Location: Watershed Management Research
Project Number: 2052-13610-012-00-D
Project Type: In-House Appropriated
Start Date: Jan 14, 2017
End Date: Jan 13, 2022
1)Quantify and predict the form and spatial distribution of precipitation and snow ablation at different scales and their effects on streamflow forecasting in mountainous terrain. 1A)Quantify changes in the rain/snow transition elevation and analyze the impact these changes will have on water supply for ecosystems and agriculture. 1B)Develop, validate and apply physics-based snow models that integrate the methods from 1A and are capable of real-time operation over large mountain basins. 2)Quantify linkages between water availability, energy balance, and terrestrial carbon dynamics in Great Basin rangeland ecosystems. 2A)Determine water and carbon fluxes along an elevation gradient across the rain/snow transition. 2B)Determine post-fire net ecosystem exchange in the rain/snow transition zone. 3)Determine how spatially variable topography and soil properties affect the spatial and temporal distribution of ET and plant productivity in mountainous terrain in a warming climate. 3A)Quantify the effects of variable slope/aspect and vegetation on soil climate in snow-affected areas. 3B)Measure and simulate the effects of early snow melt on plant water stress and recharge in complex terrain. 4)As part of the LTAR network, and in concert with similar long-term, land-based research infrastructure in the Great Basin region, use the Great Basin LTAR site to improve the observational capabilities and data accessibility of the LTAR network and support research to sustain or enhance agricultural production and environmental quality in agroecosystems characteristic of the region. Research and data collection are planned and implemented based on the LTAR site application and in accordance with the responsibilities outlined in the LTAR Shared Research Strategy, a living document that serves as a roadmap for LTAR implementation. Participation in the LTAR network includes research and data management in support of the ARS GRACEnet and/or Livestock GRACEnet projects. 4A)Enhance observational capabilities and research infrastructure in support of long-term research of Great Basin ecosystem productivity. 4B)Process, clean and publish descriptions of, and have the USDA National Agricultural Library host long-term snow, hydrologic and ecosystem data from the RCEW LTAR. 4C)Create “business as usual” and “aspirational’ production and ecosystem service system scenarios as outlined by the LTAR common experiment. Assess the sustainability of both systems and develop new strategies to enable greater sustainability.
The goal of Obj. 1 is to provide water management agencies improved streamflow forecasts by modifying the research snow model, iSnobal, for real-time operational application over large river basins. A topographically based data distribution utility will be developed using the long data record and distributed measurement network in the Reynolds Creek Experimental Watershed (RCEW) to evaluate the location and stability of the rain/snow transition zone. The ARS snow model iSnobal will be improved and applied over large basins for long periods of time, or in real-time for forecasting purposes, to evaluate its potential as a tool for water resource managers and forecasting. If iSnobal is incompatible with existing water supply models, then modifications to iSnobal will be considered. Obj. 2 will investigate how rangeland water use and productivity are affected across the rain/snow transition by measuring water and carbon fluxes along an elevational gradient that spans the transition elevation. Data from previous studies on energy and water fluxes processed for carbon fluxes will be used to understand fluxes of carbon that are influenced by water availability, climate and soils along a precipitation/elevation gradient subject to climate change. Water, energy and carbon flux data from the Upper Sheep Creek prescribed fire in RCEW will be used to identify relationships between carbon fluxes and vegetation observations before and after prescribed fire, and to assess the effect of fire on CO2 fluxes. Several approaches for assessing the influence of vegetation disturbance have been identified in anticipation that some will not prove useful. After exploring all approaches, a combination of the most fruitful will be pursued. In Obj. 3, measured soil climate data and model simulation will be used to evaluate how local variations in snow melt will affect plant water stress and recharge. Using existing measured data from two past RCEW studies in the rain/snow transition zone, the Simultaneous Heat and Water (SHAW) model will be used to simulate soil climate, snowmelt dynamics, deep percolation and evapotranspiration for varying slope, aspect and vegetative cover conditions. The impact of transitioning from snow to rain on ecohydrologic processes will be evaluated using existing RCEW data and field instrumentation to determine the correlation between melt out and dry down dates and the effect of melt out date on recharge and plant water stress. If existing data and simulation models used are found inadequate, new data will be collected and/or different models will be tested and applied. Obj. 4 will continue detailed environmental monitoring and data sharing in support of the Long-Term Agroecosystem Research (LTAR) network in order to determine productivity of critical Great Basin shrub-steppe ecosystems. The ability to study long-term effects of management practices on ecosystem productivity will be improved by enhancing observational capabilities and publishing research data sets for use by the larger scientific community in and outside ARS. If data sets cannot be published by the National Agricultural Library, other data outlets will be considered.