list based flood forecast

For both arid/semiarid and humid catchments, remote sensing products and outputs from regional scale hydrological models may provide useful data sources and information for estimating infiltration parameters. In the U.K. postcode system, the first part of a postcode has one or two letters indicating a city or a region (i.e., city/region code), followed by one or two numbers; and the city center often has the number “1” alongside the city/region code. Error statistics of the RF model in the validation period. It effectively reflects and captures the effects of localized domain features (e.g., mountains) on rainfall patterns. The downpours are expected to hit on Wednesday and last until the weekend. Finally, it should be noted that, due to the specific limitation of HiPIMS in handling subsurface flows (i.e., no explicit consideration of subsurface runoff), the current flood forecasting system may not be suitable for forecasting long‐term flood events that are sensitive to subsurface runoff, such as those induced by prolonged but less intense monsoon rainfall. In a flood event, water depth is generally much smaller than the horizontal inundation extent, and the flow hydrodynamics can be mathematically described by the 2‐D depth‐averaged shallow water equations (SWEs). Such detailed flood information is essential for assessing potential flood impact and allows relevant decision‐makers to develop better informed flood mitigation strategies and emergency management plans. The results show that the hybrid model yields accurate predictions. As a result of climate change, more intense precipitation is expected in the warmer future (Intergovernmental Panel on Climate Change, 2014; Kendon et al., 2012), which may consequently trigger more extreme rainfall‐induced flood events and increase flood risk. The performance of the UKV model for rainfall forecasting has been significantly improved, compared with the coarse‐resolution models (Kendon et al., 2012; Mittermaier & Csima, 2017). See Figures 11–15 for comparison of observed and forecasted flood hydrographs of the five flood events in the validation period. 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. Second, compute the values of antecedent precipitation at the early stage of the forecast period as follows: To evaluate the forecasting ability of the models, the simulation accuracy of each flood event is summarized. 1969) and Xin'anjiang model (Renjun et al. 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). 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. Real‐time flood forecasting is an effective means to mitigate the negative impact of flooding by providing timely and accurate flood information and warnings to the public and relevant parties. 19990711, although the CC value of the empirical model is 0.84, Figure 12 shows that the hydrograph forecasted by the empirical model only follows the trend of the observed hydrograph and the difference between forecasted peak discharge and observed peak discharge is relatively large. field observation data, for example, water level, flow discharge, and flood extent, for model calibration and verification. In general, the model provided acceptable accuracy in both the calibration and validation periods. The River Eden is 145 km long, and the average and maximum discharges at Sheepmount are 51.82 and 1,700 m. NIMROD radar rainfall (a), UKV forecasted rainfall (b) from 21:00 on 4 December to 9:00 on 6 December 2015, and their difference (c). More recently, the high‐performance computing power provided by modern graphics processing units (GPUs) has led to a step change in the flood modeling practice (e.g., Smith & Liang, 2013). The grid‐based rainfall forecasts are also compared with the point‐based rainfall observations recorded in the surface weather stations, available from the Met Office Integrated Data Archive System (MIDAS). Geology and Geophysics, Physical In the first step, peak discharge was forecasted. Hence, there is an urgent need for a flood forecasting method that can not only avoid the direct simulation of physical flood formation processes in arid and semi-arid areas but also meet forecasting accuracy requirements. The performance of the proposed forecasting system is tested and confirmed by implementation in a 2,500‐km2 domain covering the whole Eden Catchment in England to “forecast” the 2015 Storm Desmond flood event. However, the existing hydrological models are more suitable for flood forecasting in humid areas. Related to Geologic Time, Mineralogy Observed and forecasted flood hydrograph of event No. The hybrid model outperforms the currently used Antecedent Precipitation Index model in the study area. 2.2 The overall role of the New South Wales and the Australian Capital Territory Flood Warning Consultative Committee is to coordinate the development and operation of flood forecasting However, when dealing with less extreme events or events occurring in an originally drier catchment, the infiltration effect should be taken into account, and more data and extra effort are needed for model calibration. Therefore, the quantitative comparison between the simulated and surveyed flood extents is only made in the urban area of Carlisle, which is more completely covered by the postevent survey. In addition to those overly simplified statistical approaches, hydrological models are commonly used to predict flooding at a catchment scale (Blöschl et al., 2008; Garrote & Bras, 1995; J. Li et al., 2017; Liu et al., 2005). Tiantian Tang, Zhongmin Liang, Yiming Hu, Binquan Li, Jun Wang; Research on flood forecasting based on flood hydrograph generalization and random forest in Qiushui River basin, China. Another conceptual model: distributed hydrological models also have made great progress, such as the Soil and Water Assessment Tool (SWAT) model (El-Nasr et al. Figure 9 illustrates the forecasted inundation maps for Carlisle and the surrounding areas at different output times to depict the flooding process during Storm Desmond. 