Nonparametric catchment clustering using the data depth function

ABSTRACT

The clustering of catchments is important for prediction in ungauged basins, model parameterization and watershed development and management. The aim of this study is to explore a new measure of similarity among catchments, using a data depth function and comparing it with catchment clustering indices based on flow and physical characteristics. A cluster analysis was performed for each similarity measure using the affinity propagation clustering algorithm. We evaluated the similarity measure based on depth–depth plots (DD-plots) as a basis for transferring parameter sets of a hydrological model between catchments. A case study was developed with 21 catchments in a diverse New Zealand region. Results show that clustering based on the depth–depth measure is dissimilar to clustering on catchment characteristics, flow, or flow indices. A hydrological model was calibrated for the 21 catchments and the transferability of model parameters among similar catchments was tested within and between clusters defined by each clustering method. The mean model performance for parameters transferred within a group always outperformed those from outside the group. The DD-plot based method was found to produce the best in-group performance and second-highest difference between in-group and out-group performance.

EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR A. Viglione     

Spatial patterns of homogeneous pooling groups for flood frequency analysis

Abstract

Several methods for the exploration and modelling of spatial point patterns are introduced to study the spatial patterns of homogeneous pooling groups for flood frequency analysis. The study is based on selected catchments in Great Britain, where a high density of gauging stations has been established. Initial pooling groups are formed using the K-means clustering algorithm with appropriately selected similarity measures. The pooling groups are subsequently revised to improve the homogeneity in the hydrological response. Spatial patterns of the initial and final pooling groups are explored in terms of intensity and dependence of the spatial distribution of the catchments. A test against a spatial point process is used to confirm or reject the initial impression of spatial clustering. Changes in the spatial patterns from the initial to the final pooling groups are examined using two comparison methods. The spatial pattern analysis described above can be used to answer the following questions: whether homogeneous catchments tend to exist in the vicinity of each other; whether the improvement in homogeneity tends to form more clustered pooling groups; and how the spatial patterns observed can be used to direct the selection of pooling variables.     

Flood frequency analysis using historical data: accounting for random and systematic errors

Abstract

Flood frequency analysis based on a set of systematic data and a set of historical floods is applied to several Mediterranean catchments. After identification and collection of data on historical floods, several hydraulic models were constructed to account for geomorphological changes. Recent and historical rating curves were constructed and applied to reconstruct flood discharge series, together with their uncertainty. This uncertainty stems from two types of error: (a) random errors related to the water-level readings; and (b) systematic errors related to over- or under-estimation of the rating curve. A Bayesian frequency analysis is performed to take both sources of uncertainty into account. It is shown that the uncertainty affecting discharges should be carefully evaluated and taken into account in the flood frequency analysis, as it can increase the quantiles confidence interval. The quantiles are found to be consistent with those obtained with empirical methods, for two out of four of the catchments.

Citation Neppel, L., Renard, B., Lang, M., Ayral, P.-A., Coeur, D., Gaume, E., Jacob, N., Payrastre, O., Pobanz, K. & Vinet, F. (2010) Flood frequency analysis using historical data: accounting for random and systematic errors. Hydrol. Sci. J. 55(2), 192–208.     

Hydrological response characteristics of Mediterranean catchments at different time scales: a meta-analysis

ABSTRACT

This work examines 140 hydrological studies conducted in the Mediterranean region. It identifies key characteristics of the hydrological responses of Mediterranean catchments at various time scales and compares different methods and modelling approaches used for individual-catchment studies. The study area is divided into the northwestern (NWM), eastern (EM) and southern (SM) Mediterranean. The analysis indicates regional discrepancies in which the NWM shows the most extreme rainfall regime. A tendency for reduced water resources driven by both anthropogenic and climatic pressures and a more extreme rainfall regime are also noticeable. Catchments show very heterogeneous responses over time and space, resulting in limitations in hydrological modelling and large uncertainties in predictions. However, few models have been developed to address these issues. Additional studies are necessary to improve the knowledge of Mediterranean hydrological features and to account for regional specificities.

