Study On Multiscale-Multivariate Attribution Analysis and Prediction of Urban Rainstorm Flood

In order to explore the impact of the changing environment on urban rainstorm flood, and reveal the relationship between flood volume and its influencing factors at the micro level, the rainfall and flood volume are decomposed by the wavelet analysis method to perform the multiscale attribution analysis. Then the multiscale-multivariate prediction model of urban rainstorm flood is constructed in the Jialu River Basin in Zhengzhou city of China. The results show that the main influencing factors of flood volume are rainfall and underlying surface, where the latter causes the mutation of flood volume in 1994 and 2005. At the micro level, there is a constant linear relationship between rainfall and flood volume in d1, d2 and d3, while the impact of underlying surface on flood volume is mainly reflected in a3. The multiscale-multivariate prediction model has a good simulation effect on the flood volume of the first 45 rainstorm floods, NSE, R2 and Re are 0.966, 0.964 and 10.80%, respectively. Moreover, the model also has a good prediction effect, and the relative errors between the predicted and observed flood volume of 46th~50th rainstorm floods are all less than 20%.

Equivalence of Rainfall Type and Maximum Discharge to the Drainage Channel Capacity

This research will identify the equivalence of the serial rainfall to the design flood. The equivalence of serial rainfall data is very necessary to solve the flooding problem. A case study is in the University of Brawijaya-Malang-East Java Province-Indonesia. The methodology consists of analyzing the design flood using the Nakayasu Synthetic Unit Hydrograph and then analyzing the equivalence of cumulative serial rainfall to the design flood. The equivalence of rainfall in this research discusses two items: the rainfall equivalence to the hydraulic and hydrologic conditions. Based on the hydraulic condition, the capacity of the drainage channel can store the rainfall for 85.77 mm for the return period of 2 years; 105.86 mm for the return period of 5 years; and 119.26 mm for the return period of 10 years. However, based on the hydrologic condition, for the design flood with the return period of 2 years is 382.25 m3/s, and it has the equivalence close to the discharged recording of AWLR Gadang that is 386.76 m3/s which is due to the rainfall for 11 mm (the category of heavy rain); for the return period of 5 years, the design flood is 471.07 m3/s, and it is equivalent with the flood discharge of 463.73 m3/s that is caused by the rainfall of 12.1 mm (the category of heavy rain); for the return period of 10 years, the design flood is 589.99 m3/s, and it is caused by the rainfall of 13.4 mm (the category of heavy rain). Based on the hydraulic and hydrologic condition, the capacity of the drainage channel that is installed in the campus region of Brawijaya University, it can be concluded that for the return period of 2 years, the drainage channel is only able to reduce 41% of flood volume; for the return period of 5 years, the drainage channel is only able to reduce 26% of flood volume; however, for the return period of 10 years, the drainage channel is only able to reduce 23% of flood volume.

Relationship Between Rainfall Duration and Sewer System Performance Measures Within the Context of Uncertainty

Urbanization and climate change have resulted in an increase in catchment runoff, often exceeding the designed capacity of sewer systems. The decision to modernize a sewer system should be based on appropriate criteria. In engineering practice, the above is commonly achieved using a hydrodynamic model of the catchment and the simulation of various rainfall events. The article presents a methodology to analyze the effect of rainfall characteristics parametrized with intensity-duration-frequency (IDF) curves in regard to performance measures of sewerage networks (flood volume per unit impervious surface and share of overfilled manholes in the sewerage network) accounting for the model uncertainty determined via the generalized likelihood uncertainty estimation (GLUE) method. An urban catchment was modeled with the Storm Water Management Model (SWMM). Analyses showed that the model uncertainty exerts a large impact on certain measures of sewage network operation. Therefore, these measures should be analyzed in similar studies. This is very important at the stage of decision making in regard to the modernization and sustainable development of catchments. It was found that among the model parameters, the Manning roughness coefficient of sewer channels yields a key impact on the specific flood volume, while the area of impervious surfaces yields the greatest impact on the share of overflowed manholes.

