International Conference on Urban Hydrology for the 21st Century
14-16 October 2002, Kuala Lumpur

Development of a hydrological model for
predicting the effects of land use changes at Yasu River basin

KIMARO, T.A
Graduate School of Civil Engineering, Kyoto University, DPRI,
611-0011, Gokasho, Uji, Kyoto Japan.
e-mail: ktumaini@hotmail.com
TACHIKAWA, Y
Disaster Prevention Research Institute Kyoto University
611-0011, Gokasho, Uji, Kyoto Japan
TAKARA, K.
Disaster Prevention Research Institute Kyoto University
611-0011, Gokasho, Uji, Kyoto Japan

Abstract This study proposes a hydrological model for Yasu river basin. The model is developed
using the object-oriented approach defining physical structures and processes by objects, which arelinked with specific rules, to simulate river flow at catchment’s level. The digital elevation model isused to define the connection of flow routing objects. A land surface parameterization scheme,
proposed by Noilhan and Planton (1989), is used for calculation of Evapotranspiration at grid scale, toprovide net rainfall input to the runoff routing model. Test results from similar climatic conditions in
China shows that the scheme can be applied with dependable results for this purpose. In the test
simulation conducted to verify the applicability of the scheme, the net radiation was quite well
reproduced to match the magnitude and patterns of daily variations. A combination of low value (0.4)
of solar foliage-shielding factor, and assumption of saturated soil conditions throughout the simulation,
was found to be sufficient for reproducing the observed fluxes in paddy field conditions. This was
possible even without modifying the structure of the scheme. Estimated surface temperature wasfound to be at least 60 to 70C higher than observed values. The estimated sensible heat did not fit wellto the observed data. The deviation however, did not seem to affect significantly the rest of otherfluxes as the sensible heat constituted only a small fraction of the net radiation, ranging from -40 to 40
w/m2, which is considered to be within the range of measurement errors in this experiment.
Keywords Yasu river basin, distributed hydrological model land surface parameterization

INTRODUCTION
The Yasu River basin has a catchment area of about 400 sq. km. The basin is located at the
headwaters of Lake Biwa in Shiga prefecture, Honshu Island, Japan. The rainfall tends to occur insummer from July to September and annual precipitation is about 1600mm. The lower part of thebasin is very flat and consists of paddy fields and urban settlements while the upper part has a hilly
terrain and is covered by forests. Several townships are located within the basin with a total
population of 220,000. Water resources of the basin are generally used for industrial, irrigation,
domestic supply and recreation. Surface as well as groundwater resources are extensively developed
to cater for these needs. There are 2 dams, 2 major weirs (diversion points) and several irrigation
canals for supplying water to paddy fields. There is a concern for proper management of water696

International Conference on Urban Hydrology for the 21st Century
14-16 October 2002, Kuala Lumpur

resources of this basin in order to satisfy optimally conflicting demands between water use formeeting daily demands and water required to maintain the environmental quality of the river. This
involves modeling studies to establish among others the sensitivity of water resources toenvironmental and climatic factors for future planning and operational for purposes.
STUDY APPROACH
The current work employs mathematical modelling for quantification of the runoff distribution in thebasin over space and time. The underlying assumption is recent and historical river flow variation
patterns can be explained by observed changes in both the forcing climatic and land use data. It is also
known that the rivers in the basin have been extensively taped for irrigation and water supply. With
this fact inn mind one of the objectives in this study is to include the spatial information data on water
use and study their effects downstream. Statistical analyses are able to show changes in the climatic
data but to interpret the effect of such changes to a river flow a model is required. In this particularstudy a distributed rainfall runoff model for a study basin is proposed at 500x500m spatial resolution.
The net rainfall input to this model is obtained by vertical moisture balance at same spatial resolution
using a land surface parameterization scheme with spatial data generated from observed groundstations in or near the basin. The horizontal movement of water is defined by digital elevation modelof the basin using the 8D steepest flow direction algorithm. Through the object oriented programming
approach, grid cells are considered as objects, which can be connected horizontally or vertically withother objects, data files or output files. This approach makes it easier to include any objects within themodel to represent physical structures or conditions, which affect the river flow, thus including theireffect on the simulated flow. In this particular work such objects are expected to represent structures
such diversion points, reservoirs or physical processes such as overland flow or evaporation. Layersof objects forms different levels of water balance in the vertical direction while horizontal position orconnection are determined by geographical data to include processes or structures affecting thehorizontal movement of water. A conceptual model of a basin using this approach is shown in Figure
1 below.

