Flood variability east of Australia’s Great Dividing Range

The variability of flow in river channels influences the spatial and temporal variability of many biophysical processes including the transport of sediment and waterborne pollutants and the recruitment of aquatic animals and plants. In this study, inter- and intra-basin patterns of flood variability are examined for catchments east of Australia’s Great Dividing Range. Three measures of flood variability are explored with uncertainty quantified using bootstrap resampling. The two preferred measures of flood variability (namely a flood quantile ratio and a power law scaling coefficient) produced similar results. Catchments in the wet tropics of far north Queensland experience low flood variability. Flood variability increased southwards through Queensland, reaching a maximum in the vicinity of the Fitzroy and Burnett River basins. The small near-coast catchments of southern Queensland and northern New Wales experience low flood variability. Flood variability is also high in the southern Hunter River and Hawkesbury–Nepean basins. Using L-moment ratio diagrams with data from 424 streamflow stations, we also conclude that the Generalised Pareto distribution is preferable for modelling flood frequency curves for this region. These results provide a regional perspective that can be used to develop new hypotheses about the effects of hydrologic variability on the biophysical characteristics of these Australian rivers.     

Spatio-temporal changes of hydrological processes and underlying driving forces in Guizhou region, Southwest China

Understanding the changes in streamflow and associated driving forces is crucial for formulating a sustainable regional water resources management strategy in the environmentally fragile karst area of the southwest China. This study investigates the spatio-temporal changes in streamflow of the Guizhou region and their linkage with meteorological influences using the Mann–Kendall trend analysis, singular-spectrum analysis (SSA), Lepage test, and flow duration curves (FDCs). The results demonstrate that: (1) the streamflow in the flood-season (June–August) during 1956–2000 increased significantly (confidence level ≥95%) in most catchments, closely consistent with the distinct increasing trend of annual rainfall over wet-seasons. The timings of abrupt change for streamflow in most catchments are found to occur at 1986; (2) streamflow in the Guizhou region experiences significant seasonal changes prior/posterior to 1986, and in most catchments the coefficient of variation of monthly streamflow increases; (3) spatial changes in streamflow indicate that monthly streamflow in the north-west decreases but increases in other parts; (4) the spatial high- and low-flow map (Q ₅ and Q ₉₅) reveals an increase in the extremely large streamflow in the five eastern catchments but a decrease in the extremely low streamflow in the four eastern catchments and three western catchments during 1987–2000. An increase in streamflow, particularly extreme flows, during the flood season would increase the risk of extreme flood events, while a decrease in streamflow in the dry season is not beneficial to vegetation restoration in this ecologically fragile region.     

Multifractal detrended fluctuation analysis of streamflow series of the Yangtze River basin,China

Scaling and multifractal properties of the hydrological processes of the Yangtze River basin were explored by using a multifractal detrended fluctuation analysis (MF‐DFA) technique. Long daily mean streamflow series from Cuntan, Yichang, Hankou and Datong stations were analyzed. Using shuffled streamflow series, the types of multifractality of streamflow series was also studied. The results indicate that the discharge series of the Yangtze River basin are non‐stationary. Different correlation properties were identified within streamflow series of the upper, the middle and the lower Yangtze River basin. The discharge series of the upper Yangtze River basin are characterized by short memory or anti‐persistence; while the streamflow series of the lower Yangtze River basin is characterized by long memory or persistence. h(q) vs q curves indicate multifractality of the hydrological processes of the Yangtze River basin. h(q) curves of shuffled streamflow series suggest that the multifractality of the streamflow series is mainly due to the correlation properties within the hydrological series. This study may be of practical and scientific importance in regional flood frequency analysis and water resource management in different parts of the Yangtze River basin. Copyright © 2008 John Wiley & Sons, Ltd.     

Attenuation in Southeastern Sicily (Italy) by applying different coda methods

The attenuation in Southeastern Sicily has been investigated using 40aftershocks of the December 13 1990, earthquake. The quality factor ofcoda waves (Q_c) was estimated in the frequency range 1.5–24 Hz,applying three different methods in time and frequency domains. On thewhole, a clear dependence of Q_c on frequency was observed,according to the general law Q = Q₀(f/f₀)ⁿ . Thefrequency dependence relationships obtained from the analysis of codawaves at three lapse time windows (10, 20 and 30 seconds) show that, forall methods, Q₀ (Q_c at 1 Hz) significantly increases with lapsetime. In particular, Q₀ is approximately 20 at short lapse time (10s) and increases to about 70 at longer lapse time (30 s). This is attributedto the fact that larger lapse times involve deeper parts of the crust andupper lithosphere which may be characterized by larger quality factors.Moreover, the value of the exponent n decreases with increasing codalengths from about 1.3 to 0.9, suggesting a decrease in heterogeneity ofthe medium with depth.Finally, Q_c-values here found are of the same order as thosereported from other tectonic regions like the Anatolian Highlands orSouthern Spain, while significantly higher than in the neighboring volcanicarea of Mt. Etna.     

