Low flow forecasts for the Rhine at Lobith 14 days ahead A correlation analysis and an artificial neural network study

Bouwma, Pieter (2011) Low flow forecasts for the Rhine at Lobith 14 days ahead A correlation analysis and an artificial neural network study.

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Abstract:The River Rhine has periods of low flows during the year. Low flows may cause difficulties for water demand. Insight in low flows could help to understand the discharge behavior and reduce damage. The main objective of this study is to forecast the discharge at Lobith 14 days ahead during low flow conditions using an Artificial Neural Network (ANN) model. In this study a correlation analysis is carried out, and ANN models are developed and applied to simulate the sub-basin discharges and the Rhine discharge at Lobith. The Rhine basin upstream of Lobith is divers and therefore, it is sub-divided into seven subbasins. The sub-basins are East Alpine, West Alpine, Middle Rhine, Neckar, Main, Mosel and Lower Rhine. For all sub-basins an overlapping period of 16 years of daily data series is available. These data series include information about the discharge, precipitation, evapotranspiration, groundwater storage, snow depths and lake levels. The correlation analysis is performed to determine the linear relation between the discharge at the outlet of each sub-basin during low flows and a single low flow indicator. The outcomes of the correlation analysis and forecasted rainfall have been used to define the input for the ANN per sub-basin to simulate low flows. Finally, low flows at Lobith are simulated using an ANN model and the simulated discharges of five sub-basins. The results of the correlation analysis show good correlations for the Alpine sub-basins (East Alpine: 0.98 and West Alpine: 0.81), but relatively low correlations for the rainfed sub-basins (Neckar: 0.67, Main: 0.57 and Mosel: 0.68). The correlations for the Middle and Lower Rhine are unreliable, because of poor discharge data. The simulated low flows per sub-basin resulted in good Nash-Sutcliffe Efficiencies (NSE) for the Alpine sub-basins and the Mosel for the test phase (East Alpine: 0.96, West Alpine: 0.83 and Mosel: 0.77). The Neckar and the Main have a NSE of just 0.48 and 0.23. The independent test phase of the ANN for Lobith shows a low performance, namely a NSE of 0.32. The results for the training and the validation period are much better with a NSE for Lobith of 0.75 and 0.73 respectively. The results should be interpreted taking into account that perfect weather forecasts for rainfall have been used to train the ANNs. And discharges of the sub-basins Middle Rhine and Lower Rhine have been neglected. Discrepancy of rainfall in the Middle Rhine and Lower Rhine subbasins in perspective to the other rainfed sub-basins will cause a rise of the actual discharge at Lobith. However this will not be seen in the simulation at Lobith, because of these basins will be left out of the input. The performance at Lobith is poor. However the correlations and simulated discharges for the Alpine basins are very good and during low flows 70 percent of the flow at Lobith originates from the Alps. This indicates the potential of using ANN models for forecasting low flows with a lead time of 14 days. Future work should focus on improving and refining the input data and ANN modeling in order to improve the low flow forecasts at Lobith.
Item Type:Essay (Bachelor)
Faculty:ET: Engineering Technology
Subject:56 civil engineering
Programme:Civil Engineering BSc (56952)
Link to this item:http://purl.utwente.nl/essays/61075
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