Research > Geospatial Hydrology


Recent News from the Lab

The ever-increasing pressure for land and water resources requires their efficient use to meet various agricultural and non-agricultural needs. The overall goal of the Geospatial Hydrology research program is to develop and evaluate strategies that conserve soil and water, promote water use efficiency, and protect soil and water quality in diverse agro-ecosystems under changing climate.

The specific program objectives are to:

  1. Develop strategies for efficient utilization of land and water resources on crop, pasture and grazing lands under current and future climate change scenarios.
  2. Assess the hydrologic and environmental impacts of changes in land use and management, climate, and rangeland management.
  3. Identify the causes of soil degradation and sources of water quality impairment, and suggest best management practices for protecting soil and water quality.

We use a combination of simulation, field experimentation and observed data analysis approaches to achieve the above program objectives. We use several geospatial and geostatistical techniques, and hydrologic, water quality and crop growth models such as the Soil and Water Assessment Tool (SWAT), Agricultural Policy/Environmental eXtender (APEX), Decision Support System for Agrotechnology Transfer (DSSAT), DRAINMOD and ADAPT.

Current Research


Assessing grazing management impacts on hydrology, and soil and water quality at the ranch and watershed scales

Both rural and urban populations depend on ecosystem services provided by rangelands. Ecosystem services can include maintaining stable and productive soils, delivering clean water, and sustaining plants, animals and other organisms that support livelihoods and human aesthetic and cultural values. It is therefore important for ranch/land managers to adopt management practices that maintain or restore soil and ecosystem health and resilience. Grazing management practices have a significant influence on water catchment functions and soil health.

The overall goal of this project is to assess the ranch and watershed scale impacts of traditional continuous grazing and alternate adaptive multi-paddock grazing practices on key ecosystem services provided by rangelands, and suggest best grazing management practices using the SWAT and APEX models. The specific objectives are to:

  1. Evaluate the impacts of light and heavy continuous, and adaptive multi-paddock grazing management practices on water storage, water erosion, water quality, nutrient retention, soil carbon sequestration and downstream flooding risk in selected watersheds in the Southern and Northern Great Plains.
  2. Assess the impacts of climate variability and change on water catchment functions, sediment and nutrient losses, and streamflow characteristics under different grazing management practices, and suggest potential climate change adaptation/mitigation strategies.

Study Results

Results from the Clear Creek watershed (71% rangelands) study in north central Texas indicated that the simulated annual surface runoff, and sediment and nutrient losses reduced by about 31%-40% under the adaptive multi-paddock grazing when compared to traditional heavy continuous grazing. Adaptive MP grazing has also reduced the simulated highest annual streamflow by 25% and hence demonstrated the potential to reduce the risk of flooding downstream.

We are currently extending this study to the Apple watershed in North Dakota and the Lower Prairie Dog Town Fork Red watershed in northwest Texas and are interested in assessing the impacts of grazing management on soil carbon sequestration in addition to hydrology and water quality.

Development and evaluation of efficient irrigation and crop management strategies for crop production under current and future climatic conditions

Agriculture in the semi-arid Texas High Plans and Rolling Plains region is facing many challenges from rapid declines in groundwater levels, recurring droughts in the recent times, and projected warmer and drier summers in the future. We use different crop modules available in the DSSAT Cropping System Model (CSM) to develop and evaluate environmentally and economically sustainable cropping systems and production practices for the region under the current and future climate change scenarios.

The specific objectives of this study are to:

  1. Evaluate cotton, wheat, sorghum, and guar modules in the DSSAT CSM for the Texas High Plains and Rolling Plains region using the measured data from ongoing and past field experiments.
  2. Develop and evaluate efficient irrigation and crop management strategies for crop production, and formulate decision support tools using the evaluated crop modules. Some examples include:
    1. Determine the optimum periods for terminating irrigation for cotton in the Texas High Plains.
    2. Evaluate the feasibility of growing winter wheat cover crop in cotton production systems of the Texas High Plains and Rolling Plains and determine optimum cover crop termination dates.
  3. Assess the impacts of historic and future climate variability and change on crop production, water use and soil carbon sequestration, and suggest climate change mitigation/adaptation strategies.

Study Results

An investigation of the impact of potential changes in future climate in the Texas High Plains under the Intergovernmental Panel on Climate Change (IPCC) A2 scenario using the climate data projected by three Regional Climate Models (RCMs); RCM3-GFDL, RCM3-CGCM3 and CRCM-CCSM on seed cotton yield indicated that the simulated future average (2041-2070) seed cotton yield would increase within a range of 14% to 29% as compared to historic average (1971-2000) yield.

