Instantaneous Peak Flow Research Articles

Estimation of Instantaneous Peak Flow Using Machine-Learning Models and Empirical Formula in Peninsular Spain

The design of hydraulic structures and flood risk management is often based on instantaneous peak flow (IPF). However, available flow time series with high temporal resolution are scarce and of limited length. A correct estimation of the IPF is crucial to reducing the consequences derived from flash floods, especially in Mediterranean countries. In this study, empirical methods to estimate the IPF based on maximum mean daily flow (MMDF), artificial neural networks (ANN), and adaptive neuro-fuzzy inference system (ANFIS) have been compared. These methods have been applied in 14 different streamflow gauge stations covering the diversity of flashiness conditions found in Peninsular Spain. Root-mean-square error (RMSE), and coefficient of determination (R2) have been used as evaluation criteria. The results show that: (1) the Fuller equation and its regionalization is more accurate and has lower error compared with other empirical methods; and (2) ANFIS has demonstrated a superior ability to estimate IPF compared to any empirical formula.

Estimating instantaneous peak flow from mean daily flow

AbstractWe revisited three traditional methods and proposed a slope-based method, which all require only mean daily flow (MDF) records as inputs, to estimate instantaneous peak flows (IPFs). We applied these methods to 144 basins in Iowa, USA, with drainage areas in the range 7–220,000 km2. This application involves ∼3,800 peak flow events triggered by snow-melting and rainfall over the period from 1997 to 2014. The results show that: using a sequence of MDF rather than just the maximum MDF improves the accuracy of estimating IPFs from MDFs; Sangal's method tends to overestimate, Fill and Steiner's method works reasonably well and is marginally outperformed by the slope-based method. For the slope-based method, about 75% of the basins have prediction error of IPFs within ±10% and about 85% of the basins within ±20%; performances of the four methods degrade as the basin size decreases. Fill and Steiner's and the slope-based methods work well for basins larger than 500 km2, poorly for basins smaller than 100 km2, and fairly well for basins with sizes in between. Our proposed method is a simple and promising tool to estimate IPFs from MDFs for areas where IPF records are unavailable or are insufficient.

Hydroclimate drivers and atmospheric teleconnections of long duration floods: An application to large reservoirs in the Missouri River Basin

A comprehensive framework is developed to assess the flood types, their spatiotemporal characteristics and causes based on the rainfall statistics, antecedent flow conditions, and atmospheric teleconnections. The Missouri River Basin (MRB) is used as a case study for the application of the framework. Floods are defined using the multivariate characteristics of annual peak, volume, duration, and timing. The temporal clustering of flood durations is assessed using a hierarchical clustering analysis, and low-frequency modes are identified using wavelet decomposition. This is followed by an identification of the synoptic scale atmospheric processes and an analysis of storm tracks that entered the basin and their moisture releases. Atmospheric teleconnections are distinctively persistent and well developed for long duration flood events. Long duration floods are triggered by high antecedent flow conditions which are in turn caused by high moisture release from the tracks. For short duration floods, these are insignificant and appear to occur random across the MRB in the recent half-century. The relative importance of hydroclimatic drivers (rainfall duration, rainfall intensity and antecedent flow conditions) in explaining the variance in flood duration and volume is discussed using an empirical log-linear regression model. The implication of analyzing the duration and volume of the floods in the context of flood frequency analysis for dams is also presented. The results demonstrate that the existing notion of the flood risk assessment and consequent reservoir operations based on the instantaneous peak flow rate at a stream gage needs to be revisited, especially for those flood events caused by persistent rainfall events, high antecedent flow conditions and synoptic scale atmospheric teleconnections.