Hydraulic bridges in unsaturated coarse granular media: Influence of bridge size and conductivity on flow through clasts

Unsaturated flow in coarse granular media must pass through hydraulic bridges (e.g., pendular water, porous connections) that form a physical connection between adjoining clasts. Previous studies suggest that volumetric flow through a porous clast (Q) will be linearly dependent on the cross-sectional area of the hydraulic bridges, and understate the importance of bridge conductivity. Numerical simulations were performed to explore steady-state flow through a spherical clast with identical bridges located at the top and bottom. The cross-sectional area of the bridges relative to that of the clast (A_r) was varied across six orders of magnitude. The ratio of hydraulic conductivity between bridges and clasts (K_b/K_c) was varied across 12 orders of magnitude to consider resistive, neutral, and conductive bridges. Results show that hydraulic bridges place a primary control on both Q and flux distribution within the clast. For neutral and conductive bridges (K_b/K_c ≥1), A_r is the dominant factor in determining Q, while K_b/K_c is the primary control for resistive bridges (K_b/K_c < 1). For all bridges, Q shows a non-linear dependency on both A_r and K_b/K_c. The intra-clast flow distribution shifts outwards as A_r increases. Conductive bridges promote this process and resistive bridges impede it.     

Scaling and regionalization of flood flows in British Columbia,Canada

A regionalization of flood data in British Columbia reveals a common scaling with drainage area over the range 0·5×10²<A_d<10⁴ km². This scaling is not a function of flood return period, which implies that simple scaling—consistent with a snowmelt‐dominated flow regime—applies to the province. The observed scale relation takes the form , similar to values reported in previous studies. The scaling relation identified was used to define the regional pattern of hydroclimatic variability for flood flows in British Columbia after discounting the effect of drainage area. The pattern was determined by kriging a scale‐independent runoff factor k for the mean annual flood, 5 year flood and 20 year flood. The analysis permits quantification of uncertainty of the estimates, which can be used in conjunction with the mapped k‐fields to calculate a mean and range for floods with the identified return period for ungauged basins. Owing to the sparsity of data, the precision is relatively poor. The standard error is generally less than 75% of the estimate in the southern half of the province, whereas in the northern half it is often between 75 and 100%. Examination of the relative increase in flood magnitude with increasing return period reveals spatially consistent but statistically insignificant differences. Flood magnitude tends to increase more rapidly in the western regions, where rain events may contribute to flood generation. The relative increase in flood magnitude with return period is consistently lower in the eastern mountain ranges, where snowmelt dominates the flood flow regime. Copyright © 2002 John Wiley & Sons, Ltd.     

Regional coda Q in Costa Rica, Central America

Regional seismic apparent attenuation was estimated for Costa Rica, Central America, by using a time domain single scattering model of the shear wave coda decay of local earthquakes. The sensitivity of coda Q (Q_c) measurements with respect to geological differences in the crust is demonstrated in eight sub-regions with a large variety of tectonic and geologic properties. The Q_c estimations were performed for 96 selected local earthquakes recorded at 13 sites during a period of three months. In order to model the scattering as a weak process and to avoid short distance nonlinear effects, we made use of the S-wave coda data only from events within a hypocentral distance of 12 to 106 km with a lapse time between 9 and 53 s. Seismograms were also divided into groups with three different focal depths d, namely d<21 km, 21 kmc values are frequency dependent in the range 1–9 Hz, and are approximated by a least-squares fit to the power law Q_c(f) = Q₀(f/f₀)ⁿ. The estimated parameters of the power-law dependence of Q_c for the whole region, including all depths and possible wave paths, are Q₀ = 91 (± 8.4) and n = 0.72 (±0.071). Differences in the parameter of Q_c for different depths intervals are small, ranging from Q₀ = 90 (±0.7) and n = 0.70 (±0.006) for the uppermost group, with focal depths less than 21 km, to Q₀ = 97 (±0.7) and n = 0.79 (±0.005) for the deepest group with focal depths larger than 43 km. The regional differences in Q_c for the eight sub-regions are significantly larger when compared with the differences between the three focal depth groups. An attempt is made to interpret the variation of Q_c in terms of spatial variations in the geologic and tectonic properties of the crust. Other authors have found that the frequency exponent n might be larger in active tectonic areas and smaller in more stable regions. In the northern region of the Pacific coast we obtain a value of n = 0.52 (±0.011), which might indicate a lower level of tectonic activity when compared with n = 0.85 (±0.015) and 0.83 (±0.031), respectively, for the central and southern sub-regions along the Pacific coast. The latter two sub-regions are located closer to the active area near the Cocos ridge. We obtain the frequency exponent n = 0.72 (±0.052) along a major shear zone in central Costa Rica characterized by high volcanic activity and large geologic complexity. Values of n along the Panamean border are 0.62 (±0.029) in the north and 0.86 (±0.009) and 0.83 (±0.031) in two regions adjacent to the subduction zone and the Cocos Ridge, respectively.     

