A Comparative Study of Model-Driven Soil Moisture Estimateson the Chungju Demonstration Basin
Byong-Ju Lee1 , Il-Won Jung2 and Deg-Hyo Bae3
1 Graduate Student, Dept. of Civil & Environ. Eng., Sejong Univ., Seoul, Korea
bjlee0704@paran.com
2 Post Doctor, Dept. of Civil & Environ. Eng., Sejong Univ., Seoul, Korea
3 Professor, Dept. of Civil & Environ. Eng., Sejong Univ., Seoul, Korea
Abstract The objectives of this study are to provide the availability of hydrologic andmeteorologic data including soil moisture on the AWCI demonstration basin and toevaluate the model-driven soil moisture obtained from hydrologic runoff models. For
the simulation of river discharge and soil moisture over the 6,648 km2 Chungju dam
basin in Korea, SWAT, PRMS, VIC and SLURP models are used. The measured soil
moisture data revealed that the soil moistures of summer wet season are high and thoseof winter dry season are low, but the spatial variations at the same periods are very high.
Also, the simulated discharges were well presented to the observed ones, but thebehaviors of soil moisture were different depending on soil moisture generation
structures. Simple arithmetic average from a few point measurements has a possibility
to distort the basin average soil moisture.
Key words soil moisture; Chungju dam; SWAT; PRMS; VIC; SLURP
1. INTRODUCTION
Asia monsoon is one of the largest water circulation systems in the world andprovides substantial water resources that can be used for power generation, foodproduction and transportation facilities. At the same time, it sometimes causes serious
water-related problems such as flood and drought. GEOSS/AWCI was launched forsolving water-related problems caused by Asia monsoon water cycle and decided to set
up a demonstration basin per each country. The Chungju dam basin with 6,648 km2 isselected for the Korean demonstration basin.
Soil moisture is one of the most important factors for water cycle processes. It
directly affects to the variations of evapotranspiration and surface runoff. However, themeasured soil moisture data, especially for those of basin scale rather than point scale,are rarely available. The model-driven soil moisture data or satellite-based soil moisture1

measurement will be one of the remedies for solving this kind of basin-scale soil
moisture data problem.
In this study, we will evaluate the feasibility of model-driven soil moisture data for
the integrated data management system over the AWCI demonstration basin. The
hydrologic models used in this study are SWAT, PRMS, VIC and SLURP. The measured
soil moisture data are used to evaluate the model-driven soil moisture data.
2. MODEL-DRIVEN SOIL MOISTURE
It is important to select runoff model which can represent complex characteristics ofbasin to estimate model-driven soil moisture data. In this study, we chose semidistributed continuous simulation models such as SWAT, PRMS, VIC and SLURP. The
basic concepts of the model and their soil moisture accounting methods are as follows.
Soil and Water Assessment Tool (SWAT) developed by USDA is a semi-distributed
continuous simulation model. This model has been widely applied to predict the effectsof climate and vegetative changes, groundwater withdrawals and reservoir management(Arnold et al., 1998). Precipitation-Runoff Modeling System (PRMS), developed by
USGS and used for the long-term runoff analysis, is a physically-based deterministicand distributed-parameter modeling system (Leavesley et al., 1983). It is designed toanalyze the effects of precipitation, climate, and land use on streamflow and generalbasin hydrology. Variable Infiltration Capacities (VIC)-nL model is a land surface
model based on the main hydrological process in which the interaction of atmosphere,vegetation and soil, the dynamic change of water and energy flux are considered. One
distinctive feature of this model is that it represents the sub-grid spatial heterogeneity of
precipitation with sub-grid spatial variability of soil infiltration capability (Liang et al.,1994). Semi-distributed Land Use-based Runoff Processes (SLURP) is a conceptualmodel which is capable of use as a fully-distributed hydrological model, althoughnormally used in semi-distributed form (Kite, 1978).
The soil-moisture accounting method for the selected models is generally performed
as the algebraic summation of all moisture accretions to and depletions from the soil
profile, shown in Fig. 1. The depletions usually include evapotranspiration, lateral flowand percolation, while the accretions are rainfall and snowmelt input to the system.
These models, however, obviously have different structure based on their model
development purposes and simulation capabilities. The soil profile of SWAT can bedivided into a maximum of 10 layers and each soil layer is divided into the free waterand tension water fields according to the boundary of field capacity (FCi) and wilting
point (WPi). Total soil water(SW) is a summation of each SWi on the soil layers.

2However, the soil profile of PRMS is divided into two layers: the recharge zone and thelower zone. Losses from the recharge zone occur from evaporation and transpiration,
while those from the lower zone are transpiration only. The evapotranspiration losses
are a function of available soil-moisture storage. The attempt to satisfy potential
evapotranspiration is worked from the recharge zone storage before water will move tothe lower zone. When soil-zone storage reaches maximum available water capacity (FCWP) of soil zone, all additional infiltration is routed to the subsurface and ground-water
reservoirs. Land surface of VIC model is divided to different land covers and bare soil
horizontally and partitioned into 3 layers which include top soil layer (usually taken as
100 mm depth from the surface), the upper soil layer and the lower soil layer vertically.
Quick bare soil evaporation following small summer rainfall events happens in the top
soil layer; the upper soil layer is designed to represent the dynamic change of soil
moisture and the production of runoff when rainfall happened; soil moisture change andbaseflow mainly occurred in the lower soil layer of the model. Ki and Di in Fig. 1 ishydraulic conductivity (mm/d) and diffusivity (mm/mm), respectively. In the SLURP,
rainfall or snowmelt enters into the soil water storage as long as the infiltration capacity
is not exceeded. Otherwise, water is released as surface runoff. When water from thesoil water storage is higher than the field capacity (FC), then the excess is spilled as
Qlatral. Percolation takes place at a rate depending on the current store contents, theretention constant and the wilting point.
ET
FC1