Estimation of instantaneous peak flow from maximum mean daily flow by regionalization of catchment model parameters

AbstractRegionalization methods have been effectively used in many hydrological studies, such as regional flood frequency analysis and low flows. However, there is no study to estimate the instantaneous peak flow (IPF) from maximum mean daily flow (MDF) using hydrological models with regionalized parameters. In this paper, the semidistributed conceptual hydrological model Hydrologiska Byråns Vattenbalansavdelning is operated on a daily time step for 18 catchments in the Aller‐Leine basin, Germany. The model is calibrated on four different flow statistics, including winter/summer extremes distribution and flow duration curves. The model parameter values are predefined with the associated catchment descriptors by a transfer function. Two different regionalization schemes are investigated: one is carried out for all the catchments in the study area; the other one is only performed for several catchments within a cluster. The k‐means algorithm is used to 12 different catchment characteristics from all 18 catchments as the partitional clustering algorithm. Subsequently, the general extreme value distributions are fitted to the modeled MDFs, which are then transferred into IPF quantiles using a multiple regression model.The results show that (a) the uncertainty resulted from model parameter regionalization for the estimation of IPFs is much smaller than the error when using MDFs instead of IPFs; (b) the hydrological responses of the clustered catchments located in the flat areas are, in general, not as homogeneous as the ones in high elevated regions; and (c) the model with the parameters derived from the same regionalization coefficients within a cluster performs better using the corresponding parameters estimated through all the catchments.

Assessment of the climate change impacts on flood frequency (case study: Bazoft Basin, Iran)

The present study attempts to investigate potential impacts of climate change on floods frequency in Bazoft Basin which is located in central part of Iran. A combination of four general circulation models is used through a weighting approach to assess uncertainty in the climate projections. LARS-WG model is applied to downscale large scale atmospheric data to local stations. The resulting data is in turn used as input of the hydrological model Water and Energy Transfer between Soil, plants and atmosphere (WetSpa) to simulate runoff for present (1971–2000), near future (2020–2049) and far future (2071–2100) conditions. Results demonstrate good performance of both WetSpa and LARS-WG models. In addition in this paper instantaneous peak flow (IPF) is estimated using some empirical equations including Fuller, Sangal and Fill–Steiner methods. Comparison of estimated and observed IPF shows that Fill–Steiner is better than other methods. Then different probability distribution functions are fit to IPF series. Results of flood frequency analysis indicate that Pearson III is the best distribution fitted to IPF data. It is also indicated that flood magnitude will decrease in future for all return periods.

Comparison of different methods for reconstruction of instantaneous peak flow data

AbstractIn arid and semi-arid regions, documentary data of past floods remain justly rare and highly fragmentary in most cases. Existence of many effective parameters on maximum flood discharge and the complex relationships between them is an important challenge in the reconstruction of these data and hence, it limited the application of traditional methods. In this paper, an alternative approach (i.e. artificial intelligence methods) has been evaluated to determine the interactive relations of them. To this end, flow data was collected from 29 gauging stations in the central part of Iran for the period 1965 to 2007. Following quality and homogeneity controls of the data, reconstruction of instantaneous peak flow time series were made using maximum daily data by four different methods; regression method (REG), artificial neural network (ANN), genetic algorithm (GA) and adaptive neuro-fuzzy inference system (ANFIS). Results showed that in all studied stations, ANFIS reconstructs instantaneous peak flow val...

Estimation of instantaneous peak flows from maximum mean daily flows using the HBV hydrological model

AbstractThe record length and quality of instantaneous peak flows (IPFs) have a great influence on flood design, but these high resolution flow data are not always available. The primary aim of this study is to compare different strategies to derive frequency distributions of IPFs using the Hydrologiska Byråns Vattenbalansavdelning (HBV) hydrologic model. The model is operated on a daily and an hourly time step for 18 catchments in the Aller‐Leine basin, Germany. Subsequently, general extreme value (GEV) distributions are fitted to the simulated annual series of daily and hourly extreme flows. The resulting maximum mean daily flow (MDF) quantiles from daily simulations are transferred into IPF quantiles using a multiple regression model, which enables a direct comparison with the simulated hourly quantiles. As long climate records with a high temporal resolution are not available, the hourly simulations require a disaggregation of the daily rainfall. Additionally, two calibrations strategies are applied: (1) a calibration on flow statistics; (2) a calibration on hydrographs.The results show that: (1) the multiple regression model is capable of predicting IPFs with the simulated MDFs; (2) both daily simulations with post‐correction of flows and hourly simulations with pre‐processing of precipitation enable a reasonable estimation of IPFs; (3) the best results are achieved using disaggregated rainfall for hourly modelling with calibration on flow statistics; and (4) if the IPF observations are not sufficient for model calibration on flow statistics, the transfer of MDFs via multiple regressions is a good alternative for estimating IPFs. Copyright © 2015 John Wiley & Sons, Ltd.

