Optimizing Network Architecture of Artificial Neural Networks (ANNs) in Rainfall-Runoff Modeling

Khalid, Khairi; Ali, Megat Syahirul Amin Megat; Rahman, Nor Faiza Abd; Husaini, Mohammed Abdulla Salim Al; Mispan, Muhamad Radzali

doi:10.1007/978-981-10-0155-0_11

Cited by 1 publication

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References 18 publications

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“…This implies that a reduction of rainfall usually leads to a greater degree of reduction in runoff, which can be explained by the nonlinear relationship between rainfall and runoff. The nonlinear relationship has been found in many previous works [45,46]. The study of the impact of climate change and human activities on runoff is based on the assumption that the two factors are independent.…”

Section: Analysis Of Runoff Variation Without the Effect Of Human Actmentioning

confidence: 91%

Understanding the Main Causes of Runoff Change by Hydrological Modeling: A Case Study in Luanhe River Basin, North China

Zhang

Wang

Wang³

et al. 2018

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In the traditional point of view, if there is a significant decreasing trend for a runoff time series, while no significant trend for a precipitation series is present, then an unreliable conclusion will be made that the land surface change is the main contributor to the runoff change. To test it, we selected four sub-watersheds in the Luanhe river basin as the study areas where land use has changed severely. We first detected the long-term rainfall and runoff trend by the Mann–Kendall test, Sen’s slope, and the moving average method, and found that the runoff had a decreasing trend at the 0.05 significance level, while the rainfall had no significant trend in all sub-watersheds. Then an orderly cluster analysis and moving T test method were used to detect the change point of the runoff series. We quantified the contributions of the land surface change and climate variability based on Soil and Water Assessment Tool (SWAT), and the contribution of climate variability accounted for more than 50%, which implies that climate change is the main factor of runoff decrease in the study areas. To further test this, a trend analysis of a reconstructed annual runoff time series under undisturbed conditions has been done. The results showed that in some sub-watersheds, although rainfall series had no significant decreasing trend, the runoff series had significant downward trend. This can be explained by the nonlinear relationship between rainfall and runoff. This study came to a different conclusion from the common view, which observes that runoff decrease is mainly caused by land surface change if rainfall series lacks a significantly decreasing trend.

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Section: Analysis Of Runoff Variation Without the Effect Of Human Actmentioning

confidence: 91%

Understanding the Main Causes of Runoff Change by Hydrological Modeling: A Case Study in Luanhe River Basin, North China

Zhang

Wang

Wang³

et al. 2018

Water

View full text Add to dashboard Cite

show abstract

Optimizing Network Architecture of Artificial Neural Networks (ANNs) in Rainfall-Runoff Modeling

Cited by 1 publication

References 18 publications

Understanding the Main Causes of Runoff Change by Hydrological Modeling: A Case Study in Luanhe River Basin, North China

Understanding the Main Causes of Runoff Change by Hydrological Modeling: A Case Study in Luanhe River Basin, North China

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