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ARS Home » Pacific West Area » Boise, Idaho » Northwest Watershed Research Center » Research » Research Project #432406

Research Project: Ecohydrology of Mountainous Terrain in a Changing Climate

Location: Northwest Watershed Research Center

2019 Annual Report

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.

Progress Report
In regard to Objective 1, research continued quantifying and predicting the form and spatial distribution of precipitation and snow ablation at different scales and their effects on streamflow forecasting in mountainous terrain. The efforts under this objective continue to be directed towards applying-model predicted snow accumulation and melt to practical management of large basins, primarily in California. During 2019, the modeling domain for real-time simulation test and evaluation of ARS’ snow modeling and water supply forecasting program was expanded from two basins to six basins, representing most of the southern Sierra Nevada in California. This expansion represents a change from about 6,000 km2 to just over 10,000 km2 of modeled area, and from 2,300,000 to 4,100,000 50x50m model cells. The region modeled produced around 10,000,000 acre-feet of water in 2019, which represents about one third of the agricultural water supply for California. This model application was possible because researchers at Boise, Idaho, incorporated new scientific advancements into the Spatial Modeling Resource Framework (SMRF), and the Automated Water Supply Model (AWSM) previously developed in Boise, Idaho, explored the use of modeled weather outputs to replace intensive and costly processing of weather station data, and optimized highspeed computations using a computing cluster. The majority of aspects of the real-time simulation evaluation were fully automated. During the 2019 snow season, researchers at Boise, Idaho, generated 100 water supply reports for stakeholders. Many of the stakeholders are now using information from the water supply reports in their water supply, flood, and reservoir forecasts. Researchers at Boise, Idaho, also implemented an automated report generation utility for interested stakeholders. The stakeholders are now able to independently check the status of snow and water storage daily. In regard to Objective 2, researchers at Boise, Idaho, continued research on quantifying the linkages between water availability, energy balance, and terrestrial carbon dynamics in dominant Great Basin rangeland ecosystems. Four years of data has been collected using eddy covariance systems at the three core study sites in Reynolds Creek Experimental Watershed (RCEW) located in Murphy, Idaho, operated in conjunction with the Reynolds Creek Critical Zone Observatory (2052-13610-012-27R,"Reynolds Creek Carbon Critical Zone Observatory"), were processed, analyzed and submitted to the AmeriFlux Network. Data from each of these sites have been downloaded over 50 times by other researchers this year. A manuscript that evaluates factors controlling wintertime plant and soil respiration has been prepared and submitted. Researchers at Boise, Idaho, found an important interplay between the timing of soil water availability and temperature restrictions to plant growth that vary both inter-annually and with elevation. That is, water availability generally increases with elevation, while temperature restrictions increase with the cooler, higher elevation. The length of the snow-covered season is a critical variable that is expected to change (decrease) over time. A manuscript describing the controls on vegetation production for two contrasting rangeland ecosystems was published this year. Such collaborative efforts with colleagues have also improved modeling of sagebrush phenology and evapotranspiration from stony rangeland soils. In regard to Objective 3, research continued on determining how spatially variable topography and soil properties affect the spatial and temporal distribution of Evapotranspiration (ET), as well as plant productivity in mountainous terrain in a warming climate. Researchers at Boise, Idaho, completed the installation of a network of soil respiration instrumentation within RCEW to better estimate the net productivity of Great Basin rangeland plant communities. Initial results, which are currently being quantified, indicate strong controls of both soil water and temperature on soil respiration. This is complimentary to the eddy covariance work that is ongoing under Objective 2. A manuscript was drafted and submitted describing the effects of slope and aspect on soil parameters of soil temperature and water content. This is potentially an important factor in complex terrain that is often overlooked. Researchers at Boise, Idaho, have shown that north-facing aspects are on average 5 degrees Celsius cooler than corresponding south-facing slopes that are separated by less than 200 meters. This is equivalent to approximately 1,000 meters elevation difference. Soil water differences between slope aspects indicate that the summer dry periods (droughts) on north-facing slopes are about one month shorter than on south-facing slopes. This is exciting because it demonstrates a linkage of soil climate to soil carbon accumulation based on a paper that was published this year showing that north-facing slopes have three times more carbon than corresponding south-facing slopes. This difference in fertility is part of how variability of plant productivity on the landscape can be explained. One important control on the amount of water available to a plant is the amount of water “lost” to groundwater and/or streamflow generation. In 2019, researchers at Boise, Idaho, initiated new collaborative long-term studies with Idaho State University and the University of Wyoming to quantify subsurface flow using geophysical techniques and characterize water chemistry in springs, streams, and groundwater. In regard to Objective 4, efforts continued to enhance the observational capabilities and research infrastructure in RCEW and the Great Basin Long-Term Agroecosystem network site. Research efforts focused on ecosystem productivity and publishing long-term snow, hydrologic and ecosystem data. As part of unit-wide objectives, researchers at Boise, Idaho, expanded measurements of plant dynamics and are working on more automated procedures using drones and terrestrial Light Detection and Ranging (LiDAR). Sap flux instrumentation was installed to estimate the woody plant component of vegetative productivity and a network of soil respiration measurements were installed in plant communities at different elevations with varying precipitations and temperature regimes to further study overall plant community productivity. A series of data papers were published describing soil properties and net carbon fluxes within RCEW. These papers and data are available to all researchers and will enable others to participate in modeling a variety of processes in the Great Basin for network-wide research.

