scholarly journals Improving In-Stream Nutrient Routines in Water Quality Models Using Stable Isotope Tracers: A Review and Synthesis

2018 ◽  
Vol 61 (1) ◽  
pp. 139-157 ◽  
Author(s):  
Alexandria Jensen ◽  
William Ford ◽  
James Fox ◽  
Admin Husic
Keyword(s):  
Water Quality ◽  
Stable Isotopes ◽  
Stable Isotope ◽  
Water Quality Modeling ◽  
Water Quality Model ◽  
Model Structure ◽  
Quality Model ◽  
Quality Models ◽  
Stable Isotope Signatures ◽  
Water Quality Models

Abstract. Water quality models serve as an economically feasible alternative to quantify fluxes of nutrient pollution and to simulate effective mitigation strategies; however, their applicability is often questioned due to broad uncertainties in model structure and parameterization, leading to uncertain outputs. We argue that reduction of uncertainty is partially achieved by integrating stable isotope data streams within the water quality model architecture. This article outlines the use of stable isotopes as a response variable within water quality models to improve the model boundary conditions associated with nutrient source provenance, constrain model parameterization, and elucidate shortcomings in the model structure. To assist researchers in future modeling efforts, we provide an overview of stable isotope theory; review isotopic signatures and applications for relevant carbon, nitrogen, and phosphorus pools; identify biotic and abiotic processes that impact isotope transfer between pools; review existing models that have incorporated stable isotope signatures; and highlight recommendations based on synthesis of existing knowledge. Broadly, we find existing applications that use isotopes have high efficacy for reducing water quality model uncertainty. We make recommendations toward the future use of sediment stable isotope signatures, given their integrative capacity and practical analytical process. We also detail a method to incorporate stable isotopes into multi-objective modeling frameworks. Finally, we encourage watershed modelers to work closely with isotope geochemists to ensure proper integration of stable isotopes into in-stream nutrient fate and transport routines in water quality models. Keywords: Isotopes, Nutrients, Uncertainty analysis, Water quality modeling, Watershed.

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

Water ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 88
Author(s):  
Xiamei Man ◽  
Chengwang Lei ◽  
Cayelan C. Carey ◽  
John C. Little
Keyword(s):  
Water Quality ◽  
Water Temperature ◽  
Water Quality Model ◽  
Relative Performance ◽  
Bubble Plume ◽  
Quality Model ◽  
Quality Models ◽  
Management Interventions ◽  
Water Quality Models ◽  
D Model

Many researchers use one-dimensional (1-D) and three-dimensional (3-D) coupled hydrodynamic and water-quality models to simulate water quality dynamics, but direct comparison of their relative performance is rare. Such comparisons may quantify their relative advantages, which can inform best practices. In this study, we compare two 1-year simulations in a shallow, eutrophic, managed reservoir using a community-developed 1-D model and a 3-D model coupled with the same water-quality model library based on multiple evaluation criteria. In addition, a verified bubble plume model is coupled with the 1-D and 3-D models to simulate the water temperature in four epilimnion mixing periods to further quantify the relative performance of the 1-D and 3-D models. Based on the present investigation, adopting a 1-D water-quality model to calibrate a 3-D model is time-efficient and can produce reasonable results; 3-D models are recommended for simulating thermal stratification and management interventions, whereas 1-D models may be more appropriate for simpler model setups, especially if field data needed for 3-D modeling are lacking.

Identifiability analysis of the CSTR river water quality model

2006 ◽  
Vol 53 (1) ◽  
pp. 93-99 ◽  
Author(s):  
J. Chen ◽  
Y. Deng
Keyword(s):  
Water Quality ◽  
River Water ◽  
Sampling Frequency ◽  
Water Quality Model ◽  
River Water Quality ◽  
Quality Model ◽  
Identifiability Analysis ◽  
Quality Models ◽  
Observational Errors ◽  
Water Quality Models

Conceptual river water quality models are widely known to lack identifiability. The causes for that can be due to model structure errors, observational errors and less frequent samplings. Although significant efforts have been directed towards better identification of river water quality models, it is not clear whether a given model is structurally identifiable. Information is also limited regarding the contribution of different unidentifiability sources. Taking the widely applied CSTR river water quality model as an example, this paper presents a theoretical proof that the CSTR model is indeed structurally identifiable. Its uncertainty is thus dominantly from observational errors and less frequent samplings. Given the current monitoring accuracy and sampling frequency, the unidentifiability from sampling frequency is found to be more significant than that from observational errors. It is also noted that there is a crucial sampling frequency between 0.1 and 1 day, over which the simulated river system could be represented by different illusions and the model application could be far less reliable.