Was there a glacial outburst flood in the Torngat Mountains during Marine Isotope Stage 3?

We report previously unpublished evidence for a Marine Isotope Stage 3 (MIS 3; 60–26 ka) glacial outburst flood in the Torngat Mountains (northern Quebec/Labrador, Canada). We present 10Be cosmogenic exposure ages from legacy fieldwork for a glacial lake shoreline with evidence for outburst flooding in the Torngat Mountains, with a minimum age of 36 ± 3 ka (we consider the most likely age, corrected for burial, to be ~56 ± 3 ka). This shoreline position and age can potentially constrain the Laurentide Ice Sheet margin in the Torngat Mountains. This region, considered a site of glacial inception, has no published dated geologic constraints for high-elevation MIS 3 ice margins. We estimate the freshwater flux associated with the inferred glacial outburst flood using high-resolution digital elevation maps corrected for glacial isostatic adjustment. Using assumptions about the ice-dammed locations we find that a freshwater flood volume of 1.14 × 1012 m3 could have entered the Hudson Strait. This glacial outburst flood volume could have contributed to surface ocean freshening to cause a measurable meltwater signal in δ18O records, but would not necessarily have been associated with substantial ice rafted debris. Future work is required to refine estimates of the size and timing of such a glacial outburst flood. Nevertheless, we outline testable hypotheses about the Laurentide Ice Sheet and glacial outburst floods, including possible implications for Heinrich events and glacial inception in North America, that can be assessed with additional fieldwork and cosmogenic measurements.

Peak flood volume and its suspended sediment at various rainfall in Kedungbulus catchment in Gombong, Central Java, Indonesia

Flood is a natural disaster that frequently happens and causes many material and immaterial losses. During flooding, the suspended sediment is carried along by the streamflow. The amount of sediment transported varies and depends on natural and anthropogenic factors. Limited studies have been conducted regarding the relationship between peak flood volume and its sediment content. Therefore, a study with the purpose to understand the relationship of rainfall characteristics, peak flood volume, and suspended sediment was undertaken in Kedungbulus Catchment in Gombong, Central Java, Indonesia. The size of Kedungbulus catchment is 37.8 km2. To collect the required data, an automatic stream water level recorder was installed in the outlet of the catchment. In addition, an automatic and two conventional rain gauges were set up inside the catchment. Hydrograph and statistical analysis were conducted on 2016-2017 data. The results showed that during the study period, the highest peak flood volume occurred on October 8, 2016. The flood duration was 490 minutes, with the time to peak was 135 minutes. At the highest peak flood volume, the stream water was 5,091,221 m3, and the suspended sediment was around 2,394 tons. Rainfall depth significantly affects the peak flood volume and its suspended sediment. The rainfall intensity and Antecedent Soil Moisture Content (ASMC) weakly correlate with peak flood volume and its suspended sediment content.

Estimation of Urban Imperviousness and its Impacts on Flashfloods in Gazipaşa, Turkey

The paper examines flooding issues under rapid urbanization in Gazipasa city during the past seven years 2013-2019. The Storm Water Management Model (SWMM) integrated with the satellite images representing temporal variation in the land use and land cover (LULC) characteristics of the city were used to determine the variation in the runoff generation capacity, flood volume, and associated risks. The Google Earth software together with GIS technology were utilized to create and handle spatial data required for SWMM simulation. Standard design storm intensity derived from the local intensity-duration-frequency curves was used as the stationary input parameter for SWMM simulation in both the past and current LULC conditions. The comparison between LULC maps showed that the extent of urban imperviousness area has been approximately increased by 80% in average. The SWMM simulations showed the peak flood value of 51.3 m3/sec and 61.4 m³/sec for the year 2013 and 2019, respectively. Moreover, under the same design storm, Rational Method has been applied and 39 m3/sec of peak flow rate has been calculated by disregarding the urbanization activity. The results indicate that the LULC variation during the past seven years resulted in almost 20% (18%) increase in peak flow (flood volume).

