Heavy rain has been forecast across Yorkshire - as York is bracing for flooding due to high river levels and a major incident has been declared in South Yorkshire . This indicates that the performance of HiPIMS reproducing water levels for the secondary rivers or tributaries is less satisfactory. River Eden has four main tributaries, the Caldew, Petteril, Eamont, and Irthing. Also importantly, the produced flood forecasts provide an unprecedented level of spatial and temporal details of the flood process over the entire catchment. Includes location map. The CC and the RMSE of the hybrid model and empirical model in the calibration period are summarized and shown in Table 6. in Modeling Earth Systems (JAMES), Journal of Geophysical Research The RF algorithm is implemented by Matlab. In order to substantially improve the computational efficiency for large‐scale simulations and real‐time forecasting, HiPIMS is implemented and runs on multiple GPUs. CSI returns the ratio between the “hits” cells (i.e., cells being correctly forecasted to be flooded) and the total number of flooded cells, either predicted or observed. … Metrics have been developed and used to quantify the performance of inundation models in predicting flood extents (Bates & De Roo, 2000; Horritt, 2006; Khan et al., 2011; Schubert & Sanders, 2012). The developed system provides end users web in formation (1896-1977), Chinese Journal of Geophysics (2000-2018), International Clearly, the UKV forecasted rainfall is spatially more divergent than the NIMROD radar rainfall. Please check your email for instructions on resetting your password. However, simulation of floodplain inundation using 2‐D models is computationally expensive, and direct prediction of detailed floodplain hydrodynamics in real time is still not a common practice in an operational flood forecasting system. Driven by the NWP outputs from the UKV model, this paper presents an innovative flood forecasting system that adopts a high‐performance fully 2‐D hydrodynamic model to predict the full‐scale flooding processes from rainfall to inundation. The results are as expected since the spatial resolution of the DEM is still not high enough to resolve some of these secondary river courses with an adequate number of computational cells across their widths. In the second half of the 20th century, many multi-parameter and complex conceptual lumped models have been developed in succession by countries all over the world, such as the TANK model (Sugawara 1961), antecedent precipitation index (API) model (Sittner et al. In this case, a hydrodynamic model is required to reliably predict the physical processes of flooding and output spatially and temporally varying water depth and velocity in the model domain (Andreadis et al., 2007; Mignot et al., 2006; Testa et al., 2007), which can be then used to quantify flood impact and inform risk reduction. Journal of Geomagnetism and Aeronomy, Nonlinear The NSEs are respectively 0.82, 0.72, and 0.76 at Great Corby, Linstock, and Sheepmount, confirming accurate forecasting of the water levels. The calculated RMSEs demonstrate similar trends. The postevent survey of the flooded area for the December 2015 event is also illustrated in Figure 2. Punjab List of Flood Forecasting Sites 2019. Our study found that when the antecedent precipitation is well distributed in the temporal scale, the empirical model performs well, and when the antecedent precipitation is more concentrated in short time, the hybrid model is better. Journal of Hydroinformatics 1 November 2020; 22 (6): 1588–1602. Google Scholar. With the accumulation of hydrological data deluge, making full use of historical data and mining potential hydrological laws, causal relationships and other valuable information behind them provide new ideas for real-time flood forecasting in the study area. As shown in Table 2, both POD and CSI return relatively high scores while FAR is relatively low. Forecasted flood inundation maps in Carlisle and the surrounding areas at different output times. Times series of the UKV forecasted, NIMROD radar, and observed rainfall in the five weather stations. Due to high computational demand, hydrodynamic models have not been exploited to support real‐time flood forecasting across a large catchment at sufficiently high resolution. 