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Comparison of catchment grouping methods for flow duration curve estimation at ungauged sites in France
E. Sauquet ,C. Catalogne
Hydrology and Earth System Sciences (HESS) & Discussions (HESSD) , 2011,
Abstract: The study aims at estimating flow duration curves (FDC) at ungauged sites in France and quantifying the associated uncertainties using a large dataset of 1080 FDCs. The interpolation procedure focuses here on 15 percentiles standardised by the mean annual flow, which is assumed to be known at each site. In particular, this paper discusses the impact of different catchment grouping procedures on the estimation of percentiles by regional regression models. In a first step, five parsimonious FDC parametric models are tested to approximate FDCs at gauged sites. The results show that the model based on the expansion of Empirical Orthogonal Functions (EOF) outperforms the other tested models. In the EOF model, each FDC is interpreted as a linear combination of regional amplitude functions with spatially variable weighting factors corresponding to the parameters of the model. In this approach, only one amplitude function is required to obtain a satisfactory fit with most of the observed curves. Thus, the considered model requires only two parameters to be applicable at ungauged locations. Secondly, homogeneous regions are derived according to hydrological response, on the one hand, and geological, climatic and topographic characteristics on the other hand. Hydrological similarity is assessed through two simple indicators: the concavity index (IC) representing the shape of the dimensionless FDC and the seasonality ratio (SR), which is the ratio of summer and winter median flows. These variables are used as homogeneity criteria in three different methods for grouping catchments: (i) according to an a priori classification of French Hydro-EcoRegions (HERs), (ii) by applying regression tree clustering and (iii) by using neighbourhoods obtained by canonical correlation analysis. Finally, considering all the data, and subsequently for each group obtained through the tested grouping techniques, we derive regression models between physiographic and/or climatic variables and the two parameters of the EOF model. Results on percentile estimation in cross validation show that a significant benefit is obtained by defining homogeneous regions before developing regressions, particularly when grouping methods make use of hydrogeological information.
Comparison of catchment grouping methods for flow duration curve estimation at ungauged sites in France
E. Sauquet,C. Catalogne
Hydrology and Earth System Sciences Discussions , 2011, DOI: 10.5194/hessd-8-3233-2011
Abstract: The study aims at estimating flow duration curves (FDC) at ungauged sites in France and quantifying the associated uncertainties using a large dataset of 1080 FDCs. The interpolation procedure focuses here on 15 percentiles standardised by the mean annual flow, which is supposed to be known at each site. In particular, this paper discusses the relevance of different catchments grouping procedures on percentiles estimation by regional regression models. First, five parsimonious FDC parametric models were tested to approximate FDCs at gauged sites. The results show that the model based on Empirical Orthogonal Functions (EOF) expansion outperforms the other ones. In this model each FDC is interpreted as a linear combination of regional amplitude functions with weights – the parameters of the model – varying in space. Here, only one amplitude function was found sufficient to fit well most of the observed curves. Thus the considered model requires only two parameters to be estimated at ungauged locations. Second, homogeneous regions were derived according to hydrological response on one hand, and geological, climatic and topographic characteristics on the other hand. Hydrological similarity was assessed through two simple indicators: the concavity index (IC) that represents the shape of the standardized FDC and the seasonality ratio (SR) which is the ratio of summer and winter median flows. These variables were used as homogeneity criteria in three different methods for grouping catchments: (i) according to their membership in one of an a priori French classification into Hydro-Eco-Regions (HERs), (ii) by applying a regression tree clustering and (iii) by using hydrological neighbourhood obtained by canonical correlation analysis. Finally, regression models between physiographic and/or climatic variables and the two parameters of the EOF model were derived considering all the data and thereafter for each group obtained through the tested grouping techniques. Results on percentiles estimation in cross validation show a significant benefit to form homogeneous regions before developing regressions, particularly when grouping methods use hydrogeological information.
