Location: Watershed Management Research2017 Annual Report
1a. Objectives (from AD-416):
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.
1b. Approach (from AD-416):
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.
3. Progress Report:
This report documents progress for project 2052-13610-012-00D, "Ecohydrology of Mountainous Terrain in a Changing Climate," which started in January 2017 and continues research from Project 2052-13610-010-00D, "Understanding Snow and Hydrologic Processes in Mountainous Terrain with a Changing Climate." In regards to Objective 1, the Northwest Watershed Research Center (NWRC) continues to partner with National Aeronautics and Space Administration (NASA)/Jet Propulsion Laboratory on the Airborne Snow Observatory (ASO) effort to use Light Detection and Ranging (Lidar) remotely sensed estimates of snow depths to improve estimates of the volume of water stored in snow packs across the western U.S. These improved estimates are provided from the iSnobal model developed by ARS scientists in Boise, Idaho. Work is being initiated to couple iSnobal with a water routing model that will form the basis for the next generation of improved stream flow forecast modeling across the west. This past year’s very high runoff season has increased water user interest and demand for improved water supply forecasting. The Bureau of Reclamation, the State of California, and the Natural Resources Conservation Service, Water and Climate Center are now providing additional funds in support of this technology transfer and development effort. Efforts are now underway to utilize a 30-year spatially distributed data set for all of Reynolds Creek Experimental Watershed (RCEW), including precipitation, volume and phase, wind-field, air temperature, humidity, solar and thermal radiation at 10- meter (m) resolution to test critical components of iSnobal. In regards to Objective 2, in collaboration with the National Science Foundation funded Reynolds Creek Critical Zone Observatory (RC-CZO), ARS scientists in Boise, Idaho analyzed and submitted the first two years of data collected using the eddy covariance systems at the three RC-CZO core sites to the AmeriFlux Network. Using this dataset, ARS scientists drafted a manuscript describing water and carbon dioxide fluxes across the climate gradient within RCEW. Manuscripts were also drafted and submitted describing: rapid recovery of carbon fluxes after the Upper Sheep Creek 2007 prescribed fire; and sensitivity of ecosystem production on precipitation amount and snowmelt timing within sagebrush and aspen vegetation communities. In regards to Objectives 3 and 4, NWRC developed an extensive climate dataset from Johnston Draw in RCEW that spans the critical rain-snow transition zone and the data is now submitted for publication as a data report. NWRC scientists improved the Soil Ecohydrology Model to incorporate multiple profiles to enable spatial analysis of soil moisture conditions. The model now directly accepts input data from different sources thus improving model users’ ability to develop model input files. ARS scientists, in collaboration with Idaho State University scientists from the RC-CZO (2052-13610-012-01R, "Reynolds Creek Carbon Critical Zone Observatory"), have installed multiple soil carbon dioxide sensors that will contribute to the overall understanding of carbon cycling across RCEW. This increased instrumentation will also directly contribute to the long-term efforts for the Great Basin Long-Term Agroecosystem Research network.
Colliander, A., Jackson, T.J., Bindlish, R., Chan, S., Das, N., Kim, S., Cosh, M.H., Dunbar, R., Dang, L., Pashaian, L., Asanuma, J., Aida, K., Berg, A., Rowlandson, T., Bosch, D.D., Caldwell, T., Caylor, K., Goodrich, D.C., Jassar, H., Lopez-Baeza, E., Martinez-Fernandez, J., Gonzalez-Zamora, Livingston, M.S., McNairn, H., Pacheco, A., Moghaddam, M., Montzka, C., Notarnicola, C., Niedrist, G., Pellarin, T., Prueger, J.H., Pulliainen, J., Rautiainen, K., Ramo, J., Seyfried, M.S., Starks, P.J., Su, Z., Zeng, Y., Velde, R., Thibeault, M., Dorigo, W., Vreugdenhil, M., Walker, J., Wu, X., Monerris, A., O'Neill, P., Entekhabi, D., Njoku, E., Yueh, S. 2017. Validation of SMAP surface soil moisture products with core validation sites. Remote Sensing of Environment. 192:238-262.
Berry, C., Evaristo, J., Moore, G., Poco, M., Steppe, K., Verrot, L., Asbjornsen, H., Borma, L., Bretfeld, M., Herve-Fernandez, P., Seyfried, M.S., Schwendenmann, L., Sinacore, K., De Wispelaere, L., Mcdonnell, J. 2017. The two water worlds hypothesis: Addressing multiple working hypotheses and proposing a way forward. Ecohydrology. doi: 10.1002/eco.1843.
Chandler, D., Seyfried, M.S., Mcnamara, J., Hwang, K. 2017. Inference of soil hydrologic parameters from electronic soil moisture records. Frontiers in Earth Science. doi: 10.3389/feart.2017.00025.
Cowley, G.S., Niemann, J.D., Green, T.R., Seyfried, M.S., Jones, A.S., Grazaitis, P.J. 2017. Impacts of precipitation and potential evapotranspiration patterns on downscaling soil moisture in regions with large topographic relief. Water Resources Research. 53(2):1553-1574. doi:10.1002/2016WR019907.
Kormos, P.R., Marks, D.G., Pierson, F.B., Williams, C.J., Hardegree, S.P., Boehm, A.R., Havens, S.C., Hedrick, A., Svejcar, A. 2017. Meteorological, snow, streamflow, topographic, and vegetation height data from four western juniper-dominated experimental catchments in southwestern Idaho, USA. Earth System Science Data. 9:91-98. doi:10.5194/essd-9-91-2017.
Liu, J., Pan, T., Chen, D., Zhou, X., Yu, Q., Flerchinger, G.N., Liu, D., Liu, Y., Linderholm, H., Du, J., Wu, D., Shen, Y. 2017. An improved Ångström-type model for estimating solar radiation over the Tibetan Plateau. Applied Energy. 10:892. doi: 10.3390/en10070892.
Mohammed, A., Schincariol, R., Quinton, W., Nagare, R., Flerchinger, G.N. 2017. On the use of mulching to mitigate permafrost thaw due to linear disturbances in sub-arctic peatlands. Ecological Engineering. 102:207-223. doi: 10.1016/j.ecoleng.2017.02.020.
Yanlin, Z., Guodong, C., Xin, L., Xiaoli, C., Xujun, H., Flerchinger, G.N. 2017. Influences of frozen ground and climate change on hydrological processes in an alpine watershed: A case study in the upstream area of the Hei’he River, Northwest China. Permafrost and Periglacial Processes. 28(2):420-432. doi: 10.1002/ppp.1928.