MODEL CONSTRUCTION
The object-oriented approach is employed in this study as an efficient way of interrelating the various
physical process and objects interacting with water movement horizontally and vertically in the study
basin. In the current study the model is divided into two main parts to deal with the vertical andhorizontal processes. The vertical process objects are defined to link data and functions for calculationof energy and moisture balance at grid scale. In the present formulation each grid cell is treated assuch object. The ohymos library functions Takasao et al. (1996), Ichikawa et al. (2000) is applied to
input data to the object and send results to other objects or output files. A typical vertical grid object
using the proposed land surface scheme consist of eight (8) data ports for sending in data and ten (10)send data ports for sending out the calculated variables. The input data consist of air temperature,697

International Conference on Urban Hydrology for the 21st Century
14-16 October 2002, Kuala Lumpur

solar radiation, long wave radiation, specific humidity, vapor pressure, wind speed, as well as albedo
and leaf area index. The send ports sends out the evaporation at Canopy level, ground level andevapotranspiration. Other results sent out are surface and deep ground temperature, soil moisture andthe net grid rainfall.

The horizontal movement of water over the land is defined by the steepest direction method using theDEM data. At each grid level excess rainfall generated by the vertical objects is sent to the input portsof horizontal objects for flow routing. In the current stage the horizontal objects uses the lumped
kinematic wave model Shiiba et al. (1996) to route the flow to outlet of the grid where the send port
sends it to a downstream object. To effect an automatic connection of objects horizontally the flow
map at the same resolution as grid cells is stored in a file, which is referred during model construction
while executing the model. The flow network stored in this form can be considered, as channels andinformation about physical structures can be included in the network at their exact geographicallocations. In this study a 50m DEM data of Japan is used to create a flow network at 500m resolution
utilized in this model as shown in figure 4.
PHYSICAL PROCESSESIn order to study water movement realistically the model have to simulate the physical processes
involved in the local water cycle. Of major concern here are biophysical properties of the basin, whichgovern exchange of moisture between land and atmosphere. When these processes are properly
represented in the model it enables river flow studies involving the dynamics of vegetal cover to be
conducted which is one of the main objective of this study. In the current approach the physicalprocesses involved in generating the net rainfall that is the main input to the rainfall runoff model aremodeled at each grid using a scheme proposed by Noilhan and Planton (1989). The scheme models

698International Conference on Urban Hydrology for the 21st Century
14-16 October 2002, Kuala Lumpur

the radiation balance at the ground surface and vertical moisture movement at each grid depending on
the climatic input data soil types and land use as defined by leaf area index and albedo. A schematic
diagram of this model is shown in Figure 2 followed by a brief discussion of the main components.
For full discussion of this scheme a reference is made to the works Noilhan and Planton (1989) andSealers and Mintz (1986) among others.

Rainfall
Evaporation
Canopy interception
Evapotranspiration
Evaporation

Over Land Flow
Top Soil Layer

Deep Soil Layer

Groundwater
Figure 2 Vertical Model Structure
The governing equations for energy and moisture movement in vertical direction applied for each gridare given at canopy level, ground level and deep soil level. Soil heat is described by temperature at thesurface and deep soil layer by equations 1 and 2 below as∂Ts
2π= CT G − (Ts − T2 )
∂t
τ

(1)

∂T2
1
= (T s − T 2 )
τ
∂t

(2)

Where Ts is surface layer soil temperature [K], T2 is the mean daily soil temperature [K] of deep soil
layer over period τ obtained by force restore method Bhumralcar (1975) and Blackdar (1976).
In Equation 3 G is the heat storage rate in the soil vegetation medium, which is equal to the sum of all
the atmospheric energy fluxes at the surface.

G = R n − H − LE(3)where Rn is the net radiation at the surface, H and LE the sensible and latent heat fluxes from theatmosphere.
The coefficient Ct in equation 4 is expressed as699

International Conference on Urban Hydrology for the 21st Century
14-16 October 2002, Kuala Lumpur

CT = 1 1 − veg veg +C v 
 CG

( 4)

where

W 
CG = CGsat  sat  W2 

b2log10(5)

To complete the definitions the values of b and CGsat are referred to clap and Honberger (1978).
The moisture movement is modeled at canopy top soil and deep soil layers. The soil moisture at top
layer (Wg) and in the deep (W2) layer are given by

∂w g
∂t

=

C1
C
( Pg − E g ) − 2 ( w g − w geq ),ρ w d1τ0 ≤ wg≤ wsat

(6)

And

∂w2
1
=
(Pg −Eg −Etr),0 ≤ w2 ≤ wsat
∂t
ρwd2

(7)

