How can a few streamflow measurements help to predict daily hydrographs at almost ungauged sites?

Abstract

Available data from nearby gauging stations can provide a great source of hydrometric information that is potentially transferable to an ungauged site. Furthermore, streamflow measurements may even be available for the ungauged site. This paper explores the potential of four distance-based regionalization methods to simulate daily hydrographs at almost ungauged pollution-control sites. Two methods use only the hydrological information provided by neighbouring catchments; the other two are new regionalization methods parameterized with a limited number of streamflow data available at the site of interest. Based on a network of 149 streamgauges and 21 pollution-control sites located in the Upper Rhine-Meuse area, the comparative assessment demonstrates the benefit of making available point streamflow measurements at the location of interest for improving quantitative streamflow prediction. The advantage is moderate for the prediction of flow types (stormflow, recession flow, baseflow) and pulse shape (duration of rising limb and falling limb).

Editor Z.W. Kundzewicz; Associate editor A. Viglione     

Using synthetic flow duration curves for rainfall–runoff model calibration at ungauged sites

The primary objective of the study is to propose a strategy for rainfall–runoff model calibration at ungauged sites. This strategy comprises two main components: (1) development of the regional analysis method to synthesize the flow duration curves at ungauged sites; and (2) utilization of the synthetic flow duration curves for model calibration. Since the regional analysis method can synthesize the flow duration curves at ungauged sites, the continuous rainfall–runoff model coupled with a global optimization method were applied in southern Taiwan using the synthetic flow duration curve as an objective for model calibration. The results reveal that the regional flow duration curve and the strategy for model calibration at ungauged sites have good performances in the study area. Copyright © 2000 John Wiley & Sons, Ltd.     

On the use of mean monthly runoff to predict the flow–duration curve in ungauged catchments

ABSTRACT

We examine the applicability of predicting the daily flow–duration curve (FDC) using mean monthly runoff represented in its stochastic form (MM_FDC) to aid in predictions in ungauged basins, using long-term hydroclimatic data at 73 catchments of humid climate, in the eastern USA. The analysis uses soil hydrological properties, soil moisture storage capacity and the predominant runoff generation mechanism. The results show that MM_FDC did not distinguish the shapes of the upper and lower thirds of the FDC. The upper third is where the precipitation pattern and the antecedent moisture conditions are dominant, while the lower third is where drought-induced low flows and the evapotranspiration effect are prevalent. It is possible to use the MM_FDC to predict the middle third of the FDC (exceedence probabilities between 33% and 66%). The method is constrained by the catchment flow variability (slope of FDC), which changes in accordance with landscape properties and the predominant runoff generation mechanism.     

Daily flow time series patching or extension: a spatial interpolation approach based on flow duration curves

Abstract

An algorithm is described that was initially developed as a simple method for patching and extending observed time series of daily streamflow. It is based on the use of 1-day flow duration curves for each month of the year and on the assumption that flows occurring simultaneously at sites in reasonably close proximity to each other correspond to similar percentage points on their respective duration curves. The algorithm has been incorporated into a model that allows flows at a destination site to be estimated from flows occurring at several source sites. The model has been applied to six groups of catchments within southern Africa and the resulting streamflow simulations compare favourably with those obtained using a semi-distributed, physically-based, daily time step rainfall-runoff model. The current limitations of the approach and its future potential value are discussed.     

Continuous daily hydrograph simulation using duration curves of a precipitation index

The paper describes a parsimonious approach for generating continuous daily stream‐flow time‐series from observed daily rainfall data in a catchment. The key characteristic in the method is a duration curve. It is used to convert the daily rainfall information from source rain gauges into a continuous daily hydrograph at the destination river site. For each source rain gauge a time‐series of rainfall related ‘current precipitation index’ is generated and its duration curve is established. The current precipitation index reflects the current catchment wetness and is defined as a continuous function of precipitation, which accumulates on rainy days and exponentially decays during the periods of no rainfall. The process of rainfall‐to‐runoff conversion is based on the assumption that daily current precipitation index values at rainfall site(s) in a catchment and the destination site's daily flows correspond to similar probabilities on their respective duration curves. The method is tested in several small catchments in South Africa. The method is designed primarily for application at ungauged sites in data‐poor regions where the use of more complex and information consuming techniques of data generation may not be justified. Copyright © 2000 John Wiley & Sons, Ltd.     

Regional models of flow-duration curves of perennial and intermittent streams and their use for calibrating the parameters of a rainfall–runoff model

Abstract

One of the main challenges faced by hydrologists and water engineers is the estimation of variables needed for water resources planning and management in ungauged river basins. To this end, techniques for transposing information, such as hydrological regional analyses, are widely employed. A method is presented for regionalizing flow-duration curves (FDCs) in perennial, intermittent and ephemeral rivers, based on the extended Burr XII probability distribution. This distribution shows great flexibility to fit data, with accurate reproduction of flow extremes. The performance analysis showed that, in general, the regional models are able to synthesize FDCs in ungauged basins, with a few possible drawbacks in the application of the method to intermittent and ephemeral rivers. In addition to the regional models, we summarize the experience of using synthetic FDCs for the indirect calibration of the Rio Grande rainfall–runoff model parameters in ungauged basins.