Flood frequency under the influence of trends in the Pearl River basin,China: changing patterns,causes and implications

Using a nonstationary flood frequency model, this study investigates the impact of trends on the estimation of flood frequencies and flood magnification factors. Analysis of annual peak streamflow data from 28 hydrological stations across the Pearl River basin, China, shows that: (1) northeast parts of the West and the North River basins are dominated by increasing annual peak streamflow, whereas decreasing trends of annual peak streamflow are prevailing in other regions of the Pearl River basin; (2) trends significantly impact the estimation of flood frequencies. The changing frequency of the same flood magnitude is related to the changing magnitude or significance/insignificance of trends, larger increasing frequency can be detected for stations with significant increasing trends of annual peak streamflow and vice versa, and smaller increasing magnitude for stations with not significant increasing annual peak streamflow, pointing to the critical impact of trends on estimation of flood frequencies; (3) larger‐than‐1 flood magnification factors are observed mainly in the northeast parts of the West River basin and in the North River basin, implying magnifying flood processes in these regions and a higher flood risk in comparison with design flood‐control standards; and (4) changes in hydrological extremes result from the integrated influence of human activities and climate change. Generally, magnifying flood regimes in the northeast Pearl River basin and in the North River basin are mainly the result of intensifying precipitation regime; smaller‐than‐1 flood magnification factors along the mainstream of the West River basin and also in the East River basin are the result of hydrological regulations of water reservoirs. Copyright © 2014 John Wiley & Sons, Ltd.     

Bedrock geology controls on catchment storage,mixing, and release: A comparative analysis of 16 nested catchments

The bedrock controls on catchment mixing, storage, and release have been actively studied in recent years. However, it has been difficult to find neighbouring catchments with sufficiently different and clean expressions of geology to do comparative analysis. Here, we present new data for 16 nested catchments (0.45 to 410 km²) in the Alzette River basin (Luxembourg) that span a range of clean and mixed expressions of schists, phyllites, sandstones, and quartzites to quantify the relationships between bedrock permeability and metrics of water storage and release. We examined 9 years' worth of precipitation and discharge data, and 6 years of fortnightly stable isotope data in streamflow, to explore how bedrock permeability controls (a) streamflow regime metrics, (b) catchment storage, and (c) isotope response and catchment mean transit time (MTT). We used annual and winter precipitation–run‐off ratios, as well as average summer and winter precipitation–run‐off ratios to characterise the streamflow regime in our 16 study catchments. Catchment storage was then used as a metric for catchment comparison. Water mixing potential of 11 catchments was quantified via the standard deviation in streamflow δD (σδD) and the amplitude ratio (A_S/A_P) of annual cycles of δ¹⁸O in streamflow and precipitation. Catchment MTT values were estimated via both stable isotope signature damping and hydraulic turnover calculations. In our 16 nested catchments, the variance in ratios of summer versus winter average run‐off was best explained by bedrock permeability. Whereas active storage (defined here as a measure of the observed maximum interannual variability in catchment storage) ranged from 107 to 373 mm, total catchment storage (defined as the maximum catchment storage connected to the stream network) extended up to ~1700 mm (±200 mm). Catchment bedrock permeability was strongly correlated with mixing proxies of σδD in streamflow and δ¹⁸O A_S/A_P ratios. Catchment MTT values ranged from 0.5 to 2 years, based on stable isotope signature damping, and from 0.5 to 10 years, based on hydraulic turnover.     

