Declining trends of water requirements of dry season Boro rice in the north-west Bangladesh

Acharjee, Tapos Kumar; Halsema, Gerardo van; Ludwig, Fulco; Hellegers, Petra

doi:10.1016/j.agwat.2016.11.014

Cited by 50 publications

(37 citation statements)

References 27 publications

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“…Our results showed that a combination of GSL and R n decline would counteract the warming-driven ET o and ET increments during the 2030s; but it would not withhold these ET o and ET increments during the 2060s, ultimately resulting in higher NIWR during this duration. Similar conclusions were drawn by the recent studies from various parts of the world, in which the observed declines in ET and NIWR of various crops, despite a clear climate warming, were attributed either to GSL shortening and/or R n declines [1,3,25,57].…”

Section: Future Climate Change Impacts On Wheat Y and Wfssupporting

confidence: 88%

Future Wheat Yield Variabilities and Water Footprints Based on the Yield Sensitivity to Past Climate Conditions

et al. 2019

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This article analyzed the wheat yield variabilities and water footprints under projected future climate based on wheat yield sensitivity to past (1980–2017) trends of maximum temperature (Tmax), minimum temperature (Tmin), solar radiation (Rn) and rainfall (P) for the semi-arid condition of Punjab, Pakistan. The past and projected future trends of the climate variables were identical featuring prominent Tmin rise than Tmax accompanied by Rn and P declines. Based on the past influences and the projected future trends of the climate variables, Tmin was the principal driver of wheat yield decline followed by the Tmax, P and Rn. Wheat evapotranspiration and net irrigation water requirement declined due to the influence of both decrease of growing season length and Rn for the first half of 21st-century, and this trend reversed during the second half of 21st-century. These phenomena were caused by different degree of climate warming between the two-time slices. Due to future wheat yield decline and a gradual rise in green water scarcity the blue and grey water footprints rise consistently particularly during 2nd-time slices. CO2 enrichment showed limited mitigation potential of nullifying the warming-induced threats on future wheat yield and water footprints.

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Section: Future Climate Change Impacts On Wheat Y and Wfssupporting

confidence: 88%

Future Wheat Yield Variabilities and Water Footprints Based on the Yield Sensitivity to Past Climate Conditions

et al. 2019

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“…However, positive trends in the rainfall and temperature dominated the western part of Bangladesh (Shahid and Khairulmaini, 2009;Kamruzzaman et al, 2016a). Moreover, a recent study found a negative trend in the evapotranspiration for four stations located in northwest Bangladesh (Acharjee et al, 2017). Although the annual rainfall and temperature of the Satkhira station exhibited positive trends (Kamruzzaman et al, 2016a), its P ET exhibited a significant decreasing trend.…”

Section: Discussionmentioning

confidence: 99%

“…As a result, detecting the periodicity through the wavelet transformation of hydrometeorological time series data has gained popularity in recent years (Partal and Küçük, 2006;Partal, 2009;Nalley et al, 2013;Araghi et al, 2015;Pathak et al, 2016). Studies have been conducted on the spatiotemporal characteristics of hydrometeorological variables, such as rainfall (Shahid and Khairulmaini, 2009;Ahasan et al, 2010;Kamruzzaman et al, 2016a;Rahman and Lateh, 2016;Syed and Al Amin, 2016), temperature (Shahid, 2010;Nasher and Uddin, 2013;Syed and Al Amin, 2016;Kamruzzaman et al, 2016a), and P ET Acharjee, 2017), in Bangladesh. Karim et al (2012) studied the WBCs, such as the P ET , A ET , deficit of water, and surplus of water, of 12 districts in Bangladesh.…”

Section: Introductionmentioning

confidence: 99%

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

Rahman

Ahmed

Adnan

et al. 2018

Hydrol. Earth Syst. Sci.

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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 (P ET ) 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 (A ET ), 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 P ET 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 (R 2 ). 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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“…As a result, detecting the periodicity through the wavelet transformation of hydrometeorological time series data has gained popularity in recent years (Partal and Küçük, 2006;Partal, 2009;Nalley et al, 2013;Araghi et al, 2015;Pathak et al, 2016). Studies have been conducted on the spatiotemporal characteristics of hydrometeorological variables, such as rainfall (Shahid and Khairulmaini, 2009;Ahasan et al, 2010;Kamruzzaman et al, 2016a;Rahman and Lateh, 2016;Syed and Al Amin, 2016), temperature (Shahid, 2010;Nasher and Uddin, 2013;Rahman, 2016;Syed and Al Amin, 2016;Kamruzzaman et al, 2016a), and P ET (Hasan et al, 2014;Acharjee, 2017), in Bangladesh. Karim et al (2012) studied the WBCs, such as the P ET , A ET , deficit of water, and surplus of water, of 12 districts in Bangladesh.…”

Section: Introductionmentioning

confidence: 99%

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Anonymous

2018

Preprint

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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 (P ET) 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 (A ET), 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 P ET changes associated with temperature changes could not explain the change in the WBCs. Moreover, the 8-year (D3) and 16year (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 (R 2). 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.

show abstract

Declining trends of water requirements of dry season Boro rice in the north-west Bangladesh

Cited by 50 publications

References 27 publications

Future Wheat Yield Variabilities and Water Footprints Based on the Yield Sensitivity to Past Climate Conditions

Future Wheat Yield Variabilities and Water Footprints Based on the Yield Sensitivity to Past Climate Conditions

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

Reply to interactive comments of Referee #1

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