Blankenship, Clay

Case, Jonathan

Elmer, Nicholas

Molthan, Andrew

Zavodsky, Bradley

NASA Technical Reports Server

1. Introduction
• National Water Center implemented operational 
National Water Model (NWM) to improve 
hydrological prediction (Figure 1)
• NWM is instantiation of Weather Research and 
Forecasting model hydrological extension 
package (WRF-Hydro) [Gochis et al., 2013] 
coupled with Noah Land Surface Model with 
Multi-Parameterization options (Noah-MP) [Niu
et al., 2011]
• Noah-MP includes vegetation parameterizations 
which use monthly climatological tables to 
define leaf area index (LAI) and green vegetation 
fraction (GVF) within the model
• However, LAI and GVF can deviate greatly from 
climatology as result of anomalous 
meteorological conditions or changes in land 
use-land cover due to agriculture, forest fires, 
etc.
• Changes in vegetation influence soil moisture 
and surface runoff, which are intrinsically linked 
to streamflow
• This study investigates the impact of replacing 
climatological vegetation in Noah-MP with real-
time vegetation
Figure 1. Example of streamflow product generated by 
the National Water Model.
Impacts of Real-time Satellite-derived Vegetation 
on WRF-Hydro Simulated Streamflow
Nicholas Elmer1,5, Bradley Zavodsky2,5, Andrew Molthan2,5, Jonathan Case3,5, Clay Blankenship4,5
Nicholas Elmer
University of Alabama in Huntsville
320 Sparkman Drive
Huntsville, AL 35805
nicholas.j.elmer@nasa.gov
256-961-7356
5. Conclusions and Future Work
• Accurate depiction of vegetation is needed for hydrological modeling applications
• Further calibration of WRF-Hydro against stream gauge observations using PEST parameter 
estimation tool (http://www.pesthomepage.org/)
• Investigate impacts of assimilating other NASA satellite datasets (e.g., SMAP, SWOT) into WRF-Hydro 
on simulated streamflow
References
Gochis, D. J., W. Yu, and D. N. Yates (2013), The WRF-Hydro Model Technical Description and User’s Guide, Version 1.0, NCAR Technical Document, 
120 pp., NCAR, Boulder, Colo. [Available at http://www.ral.ucar.edu/projects/wrf_hydro/.]
Niu, G.-Y., et al. (2011), The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and 
evaluation with local-scale measurements, J. Geophys. Res., 116, D12109, doi:10.1029/2010JD015139.
Xia, Y., et al. (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., 117, D03109, doi:10.1029/2011JD016048.
3. Methodology
• Coupled WRF-Hydro (version 3.0) with 
Noah-MP
• Real-time Suomi National Polar-orbiting 
Partnership (S-NPP) Visible Infrared 
Imaging Radiometer Suite (VIIRS) Green 
Vegetation Fraction (GVF) and SPoRT Land 
Information System (LIS) LAI replace 
climatological vegetation in Noah-MP
• Case study of 2015 December North 
Alabama Flood
• 2-year model spin-up, manual calibration
Figure 2. Leaf area index. (a) Noah-MP mean LAI for December. (b) VIIRS-derived LAI for 23 December 2015.
H51H-1618
2. 2015 December North Alabama Flood
• Warmer than average temperatures leading up to event
• LAI higher than climatological values (Figure 2)
• Heavy rainfall over multiple days in excess of 100 mm (4 in.) across much of northern 
Alabama and over 250 mm (10 in.) in some locations (Figure 3)
• Moderate to major flooding along several rivers in North Alabama, including Flint River 
and Paint Rock River (Figure 5) 
Figure 8. 0000 UTC 30 December 2015 (a) 10-40 cm volumetric soil moisture (%) for simulation using Noah-MP mean 
LAI and (b) the 10-40 cm volumetric soil moisture difference between (a) and the simulation using real-time VIIRS 
vegetation.
4. Preliminary Results
• Model hydrographs follow observations trend, but 
magnitude is lower than observed
• Replacing climatological vegetation with real-time 
vegetation in Noah-MP noticeably changes WRF-
Hydro streamflow
• 10-40 cm volumetric soil moisture is relatively 
unchanged when using real-time vegetation
Figure 3. Multi-Radar Multi-Sensor (MRMS) gauge 
corrected total precipitation (mm) for 72-hour 
period beginning 1200 UTC 23 December 2015.
Figure 5. 20-29 December 2015 observed discharge for the (a) Flint River and (b) Paint Rock River. National 
Weather Service flood categories (action, flood, moderate, major) are indicated by the colored shading 
(yellow, orange, red, and purple, respectively).  Gauge locations shown in Fig. 7. Hydrographs generated by 
http://nwis.waterdata.usgs.gov/.
Figure 4. 1200 UTC 23 December 2015 SPoRT-LIS 
0-10 cm volumetric soil moisture (%).
1Dept. of Atmospheric Science, Univ. of Alabama in Huntsville, Huntsville, AL
3ENSCO, Inc., Huntsville, AL
5NASA Short-term Prediction Research and Transition (SPoRT) Center, Huntsville, AL
2Earth Science Office, NASA Marshall Space Flight Center, Huntsville, AL
4Universities Space Research Association (USRA), Huntsville, AL
Figure 6. 20-29 December 2015 modeled streamflow 
for the (a) Flint River and (b) Paint Rock River.
Figure 7. 1200 UTC 28 December 2015 WRF-Hydro 
streamflow (cubic feet per second) for the simulation using 
real-time vegetation.
(a) (b)
(a) (b)
(a) (b)
(a)
(b)
https://ntrs.nasa.gov/search.jsp?R=20160014669 2019-08-29T17:08:26+00:00Z


Impacts of Real-Time Satellite-Derived Vegetation on WRF-Hydro Simulated Streamflow

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