Location: Range Management ResearchTitle: Water informatics approach to analyze the dynamics of surface water runoff with climate change
|IFTIKHAR, ISLAM - New Mexico State University|
|BROWN, CHRISTOPHER - New Mexico State University|
Submitted to: American Geophysical Union
Publication Type: Abstract Only
Publication Acceptance Date: 11/5/2019
Publication Date: 12/9/2019
Citation: Iftikhar, I., Elias, E.H., Brown, C. 2019. Water informatics approach to analyze the dynamics of surface water runoff with climate change [abstract]. American Geophysical Union. December 9-13, 2019. San Francisco, California. #H33M-2160.
Technical Abstract: Reduction in precipitation, snowpack, and droughts along with warmer and drier springs have caused water supply in the Rio Grande basin to decrease. Climate change is highly likely to aggravate the scenario here in southwest of U.S. Therefore, the prospects of inadequate surface water runoff, and the effect that climate change is having on stream flow dynamics (and consequently surface water availability) need to be modeled and assessed. The performance of hydrologic models has been improved in recent times in terms of agreement with measured field values, however the models still warrant further exploration in delineating spatially distributed hydrologic and hydrodynamic processes. The intention of the work is to explore how reduced snowpack is impacting estimated runoff. We will also determine the long-term changes of hydrologic patterns in terms of stream flow in response to climate change through performance based hydrologic models' analyses. The first step in this work is a pilot analysis using in situ SNOTEL data in the upper Rio Grande basin to assess several mechanisms likely to impact reduced snowmelt runoff. A subset of hydrologic models (i.e. HEC-HMS, SWAT, ANN) are examined, and these models’ performances will be evaluated through statistical analysis. In latter stages of the research, the best performing hydrologic model will be re-run to project the flow for future climatic scenarios. Hydrological extremes (i.e. low flow, flood) within the regional context will be evaluated through analyzing the seasonal variation of the predicted data. Based on our current literature review, we expect that reduced snowfall, increased sublimation, and lower snow albedo with increased dust will be the contributing factors to runoff reduction.