Articles | Volume 24, issue 5
https://doi.org/10.5194/hess-24-2235-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-24-2235-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Optimal design of hydrometric station networks based on complex network analysis
Ankit Agarwal
CORRESPONDING AUTHOR
GFZ German Research Centre for Geosciences, Section 4.4: Hydrology,
Telegrafenberg, Potsdam, 14473 Germany
Institute for Environmental Sciences and Geography, University of
Potsdam, Potsdam, 14476 Germany
Complexity Science research department, Potsdam Institute for Climate
Impact Research, Member of the Leibniz Association, Telegrafenberg, Potsdam,
14473 Germany
Department of Hydrology, Indian Institute of Technology Roorkee, Roorkee,
247667, India
Norbert Marwan
Complexity Science research department, Potsdam Institute for Climate
Impact Research, Member of the Leibniz Association, Telegrafenberg, Potsdam,
14473 Germany
Rathinasamy Maheswaran
Department of Civil Engineering, MVGR College of Engineering,
Vizianagaram, 535005, India
Ugur Ozturk
Institute for Environmental Sciences and Geography, University of
Potsdam, Potsdam, 14476 Germany
Jürgen Kurths
Institute for Environmental Sciences and Geography, University of
Potsdam, Potsdam, 14476 Germany
Complexity Science research department, Potsdam Institute for Climate
Impact Research, Member of the Leibniz Association, Telegrafenberg, Potsdam,
14473 Germany
Bruno Merz
GFZ German Research Centre for Geosciences, Section 4.4: Hydrology,
Telegrafenberg, Potsdam, 14473 Germany
Institute for Environmental Sciences and Geography, University of
Potsdam, Potsdam, 14476 Germany
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37 citations as recorded by crossref.
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36 citations as recorded by crossref.
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- Integrating multi-criteria decision analysis (MCDA) with kriging and entropy methods for optimising streamflow measurement in a scantly monitored river basin G. Weldearegay et al. 10.1080/15715124.2023.2286893
- Quantile-based Bayesian Model Averaging approach towards merging of precipitation products K. Yumnam et al. 10.1016/j.jhydrol.2021.127206
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- Collective behavior in a two-layer neuronal network with time-varying chemical connections that are controlled by a Petri net A. Bahramian et al. 10.1063/5.0045840
- Spatial organization of connectivity in functional climate networks describing event synchrony of heavy precipitation F. Wolf & R. Donner 10.1140/epjs/s11734-021-00166-1
- Site Selection for a Network of Weather Stations Using AHP and Near Analysis in a GIS Environment in Amazonas, NW Peru N. Rojas Briceño et al. 10.3390/cli9120169
- A modified extreme event-based synchronicity measure for climate time series M. Gao et al. 10.1063/5.0131133
- A multi-node attack scheme based on community partitioning in large scale infrastructure networks B. Li & W. Hu 10.1016/j.comnet.2024.110386
- Spatio-temporal connections in streamflow: a complex networks-based approach N. Yasmin & B. Sivakumar 10.1007/s00477-021-02022-z
- Inter-Comparison of Gauge-Based Gridded Data, Reanalysis and Satellite Precipitation Product with an Emphasis on Hydrological Modeling S. Setti et al. 10.3390/atmos11111252
- A complex network theoretic approach for interdependence investigation: An application to radionuclide behavior in the subsurface B. Narayanan et al. 10.1016/j.cageo.2021.104913
- Canonical correlation and visual analytics for water resources analysis A. Bybordi et al. 10.1007/s11042-023-16926-1
- Synchronized Structure and Teleconnection Patterns of Meteorological Drought Events over the Yangtze River Basin, China L. Liu et al. 10.3390/w15213707
- Investigating the spatial propagation patterns of meteorological drought events and underlying mechanisms using complex network theory: A case study of the Yangtze River Basin, China L. Liu et al. 10.1007/s00382-024-07322-y
- Multi-scale investigation on streamflow temporal variability and its connection to global climate indices for unregulated rivers in India P. Yeditha et al. 10.2166/wcc.2021.189
- An Extended Triple Collocation Method With Maximized Correlation for Near Global‐Land Precipitation Fusion L. Wei et al. 10.1029/2023GL105120
- Spatial propagation of different drought types and their concurrent societal risks: A complex networks-based analysis D. Muthuvel & B. Sivakumar 10.1016/j.jhydrol.2024.131247
- Spatiotemporal evolution patterns and underlying formation mechanisms of monsoon rainfall across eastern China: A complex network perspective L. Liu et al. 10.1016/j.atmosres.2024.107363
- Evaluation of the performance of satellite products and microphysical schemes with the aim of forecasting early flood warnings in arid and semi-arid regions (a case study of northeastern Iran) R. Sarvestan et al. 10.1007/s11069-024-06689-9
- Forecasting of extreme flood events using different satellite precipitation products and wavelet-based machine learning methods P. Yeditha et al. 10.1063/5.0008195
- Catchment classification using community structure concept: application to two large regions S. Tumiran & B. Sivakumar 10.1007/s00477-020-01936-4
- Identifying Potential Locations of Hydrologic Monitoring Stations Based on Topographical and Hydrological Information A. Singhal et al. 10.1007/s11269-023-03675-x
- Multiscale investigation of precipitation extremes over Ethiopia and teleconnections to large-scale climate anomalies T. Beyene et al. 10.1007/s00477-021-02120-y
- Framework for developing IDF curves using satellite precipitation: a case study using GPM-IMERG V6 data K. Venkatesh et al. 10.1007/s12145-021-00708-0
- Improving the predictability of compound dry and hot extremes through complexity science R. Guntu & A. Agarwal 10.1088/1748-9326/ad0c0c
- Networks behind the morphology and structural design of living systems M. Gosak et al. 10.1016/j.plrev.2022.03.001
- Network-based exploration of basin precipitation based on satellite and observed data M. Gadhawe et al. 10.1140/epjs/s11734-021-00017-z
- Flow regionalization using precipitation data from different bases as a predictive variable S. Pinheiro et al. 10.1016/j.pce.2023.103516
1 citations as recorded by crossref.
Latest update: 14 Nov 2024
Short summary
In the climate/hydrology network, each node represents a geographical location of climatological data, and links between nodes are set up based on their interaction or similar variability. Here, using network theory, we first generate a node-ranking measure and then prioritize the rain gauges to identify influential and expandable stations across Germany. To show the applicability of the proposed approach, we also compared the results with existing traditional and contemporary network measures.
In the climate/hydrology network, each node represents a geographical location of climatological...