Hydrometric network design using streamflow signatures and indicators of hydrologic alteration

Leach, James M.; Kornelsen, Kurt C.; Samuel, Jos; Coulibaly, Paulin

doi:10.1016/j.jhydrol.2015.08.048

Cited by 37 publications

(32 citation statements)

References 26 publications

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“…Leach et al . () identified three signatures which displayed the least correlation to the others and used these three as additional CR‐DEMO inputs. This was done in order to reduce computational complexity while retaining most of the diversity between the signatures.…”

Section: Methodsmentioning

confidence: 99%

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Assessing Spatial Scale Effects on Hydrometric Network Design Using Entropy and Multi‐objective Methods

Werstuck

Coulibaly

2017

J American Water Resour Assoc

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In order to facilitate water resources decisions, it is important that accurate and informative hydrometric data are collected. Combining information theory with multi-objective optimization has led to methods of optimizing the information content provided by hydrometric networks; however, there is no available study on the effects of spatial scale and data limitation on these methods. Herein, a dual entropy multi-objective optimization (DEMO) and a transinformation (TI) analysis were done to recommend optimal locations for additional hydrometric stations in the Madawaska Watershed. This analysis was designed to be comparative to a similar study conducted on the Ottawa River Basin which encompasses the Madawaska Watershed to allow for an investigation of the spatial scale effects in this type of network design. This study concludes that TI analysis is not adversely affected by scaling; however, the DEMO analysis is sensitive to the placement of potential station locations and the size of the study area. This study also examines the benefit of including nearby stations when the area of interest does not have a sufficient number of existing hydrometric stations for analysis. It is shown that these stations can provide useful information because their inclusion in the analysis increased the average TI in the watershed. Recommendations were made as to the ideal locations of additional stations in the Madawaska Watershed hydrometric network.(KEY TERMS: entropy; hydrometric network; multi-objective optimization; network design; water resources; spatial scale.) Werstuck, Connor and Paulin Coulibaly, 2018. Assessing Spatial Scale Effects on Hydrometric Network Design Using Entropy and Multi-objective Methods.

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Section: Methodsmentioning

confidence: 99%

“…For further details on the application of signatures and IHA in hydrometric network design, the reader should refer to Leach et al . ().…”

Section: Methodsmentioning

confidence: 99%

Assessing Spatial Scale Effects on Hydrometric Network Design Using Entropy and Multi‐objective Methods

Werstuck

Coulibaly

2017

J American Water Resour Assoc

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“…They compared the performance of various regionalization methods including not only a conceptual hydrologic model, but also spatial proximity, physical similarity and their combinations with drainage area ratio. Based on the performance statistics by applying multiple basins, inverse distance weighting coupled with drainage area ratio performed the best, and this conclusion has been adopted in several studies [34,35,37,55].…”

Section: Streamflow and Water Level Networkmentioning

confidence: 98%

“…However, the network design studies using the permutation entropy are still limited. On the other hand, Leach et al [37] applied additional features to the network design. While the common objectives in water monitoring network design using an optimization technique are to maximize the information and to minimize the redundancy in the network, they additionally considered the physical properties of watersheds, such as the streamflow signatures [72,73] and the indicators of hydrologic alterations (IHAs) [74,75].…”

Section: Streamflow and Water Level Networkmentioning

confidence: 99%

Entropy Applications to Water Monitoring Network Design: A Review

Keum

Kornelsen

Leach

et al. 2017

Entropy

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Abstract:Having reliable water monitoring networks is an essential component of water resources and environmental management. A standardized process for the design of water monitoring networks does not exist with the exception of the World Meteorological Organization (WMO) general guidelines about the minimum network density. While one of the major challenges in the design of optimal hydrometric networks has been establishing design objectives, information theory has been successfully adopted to network design problems by providing measures of the information content that can be deliverable from a station or a network. This review firstly summarizes the common entropy terms that have been used in water monitoring network designs. Then, this paper deals with the recent applications of the entropy concept for water monitoring network designs, which are categorized into (1) precipitation; (2) streamflow and water level; (3) water quality; and (4) soil moisture and groundwater networks. The integrated design method for multivariate monitoring networks is also covered. Despite several issues, entropy theory has been well suited to water monitoring network design. However, further work is still required to provide design standards and guidelines for operational use.

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“…Chebbi et al [13] identified the optimal network using an intensity-duration-frequency curve and a variance-reduction method. Related works based on entropy since Krstanovic and Singh [14] is widen and undergoing [15][16][17][18]. Wei et al [19] introduced entropy to evaluate the effect of spatiotemporal scaling on rainfall network design.…”

Section: Introductionmentioning

confidence: 99%

Rainfall Network Optimization Using Radar and Entropy

Yeh

Chen

Chang

et al. 2017

Entropy

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Abstract:In this study, a method combining radar and entropy was proposed to design a rainfall network. Owing to the shortage of rain gauges in mountain areas, weather radars are used to measure rainfall over catchments. The major advantage of radar is that it is possible to observe rainfall widely in a short time. However, the rainfall data obtained by radar do not necessarily correspond to that observed by ground-based rain gauges. The in-situ rainfall data from telemetering rain gauges were used to calibrate a radar system. Therefore, the rainfall intensity; as well as its distribution over the catchment can be obtained using radar. Once the rainfall data of past years at the desired locations over the catchment were generated, the entropy based on probability was applied to optimize the rainfall network. This method is applicable in remote and mountain areas. Its most important utility is to construct an optimal rainfall network in an ungauged catchment. The design of a rainfall network in the catchment of the Feitsui Reservoir was used to illustrate the various steps as well as the reliability of the method.

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Hydrometric network design using streamflow signatures and indicators of hydrologic alteration

Cited by 37 publications

References 26 publications

Assessing Spatial Scale Effects on Hydrometric Network Design Using Entropy and Multi‐objective Methods

Assessing Spatial Scale Effects on Hydrometric Network Design Using Entropy and Multi‐objective Methods

Entropy Applications to Water Monitoring Network Design: A Review

Rainfall Network Optimization Using Radar and Entropy

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