Cooperative Institute for Research in Environmental Sciences

Ben Livneh

Ben Livneh

Research Interests

My primary research interest is in quantifying the hydrologic impacts of both climate change and land cover disturbance processes across multiple scales. The scientific community’s understanding of climate change continues to evolve, and so we need a flexible framework—models, observations, and communication—to evolve together with this understanding. The tools I use to address these challenges involve integrating observations with modeling and statistics, to attribute causes and improve process understanding.


Current Research

Since 2002, the Upper Colorado River Basin (UCRB) region has experienced widespread tree mortality from bark beetle infestation that has taken place across a range of forest types, elevation, and latitude. Additional disturbance has resulted from deposition of regional dust on mountain snowpacks, which strongly alters the snow surface albedo. Potential changes in regional hydrology have important implications for regional water management decisions, i.e. reservoir operation and planning. To address these issues, I led an interdisciplinary research effort to quantify how the aforementioned snowmelt perturbations affect water regional resources.

This was the first study to explore the combined hydrologic impacts of bark beetle and dry-land dust deposition on snow. The extent and severity of hydrologic disturbances were used to parameterize and drive a high-resolution hydrologic modeling framework (~100 m grid cells) using aerial survey data, MODIS-derived leaf area index (LAI), and dust-on-snow radiative loading, as well as in situ measurements. Results show that bark beetles contribute to overall increases in annual water yield of approximately 10%, primarily due to greater snow accumulation from reduced canopy interception and ET. However, maximum understory regeneration roughly halves the changes in water yield. Dust-on-snow led to earlier simulated peak streamflow rates of 1–3 weeks, consistent with previous literature, while combined bark beetle and dust-on-snow produced modest compounding effects, due to their relatively exclusive nature.

Observational Hydrometeorological Dataset Development

A common challenge in driving land surface models, or evaluating climate model predictions is the lack of comprehensive observations at the spatial and temporal resolutions that the models operate. To address this issue, I’ve developed station-based gridded hydrometeorological data sets over large parts of the North American continent with data sets extending as far back as the year 1915. Daily temperature and precipitation data from thousands of stations are combined to estimate gridded fields at a 1/16° (~6 km) resolution that I’ve used to create a set of model-derived hydrologically consistent states and fluxes at a daily time step over this large domain. Many applications for these data exist that offer insights into impacts of climate on water availability, such as mapping precipitation deficits and high temperatures during drought and simulating their effect on soil moisture.

Drought Characterization

The occurrence of drought is associated with damage to property, outbreaks of disease, and famine. One possible explanation for these impacts is the lack of prompt and comprehensive preparation and response due to the lack of proper recognition of drought development. Therefore, improving drought prediction has potential to prevent innumerable damages, yet drought remains difficult to observe and model drought due to its broad scale and scope. My research aims to advance the understanding of drought processes by modeling relationships between precipitation deficits, high temperatures, and soil response. Major regions of interest include the Colorado River Basin, California, and the Great Plains—all areas of either regional importance, large populations, or agricultural vulnerability. My preliminary analyses shows that physically-based land surface models and remote sensing independently reproduce key drought signals. The ability to realistically model drought enables a clearer process understand of historical events as well as potential future drought characteristics altered by climate change.


