Modelling approach for characterizing thermal stratification and assessing water quality for a large tropical reservoir

The dynamics of water temperature, dissolved oxygen and total dissolved solids concentrations in Aguamilpa Reservoir was analysed by considering horizontal and water column variations. The reservoir model, CE‐QUAL‐W2, was used to simulate the temporal variations calibrated with data gathered every 2...

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Bibliographic Details
Published in:Lakes & Reservoirs : Science, Policy and Management for Sustainable Use Policy and Management for Sustainable Use, 2012-06, Vol.17 (2), p.119-129
Main Authors: Rangel‐Peraza, J. G, Obregon, O, Nelson, J, Williams, G. P, de Anda, J, González‐Farías, F, Miller, J
Format: Article
Language:English
Subjects:
Aguamilpa reservoir
best management practices
CE-QUAL-W2 model
Dissolution
dissolved oxygen
Dynamical systems
Dynamics
Mathematical models
organic matter
Reservoirs
Seasons
soil erosion
Stratification
temperature profiles
thermal stratification
total dissolved solids
tropical reservoir
vegetation
Water quality
water temperature
wet season
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Summary:The dynamics of water temperature, dissolved oxygen and total dissolved solids concentrations in Aguamilpa Reservoir was analysed by considering horizontal and water column variations. The reservoir model, CE‐QUAL‐W2, was used to simulate the temporal variations calibrated with data gathered every 2 months from June 2008 to June 2009. Temperature depth profiles indicated a typical asymmetry of reservoirs exhibiting a large stratification in the lower part near the dam. Dissolved oxygen concentration profiles exhibited some degree of anoxia in the bottom water during the rainy season (May through October). This is most likely due to decomposition vegetation and organic matter via soil erosion and run‐off from the basin accumulating at the bottom of the reservoir. The reservoir stratification is clearly seasonal, occurring during the rainy season, especially in the lowest reservoir zones. The CE‐QUAL‐W2 model results provided a comprehensive understanding of the temporal behaviour of the study variables during the modelling study period. Application of this water quality model is directed to water resource managers to help them better understand the dynamics of physico‐chemical processes, and how they vary temporally and spatially in the reservoir, and to propose the best management practices for preserving or improving the water quality of the system.
ISSN:1320-5331
1440-1770
DOI:10.1111/j.1440-1770.2012.00503.x