Climate change projections for the Texas High Plains and Rolling Plains

Potential changes in future climate in the Texas Plains region were investigated in the context of agriculture by analyzing three climate model projections under the A2 climate scenario (medium–high emission scenario). Spatially downscaled historic (1971–2000) and future (2041–2070) climate datasets (rainfall and temperature) were downloaded from the North American Regional Climate Change Assessment Program (NARCCAP). Climate variables predicted by three regional climate models (RCMs) namely the Regional Climate Model Version3–Geophysical Fluid Dynamics Laboratory (RCM3-GFDL), Regional Climate Model Version3–Third Generation Coupled Global Climate Model (RCM3-CGCM3), and Canadian Regional Climate Model–Community Climate System Model (CRCM-CCSM) were evaluated in this study. Gaussian and Gamma distribution mapping techniques were employed to remove the bias in temperature and rainfall data, respectively. Both the minimum and maximum temperatures across the study region in the future showed an upward trend, with the temperatures increasing in the range of 1.9 to 2.9 °C and 2.0 to 3.2 °C, respectively. All three climate models predicted a decline in rainfall within a range of 30 to 127 mm in majority of counties across the study region. In addition, they predicted an increase in the intensity of extreme rainfall events in the future. The frost-free season as predicted by the three models showed an increase by 2.6–3.4 weeks across the region, and the number of frost days declined by 17.9 to 30 %. Overall, these projections indicate considerable changes to the climate in the Texas Plains region in the future, and these changes could potentially impact agriculture in this region.

     

Groundwater App to Determine Flow Direction and Gradient

A computational program, called the groundwater flow calculator, was created to quickly and easily determine the hydraulic gradient and direction of groundwater flow. The groundwater flow calculator automates the hand‐drawn process by Ralph Heath in the U.S. Geological Survey (USGS) Water Supply Paper 2220. In addition, a mobile app was developed to allow this procedure to run on a smart phone for use in the field.     

Field Test of the In Situ Permeable Ground Water Flow Sensor

Two in situ permeable flow sensors, recently developed at Sandia National Laboratories, were field tested at the Brazos River Hydrologic Field Site near College Station, Texas. The flow sensors use a thermal perturbation technique to quantify the magnitude and direction of ground water flow in three dimensions. Two aquifer pumping tests lasting eight and 13 days were used to field test the flow sensors. Components of ground water flow as determined from piezometer gradient measurements were compared with ground water flow components derived from the 3-D flow sensors. The changes in velocity magnitude and direction of ground water flow induced by the pump were evaluated using flow sensor data and piezometric analyses. Flow sensor performance closely matched piezometric analysis results. Ground water flow direction (azimuth), as measured by the flow sensors and derived in the piezometric analysis, predicted the position of the pumping well accurately. Ground water flow velocities measured by the flow sensors compared well to velocities derived in the piezometric analysis. A significant delay in flow sensor response to relatively rapid changes in ground water flow was observed. Preliminary tests indicate that the in situ permeable flow sensor provides accurate and timely information on the velocity magnitude and direction of ground water flow.     

Seasonal variation of infiltration rates through pond bed in a managed aquifer recharge system in St-André, Belgium

In Belgium, IWVA uses managed aquifer recharge (MAR) to recharge the aquifer with treated wastewater generated from the communities to sustain the potable water supply on the Belgian coast. This MAR facility is faced with a challenge of reduced infiltration rates during the winter season when pond water temperatures near 4°C. This study involves the identification of the predominant factor influencing the rate of infiltration through the pond bed. Several factors, including pumping rates, natural recharge, tidal influences of the North Sea and pond-water temperature, were identified as potential causes for variation of the recharge rate. Correlation statistics and linear regression analysis were used to determine the sensitivity of the infiltration rate to the aforementioned factors. Two groundwater flow models were developed in visual MODFLOW to simulate the water movement under the pond bed and to obtain the differences in flux to track the effects of variation of hydraulic conductivity during the two seasons. A 32% reduction in vertical hydraulic gradient in the top portion of the aquifer was observed in winter, causing the recharge rates to fluctuate. Results showed that water temperature caused a 30% increase in hydraulic conductivity in summer as compared with winter and has the maximum impact on infiltration rate. Cyclic variations in water viscosity, occurring because of seasonal temperature changes, influence the saturated hydraulic conductivity of the pond bed. Results from the models confirm the impact on infiltration rate by temperature-influenced hydraulic conductivity.