Research Project: Ecohydrology of Mountainous Terrain in a Changing Climate

Location: Northwest Watershed Research Center

2022 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
This is the final report for project 2052-13610-012-000D, Ecohydrology of Mountainous Terrain in a Changing Climate, which expired in January 2022 and has been replaced by new project 2052-13610-015-00D, Ecohydrology of Sustainable Mountainous Rangeland Ecosystems. For additional information, see the new project report. Progress was completed on all four objectives, and substantial accomplishments were realized at ARS in Boise, Idaho, over the last five years. In this semiarid part of the world, snow accumulation is the driving factor for water supply and many ecohydrological processes. Understanding interactions between snow processes, streamflow, water supply, plant water use, rangeland productivity, and carbon dynamics is critical for management of natural resources in the region. Seasonal mountain snowmelt is the primary contributor to streamflow in the Western United States, yet operational efforts to accurately predict mountain runoff are rooted in decades-old statistical approaches. In support of Objective 1, ARS researchers in Boise, Idaho, have continued to quantify effects of altering precipitation and temperature regimes on snow accumulation and melt in headwater catchments throughout the region. Much of this research has been accomplished by continually developing the ARS energy balance snow model (iSnobal). Within the ARS-managed Reynolds Creek Experimental Watershed (RCEW) near Murphy, Idaho, research was performed that led to publication of 31-years of gridded meteorological data at 10-m resolution. That data was then used to drive the physically based iSnobal model to monitor effects of climatic trends on snowmelt generation and runoff in the watershed. Additionally, using an elevational measurement transect in the Johnston Draw sub-watershed of RCEW, researchers continued to analyze the hydrologic influences within the rain-snow transition zone. The operational component of the iSnobal modeling framework was continually improved to permit large-scale simulations of snowpack conditions in real-time. The development and publication of the Spatial Resources for Modeling Framework (SMRF) now allows model users to largely automate the creation of spatial forcing data required by iSnobal. Additionally, the published Automated Water Supply Model (AWSM) has been developed to significantly decrease computational time by using distributed computer resources, while also introducing the ability to use atmospheric model output as iSnobal forcing data, as opposed to weather station measurements that often requires intensive user quality control. The continued partnership with the National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL) Airborne Snow Observatory (ASO) demonstrated the improvement to iSnobal modeled spatial Snow Water Equivalent (SWE) predictions through periodic assimilation of high-resolution Light Detection and Ranging (LiDAR)-derived snow depths. In addition, an improved snow density algorithm was integrated into iSnobal, and real-time snow modeling was ramped up to five large basins in California's Sierra Nevada. Stakeholder relationships in California were maintained through real-time snowpack modeling and dissemination of reports through an automated report generation utility that enabled water managers to access snowpack state information at any time. Finally, initial simulations of a coupled snowmelt to streamflow model were performed in the Tollgate sub-watershed of RCEW and in the Tuolumne River Basin in California. Sagebrush ecosystems in the Western United States are in jeopardy of being lost due to a variety of stresses, including woody encroachment, cheatgrass invasion, and climate change, but these ecosystems are notoriously understudied. Through a progression of studies that included computer model improvements guided by field observations under Objective 2, ARS researchers in Boise, Idaho, have improved our ability to predict the effects of fire, climate change, management, and vegetation shifts on ecosystem response, productivity, and carbon sequestration. Specifically, ARS researchers demonstrated rapid recovery of the hydrology, vegetation, and ecosystem productivity following prescribed fire. ARS researchers have also improved computer models that simulate plant phenology and carbon uptake, and then used these improved computer models to assess potential effects of climate change on rangeland sagebrush ecosystems and to map soil organic carbon content (i.e., organic matter) over the RCEW. ARS researchers in Boise, Idaho, demonstrated that climate warming may increase productivity of these ecosystems where precipitation is above 450 mm, but will result in increased water stress, greater opportunity for invasive weeds, and potentially accelerate the loss of sagebrush ecosystems at lower elevations. Studies also suggested that the natural heterogeneity, diversity, and mosaic of patchy vegetation in these ecosystems may be lost with climate warming. In support of Objective 3, ARS researchers in Boise, Idaho, quantified and developed models to predict how spatial variability of the topography and soil properties affect microclimate processes and plant productivity. Using multiyear records of Gross Ecosystem Productivity (GEP), micrometeorology, and streamflow in a small headwater basin, ARS researchers demonstrated that spatial variability of Critical Zone structure (CZ, defined as the zone between the top of the vegetation canopy and the groundwater) largely controls GEP, plant productivity, and the mosaic of aspen and sagebrush vegetation. Using long-term records of winter carbon dioxide emission, low elevation sites were found to have limited carbon dioxide emission 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. Local slope and aspect effects were demonstrated to have a large influence on soil climate. This was quantified by soil temperature and water content, influencing snow dynamics, and vegetation productivity. A physically based simulation model was shown to capture the dynamics but results suggest that realistic simulations of many CZ processes require high resolution inputs in complex topography to capture slope-aspect effects. The long-term observational infrastructure of RCEW has been greatly expanded as part of Objective 4 and in support of Long-Term Agroecosystem Research (LTAR) and the Reynolds Creek Critical Zone Observatory. Expansion has included installation of water quality and organic carbon sampling in surface and ground waters, soil carbon dioxide profiles, dust collectors to quantify composition of aeolian deposits, and expansion of geophysical surveys within several sub-watersheds. These efforts have resulted from extensive collaboration with Idaho State University (2052-13610-012-27R, "Reynolds Creek Carbon Critical Zone Observatory"). Additionally, ARS researchers in Boise, Idaho, contributed to numerous LTAR network papers on topics including water balance, plant phenology, water use efficiency, and measurement protocols.

Accomplishments

Review Publications
Flinker, R., Cardenas, M., Caldwell, T., Flerchinger, G.N., Rich, R., Reich, P. 2021. Promise and pitfalls of modeling grassland soil moisture in a free-air CO2 enrichment experiment (BioCON) using the SHAW model. Pedosphere. 31(5):783-795. https://doi.org/10.1016/S1002-0160(21)60037-1.
Glossner, K., Lohse, K., Appling, A.P., Cram, Z.K., Murray, E.M., Godsey, S., Van Vactor, S.S., McCorkle, E., Seyfried, M.S., Pierson Jr., F.B. 2022. Long-term suspended sediment and particulate organic carbon yields from the Reynolds Creek Experimental Watershed and Critical Zone Observatory. Hydrological Processes. 36(2). Article e14484. https://doi.org/10.1002/hyp.14484.
Marshall, A.M., Link, T.E., Flerchinger, G.N., Lucash, M.S. 2021. Importance of parameter and climate data uncertainty for future changes in boreal hydrology. Water Resources Research. 57(8). Article e2021WR029911. https://doi.org/10.1029/2021WR029911.
Seyfried, M.S., Flerchinger, G.N., Bryden, S., Link, T., Marks, D.G., McNamara, J. 2021. Slope and aspect controls on soil climate: Field documentation and implications for large-scale simulation of critical zone processes. Vadose Zone Journal. 20(6). Article e20158. https://doi.org/10.1002/vzj2.20158.