Editor D. Koutsoyiannis

Citation Costa, V., Fernandes, W., and Naghettini, M., 2013. Regional models of flow-duration curves of perennial and intermittent streams and their use for calibrating the parameters of a rainfall–runoff model. Hydrological Sciences Journal, 59 (2), 262–277.     

A regional model of low flow for southern Taiwan

The primary purpose of this study is to develop regional models of the lower part of flow duration curves (LPFDCs) to synthesize low‐flow characteristics at ungauged sites in southern Taiwan. Because of the close relationship between low streamflow regimes and hydrogeological features, the model development first involved delimiting homogeneous hydrogeological regions by using two‐step cluster analysis. Each homogeneous region was then discriminated by an equation developed on the basis of its hydrogeological features, which was then used to determine which of three sets of regional LPFDC models would be appropriate for a particular ungauged site. Each of the three sets of regional LPFDC models were developed using both conventional multivariate statistical regression and fuzzy regression. Thirty‐four stream‐gauged watersheds located in southern Taiwan provide the data set. The study results reveal that the regional LPFDC models developed in this study could be applied reasonably at ungauged sites. Copyright © 2002 John Wiley & Sons, Ltd.     

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.     

Neural network model for discharge and water-level prediction for Ramganga River catchment of Ganga Basin,India

ABSTRACT

Discharges and water levels are essential components of river hydrodynamics. In unreachable terrains and ungauged locations, it is quite difficult to measure these parameters due to rugged topography. In the present study an artificial neural network model has been developed for the Ramganga River catchment of the Ganga Basin. The modelled network is trained, validated and tested using daily water flow and level data pertaining to 4 years (2010–2013). The network has been optimized using an enumeration technique and a network topology of 4-10-2 with a learning rate set at 0.06, which was found optimum for predicting discharge and water-level values for the considered river. The mean square error values obtained for discharge and water level for the tested data were found to be 0.046 and 0.012, respectively. Thus, monsoon flow patterns can be estimated with an accuracy of about 93.42%.

Editor M.C. Acreman; Associate editor E. Gargouri     

Prediction of base flows from basin characteristics: a case study from Zimbabwe / Prévision de débits de base à partir de caractéristiques du bassin: une étude de cas au Zimbabwe

Abstract

Abstract Base flows make up the flows of most rivers in Zimbabwe during the dry season. Prediction of base flows from basin characteristics is necessary for water resources planning of ungauged basins. Linear regression and artificial neural networks were used to predict the base flow index (BFI) from basin characteristics for 52 basins in Zimbabwe. Base flow index was positively related to mean annual precipitation (r = 0.71), basin slope (r = 0.76), and drainage density (r = 0.29), and negatively related to mean annual evapotranspiration (r = –0.74), and proportion of a basin with grasslands and wooded grasslands (r = –0.53). Differences in lithology did not significantly affect BFI. Linear regression and artificial neural networks were both suitable for predicting BFI values. The predicted BFI was used in turn to derive flow duration curves of the 52 basins and with R ² being 0.89–0.99.     

The effects of climate variability on discharge as dependent on catchment characteristics in the Upper Loire basin,France

Abstract

The effects of climatically deviating periods of at least four years on discharge were investigated employing flow duration curves in the Upper Loire basin, France. The periods were determined using the standardized cumulative yearly deviation from the mean precipitation for ten climate stations. Flow duration curves from 27 catchments were determined and parameterized for each period. Results show that the effect of precipitation on discharge is more pronounced than the effect of temperature. They also show that the parameter values that determine the flow duration curve differ significantly between dry and wet periods. Furthermore the effect of drought on discharge is larger than the effect of wetness. Catchments with a high variability of discharge are more sensitive to changes of precipitation than catchments with a low variability of discharge.     

Derivation of a curve number and kinematic-wave based flood frequency distribution

Abstract

The physically-based flood frequency models use readily available rainfall data and catchment characteristics to derive the flood frequency distribution. In the present study, a new physically-based flood frequency distribution has been developed. This model uses bivariate exponential distribution for rainfall intensity and duration, and the Soil Conservation Service-Curve Number (SCS-CN) method for deriving the probability density function (pdf) of effective rainfall. The effective rainfall-runoff model is based on kinematic-wave theory. The results of application of this derived model to three Indian basins indicate that the model is a useful alternative for estimating flood flow quantiles at ungauged sites.     

