BASIN
G. Chirila & S. Matreata
National Institute of Hydrology and Water Management, Sos. Bucuresti – Ploiesti 97, 013686, Bucharest, Romania
Corresponding author: G. Chirila
ABSTRACT
This paper presents some results regarding the climate change impact on the water resources, in a small river basin. For the evaluation of the climate change impact more hypothetical scenarios were used; scenarios which take into consideration uniform changes for temperature and precipitation. The impact of those possible climatic changes on the catchment runoff was analysed using an integrated water balance model – the WATbal model.
The analysis was done on the Representative Basin Tinoasa Ciurea, which is a small catchment situated in the north-eastern part of Romania. The simulation results show a significant vulnerability of the water resources to climate change. For example, the impact estimated using the WATbal model, shows that an increase of air temperature by 1o C should reduce runoff by 3.5%, and an increase or a decrease of precipitation by 20% leads to an increase or a decrease of runoff by more than 30%.
Keywords: WATbal model, small basin, climate change impact
Introduction
This paper aims at estimating through the use of the WATbal model the vulnerability of water resources in a small river basin, as a response to climate change. Another objective of this paper is the estimation of differences resulting from the application of the model in the same representative basin, but using as input meteorological data that were recorded at meteorological stations situated outside of the studied basin.
For the evaluation of climate change impacts in the analyzed basin, several hypothetical scenarios were used, representing a series of future possible climates. The chosen scenarios take into consideration uniform annual changes for temperature and precipitation, considering that they will cover the future possible range of climate change.
The WATbal Model (WATer BALance Model) – relies on concentrated parameters and was developed by Kazmarek (1993). It uses simple hypotheses linked to the water balance and robust physical estimation approaches of potential evapotranspiration. Due to the capacity of the WATbal model to allow different approaches, variable time steps can be used depending on available data and river basin characteristics.
Methodology
The components of the Watbal model
The uniqueness of this global conceptual model for representing the water balance consists in using continuous functions for the relative storing (accumulation) in order to determine the surface, subsurface runoff and evapotranspiration. In this approach the mass balance is written as a differential equation and the accumulation is presented as a unique reservoir, conceptualized with discharge and infiltration components depending on the state, relative storage variable.
Evapotranspiration,
Fig. 1: Conceptualization of the water balance for the WATbal model (after Yates and Strezepek, 1994b).
The model has two components:
• The water balance component (using continuous functions in order to describe water movements in a conceptualized basin);
• Potential evapotranspiration, based on the Priestley-Taylor method (Yates 1994a).
The water balance component (Fig. 1) contains 5 parameters which refer to:
• Direct runoff,
β
• Surface runoff, ε
• Subsurface runoff,
γ
• Maximum capacity of the water retention basin (field capacity, Smax)
• Base runoff, Rb.
The direct runoff coefficient
β
and the strength factor of hypodermic runoffγ
are not part of the automated optimization procedure (they are defined by the author).The potential evapotranspiration is calculated with the Priestley-Taylor method which contains 3 parameters:
• Cf = has a value of 1.26 for a humid climate (relative humidity > 60%) and 1.74 for an arid humid climate (relative humidity < 60%);
• Priestley-Taylor coefficient PT
• terrain coverage coefficient GC
For the calibration and validation of the model the data on precipitation, potential evapotranspiration, and runoff (discharge) are needed. Potential evapotranspiration can be provided as mean monthly values (calculated with different methods). Alternatively, it can be calculated by the model with the Priestley – Taylor method. In such a case, temporal series of air temperature, duration of sunshine, relative sunshine and wind speed are needed as input data.
The evaluation of the model is based on the use of two data series: one used for calibration and another for validation. If the statistical values, namely the correlation coefficient (
ρ
) and the mean monthly error between the measured discharges and the simulated ones( )
EP,O , resulting from the calibration and validation procedures are similar, the model can be considered acceptable.The variation coefficient is given by:
( )
where: Cov
(
QO,QP)
is the covariation of the observed and simulated dischargesP
O Q
Q σ
σ are the standard deviations of the observed and simulated series.
The mean monthly error between the simulated and the observed discharges is given by:
( )
where: QO is the observed mean monthly discharge,
QP is the mean monthly discharge simulated with the model.
The elaboration of scenarios for the evaluation of an impact of climate change
The elaboration of the scenario for the evaluation of the impact of a climatic change was made through the hypothetic scenario method. The hypothetic scenarios are a set of future possible climates. These chosen scenarios consider uniform changes for air temperature (∆T) and precipitation (%P), in the following combinations, considering that they will cover the possible future climate domain (Table 1).
Table 1: Used uniform climatic scenarios (0*- basic scenario) T [ºC], P[%].
T+0, P+0* T+0, P+10 T+0, P+20 T+0, P-10 T+0, P-20
T+2, P+0 T+2, P+10 T+2, P+20 T+2, P-10 T+2, P-20
T+4, P+0 T+4, P+10 T+4, P+20 T+4, P-10 T+4, P-20
Case study
Physical – geographical description of the analyzed river basin – R. B Tinoasa – Ciurea
The representative basin Tinoasa Ciurea has a catchment area of 4.17 km2 and its elevation ranges between 119 and 410 m. a.s.l. The average slope is 15.9% with a predominantly northern orientation.