Volumetric Quantification of Flash Flood Using Microwave Data on a Watershed Scale in Arid Environments, Saudi Arabia

Actual flood mapping and quantification in an area provide valuable information for the stakeholder to prevent future losses. This study presents the actual flash flood quantification in Al-Lith Watershed, Saudi Arabia. The study is divided into two steps: first is actual flood mapping using remote sensing data, and the second is the flood volume calculation. Two Sentinel-1 images are processed to map the actual flood, i.e., image from 25 May 2018 (dry condition), and 24 November 2018 (peak flood condition). SNAP software is used for the flood mapping step. During SNAP processing, selecting the backscatter data representing the actual flood in an arid region is challenging. The dB range value from 7.23–14.22 is believed to represent the flood. In GIS software, the flood map result is converted into polygon to define the flood boundary. The flood boundary that is overlaid with Digital Elevation Map (DEM) is filled with the same elevation value. The Focal Statistics neighborhood method with three iterations is used to generate the flood surface elevation inside the flood boundary. The raster contains depth information is derived by subtraction of the flood surface elevation with DEM. Several steps are carried out to minimize the overcalculation outside the flood boundary. The flood volume can be derived by the multiplication of flood depth points with each cell size area. The flash flood volume in Al-Lith Watershed on 24 November 2018 is 155,507,439 m3. Validity checks are performed by comparing it with other studies, and the result shows that the number is reliable.

Multi-scale flood prediction based on GM (1,2)-fuzzy weighted Markov and wavelet analysis

In order to forecast flood accurately and reveal the relationship between rainstorm and flood at the micro level, a model which combines wavelet analysis, GM (1,2) and fuzzy weighted Markov is built. Taking the Jialu River of Zhengzhou City in China as study area, the GM (1,2) model is constructed between the components of rainfall and flood volume by wavelet decomposition to connect the two variables, then a fuzzy weighted Markov method is introduced to correct the predicted component of flood volume. The corrected results are superimposed to obtain the predicted value of flood. To verify the reliability of the model, the maximum daily, 3-, 5- and 7-day flood volume of the next five floods in Zhongmu and Jiangang hydrological stations are predicted in turn. The results show that the multi-scale flood forecasting model has high overall forecasting accuracy, with the average relative errors all less than 10%. The forecasting accuracy of maximum five-day flood volume is higher than other periods. On the micro level, the results indicate that the fluctuation trend and period of rainfall-flood volume in d1, d2 and d3 are basically the same. Among the components of forecasted flood, the impact of rainfall on flood volume is most significant in the d3 component.

Calculation Method of Short Duration Rainstorm Intensity Formula Considering Non-Stationarity of Rainfall Series: Impacts on Simulation of Urban Drainage System

The changing nature of the earth's climate and rapid urbanization lead to the change of rainfall characteristics in urban areas, and the stability of rainfall series is destroyed, it is a difficult challenge to consider this change in urban drainage simulation. A variety of methods are used to test the stationarity of annual maximum rainfall intensity series of Zhengzhou meteorological station from 1981 to 2010, and the intensity-duration-frequency (IDF) curves of changing environment are fitted by GAMLSS model and further generalized into short duration rainstorm intensity formula. The 3-hour design rainstorm in different scenarios was used as the input of Mike Flood model to simulate the operation of the campus drainage system of Zhengzhou University. Results indicated that: The rainfall series is non-stationary and has an increasing trend. Although the parameters of the short duration rainstorm intensity formula have no fixed change rules, there are traces to follow in the design rainstorm. According to Mike Flood model, the non-stationary scenario provides a series of dangerous signals such as more flood volume, larger inundation area, higher flood depth and slower recession process. The flood volume of the non-stationary scenario is 23.5% more than that of the stationary scenario, and the inundated area is 18.5% more when the return period is 5 years. In the future, the difference is 34.0% and 24.6% respectively, and it can reach more than 50% when the return period is once in two years. We will discuss the non-stationarity and challenges brought about by changing environments.