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. Compare the new method with the empirical model: the API model, which is currently used in actual work. Search for other works by this author on: Journal of Hydroinformatics (2020) 22 (6): 1588–1602. Driven by radar rainfall data, both of the 5‐ and 10‐m simulations use the same model parameters and initial conditions as the aforementioned whole‐catchment simulation. Thus, this study provides a method for improving the accuracy of flood forecasting. As the difference between the NIMROD radar rainfall and the UKV forecasted rainfall is noticeable (refer to the discussion in section 4.2), it is necessary to compare the flood modeling results driven by different rainfall sources and confirm the reliability of the flood forecasting outputs. Performance comparison of the hybrid and empirical model in the calibration period. 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. Table 4 shows the forecasting statistics of the RF model in the validation period. JEAN-CLAUDE BADER Institut de Recherche pour le Développement , BP 64501, F-34394, Montpellier Cedex 5, France E-mail: bader@mpl.ird.fr , JEAN-PHILIPPE PIEDELIEVRE Météo France, CNRM , 42 Avenue G. Coriolis, F-31057, Toulouse Cedex, France E-mail: jean … First, selected flood events from 1980 to 2010 were generalized using the flood hydrograph generalization method. The two sets of hydrographs are actually similar during the high‐flow period but are significantly different at the low‐flow sections when the river flow starts to rise at the beginning and fall back to the normal flow condition at the end. Other distributed models include the IHDM (Institute of Hydrology Distributed Model) model and Variable Infiltration Capacity (VIC) model (Liang et al. As such, the committee is responsible for reviewing this Service Level Specification on an annual basis or as required. An RF is a classifier consisting of a collection of tree-structured classifiers ⁠, where are independent identically distributed random vectors, and each tree casts a unit vote for the most popular class at input x (Breiman 2001). So the surveyed flood map should be used with great care. Dec. 24, 2020 Updated: Dec. 24, 2020 7:20 a.m. Facebook Twitter Email. RF utilizes bootstrap resampling technology to sample original samples to generate a number of training samples, each of which randomly selects feature attributes through random subspace methods to construct a decision tree. Figure 10 presents the water level hydrographs predicted using the different 63‐hr rainfall inputs, compared with the corresponding observations at the three selected river gauges. It is a tributary of the Yellow River and covers an area of 1,989 km2. Punjab List of Flood Forecasting Sites 2019. Eden is a relatively wet catchment with an annual average rainfall of over 2,800 mm, 3 times of the annual average in England. Then the performance of the flood forecasting system is demonstrated by directly using the UKV numerical rainfall predictions as the model inputs. 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. According to the surveyed flood extent provided by the EA, Carlisle and its upstream region along River Eden are mostly flooded during Storm Desmond (see Figure 7). However, the peak discharge is higher and the peak time is earlier. Performance comparison of the hybrid and empirical model in the validation period. However, in semi-arid and arid areas, the use of the hydrological model is restricted by technical and data conditions. 19840701 and No. As shown in Figure 2, the Eden Catchment is located in the northwest of England with an approximate area of 2,400 km2. In hydrodynamic flood simulations, the performance of a model is usually sensitive to spatial resolution. Yet, there are two events which have different results. It is a parcel‐based land cover map created by classifying satellite data into 21 classes (Rowland et al., 2017), available at a spatial resolution of up to 25 m for the whole United Kingdom. The amounts of rainfall in one day and two consecutive days both set new historical records in the catchment, as did the water levels and flow rates at some river gauges, such as Sheepmount, on the River Eden (Environment Agency, 2016). Random forest (RF) is one of a data-driven model which combines the prediction from an ensemble of decision trees (Breiman 2001). However, for a more humid catchment in England that is predominantly featured with saturation‐excess runoff generation, an additional step is needed to spatially divide the model domain into two categories, that is, saturated zones and unsaturated zones. Whole Eden is a deterministic model that produces one prediction in each output is typically time series of rate! Damage and impact to the location of the precipitation intensity is large, mainly because the observed and water... Less straightforward smaller than those calculated against the originally predicted water depth at three. Was 20.4 and 24.2 %, respectively highly transient flooding process from intense rainfall 2,500‐km2 computational domain covering downstream! The risk of localised flooding as four days of heavy rain are for... 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