Biological and Environmental Research - Earth and Environmental System Sciences
Earth and Environmental System Modeling

A Multilayer Reservoir Thermal Stratification Module for Earth System Models

TitleA Multilayer Reservoir Thermal Stratification Module for Earth System Models
Publication TypeJournal Article
Year of Publication2019
AuthorsYigzaw, Wondmagegn, Li Hong-Yi, Fang Xing, L. Leung Ruby, Voisin Nathalie, Hejazi Mohamad I., and Demissie Yonas
JournalJournal of Advances in Modeling Earth Systems
Volume11
Number10
Pages3265-3283
Abstract / Summary

Thermal stratification in reservoirs is a critical process that regulates downstream riverine energy and biogeochemical cycling. Current stratification models either simplify vertical energy process, reservoir geometry or neglecting the effects of reservoir operation. Here we present a new multilayer reservoir stratification model that can be applied for reservoir and stream temperature simulation at regional or global scale. With a multilayer 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 1,400 reservoirs over the contiguous United States 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 3.6 °C and −1.1 °C, 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.

URLhttp://dx.doi.org/10.1029/2019ms001632
DOI10.1029/2019ms001632
Funding Program: 
Journal: Journal of Advances in Modeling Earth Systems
Year of Publication: 2019
Volume: 11
Number: 10
Pages: 3265-3283
Publication Date: 10/2019

Thermal stratification in reservoirs is a critical process that regulates downstream riverine energy and biogeochemical cycling. Current stratification models either simplify vertical energy process, reservoir geometry or neglecting the effects of reservoir operation. Here we present a new multilayer reservoir stratification model that can be applied for reservoir and stream temperature simulation at regional or global scale. With a multilayer 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 1,400 reservoirs over the contiguous United States 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 3.6 °C and −1.1 °C, 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
Citation:
Yigzaw, W, H Li, X Fang, L Leung, N Voisin, M Hejazi, and Y Demissie.  2019.  "A Multilayer Reservoir Thermal Stratification Module for Earth System Models."  Journal of Advances in Modeling Earth Systems 11(10): 3265-3283.  https://doi.org/10.1029/2019ms001632.