Noori, R., Tian, F., Ni, G. et al. ThSSim: A novel tool for simulation of reservoir thermal stratification. Sci Rep 9, 18524 (2019). https://doi.org/10.1038/s41598-019-54433-2
ThSSim : a novel tool for simulation of reservoir thermal stratification
|Author:||Noori, Roohollah1,2; Tian, Fuqiang2; Ni, Guangheng2;|
1School of Environment, College of Engineering, University of Tehran, Tehran, 1417853111, Iran
2Department of Hydraulic Engineering, State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing, 100084, China
3Department of Agricultural and Biological Engineering, University of Illinois at Urbana Champaign, 1304W Pennsylvania Ave, Urbana, IL, 61801, USA
4Department of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, 1477893855, Iran
5Water, Energy and Environmental Engineering Research Unit, University of Oulu, PO Box 4300, 90014, Finland, Oulu, Finland
|Online Access:||PDF Full Text (PDF, 3.3 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe202002185663
|Publish Date:|| 2020-02-18
This study presents a novel tool, ThSSim, for simulation of thermal stratification (ThS) in reservoirs. ThSSim is a simple and flexible reduced-order model-based the basis function (RMBF) that combines CE-QUAL-W2 (W2) and proper orthogonal decomposition (POD). In a case study, it was used to simulate water temperature in the Karkheh Reservoir (KR), Iran, for the period 2019–2035. ThSSim consists of two space- and time-dependent components that add predictive ability to the RMBF, a major refinement that extends its practical applications. Water temperature simulations by the W2 model at three-hour time intervals for the KR were used as input data to the POD model to develop ThSSim. To add predictive ability to ThSSim and considering that space-dependent components are not a function of time, we extrapolated the first three time-dependent components by September 30, 2035. We checked the predictive ability of ThSSim against water temperature profiles measured during eight sampling campaigns. We then applied ThSSim to simulate water temperature in the KR for 2019–2035. Simulated water temperature values matched well those measured and obtained by W2. ThSSim results showed an increasing trend for surface water temperature during the simulation period, with a reverse trend observed for water temperature in the bottom layers for three seasons (spring, summer and autumn). The results also indicated decreasing and increasing trends in onset and breakdown of thermal stability, respectively, so that the duration of ThS increased from 278 days in 2019 to 293 days in 2035. ThSSim is thus useful for reservoir temperature simulations. Moreover, the approach used to develop ThSSim is widely applicable to other fields of science and engineering.
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
218 Environmental engineering
This research was funded by the Department of Hydraulic Engineering, State Key Laboratory of Hydroscience and Engineering, Tsinghua University, China. The authors also gratefully acknowledge the Iran Water Resources Management Company for cooperation in data preparation.
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