Hikmet Kerem Cigizoglu

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The methods available in the literature for sediment concentration estimation are complicated and time consuming and necessitate cumbersome parameter estimation procedures. In this study, artificial neural networks (ANNs) are used to forecast and estimate sediment concentration values. The forecasting results obtained using previously observed sediment(More)
The methods available for sediment concentration and flux estimation are largely empirical, with sediment rating curves being the most widely applied. In this study, a comparison is made between artificial neural networks (ANNs) and sediment rating curves for two rivers with very similar catchment areas and characteristics in the north of England. Data from(More)
Streamflow time series in arid and semi-arid regions can be characterized as a sequence of single discrete flow episodes or clusters of hydrographs separated by periods of zero discharge. Here, two point process models are presented for the joint occurrence of flow events at neighbouring river sites. The first allows for excess clustering by adding(More)
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