Where Pg is the flux of liquid water reaching soil surface, Eg the evaporation at the soil surface, Etr thetranspiration rate, ρw the density of liquid water and d1 an arbitrary normalization depth of ten
centimeters. The two coefficients C1 and C2 and the surface volumetric moisture Wgeq when gravity
balances the capillarity forces have been calibrated for different soil moistures as discussed in Noilhan
and Planton (1989). The equation governing intercepted water at the canopy level is stated as∂wr= vegP − (Ev − Etr ) − Rr∂t(8)where P is the precipitation rate at the top of the vegetation, Ev the evaporation from vegetation
including the transpiration Etr and direct evaporation Er when positive, and dew flux when negative(in this case Etr = 0), Rr is the runoff of the interception reservoir. This runoff occurs when Wr exceeds
a maximum value Wrmax depending on the density of the canopy. Wrmax is calculated according toDickinson (1984) as

Wr max = 0.2vegLAI[mm](9)For calculation purposes Equations 1 and 2 and 6 to 8 can be written in the following compact form

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International Conference on Urban Hydrology for the 21st Century
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















∂Tt
= f 1 (T s , T 2 , W 2 , W g , W r ; t )∂t∂T 2= f 2 (T s , T 2 ; t )∂t∂w g= f 3 (T s , W g , W 2 ; t )∂t∂w 2= f 4 (T s , W g , W 2 , W r ; t )∂t∂w r= f 5 (T s , w r ; t )
∂t

(10 )

Where f1 to f5 are functions representing the right-hand side of the original equations 1-2 and 6-8
above. A five step Runge Kutta method William et al. (1995) was utilized to obtain a simultaneous
solution of the system of equations (10) above for Ts, T2, W2, Wg and Wr while imposing the necessary
conditions for moisture and energy balance. As cited earlier the scheme even though taking into
consideration all important runoff generation factors such as soil types, vegetation cover soil moisture
yet it has remained simple enough to be applied with easy to a local area using operational
meteorological data. The real challenge however is specification of the initial conditions for moistureand temperature, which are important to arrive at correct results.
The Yasu River basin

The Yasu river basin is in Shiga prefecture Japan. The basin is approximately 400 square kilometers.
The mean annual rainfall is estimated at 1600 mm and the main land use categories are forests (60%),
paddy fields (20%) and urban area (9%). The urban area percentage is expected to increase in the near
future due urban rural migration caused by people looking for cleaner countryside environment for ahome away from overcrowded noisy urban areas of Osaka and Kyoto cities.

The upper reaches of the river have 3 dams namely Taniguchi, Yasugawa and Ohara for regulatingflows in the river during floods. The river gauges are installed at Ukawa, Kashiki, Chuugumbashi,

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International Conference on Urban Hydrology for the 21st Century
14-16 October 2002, Kuala Lumpur

Mikumo and Yasu and there are rain gauges at seven location fairly distributed over the basin asshown in Figure 5 above. Data available at these stations are summarized in Tables 1 and 2 below.
Table 1 Available River flow data in Yasu river basin

StationYasu
Chuugumbashi
Kasiki
MikumoUkawa

Available water level(hourly data)
1975-2001
1978-2000
1975-1998

Available Water level(daily data)
1975-2001
1978-2000
1978-2000
1975-1998
1978-1998

The Yasu river gauge is the main focus of river flow study and a point for comparing model
simulation and observed data. The station is located in the lower reaches of the river and the effect ofchanges upstream can thus be studied. The river flow at this station is also highly regulated by
upstream headwater works and dams requiring necessarily inclusion of such effects in the model inorder to compare the observed and estimated hydrographs. Rainfall records are better and extend alarger time period than river flow data as shown in Table 2.
Table 2 Available Rainfall data in Yasu river basin

StationLocation

Yasu (R27)
Kouga (R24)
Minakuti (R19)
Sasagi (R22)
KasigaKumoi
OgawaraShindenTouji

136o00’22” 35o04’10“136o14’17” 34o54’03”
136o10’07” 34o50’13”
136o19’40” 34o55’03.”
136o09’53” 35o00’35”
136o05’14” 34o58’04”
136o21’10” 34o58’39”
136o08’11” 34o53’50”
136o03’56” 34o58’57”

Available
continuous
hourly data
1969-1996
1969-1996
1969-1996
1969-1996
1969-1996
1969-1996
1971-1996
1970-1996
1969-1996

Meteorological data is available only at special observatories managed by the Japan meteorologicalagency. The nearest station is at Hikone observatory where input data required for evapotranspiration
has been obtained. This data includes the sunshine hours, vapor pressure and air temperature, which isused to calculate the long and short wave radiation input to the model. At least the records consist of
12 years of data dating back to 1989 from 2000.
Test simulations and discussions
Before using the model for studying the land use and climate changes it is required to test the various
components of the model to verify their ability to model the natural behavior. This not only involves
the check of the accuracy of calculations but more importantly the performance of the model in thesame climatic and environmental factors specific to a given basin. Since in this approach the model isdeterministic longterm term records are not necessary for calibration and verification as for a blackbox approach. However the tuning of parameters to obtain desirable results under assumptions ofvarious initial conditions are necessary. In the first part of this study the vertical process component
utilizing the Noilhan and Planton scheme was tested for paddy field conditions using Game/HubexIOP data Tanaka et al. (1998) obtained from test sites in China. The data was collected during thesummer season of 1998. During this experiment full set of flux data was obtained including radiation
data and climatic variables required as input to the land surface scheme. The experiment alsocollected data for temperature at ground surface and deep soil level thus providing a basis for702

