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Title: A Multilayer Reservoir Thermal Stratification Module for Earth System Models

Abstract

Thermal stratification in reservoirs is a critical process that regulates downstream riverine energy and biogeochemical cycling. Current stratification models either simplify reservoir geometry or neglecting the effects of reservoir operation. Here we present a new multi-layer reservoir stratification model that can be coupled to earth system models at regional or global scale. With a multi-layer vertical discretization, we introduce a newly developed storage-area-depth dataset to improve parameterization of advection processes in and out of the reservoir. The new model better represents vertical temperature gradient and subsequently temperature of water released to downstream. The stratification model is applied to 1400 reservoirs over the contiguous US and validated against observed surface, profile, and outflow temperature data over 130 reservoirs subjected to various levels of regulation. The Nash-Sutcliffe values are higher than 0.5 for about 77% of the validated reservoirs using surface temperature while the average values of root mean square error and bias are 3.6oC and -1.1oC, respectively. Using the new reservoir storage-area-depth dataset improves the simulation of surface temperature at over 69% of the validated reservoirs compared to using simplified reservoir geometry. The reservoir stratification model contributes to improving predictive understanding of anthropogenic impact on terrestrial hydrological, ecological and biogeochemical cycles.

Authors:
 [1];  [1];  [2]; ORCiD logo [3]; ORCiD logo [3];  [3];  [4]
  1. University of Houston
  2. Auburn University
  3. BATTELLE (PACIFIC NW LAB)
  4. Washington State University
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1581434
Report Number(s):
PNNL-SA-141532
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article
Journal Name:
Journal of Advances in Modeling Earth Systems
Additional Journal Information:
Journal Volume: 11; Journal Issue: 10
Country of Publication:
United States
Language:
English

Citation Formats

Yigzaw, Wondmagegn, Li, Hong-Yi, Fang, Xing, Leung, Lai-Yung, Voisin, Nathalie, Hejazi, Mohamad I., and Demissie, Yonas. A Multilayer Reservoir Thermal Stratification Module for Earth System Models. United States: N. p., 2019. Web. doi:10.1029/2019MS001632.
Yigzaw, Wondmagegn, Li, Hong-Yi, Fang, Xing, Leung, Lai-Yung, Voisin, Nathalie, Hejazi, Mohamad I., & Demissie, Yonas. A Multilayer Reservoir Thermal Stratification Module for Earth System Models. United States. doi:10.1029/2019MS001632.
Yigzaw, Wondmagegn, Li, Hong-Yi, Fang, Xing, Leung, Lai-Yung, Voisin, Nathalie, Hejazi, Mohamad I., and Demissie, Yonas. Tue . "A Multilayer Reservoir Thermal Stratification Module for Earth System Models". United States. doi:10.1029/2019MS001632.
@article{osti_1581434,
title = {A Multilayer Reservoir Thermal Stratification Module for Earth System Models},
author = {Yigzaw, Wondmagegn and Li, Hong-Yi and Fang, Xing and Leung, Lai-Yung and Voisin, Nathalie and Hejazi, Mohamad I. and Demissie, Yonas},
abstractNote = {Thermal stratification in reservoirs is a critical process that regulates downstream riverine energy and biogeochemical cycling. Current stratification models either simplify reservoir geometry or neglecting the effects of reservoir operation. Here we present a new multi-layer reservoir stratification model that can be coupled to earth system models at regional or global scale. With a multi-layer vertical discretization, we introduce a newly developed storage-area-depth dataset to improve parameterization of advection processes in and out of the reservoir. The new model better represents vertical temperature gradient and subsequently temperature of water released to downstream. The stratification model is applied to 1400 reservoirs over the contiguous US and validated against observed surface, profile, and outflow temperature data over 130 reservoirs subjected to various levels of regulation. The Nash-Sutcliffe values are higher than 0.5 for about 77% of the validated reservoirs using surface temperature while the average values of root mean square error and bias are 3.6oC and -1.1oC, respectively. Using the new reservoir storage-area-depth dataset improves the simulation of surface temperature at over 69% of the validated reservoirs compared to using simplified reservoir geometry. The reservoir stratification model contributes to improving predictive understanding of anthropogenic impact on terrestrial hydrological, ecological and biogeochemical cycles.},
doi = {10.1029/2019MS001632},
journal = {Journal of Advances in Modeling Earth Systems},
number = 10,
volume = 11,
place = {United States},
year = {2019},
month = {10}
}

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