Location: Northwest Watershed Research Center
2020 Annual Report
Objectives
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.
Approach
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.
Progress Report
In support of Objective 1, research continued to more accurately quantify mountain precipitation at varying scales and the resultant effects of changes in seasonal precipitation phase on streamflow generation. To address streamflow responses to changes in precipitation phase, researchers in Boise, Idaho, began the initial coupling of a hydrological routing model to the physically based iSnobal snow accumulation and melt model in the Tollgate sub-watershed of Reynolds Creek Experimental Watershed (RCEW) located in Murphy, Idaho, and the larger Tuolumne River basin in California. In order to identify climatic trends across the RCEW, 30 years of snowpack simulations were performed using station measurements of meteorological variables as model input. Researchers have been additionally focused elsewhere in the western United States where long-term measurement records are not available at the scale required for iSnobal and began using long-term (20-30 years) atmospheric reanalysis datasets as forcing data in order to compare snowpack characteristics across different regions. Regarding efforts to more accurately quantify mountain precipitation during the snow accumulation season, researchers began developing a new precipitation rescaling algorithm that relies on high-resolution spatially distributed snow depths from multiple airborne Light Detection and Ranging (LiDAR) surveys. This rescaling will lead to more realistic precipitation distributions in complex mountain terrain when coarse atmospheric model output is used as iSnobal forcing data. Conversely, throughout the melt season, researchers in Boise, Idaho, expanded model validation assessments in real-time using measurements from weather stations and stakeholder snow courses. Monitoring model performance in near-real time allows evaluation of model melt rates across large elevation gradients so that model parameters can be adjusted midseason for more accurate snowmelt predictions. Lastly, researchers have maintained stakeholder relationships in California by continuing to produce biweekly reports of snowpack model results across five large river basins.
In support of Objective 2, ARS researchers worked to better understand and predict how water and temperature control carbon flux into and out of the soil and vegetation by expanding computer simulation modeling capabilities. The Soil Heat and Water (SHAW) model, developed by scientists in Boise, Idaho, was expanded to include calculations of soil carbon dioxide production and diffusion to the atmosphere, providing the ability to calculate soil “losses” over time and with soil depth. Boise, Idaho, scientists collect water, energy, and carbon dioxide flux data using eddy covariance towers and contribute that data to the national Ameriflux Network. Representatives from the Ameriflux Network made a field site visit and provided recommendations that have been implemented assuring that local measurements of energy, water and carbon exchange made at RCEW are of the highest quality. Data from two additional eddy covariance towers in Reynolds Creek have now been submitted to the Ameriflux Network for a total of five sites representing 24 site-years. A portion of the eddy flux data were analyzed and published in a manuscript that evaluates factors controlling wintertime plant and soil respiration. Researchers at Boise, Idaho, also completed a draft of an invited chapter for Modeling Soil-Plant-Climate-Management Processes and Their Interactions in Cropping Systems: Challenges for the 21st Century.
In support of Objective 3, ARS researchers used soil water content, temperature and carbon dioxide measured along a natural climatic gradient imposed by elevation in a sage-steppe ecosystem to determine soil climatic parameters that control emission of soil carbon dioxide. The researchers found that carbon dioxide production varies with 1) depth within the soil profile, 2) elevation within the watershed, and 3) seasonality. Three field sites were located at long-term experimental sites in the RCEW at elevations ranging from 1425 to 2111 m, with corresponding mean annual temperature and precipitation ranges of 9.4 to 5.6 degrees Celsius and 292 to 800 mm, respectively. Snow cover ranged from ephemeral to seasonal with important impacts on soil freeze-thaw dynamics. Co-located eddy covariance data indicate a large productivity gradient with elevation. Rates of carbon dioxide efflux to the atmosphere and production were simulated using estimated values of soil porosity and measured hydraulic characteristics to account for changes in diffusivity with variable soil moisture. Cumulative soil carbon dioxide efflux was controlled by both soil water and temperature and varied considerably among sites. This approach illustrates how the terrestrial carbon balance can be estimated for a variety of environments with the goal of understanding changes in soil carbon at a global scale.
In support of Objective 4, efforts continued to enhance the observational capabilities and research infrastructure in the RCEW and the Great Basin Long-Term Agroecosystem Research (LTAR) network site. To better quantify the critical and often-overlooked role of groundwater in the watershed-scale water balance, ARS scientists at Boise, Idaho, working in conjunction with the Reynolds Creek Critical Zone Observatory (2052-13610-012-27R, "Reynolds Creek Carbon Critical Zone Observatory"), opened over a dozen wells in the lower elevations of RCEW and are currently monitoring groundwater levels at three of those wells. In addition, water samples were taken from each site and are currently undergoing chemical analysis. In an effort to better understand the flow paths that deliver water from snowmelt sources to down slope streams, scientists at Boise, Idaho, working with researchers at the University of Wyoming and Idaho State University, opened a bore hole 300 feet deep to use as “ground truth” for geophysical data and further check on water chemistry.