The results from this study implied that cotton is sensitive to atmospheric carbon dioxide concentrations. We also determined that cotton production in this region could potentially withstand the effects of future climate variability under moderate increases in carbon dioxide levels if irrigation water availability remains at current levels. Assessment of climate change impacts on other important crops in this region such as grain sorghum, corn and winter wheat, and evaluation of water use-efficient strategies for these crops are in progress.

Assessing the impacts of biofuel-induced land use change on watershed hydrology and water quality

The increasing demand for land for biofuel production in the U.S. has led to increased competition for productive agricultural land, shifts in land use among different crops, and conversion of land from other uses into biofuel production. About half of the targeted second-generation biofuels for 2022 is identified to be produced in the Southeastern Region of the U.S, which includes several states traditionally in the U.S. Cotton Belt. USDA estimates that approximately 11.4% of existing croplands and pastures in this region will be required for second-generation biofuel production. The overall goal of this study is to assess the hydrologic and water quality impacts associated with the change in agricultural land use to biofuels-dominated cropping systems in the semi-arid Southwestern U.S. Cotton Belt region using the SWAT, APEX and Integrated SWAT-APEX models. The specific objectives are to:

  1. Assess the impacts of potential land use change from cotton to cellulosic bioenergy crops such as Alamo switchgrass, Miscanthus, big bluestem and biomass sorghum on water balances and water quality at the landscape and watershed scales.
  2. Study the effects of historic and future climate variability on water balances, sediment and nutrient loads, and crop yields under baseline and biofuel-induced land use change scenarios.

Study Results

Results from the Double Mountain Fork Brazos watershed in the Southern High Plains of Texas indicated that Miscanthus and switchgrass would serve as ideal bioenergy crops for the dryland and irrigated systems, respectively. This is due to their higher water use efficiency, better water conservation and water quality improvement effects, greater biomass and biofuel production potential, and minimum crop management requirements.

Replacing cotton with perennial grasses (switchgrass in irrigated areas and Miscanthus in drylands) decreased simulated annual surface runoff, total nitrogen load through surface runoff and nitrate leaching to groundwater by 88%, 86% and 100%, respectively and increased percolation by 28%. The climate change analysis indicated that the simulated annual irrigation water use and total nitrogen load under the future perennial grass land uses would reduce by 60% and 30%, respectively, when compared to future cotton land use.

Assessment of spatio-temporal variability of groundwater quality and availability in Texas

Texas is largely dependent upon groundwater resources. About 59% of state’s total water supply and about 99% of the rural household needs are met from the groundwater extracted from 9 major and 21 minor aquifers of the state. Future projections, however, indicate about 30% reduction in water availability over the next few decades due to adverse climatic conditions and depletion of major aquifers. Numerous studies have documented groundwater quality degradation in several parts of the state, which threatens community welfare and sustainable development.

In the face of snowballing crises of water availability and water quality deterioration, the overall objective of this study is to identify long-term spatio-temporal trends in groundwater levels and groundwater quality across the state and unravel the nexus between the two.

We integrate different geochemical, graphical, and statistical techniques within a geospatial environment to seek answers to questions such as:

  1. Where are the hotspots of groundwater contamination and groundwater level declines?
  2. Is groundwater contamination a manifestation of changes in groundwater levels?
  3. What are the potential causes of groundwater contamination and groundwater level declines?
  4. What are the effects of different agricultural and land management practices on groundwater quality and availability?
  5. What are the best management practices for conserving groundwater resources and protecting water quality?

Study Results

Our long-term assessment of groundwater quality (nitrates, fluoride and salinity) in several major and minor aquifers of Texas has provided more insights into various factors that affected groundwater quality and led to identification of groundwater quality degradation hotspots. We have also delineated spatially associated zones of groundwater level declines in Texas, and identified hotspots that warrant implementation of appropriate management strategies. The state-wide decadal median groundwater levels in Texas were found to decline from about 14 m from land surface in the 1930s to about 36 m in the 2000s. Groundwater level declines across the state, however, mostly followed logarithmic trends marked by levelling-off phenomena in recent times due to implementation of conservation measures and regulatory strategies.

Dr. Srinivasulu Ale

Photo of Srinivasulu Ale

Associate Professor and Geospatial Hydrologist at the Texas A&M AgriLife Research Center at Vernon.

He has extensive research experience in hydrologic, water quality and crop growth modeling, and he has lead or contributed to various research projects in the USA, India, and the Netherlands.

