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Modelling climate change impacts on the seasonality of water resources in the Upper Ca River Watershed in Southeast Asia.

Giang PQ, Toshiki K, Sakata M, Kunikane S, Vinh TQ - ScientificWorldJournal (2014)

Bottom Line: The results indicated that temperature and evapotranspiration will increase in all months of future years.The greatest monthly increase of up to 29% and the greatest monthly decrease of up to 30% are expected in the 2090 s.As a result, decreases in dry season discharge and increases in wet season discharge are expected, with a span of ± 25% for the highest monthly changes in the 2090 s.

View Article: PubMed Central - PubMed

Affiliation: Department of Environmental and Life Sciences, University of Shizuoka, 52-1 Yada, Suruga-ku, Shizuoka-shi, Shizuoka 422-8526, Japan ; Faculty of Land Management, Vietnam National University of Agriculture, Hanoi 131000, Vietnam.

ABSTRACT
The impact of climate change on the seasonality of water resources in the Upper Ca River Watershed in mainland Southeast Asia was assessed using downscaled global climate models coupled with the SWAT model. The results indicated that temperature and evapotranspiration will increase in all months of future years. The area could warm as much as 3.4(°)C in the 2090 s, with an increase of annual evapotranspiration of up to 23% in the same period. We found an increase in the seasonality of precipitation (both an increase in the wet season and a decrease in the dry season). The greatest monthly increase of up to 29% and the greatest monthly decrease of up to 30% are expected in the 2090 s. As a result, decreases in dry season discharge and increases in wet season discharge are expected, with a span of ± 25% for the highest monthly changes in the 2090 s. This is expected to exacerbate the problem of seasonally uneven distribution of water resources: a large volume of water in the wet season and a scarcity of water in the dry season, a pattern that indicates the possibility of more frequent floods in the wet season and droughts in the dry season.

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Related in: MedlinePlus

Monthly time series comparison of simulated versus observed river discharge at Yen Thuong Station with reference to monthly precipitation during the 15-year validation period (1996–2010).
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Related In: Results  -  Collection


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fig3: Monthly time series comparison of simulated versus observed river discharge at Yen Thuong Station with reference to monthly precipitation during the 15-year validation period (1996–2010).

Mentions: Figures 2 and 3 graphically illustrate the time series comparison of simulated and observed cumulative monthly river discharge with reference to monthly precipitation for the Ca River at Yen Thuong Station, over the 25-year calibration (1971 through 1995) and 15-year validation (1996 through 2010), respectively. Overall, the SWAT model accurately tracked the observed river discharge for both time periods, although some of the low flow months were overpredicted and most of the peak flow months were underpredicted. Compared to the calibration period, in the validation period the simulated discharge followed more closely the corresponding observed discharge, with less underprediction of peak flow months and less overprediction of low flow months. This can also be seen in the regression plots (Figures 4(a) and 4(b)), where the linear trend line computed for the validation period was closer to the 1 : 1 line than in the calibration period. The regression plots also show that underprediction primarily occurred for the high discharge values, whilst overprediction mostly occurred for low discharge values. Evaluation statistics computed for both time periods are presented in Table 4. All of them showed a very good performance rating relative to the guidelines recommended by Moriasi et al. [42], which were previously shown in Table 3. Again, the performance of SWAT for the validation period was better than for calibration period as all of the statistics computed for this period were stronger than those computed for the calibration period. A positive bias of 3.17 percent was found for the calibration period, whereas the validation period resulted in a negative bias of −1.44 percent. This indicates that there were a model underestimation bias for the calibration period and an overestimation bias for the validation period. However, the magnitude of these biases was insignificant.


Modelling climate change impacts on the seasonality of water resources in the Upper Ca River Watershed in Southeast Asia.

Giang PQ, Toshiki K, Sakata M, Kunikane S, Vinh TQ - ScientificWorldJournal (2014)

Monthly time series comparison of simulated versus observed river discharge at Yen Thuong Station with reference to monthly precipitation during the 15-year validation period (1996–2010).
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4150503&req=5

fig3: Monthly time series comparison of simulated versus observed river discharge at Yen Thuong Station with reference to monthly precipitation during the 15-year validation period (1996–2010).
Mentions: Figures 2 and 3 graphically illustrate the time series comparison of simulated and observed cumulative monthly river discharge with reference to monthly precipitation for the Ca River at Yen Thuong Station, over the 25-year calibration (1971 through 1995) and 15-year validation (1996 through 2010), respectively. Overall, the SWAT model accurately tracked the observed river discharge for both time periods, although some of the low flow months were overpredicted and most of the peak flow months were underpredicted. Compared to the calibration period, in the validation period the simulated discharge followed more closely the corresponding observed discharge, with less underprediction of peak flow months and less overprediction of low flow months. This can also be seen in the regression plots (Figures 4(a) and 4(b)), where the linear trend line computed for the validation period was closer to the 1 : 1 line than in the calibration period. The regression plots also show that underprediction primarily occurred for the high discharge values, whilst overprediction mostly occurred for low discharge values. Evaluation statistics computed for both time periods are presented in Table 4. All of them showed a very good performance rating relative to the guidelines recommended by Moriasi et al. [42], which were previously shown in Table 3. Again, the performance of SWAT for the validation period was better than for calibration period as all of the statistics computed for this period were stronger than those computed for the calibration period. A positive bias of 3.17 percent was found for the calibration period, whereas the validation period resulted in a negative bias of −1.44 percent. This indicates that there were a model underestimation bias for the calibration period and an overestimation bias for the validation period. However, the magnitude of these biases was insignificant.

Bottom Line: The results indicated that temperature and evapotranspiration will increase in all months of future years.The greatest monthly increase of up to 29% and the greatest monthly decrease of up to 30% are expected in the 2090 s.As a result, decreases in dry season discharge and increases in wet season discharge are expected, with a span of ± 25% for the highest monthly changes in the 2090 s.

View Article: PubMed Central - PubMed

Affiliation: Department of Environmental and Life Sciences, University of Shizuoka, 52-1 Yada, Suruga-ku, Shizuoka-shi, Shizuoka 422-8526, Japan ; Faculty of Land Management, Vietnam National University of Agriculture, Hanoi 131000, Vietnam.

ABSTRACT
The impact of climate change on the seasonality of water resources in the Upper Ca River Watershed in mainland Southeast Asia was assessed using downscaled global climate models coupled with the SWAT model. The results indicated that temperature and evapotranspiration will increase in all months of future years. The area could warm as much as 3.4(°)C in the 2090 s, with an increase of annual evapotranspiration of up to 23% in the same period. We found an increase in the seasonality of precipitation (both an increase in the wet season and a decrease in the dry season). The greatest monthly increase of up to 29% and the greatest monthly decrease of up to 30% are expected in the 2090 s. As a result, decreases in dry season discharge and increases in wet season discharge are expected, with a span of ± 25% for the highest monthly changes in the 2090 s. This is expected to exacerbate the problem of seasonally uneven distribution of water resources: a large volume of water in the wet season and a scarcity of water in the dry season, a pattern that indicates the possibility of more frequent floods in the wet season and droughts in the dry season.

Show MeSH
Related in: MedlinePlus