Accomplishments
1. Reduced wintertime carbon dioxide emission from sagebrush ecosystems. The carbon budget associated with terrestrial ecosystems, such as the vast sagebrush steppe region of North America, is not well understood and accounted for in estimations of the overall global carbon balance. ARS scientists in Boise, Idaho, documented climate warming across the Great Basin causing shifts in winter precipitation from snow to rain and was found to adversely impact wintertime plant and soil respiration, carbon cycling, and carbon storage. Limited carbon dioxide emission was observed at low elevation sites due to lack of snow cover to insulate the soil from freezing, limited water availability, and low soil organic content. Conversely, high soil organic content and a deep winter snowpack at high elevation sites led to increased carbon dioxide emission from increased organic decomposition. These results suggest the future global carbon balance will be negatively impacted by climate induced reductions in snow cover through colder winter soil temperatures, increased soil freezing, and therefore, reduced winter carbon dioxide emissions across sagebrush ecosystems.
Review Publications
Chaubell, J., Yueh, S., Dunbar, S., Colliander, A., Chen, F., Chan, S., Entekhabi, D., Bindlish, R., O'Neill, P., Asansuma, J., Berg, A., Bosch, D.D., Caldwell, T., Cosh, M.H., Holifield Collins, C.D., Martinez-Fernandez, J., Seyfried, M.S., Starks, P.J., Su, Z., Thibeault, M., Walker, J. 2020. Improved SMAP dual-channel algorithm for the retrieval of soil moisture. IEEE Transactions on Geoscience and Remote Sensing. 58(6):3894-3905. https://doi.org/10.1109/TGRS.2019.2959239.
Fellows, A.W., Flerchinger, G.N., Seyfried, M.S., Biederman, J.A., Lohse, K. 2020. Winter CO2 efflux from sagebrush shrublands distributed across the rain-to-snow transition zone. Journal of Geophysical Research-Biogeosciences. 125(2). https://doi.org/10.1029/2019JG005325.
Fullhart, A., Kelleners, T., Chandler, D., McNamara, J., Seyfried, M.S. 2019. Bulk density optimization to determine subsurface hydraulic properties in Rocky Mountain catchments using the GEOtop model. Hydrological Processes. 33(17):2323-2336. https://doi.org/10.1002/hyp.13471.
Hedrick, A., Marks, D.G., Marshall, H., McNamara, J., Havens, S.C., Trujillo, E., Sandusky, M.L., Robertson, M.E., Johnson, M.J., Bormann, K., Painter, T.H. 2020. From drought to flood: A water balance analysis of the Tuolumne River Basin during extreme conditions (2015 – 2017). Hydrological Processes. 34(11):2560-2574. https://doi.org/10.1002/hyp.13749.
Pandit, K., Dashiti, H., Glenn, N., Flores, A., Shinneman, D., Maguire, K., Flerchinger, G.N., Fellows, A.W. 2019. Developing and optimizing shrub parameters representing sagebrush (Artemisia spp.) ecosystems in the northern Great Basin using the Ecosystem Demography (EDv2.2) model. Geoscientific Model Development. 12(11):4585-4601. https://doi.org/10.5194/gmd-12-4585-2019.
Radke, A., Godsey, S., Lohse, K., McCorkle, E., Perdrial, J., Seyfried, M.S., Holbrook, S. 2019. Spatiotemporal heterogeneity of water flowpaths controls dissolved organic carbon sourcing in a snow-dominated, headwater catchment. Frontiers in Ecology and Evolution. 7(46). https://doi.org/10.3389/fevo.2019.00046.
Vega, S., Williams, C.J., Brooks, E., Pierson Jr, F.B., Strand, E., Robichaud, P., Brown, R., Seyfried, M.S., Lohse, K., Glossner, K., Pierce, J., Roehner, C. 2020. Interaction of wind and cold-season hydrologic processes on erosion from complex topography following wildfire in sagebrush steppe. Earth Surface Processes and Landforms. 45(4):841-861. https://doi.org/10.1002/esp.4778.
Zhou, L., Zhao, W., He, J., Flerchinger, G.N., Feng, H. 2019. Simulating soil surface temperature under plastic film mulching during seedling emergence of spring maize with the RZ–SHAW and DNDC models. Soil & Tillage Research. 197. https://doi.org/10.1016/j.still.2019.104517.