Prediction of Flow Duration Curves for Ungauged Basins with Quasi-Newton Method  [PDF]
Mutlu Ya?ar, Neset Orhan Baykan
Journal of Water Resource and Protection (JWARP) , 2013, DOI: 10.4236/jwarp.2013.51012
Abstract:

Prediction of flow-duration-curves (FDC) is an important task for water resources planning, management and hydraulic energy production. Classification of the basins as carstic and non-carstic may be used to estimate parameters of the FDC with predictive tools for catchments with/without observed stream flow. There is a need for obtaining FDC for ungauged stations for efficient water resource planning. Thus, study proposes a quite new approach, called the EREFDC model, for estimating the parameters of the FDC for which the parameters of the FDC are obtained with quasi-Newton method. Estimation are made for using the bv gauged stations at first than the FDC parameters are estimated for ungauged stations based on drainage area, annual mean precipitation, mean permeability, mean slope, latitude, longitude, and elevation from the mean sea level are used. The EREFDC model consists of various type of linear- and nonlinear mathematical equations, is able to predict a wide range of the FDC parameters for gauged and ungauged basins. The method is applied to 72 unimpaired catchments studied are about for 50 years average daily measured stream flow. Results showed that the EREFDC model may be used for estimating. FDC parameters for ungauged hydrological basins in order to find FDC for ungauged stations. Results also showed that the EREFDC model performs better in carstic regions than non-carstic regions. In addition, parameters of FDC for tributaries at the basins with insufficient flow data or without flow data may be determined by using basin characteristics.

A region of influence approach to predicting flow duration curves within ungauged catchments
M. G. R. Holmes,A. R. Young,A. Gustard,R. Grew
Hydrology and Earth System Sciences (HESS) & Discussions (HESSD) , 2002,
Abstract: The development of regionalised hydrological models or procedures for estimating flow duration statistics has been the subject of international research since the 1970s. Historically these models have been based on multivariate statistical models that relate flow statistics to the physical and climatic characteristics of a catchment. The a priori classification of catchments has often been a component of this analysis. This paper discusses the background to the development of such models, with particular emphasis on the United Kingdom; it describes a new region of influence approach to estimating flow duration statistics and compares the performance of this method with current multivariate regression based methods for estimating flow duration statistics within the United Kingdom. Keywords: hydrological models, regionalisation, river networks, water resources, flow duration curves, region of influence
Application of Parametric-Based Framework for Regionalisation of Flow Duration Curves  [PDF]
Martins Yusuf Otache, Muhammad Abdullahi Tyabo, Iyanda Murtala Animashaun, Lydia Pam Ezekiel
Journal of Geoscience and Environment Protection (GEP) , 2016, DOI: 10.4236/gep.2016.45009
Abstract: It is common knowledge that the end user of stream flow data may necessarily not have any prior knowledge of the quality control measures applied in their generation, therefore, conclusions drawn most often times may not be effective as desired. Thus, this study is an attempt at providing an independent quality construct to boost the confidence in the use of stream flow data by developing regional flow duration curves for selected ungauged stations of the upper Niger River Basin, Nigeria. Toward this end, stream flow data for seven gauging stations cover some sub basins in the Basin were obtained; precisely, monthly stream flow data covering a range of eleven to fifty-three years period. The flow duration curves from the gauging stations were fitted with three probability distribution models; i.e., logarithmic, power and exponential regression models. For the regionalisation, parameterisation was carried out in terms of the drainage area alone to allow for simplicity of models. Results obtained showed that the exponential regression model, in terms of Coefficient of Determination (R2) had the best fit. Though the regionalised model was simple, measurable agreement was obtained during the calibration and validation phases. However, considering the length of data used and probable variability in the stream flow regime, it is not possible to objectively generalise on the quality of the results. Against this backdrop, it suffices to take into cognisance the need to use an ensemble of catchment characteristics in the development of the flow duration curves and the overall regional models; this is important considering the implications of anthropogenic activities and hydro-climatic variations.
