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This study assesses the water availability and the water scarcity based on the hydrologic behavior under different weather conditions and crop coverages in an irrigated agricultural area of Rincon Valley in New Mexico using the SWAT (Soil and Water Assessment Tool) model. Two spatial crop coverages included normal (2008) and dry (2011) years with 14 different crop sets for each year. The SWAT was applied to generate the five essential indicators (surface flow, evapotranspiration, soil water, groundwater recharge, and irrigation water) to evaluate the integrated water availability based on hydrologic response units (HRUs) along with the Arrey Canal to supply irrigation water in the crop areas. The water availability index scores (0–1 range with 1 being the most available and 0 the least available) of alfalfa, corn, cotton, and pecans were 0.21, 0.56, 0.91, and 0.20, respectively, in the normal year and 0.16, 0.78, 0.88, and 0.24, respectively, in the dry year. In the dry year, water scarcity values were high in mostly alfalfa areas, whereas cotton areas have mostly no stress with good water availability. The major water users of crops, ranked in order, were alfalfa, pecans, cotton, and corn. During the dry year, water availability showed to be balanced in terms of water supply and demand by controlling crop patterns from reducing alfalfa acreage by 12% and increasing cotton acreage by 13%. [ABSTRACT FROM AUTHOR]

Unlike rivers in humid regions, dryland rivers typically exhibit reduced flow in the downstream direction as a result of transmission losses, which include seepage of streamflow into the aquifer, evaporation, and transpiration. However, much remains to be learned about the nature of the exchange between surface water and groundwater in these landscapes, especially in terms of spatial and temporal variability. Our study focused on streambank seepage and groundwater flow in the alluvial aquifer, specifically on answering questions such as: Is there seasonal variability in seepage losses? Is seepage permanently lost? Can losses be reduced by killing riparian vegetation? To better understand the magnitude, variability, and fate of streambank seepage, we assessed river stages, groundwater hydraulic gradients, and groundwater flow paths at two sites along a reach of the Pecos River, a dryland perennial river in West Texas. We found that along this reach the river was losing water to the aquifer even under low-flow conditions; but seepage was controlled by a number of different mechanisms. Seepage increased not only during high-flow events but also when the groundwater level was declining owing to long periods of no irrigation release. Tamarix (saltcedar) control did not affect hydraulic gradients nor reduce streambank seepage and given that this reach of the Pecos River is a losing one, streamflow will not be enhanced by controlling saltcedar. These findings can be used to improve basic conceptual models of dryland river systems and to predict hydrologic responses to changes in the timing and magnitude of streamflows and to riparian vegetation management. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abudu, S., J.P. King, Z. Sheng, 2011. Comparison of the Performance of Statistical Models in Forecasting Monthly Total Dissolved Solids in the Rio Grande. Journal of the American Water Resources Association (JAWRA) 48(1): 10-23. DOI: 10.1111/j.1752-1688.2011.00587.x Abstract: This paper presents the application of autoregressive integrated moving average (ARIMA), transfer function-noise (TFN), and artificial neural networks (ANNs) modeling approaches in forecasting monthly total dissolved solids (TDS) of water in the Rio Grande at El Paso, Texas. Predictability analysis was performed between the precipitation, temperature, streamflow rates at the site, releases from upstream reservoirs, and monthly TDS using cross-correlation statistical tests. The chi-square test results indicated that the average monthly temperature and precipitation did not show significant predictability on monthly TDS series. The performances of one- to three-month-ahead model forecasts for the testing period of 1984-1994 showed that the TFN model that incorporated the streamflow rates at the site and Caballo Reservoir release improved monthly TDS forecasts slightly better than the ARIMA models. Except for one-month-ahead forecasts, the ANN models using the streamflow rates at the site as inputs resulted in no significant improvements over the TFN models at two-month-ahead and three-month-ahead forecasts. For three-month-ahead forecasts, the simple ARIMA showed similar performance compared to all other models. The results of this study suggested that simple deseasonalized ARIMA models could be used in one- to three-month-ahead TDS forecasting at the study site with a simple, explicit model structure and similar model performance as the TFN and ANN models for better water management in the Basin. [ABSTRACT FROM AUTHOR]