Editor D. Koutsoyiannis Associate editor A. Efstratiadis     

Bias compensation in flood frequency analysis

Abstract

Flood frequency analysis (FFA) is essential for water resources management. Long flow records improve the precision of estimated quantiles; however, in some cases, sample size in one location is not sufficient to achieve a reliable estimate of the statistical parameters and thus, regional FFA is commonly used to decrease the uncertainty in the prediction. In this paper, the bias of several commonly used parameter estimators, including L-moment, probability weighted moment and maximum likelihood estimation, applied to the general extreme value (GEV) distribution is evaluated using a Monte Carlo simulation. Two bias compensation approaches: compensation based on the shape parameter, and compensation using three GEV parameters, are proposed based on the analysis and the models are then applied to streamflow records in southern Alberta. Compensation efficiency varies among estimators and between compensation approaches. The results overall suggest that compensation of the bias due to the estimator and short sample size would significantly improve the accuracy of the quantile estimation. In addition, at-site FFA is able to provide reliable estimation based on short data, when accounting for the bias in the estimator appropriately.

Editor D. Koutsoyiannis; Associate editor Sheng Yue     

The impact of seasonal flood peak dependence on annual maxima design quantiles

If the maximum annual peak flow series are a mixture of summer and winter flows, a seasonal approach to flood frequency analysis is necessary. While considering seasonal maxima as mutually independent events, the annual maxima distribution is defined as the product of seasonal distributions. However, if the independency assumption does not hold, a bivariate approach with dependent margins should be applied, i.e. the copula approach. The impact of dependency on design quantiles is investigated here in the context of the Fréchet-Hoeffding inequality defining copula bounds and the definition of dependency. The results of the two approaches are compared using six catchments in the San River basin, where in four cases the dependency of seasonal maxima has been identified as positive significant and no strong dominance of any one season is observed. The product model leads to higher estimates of design quantiles than do models where the dependency is taken into account and, therefore, is safe.

EDITOR R. Woods ASSOCIATE EDITOR A. Fiori     

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

The 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.     

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.     

Characterizing and understanding the variability of streamflow drought indicators within the USA

ABSTRACT

Low streamflow conditions can have adverse consequences for society and river ecology. The variability and drivers of streamflow drought indicators within the USA were investigated using observed streamflow records from 603 gauges across the USA. The analysis was based on two main approaches: (i) low-flow magnitude indicators, and (ii) streamflow deficit indicators. First, we examined how streamflow drought indicators vary spatially across the USA. Second, we used a data-driven clustering method to identify spatial clusters for each indicator. Finally, we assessed the association with regional climate drivers. The results show that the spatial variability of low-flow magnitude indicators is significantly different from the deficit indicators. Further, our clustering approach identifies regions of spatial homogeneity, which can be linked to the extreme regional climate drivers and land–atmosphere interactions. The influence of regional climate on streamflow drought indicators varies more between clusters than between indicators.     

Basin-scale analysis of rainfall and runoff in Peru (1969–2004): Pacific,Titicaca and Amazonas drainages

Abstract

We present a procedure for estimating Q95 low flows in both gauged and ungauged catchments where Q95 is the flow that is exceeded 95% of the time. For each step of the estimation procedure, a number of alternative methods was tested on the Austrian data set by leave-one-out cross-validation, and the method that performed best was used in the final procedure. To maximise the accuracy of the estimates, we combined relevant sources of information including long streamflow records, short streamflow records, and catchment characteristics, according to data availability. Rather than deriving a single low flow estimate for each catchment, we estimated lower and upper confidence limits to allow local information to be incorporated in a practical application of the procedure. The components of the procedure consist of temporal (climate) adjustments for short records; grouping catchments into eight seasonality-based regions; regional regressions of low flows with catchment characteristics; spatial adjustments for exploiting local streamflow data; and uncertainty assessment. The results are maps of lower and upper confidence limits of low flow discharges for 21 000 sub-catchments in Austria.     