View Publications

  • Raleigh, MS, Ben Livneh, K Lapo and JD Lundquist (2016), How Does Availability of Meteorological Forcing Data Impact Physically Based Snowpack Simulations?. J. Hydrometeorol. Version: 1 17 (1) 99-120, issn: 1525-755X, ids: CZ9FH, doi: 10.1175/JHM-D-14-0235.1
  • Mizukami, N, MP Clark, ED Gutmann, PA Mendoza, AJ Newman, B Nijssen, Ben Livneh, LE Hay, JR Arnold and LD Brekke (2016), Implications of the Methodological Choices for Hydrologic Portrayals of Climate Change over the Contiguous United States: Statistically Downscaled Forcing Data and Hydrologic Models. J. Hydrometeorol. Version: 1 17 (1) 73-98, issn: 1525-755X, ids: CZ9FH, doi: 10.1175/JHM-D-14-0187.1
  • Livneh, Ben, Theodore J. Bohn, David W. Pierce, Francisco Munoz-Arriola, Bart Nijssen, Russell Vose, Daniel R. Cayan and Levi Brekke (2015), A spatially comprehensive, hydrometeorological data set for Mexico, the US, and Southern Canada 1950-2013. Version: 1 SCIENTIFIC DATA 2 , Art. No. 150042, issn: 2052-4463, doi: 10.1038/sdata.2015.42
  • Livneh, B, R Kumar and L Samaniego (2015), Influence of soil textural properties on hydrologic fluxes in the Mississippi river basin. Hydrol. Process. Version: 1 AGU Fall Meeting 29 (21) 4638-4655, San Francisco, CA, DEC 09-13, 2013, issn: 0885-6087, ids: CU1JQ, doi: 10.1002/hyp.10601
  • Lundquist, JD, M Hughes, B Henn, ED Gutmann, B Livneh, J Dozier and P Neiman (2015), High-Elevation Precipitation Patterns: Using Snow Measurements to Assess Daily Gridded Datasets across the Sierra Nevada, California. J. Hydrometeorol. Version: 1 16 (4) 1773-1792, issn: 1525-755X, ids: CP3FI, doi: 10.1175/JHM-D-15-0019.1
  • Livneh, B, JS Deems, B Buma, JJ Barsugli, D Schneider, NP Molotch, K Wolter and CA Wessman (2015), Catchment response to bark beetle outbreak and dust-on-snow in the Colorado Rocky Mountains. J. Hydrol. Version: 1 523 196-210, issn: 0022-1694, ids: CE6TS, doi: 10.1016/j.jhydrol.2015.01.039
  • Funk, C, S Shukla, A Hoell and B Livneh (2015), ASSESSING THE CONTRIBUTIONS OF EAST AFRICAN AND WEST PACIFIC WARMING TO THE 2014 BOREAL SPRING EAST AFRICAN DROUGHT. Bull. Amer. Meteorol. Soc. Version: 1 96 (12) S77-S82, issn: 0003-0007, ids: DB4SL, doi: 10.1175/BAMS-D-15-00106.1
  • Chen, F, M Barlage, M Tewari, R Rasmussen, JM Jin, D Lettenmaier, B Livneh, CY Lin, G Miguez-Macho, GY Niu, LJ Wen and ZL Yang (2014), Modeling seasonal snowpack evolution in the complex terrain and forested Colorado Headwaters region: A model intercomparison study. J. Geophys. Res.-Atmos. Version: 1 119 (24) 13795-13819, issn: 2169-897X, ids: AZ8IX, doi: 10.1002/2014JD022167
  • Livneh, B, JS Deems, D Schneider, JJ Barsugli and NP Molotch (2014), Filling in the gaps: Inferring spatially distributed precipitation from gauge observations over complex terrain. Water Resour. Res. Version: 1 50 (11) 8589-8610, issn: 0043-1397, ids: AX0PQ, doi: 10.1002/2014WR015442
  • Kumar, SV, CD Peters-Lidard, D Mocko, R Reichle, YQ Liu, KR Arsenault, YL Xia, M Ek, G Riggs, B Livneh and M Cosh (2014), Assimilation of Remotely Sensed Soil Moisture and Snow Depth Retrievals for Drought Estimation. J. Hydrometeorol. Version: 1 15 (6) 2446-2469, issn: 1525-755X, ids: AU9FZ, doi: 10.1175/JHM-D-13-0132.1
  • Livneh, B and DP Lettenmaier (2013), Regional parameter estimation for the unified land model. Water Resour. Res. Version: 1 49 (1) 100-114, issn: 0043-1397, ids: 129GR, doi: 10.1029/2012WR012220
  • Livneh, B, EA Rosenberg, CY Lin, B Nijssen, V Mishra, KM Andreadis, EP Maurer and DP Lettenmaier (2013), A Long-Term Hydrologically Based Dataset of Land Surface Fluxes and States for the Conterminous United States: Update and Extensions. J. Clim. Version: 1 26 (23) 9384-9392, issn: 0894-8755, ids: 253AN, doi: 10.1175/JCLI-D-12-00508.1
  • Kumar, R, B Livneh and L Samaniego (2013), Toward computationally efficient large-scale hydrologic predictions with a multiscale regionalization scheme. Water Resour. Res. Version: 1 49 (9) 5700-5714, issn: 0043-1397, ids: 238ZO, doi: 10.1002/wrcr.20431
  • Bohn, TJ, B Livneh, JW Oyler, SW Running, B Nijssen and DP Lettenmaier (2013), Global evaluation of MTCLIM and related algorithms for forcing of ecological and hydrological models. Agric. For. Meteorol. Version: 1 176 38-49, issn: 0168-1923, ids: 165IE, doi: 10.1016/j.agrformet.2013.03.003
