This paper presents the developments towards the next generation of overland flow modelling of urban pluvial flooding. Using a detailed analysis of the Digital Elevation Model (DEM) the developed GIS tools can automatically generate surface drainage networks which consist of temporary ponds (floodable areas) and flow paths and link them with the underground network through inlets. For different commercially-available Rainfall-Runoff simulation models, the tool will generate the overland flow network needed to model the surface runoff and pluvial flooding accurately. In this paper the emphasis is placed on a sensitivity analysis of ponds and preferential overland flow paths creation. Different DEMs for three areas were considered in order to compare the results obtained. The DEMs considered were generated using different acquisition techniques and hence represent terrain with varying levels of resolution and accuracy. The results show that DEMs can be used to generate surface flow networks reliably. As expected, the quality of the surface network generated is highly dependent on the quality and resolution of the DEMs and successful representation of buildings and streets.
In order to simulate surface runoff and flooding, one-dimensional (1D) overland flow networks can be automatically delineated using digital elevation models (DEM). The resulting network comprises flow paths and terrain depressions/ponds and is essential to reliably model pluvial (surface) flooding events in urban areas by so-called ID/ID models. Conventional automatic DEM-based flow path delineation methods have problems in producing realistic overland flow paths when detailed highresolution DEMs of urban areas are used. The aim of this paper is to present the results of research and development of three enhanced DEM-based overland flow path delineation methods; these methods are triggered when the conventional flow path delineation process stops due to a flow obstacle. Two of the methods, the 'bouncing ball and buildings' and 'bouncing ball and A*' methods, are based on the conventional 'bouncing ball' concept; the third proposed method, the 'sliding ball' method, is based on the physical water accumulation concept. These enhanced methods were tested and their results were compared with results obtained using two conventional flow path delineation methods using a semi-synthetic test DEM. The results showed significant improvements in terms of the reliability of the delineated overland flow paths when using these enhanced methods.
Water level data obtained from telemetry stations typically contains large number of outliers. Anomaly detection and a data imputation are necessary steps in a data monitoring system. Anomaly data can be detected if its values lie outside of a normal pattern distribution. We developed a median-based statistical outlier detection approach using a sliding window technique. In order to fill anomalies, various interpolation techniques were considered. Our proposed framework exhibited promising results after evaluating with F1-score and root mean square error (RMSE) based on our artificially induced data points. The present system can also be easily applied to various patterns of hydrological time series with diverse choices of internal methods and fine-tuned parameters. Specifically, the Spline interpolation method yielded a superior performance on non-cyclical data while the long short-term memory (LSTM) outperformed other interpolation methods on a distinct tidal data pattern.
SummaryIt is predicted that energy requirements in developing countries will increase global water consumption as a result of implementation of new power generation systems, and to population growth of the middle classes. Thus, it is anticipated that increased regional energy consumption will likely increase global water scarcity as a result of the consequent international energy trade. The degree of impact, however, depends on the degree of water scarcity in the energy-export regions. Therefore, the impact on global water scarcity by the international energy trade of Thailand was evaluated, using virtual water flow, and considering water scarcity. First, the amount of natural gas, crude oil, coal, and electricity imported and exported by each country was determined from energy and trading statistics. Concurrently, a database of water withdrawn per unit of energy production was built using commodity and water scarcity indices by country. Next, standard, scarcity-weighted, and region-based scarcity-weighted virtual water flows were calculated using a bottom-up approach. From this, the net virtual water import (NVWI) was determined to be 1,267 to 7,353 million cubic meters (m 3 ), whereas the stress-weighted and region-based stressweighted NVWIs were determined to be from −2 to 1,820, and −4 to 3,696 million m 3 , respectively, over the past 20 years. It was found that, although the amount of virtual water import for the power generation was significant, imported crude oil was the greatest contributor to global water scarcity. Finally, the implications of these results for policy to prevent global water scarcity are considered, with discussion of the usability and uncertainty, of the water scarcity index. Keywords:bottom-up approach industrial ecology scarcity-weighted virtual water flow water-energy nexus water scarcity index Supporting information is available on the JIE Web site
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