International Conference on Urban Hydrology for the 21st Century
14-16 October 2002, Kuala Lumpur

comparing the results of the model with observation data at site. A total of 17 days of hourly data wasused in this study for simulation of surface energy balance and compare with the observation data tocheck the applicability of the scheme under paddy field conditions. Figure 6a to 6d presents the resultsof this simulation. In this simulation hourly net, latent, sensible and ground heat flux outputs from themodel are made and compared to observed values. Soil parameters obtained from literature were usedand vegetation parameters including solar foliage shielding factor (veg) were chosen to yield the best
representation of the observed fluxes. The net radiation (Figure 6a) was found to be the easiest to
reproduce since it has the minimum dependence on soil and vegetation parameters. The pattern andmagnitude of the estimated flux agrees quite well with the observations. The latent heat estimates(Figure 6b) could not be reproduced reasonably well except for a proper estimate of the solar foliageshielding factor (veg). In this case a value as low as 0.4 was found to be the most suitable forreproducing the observed fluxes in the paddy field site. A combination of this low value of foliage
shielding factor and saturation conditions in the soil layers throughout the simulation period enabled
the scheme to give good estimates of net radiation, latent and ground heat fluxes comparable to resultsof studies in sites with different land cover such as cropland and forests. It was thought earlier that
this scheme might need some modifications like those reported by Woskin et al. (2001) for Sib model
to reproduce observed fluxes in paddy field conditions. However the results of this study does notindicate the need for such modifications. The fact that a low foliage shielding factor gives good resultsin paddy field environment follows from the fact that more evaporation is expected from the water
covered ground in the paddy field than from transpiration. Estimated surface temperature was foundto be at least 60C to 70C too higher than observed values and highly dependent on the initially
specified temperature. This however was found to be necessary to maintain a good partition of the net
radiation at the surface into latent sensible and ground heat flux. The diurnal variation pattern andmagnitude of sensible heat flux (Figure 6c) deviated much from the observations. The deviation
however does not seem to affect the rest of fluxes as it constituted only a small fraction of the net
radiation ranging from -40 to 40 w/m2. This range is considered to be within the range ofmeasurement errors. The ground heat flux (Figure 6d) was also found to match well with theobservations. Since this scheme can easily utilize operational meteorological data it is recommended
for incorporating into distributed hydrological model to provide a better-estimated input.

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International Conference on Urban Hydrology for the 21st Century
14-16 October 2002, Kuala Lumpur

CONCLUSIONS AND FURTHER WORKS

This study has developed a hydrological model for Yasu River basin using the object-oriented
approach that defines physical structures and processes by objects, which are linked with specificrules to simulate flow at catchment’s level. The digital elevation model has been used to define theconnection of flow routing objects. The Noilhan and Planton land surface parameterization proposedfor calculation of evapotranspiration at grid-cell size in order to generate the net rainfall input to therunoff routing model has been tested using data from similar climatic condition. Test results showsthat the scheme can be applied with dependable results for this purpose.
Specifically the results of this study indicate thatz The land parameterization scheme of the Noilhan and Planton (1989) can used be in swampy
areas or paddy fields without necessarily having to modify the structure of the scheme making it
more complex provided the right conditions are specified during simulation.
z In order to estimate properly the evaporation losses from paddy field, a low value of solar foliage
shielding factor veg have to be specified despite the fact that paddy crop seems to cover thewhole ground suggesting a high value for this parameter.
z The representation of the basin’s physical processes and structures as objects interacting witheach other in the simulation process is suggested as the best way of including man made effects
such as dams and diversions to hydrological models.
The next work in this study is to apply the proposed parameterization scheme to the whole of Yasu
basin and use the calculated net rainfall to simulate river discharge. It is expected that a continuous
simulation with real land use data as represented by leaf area Index and albedo in the Noilhan and
Planton scheme used evapotranspiration calculations will give clue to the effect of land use changes
on the river flow.

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International Conference on Urban Hydrology for the 21st Century
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ACKNOWLEDGEMENT

The authors thank Dr. Tanaka Kenji, Water Resources Research Center, Kyoto University for making
available the data used in the evapotranspiration studies.
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