DCHM - Duke Coupled surface-subsurface Hydrology Model

Update 1 - February 2016 (APB)
Environmental Physics Laboratory – Duke University (Ana P. Barros, Faculty Director)

The DCHM (Duke Coupled surface-subsurface Hydrology Model) is a research model that is freely available to all interested scientists. Due to the lack of appropriate funding, the model is documented in the literature, but a User’s Manual and FAQ documentation are not maintained and regularly updated. Therefore, interested users should plan to spend time in-residence at Duke toward hands-on orientation and applications using the model.

DCHM Development Timeline and Milestones
The DCHM has been in development since 1991. It started as the LSHM (Land-Surface Hydrology Model) as an independent effort by Ana P. Barros at the University of Washington to code the column land-surface used in the ECMWF model at the time following the corresponding ECMWF technical note but implemented in a finite-element framework including different numerical formulations and boundary conditions for heat and water fluxes in the subsurface. The model was used for the first time in Barros (1995, J. Climate). The 1D-LSHM was subsequently tested by undergraduate and graduate students working with Barros at Penn State, including two M.Sc. Thesis (ElRasheed-Eltayebb and Eve Devonec), with the first comprehensive manuscript documenting the column model (1D-LSHM) was published in 2002 (Devonec and Barros, 2002, J. Hydrology). Osman Yildiz developed the model into a full-distributed hydrology model including runoff and streamflow routing and surface-subsurface interactions for his Penn State doctoral dissertation (Yildiz and Barros 2005, 2007, 2009, J. Hydrology and others). Juan Garcia-Quijano worked with Barros at Harvard to introduce a dynamic vegetation module to simulate photosynthesis coupled with hydrologic processes at sub-hourly scale (Garcia-Quijano and Barros, 2005, Ecological Modeling). At Duke, Shanti Bushan coupled the 1D-LSHM to a NWP model, the Clark-Hall model, at cloud allowing resolution (1 km, Bushan and Barros, 2007, J. Hydrometeorology). Do-Hyuk Kang changed the snow physics to include multiple layers and linked the model to a forward microwave emission model (Kang and Barros, 2011a and 2011b, IEEE TGARS). Jing Tao implemented the model at high resolution and introduced an aquifer model, variable soil depths and full two-way coupling to the streamflow routing, wetland physics, and data assimilation (Tao and Barros 2013 and 2014a,b,c, Tao et al. 2016, Tao and Barros 2016, J. Hydrology and HESS and others). Lauren Lowman introduced prognostic phenology and dynamic vegetation roots (Lowman and Barros, 2016) and in preparation.

 

DCHM (and LSHM) Bibliography

Peer-Reviewed Journal Publications

Lowman,L.E.L, and Barros, A.P., 2016: Interplay of Drought andTropical Cyclone Activity in SE US Gross Primary Productivity. J. Geophys. Res.- Biogeosciences, pending revisions.

Tao, J., Wu, D., Gourley, J., Zhang, S.Q., Crow, W., Peters-Lidard, C.,and Barros, A.P., 2016: Operational Hydrological Forecasting during the IPHEx-IOP Campaign- Meet the
Challenge. J. Hydrology, in press.

Nogueira, M., and Barros, A.P., 2015: Transient Stochastic Downscaling of Quantitative Precipitation Estimates for Hydrological Applications. J. Hydrology, No. 529, 1407- 1421. DoI:10.1016/j.jhydrol.2015.08.041.

Tao, J. and Barros, A.P., 2014: Coupled Prediction of flood response and debris flows initiation during warm and cold season events in the Southern Appalachians, USA. Hydrol. and
Earth System Sciences. DOI:10.5194/hess-18-1-2014.

Tao, J, and Barros, A. P., 2013: Prospects for Flash Flood Forecasting In Mountainous Regions-An Investigation of Tropical Storm Fay in the Southern Appalachians. J. Hydrology,
DOI:10.1016/j.jhydrol.2013.02.052.

Kang, D.H., and Barros, A. P., 2011b: Observing System Simulation of Snow Microwave Emissions over Data Sparse Regions. Part 2: Multilayer Physics, IEEE TGRSS, doi:10.1109/TGRS.2011.2169074.

Kang, D.H., and Barros, A. P., 2011a: Observing System Simulation of Snow Microwave Emissions over Data Sparse Regions. Part 1: Single Layer Physics, IEEE TGRSS, doi:10.1109/TGRS.2011.2169073.

Yildiz, O. and Barros, A.P., 2009. Evaluating spatial variability and scale effects on hydrologic processes in a midsize river basin. Scientific Research and Essays, 4(4): 217-225.

Bhushan, S., and Barros, A.P., 2007: A Numerical Study to Investigate the Relationship Between Moisture Convergence Patterns and the Spatial Distribution of Orographic
Precipitation Features from TRMM in Central Mexico. J. of Hydromet., 8,1264-1284.

Yildiz, O, and Barros, A.P., 2007: Elucidating Vegetation Controls on the Hydroclimatology of a Mid-Latitude Basin. J. Hydrology, 333,431-448, doi:10.1016/j.jhydrol.2006.09.10.

Yildiz, O., and Barros, A.P., 2005: Climate Variability and Hydrologic Extremes – Modeling the Water and Energy Budgets in the Monongahela River Basin. Climate and Hydrology in Mountain Areas. de Jong, C., Collins, D., and Ranzi, R. (Eds.), Wiley(Pub.), 303-318.

Gebremichael, M, and Barros, A.P., 2005: Evaluation of MODIS Gross Primary productivity (GPP) in the Tropics During the Monsoon. Remote Sensing of the Environment,
doi:10.1016/j.rse.2005.10.009.

Garcia-Quijano, J. and Barros, A.P., 2005: Incorporating Vegetation Dynamics into a Hydrological Model: Photosynthesis, Dynamic Respiration and Stomatal
Sensitivity. Ecological Modeling, Vol. 185, 29-49 .

Devonec, E. and Barros, A. P., 2002: Exploring the Transferability of a Land-Surface Hydrology Model. J. Hydrology, Vol. 265, 258-282.

Barros, A.P., 1995: Adaptive Multilevel Modeling of Land-Atmosphere Interactions. J. Climate, 8, 2144-2160.

Research Reports

Nogueira, M. and Barros, A.P., 2014: The Integrated Precipitation and Hydrology Experiment. Part III: High-Resolution Ensemble Rainfall Products Precipitation Datasets. Report
EPL-2013-IPHEX-H4SE-3, EPL/Duke University (Pub.), 38pp. http://dx.doi.org/10.7924/G8MW2F2W

Tao, J. and Barros, A.P., 2014a: The Integrated Precipitation and Hydrology Experiment. Part I: Quality High-Resolution Landscape Attributes Datasets. Report EPL-2013-
IPHEX-H4SE-1, EPL/Duke University (Pub.), V.1., 60 pp. http://dx.doi.org/10.7924/G8H41PBG

Tao, J. and Barros, A.P., 2014b: The Integrated Precipitation and Hydrology Experiment. Part
II: Atmospheric Forcing and Topographic Corrections. Report EPL-2013-IPHEX-H4SE- 2, EPL/Duke University (Pub.), V.1., 80pp. http://dx.doi.org/10.7924/G8RN35S6