Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 5.153
IF5.153
IF 5-year value: 5.460
IF 5-year
5.460
CiteScore value: 7.8
CiteScore
7.8
SNIP value: 1.623
SNIP1.623
IPP value: 4.91
IPP4.91
SJR value: 2.092
SJR2.092
Scimago H <br class='widget-line-break'>index value: 123
Scimago H
index
123
h5-index value: 65
h5-index65
Volume 21, issue 5
Hydrol. Earth Syst. Sci., 21, 2531–2544, 2017
https://doi.org/10.5194/hess-21-2531-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Rainfall and urban hydrology

Hydrol. Earth Syst. Sci., 21, 2531–2544, 2017
https://doi.org/10.5194/hess-21-2531-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 22 May 2017

Research article | 22 May 2017

A gain–loss framework based on ensemble flow forecasts to switch the urban drainage–wastewater system management towards energy optimization during dry periods

Vianney Courdent1,2, Morten Grum1,a, Thomas Munk-Nielsen1, and Peter S. Mikkelsen2 Vianney Courdent et al.
  • 1Krüger Veolia, Søborg, 2860, Denmark
  • 2Department of Environmental Engineering, Technical University of Denmark, Kgs. Lyngby, 2800, Denmark
  • apresent address: WaterZerv, Environmental Services, Denmark

Abstract. Precipitation is the cause of major perturbation to the flow in urban drainage and wastewater systems. Flow forecasts, generated by coupling rainfall predictions with a hydrologic runoff model, can potentially be used to optimize the operation of integrated urban drainage–wastewater systems (IUDWSs) during both wet and dry weather periods. Numerical weather prediction (NWP) models have significantly improved in recent years, having increased their spatial and temporal resolution. Finer resolution NWP are suitable for urban-catchment-scale applications, providing longer lead time than radar extrapolation. However, forecasts are inevitably uncertain, and fine resolution is especially challenging for NWP. This uncertainty is commonly addressed in meteorology with ensemble prediction systems (EPSs). Handling uncertainty is challenging for decision makers and hence tools are necessary to provide insight on ensemble forecast usage and to support the rationality of decisions (i.e. forecasts are uncertain and therefore errors will be made; decision makers need tools to justify their choices, demonstrating that these choices are beneficial in the long run).

This study presents an economic framework to support the decision-making process by providing information on when acting on the forecast is beneficial and how to handle the EPS. The relative economic value (REV) approach associates economic values with the potential outcomes and determines the preferential use of the EPS forecast. The envelope curve of the REV diagram combines the results from each probability forecast to provide the highest relative economic value for a given gain–loss ratio. This approach is traditionally used at larger scales to assess mitigation measures for adverse events (i.e. the actions are taken when events are forecast). The specificity of this study is to optimize the energy consumption in IUDWS during low-flow periods by exploiting the electrical smart grid market (i.e. the actions are taken when no events are forecast). Furthermore, the results demonstrate the benefit of NWP neighbourhood post-processing methods to enhance the forecast skill and increase the range of beneficial uses.

Publications Copernicus
Download
Short summary
Urban drainage and wastewater systems are heavily impacted by precipitation. Hence, weather forecasts are valuable in improving their management. However, forecasts are intrinsically uncertain, especially when fine model resolution is required, which is the case for urban hydrology. Handling uncertainty is challenging for decision makers. This study presents an economic framework to support the decision-making process by providing information on when acting on the forecast is beneficial.
Urban drainage and wastewater systems are heavily impacted by precipitation. Hence, weather...
Citation