Predicting landscape sensitivity to present and future floods in the Pacific Northwest, USA

AbstractFloods are the most frequent natural disaster, causing more loss of life and property than any other in the USA. Floods also strongly influence the structure and function of watersheds, stream channels, and aquatic ecosystems. The Pacific Northwest is particularly vulnerable to climatically driven changes in flood frequency and magnitude, because snowpacks that strongly influence flood generation are near the freezing point and thus sensitive to small changes in temperature. To improve predictions of future flooding potential and inform strategies to adapt to these changes, we mapped the sensitivity of landscapes to changes in peak flows due to climate warming across Oregon and Washington. We first developed principal component‐based models for predicting peak flows across a range of recurrence intervals (2‐, 10‐, 25‐, 50‐, and 100‐years) based on historical instantaneous peak flow data from 1000 gauged watersheds in Oregon and Washington. Key predictors of peak flows included drainage area and principal component scores for climate, land cover, soil, and topographic metrics. We then used these regression models to predict future peak flows by perturbing the climate variables based on future climate projections (2020s, 2040s, and 2080s) for the A1B emission scenario. For each recurrence interval, peak flow sensitivities were computed as the ratio of future to current peak flow magnitudes. Our analysis suggests that temperature‐induced changes in snowpack dynamics will result in large (>30–40%) increases in peak flow magnitude in some areas, principally the Cascades, Olympics, and Blue Mountains and parts of the western edge of the Rocky Mountains. Flood generation processes in lower elevation areas are less likely to be affected, but some of these areas may be impacted by floodwaters from upstream. These results can assist land, water, and infrastructure managers in identifying watersheds and resources that are particularly vulnerable to increased peak flows and developing plans to increase their resilience. Copyright © 2015 John Wiley & Sons, Ltd.

Lithologic and hydrologic controls of mixed alluvial–bedrock channels in flood-prone fluvial systems: Bankfull and macrochannels in the Llano River watershed, central Texas, USA

The rural and unregulated Llano River watershed located in central Texas, USA, has a highly variable flow regime and a wide range of instantaneous peak flows. Abrupt transitions in surface lithology exist along the main-stem channel course. Both of these characteristics afford an opportunity to examine hydrologic, lithologic, and sedimentary controls on downstream changes in channel morphology. Field surveys of channel topography and boundary composition are coupled with sediment analyses, hydraulic computations, flood-frequency analyses, and geographic information system mapping to discern controls on channel geometry (profile, pattern, and shape) and dimensions along the mixed alluvial–bedrock Llano River and key tributaries. Four categories of channel classification in a downstream direction include: (i) uppermost ephemeral reaches, (ii) straight or sinuous gravel-bed channels in Cretaceous carbonate sedimentary zones, (iii) straight or sinuous gravel-bed or bedrock channels in Paleozoic sedimentary zones, and (iv) straight, braided, or multithread mixed alluvial–bedrock channels with sandy beds in Precambrian igneous and metamorphic zones. Principal findings include: (i) a nearly linear channel profile attributed to resistant bedrock incision checkpoints; (ii) statistically significant correlations of both alluvial sinuosity and valley confinement to relatively high f (mean depth) hydraulic geometry values; (iii) relatively high b (width) hydraulic geometry values in partly confined settings with sinuous channels upstream from a prominent incision checkpoint; (iv) different functional flow categories including frequently occurring events (<1.5-year return periods) that mobilize channel-bed material and less frequent events that determine bankfull channel (1.5- to 3-year return periods) and macrochannel (10- to 40-year return periods) dimensions; (v) macrochannels with high f values (mostly ≥0.45) that develop at sites with unit stream power values in excess of 200watts per square meter (W/m2); and (vi) downstream convergence of hydraulic geometry exponents for bankfull and macrochannels, explained by co-increases of flood magnitude and noncohesive sandy sediments that collectively minimize development of alluvial bankfull indicators. Collectively, these findings indicate that mixed alluvial–bedrock channels exhibit first-order lithologic controls (lithologic resistance and valley confinement) of channel geometry, second-order hydrologic (flow regime) control of channel dimensions, and third-order sedimentary controls that exert subsidiary influence on channel shape and bed configuration.

