Hydrological Modeling for Upper Chao
Phraya Basin Using HEC-HMS
UNDP/ADAPT Asia-Pacific First Regional Training Workshop
Assessing Costs and Benefits of Adaptation: Methods and Data
March 11-14, 2013
Dr. Dilip K. Gautam
RIMES, AIT Campus, Bangkok

 A model is a simplified representation of reality.
 A mathematical model consists of series of equations defining the system we are dealing with. The function of model is to convert the given input into an output.
 A hydrological model is the mathematical representation of the response of a catchment system to hydrologic events during the time period under consideration.
 Hydrological phenomena are extremely complex, highly non-linear and highly variable in space and time.
 A model is needed to predict the watershed runoff for the design and management of water resources utilization and flood control projects.

Classification of Hydrological Models

Hydrological Model Outputs for
Climate Change Impact Assessment
 Simulated flow peaks, volumes and hydrographs at the outlets of subbasins and the points of special interest such as reservoirs, weirs or other hydraulic structures
 Simulated long flow sequences for water budget and drought analyses
 Simulated extent of flooded areas for different precipitation events and various antecedent basin conditions

Hydrologic processes that need to be captured by the model
 Single-event precipitation-runoff transformation
 Continuous precipitation-runoff transformation
 Snow accumulation and melt
 Interception, infiltration, soil moisture accounting
 Evapotranspiration
 Regulated reservoir operation

HEC-HMS
• US Army Corps of Engineers, Hydrologic Engineering
Center’s Hydrologic Modeling System software
• Designed to simulate both single event and continuous rainfallrunoff process
• Simulates precipitation-runoff and routing processes, both natural and controlled
• HEC-HMS uses a separate model to represent each component of the runoff process including:
 runoff volume;
 direct runoff (overland flow and interflow);
 baseflow;
 channel routing.

HEC-HMS representation of watershed runoff

 Runoff Volume models: separate infiltration from pervious surface, runoff from impervious surface, compute the direct runoff volume
 Direct Runoff models: transform direct runoff volume from excess precipitation into fast component of flow
 Base Flow models: compute slow subsurface drainage component
 Routing models: compute flow attenuation and translation over channel
 Reservoir models: flow regulation

Data Required
 Digital Elevation Model (DEM), land use, soil types and other physiographic data
 Precipitation, temperature data
 Evaporation/evapotranspiration data
 Discharge, Water level and Rating curve data
 Channel and reservoir hydraulic data
 Generated sequence of meteorological data representing various scenarios of future climate

Upper Chao
Phraya Basin,
Thailand
Catchment Area
= 105553 sq. km.

Dams and Reservoirs
 Bhumibol dam in the Ping River (Storage 13462 MCM)
 Sirikit dam in the Nan River (Storage 9510 MCM)
 Kwae Noi dam in Kwae Noi River (Storage 766 MCM)
 Kiew Kor Mha dam in Wang River (Storage 171 MCM)
 Kiew Lom dam in Wang River (Storage 112 MCM)

Data preparation using HEC-GeoHMS
 Delineate catchment and river network
 Obtain catchment characteristics data (area, slope etc)
 Make Thiessen polygon
 Obtain Thiessen weights
 Prepare basin file

Data preparation using HEC-DSSVue
 Time series data (rainfall, discharge etc.)
 Pair data (elevation-storage)

Model Setup
 Basin model
 Meteorological model
 Time series data
 Pair data
 Control specification

Meteorologic model
 Precipitation
 Evapotranspiration
 Snowmelt : not applicable for upper Chao Phraya

Precipitation methods
 Gauge weights : selected for upper Chao Phraya
 Inverse distance
 Gridded precipitation
 Frequency storm
 SCS storm
 Specified Hyetograph
 Standard project storm

Evapotranspiration methods
 Monthly Average : selected for upper Chao Phraya
 Priestley-Taylor
 Gridded Priestley-Taylor

Snowmelt methods
 Gridded temperature index
 Temperature index

Control Specifications
 Simulation start date/time
 Simulation end date/time
 Time interval

Model Calibration
 Finding optimal parameter values
 Minimizing difference between simulated flow and observed flow
 Objective functions
 Peak weighted RMS error
 Percent error peak
 Percent error volume
 RMS log error
 Sum of absolute residuals
 Sum of squared residuals
 Time weighted error

Search Algorithms
 Nelder Mead
 Univariate Gradient

Simulated Hydrograph at Basin Outlet
R2 = 0.71
BIAS = 6.7 % NS = 0.71

Conclusions
 Semi-distributed physically based deterministic hydrological models are powerful tools for assessing climate change impact on water resources.
 Continuous modeling approach could be taken to assess the impact on flow volume.
 Care should be taken to interpret the results as there are lots of uncertainties in the model inputs, parameters and structure of the model. Uncertainties associated with climate models will also be carried over.

Dr. Dilip K. Gautam, Senior Hydrologist, RIMES
E-mail: dilip.gautam@rimes.int
Website: www.rimes.int