On the effect of scaling conceptual model complexity on stochastic response for water quality modeling

2011 ◽  
Vol 63 (2) ◽  
pp. 360-366
Author(s):  
G. T. Parker
Keyword(s):  
Water Quality ◽  
Conceptual Model ◽  
Water Quality Modeling ◽  
Response Surfaces ◽  
Model Complexity ◽  
Quality Model ◽  
Real World Data ◽  
Quality Models ◽  
Modelling Framework ◽  
Water Quality Models

This paper extends previous work comparing the response of water quality models under uncertainty. A new model, the River Water Quality Model no. 1 (RWQM1), is compared to the previous work of two commonly used water quality models. Additionally, the effect of conceptual model scaling within a single modelling framework, as allowed by RWQM1, is explored under uncertainty. Model predictions are examined using against real-world data for the Potomac River with a Generalized Likelihood Uncertainty Estimation used to assess model response surfaces to uncertainty. Generally, it was found that there are tangible model characteristics that are closely tied to model complexity and thresholds for these characteristics were discussed. The novel work has yielded an illustrative example but also a conceptually scaleable water quality modelling tool, alongside defined metrics to assess when scaling is required under uncertainty. The resulting framework holds substantial, unique, promise for a new generation of modelling tools that are capable of addressing classically intractable problems.

Modelling of cyanobacterial blooms in the mixed layer of lakes and reservoirs

1994 ◽  
Vol 45 (5) ◽  
pp. 829 ◽  
Author(s):  
JC Patterson ◽  
DP Hamilton ◽  
JM Ferris
Keyword(s):  
Water Quality ◽  
Growth Rate ◽  
Functional Form ◽  
Water Quality Model ◽  
Cyanobacterial Blooms ◽  
Quality Model ◽  
Quality Models ◽  
Photosynthesis Model ◽  
Lakes And Reservoirs ◽  
Water Quality Models

The chemical and biological components of existing water quality models are in general described by simple first-order rate equations in which the production and uptake coefficients are fixed functions of the other variables of the model. Thus although, for example, in a photosynthesis model the specific algal growth rate may be a function of light intensity, nutrient concentration and temperature, the form of this dependence on these variables is assumed to be fixed. In this paper, the effect on the performance of a water quality model of removing this assumption for the specific case of photosynthesis is examined. An existing coupled motion-photosynthesis model has been installed in the water quality model DYRESM-WQ and the result compared with the original model, which assumes a fixed functional dependence. The resulting model has been applied to two reservoirs, without recalibration. The result shows that the removal of the assumption of a fixed functional form for the photosynthetic growth rate may have a significant effect on the magnitude and timing of predicted cyanobacterial blooms in lakes and reservoirs, which would have important implications for reservoir and lake management. In addition, the result suggests that, in general, the validity of the assumption of fixed functional form for the rate coefficients in water quality models is not assured.

scholarly journals Environmental Flow for Sungai Johor Estuary

2018 ◽  
Vol 34 ◽  
pp. 02041
Author(s):  
A.Kadir Adilah ◽  
Yusop Zulkifli ◽  
Z. Noor Zainura ◽  
Baharim N. Bakhiah
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
Water Temperature ◽  
Oxygen Demand ◽  
Correlation Coefficients ◽  
Water Quality Model ◽  
Surface Elevation ◽  
Quality Model ◽  
Quality Models ◽  
Water Quality Models

Sungai Johor estuary is a vital water body in the south of Johor and greatly affects the water quality in the Johor Straits. In the development of the hydrodynamic and water quality models for Sungai Johor estuary, the Environmental Fluid Dynamics Code (EFDC) model was selected. In this application, the EFDC hydrodynamic model was configured to simulate time varying surface elevation, velocity, salinity, and water temperature. The EFDC water quality model was configured to simulate dissolved oxygen (DO), dissolved organic carbon (DOC), chemical oxygen demand (COD), ammoniacal nitrogen (NH3-N), nitrate nitrogen (NO3-N), phosphate (PO4), and Chlorophyll a. The hydrodynamic and water quality model calibration was performed utilizing a set of site specific data acquired in January 2008. The simulated water temperature, salinity and DO showed good and fairly good agreement with observations. The calculated correlation coefficients between computed and observed temperature and salinity were lower compared with the water level. Sensitivity analysis was performed on hydrodynamic and water quality models input parameters to quantify their impact on modeling results such as water surface elevation, salinity and dissolved oxygen concentration. It is anticipated and recommended that the development of this model be continued to synthesize additional field data into the modeling process.

Parameter identification of river water quality models using a genetic algorithm

2013 ◽  
Vol 69 (4) ◽  
pp. 687-693 ◽  
Author(s):  
Xiaodong Liu ◽  
Yuanyuan Zhou ◽  
Zulin Hua ◽  
Kejian Chu ◽  
Peng Wang ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Water Quality ◽  
Parameter Identification ◽  
River Water ◽  
Unsteady Flows ◽  
Water Quality Model ◽  
River Water Quality ◽  
Quality Model ◽  
Quality Models ◽  
Water Quality Models

For solving the multi-parameter identification problem of a river water quality model, analytical methods for solving a river water quality model and traditional optimization algorithms are very difficult to implement. A new parameter identification model based on a genetic algorithm (GA) coupled with finite difference method (FDM) was constructed for the determination of hydraulic and water quality parameters such as the longitudinal dispersion coefficient, the pollutant degradation coefficient, velocity, etc. In this model, GA is improved to promote convergence speed by adding the elite replacement operator after the mutation operator, and FDM is applied for unsteady flows. Moreover the influence of observation noise on identified parameters was discussed for the given model. The method was validated by two numerical cases (in steady and unsteady flows respectively) and one practical application. The computational results indicated that the model could give good identification precision results and showed good anti-noise abilities for water quality models when the noise level ≤10%.