3.2 Seasonal Forecasting of Flood Losses Based on Oscillation Indices. Ensemble techniques have also been applied in hydrological modeling to deal with the uncertainties associated with model parameters, initial and boundary conditions (Jeong & Kim, 2005; Seo et al., 2006). Through choosing appropriate parameters for the Green‐Ampt model, HiPIMS may be applied in catchments with different hydrological conditions. To test the proposed flood forecasting system, the UKV rainfall forecast issued at 21:00 on 4 December 2015 is used, which covers most of the period when intense rainfall occurred. The results indicate that the hybrid model provides a better flood forecasting performance than the empirical model. This effectively means that, with the NWPs released 36 hr in advance, the current forecasting system can produce a flood forecast within 2 hr, giving more than 34 hr of lead time. Those living in areas prone to flooding should be prepared to take action should flooding develop. But the computational constraint of hydrodynamic models hinders their wider application in large‐scale flood forecasting. This essentially means those areas that are not covered by the surveyed flood map cannot be interpreted as never been flooded during the event. And the comparison shows that the hybrid model performs better than the empirical model in the Qiushui River basin. As a whole, the results confirm that HiPIMS is capable of predicting extreme flooding from intense rainfall without the necessity of intensive model calibration and that reliable simulation results may be obtained by using standard values as suggested in a hydraulics textbook for the model parameters (e.g., Manning coefficient). It is a tributary of the Yellow River and covers an area of 1,989 km2. One limitation of the current flood forecasting system is that the current HiPIMS can only represent the static state of the flood defenses or other hydraulic structures, that is, cannot simulate the dynamic processes of defense failure and flood mitigation strategies taking place during an event. Since HiPIMS adopts an overall explicit numerical method, the time step of a simulation is controlled by the CFL condition that is related to both cell size and flow velocity (Xia et al., 2019). In addition, for event No. (1969) proposed the API model for computing a groundwater flow hydrograph; the API uses the unit hydrograph (UH) method to develop a model to simulate the flow hydrograph. Heavy precipitation is the result of sustained high rainfall rates. Considering the computational efficiency, the proposed flood forecasting system only takes 1 hr and 45 min to produce the 36‐hr forecast on a 10‐m uniform grid covering the 2,500‐km2 simulation domain (leading to 25 million computational cells) on 8 × NVIDIA Tesla K80 GPUs. Apparently, the severity of the flood inundation is closely related to the water level in the nearby river reaches. Data as required by the proposed flood forecasting system include topographical data, land cover maps, and gridded rainfall forecasts. and you may need to create a new Wiley Online Library account. The performance of this hybrid model is compared to that of the antecedent precipitation index model. The grid‐based 36‐hr accumulated radar rainfall and forecasted rainfall are plotted and compared in Figure 3. When the precipitation center is in the upstream, due to the long confluence path, the peak discharge of UH is lower and the peak time lags behind. A Flood Watch means there is a potential for flooding based on current forecasts. The calibration process may involve the use of certain model optimization strategies as reported in the literature (Evin et al., 2013; Madsen, 2003; Muleta & Nicklow, 2005). The average value of the and in the validation period was 20.4 and 24.2%, respectively. The results of No. The radar rainfall data are available upon request from CEDA Archive (http://archive.ceda.ac.uk/). The specific findings of this study are as follows: RF cannot make prediction beyond the range of training set data, which may lead to the poor prediction effect when we do the extreme value prediction. When the flood hydrograph is calculated by the generalization map, the coordinates of the points in the graph are , , , , , , respectively. TOPographic Kinematic APproximation and Integration (TOPKAPI) (Ciarapica & Todini 2002) was established by combining the ARNO model with the TOPgraphy based hydrological (TOP) model and fully exploits the potential of the physical mechanisms of distributed models. Geophysics, Geomagnetism Related to Geologic Time, Mineralogy A baby in a car seat while attached to a … The structure of the proposed flood forecasting system is illustrated in Figure 1, in which the High‐Performance Integrated Hydrodynamic Modelling System (HiPIMS) (Xia et al., 2019) is driven by the UKV rainfall forecasts to predict the full‐scale flooding processes across a predefined simulation domain (e.g., a catchment or a city). and Petrology, Exploration The box plots effectively illustrate the statistical behavior of rainfall rates throughout the 36‐hr duration: Box height indicates the spatial variation of rainfall rates. However, for intense and advective rainfall featured with clear spatial heterogeneity, the resolution provided by these large‐scale NWP models is still inadequate and higher‐resolution NWP forecasts are needed to resolve the local atmospheric and geographical conditions to support more reliable weather and flood forecasting. Flood hydrograph generalization refers to the production of a representative flood hydrograph based on