  • Xia, YL, M Ek, J Sheffield, B Livneh, MY Huang, HL Wei, S Feng, LF Luo, J Meng and E Wood (2013), Validation of Noah-Simulated Soil Temperature in the North American Land Data Assimilation System Phase 2. J. Appl. Meteor. Clim. Version: 1 52 (2) 455-471, issn: 1558-8424, ids: 097JO, doi: 10.1175/JAMC-D-12-033.1
  • Xia, YL, K Mitchell, M Ek, J Sheffield, B Cosgrove, E Wood, LF Luo, C Alonge, HL Wei, J Meng, B Livneh, D Lettenmaier, V Koren, QY Duan, K Mo, Y Fan and D Mocko (2012), Continental-scale water and energy flux analysis and validation for the North American Land Data Assimilation System project phase 2 (NLDAS-2): 1. Intercomparison and application of model products. J. Geophys. Res.-Atmos. Version: 1 117 , Art. No. D03109, issn: 2169-897X, ids: 887VW, doi: 10.1029/2011JD016048
  • Livneh, B and DP Lettenmaier (2012), Multi-criteria parameter estimation for the Unified Land Model. Hydrol. Earth Syst. Sci. Version: 1 16 (8) 3029-3048, issn: 1027-5606, ids: 998ND, doi: 10.5194/hess-16-3029-2012
  • Sheffield, J, B Livneh and EF Wood (2012), Representation of Terrestrial Hydrology and Large-Scale Drought of the Continental United States from the North American Regional Reanalysis. J. Hydrometeorol. Version: 1 13 (3) 856-876, issn: 1525-755X, ids: 965OH, doi: 10.1175/JHM-D-11-065.1
  • Mahanama, S, B Livneh, R Koster, D Lettenmaier and R Reichle (2012), Soil Moisture, Snow, and Seasonal Streamflow Forecasts in the United States. J. Hydrometeorol. Version: 1 13 (1) 189-203, issn: 1525-755X, ids: 890IN, doi: 10.1175/JHM-D-11-046.1
  • Xia, YL, K Mitchell, M Ek, B Cosgrove, J Sheffield, LF Luo, C Alonge, HL Wei, J Meng, B Livneh, QY Duan and D Lohmann (2012), Continental-scale water and energy flux analysis and validation for North American Land Data Assimilation System project phase 2 (NLDAS-2): 2. Validation of model-simulated streamflow. J. Geophys. Res.-Atmos. Version: 1 117 , Art. No. D03110, issn: 2169-897X, ids: 887VW, doi: 10.1029/2011JD016051
  • Livneh, B, PJ Restrepo and DP Leitenmaier (2011), Development of a Unified Land Model for Prediction of Surface Hydrology and Land-Atmosphere Interactions. J. Hydrometeorol. Version: 1 12 (6) 1299-1320, issn: 1525-755X, ids: 864CU, doi: 10.1175/2011JHM1361.1
  • Koster, RD, SPP Mahanama, B Livneh, DP Lettenmaier and RH Reichle (2010), Skill in streamflow forecasts derived from large-scale estimates of soil moisture and snow. Nat. Geosci. Version: 1 3 (9) 613-616, issn: 1752-0894, ids: 645NL, doi: 10.1038/NGEO944
  • Livneh, B, YL Xia, KE Mitchell, MB Ek and DP Lettenmaier (2010), Noah LSM Snow Model Diagnostics and Enhancements. J. Hydrometeorol. Version: 1 11 (3) 721-738, issn: 1525-755X, ids: 618PI, doi: 10.1175/2009JHM1174.1
  • Barlage, M, F Chen, M Tewari, K Ikeda, D Gochis, J Dudhia, R Rasmussen, B Livneh, M Ek and K Mitchell (2010), Noah land surface model modifications to improve snowpack prediction in the Colorado Rocky Mountains. J. Geophys. Res.-Atmos. Version: 1 115 , Art. No. D22101, issn: 2169-897X, ids: 683MY, doi: 10.1029/2009JD013470
  • Casola, JH, L Cuo, B Livneh, DP Lettenmaier, MT Stoelinga, PW Mote and JM Wallace (2009), Assessing the Impacts of Global Warming on Snowpack in the Washington Cascades. J. Climate Version: 1 22 (10) 2758-2772, issn: 0894-8755, ids: 453CG, doi: 10.1175/2008JCLI2612.1
  • Livneh, B and MH El Naggar (2008), Axial testing and numerical modeling of square shaft helical plies under compressive and tensile loading. Can. Geotech. J. Version: 1 45 (8) 1142-1155, issn: Aug-74, ids: 353NS, doi: 10.1139/T08-044
Snake River watershed

Forest Disturbance. Depiction of land cover classifications for the Snake R near Montezuma, CO study catchment showing cumulative bark beetle mortality as of 2011 based on U.S. Forest Service annual aerial surveys.

Inferring drought conditions from multiple sources Monthly anomalies (2002-2013) for observed precipitation (right ordinate axis), as well as independent estimates of terrestrial water anomalies from the GRACE satellite and two land surface models, ULM, and VIC (left ordinate axis) averaged over the Great Plains domain.