scholarly journals Water Quality Modeling of Bhima River by using HEC-RAS Software

2020 ◽  
Vol 9 (3) ◽  
pp. 2886-2889
Keyword(s):  
Water Quality ◽  
River Water ◽  
Hydrodynamic Model ◽  
Algal Blooms ◽  
Agricultural Runoff ◽  
Water Quality Modeling ◽  
Water Quality Model ◽  
River Water Quality ◽  
Water Levels ◽  
Quality Model

The River has got religious importance in India. The Bhima River is beginning from Bhimashankar hill and it flows through some parts of Maharashtra and Karnataka state. The assessment of water quality for the development of the places near the bank of River is important. These is controlled by various manmade activities. The quality of river water resources is facing problems because of the continuous agricultural runoff, development and urbanization. Due to mixing of nutrients causes algal blooms, which results eutrophication. The modeling of water quality can be deliberated as useful tool for assessing river water. Bhima River is demarcated as a major and important water body located in Pandharpur, dist. Solapur, Maharashtra. As Pandharpur is having historical background and known as one of the famous Holly places in Maharashtra, this place is facing huge population fluctuation due to migrated pilgrims and rapid growth of urbanization. These two things detrimentally affect River water quality. The main objective of current study was to develop a hydrodynamic model combined with river water quality model for the Bhima River to measure and recognize the processes harmful for the River. For Bhima River a hydrodynamic model was constructed using the HEC-RAS 4.1 software combined with a river water quality model to estimate the amount, distribution and sources of algae, nitrate and temperature. The river model has standardized with the help of previous water levels near the Pandharpur region. It has standardized and calibrated for the assessed parameters by competing them with the present data. The result showed a relationship between DO and temperature range. DO level in Pandharpur and Gopalpur were observed to be fluctuating with respective temperature and during Vari season. However, wastewater discharge from Nalha in sample station 3 i.e. Goplapur shows slit changes in DO and due to this there is necessity to learn other parameters also.

scholarly journals Benchmarking the efficiency of a metamodeling-enabled algorithm for the calibration of surface water quality models

2020 ◽  
Vol 22 (6) ◽  
pp. 1718-1726
Author(s):  
K. Kandris ◽  
E. Romas ◽  
A. Tzimas
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Surface Water Quality ◽  
Water Quality Modeling ◽  
Automatic Calibration ◽  
High Fidelity ◽  
Quality Models ◽  
Derivative Free Optimization ◽  
Tangible Evidence ◽  
Water Quality Models

Abstract Computational efficiency is a major obstacle imposed in the automatic calibration of numerical, high-fidelity surface water quality models. To surpass this obstacle, the present work formulated a metamodeling-enabled algorithm for the calibration of surface water quality models and assessed the computational gains from this approach compared to a benchmark alternative (a derivative-free optimization algorithm). A radial basis function was trained over multiple snapshots of the original high-fidelity model to emulate the latter's behavior. This data-driven proxy of the original model was subsequently employed in the automatic calibration of the water quality models of two water reservoirs and, finally, the computational gains over the benchmark alternative were estimated. The benchmark analysis revealed that the metamodeling-enabled optimizer reached a solution with the same quality compared to its benchmark alternative in 20–38% lower process times. Thereby, this work manifests tangible evidence of the potential of metamodeling-enabled strategies and sets out a discussion on how to maximize computational gains deriving from such strategies in surface water quality modeling.

Steady State and Time-Varying Water Quality Models for the Hooghly Estuary, India

1986 ◽  
Vol 18 (4-5) ◽  
pp. 257-265 ◽  
Author(s):  
S. K. Bose ◽  
B. K. Dutta
Keyword(s):  
Water Quality ◽  
Steady State ◽  
Time Varying ◽  
Quality Model ◽  
Quality Models ◽  
System Parameters ◽  
Hooghly Estuary ◽  
Advection Diffusion ◽  
Ground Slope ◽  
Water Quality Models

Steady state and time-varying water quality models for the Hooghly estuary have been developed for the 92.5 km stretch from Tribeni to Mayapur. A hydraulic model of the estuary was previously developed in this connection, based on a simulated channel of trapezoidal cross-section, gradually increasing downstream, and with uniform ground slope. The estuary has also been assumed to be section-ally homogeneous in each of the thirty-seven sections. The advection-diffusion equations have been numerically integrated to compute the instantaneous and time-averaged distribution of BOD and DO. The monthly averages of the quantities over the year have also been determined. The different system parameters have been estimated using available equations and correlations. The calculated BOD and DO values agree reasonably well with the available field data. The study shows that a water quality model based on simulated channel geometry may work well and is useful where a more rigorous hydrodynamic model is difficult to construct and verify.

Sign in / Sign up

Export Citation Format

Share Document