It has an excessive continental climate which is characterized by an annual precipitation of 600-650 mm. The seasonal distribution of precipitation is uneven during the year: minimum monthly precipitation of 30 mm is recorded between August and October. Almost half of the annual precipitation falls between May and August with a maximum in July, often having torrential character. The mean annual temperature is around 9 °C (the hottest month is July with 21.3 0C and the coldest month is January with a mean temperature of minus 3.6 oC;
the temperature drops below 0oC starting with the second decade of December). This type of climate generates a large amplitude in runoff.
Forests cover the largest part of the catchment (63%) and contribute to the diminishing of surface runoff quantity.
Calibration and validation the WATbal model
For the Ciurea Basin 16 years of data were available (1979-1994), from which 10 were used for calibration (1979-1988) and the last 6 years for validation. The results are presented in figures 2-3.
0
1979 1980 1981 1982 1983 1984 1985 1986 1987 1988
Discharge(mm/day)
Precipitation Q modeled Q obs erved 0
1979 1980 1981 1982 1983 1984 1985 1986 1987 1988
Discharge(mm/day)
Precipitation Q modeled Q obs erved
Fig. 2: Precipitation and mean monthly observed and modeled hydrographs in the calibration period – R.B. Tinoasa Ciurea.
1989 1990 1991 1992 1993 1994
Discharge (mm/day)
Precip itation Q m odeled Q obs erved
Fig. 3: Precipitation and mean monthly observed and modeled hydrographs in the validation period – R.B. Tinoasa Ciurea.
Calibrated and validated coefficients used in the WATbal model for the Tinoasa-Ciurea basin are:
• subsurface flow coefficient
γ
= 2.0• subsurface flow coefficient α = 1.0
• surface runoff coefficient
ε
= 1.34• maximum accumulation capacity coefficient
S
max= 313• initial accumulation zi = 0.5
• direct runoff coefficients
β :
= 0.0• latitude 47O N ;
• Priestley –Taylor coefficient PT = 1.74
• terrain coverage coefficient GC = 0.65
• base runoff Rb = 0.0
In Table 2 are presented the values of the correlation coefficients and the mean monthly errors between the measured and the simulated results for the calibration and validation periods.
Table 2: Calibration and validation values for R.B. Tinoasa – Ciurea.
Correlation Coefficient Mean Error
Calibration 0.88 0.24
Validation 0.90 0.27
Impacts of climate change scenarios on runoff, for R.B. Tinoasa-Ciurea:
The hypothetic impacts of climate change scenarios on runoff, estimated using the WATbal, model are presented in Table 3 and Fig. 4. Table 3 shows sensitivity of catchment runoff to the change in climatic variables. For example, an increase of air temperature by 1o C is likely to reduce runoff by 3.5%. An increase or a decrease of precipitation by 20% leads to an increase or a decrease of runoff by more than 30%.
Table 3: Change in runoff [%] in the studied catchment related to changes in air temperature and precipitation.
P 0 P 10% P 20% P-10% P- 20%
Fig. 4: Observed (To) and simulated mean monthly discharges (T2, T4), corresponding to temperature increases of 2°C and 4°C, respectively.
Another objective of the paper was the application of the model in the same representative basin, but with input meteorological data, taken from a meteorological station situated outside of the basin (Solesti Meteorological Station situated at an altitude of 118 m.a.s.l.) (Figs. 5-6). Catchment precipitation was calculated from several nearby stations using the elevation gradient method. Statistical parameters for calibration and validation periods (Table 4) emphasize weaker results that are caused by the extrapolation of the input data.
Table 4. Calibration and validation values using data from M.S. Solesti.
Correlation coefficient Average error
Calibration 0.75 0.28
Fig. 5: Precipitation and the observed and modeled mean monthly hydrographs in the calibration period – R.B. Tinoasa Ciurea, M.S. Solesti.
0
Fig. 6: Precipitation and mean monthly hydrographs in the validation period – R.B. Tinoasa Ciurea, M.S.
Solesti.
Conclusions
The WATbal model chosen in the present study is a water balance model for the evaluation of climate change impacts in a river basin. The model uses a simple hypothesis regarding the water balance and a strong physical approach for the estimation of potential evapotranspiration. The model was applied to the representative basin Tinoasa-Ciurea. Even though the WATbal model has a quite simple conceptual structure, the good results confirm the possibility of using it in the case of a little hydrographic basin, too.
After calibration and validation of the model on this representative basin Tinoasa – Ciurea, it was possible to evaluate the impact of different climate changes using more hypothetical scripts. Thus, for a uniform increase of temperature with 1oC resulted a decrease in discharge of 3.5%. An increase or a decrease of precipitation by 20% would lead to an increase or a decrease of catchment runoff of more than 30%.
To point out the model’s sensitivity to the accurate estimation of the input data, a comparative analysis of the model’s performances using input data from a station situated outside of the basin was done. A significant decrease of the calibration and validation performance was noted as a result.
References
Kaczmarek Z. (1993). Water balance model for climate impact analysis. Acta Geophysica Polonica, 41: 1-16.
Yates D.N., Strzepek K.M. (1994a). The Impact of Potential Evapotranspiration Methodology on the Determination of River Runoff. IIASA Working Paper, WP-94-46, Laxenburg, Austria.
Yates D.N., Strzepek K.M. (1994b). Comparison of Models for Climate Change Assessment of River Basin Runoff. IIASA Working Paper, WP-94-45, Laxenburg, Austria.