Estimation of the instantaneous peak flow from maximum daily flow: a comparison of three methods

Three different methods are compared to estimate the instantaneous peak flow (IPF) from the corresponding maximum daily flow (MDF), as the daily data are more often available at gauges of interest and often with longer recording periods. In the first approach, simple linear regression is applied to calculate IPF from MDF values using probability weighted moments and quantile values. In the second method, the use of stepwise multiple linear regression analysis allows to identify the most important catchment descriptors of the study basin. The resulting equation can be applied to transfer MDF into IPF. With the third method, the temporal scaling properties of annual maximum flow series are investigated based on the hypothesis of piece wise simple scaling combined with the generalized extreme value distribution. The scaling formulas developed from three 15 min stations in the Aller-Leine river basin of Germany are transferred to all daily stations to estimate the IPF. The method based on stepwise multiple linear regression gives the best results compared with the other two methods. The simple regression method is the easiest to apply given sufficient peak flow data, while the scaling method is the most efficient method with regard to data use.

River instantaneous peak flow estimation using daily flow data and machine-learning-based models

Estimation of the design flood flow for hydraulic structures is often performed by adjusting probabilistic models to daily mean flow series. In most cases, this may cause under design of the structure capacity with possible risks of failure because instantaneous peak flows may be considerably larger than the daily averages. As there is often a lack of instantaneous flow data at a given site of interest, the peak flow has to be estimated. This paper develops new machine-learning-based methods to estimate the instantaneous peak flow from mean daily flow data where long daily data series exist but the instantaneous peak data series are short. However, the presented methods cannot be used where only daily flow data are available. Developed methodologies have been successfully applied to series of flow information from different gauging stations in Iran, with important improvements compared to traditional empirical methods available in the literature. Reliable results produced by the machine-learning-based models compared to the traditional methods show the superior ability of these techniques to solve the problem of inadequate measured peak flow data periods, especially in developing countries where it is difficult to find sufficiently long instantaneous peak flow data series.

Application of Artificial Neural Networks in Instantaneous Peak Flow Estimation for Kharestan Watershed, Iran

Abstract: Understanding the amount of instantaneous peak flow in watersheds is one of the most important factors that plays important role in planning and designing of projects related to water and river engineering. The purpose of this study is to compare the efficiency of artificial neural network and empirical methods for estimating instantaneous peak flow in Kharestan Watershed located northwest of Fars Province, Iran. For this purpose, 25 years of daily peak and instantaneous peak flow of Jamal Beig Hydrometrie Station was considered. Then the estimation was done based on empirical methods including Fuller, Sangal and Fill—Steiner and artificial neural network and were compared based on RMSE and R 2 . Results showed that estimation of artificial neural network is more accurate than empirical methods with RMSE = 13.710 and R2 = 0.942 which indicated the lower errors of artificial neural network method compared with empirical methods.

