Research Project: Ecohydrology of Sustainable Mountainous Rangeland Ecosystems

Location: Northwest Watershed Research Center

2023 Annual Report

Objectives
Objective 1) Develop improved snowmelt and streamflow forecasting tools. Sub-objective 1A) Improve spatial representation of precipitation and solar radiation as snow model forcing data. Sub-objective 1B) Develop and improve model linkages between spatially distributed snowmelt and streamflow generation. Objective 2) Quantify and predict terrestrial ecosystem carbon dynamics, including rangeland productivity, soil respiration, carbon flux, and carbon sequestration in response to water availability and climate variability. Sub-objective 2A) Identify and model linkages between climate variability, water availability, and primary productivity. Sub-objective 2B) Improve understanding of soil carbon dynamics related to soil carbon sequestration. Objective 3) Develop long-term observational data sets for climate, hydrology, vegetation, soils, geophysics, and water quality to make inferences about function, long-term productivity and sustainability of rangeland ecosystems that can be widely used in local, regional, and national models and in collaboration with the LTAR network. Sub-objective 3A) Maintain and enhance long-term observational infrastructure for climate, hydrology, vegetation, soils, geophysics, and water quality in support of network wide LTAR collaborations and research community at large. Sub-objective 3B) Quantify climate change effects on hydrology and the past, present, and future sustainability of rangeland ecosystems using the long-term dataset from RCEW.

Approach
Objective 1 builds on the snowmelt and streamflow forecasting advancements made with the iSnobal model during the last five-year project cycle that enabled near real-time snowmelt forecasting in support of operational water supply forecasting and water management. We will take a four-pronged approach to further improve operational streamflow forecasting: 1) We will take advantage of recent advances in estimating precipitation patterns and snow depth over mountainous areas from airplane overflights; 2) We will use satellite observations of solar reflectance, snow cover, and cloud cover to better estimate the solar energy absorbed by the snow; 3) We will develop approaches to estimate streamflow from simulated snowmelt using historical relationships between measured streamflow and simulated snow melt; and 4) We will couple the iSnobal model with an existing model that routes snowmelt water to the stream. In Objective 2, we will combine field observations and modeling tools to better understand and predict water and carbon dynamics in semi-arid rangeland ecosystems. Tools for quantifying and modeling vegetation productivity and carbon storage of sagebrush ecosystems will be developed, providing a better understanding of vegetation productivity and soil carbon sequestration in water-limited ecosystems. Research will capitalize on the network of research sites along an elevation/climate gradient within the Reynolds Creek Experimental Watershed (RCEW). Measurements include CO2 uptake and emission from plants and soil, weather observations, soil temperature/water/CO2 profiles, chambers that measure soil CO2 emission, etc. Annual vegetation surveys and cameras that track plant growth/phenology are available at three of the sites. Using the natural gradient in climate and productivity across the research sites presents a unique opportunity to study factors regulating carbon fluxes and productivity and observe changes in ecosystem function as climate and ecohydrological properties shift. Data will be used to test and improve existing models that simulate management and climate on vegetation productivity and carbon storage within the soil. In Objective 3, we will expand the scientific infrastructure of the RCEW to: 1) quantify offsite transfer of water and carbon in streams and groundwater; 2) measure changes in productivity and carbon cycling as sagebrush ecosystems transition to invasive annual grasses; and 3) support collaborations both within USDA-ARS, especially with the Long-Term Agroecosystem Research (LTAR) network, and with our University collaborators. We also take advantage of our long-term record to document ecohydrological change that has occurred in the past 60 years on the RCEW. Approaches that will be pursued if initial methods are unsuccessful include: 1) using alternative satellite products if the data from the aging MODIS satellite proves problematic, 2) using existing inhouse computational infrastructure if the coupled snowmelt-streamflow model does not lend itself to a High-Performance Cluster, 3) using a different model (UNSATCHEM) if soil inorganic process are significant and cannot be easily implemented into the SHAW model.

Progress Report
In support of Objective 1, collaborative research with University of Utah researchers and the Colorado Basin River Forecast Center resulted in a published manuscript describing the effects of forcing a physics-based snow model (iSnobal) with numerical weather prediction forecasts. ARS researchers in Boise, Idaho, are finalizing a manuscript for submission on improving iSnobal model simulations through integration of satellite-derived snow albedo. A second manuscript, based on validating ground-penetrating radar (GPR)-derived snow density transects using iSnobal estimated snow densities. The precipitation rescaling procedure that performs parameter checks to properly run the Automated Water Supply Model (AWSM) was used to guide snowpack spatial variability for model results in the second manuscript. Detailed information about the measurement network within the Reynolds Creek Experimental Watershed (RCEW) was shared with the International Network for Alpine Research Catchment Hydrology (INARCH) to further the goal of future collaboration with international researchers. Lastly, ARS researchers in Boise, Idaho, have continued to support engineers at the California Department of Water Resources (CADWR) for model support in their endeavor to run the AWSM/iSnobal snow model for forecasting opportunities. Model support has been successful as CADWR has begun modeling 19 basins in the Sierra Nevada to produce high resolution estimates of snow water equivalent for predicting runoff. ARS researchers in Boise, Idaho, support included testing new solar radiation calculations and model sensitivity to varying soil temperatures. CADWR has opted to hire three full-time staff to work on physics-based snow modeling in the Sierra Nevada. In support of Objective 2, manuscripts are under review or near publication on the following research topics: seasonality of evapotranspiration in RCEW; modeling evapotranspiration and gross primary production of sagebrush ecosystems; landcover controls on ground freezing and groundwater recharge in permafrost; methods for unfrozen water and ice content measurement; and evapotranspiration and baseflow control of stream drying. Model runs have been conducted to assess suitability of validation data for sensitivity analysis and optimization of input parameters for simulating soil respiration. An informal collaborative effort was continued with University of Texas, El Paso, to include sites within RCEW as part of the National Science Foundation Critical Zone Network (CZNet) to study dryland soil carbon processes. ARS researchers in Boise, Idaho, in collaboration with colleagues from University of Texas conducted geophysics studies and quantified soil carbon storage at the ARS Kimberly, Idaho, Drylands Critical Zone Observatory site. In support of Objective 3, a manuscript is under review describing stream water quality data on the RCEW. Infrastructure and data collection within Johnston Draw has been expanded to quantify effects of the prescribed fire scheduled for September 2023, including: piezometers; water quality, streamflow, temperature, and soil moisture sensors; and remote sensing from drone flights. Data from the Reynolds Creek Experimental Watershed have been assessed for quality control and public dissemination through 2021. Continued work was performed for quality assurance/quality control of precipitation data measured in Reynolds Creek Experimental Watershed using the Automated Precipitation Correction Program (APCP) for water years 2006–2021, which will lead to a 60-year dataset (1962–2021) of precipitation trends in the watershed. ARS scientists at Boise, Idaho, working in conjunction with the Reynolds Creek Critical Zone Observatory (2052-13610-015-004A, “Collaborative Critical Zone Experimentation”), analyzed geophysical transect data designed to enhance the understanding of aspect effects.