Qsep,nFC10

free water
SW 10tension water

WP10Qlateral

FCWP…

WP1

TINF

free water
SW 1tension water

Qlateral

ETET

INF

SW 1 top thin layer

recharge zoneSW

FC1

lower zone
subsurface res.
Qsubsurf,rcg
groundwater res.
Qgw,rcg

K1

WP1

Qlateral FC2
Qgw

K2

D1
SW 2
upper layer
SW 3lower layer

WP2

PERCa) SWAT

ET

INF

b) PRMS

FC

D2

INF

free water
SW

Qlateraltension water
WP

QbPERCc) VICd) SLURP

Fig. 1 Conceptual structure of soil water movement on SWAT, PRMS, VIC and SLURP
3. SOIL MOISTURE MEASUREMENT
Soil moisture data provided by Agriculture Weather Information System is used in thisstudy, as shown in Fig. 2. Among 113 observation stations, we used the data of 50
stations that have multi-year records. TDR (Time Domain Reflectometry) is used tomeasure the soil moisture and the percent (%) of soil water content for total soil volume
is adopted as an unit of the measurement. The monthly averages for the stations during
the period 2004-2005 are shown in Fig. 3. It can be seen that the soil moisture is higher3

during the rainy season (July-Sept.), while lower during dry season (Dec.-Jan.).
Although in the same month, the soil moisture is different up to 5 times depending on
the region of the station. Some of the stations located in northern part have the increaseof soil moisture in March due to snowmelt effect.
4. MODEL APPLICATIONThe Chungju dam basin, which is about 6,648 km2, isdecided to the Korean demonstration basin of AWCI and
selected for the soil moisture study. There exist 56
precipitation stations, 21 discharge stations and 12meteorological stations and routinely collect thehydrological and meteorological data that are essential for
configuration of water cycle behaviors. However, only 2
stations are operating for the soil moisture measurement.
We used 4 different hydrologic models for the soil
moisture computations. Before generating soil moisturefrom the models, all the models are calibrated for themodel parameter estimation and verified for confirming

KOREA

OBS2
OBS1
Chungju dam

station (less than 1 year)
station (more than 1 year)
available station (2004-2005)

Soil moisture / Soil (%)

their model performance for 10-year data (1996-2005 forFig. 2 The status of soil
the calibration and 1986-1995 for the verification). Somemoisture stationof the simulated daily runoff, as a60max. boundaryfunction of transformed flow (Hogue40et al., 2000), are shown in Fig 4. The
simulated flow data are well fitted to20Min. boundary
the measured values for both high and012345678910 11 12
low water levels. The Nash-SutcliffeMonthefficiencies between the simulated and Fig. 3 The average monthly soil moisture(%)
the measured flows were ranged on on the 30 sites.
0.61-0.86. Fig. 5 shows the modeldriven monthly averaged soil moisture ratios in addition to the observations during
2003-2004. These ratios are varied on the range of 10-30% and the model-driven soilmoistures were different from models depending on evapotranspiration and runoff
mechanisms.

4

Tran. flow (m3/s)

Tran. flow (m3/s)

60

OBS
SIM

SWAT
40
200
2002

2003

2004

2005

60
40
200
2002

2003

60

OBS
SIM

VIC
40202003

2004

2005

Year
Tran. flow (m3/s)

Tran. flow (m3/s)

Year02002

OBS
SIM

PRMS

2004

2005

60OBSSIMSLURP
402002002

2003

Year

2004

2005

Year

Soil moisture / Soil (%)

Fig. 4 The daily measured and simulated flow from each model.
40OBS_JCOBS_PCPRMS
SLURPSWAT
VIC

30
20100

123456789101112MonthFig. 5 Monthly averages of the measured and the simulated water contents
5. CONCLUSION AND RECOMMENDATIONSThe spatial and temporal variations of soil moisture are important for the Asia water
cycle investigation, but difficult to maintain the measurement data covering the wholewater cycle domain. In this study, we provided the current measurement of soil moisturein Korea and analyzed the monthly variations. We also applied 4 different semidistributed hydrologic models for soil moisture generations on the AWCI demonstration
basin.
In general, the measured soil moisture data revealed that the soil moistures of summer
wet season are high and those of winter dry season are low, but the spatial variations at
the same periods are very high. It represents that the simple arithmetic average of point
soil moisture measures within the study basin area has a possibility to distort the truebehavior of soil moisture. Also, the model-driven soil moistures are different frommodel to model, although each model was calibrated for the model parameter estimatesand verified for the model performance by using observed and simulated riverdischarges. It maybe caused by different soil moisture structures and evapotranspiration
computation mechanisms. Further investigations will be necessary, especially focusing5

on inter-comparison analysis of soil moisture and evapotranspiration. Also, the use ofsatellite data will be another approach for soil moisture generations.
Acknowledgements
This research was supported by a Natural Hazard Mitigation Research (Development of realtime inland flooding prediction techniques considering urban characteristics) in Korea.

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