Hydrologic Footprint Residence: Environmentally Friendly Criteria for Best Management Practices

The natural hydrologic flow regime is altered by urbanization, which can be mitigated through best management practices (BMPs) or low impact development (LID). Typically, the effectiveness of different management scenarios is tested by comparing post- and predevelopment instantaneous peak flows. This approach, however, does not capture the extent of hydrologic change and the effect on downstream communities. A new hydrologic sustainability metric is presented here to quantify the impact of urbanization on downstream water bodies on the basis of the inundation dynamics of the flow regime. The hydrologic footprint residence (HFR) is designed to capture both temporal and spatial hydrological changes to an event-based flow regime by calculating the inundated areas and duration of a flood. The HFR is demonstrated for a hypothetical watershed and a watershed on the Texas A&M University Campus, located in College Station, Texas. For the campus watershed, three design storms (2-, 10-, and 100-year) and a set of historical events (during the period 1978–2009) are simulated for various management scenarios, representing predevelopment conditions, development on campus, BMP-based control, and LID-based control. The results indicate that the HFR can better capture alterations to the shape of the hydrograph compared with the use of the peak flow only.

Testing the relationship between instantaneous peak flow and mean daily flow in a Mediterranean Area Southeast Spain

Abstract Extreme hydrologic events have great importance in Southeastern Spain regarding the personal and economic damage they imply. The commonly-used design parameter for hydraulic structures is the maximum annual instantaneous stream flow recorded in conventional gauging stations. However, the majority of available data in Southeastern Spain is mean daily stream flows. This paper explores possible linear relationships between annual instantaneous peak discharge (IPF) and the corresponding (MDF) mean daily stream flow. This relationship was previously explored by other authors such as Fuller [Fuller, W.E., 1914. Flood flows. Trans. Am. Soc. Civ. Eng., 77: 564–617]. Non-linear responses of IPF–-MDF were observed in several study basins. The use of Principal Components Analysis (PCA) allowed characterizing the most important topographic and hydrological attributes of the basins and provided important information about variables that should be included in IPF–MDF regional equations. The key factor to justify the different IPF–MDF relationships in a relatively small area is the nature of the extreme events and their effects on semi-arid soil conditions. In addition, a regional equation to estimate IPF from MDF was developed. This equation was applied to a series of flow of nine stations of the Southeast Basin of Spain, and a significant improvement was achieved when applying this formula in comparison to the traditional method of Fuller. This study indicates possible restrictions to take into account when traditional hydrological model are applied in semi-arid areas.

Anatomy of an Extreme Event: The July 14–15, 2004 Peterborough Rainstorm

The July 14−15, 2004 rainstorm in Peterborough, Ontario, produced the largest 24 hour total rainfall depth (>220 mm) on record for southern Ontario. The storm was localized over the city for much of this period and rainfall depths and peak rainfall intensities dropped markedly with distance from the city. Peak intensity for 0.5 hour duration at the Trent Weather Station (TWS) in the north end of the city was 93 mm h−1, while peak intensity for one hour duration was 87 mm h−1. Even greater intensities may have occurred in other parts of the city. These intensities exceeded the corresponding 100−year return period values (81 and 53 mm h−1, respectively) estimated from the 1971 to 2002 record at the Peterborough Airport (PA) station, southwest of the city. Another critical characteristic of the July 14−15, 2004 storm was the distinctive shape of its intensity−duration−frequency curve relative to that for the PA. The TWS intensities for the July 14−15, 2004 storm showed a more protracted decline with increasing duration compared to the PA 100−year return period values. The storm produced the largest instantaneous peak flow on record for Jackson Creek, which flows through Peterborough's downtown area. Peak rainfall intensities exceeded the infiltration capacities of artificial surfaces as well as many nominally−pervious surfaces in Peterborough and the ensuing surface runoff contributed to widespread flooding in the city. These results strongly suggest that such storm properties, and their influence on surface runoff generation in urban areas, need to be considered when planning engineering structures such as storm sewer networks and storm water retention ponds in the Peterborough region.

