al., 2009; Burke et al., 2021). However, the aquifer is a closed basin, and the recharge rate is dependent on precipitation. The saturated thickness and subsequent water quality of certain areas of the aquifer are decreasing at an unsustainable rate due to the withdrawal far exceeding the annual recharge rate. Projected climate change is expected to compound the issue with predicted increases in annual temperature in the SHP paired alongside more frequent extreme weather events such as droughts and dust storms (Banner et al., 2010; U.S. Global Change Research Program, 2018). As a result, many producers in this region have been transitioning to dryland cotton production systems (Ale et al., 2021). The continued unsustainable withdrawal of the groundwater from the Ogallala Aquifer for irrigation, paired with the potential increase in annual mean temperature due to climate change puts the future agricultural viability of the region at risk.
We are currently researching how regenerative agricultural practices can be optimized for the harsh conditions of the SHP in order to increase soil moisture storage, infiltration, and water-use efficiency while simultaneously reducing evapotranspiration. Figures 2 & 3 display the annual fluctuations in vegetative growth and water stress across the county. These figures evince the dynamic nature and annual intensification of agriculture across the SHP.
Christopher Cobos- Christopher.cobos@ag.tamu.edu
Figure 2: The normalized difference moisture index (NDMI) for Dawson County from January 2021 to March 2022. NDMI is used to determine vegetation water content and monitor droughts. The value range of the NDMI is -1 to 1. Negative values of NDMI (values approaching -1; indicated in red) correspond to barren soil. Values around zero (-0.2 to 0.4; indicated in green) generally correspond to water stress. High, positive values represent high canopy without water stress (approximately 0.4 to 1; indicated in blue).
Figure 3: The normalized difference vegetation index (NDVI) for Dawson County from January 2021 to March 2022. NDVI is a simple, but effective index for quantifying green vegetation. It is a measure of the state of vegetation health based on how plants reflect light at certain wavelengths. The value range of the NDVI is -1 to 1. Negative values of NDVI (values approaching -1; indicated in black) correspond to water. Values close to zero (-0.1 to 0.1; indicated in white) generally correspond to barren areas of rock, sand, or snow. Low, positive values represent shrub and grassland (approximately 0.2 to 0.4; indicated in light green), while high values indicate temperate and tropical rainforests (values approaching 1; indicated in dark green). In the figure above, values approaching 1 can generally be attributed to annual cotton crops across the county.