Exploring the physical controls of regional patterns of flow duration curves – Part 3: A catchment classification system based on regime curve indicators
E. Coopersmith, M. A. Yaeger, S. Ye, L. Cheng,M. Sivapalan
Hydrology and Earth System Sciences (HESS) & Discussions (HESSD) , 2012,
Abstract: Predictions of hydrological responses in ungauged catchments can benefit from a classification scheme that can organize and pool together catchments that exhibit a level of hydrologic similarity, especially similarity in some key variable or signature of interest. Since catchments are complex systems with a level of self-organization arising from co-evolution of climate and landscape properties, including vegetation, there is much to be gained from developing a classification system based on a comparative study of a population of catchments across climatic and landscape gradients. The focus of this paper is on climate seasonality and seasonal runoff regime, as characterized by the ensemble mean of within-year variation of climate and runoff. The work on regime behavior is part of an overall study of the physical controls on regional patterns of flow duration curves (FDCs), motivated by the fact that regime behavior leaves a major imprint upon the shape of FDCs, especially the slope of the FDCs. As an exercise in comparative hydrology, the paper seeks to assess the regime behavior of 428 catchments from the MOPEX database simultaneously, classifying and regionalizing them into homogeneous or hydrologically similar groups. A decision tree is developed on the basis of a metric chosen to characterize similarity of regime behavior, using a variant of the Iterative Dichotomiser 3 (ID3) algorithm to form a classification tree and associated catchment classes. In this way, several classes of catchments are distinguished, in which the connection between the five catchments' regime behavior and climate and catchment properties becomes clearer. Only four similarity indices are entered into the algorithm, all of which are obtained from smoothed daily regime curves of climatic variables and runoff. Results demonstrate that climate seasonality plays the most significant role in the classification of US catchments, with rainfall timing and climatic aridity index playing somewhat secondary roles in the organization of the catchments. In spite of the tremendous heterogeneity of climate, topography, and runoff behavior across the continental United States, 331 of the 428 catchments studied are seen to fall into only six dominant classes.
Exploring the physical controls of regional patterns of flow duration curves – Part 3: A catchment classification system based on regime curve indicators
E. Coopersmith,M. A. Yaeger,S. Ye,L. Cheng
Hydrology and Earth System Sciences (HESS) & Discussions (HESSD) , 2012, DOI: 10.5194/hess-16-4467-2012
Abstract: Predictions of hydrological responses in ungauged catchments can benefit from a classification scheme that can organize and pool together catchments that exhibit a level of hydrologic similarity, especially similarity in some key variable or signature of interest. Since catchments are complex systems with a level of self-organization arising from co-evolution of climate and landscape properties, including vegetation, there is much to be gained from developing a classification system based on a comparative study of a population of catchments across climatic and landscape gradients. The focus of this paper is on climate seasonality and seasonal runoff regime, as characterized by the ensemble mean of within-year variation of climate and runoff. The work on regime behavior is part of an overall study of the physical controls on regional patterns of flow duration curves (FDCs), motivated by the fact that regime behavior leaves a major imprint upon the shape of FDCs, especially the slope of the FDCs. As an exercise in comparative hydrology, the paper seeks to assess the regime behavior of 428 catchments from the MOPEX database simultaneously, classifying and regionalizing them into homogeneous or hydrologically similar groups. A decision tree is developed on the basis of a metric chosen to characterize similarity of regime behavior, using a variant of the Iterative Dichotomiser 3 (ID3) algorithm to form a classification tree and associated catchment classes. In this way, several classes of catchments are distinguished, in which the connection between the five catchments' regime behavior and climate and catchment properties becomes clearer. Only four similarity indices are entered into the algorithm, all of which are obtained from smoothed daily regime curves of climatic variables and runoff. Results demonstrate that climate seasonality plays the most significant role in the classification of US catchments, with rainfall timing and climatic aridity index playing somewhat secondary roles in the organization of the catchments. In spite of the tremendous heterogeneity of climate, topography, and runoff behavior across the continental United States, 331 of the 428 catchments studied are seen to fall into only six dominant classes.
