Developments in hydrometric network design: A review

Mishra, Ashok Kumar; Coulibaly, Paulin

doi:10.1029/2007rg000243

Cited by 283 publications

(191 citation statements)

References 156 publications

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“…For instance, streamflow is governed not only by the distribution of rainfall (in both space and time) but also by the nature and state of the catchment (e.g., topography, vegetation, soil, geology); see Beven (2006) for a compilation of, and stimulating insight into, some early benchmark studies on streamflow generation processes. Attempts to monitor, model, and predict streamflow have been a central topic in hydrology during the last century or so; see, for example, Salas et al (1995), Grayson and Blöschl (2000), Duan et al (2003), Mishra and Coulibaly (2009), and Hrachowitz et al (2013) for comprehensive accounts on streamflow monitoring, modeling, and prediction.…”

Section: Introductionmentioning

confidence: 99%

Complex networks for streamflow dynamics

Sivakumar

Woldemeskel

2014

Hydrol. Earth Syst. Sci.

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Abstract. Streamflow modeling is an enormously challenging problem, due to the complex and nonlinear interactions between climate inputs and landscape characteristics over a wide range of spatial and temporal scales. A basic idea in streamflow studies is to establish connections that generally exist, but attempts to identify such connections are largely dictated by the problem at hand and the system components in place. While numerous approaches have been proposed in the literature, our understanding of these connections remains far from adequate. The present study introduces the theory of networks, in particular complex networks, to examine the connections in streamflow dynamics, with a particular focus on spatial connections. Monthly streamflow data observed over a period of 52 years from a large network of 639 monitoring stations in the contiguous US are studied. The connections in this streamflow network are examined primarily using the concept of clustering coefficient, which is a measure of local density and quantifies the network's tendency to cluster. The clustering coefficient analysis is performed with several different threshold levels, which are based on correlations in streamflow data between the stations. The clustering coefficient values of the 639 stations are used to obtain important information about the connections in the network and their extent, similarity, and differences between stations/regions, and the influence of thresholds. The relationship of the clustering coefficient with the number of links/actual links in the network and the number of neighbors is also addressed. The results clearly indicate the usefulness of the network-based approach for examining connections in streamflow, with important implications for interpolation and extrapolation, classification of catchments, and predictions in ungaged basins.

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Section: Introductionmentioning

confidence: 99%

Complex networks for streamflow dynamics

Sivakumar

Woldemeskel

2014

Hydrol. Earth Syst. Sci.

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“…In many cases, however, additional investment of resources may improve reliable flow measurement, thereby realising the potential of key sites. Mishra and Coulibaly (2009) discuss the potential of recent developments in streamflow measurement for network improvement, including new methods such as Acoustic Doppler Current Profilers (ADCPs), which enable measurements to be carried out at a lower cost in environments which would previously have been very challenging.…”

Section: Identifying Priority Gauging Stations For Improvementmentioning

confidence: 99%

“…Previous authors have argued that network design strategies should ensure that streamflow/precipitation variability in space and time is sampled optimally, to facilitate estimation at ungauged sites (Mishra and Coulibaly, 2009). Whilst this aspiration is implicit in many statistical network evaluation methods, there is a good argument for using regionalisation methods as a starting point for network evaluation: the utility of regionalisation techniques largely depends on the number, spatial disposition and measurement capabilities of gauging stations in a hydrometric network.…”

Section: Introductionmentioning

confidence: 99%

“…A significant body of research has been devoted towards developing network appraisal methods; a comprehensive review has recently been undertaken by Mishra and Coulibaly (2009). A majority of approaches are statistically-based, employing regression analyses of streamflow parameters and physiographic properties of catchments (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…Around the world, however, hydrometric monitoring networks face increasing financial constraints and, in many countries, are declining (Vörösmarty, 2002;Mishra and Coulibaly, 2009). Under such circumstances, there is a growing need for improved network evaluation tools, to ensure that the potential of existing networks is maximised, within resource constraints.…”

Section: Introductionmentioning

confidence: 99%

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Evaluating hydrometric networks for prediction in ungauged basins: a new methodology and its application to England and Wales

et al. 2012

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Flow estimates for ungauged catchments are often derived through regionalisation methods, which enable data transfer from a pool of hydrologically-similar catchments with existing gauging stations (i.e. pooling-groups). This paper presents a methodology for indexing the utility of gauged catchments within widely-used pooling-group methodologies for high and low flow estimation; this methodology is then used as the basis for a network evaluation strategy. The utility of monitoring stations is assessed using catchment properties and a parallel, but independent, appraisal of the quality of gauging station data, which considers hydrometric performance, anthropogenic disturbances and record length. Results from the application of the method to a national network of over 1100 gauging stations in England andWales are presented. Firstly, the method is used to appraise the fitness-for-purpose of the network for regionalisation. The method is then used to identify gauges which monitor catchments with high potential for regionalisation, but which are deficient in terms of data quality -where upgrades in hydrometric performance would yield the greatest benefits.Finally, gauging stations with limited value for regionalisation, given the pooling-group criteria employed, are identified. Alongside a wider review of other uses of the network, this analysis could inform a judicious approach to network rationalisation.

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CRDEMO: Combined regionalization and dual entropy-multiobjective optimization for hydrometric network design

2013

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[1] Establishing an adequate hydrometric network to provide accurate and reliable continuous flow information for various users remains a major challenge. This includes the design of new networks or the evaluation of existing networks. This study proposes a combined regionalization and dual entropy-multiobjective optimization (CRDEMO) method for determining minimum network that meets the World Meteorology Organization (WMO) standards, which is considered herein an optimal minimum network. A regionalization approach is used to estimate flows in potential locations for new additional stations, and a dual entropy-multiobjective optimization approach is used to identify optimal trade-offs between the maximum possible information content and the minimum shared information among the stations. The method was examined in two Canadian River basins, namely, the St. John River and St. Lawrence River basins. The St. John River basin has a higher network density compared to the St. Lawrence River basin. Results of the analysis indicate that the St. Lawrence River basin requires a high number of new additional stations to meet the WMO minimum network density. It was also determined that existing stations do not have a significant influence in determining the locations of new stations in the St. Lawrence River basin. Conversely, however, in the St. John River basin, existing stations have significant influence on the determination of locations of new stations due to the higher number of existing stations. Overall, the CRDEMO technique is shown to be robust for designing optimal minimum hydrometric networks and can be a useful tool for evaluating current and proposed networks.Citation: Samuel, J., P. Coulibaly, and J. Kollat (2013), CRDEMO: Combined regionalization and dual entropy-multiobjective optimization for hydrometric network design, Water Resour. Res., 49,[8070][8071][8072][8073][8074][8075][8076][8077][8078][8079][8080][8081][8082][8083][8084][8085][8086][8087][8088][8089]

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Developments in hydrometric network design: A review

Cited by 283 publications

References 156 publications

Complex networks for streamflow dynamics

Complex networks for streamflow dynamics

Evaluating hydrometric networks for prediction in ungauged basins: a new methodology and its application to England and Wales

CRDEMO: Combined regionalization and dual entropy-multiobjective optimization for hydrometric network design

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