Floods – From Risk to Opportunity
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- Impact of urbanization on flood vulnerability in a shallow groundwater catchment AMILA P. BASNAYAKA 1 , R. SARUKKALIGE 1 I. WERELLAGAMA 2
- A decision support framework for flood risk assessment: an application to the Brahmaputra River in Bangladesh
- Rainfall–runoff modelling with data driven techniques: constraints and proper implementation lekhangani Arunoda basnayake 1 vladan babovic 1,2
- The stochastic discharge forecast – creation, interpretation and other applications lucie březková
- Analysis of the “needs” of the users for the newly introduced X-Band MP (multi-parameter) radar N. Fujiwara, T. Yagami, N. Hashido, S. Moriyama, K. Araki Y. Yonese
- Evaluation of flood discharge hydrographs and bed variations in a channel network on the Ota River delta, Japan T. GOTOH 1 , S. FUKUOKA 1 R. TANAKA 2
- Ensemble short-term rainfall–runoff prediction and its application in urban flood risk mapping RATIH INDRI Hapsari
- DIAN Sisinggih
- Probable maximum precipitation (PMP) in the Jajroud basin of Iran using a synoptic model MaHmoUd Ahmadi 1 , E. Fattahi 2 A. Noormohmmadi 3
- Study on spatial-tempor a l distribution of rainstorm in China from 1961 to 2010 F
- Sequential data assimilation for streamflow forecasting using a distributed hydrologic model: particle filtering and ensemble Kalman filtering Seong Jin Noh
Key words glacial lake outburst; numerical model; Tsho Rolpa glacial lake; potential flood; prediction -------------------------------------------------------------------------------------------------------------------------------------- Floods: From Risk to Opportunity (IAHS Publ. 357, 2013), 255-262 Impact of urbanization on flood vulnerability in a shallow groundwater catchment AMILA P. BASNAYAKA1, R. SARUKKALIGE1 & I. WERELLAGAMA2 1 Department of Civil Engineering, Curtin University, GPO Box U1987, Perth, Australia a.basnayak@postgrad.curtin.edu.au 2 Department of Civil Engineering, University of Peradeniya, Sri Lanka Abstract Rapid urbanization of modern cities has changed their urban hydrology leading to urban floods. Assessment of flood vulnerability in urban catchments is complicated with urban infrastructure. Urban hydrology of the Central Catchment, size 248 ha in a rapidly urbanizing city, Canning Vale in Western Australia was assessed using a numerical model. The study combines 2D overland flow elements and 1D drainage networks to represent urban catchment. The model was used to investigate the impact of the land use changes, presence of shallow groundwater, and urban infrastructure on urban hydrology. Results show that shallow groundwater plays a main role in urban flood process in Canning Vale. Results of the study were used to develop flood vulnerability maps while recommending the necessary improvements to the urban storm water system, and will assist local city council decision-makers in coming up with better land management concepts to minimize anthropogenic stress. Key words stormwater management; 2D modelling; urban hydrology; flood mapping; Western Australia -------------------------------------------------------------------------------------------------------------------------------------- Floods: From Risk to Opportunity (IAHS Publ. 357, 2013), 263-272 A decision support framework for flood risk assessment: an application to the Brahmaputra River in Bangladesh MUKAND S. BABEL1, S. H. M. FAKHRUDDIN2 & Akiyuki Kawasaki1 1 Water Engineering and Management (WEM), School of Engineering and Technology (SET), Asian Institute of Technology (AIT), Thailand msbabel@ait.asia 2 Regional Integrated Multi Hazard Early Warning Center (RIMES), AIT Campus, Thailand Abstract Early warning is a key element for disaster risk reduction. However, the advances in generating hazard risk information have not yet been incorporated into operational forecast systems and consequently, operational forecasts have not been integrated into decision making processes in order to reduce disaster risks. This article aims to design location-specific user-need based flood forecast products on different time scales for reducing flood risks. Using 1–10 days multiple weather ensemble (EPS) forecasts of the European Center for Medium Range Forecasts (ECMWF), integrating hydrological models, and combining these with GIS and local user needs, the decision support system (DSS) is designed to interpret, translate, and communicate science-based risk information into user-friendly early warning information products to assist emergency managers and decision makers. The DSS interface allows users to interactively specify the objectives and criteria that are relevant to a particular situation, and obtain the management options (strategies) that are possible, and the exogenous influences (scenarios) that should be taken into account before policy planning and decision making. The proposed framework is applied to a pilot area in the Brahmaputra River basin in Bangladesh for the agricultural sector. Key words ensembles probabilistic forecasts; flood risk; decision support system; community response -------------------------------------------------------------------------------------------------------------------------------------- Floods: From Risk to Opportunity (IAHS Publ. 357, 2013), 273-282 Rainfall–runoff modelling with data driven techniques: constraints and proper