Exploring the physical controls of regional patterns of flow duration curves – Part 3: A catchment classification system based on seasonality and runoff regime
E. Coopersmith,M. Yaeger,S. Ye,L. Cheng
Hydrology and Earth System Sciences Discussions , 2012, DOI: 10.5194/hessd-9-7085-2012
Abstract: Predictions of hydrological responses in ungauged catchments can benefit from a classification scheme that can organize and pool together catchments that exhibit a level of hydrologic similarity, especially similarity in some key variable or signature of interest. Since catchments are complex systems with a level of self-organization arising from co-evolution of climate and landscape properties, including vegetation, there is much to be gained from developing a classification system based on a comparative study of a population of catchments across climatic and landscape gradients. The focus of this paper is on climate seasonality and seasonal runoff regime, as characterized by the ensemble mean of within-year variation of climate and runoff. The work on regime behavior is part of an overall study of the physical controls on regional patterns of Flow Duration Curves (FDCs), motivated by the fact that regime behavior leaves a major imprint upon the shape of FDCs, especially the slope of the FDCs. As an exercise in comparative hydrology, the paper seeks to assess the regime behavior of 428 catchments from the MOPEX database simultaneously, classifying and regionalizing them into homogeneous or hydrologically similar groups. A decision tree is developed on the basis of a metric chosen to characterize similarity of regime behavior, using a variant of the Iterative Dichotomiser (ID3) algorithm to form a classification tree and associated catchment classes. In this way, several classes of catchments are distinguished, in which the connection between the catchments' regime behavior and climate and catchment properties becomes self-evident. Only four similarity indices are entered into the algorithm, all of which are obtained from smoothed daily regime curves of climatic variables and runoff. Results demonstrate that climate seasonality plays the most significant role in the classification of US catchments, with rainfall timing and climatic aridity index playing somewhat secondary roles in the organization of the catchments. In spite of the tremendous heterogeneity of climate, topography, and runoff behavior across the continental US, 331 of the 428 catchments studied are seen to fall into only six dominant classes.
A spatial neural fuzzy network for estimating pan evaporation at ungauged sites
C.-H. Chung, Y.-M. Chiang,F.-J. Chang
Hydrology and Earth System Sciences (HESS) & Discussions (HESSD) , 2012,
Abstract: Evaporation is an essential reference to the management of water resources. In this study, a hybrid model that integrates a spatial neural fuzzy network with the kringing method is developed to estimate pan evaporation at ungauged sites. The adaptive network-based fuzzy inference system (ANFIS) can extract the nonlinear relationship of observations, while kriging is an excellent geostatistical interpolator. Three-year daily data collected from nineteen meteorological stations covering the whole of Taiwan are used to train and test the constructed model. The pan evaporation (Epan) at ungauged sites can be obtained through summing up the outputs of the spatially weighted ANFIS and the residuals adjusted by kriging. Results indicate that the proposed AK model (hybriding ANFIS and kriging) can effectively improve the accuracy of Epan estimation as compared with that of empirical formula. This hybrid model demonstrates its reliability in estimating the spatial distribution of Epan and consequently provides precise Epan estimation by taking geographical features into consideration.
A spatial neural fuzzy network for estimating pan evaporation at ungauged sites
C.-H. Chung,Y.-M. Chiang,F.-J. Chang
Hydrology and Earth System Sciences (HESS) & Discussions (HESSD) , 2012, DOI: 10.5194/hess-16-255-2012
Abstract: Evaporation is an essential reference to the management of water resources. In this study, a hybrid model that integrates a spatial neural fuzzy network with the kringing method is developed to estimate pan evaporation at ungauged sites. The adaptive network-based fuzzy inference system (ANFIS) can extract the nonlinear relationship of observations, while kriging is an excellent geostatistical interpolator. Three-year daily data collected from nineteen meteorological stations covering the whole of Taiwan are used to train and test the constructed model. The pan evaporation (Epan) at ungauged sites can be obtained through summing up the outputs of the spatially weighted ANFIS and the residuals adjusted by kriging. Results indicate that the proposed AK model (hybriding ANFIS and kriging) can effectively improve the accuracy of Epan estimation as compared with that of empirical formula. This hybrid model demonstrates its reliability in estimating the spatial distribution of Epan and consequently provides precise Epan estimation by taking geographical features into consideration.
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