An integrated approach to the estimation of streamflow drought quantiles / Une méthode intégrée d’estimation des quantiles de sécheresse hydrologique

Abstract

Abstract An approach was developed for combining streamflow drought information from synthetic (generated) data with data reconstructed based on palaeoclimatic information (tree ring widths). The tree ring data were used to reconstruct streamflow in periods when no streamflow data were collected. The reconstructed data were then used as a source of historical data for estimating drought severity quantiles. The generated data were obtained using a nearest neighbour resampling method while the tree ring reconstruction was accomplished using a regression model. The application of the approach was to data from the Athabasca River in Alberta, Canada. The results demonstrate the feasibility and the utility of the approach for obtaining more accurate and precise estimates of extreme drought severity quantiles.     

Regional frequency analysis of rainfall extremes in Southern Malawi using the index rainfall and L-moments approaches

Rainfall extremes often result in the occurrence of flood events with associated loss of life and infrastructure in Malawi. However, an understanding of the frequency of occurrence of such extreme events either for design or disaster planning purposes is often limited by data availability at the desired temporal and spatial scales. Regionalisation, which involves “trading time for space” by pooling together observations for stations with similar behavior, is an alternative approach for more accurate determination of extreme events even at ungauged areas or sites with short records. In this study, regional frequency analysis of rainfall extremes in Southern Malawi, large parts of which are flood prone, was undertaken. Observed 1-, 3-, 5- and 7-day annual maximum rainfall series for the period 1978–2007 at 23 selected rainfall stations in Southern Malawi were analysed. Cluster analysis using scaled at-site characteristics was used to determine homogeneous rainfall regions. L-moments were applied to derive regional index rainfall quantiles. The procedure also validated the three rainfall regions identified through homogeneity and heterogeneity tests based on Monte Carlo simulations with regional average L-moment ratios fitted to the Kappa distribution. Based on assessments of the accuracy of the derived index rainfall quantiles, it was concluded that the performance of this regional approach was satisfactory when validated for sites not included in the sample data. The study provides an estimate of the regional characteristics of rainfall extremes that can be useful in among others flood mitigation and engineering design.     

Sediment yield variability in central Tunisia: a quantitative analysis of its controlling factors

Abstract

This paper refers to the quantification and prediction of the sedimentation rate of 26 hillside-dam reservoirs in Central Tunisia. The objectives of the study are to develop a simple and practical methodology to identify controlling factors of sedimentation, and to propose a regionalization from the study sites. Principal component analysis (PCA) and complementary multi-dimensional statistical methods are used to relate highly variable area-specific sediment yield to hydro-morphometric, lithological, geomorphological and anthropogenic characteristics of catchments. It appears that catchment area is not the main controlling factor of sedimentation in the studied area. The overall slope index, drainage network characteristics and runoff parameters are also important in characterizing sediment yield. Applied to the annual sedimentation rate series, PCA resulted in retaining the first three principal axes, explaining 65% of the total variance. Statistical methods showed that the overall slope index, the total drainage length, the compacity index and the runoff parameters are as important for the sedimentation quantification. This allowed a graphical clustering of the study zone into three distinct groups having similar behaviours: (i) watersheds characterized by high sediment transport rates and high runoff coefficients, (ii) basins distinguished by relatively low values of both flow discharge and sediment transport rates, and (iii) watersheds with an intermediate sediment yield, especially characterized by relatively high relief. In a second step, a multiple regression model including the four characteristic catchment properties was developed, presenting a valuable tool to predict area-specific sediment yield from catchments in central Tunisia. This model shows reasonable efficiency with an absolute prediction error of 81%.