implementation lekhangani Arunoda basnayake1 & vladan babovic1,2 1 Department of Civil and Environmental Engineering, National University of Singapore, E1A-07-03, no.1 Engineering Drive 2, Singapore 117576 arunodab@yahoo.com 2 Singapore-Delft Water Alliance, EW1-02-05, no.2 Engineering Drive 2, Singapore 117577 Abstract Data driven models (DDMs) are widely recognized as being an important tool for decision support systems. Nonlinear time series techniques are widely applied in hydrological process analysis. DDMs are primarily based on observations and therefore they are sensitive to the strong autocorrelation of observed time series data. This constraint may worsen the forecasting accuracy. In this study, we address the effect of autoregressive components on nonlinear time series forecasting. The performance of Artificial Neural Networks (ANNs) and linear stochastic models in predicting runoff have been investigated for different time intervals. Adjacent differencing provides much better results with refined data and this is significant in extended forecasting horizons. We found that ANN performs slightly better than the linear models. This is because a single ANN model is not sufficient to predict all runoff generation instances. Key words rainfall–runoff modelling; artificial neural networks; linear stochastic models; forecasting accuracy; data time interval -------------------------------------------------------------------------------------------------------------------------------------- Floods: From Risk to Opportunity (IAHS Publ. 357, 2013), 283-291 The stochastic discharge forecast – creation, interpretation and other applications lucie březková1,2 & miloš starý1 1 Brno University of Technology, Faculty of Civil Engineering, Veveří 95, 60200 Brno, Czech Republic lucie.brezkova@chmi.cz 2 Czech Hydrometeorological Institute – regional office Brno, Kroftova 43, 61667 Brno, Czech Republic Abstract The deterministic discharge forecast calculated by hydrological models is now a common product of the Flood Forecasting Service in the Czech Republic. However, the deterministic forecast does not describe the determination which must be considered not only during the creation of the flow forecast, but mainly within the interpretation of the final predicted hydrograph. The deterministic forecast is a great simplification of the real conditions in the catchment taking into account only one possible (although the most probable) scenario of the future development of the meteorological and hydrological situation. The stochastic flow forecast based on simulation of many probable meteorological scenarios (all members of the meteorological ensemble) aims to describe the spread of the possible flow developments during the predicted period. The paper describes the generator of the random fields of meteorological quantities – the inputs of the hydrological model. The sets of precipitation, temperature and snow fields cover the estimated uncertainty of the measured and predicted quantities. The coinciding set of discharge forecasts is then evaluated. The case studies of floods which hit the Dyje catchment in 2002 and 2006 show the application of the proposed method. Whereas the stochastic flow forecast is not very common in operation, attention is also paid to the correct interpretation of the stochastic flow forecast and to other uses of this product. The method has been tested in operation in the Dyje catchment since 2009, within the Flood Forecasting Service ensured by the Czech Hydro-meteorological Institute. Key words flood; operative discharge forecast; stochastic forecast; Monte Carlo -------------------------------------------------------------------------------------------------------------------------------------- Floods: From Risk to Opportunity (IAHS Publ. 357, 2013), 292-299 Analysis of the “needs” of the users for the newly introduced X-Band MP (multi-parameter) radar N. Fujiwara, T. Yagami, N. Hashido, S. Moriyama, K. Araki & Y. Yonese CTI Engineering Co., Ltd., 3-21-1 Nihombashi Hamacho Chuo-ku, Tokyo 103-8430, Japan fujiwara@ctie.co.jp Abstract It is envisaged that the newly introduced X-Band MP (multi parameter) radar will provide higher precision rainfall information compared to the conventional radar, contributing to river and disaster management in Japan. The objective of this research is to analyse the “needs” of the users for the MP radar from the perspectives of river managers, municipalities, general public, etc. It aims to propose the operational procedures to realize the functionalities demanded by the users, and to make recommendations for developing disaster management support systems. The research involved two main elements. The first one conducting interviews with a wide variety of users to analyse their needs for radar rainfall and disaster information; and the second one developing a prototype system for flood/inundation forecasting and flood disaster evacuation support systems which disseminate information to mobile phones. The questionnaire surveys and interviews were conducted targeting the users of flood information in order to determine the types of information needed during flood events. Potential users of flood information include such entities as organizations related to disaster-prevention, administrators of rivers, sewerage or roads, managers of underground facilities, river users, recreational users and the