Download CV

Team Members

  • Dr. JungJin Kim, Postdoctoral Research Associate (Range Hydrology).
  • Dr. Sushil Himanshu, Postdoctoral Research Associate (Geospatial Hydrology)
  • Ms. Kritika Kothari, Ph.D. Candidate, Dept. of Biological & Agricultural Engineering, TAMU, College Station (co-advised by Dr. Clyde Munster and Dr. Srinivasulu Ale).
  • Mr. Abhinav Kandpal, M.Eng. student, Dept. of Biological & Agricultural Engineering, TAMU, College Station (co-advised by Dr. Srinivasulu Ale and Dr. Clyde Munster).


Selected recent important journal articles that cover our research interests/areas

For a complete list of publications from our group, please refer to my homepage on Google Scholar or Research Gate.

(*Post-Doc supervisee            **Graduate Student advisee/co-advisee)

  1. Chen**, Y., S. Ale, and N. Rajan. 2018. Implications of Biofuel-Induced Changes in Land Use and Crop Management on Sustainability of Agriculture in the Texas High PlainsBiomass and Bioenergy. 111: 13-21.
  2. Adhikari*, P., N. Omani*, S. Ale, P.B. DeLaune, K. R. Thorp, E.M. Barnes, and G. Hoogenboom. 2017. Simulated effects of winter wheat cover crop on cotton production systems of the Texas Rolling PlainsTransactions of ASABE. 60(6): 2083-2096.
  3. Chen**, Y., S. Ale, N. Rajan, and C.L. Munster. 2017. Assessing the hydrologic and water quality impacts of biofuel-induced changes in land use and managementGlobal Change Biology – Bioenergy. 9(9): 1461-1475.
  4. Park*, J., S. Ale, W.R. Teague, and J. Jeong. 2017. Evaluating the ranch and watershed scale impacts of using traditional and adaptive multi-paddock grazing on runoff, sediment, and nutrient losses in North TexasAgriculture, Ecosystems and Environment. 240: 32-44.
  5. Park*, J., S. Ale, W.R. Teague, and S.L. Dowhower. 2017. Simulating hydrologic responses to alternate grazing management practices at the ranch and watershed scalesJournal of Soil and Water Conservation. 72(2): 102-121.
  6. Chen**, Y., S. Ale, and N. Rajan. 2016. Spatial variability of biofuel production potential and hydrologic fluxes of land use change from cotton (Gossypium hirsutum L.) to Alamo switchgrass (Panicum virgatum L.) in the Texas High PlainsBioEnergy Research. 9(4): 1126-1141.
  7. Modala**, N.R., S. Ale, D. Goldberg, M. Olivares, C. Munster, N. Rajan and R. Feagin. 2017. Climate change projections for the Texas High Plains and Rolling PlainsTheoretical and Applied Climatology. 129(1): 263-280.
  8. Adhikari*, P., S. Ale, J.P. Bordovsky, K. R. Thorp, N.R. Modala, N. Rajan, and E.M. Barnes. 2016. Simulating future climate change impacts on seed cotton yield in the Texas High Plains using the CSM-CROPGRO-Cotton modelAgricultural Water Management.164:317-330.
  9. Modala**, N.R., S. Ale, N. Rajan, C. Munster, P.B. DeLaune, K. R. Thorp, S. Nair and E. Barnes. 2015. Evaluation of the CSM-CROPGRO-Cotton model for the Texas Rolling Plains region and simulation of deficit irrigation strategies for increasing water use efficiencyTransactions of the ASABE. 58(3): 685-696.
  10. Daggupati, P., N. Pai, S. Ale, K.R. Douglas-Mankin, R. Zeckoski, J. Jeong, P.B. Parajuli, Saraswat, D., and M.A. Youssef. 2015. A recommended calibration and validation strategy for hydrologic and water quality modelsTransactions of the ASABE. 58(6): 1705-1719.
  11. Chaudhuri*, S. and S. Ale, 2014. Long-term (1930-2010) trends in groundwater levels in Texas: Influences of soils, landcover and water useScience of the Total Environment. 490: 379-390.
  12. Chaudhuri*, S. and S. Ale, 2014. Lon-term (1960-2010) trends in groundwater contamination and salinization in the Ogallala aquifer in Texas, USAJournal of Hydrology. 513: 376-390.
  13. Ale, S., P.H. Gowda, D.J. Mulla, D.N. Moriasi, and M.A. Youssef 2013. Comparison of the performances of DRAINMOD-NII and ADAPT models in simulating nitrate losses from subsurface drainage systemsAgricultural Water Management. 129: 21-30.