Accomplishments

Review Publications
Flerchinger, G.N., Seyfried, M.S. 2022. Heat transport, water balance, snowpack and soil freezing. In: Ahuja, L.R., Kersebaum, K.C., Wendroth, O., editors. Modeling Processes and Their Interactions in Cropping Systems: Challenges for the 21st Century. Madison, WI: American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc. p. 33-52.
Hale, K., Kiewiet, L., Trujillo, E., Krohe, C., Hedrick, A., Marks, D., Kormos, P., Havens, S.C., McNamara, J., Link, T., Godsey, S. 2022. Drivers of spatiotemporal patterns of surface water inputs in a catchment at the rain-snow transition zone of the water-limited western United States. Journal of Hydrology. 616. Article 128699. https://doi.org/10.1016/j.jhydrol.2022.128699.
Hardegree, S.P., Boehm, A.R., Glenn, N., Sheley, R.L., Reeves, P.A., Pastick, N., Hojjati, A., Boyte, S., Enterkine, J., Moffet, C., Flerchinger, G.N. 2022. Elevation and aspect effects on soil microclimate and the germination timing of fall-planted seeds. Rangeland Ecology and Management. 85:15-27. https://doi.org/10.1016/j.rama.2022.08.003.
Hoover, D.L., Abendroth, L.J., Browning, D.M., Saha, A., Snyder, K.A., Wagle, P., Witthaus, L.M., Baffaut, C., Biederman, J.A., Bosch, D.D., Bracho, R., Busch, D., Clark, P., Ellsworth, P.Z., Fay, P.A., Flerchinger, G.N., Kearney, S.P., Levers, L.R., Saliendra, N.Z., Schmer, M.R., Schomberg, H.H., Scott, R.L. 2022. Indicators of water use efficiency across diverse agroecosystems and spatiotemporal scales. Science of the Total Environment. 864. Article e160992. https://doi.org/10.1016/j.scitotenv.2022.160992.
Hou, B., Jin, H., Flerchinger, G.N., Lv, J., He, H. 2023. Canopy effect: Water vapor transmission in frozen soils with impermeable surface. Acta Geotechnica. https://doi.org/10.1007/s11440-023-01845-0.
Hwang, K., Chandler, D., Flerchinger, G.N. 2023. Ground-based infrared thermometry reveals seasonal evapotranspiration patterns in semiarid rangelands. Hydrological Processes. 37(3). Article e14827. https://doi.org/10.1002/hyp.14827.
Lohse, K., Pierson, D., Patton, N., Sanderman, J., Huber, D., Finney, B., Facer, J., Meyers, J., Seyfried, M.S. 2022. Multiscale responses and recovery of soils to wildfire in a sagebrush steppe ecosystem. Scientific Reports. 12. Article 22438. https://doi.org/10.1038/s41598-022-26849-w.
Lucash, M., Marshall, A., Weiss, S., McNabb, J., Nicolsky, D., Flerchinger, G.N., Link, T., Vogel, J.G., Scheller, R., Abramoff, R.Z., Romanovsky, V. 2023. Burning trees in frozen soil: Simulating fire, vegetation, soil, and hydrology in the boreal forests of Alaska. Ecological Modelling. 481. Article 110367. https://doi.org/10.1016/j.ecolmodel.2023.110367.
Meyer, J., Horel, J., Kormos, P., Hedrick, A., Trujillo, E., Skiles, M. 2023. Operational water forecast ability of the HRRR-iSnobal combination: An evaluation to adapt into production environments. Geoscientific Model Development. 16(1):233-250. https://doi.org/10.5194/gmd-16-233-2023.
Winter-Billington, A., Dadic, R., Moore, D., Flerchinger, G.N., Wagnon, P., Banerjee, A. 2022. Modelling debris-covered glacier ablation using the Simultaneous Heat and Water transport model. Part 1: Model development and application to North Changri Nup. Frontiers in Earth Science. 10. Article 796877. https://doi.org/10.3389/feart.2022.796877.