TY - JOUR
T1 - Application of non-parametric approaches to identify trend in streamflow during 1976–2007 (Naula watershed)
AU - Malik, Anurag
AU - Kumar, Anil
AU - Najah Ahmed, Ali
AU - Ming Fai, Chow
AU - Abdulmohsin Afan, Haitham
AU - Sefelnasr, Ahmed
AU - Sherif, Mohsen
AU - El-Shafie, Ahmed
N1 - Funding Information:
This research financially supported from Bold 2025 grant coded RJO:10436494 by the Innovation & Research Management Center (iRMC), Universiti Tenaga Nasional (UNITEN), Malaysia, and research grant coded GPF082A-2018 funded by the University of Malaya and by Ministry of Higher Education Malaysia from Fundamental Research Grant Scheme (FRGS, Grant No: FRGS/1/2019/TK01/UNITEN/02/3).
Publisher Copyright:
© 2020 Faculty of Engineering, Alexandria University
PY - 2020/6
Y1 - 2020/6
N2 - The identification of trends in hydrological data is crucial for sustainable planning and management of water resources under the climate-change scenario. This research, identify the long-term temporal trend and magnitude (m3/s/time scale) in monthly, seasonal, and annual streamflow by employing three non-parametric approaches conventional Mann-Kendall (MK), Innovative-Şen trend (IŞT), and Sen-slope (SS) on 5% level of significance. The monthly streamflow data of 32-years (1976–2007) were recorded at Naula and Kedar stations positioned in the upper Ramganga River catchment (RRC), Uttarakhand State (India). Results of scrutiny reveal a significant negative trend in 17 time-series was detected by conventional MK test, and significant positive/negative trend in 1/30 time-series was inspected by the IŞT method with changing magnitude over monthly, seasonal, and annual scales at both stations, respectively. Furthermore, a comparison among results of the MK and IŞT showed that the IŞT method examined the unseen trend that cannot be detected by the MK technique at the Naula watershed. The pattern of trend detected on annual, seasonal, and monthly time-scales by three non-parametric approaches can help the water resources management authorities and hydrologists to comprehend the hazard and vulnerability under climate-change scenario over the study catchment area.
AB - The identification of trends in hydrological data is crucial for sustainable planning and management of water resources under the climate-change scenario. This research, identify the long-term temporal trend and magnitude (m3/s/time scale) in monthly, seasonal, and annual streamflow by employing three non-parametric approaches conventional Mann-Kendall (MK), Innovative-Şen trend (IŞT), and Sen-slope (SS) on 5% level of significance. The monthly streamflow data of 32-years (1976–2007) were recorded at Naula and Kedar stations positioned in the upper Ramganga River catchment (RRC), Uttarakhand State (India). Results of scrutiny reveal a significant negative trend in 17 time-series was detected by conventional MK test, and significant positive/negative trend in 1/30 time-series was inspected by the IŞT method with changing magnitude over monthly, seasonal, and annual scales at both stations, respectively. Furthermore, a comparison among results of the MK and IŞT showed that the IŞT method examined the unseen trend that cannot be detected by the MK technique at the Naula watershed. The pattern of trend detected on annual, seasonal, and monthly time-scales by three non-parametric approaches can help the water resources management authorities and hydrologists to comprehend the hazard and vulnerability under climate-change scenario over the study catchment area.
KW - Innovative-Şen trend method
KW - Mann-Kendall test
KW - Naula watershed
KW - Sen-slope method
KW - Temporal trend
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U2 - 10.1016/j.aej.2020.04.006
DO - 10.1016/j.aej.2020.04.006
M3 - Article
AN - SCOPUS:85085940183
SN - 1110-0168
VL - 59
SP - 1595
EP - 1606
JO - Alexandria Engineering Journal
JF - Alexandria Engineering Journal
IS - 3
ER -