Abstract. The increasing number and severity of floods, driven by phenomena such as urbanization, deforestation, subsidence and climate change, create a growing need for accurate and timely flood maps. In this paper we present and evaluate a method to create deterministic and probabilistic flood maps from Twitter messages that mention locations of flooding. A deterministic flood map created for the December 2015 flood in the city of York (UK) showed good performance (F (2) = 0.69; a statistic ranging from 0 to 1, with 1 expressing a perfect fit with validation data). The probabilistic flood maps we created showed that, in the York case study, the uncertainty in flood extent was mainly induced by errors in the precise locations of flood observations as derived from Twitter data. Errors in the terrain elevation data or in the parameters of the applied algorithm contributed less to flood extent uncertainty. Although these maps tended to overestimate the actual probability of flooding, they gave a reasonable representation of flood extent uncertainty in the area. This study illustrates that inherently uncertain data from social media can be used to derive information about flooding.
Abstract. The increasing number and severity of floods, driven by phenomena such as urbanization, deforestation, subsidence and climate change, creates a growing need for accurate and timely flood maps. This research focussed on creating flood maps using user generated content from Twitter. Twitter data has added value over traditional methods such as remote sensing and hydraulic models, since the data is available almost instantly, in contrast to remote sensing and requires less detail than hydraulic models. Deterministic flood maps created using these data showed good performance (F(2) = 0.69) for a case study in York (UK). For York the main source of uncertainty in the probabilistic flood maps was found to be the error of the locations derived from the Twitter data. Errors in the elevation data and parameters of the applied algorithm contributed less to flood extent uncertainty. Although the generated probabilistic maps tended to overestimate the actual probability of flooding, they gave a reasonable representation of flood extent uncertainty in the area. This study illustrates that inherently uncertain data from social media can be used to derive information about flooding.
Everywhere in the world where canal systems have been constructed, often the main purpose was transportation. But for most canal systems it was inevitable that they also started to play a role in the hydrology of the regions the canals crossed. In normal situations the canals have a drainage function, but in dry periods the systems can provide fresh water. An important goal for the operators is to maintain water levels on setpoint for navigation purposes. Their target is to minimize operating costs, while giving operation for navigation the highest priority. Thereby they have to take into account that the control structures have a limited operating range. A short-term optimization approach for the operational management of the canal system can increase efficiency of the water management, thereby decreasing operation costs. For the Twente Canal system, located in the eastern part of The Netherlands, such an short-term optimization approach was implemented in the operational system. This advisory module calculates the optimal operation of the available structures, given expected fluxes and system boundaries. The approach is based on Model Predictive Control and integrates observations from a gauge network and forecasted fluxes to calculate the best use of pumps and gates. The approach anticipates future lateral inflow and lock operation. The future lateral inflow in the canal sections is calculated by a rainfall-runoff model, which uses observed and forecast precipitation and evaporation. Future lock operation is estimated based on the expertise of the operators. Both have a large impact on the water balance and contain related uncertainties. The short-term optimization is implemented in the Operational Monitoring System for regulated water systems under authority of the National Water Authority (Rijkswaterstaat). This monitoring system advises operating staff on the operation of the related hydraulic structures.A. van Loenen ( ) • M. Xu Deltares,
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