1. Using modeled weather input data for snow water supply forecasting in western mountains. The greatest barrier to application of hydrologic simulation models over large areas is collection and quality control of the weather input data needed to drive the model. Researchers in Boise, Idaho, collaborated with Boise State University to test the use of the High Resolution Rapid Refresh (HRRR) operational atmospheric model, from the National Oceanic and Atmospheric Administration (NOAA), to drive real-time simulations of snow water supply forecasts in the Sierra Nevada mountains of California. This resulted in large operational efficiencies with minimal degradation of modeled results that provided operational scaling of model application from two to six river basins, or roughly 3,000 square kilometers to 14,000 square kilometers. Stakeholders and water managers used the model output information provided through weekly reports to make critical flood control and reservoir management decisions, thus potentially providing a longer irrigation season to downstream agricultural users across the San Joaquin Valley of California.

2. Impacts of climate change on sagebrush ecosystems will vary with elevation. Sagebrush ecosystems in the western U.S. are in jeopardy of being lost due to a variety of stresses, including woody encroachment, cheat grass invasion, and climate change, although these ecosystems are notoriously understudied. A unique transect of vegetation, water and carbon observations across an elevation/climate gradient was established by researchers in Boise, Idaho, to gain an understanding of the potential effects of climate change on these ecosystems. Study results suggest that climate warming may increase productivity of these rangelands where precipitation is above 450 millimeters. However, areas with limited precipitation will likely encounter longer periods of water stress through the summer. Thus, while climate warming may not add to the loss of sagebrush at higher elevations, increased water stress at lower elevations may result in increased opportunity for invasive weeds and accelerate the loss of sagebrush ecosystems at lower elevations.

