| Autor: |
Anurag Malik, Anil Kumar, Ali Najah Ahmed, Chow Ming Fai, Haitham Abdulmohsin Afan, Ahmed Sefelnasr, Mohsen Sherif, Ahmed El-Shafie |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
Alexandria Engineering Journal, Vol 59, Iss 3, Pp 1595-1606 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
1110-0168 |
| DOI: |
10.1016/j.aej.2020.04.006 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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