Post-event Flood Behaviour Analysis for the Richmond River - February 2022 Event URBS Hydrology Model

This report details the flood gauging operations undertaken from 1700 hrs on March 21st, 1983 to 0200 hrs on March 22nd, 1983 and presents previous flood data collected on the Georges River. The Georges River has a total catchment area of approximately 650 square kilometres and flows into the south-western corner of Botany Bay about 15km south of Sydney. The tidal influence under low freshwater discharge conditions extends approximately 40km upstream and terminates at Liverpool Weir. Flood monitoring at selected sites as defined in Figure 1 is undertaken for floods in excess of a one in ten year frequency. Flood monitoring is commenced on receipt of Confidential/Preliminary Flood Warning advice when it is predicted that a stage level of 2.0 meters at the Liverpool Weir gauge (approximately 4.7m AHD) will be exceeded. The collection of this flood data has in the past and will in the future be used to calibrate physical modeIs which are constructed at the PWD Manly Hydraulics Laboratory and U.N.S.W. Water Research Laboratory. The current metering- lines, flood gauge location and automatic recorder locations are as follows: i) Current metering/flood level observations: East Hills Footbridge Milperra Road Bridge Rabaul Road (gauge readings only) Lansdowne Bridge - Prospect Creek Irelands Bridge - Cabramatta Creek Mountbatten Bridge - Warwick Farm ii) Automatic recorders are located: Milperra Bridge (see note below) Lansdowne Bridge Cutler Road, Lansvale Scrivener Street, Warwick Farm Liverpool weir (upstream) Note on Milperra - The Milperra automatic recorder is located immediately upstream of the road bridge. It consisted of two measurement points, however only the downstream one was operating at the time of the monitoring. The recorder has since been modified and now has only one measurement point.

The flood magnitude statistics can be used for applications such as flood plain delineation and design of hydraulic structures. The drought severity statistics can be used for applications such as water abstraction and effluent dilution.

Post-event Flood Behaviour Analysis for the Richmond River - February 2022 Event Hydraulic Model

This data release provides the source data and results of a flood frequency analysis and annual exceedance probability estimation for a flood that occurred on July 11, 2022 in the Delta River Basin, Alaska. Data are provided for two streamgages that had at least 10 years of peak-flow record. The data include streamgage information, PeakFQ input (.txt and .PSF files) PeakFQ output (.PRT, .EXP, and .JPEG files), flood frequency parameters, flood frequency estimates for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, and annual exceedance probability estimates for the flood of interest. These data were intended to support investigations of streamflow in the Delta River Basin.

This data release provides the source data and results of a flood frequency analysis and annual exceedance probability estimation for a flood that occurred on July 11, 2022 in the Delta River Basin, Alaska. Data are provided for two streamgages that had at least 10 years of peak-flow record. The data include streamgage information, PeakFQ input (.txt and .PSF files) PeakFQ output (.PRT, .EXP, and .JPEG files), flood frequency parameters, flood frequency estimates for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, and annual exceedance probability estimates for the flood of interest. These data were intended to support investigations of streamflow in the Delta River Basin.

The U.S. Geological Survey (USGS), in cooperation with Connecticut Department of Transportation, completed a study to improve flood-frequency estimates in Connecticut. This companion data release is a Microsoft Excel workbook for: (1) computing flood discharges for the 50- to 0.2-percent annual exceedance probabilities from peak-flow regression equations, and (2) computing additional prediction intervals, not available through the USGS StreamStats web application. The current StreamStats application (version 4) only computes the 90-percent prediction interval for stream sites in Connecticut. The Excel workbook can be used to compute the 70-, 80-, 90-, 95-, and 99-percent prediction intervals. The prediction interval provides upper and lower limits of the estimated flood discharge with a certain probability, or level of confidence in the accuracy of the estimate. The standard error of prediction for the Connecticut peak-flow regression equations ranged from 26.3 to 45.0 percent (Ahearn and Hodgkins, 2020). The Excel workbook consists of four worksheets. The worksheets provide an overview of how the application works; input and output tables of the explanatory variables and flood discharges, and graphical display of the results; and the computational formulas used to estimate the flood discharges and prediction intervals.

The U.S. Geological Survey (USGS), in cooperation with Connecticut Department of Transportation, completed a study to improve flood-frequency estimates in Connecticut. This companion data release is a Microsoft Excel workbook for: (1) computing flood discharges for the 50- to 0.2-percent annual exceedance probabilities from peak-flow regression equations, and (2) computing additional prediction intervals, not available through the USGS StreamStats web application. The current StreamStats application (version 4) only computes the 90-percent prediction interval for stream sites in Connecticut. The Excel workbook can be used to compute the 70-, 80-, 90-, 95-, and 99-percent prediction intervals. The prediction interval provides upper and lower limits of the estimated flood discharge with a certain probability, or level of confidence in the accuracy of the estimate. The standard error of prediction for the Connecticut peak-flow regression equations ranged from 26.3 to 45.0 percent (Ahearn and Hodgkins, 2020). The Excel workbook consists of four worksheets. The worksheets provide an overview of how the application works; input and output tables of the explanatory variables and flood discharges, and graphical display of the results; and the computational formulas used to estimate the flood discharges and prediction intervals.

환경부에서 제공하는 도시침수 지도에서 장마철 집중호우·소나기 등으로 쌓인 침수심 통계 데이터(0.5m 이하, 0.5~1.0m, 1.0~2.0m, 2.0~5.0m, 5.0m 이상)를 행정구역별(시군구, 읍면동), 빈도별(30년, 50년, 80년, 100년)로 조회할 수 있는 서비스.

The U.S. Geological Survey (USGS), in cooperation with the New Mexico Department of Transportation, estimated the magnitude and frequency of floods corresponding to the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities (AEPs; otherwise known as the 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year floods, respectively) for 346 selected streamgages in New Mexico and parts of Arizona, Colorado, Oklahoma, Texas, and Utah using data through water year 2020. An updated regional flood skew, -0.145, standard error 0.454, was computed for the study area. Regression equations were developed which can be used to estimate the magnitude and frequency of floods at ungaged locations on unregulated streams in the study area. The methods and results of the study are published in the parent report (Bell and others, 2022, https://doi.org/10.5066/XXXXXXXX). For the 346 selected streamgages, this dataset includes peak-flow (*.pkf) and specification (*.psf), output (*.PRT), and export (*.EXP) files from version 7.3 of USGS PeakFQ software (Veilleux and others, 2014; Flynn and others, 2006). Within PeakFQ software, the Expected Moments Algorithm (EMA) was used to conduct frequency analyses to estimate stream discharges corresponding to the 0.5, 0.2, 0.1, 0.04, 0.02, 0.01, 0.005, and 0.002 AEPs. When appropriate, the updated regional skew was used to weight the at-site skew in the frequency analyses. Results of the frequency analyses were used in generalized least-squares (GLS) regression to generate equations that predict discharges corresponding to selected AEPs at ungaged locations on streams in the study area (Bell and others, 2022).