nearby residents. The survey revealed the needs of and the information required by river, sewerage and disaster prevention managers, and also the key issues regarding flood information that are considered important to resolve. In addition, the prototype system which provides flood/inundation forecasting and flood disaster evacuation support information using X-band MP radar was designed and developed. The system provides information such as current and estimated rainfall, water level and inundation depth at any given locations and ranges, and can be accessed through mobile phones. Pilot testing of the system is being conducted this year in order to verify the effectiveness of the system and to refine its specifications. Key words X-Band MP (multi- parameter) radar; disaster evacuation support systems -------------------------------------------------------------------------------------------------------------------------------------- Floods: From Risk to Opportunity (IAHS Publ. 357, 2013), 300-307 Evaluation of flood discharge hydrographs and bed variations in a channel network on the Ota River delta, Japan T. GOTOH1, S. FUKUOKA1 & R. TANAKA2 1 Research and Development Initiative, Chuo University, 1-13-27 Kasuga, Bunkyo-ku, Tokyo, 112-8551, Japan goto510@tamacc.chuo-u.ac.jp 2 Chugoku Regional Development Bureau, MLIT, 3-20 Hattyoubori, Naka-ku, Hiroshima-City, 730-0013, Japan Abstract A channel network consisting of the Ota River floodway and five branched rivers is formed on the Ota River delta. To estimate bed variation and flood discharge distributions in the channel network of the Ota River delta is important for proper river management. The objective of this study is to develop the calculation method of flood flows and bed variations by using time series of water surface profiles measured in the channel network of the Ota River delta. We developed a quasi-3D numerical model for the flood flow and bed variation analyses using time series of observed water surface profiles. The unsteady quasi-3D analysis of flood flows and 2D analysis of bed variations using time series of observed water surface profiles are found to provide good explanations for the flood discharge distributions and bed variations of the channel network on the Ota River delta. Key words channel network; Ota River delta, Japan; time series of observed water surface profiles; flood discharge distributions; bed variation -------------------------------------------------------------------------------------------------------------------------------------- Floods: From Risk to Opportunity (IAHS Publ. 357, 2013), 308-319 Ensemble short-term rainfall–runoff prediction and its application in urban flood risk mapping RATIH INDRI Hapsari1, SATORU Oishi2, KENGO Sunada3, TETSUYA Sano3 & DIAN Sisinggih4 1 Interdisciplinary Graduate School of Medicine and Engineering, University of Yamanashi, 4-3-11 Takeda, Kofu 400-8510, Japan ratihindri@gmail.com 2 Research Centre for Urban Safety and Security, Kobe University, 1-1 Rokko-dai, Nada-ku, Kobe 657-8501, Japan 3 International Research Centre for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu 400-8510, Japan 4 Department of Water Resources Engineering, Faculty of Engineering, University of Brawijaya, Jl. MT. Haryono 167, Malang 65145, Indonesia Abstract This paper describes the ensemble approach to account for the uncertainty in both rainfall and hydrological short-term prediction. The range of probabilistic products generated by ensemble prediction and their potential for obtaining flood risk estimates is demonstrated. An ensemble rainfall prediction is developed by perturbing the initial condition of the radar echo extrapolation model. The ensemble members are subsequently considered as uncertain input of the distributed hydrological model. Uncertainty in rainfall–runoff model parameters is assessed by the generalized likelihood uncertainty estimation (GLUE) method. The methodology is demonstrated through case studies in the Kofu urban river basin, Japan. The results reveal that plausible results can be achieved, thus indicating that this approach could serve as a reliable method for estimating the uncertainty range in short-term prediction of runoff dynamics. When utilized along with the flood damage model, we highlight the value of ensemble prediction for deriving flood risk information through risk mapping. Key words ensemble prediction; flash flood; GLUE; parameter uncertainty; probabilistic prediction; risk -------------------------------------------------------------------------------------------------------------------------------------- Floods: From Risk to Opportunity (IAHS Publ. 357, 2013), 320-327 Probable maximum precipitation (PMP) in the Jajroud basin of Iran using a synoptic model MaHmoUd Ahmadi1, E. Fattahi2 & A. Noormohmmadi3 1 Physical Geography Department, Shahid Beheshti University, Tehran, Iran 44ahmadi@gmail.com 2 Meteorological Research Center, Tehran, Iran 3 MS student of Climatology, Islamic Azad University, Tehran, Iran Abstract The probable maximum precipitation (PMP) is the maximum amount of precipitation that may occur in a basin. The Jajroud Basin north of Tehran is important for the agricultural activities of the area and the urban planning of Tehran city. Therefore, the main objective of this research is to determine the PMP in this basin using a synoptic model. In this model, most of the attention