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Volume 22, issue 8 | Copyright

Special issue: The changing water cycle of the Indo-Gangetic Plain

Hydrol. Earth Syst. Sci., 22, 4213-4228, 2018
https://doi.org/10.5194/hess-22-4213-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 09 Aug 2018

Research article | 09 Aug 2018

Modeling the changes in water balance components of the highly irrigated western part of Bangladesh

A. T. M. Sakiur Rahman1, M. Shakil Ahmed2, Hasnat Mohammad Adnan3, Mohammad Kamruzzaman4, M. Abdul Khalek2, Quamrul Hasan Mazumder3, and Chowdhury Sarwar Jahan3 A. T. M. Sakiur Rahman et al.
  • 1Hydrology Lab, Department of Earth and Environmental Sciences, Graduate School of Science and Technology, Kumamoto University, 2-40-1 Kurokami, Kumamoto, Japan
  • 2Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh
  • 3Department of Geology and Mining, University of Rajshahi, Rajshahi 6205, Bangladesh
  • 4Institute of Bangladesh Studies, University of Rajshahi, Rajshahi 6205, Bangladesh

Abstract. The objectives of the present study were to explore the changes in the water balance components (WBCs) by co-utilizing the discrete wavelet transform (DWT) and different forms of the Mann–Kendall (MK) test and develop a wavelet denoise autoregressive integrated moving average (WD-ARIMA) model for forecasting the WBCs. The results revealed that most of the potential evapotranspiration (PET) trends (approximately 73%) had a decreasing tendency from 1981–1982 to 2012–2013 in the western part of Bangladesh. However, most of the trends (approximately 82%) were not statistically significant at a 5% significance level. The actual evapotranspiration (AET), annual deficit, and annual surplus also exhibited a similar tendency. The rainfall and temperature exhibited increasing trends. However, the WBCs exhibited an inverse trend, which suggested that the PET changes associated with temperature changes could not explain the change in the WBCs. Moreover, the 8-year (D3) and 16-year (D4) periodic components were generally responsible for the trends found in the original WBC data for the study area. The actual data was affected by noise, which resulted in the ARIMA model exhibiting an unsatisfactory performance. Therefore, wavelet denoising of the WBC time series was conducted to improve the performance of the ARIMA model. The quality of the denoising time series data was ensured using relevant statistical analysis. The performance of the WD-ARIMA model was assessed using the Nash–Sutcliffe efficiency (NSE) coefficient and coefficient of determination (R2). The WD-ARIMA model exhibited very good performance, which clearly demonstrated the advantages of denoising the time series data for forecasting the WBCs. The validation results of the model revealed that the forecasted values were very close to actual values, with an acceptable mean percentage error. The residuals also followed a normal distribution. The performance and validation results indicated that models can be used for the short-term forecasting of WBCs. Further studies on different combinations of wavelet analysis are required to develop a superior model for the hydrological forecasting in the context of climate change. The findings of this study can be used to improve water resource management in the highly irrigated western part of Bangladesh.

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