Location: Northwest Watershed Research Center
2022 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 obseravations 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 simuated 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 thatr 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
This report documents progress for project 2052-13610-015-000D, Ecohydrology of Sustainable Mountainous Rangeland Ecosystems, which started in January 2022 and continues research from project 2052-13610-012-000D, Ecohydrology of Mountainous Terrain in a Changing Climate.
In support of Objective 1, research continued to quantify mountain precipitation during the snow accumulation season more accurately at varying scales and the resultant effects of changes in the seasonal precipitation phase on streamflow generation. ARS researchers in Boise, Idaho, have a manuscript that is in review on Snow Water Equivalent (SWE) variability in large hydrologically significant basins. A second manuscript, based on a study developed in collaboration with California stakeholders, is being prepared by ARS researchers in Boise, Idaho, regarding the role of precipitation phase on runoff generation for a 42-year time span (1980-2022) in fourteen large basins in the Sierra Nevada. Research with collaborators at the University of Utah and National Weather Service Colorado Basin River Forecast Center (CBRFC) concerning physically based snow modeling in the East River Basin of Colorado has been submitted for publication. SnowEx is a five-year program initiated and funded by the National Aeronautics and Space Administration (NASA) to address the most important gaps in snow remote sensing knowledge. Measurement efforts contributing to the NASA SnowEx2020 community measurement campaign were continued, and datasets of various snow properties have been compiled and organized for dissemination to the snow and mountain hydrology research community. 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 worked collaboratively with Kings River Association and Natural Resources Conservation Service by continuing to produce biweekly reports of snowpack results across five large river basins.
In support of Objective 2, five manuscripts are under review or near publication on the following research topics: estimating evapotranspiration (ET) from infrared thermometry; predicting soil organic carbon; simulating fire, vegetation, and hydrologic feedbacks in forests; post-planting microclimate and emergence of grasses, and vapor transmission in freezing soil. Coupling of the Simultaneous Heat and Water (SHAW) model to the Parameter Estimation and Uncertainty (PEST) optimization software is complete, and model runs have been conducted for sensitivity analysis and optimization of input parameters for simulating ET and ecosystem productivity. 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, conducted geophysics studies at the Drylands Critical Zone Observatory site, and colleagues from New Mexico State University collected biocrust samples for analysis of carbon dioxide uptake.
In support of Objective 3, infrastructure in the RCEW continues to be improved; water quality sensors have been installed in streams and groundwater wells in a sub-watershed where a prescribed fire is planned for the fall of 2023. ARS researchers in Boise, Idaho, contributed to draft manuscripts being generated by the Long-Term Agroecosystem Research (LTAR) network scientists on Water Use Efficiency (WUE) and measurement protocols. One manuscript has been published with collaborators from Idaho State University (2052-13610-012-27R, “Reynolds Creek Carbon Critical Zone Observatory”) and Colorado State University examining the effect of climate signals on snow and streamflow within the rain-on-snow transition elevation. In support of Sub-objective 3B, a manuscript is in the second round of revisions concerning spatial and temporal patterns of snow water input to the hydrologic system across varying years of climatology.
Accomplishments
1. Transfer of snowmelt modeling technology to California Department of Water Resources. Drought and ongoing climate warming have greatly altered snow water supply in the mountainous Western United States, requiring new approaches to water supply forecasting that explicitly account for variations in snow accumulation and melt. The California Department of Water Resources (CADWR) has initiated a pilot program for incorporating the Automated Water Supply Model (AWSM)/iSnobal snow model developed by ARS researchers in Boise, Idaho, into their operational snow water supply forecasting infrastructure. The ARS researchers provided technical support and software troubleshooting to CADWR engineers. The pilot program demonstrated that the physically based modeling framework was successfully implemented in real time on CADWR computing resources, and the spatial snowmelt information was integrated into the CADWR operational forecast used to allocate limited water resources. This valuable tool has allowed water supply forecasters with CADWR to readily incorporate complex physically based modeling to develop more accurate water supply forecasts.
Review Publications
Chu, X., Flerchinger, G.N., Ma, L., Fang, Q., Malone, R.W., Yu, Q., He, J., Wang, N., Feng, H., Zou, Y. 2022. Development of RZ-SHAW for simulating plastic mulch effects on soil water, soil temperature, and surface energy balance in a maize field. Agricultural Water Management. 269. Article 107666. https://doi.org//10.1016/j.agwat.2022.107666.
Hardegree, S.P., Sheley, R.L., James, J., Reeves, P.A., Flerchinger, G.N., Moffet, C. 2022. Postplanting microclimate, germination, and emergence of perennial grasses in Wyoming big sagebrush steppe. Rangeland Ecology and Management. 84:63-74. https://doi.org/10.1016/j.rama.2022.05.008.
Kiewiet, L., Trujillo, E., Hedrick, A., Havens, S.C., Hale, K., Seyfried, M.S., Kampf, S., Godsey, S. 2022. Effects of spatial and temporal variability in surface water inputs on streamflow generation and cessation in the rain–snow transition zone. Hydrology and Earth System Sciences. 26(10):2779-2796. https://doi.org/10.5194/hess-26-2779-2022.
Pierson, D., Lohse, K.A., Wieder, W.R., Patton, N.R., Facer, J., de Graaff, M., Georgiou, K., Seyfried, M., Flerchinger, G.N., Will, R. 2022. Optimizing process-based models to predict current and future soil organic carbon stocks at high-resolution. Scientific Reports. 12. Article 10824. https://doi.org/10.1038/s41598-022-14224-8.
Wang, X., Biederman, J.A., Knowles, J.F., Scott, R.L., Turner, A., Dannenberg, M., Kohler, P., Frankenberg, C., Litvak, M., Flerchinger, G.N., Law, B., Kwon, H., Reed, S., Parton, W., Barron-Gafford, G., Smith, W. 2022. Satellite solar-induced chlorophyll fluorescence and near-infrared reflectance capture complementary aspects of dryland vegetation productivity dynamics. Remote Sensing of Environment. 270. Article 112858. https://doi.org/10.1016/j.rse.2021.112858.