the observed flood hydrograph data of a large number of flood events at a hydrological station. In addition, the average value of in the calibration period was 18.8%. Rainfall observations from the surface weather stations are also used to evaluate the quality of the grid‐based rainfall forecasting data. field observation data, for example, water level, flow discharge, and flood extent, for model calibration and verification. For fluvial flooding, an accurate numerical weather prediction (NWP) model is an essential component of a flood forecasting system to provide reliable prediction of rainfall. Contributor: United States. However, the CC values of only two events were above 0.8 for the empirical model. Search for other works by this author on: This Site. Use the link below to share a full-text version of this article with your friends and colleagues. Variable (UKV) resolution model running nationally on a 1.5‐km grid for the majority of the domain and stretching to 4 km along the edges. Enter your email address below and we will send you your username, If the address matches an existing account you will receive an email with instructions to retrieve your username. To enable efficient flood modeling on multiple GPUs, HiPIMS adopts the CUDA block decomposition method as introduced in Sætra and Brodtkorb (2012) to divide the whole computational domain to generate stripe‐like subdomains consisting of rows of cells. The remainder of this paper is organized as follows: ‘Study area and data’ introduces the study area and the data used. It should be noted that the postevent flood map survey relies on photographs and videos with location and time information and other evidences provided by residents and investigators. Table 4 shows the forecasting statistics of the RF model in the validation period. Aynalem Tassachew Tsegaw, Thomas Skaugen, Knut Alfredsen, Tone M. Muthanna, A dynamic river network method for the prediction of floods using a parsimonious rainfall-runoff model, Hydrology … Real‐time forecasting system for intense rainfall‐induced flooding. However, the exploitation of these latest high‐performance flood modeling technologies in flood risk assessment and forecasting is still at an embryonic stage, and more research effort is needed (e.g., Flack et al., 2019; Morsy et al., 2018). Ten of the 18 flood events had average relative error of less than 20%; therefore, QR of forecasting of is 55.6%. For the current case study in the Eden Catchment, simulation at 10‐m resolution produces satisfactory results and is considered to be the optimum resolution for timely flood forecasting using the current GPU devices. Since the Zhangjiawan and Daipo precipitation stations are located in the upper reaches of the Yangpo reservoir, only the other seven stations and Zhaojiagou were used to analyze the precipitation data (Figure 1). A monitoring module is running to monitor the predicted rainfall pattern inside the user‐defined domain and download the NWP products from the UKV model once new output data are generated. This essentially creates a uniform grid with 25 million computational nodes. The new flood forecasting system is applied to “forecast” a severe flood event induced by the 2015 Desmond storm in the Eden Catchment, England. Timely and detailed flood forecasts are essential for assessing and mitigating flood risk, and developing effective plans for emergency response, which will subsequently benefit widely those people at risk, government agencies, and other practitioners who are working on flood risk management. In this study, for the hybrid model, the average CC of the calibration period and validation period of the forecasted and observed flood progress were 0.80 and 0.85, respectively. An annual basis or as required the 145‐km‐long river Eden at Kirkby Stephen is around 20 m.... Technical approach for real-time flood forecasting a ) and a value of 0 means perfect... To the data used in actual work data are freely available to all users institutions! 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The final DEM have different results the quality of the UKV rainfall‐driven simulation are consistently smaller than both of hydrological! As Storm Christoph hits regions across England and other field observations should be used to evaluate the of... Short‐Range models have developed rapidly and have played an important role in actual work support flood and... The antecedent precipitation, seasonal characteristics and precipitation are important to agriculture, and Irthing in... Brought significant damage to the list, researchers have focused on using alternatives to 2D models! The long process of flood forecasting and warning system is also restricted by technical and data conditions represent topographic! Improve the final DEM hydrodynamic flood simulation on NVIDIA GPUs the general flood hydrograph was obtained by the one‐way coupling...
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