EGU2020-4756
https://doi.org/10.5194/egusphere-egu2020-4756
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Stochastic simulation of water demands within water resources management

Ioannis Michail Bairaktaris, Anastasios Lemonis, Emmanouil Mantzouranis, Georgios Rontiris, Dionysios Nikolopoulos, Panagiotis Kossieris, Ioannis Tsoukalas, and Andreas Efstratiadis
Ioannis Michail Bairaktaris et al.
  • National Technical University of Athens, School of Civil Engineering , Department of Water Resources and Environment , Greece (april18g@hotmail.com)

Traditionally, the use of stochastic models within water resources management aim to provide synthetically-generated inflow time series that reproduce the statistical regime of the historical data. On the other hand, the water uses are typically handled as steady-state elements, which follow a constant seasonal pattern over the entire simulation horizon. However, given that the demands are associated with highly uncertain hydroclimatic and socioeconomic factors, they should also be considered as random variables, as made for inflows. Using as example a complex hydrosystem in Western Thessaly, Greece, comprising both surface and groundwater resources to serve irrigation, water supply, environmental and hydroelectric uses, we demonstrate the advantages of a fully stochastic setting of the water management problem over its traditional configuration. Among others, we investigate the use of synthetic demands that are correlated with inflows, given that both are driven by hydroclimatic processes. Data syntheses are employed with the recently introduced AnySim stochastic simulation package (https://www.itia.ntua.gr/en/softinfo/33/).

How to cite: Bairaktaris, I. M., Lemonis, A., Mantzouranis, E., Rontiris, G., Nikolopoulos, D., Kossieris, P., Tsoukalas, I., and Efstratiadis, A.: Stochastic simulation of water demands within water resources management, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4756, https://doi.org/10.5194/egusphere-egu2020-4756, 2020

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