Watershed modelling of hydrology and water quality in the Sacramento River watershed,California

Agricultural pollutant runoff is a major source of water contamination in California's Sacramento River watershed where 8500 km² of agricultural land influences water quality. The Soil and Water Assessment Tool (SWAT) hydrology, sediment, nitrate and pesticide transport components were assessed for the Sacramento River watershed. To represent flood conveyance in the area, the model was improved by implementing a flood routing algorithm. Sensitivity/uncertainty analyses and multi‐objective calibration were incorporated into the model application for predicting streamflow, sediment, nitrate and pesticides (chlorpyrifos and diazinon) at multiple watershed sites from 1992 to 2008. Most of the observed data were within the 95% uncertainty interval, indicating that the SWAT simulations were capturing the uncertainties that existed, such as model simplification, observed data errors and lack of agricultural management data. The monthly Nash–Sutcliffe coefficients at the watershed outlet ranged from 0.48 to 0.82, indicating that the model was able to successfully predict streamflow and agricultural pollutant transport after calibration. Predicted sediment loads were highly correlated to streamflow, whereas nitrate, chlorpyrifos and diazinon were moderately correlated to streamflow. This indicates that timing of agricultural management operations plays a role in agricultural pollutant runoff. Best management practices, such as pesticide use limits during wet seasons, could improve water quality in the Sacramento River watershed. The calibrated model establishes a modelling framework for further studies of hydrology, water quality and ecosystem protection in the study area. Copyright © 2012 John Wiley & Sons, Ltd.     

A regional Bayesian POT model for flood frequency analysis

Flood frequency analysis is usually based on the fitting of an extreme value distribution to the local streamflow series. However, when the local data series is short, frequency analysis results become unreliable. Regional frequency analysis is a convenient way to reduce the estimation uncertainty. In this work, we propose a regional Bayesian model for short record length sites. This model is less restrictive than the index flood model while preserving the formalism of “homogeneous regions”. The performance of the proposed model is assessed on a set of gauging stations in France. The accuracy of quantile estimates as a function of the degree of homogeneity of the pooling group is also analysed. The results indicate that the regional Bayesian model outperforms the index flood model and local estimators. Furthermore, it seems that working with relatively large and homogeneous regions may lead to more accurate results than working with smaller and highly homogeneous regions.     

Application of a multi‐temporal,LiDAR‐derived,digital terrain model in a landslide‐volume estimation

Sediments produced by landslides are crucial in the sediment yield of a catchment, debris flow forecasting, and related hazard assessment. On a regional scale, however, it is difficult and time consuming to measure the volumes of such sediment. This paper uses a LiDAR‐derived digital terrain model (DTM) taken in 2005 and 2010 (at 2 m resolution) to accurately obtain landslide‐induced sediment volumes that resulted from a single catastrophic typhoon event in a heavily forested mountainous area of Taiwan. The landslides induced by Typhoon Morakot are mapped by comparison of 25 cm resolution aerial photographs taken before and after the typhoon in an 83.6 km² study area. Each landslide volume is calculated by subtraction of the 2005 DTM from the 2010 DTM, and the scaling relationship between landslide area and its volume are further regressed. The relationship between volume and area are also determined for all the disturbed areas (V_L = 0.452A_L^1.242) and for the crown areas of the landslides (V_L = 2.510A_L^1.206). The uncertainty in estimated volume caused by use of the LiDAR DTMs is discussed, and the error in absolute volume estimation for landslides with an area >10⁵ m² is within 20%. The volume–area relationship obtained in this study is also validated in 11 small to medium‐sized catchments located outside the study area, and there is good agreement between the calculation from DTMs and the regression formula. By comparison of debris volumes estimated in this study with previous work, it is found that a wider volume variation exists that is directly proportional to the landslide area, especially under a higher scaling exponent. Copyright © 2013 John Wiley & Sons, Ltd.     

Simple scaling properties of Canadian annual average streamflow

The spatial scaling properties of Canadian annual average streamflow (abbreviated as AASF) are assessed using both the product moments (PMs) and the probability weighted moments (PWMs) of AASF across the entire country and in its sub-climatic regions. By the PMs, the log relationship between the kth moments of AASF and the drainage area can be almost represented by a perfect straight line across the entire country and in its sub-climatic regions, whose regression parameters are a linear function of the moment order. By the PWMs, the logarithm of the kth PWM is a linear function of the logarithm of drainage area for the entire country and its sub-climatic regions, where its slope (or scale exponent) in a region is constant and is independent of the order. These results indicate that Canadian AASF exhibits simple scaling and drainage area alone may describe most of the variability in the moments of AASF. The third approach, based on the log linearity between quantiles and drainage area, is applied to Region 2, also demonstrate simple scaling of AASF in that region, as concluded from using PMs and PWMs methods, which indicates that all three methods are consistent. The simple scaling results provide a basis for using the index flood method to conduct regional frequency analysis of AASF in Canada.     

