Crop Specific Drought Indices For Groundwater Management In The Texas High Plains PDF Download

Severe droughts have plagued the United States over the last few years. The 2011 Texas drought, the 2012 U.S. drought, and the current California drought have greatly impacted the nation's economy and agricultural production. Different crops vary in their response to water stress. Despite this, commonly used drought indices, such as the Palmer Drought Severity Index, do not consider crop specific factors. The goal of this project was to create a methodology to produce crop and location specific drought and yield trend forecasts to help agricultural producers make more informed water management decisions. To achieve this, a drought index was developed and analyzed, weather forecasts were used in a hydrology/crop model to predict hydrologic conditions and crop yields, and an example interactive map interface were created to convey this information to water stakeholders. The drought index uses five parameters that affect or are affected by drought. These parameters include precipitation, temperature, cumulative biomass, soil moisture, and transpiration. Soil moisture and temperature are ranked against crop-specific threshold values, while precipitation and cumulative biomass are ranked against location-specific normal values. Transpiration is ranked against the location-specific potential transpiration. A case study was performed in the Upper Colorado River Basin located in West Texas using this drought index. Cotton is the primary crop grown in the watershed and was used in this study. The Soil and Water Assessment Tool (SWAT) was used to estimate the cumulative biomass, soil moisture, and transpiration. A multiple linear regression model was developed for each week of the growing season based on the significant parameters during that stage of the growing season. These models were used to predict yield trends and drought severity. Two week forecasts for each drought parameter, yield trends, and the drought index were generated for 2010 through 2013 by using forecasted precipitation and temperature data as inputs for the hydrologic and crop model. This provided forecasted soil moisture, transpiration, and cumulative biomass production. Parameter rankings, yield trends, and the drought index were compared for those calculated with actual precipitation and temperature data as well as forecasted precipitation and temperature data. The precipitation ranking, temperature ranking, cumulative biomass ranking, transpiration ranking, estimated yield trends, and drought index indicated satisfactory forecast results. The soil moisture forecast did not result in satisfactory forecast. The final step in the project was to create an example interface for agricultural producers and water managers to view drought related stresses. ArcGIS online was used to create maps which show graphs of the weekly drought index and soil moisture ranking. Maps were created at the county scale. These maps provide agricultural producers readily accessible information that can be used for decision making related to water management. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/155528