The great Atacama flood of 2001 and its implications for Andean hydrology

AbstractIn February 2001, widespread flooding occurred throughout the Atacama Desert of northern Chile and southern Peru. It was particularly severe in the Río Loa basin, where roads and bridges were disrupted and the town of Calama inundated. The instantaneous peak flow in the Río Salado, a tributary of the Río Loa, reached 310 m3 s−1, an order of magnitude higher than any previously recorded event. The flood is estimated to have a return period of 100–200 years and is shown to have been caused by intense, long‐duration rainfall in the western Cordillera associated with La Niña. The surface water response is typical of arid areas and highly dependent on antecedent conditions, but is quite different in perennial and ephemeral catchments. Ephemeral flood flows suffer high transmission losses, recharging phreatic aquifers. Perennial rivers have lower runoff coefficients, but baseflow levels remained high after the event for several months due to bank storage rebound and interflow. Extremely high energies of ∼3000 W m−2 were generated by the floods in the Cordillera, becoming less in the Precordillera and downstream. Erosion and sediment transport were consequently highest in the upper and middle reaches of the rivers, with mixed erosion‐deposition in the lowest reach. The new insights gained from the interpretation and quantification of this event have important implications for palaeoenvironmental analysis, hazard management, water resource evaluation and the palaeohydrological evolution of the Andes. Copyright © 2005 John Wiley &amp; Sons, Ltd.

Estimating Instantaneous Peak Flow from Mean Daily Flow Data

Estimation of the design flood flow for hydraulic structures is often performed adjusting probabilistic models to daily mean flow series. This may cause an underdesign of the structure capacity with possible risks of failure, because instantaneous peak flows may be considerably larger than daily averages. Estimation of the instantaneous peak flows is often needed for simulation of the reservoir operation based on the hydraulic characteristics of the structures and the operation rules. Because there is often a lack of instantaneous flow data at a given site of interest, the peak flow has to be estimated. This paper develops a new method to estimate the instantaneous peak flow from mean daily flow data. This methodology was successfully applied to a series of flow information from gauging stations in Brazil, with important improvements compared to the traditional methods available in the literature.

Recommendations for evaluation of the severity of native valvular regurgitation with two-dimensional and doppler echocardiography

Recommendations for evaluation of the severity of native valvular regurgitation with two-dimensional and doppler echocardiography

Regional differences in the effects of El Niño and La Niña on low flows and floods

The response of monthly 7-day low flow, monthly instantaneous peak flow, and monthly frequency of flood events to El Niño and La Niña episodes is investigated for 18 rivers that represent a diverse range of climatic types throughout New Zealand. A significant positive or negative deviation from the long-term average was observed in over half the possible combinations of river, streamflow index, and type of ENSO episode; significant deviations were most frequent in the case of low flow, especially during La Niña episodes. Patterns of streamflow response differ widely between rivers, and the response of a given river to individual ENSO episodes is very variable. The patterns of streamflow response to ENSO are consistent to some extent with the climatic effects of ENSO already identified by meteorologists. Two core regions can be defined in which streamflow tends to respond in the same way. These are in the northeast of the North Island, and in the axial ranges of the South Island, where there are significant effects of ENSO on the frequency and duration of rain-bearing northeasterly and westerly winds respectively. The patterns of response strongly reflect topography, and the exposure of catchments to predominant air masses.

Modified Pipe Network Model for Incorporating Peak Demand Requirements

In some states the design of branched pipes in rural water systems must be carried out based on pressure drops calculated using expected instantaneous peak flows. These instantaneous peak flows are based on the number of users served by the pipe link, and field measurements have led to various tables of recommended values. Hydraulic calculations using instantaneous peak flows require a special approach. This approach, which can be incorporated into a pipe network hydraulic model, is described. An example illustrates the significant differences possible in a hydraulic analysis using a conventional approach based on a peak per-capita demand and a modified one based on satisfying instantaneous peak flow requirements.