Estimating minimum streamflow from measurements at ungauged sites in regions with streamflow‐gauging networks

Estimation of low flows in rivers continues to be a vexing problem despite advances in statistical and process‐based hydrological models. We develop a method to estimate minimum streamflow at seasonal to annual timescales from measured streamflow based on regional similarity in the deviations of daily streamflow from minimum streamflow for a period of interest. The method is applied to 1,019 gauged sites in the Western United States for June to December 2015. The gauges were clustered into six regions with distinct timing and magnitude of low flows. A gamma distribution was fit each day to the deviations in specific discharge (daily streamflow divided by drainage area) from minimum specific discharge for gauges in each region. The Kolmogorov–Smirnov test identified days when the gamma distribution was adequate to represent the distribution of deviations in a region. The performance of the gamma distribution was evaluated at gauges by comparing daily estimates of minimum streamflow with estimates from area‐based regression relations for minimum streamflow. Each region had at least 8 days during the period when streamflow measurements would provide better estimates than the regional regression equation, but the number of such days varied by region depending on aridity and homogeneity of streamflow within the region. Synoptic streamflow measurements at ungauged sites have value for estimating minimum streamflow and improving the spatial resolution of hydrological model in regions with streamflow‐gauging networks.     

Hydrologic response to valley‐scale structure in alpine headwaters

Few systematic studies of valley‐scale geomorphic drivers of streamflow regimes in complex alpine headwaters have compared response between catchments. As a result, little guidance is available for regional‐scale hydrological research and monitoring efforts that include assessments of ecosystem function. Physical parameters such as slope, elevation range, drainage area and bedrock geology are often used to stratify differences in streamflow response between sampling sites within an ecoregion. However, these metrics do not take into account geomorphic controls on streamflow specific to glaciated mountain headwaters. The coarse‐grained nature of depositional features in alpine catchments suggests that these landforms have little water storage capacity because hillslope runoff moves rapidly just beneath the rock mantle before emerging in fluvial networks. However, recent studies show that a range of depositional features, including talus slopes, protalus ramparts and ‘rock‐ice’ features may have more storage capacity than previously thought. To better evaluate potential differences in streamflow response among basins with extensive coarse depositional features and those without, we examined the relationships between streamflow discharge, stable isotopes, water temperature and the amplitude of the diurnal signal at five basin outlets. We also quantified the percentages of colluvial channel length measured along the stepped longitudinal profile. Colluvial channels, characterized by the presence of surficial, coarse‐grained depositional features, presented sediment‐rich, transport‐limited morphologies that appeared to have a cumulative effect on the timing and volume of flow downstream. Measurements taken from colluvial channels flowing through depositional landforms showed median recession constants (K_r) of 0.9–0.95, δ¹⁸O values of ≥?14.5 and summer diurnal amplitudes ≤0.8 as compared with more typical surface water recession constant values of 0.7, δ¹⁸O ≤ ?13.5 and diurnal amplitudes >2.0. Our results demonstrated strong associations between the percentage of colluvial channel length within a catchment and moderated streamflow regimes, water temperatures, diurnal signals and depleted δ¹⁸O related to groundwater influx. Copyright © 2014 John Wiley & Sons, Ltd.     

Addressing uncertainty in reflectivity‐rainfall relations in mountain watersheds during summer convection

The use of precipitation estimates from weather radar reflectivity has become widespread in hydrologic predictions. However, uncertainty remains in the use of the nonlinear reflectivity–rainfall (Z‐R) relation, in particular for mountainous regions where ground validation stations are often lacking, land surface data sets are inaccurate and the spatial variability in many features is high. In this study, we assess the propagation of rainfall errors introduced by different Z‐R relations on distributed hydrologic model performance for four mountain basins in the Colorado Front Range. To do so, we compare spatially integrated and distributed rainfall and runoff metrics at seasonal and event time scales during the warm season when convective storms dominate. Results reveal that the basin simulations are quite sensitive to the uncertainties introduced by the Z‐R relation in terms of streamflow, runoff mechanisms and the water balance components. The propagation of rainfall errors into basin responses follows power law relationships that link streamflow uncertainty to the precipitation errors and streamflow magnitude. Overall, different Z‐R relations preserve the spatial distribution of rainfall relative to a reference case, but not the precipitation magnitude, thus leading to large changes in streamflow amounts and runoff spatial patterns at seasonal and event scales. Furthermore, streamflow errors from the Z‐R relation follow a typical pattern that varies with catchment scale where higher uncertainties exist for intermediate‐sized basins. The relatively high error values introduced by two operational Z‐R relations (WSR‐57 and NEXRAD) in terms of the streamflow response indicate that site‐specific Z‐R relations are desirable in the complex terrain region, particularly in light of other uncertainties in the modelling process, such as model parameter values and initial conditions. Copyright © 2012 John Wiley & Sons, Ltd.     

