A linked hydrodynamic and water quality model for the Salton Sea

Abstract

A linked hydrodynamic and water quality model was developed and applied to the Salton Sea. The hydrodynamic component is based on the onedimensional numerical model, DLM. The water quality model is based on a new conceptual model for nutrient cycling in the Sea, and simulates temperature, total suspended sediment concentration, nutrient concentrations, including PO À3 4 ; NO À1 3 and NH þ1 4 ; DO concentration and chlorophyll a concentration as functions of depth and time. Existing water temperature data from 1997 were used to verify that the model could accurately represent the onset and breakup of thermal stratification. 1999 is the only year with a near-complete dataset for water quality variables for the Salton Sea. The linked hydrodynamic and water quality model was run for 1999, and by adjustment of rate coefficients and other water quality parameters, a good match with the data was obtained. In this article, the model is fully described and the model results for reductions in external phosphorus load on chlorophyll a distribution are presented.

Relative Performance of 1-D Versus 3-D Hydrodynamic, Water-Quality Models for Predicting Water Temperature and Oxygen in a Shallow, Eutrophic, Managed Reservoir

“…GLM adopts a 1-D approach that resolves a series of horizontal layers [32], with core layer and mixing algorithms similar to the dynamic reservoir simulation model (DYRESM) [1] and the dynamic lake model (DLM) [37]. This approach defines each layer as a 'control volume' that can contract or expand in response to inflows/outflows and mixing with adjacent layers.…”

A General Lake Model (GLM 2.4) for linking with high-frequency sensor data from the Global Lake Ecological Observatory Network (GLEON)

“…The model is suitable for operation in a wide range of climate conditions and is able to simulate ice formation, as well as accommodating a range of atmospheric forcing conditions. Although GLM is a new model code written in the C programming language, the core layer structure and mixing algorithms is founded on principles and experience from model platforms including the Dynamic Reservoir Simulation Model 20 (DYRESM;Imberger and Patterson, 1981;Hamilton and Schladow, 1997) and the Dynamic Lake Model (DLM; Chung et al, 2008). Other variations have been introduced to extend this underlying approach through applications to a variety of lake and reservoir environments, to which the reader is also referred (e.g., Hocking & Patterson, 1991;McCord & Schladow, 1998;Gal et al, 2003;Yeates and Imberger, 2003).…”

Inflow–outflow boundary conditions along arbitrary directions in Cartesian lake models

“…Given that river inflows represent one of the major sources of nutrients to river valley reservoirs (Kennedy, 1999), inflow angles might also be important in determining the ecosystem response. In the uncertainty analysis conducted by Ayala et al (2014) in Lake Béznar with a one-dimensional lake model , Chung et al, 2008, the initial mixing ratio was allowed to vary randomly within the range of values reported in the literature, from 1 to 4 (Ayala et al, 2014). The model in that work was used to simulate the fate of river inflows and the loads of river-borne nutrients (phosphorus, in particular) in the surface mixed-layer SML during a period of 180 days in 2010.…”