Citation Ayadi, I., Abida, H., Djebbar, Y. & Mahjoub, M. R. (2010) Sediment yield variability in central Tunisia: a quantitative analysis of its controlling factors. Hydrol. Sci. J. 55(3), 446–458.     

Application of L‐moments and Bayesian inference for low‐flow regionalization in Sefidroud basin,Iran

Reliable estimation of low flows at ungauged catchments is one of the major challenges in water‐resources planning and management. This study aims at providing at‐site and ungauged sites low‐flow frequency analysis using regionalization approach. A two‐stage delineating homogeneous region is proposed in this study. Clustering sites with similar low‐flow L‐moment ratios is initially conducted, and L‐moment‐based discordancy and heterogeneity measures are then used to detect unusual sites. Based on the goodness‐of‐fit test statistic, the best‐fit regional model is identified in each hydrologically homogeneous region. The relationship between mean annual 7‐day minimum flow and hydro‐geomorphic characteristics is also constructed in each homogeneous region associated with the derived regional model for estimating various low‐flow quantiles at ungauged sites. Uncertainty analysis of model parameters and low‐flow estimations is carried out using the Bayesian inference. Applied in Sefidroud basin located in northwestern Iran, two hydrologically homogeneous regions are identified, i.e. the east and west regions. The best‐fit regional model for the east and west regions are generalized logistic and Pearson type III distributions, respectively. The results show that the proposed approach provides reasonably good accuracy for at‐site as well as ungauged‐site frequency analysis. Besides, interval estimations for model parameters and low flows provide uncertainty information, and the results indicate that Bayesian confidence intervals are significantly reduced when comparing with the outcomes of conventional t‐distribution method. Copyright © 2013 John Wiley & Sons, Ltd.     

INTERNATIONAL HYDROLOGICAL DECADE / WORKING GROUP ON “THE INFLUENCE OF MAN ON THE HYDROLOGICAL CYCLE”

Abstract

Floods, as extreme hydrological phenomena, can be described by more than one correlated characteristic, such as peak, volume and duration. These characteristics should be jointly considered since they are generally not independent. For an ungauged site, univariate regional flood frequency analysis (FA) provides a limited assessment of flood events. A recent study proposed a procedure for regional FA in a multivariate framework. This procedure represents a multivariate version of the index-flood model and is based on copulas and multivariate quantiles. The performance of the proposed procedure was evaluated by simulation. However, the model was not tested on a real-world case study data. In the present paper, practical aspects are investigated jointly for flood peak (Q) and volume (V) of a dataset from the Côte-Nord region in the province of Quebec, Canada. The application of the proposed procedure requires the identification of the appropriate marginal distribution, the estimation of the index flood and the selection of an appropriate copula. The results of the case study show that the regional bivariate FA procedure performed well. This performance depends strongly on the performance of the two univariate models and, more specifically, the univariate model of Q. The results show also the impact of the homogeneity of the region on the performance of the univariate and bivariate models.

Editor D. Koutsoyiannis     

Empirical statistical characterization and regionalization of amplitude–duration–frequency curves for extreme peak flows in the Lake Victoria Basin,East Africa

Abstract

This paper focuses on a regionalization attempt to partly solve data limitation problems in statistical analysis of high flows to derive discharge–duration–frequency (QDF) relationships. The analysis is based on 24 selected catchments in the Lake Victoria Basin (LVB) in East Africa. Characteristics of the theoretical QDF relationships were parameterized to capture their slopes of extreme value distributions (evd), tail behaviour and scaling measures. To enable QDF estimates to be obtained for ungauged catchments, interdependence relationships between the QDF parameters were identified, and regional regression models were developed to explain the regional difference in these parameters from physiographic characteristics. In validation of the regression models, from the lowest (5 years) to the highest (25 years) return periods considered, the percentage bias in the QDF estimates ranged from –2% for the 5-year return period to 27% for 25-year return period.

Editor D. Koutsoyiannis