Thresholds in the storm response of a lake chain system and the occurrence and magnitude of lake overflows: Implications for flood frequency

The aim of this paper is to illustrate the effects of spatial organization of lake chains and associated storage thresholds upon lake-overflow behaviour, and specifically their impact upon large scale flow connectivity and the flood frequency of lake overflows. The analysis was carried out with the use of a multiple bucket model of the lake chain system, consisting of a network of both lakes and associated catchment areas, which explicitly incorporated within it three storage thresholds: a catchment field capacity threshold that governs catchment subsurface stormflow, a total storage capacity threshold that governs catchment surface runoff, and a lake storage capacity threshold that determines lake overflow. The model is driven by rainfall inputs generated by a stochastic rainfall model that is able to capture rainfall variability at a wide range of time scales. The study is used to gain insights into the process controls of lake-overflow generation, and in particular, to explore the crucial role of factors relating to lake organization, such as the average catchment area to lake area (A_C/A_L) ratio and the distribution of A_C/A_L with distance in the downstream direction (increasing or decreasing). The study showed that the average A_C/A_L value was the most important factor determining the frequency of occurrence and magnitude of floods from a landscape consisting of lake chains. The larger the average A_C/A_L value the more runoff is generated from catchments thus increasing both the occurrence and magnitude of lake overflows. In this case the flood frequency curve reflects that of the catchment area, and lake organization does not play an important role. When A_C/A_L is small the landscape is lake dominated, the spatial organization of lakes has a significant impact on lake connectivity, and consequently on flood frequency. One of the aspects of lake organization that may have a significant influence on lake connectivity is the spatial distribution of A_C/A_L from upstream to downstream (increasing or decreasing). In a landscape in which A_C/A_L increases downstream, lake overflow will occur more frequently relative to a similar landscape (i.e. identical A_C/A_L) with a constant value of A_C/A_L. When A_C/A_L decreases downstream, however, runoff inputs from the upstream parts will trigger lake overflow in the downstream parts, and consequently, full connectivity may be achieved leading to increased flood frequencies.     

Artificial intelligence for identifying hydrologically homogeneous regions: A state‐of‐the‐art regional flood frequency analysis

Due to the severity related to extreme flood events, recent efforts have focused on the development of reliable methods for design flood estimation. Historical streamflow series correspond to the most reliable information source for such estimation; however, they have temporal and spatial limitations that may be minimized by means of regional flood frequency analysis (RFFA). Several studies have emphasized that the identification of hydrologically homogeneous regions is the most important and challenging step in an RFFA. This study aims to identify state‐of‐the‐art clustering techniques (e.g., K ‐means, partition around medoids, fuzzy C‐means, K ‐harmonic means, and genetic K ‐means) with potential to form hydrologically homogeneous regions for flood regionalization in Southern Brazil. The applicability of some probability density function, such as generalized extreme value, generalized logistic, generalized normal, and Pearson type 3, was evaluated based on the regions formed. Among all the 15 possible combinations of the aforementioned clustering techniques and the Euclidian, Mahalanobis, and Manhattan distance measures, the five best were selected. Several watersheds' physiographic and climatological attributes were chosen to derive multiple regression equations for all the combinations. The accuracy of the equations was quantified with respect to adjusted coefficient of determination, root mean square error, and Nash–Sutcliffe coefficient, whereas, a cross‐validation procedure was applied to check their reliability. It was concluded that reliable results were obtained when using robust clustering techniques based on fuzzy logic (e.g., K ‐harmonic means), which have not been commonly used in RFFA. Furthermore, the probability density functions were capable of representing the regional annual maximum streamflows. Drainage area, main river length, and mean altitude of the watershed were the most recurrent attributes for modelling of mean annual maximum streamflow. Finally, an integration of all the five best combinations stands out as a robust, reliable, and simple tool for estimation of design floods.