is paid to the moisture and thermal characteristics of rainstorms in the region. In order to achieve the objective of the study, eight intensive and widespread storms that lasted one to four days were selected. The results showed that the intensive rainstorms of the basin are intensified by the merging of Mediterranean cyclones with Sudan lows. Through the largest rainstorms, the PMP of the basin was computed as 102 mm. The results from the study are the main input for the calculation of the probable maximum flooding (PMF) of the basin. Key words Jajroud basin, Iran; Mediterranean cyclones; PMP; rainstorm; synoptic model -------------------------------------------------------------------------------------------------------------------------------------- Floods: From Risk to Opportunity (IAHS Publ. 357, 2013), 328-340 Study on spatial-temporal distribution of rainstorm in China from 1961 to 2010 FEI Mao1, DAPENG Huang1, RENHE Zhang1, ZHIGUO Huo1, E. YOUHAO1 & HUIFEI Jiang2 1 Chinese Academy of Meteorological Sciences, Beijing 100081, China dapenghuang@163.com 2 China Agricultural University, Beijing 100094, China Abstract Using daily precipitation data of 601 stations from 1961 to 2010 in China, the spatial and temporal distribution of rainstorm (daily precipitation 50 mm), heavy rainstorm (daily precipitation 100 mm) and extremely heavy rainstorm (daily precipitation 200 mm) were analysed based on mathematical statistics. The main results show that the days of rainstorm, heavy rainstorm and extremely heavy rainstorm all decreased gradually from southeast to northwest China, and the maximum records of them reached 737 days, 259 days, 50 days, respectively, during the last 50 years. There were almost no rainstorms in the western regions of China. The annual days of rainstorm, heavy rainstorm and extremely heavy rainstorm increased mainly in the Lower Yangtze-Huaihe areas, the south of the Lower Yangtze River, Guangdong Province, Guangxi Zhuang Nationality Autonomous Region, Hainan Island, etc. In these areas, the risk of meteorological and geological disasters such as flood inundation, mud-rock flow, landslide, etc. were increased. The annual curves of the rainstorm days with unimodal distribution were found in most regions of China, and with double-peaks in the Tibetan Plateau and Xisha Islands in the South China Sea. The maximum rainstorms occur in July in most regions of China, in June in Jiangnan (Shanghai City, Zhejiang Province, Fujian Province, Jiangxi Province and Hunan Province) and South China (Guangdong Province and Guangxi), in August in the Tibetan Plateau and Xisha Islands, and in October in Hainan Island. Some research results in this paper provide important information of climate background for analysing and evaluating disasters of flood inundation, mud-rock flow, landslides, etc. Key words China; rainstorm; spatial and temporal distribution -------------------------------------------------------------------------------------------------------------------------------------- Floods: From Risk to Opportunity (IAHS Publ. 357, 2013), 341-349 Sequential data assimilation for streamflow forecasting using a distributed hydrologic model: particle filtering and ensemble Kalman filtering Seong Jin Noh1, 2, YASUTO Tachikawa3, Michiharu SHIIBa3 & Sunmin KIM3 1 Dept. of Urban and Env. Eng., Kyoto University, Kyoto 615-8540, Japan seongjin.noh@gmail.com 2 Water Resources & Environment Research Department, Korea Institute of Construction Technology, 2311 Daewha-Dong, Ilsan-Gu, Goyang-Si, Gyeonggi-Do 411-712, Korea 3 Dept. of Civil and Earth Resources Engineering, Kyoto University, Kyoto 615-8540, Japan Abstract Accurate streamflow predictions are crucial for mitigating flood damage and addressing operational flood scenarios. In recent years, sequential data assimilation methods have drawn attention due to their potential to handle explicitly the various sources of uncertainty in hydrologic models. In this study, we implement two ensemble-based sequential data assimilation methods for streamflow forecasting via the particle filters and the ensemble Kalman filter (EnKF). Among variations of filters, the ensemble square root filter (EnSRF) and the lagged regularized particle filter (LRPF) are implemented for a distributed hydrologic model. Two methods are applied for short-term flood forecasting in a small-sized catchment located in Japan (<1000 km2). Soil moisture contents are perturbed by process noises and model ensembles are updated by streamflow observation at the outlet. In the case of the LRPF, state updating is performed through a lag-time window to take into account the different response times of hydrologic processes. For different flood events and various forecast lead times, LRPF forecasts outperform EnSRF forecasts and deterministic cases. The EnSRF shows limited performance in both forecasting accuracy and probabilistic intervals, which require introduction of a lag-time window in the filtering processes. Key words sequential data assimilation; flood forecasting; particle filter; ensemble Kalman filter; distributed hydrologic model -------------------------------------------------------------------------------------------------------------------------------------- Floods: From Risk to Opportunity (IAHS Publ. 357, 2013), 350-356 Download 369.75 Kb. Share with your friends:
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