Estimating daily inflows of large lakes using a water‐balance‐based runoff coefficient scaling approach

Daily river inflow time series are highly valuable for water resources and water environment management of large lakes. However, the availability of continuous inflow data for large lakes is still relatively limited, especially for large lakes situated within humid plain regions with tens or even hundreds of tributaries. In this study, we choose the fifth largest freshwater Lake Chaohu in China as our study area to introduce a new approach to reconstruct historical daily inflows at ungauged subcatchments of large lakes. This approach makes use of water level, lake surface rainfall, evaporation from the lake, and catchment rainfall observations. Rainfall–runoff relationship at a reference catchment was analysed to select rainfall input and estimate run‐off coefficient firstly, and the run‐off coefficient was then transferred to ungauged subcatchments to initially estimate daily inflows. Run‐off coefficient was scaled to adjust daily inflows at ungauged subcatchments according to water balance of the lake. This approach was evaluated using sparsely measured inflows at eight subcatchments of Lake Chaohu and compared with the commonly used drainage area ratio method. Results suggest that the inflow time series reconstructed from this approach consistent well to corresponding observations, with mean R² and Nash–Sutcliffe efficiency values of 0.69 and 0.6, respectively. This approach outperforms drainage area ratio method in terms of mean R² and Nash–Sutcliffe efficiency values. Accuracy of this approach holds well when the number of water‐level station being used decreased from four to one.     

Improving streamflow estimation in ungauged basins using a multi-modelling approach

ABSTRACT

In this study, a multi-modelling approach is proposed for improved continuous daily streamflow estimation in ungauged basins using regionalization—the process of transferring hydrological data from gauged to ungauged watersheds. Four regionalization models, two data-driven and two hydrological, were used for continuous daily streamflow estimation. Comparison of the individual models reveals that each of the four models performed well on a limited number of ungauged basins while none of them performed well for the entire 90 selected watersheds. The results obtained from the four models are evaluated and reported in a deterministic way by a model combination approach along with its uncertainty range consisting of 16 ensemble members. It is shown that a combined model of the four individual models performed well on all 90 watersheds and the ensemble range can account for the uncertainty of models. The combined model was more efficient and appeared more robust compared to the individual models. Furthermore, continuous ranked probability scores (CRPS) calculated for the ensemble model outputs indicate better performance compared to individual models and competitive with the combined model.

EDITOR A. Castellarin ASSOCIATE EDITOR G. Di Baldassarre     

Introducing environmental thresholds into water withdrawal management of mountain streams in the Kura River basin,Azerbaijan

Abstract

The study aims to set and implement environmentally relevant limits for the exploitation of mountain streams in the Kura River basin of Azerbaijan. Such streams represent the preferred spawning grounds for valuable sturgeon of the Caspian Sea, but experience continuously increasing exploitation in the form of water withdrawals for industry and irrigation. Since no detailed environmental flow assessments have been conducted on any of the Kura basin streams, an interim approach is suggested based on minimum flow, referred to as “base environmental minimum”. The latter may be estimated from the unregulated parts of observed or simulated daily flow records. Environmental flow requirements for individual months of an individual year may be calculated using correction factors related to monthly rainfall. Simple relationships are suggested for base environmental flow estimation at ungauged sites, and the implications of river pollution for monthly environmental requirements are examined. Further, definition of environmentally critical periods in a stream is proposed based on a ratio of observed to “environmental” flow as an indicator of environmental stress. It is illustrated that the conjunctive use of several closely located streams for water supply may significantly reduce the duration of, or completely eliminate, environmentally critical periods. The idea of environmentally acceptable areal water withdrawal is formulated, so that the overall approach may be applied for environmentally sustainable water withdrawal management in other small streams.     

Prediction of streamflow regimes over large geographical areas: interpolated flow–duration curves for the Danube region

ABSTRACT

Flow–duration curves (FDCs) are essential to support decisions on water resources management, and their regionalization is fundamental for the assessment of ungauged basins. In comparison with calibrated rainfall–runoff models, statistical methods provide data-driven estimates representing a useful benchmark. The objective of this work is the interpolation of FDCs from ~500 discharge gauging stations in the Danube. To this aim we use total negative deviation top-kriging (TNDTK), as multi-regression models are shown to be unsuitable for representing FDCs across all durations and sites. TNDTK shows a high accuracy for the entire Danube region, with overall Nash-Sutcliffe efficiency values computed in a leave-p-out cross-validation scheme (p equal to one site, one-third and half of the sites), all above 0.88. A reliability measure based on kriging variance is attached to each interpolated FDC at ~4000 prediction nodes. The GIS layer of regionalized FDCs is made available for broader use in the region.     

Evaluation of storage–discharge relationships and recession analysis-based distributed hourly runoff simulation in large-scale,mountainous and snow-influenced catchment

ABSTRACT

Evaluation of a recession-based “top-down” model for distributed hourly runoff simulation in macroscale mountainous catchments is rare in the literature. We evaluated such a model for a 3090 km² boreal catchment and its internal sub-catchments. The main research question is how the model performs when parameters are either estimated from streamflow recession or obtained by calibration. The model reproduced observed streamflow hydrographs (Nash-Sutcliffe efficiency up to 0.83) and flow duration curves. Transferability of parameters to the sub-catchments validates the performance of the model, and indicates an opportunity for prediction in ungauged sites. However, the cases of parameter estimation and calibration excluding the effects of runoff routing underestimate peak flows. The lower end of the recession and the minimum length of recession segments included are the main sources of uncertainty for parameter estimation. Despite the small number of calibrated parameters, the model is susceptible to parameter uncertainty and identifiability problems.

EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR A. Carsteanu