IUKWC Workshop Nov16: Developing Hydro-climatic Services for Water Security – Session 6 – Item 3 P_Srivastava
WRF-PDM: Prototype for
discharge prediction in
Prashant K. Srivastava
IESD, Banaras Hindu University,
Hydro-meteorological variables such as Precipitation
and Reference Evapotranspiration (ET) are the most
important variables for discharge prediction.
The mesoscale model such as WRF (Weather
Research & Forecasting model) can be used for
prediction of hydro-meteorological variables.
While, Probability Distributed Model (PDM)--a rainfall
runoff model can be used for discharge prediction and
Therefore, an integration of WRF with PDM up to some
extent can solve the problem of discharge prediction in
data limited regions.
Sensitivity and Uncertainty analysis
The sensitivity analysis (SA) and uncertainty
estimation (UE) are important for rigorous model
calibration and thus facilitate a good modelling
practice for hydrological predictions.
There are many models available for SA and UE such
as GLUE, SUFI, Parasol etc.
In WRF-PDM, for sake of simplicity GLUE model is
used in integration with PDM for SA and UE.
The main advantage with the GLUE parameter
uncertainty is that it takes into account all sources of
uncertainty either explicitly or implicitly.
In future other models will be also integrated in WRF-
PDM framework such as IHACRES, Top model etc
Srivastava et al., 2015. Theoretical and Applied Climatology
Performance of ET extracted from satellite
After acquiring input information required
for any rainfall runoff model i.e. rainfall and
ET, the discharge can be predicted.
However, as mentioned before making any
prediction a rigorous calibration of those
models are needed.
Further uncertainty should be taken into
account before using the forecast for
operational applications to minimize any
Discharge prediction using WRF-PDM
with SA and UE
Further development of WRF-PDM: Inclusion
of Bias correction schemes
Srivastava et al., 2015, Water Resource Management
Pairs %Bias RMSE d r
Obs/WRF calibration 83.0 0.10 0.76 0.75
Obs/WRF validation 82.0 0.11 0.72 0.68
Obs/RVM calibration -1.1 0.09 0.85 0.76
Obs/RVM validation 3.9 0.10 0.79 0.69
Obs/GLM calibration -- 0.10 0.84 0.75
Obs/GLM validation 3.3 0.10 0.80 0.68
Pairs %Bias RMSE d r
Obs/WRF calibration 4.5 0.55 0.41 0.25
Obs/WRF validation -4.9 0.70 0.29 0.15
Obs/RVM calibration -3.3 0.37 0.42 0.38
Obs/RVM validation 2.6 0.44 0.20 0.20
Obs/GLM calibration -- 0.39 0.22 0.25
Obs/GLM validation 22.30 0.45 0.16 0.15
Other Possible Applications of
• Agricultural water management: Framework can be used
for irrigation water management using soil moisture deficit
from WRF-PDM, crop type and soil hydraulic parameters
• Weather applications: The downscaled meteorological
products can be used for climate variability and trend
• Natural disaster management: Flood and drought
• Calibration and validation of optical/microwave satellite
• Several other applications: Land trafficability, crop
Srivastava et al., 2015 Journal of Hydrology
The suitability of data for rainfall–runoff modelling suggests that ET from
WRF meteorological dataset is promising and has comparable
performance to the observed datasets.
On the other hand, WRF downscaled precipitation and ET together give a
poor performance, indicating that there is a need of more work on
parameterization schemes to improve the precipitation estimates or
utilization of some other sources are needed such as radar for
Further more work is needed on the bias correction of the mesoscale or
satellite data to reduce the error in the prediction
Integration of SA and UE in prediction modelling is needed. It will be
useful for planner and disaster management and important for quality
control in the estimation of underlying uncertainty and related
There is need of exploration of other hydrological models (IHACRES,
Framework for Understanding Structural Errors (FUSE) etc) as well as SA
and UE techniques to improve the performances and prediction quality.
Assimilation of satellite dataset such as soil moisture or precipitation in
WRF-PDM can improve the performance, so will be attempted in future.