Review Publications
Chandler, D.G., Cheng, Y., Seyfried, M.S., Madsen, M.D., Johnson, C.E., Williams, C.J. 2018. Seasonal wetness, soil organic carbon, and fire influence soil hydrological properties and water repellency in a sagebrush-steppe ecosystem. Water Resources Research. 54(10):8514-8527.
Fellows, A.W., Flerchinger, G.N., Seyfried, M.S., Lohse, K.A., Patton, N.R. 2019. Controls on gross production in an aspen-sagebrush vegetation mosaic. Ecohydrology. 12(1):e2046.
Flerchinger, G.N., Fellows, A.W., Seyfried, M.S., Clark, P.E., Lohse, K.A. 2019. Water and carbon fluxes along an elevational gradient in a sagebrush ecosystem. Ecosystems.
Goodwell, A.E., Kuman, P., Fellows, A.W., Flerchinger, G.N. 2018. Dynamic process connectivity explains ecohydrologic responses to rainfall pulses and drought. Proceedings of the National Academy of Sciences. 115(37):E8604-E8613.
Havens, S., Marks, D., FitzGerald, K., Masarik, M., Flores, A.N., Kormos, P., Hedrick, A. 2019. Approximating input data to a snowmelt model using weather research and forecasting model outputs in lieu of meteorological measurements. Journal of Hydrometeorology. 20(5):847-862.
Hedrick, A.R., Marks, D., Havens, S., Robertson, M., Johnson, M., Sandusky, M., Marshall, H., Kormos, P.R., Bormann, K.J., Painter, T.H. 2018. Direct insertion of NASA airborne snow observatory-derived snow depth time series into the iSnobal energy balance snow model. Water Resources Research. 54:8045-8063.
Kraatz, S., Jacobs, J., Schroeder, R., Cho, E., Cosh, M.H., Seyfried, M.S., Prueger, J.H., Livingston, S.J. 2019. Evaluation of SMAP freeze/thaw retrieval accuracy at core validation sites in the contiguous United States. Remote Sensing. 10(9):1483.
Krinner, G., Derksen, C., Essery, R., Flanner, M., Hagemann, S., Clark, M., Hall, A., Rott, H., Brutel-Vuilmet, C., Kim, H., Menard, C.B., Mudryk, L., Thackeray, C., Wang, L., Arduini, G., Balsamo, G., Bartlett, P., Boike, J., Boone, A., Cheruy, F., Colin, J., Cuntz, M., Dai, Y., Decharme, B., Derry, J., Ducharne, A., Dutra, E., Fang, X., Fierz, C., Ghattas, J., Gusev, Y., Haverd, V., Kontu, A., Lafaysse, M., Law, R., Lawrence, D., Li, W., Marke, T., Marks, D. 2018. ESM-SnowMIP: Assessing models and quantifying snow-related climate feedbacks. Geoscientific Model Development. 11(12):5027-5049.
Marshall, A.M., Link, T.E., Abatzoglou, J.T., Flerchinger, G.N., Marks, D.G., Tedrow, L. 2019. Warming alters hydrologic heterogeneity: Simulated climate sensitivity of hydrology-based microrefugia in the snow-to-rain transition zone. Water Resources Research. 55:2122-2141.
Menard, C.B., Essery, R., Barr, A., Bartlett, P., Derry, J., Dumont, M., Fierz, C., Kim, H., Kontu, A., Lejeunne, Y., Marks, D., Niwano, M., Raleigh, M., Wang, L., Wever, N. 2019. Meteorological and evaluation datasets for snow modelling at 10 reference sites: description of in situ and bias-corrected reanalysis data. Earth System Science Data. 11:865-880.
Patton, N.R., Lohse, K.A., Godsey, S.E., Crosby, B.T., Seyfried, M.S. 2018. Predicting soil thickness on soil mantled hillslopes. Nature Communications. 9(1):3329.
Patton, N.R., Lohse, K.A., Seyfried, M., Will, R., Benner, S.G. 2018. Lithology and coarse fraction adjusted bulk density estimates for determining total organic carbon stocks in dryland soils. Geoderma. 337:844-852.
Patton, N.R., Lohse, K.A., Seyfried, M.S., Godsey, S.E., Parsons, S.B. 2019. Topographic controls of soil organic carbon in semi-mantled landscapes. Scientific Reports. 9:6390.
Parajuli, K., Jones, S.B., Tarboton, D.G., Flerchinger, G.N., Hipps, L.E., Allen, L.N., Seyfried, M.S. 2019. Estimating actual evapotranspiration from stony-soils in montane ecosystems. Agricultural and Forest Meteorology. 265:183-194.
Renwick, K.M., Fellows, A., Flerchinger, G.N., Lohse, K.A., Clark, P.E., Smith, W.K., Emmett, K., Poulter, B. 2019. Modeling phenological controls on carbon dynamics in dryland sagebrush ecosystems. Agricultural and Forest Meteorology. 274:85-94.
Sohrabi, M.M., Tonina, D., Benjankar, R., Kumar, M., Kormos, P., Marks, D., Luce, C. 2019. On the role of spatial resolution on snow estimates using a process-based snow model across a range of climatology and elevation. Hydrological Processes. 33(8):1260-1275.
Sohrabi, M.M., Tonina, D., Benjankar, R., Kumar, M., Kormos, P.R., Marks, D. 2018. Role of temporal resolution on meteorological inputs for process-based snow modeling. Hydrological Processes. 32(19):2976-2989.
Zhang, Y.L., Li, X., Cheng, G.D., Jin, H.J., Yang, D.W., Flerchinger, G.N., Chang, X.L., Wang, X., Liang, J. 2018. Influence of topographic shadows on the thermal and hydrological processes in a cold region mountainous watershed in Northwest China. Journal of Advances in Modeling Earth Systems. 10:1439-1457.
Zhou, Q., Fellows, A., Flerchinger, G.N., Alejandro, F.N. 2019. Examining interactions between and among predictors of net ecosystem exchange: A machine learning approach in a semi-arid landscape. Science of the Total Environment. 9(1):2222.