A review of water quality models and monitoring methods for capabilities of pollutant source identification, classification, and transport simulation

Talukdar, P.; Kumar, Bimlesh; Kulkarni, Vihangraj V.

doi:10.1007/s11157-023-09658-z

Cited by 5 publications

(4 citation statements)

References 114 publications

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“…The study area is divided into the following subareas, based on bottom morphology: (i) Elefsis Bay, connected with the adjacent sub-basins through two narrow and shallow straits, located in the west (Megara strait) and the southeast (Keratsini strait), (ii) eastern Saronikos basin that is further divided into the inner Saronikos to the north and the outer Saronikos to the southeast, from where the gulf connects with the Aegean Sea, and (iii) western Saronikos Gulf (Table S1). The network of monitoring stations (S1, S2, S3, S7, S8, S11, S13, S16, S18, S43) as implemented in the framework of the action 'Monitoring of the Saronikos Gulf ecosystem under the influence of the Psittalia sewage outflow' [21], as well as the sources of pollution (1)(2)(3)(4)(5)(6)(7)(8)(9), are displayed in Figure 1b. Five trace elements were chosen to set up and validate a water quality model configuration: cadmium (Cd), lead (Pb), nickel (Ni), copper (Cu), and zinc (Zn).…”

Section: Study Area and Target Compoundsmentioning

confidence: 99%

“…Copper [g m −3 ] Nickel [g m −3 ] Lead [g m −3 ] Zinc [g m −3 3 Special Secretariat for Water, WWTP monitoring database [43], 4 according to the company's published data [46] and published methodology for estimation [47], 5 according to the company's published data [48] and published methodology for estimation [47], 6…”

Section: Cadmiummentioning

confidence: 99%

“…Otherwise, the settling rate is equal to zero. The settling flux (F set ) depends on the concentration of the substance and is calculated according to Equations ( 4) and (5).…”

Section: Trace Element Settlingmentioning

confidence: 99%

“…Water quality modeling is an implementation moving towards that direction, used in various applications and for all types of aquatic environments [4]. Some fields in which water quality models are used are: human health protection from pathogen pollution [5]; prediction of eutrophication [6]; prediction and investigation of chemical pollution, including heavy metals [7], emerging contaminants, and antibiotics [8,9]; antibiotic resistance of aquatic environments [10]; and many others. The most crucial and valuable usage of water quality modeling as a tool is the provision of support for the development of policies and environmental management strategies [11,12].…”

Section: Introductionmentioning

confidence: 99%

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Implementation of a Far-Field Water Quality Model for the Simulation of Trace Elements in an Eastern Mediterranean Coastal Embayment Receiving High Anthropogenic Pressure

Mazioti,

Kolovoyiannis,

Krasakopoulou

et al. 2024

JMSE

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Water quality modeling is a key element for the support of environmental protection and policymaking. The aim of this work is to describe the application of a far-field water quality model for the simulation of marine pollution occurring from heavy metals (cadmium, lead, nickel, copper, and zinc). The highly stressed marine area of the Saronikos Gulf (Aegean Sea, Eastern Mediterranean) was chosen for investigation. Major pollution sources were identified, loads were estimated, and the model was parameterized to reproduce the local seawater conditions. The distribution of the pollutants between the dissolved and particulate phases was examined. The performance of the model set-up was evaluated using field concentration measurements. The described implementation succeeded in reproducing the observed levels of pollution and therefore can be used as a baseline configuration to examine the cumulative impact of future pollution sources; for example, accidental pollution events.

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Section: Study Area and Target Compoundsmentioning

confidence: 99%

Section: Cadmiummentioning

confidence: 99%

“…Otherwise, the settling rate is equal to zero. The settling flux (F set ) depends on the concentration of the substance and is calculated according to Equations ( 4) and (5).…”

Section: Trace Element Settlingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Implementation of a Far-Field Water Quality Model for the Simulation of Trace Elements in an Eastern Mediterranean Coastal Embayment Receiving High Anthropogenic Pressure

Mazioti,

Kolovoyiannis,

Krasakopoulou

et al. 2024

JMSE

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A hybrid approach to improvement of watershed water quality modeling by coupling process–based and deep learning models

Jeong,

Kim

et al. 2024

Water Environment Research

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Watershed water quality modeling to predict changing water quality is an essential tool for devising effective management strategies within watersheds. Process‐based models (PBMs) are typically used to simulate water quality modeling. In watershed modeling utilizing PBMs, it is crucial to effectively reflect the actual watershed conditions by appropriately setting the model parameters. However, parameter calibration and validation are time‐consuming processes with inherent uncertainties. Addressing these challenges, this research aims to address various challenges encountered in the calibration and validation processes of PBMs. To achieve this, the development of a hybrid model, combining uncalibrated PBMs with data‐driven models (DDMs) such as deep learning algorithms is proposed. This hybrid model is intended to enhance watershed modeling by integrating the strengths of both PBMs and DDMs. The hybrid model is constructed by coupling an uncalibrated Soil and Water Assessment Tool (SWAT) with a Long Short‐Term Memory (LSTM). SWAT, a representative PBM, is constructed using geographical information and 5‐year observed data from the Yeongsan River Watershed. The output variables of the uncalibrated SWAT, such as streamflow, suspended solids (SS), total nitrogen (TN), and total phosphorus (TP), as well as observed precipitation for the day and previous day, are used as training data for the deep learning model to predict the TP load. For the comparison, the conventional SWAT model is calibrated and validated to predict the TP load. The results revealed that TP load simulated by the hybrid model predicted the observed TP better than that predicted by the calibrated SWAT model. Also, the hybrid model reflects seasonal variations in the TP load, including peak events. Remarkably, when applied to other sub‐basins without specific training, the hybrid model consistently outperformed the calibrated SWAT model. In conclusion, application of the SWAT‐LSTM hybrid model could be a useful tool for decreasing uncertainties in model calibration and improving the overall predictive performance in watershed modeling.Practitioner points We aimed to enhance process‐based models for watershed water‐quality modeling. The Soil and Water Assessment Tool‐Long Short‐Term Memory hybrid model's predicted and total phosphorus (TP) matched the observed TP. It exhibited superior predictive performance when applied to other sub‐basins. The hybrid model will overcome the constraints of conventional modeling. It will also enable more effective and efficient modeling.

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A real-time simulation model of water quality with the impact of internal pollution for water source reservoir

Zhang,

et al. 2024

Environ Sci Pollut Res

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A review of water quality models and monitoring methods for capabilities of pollutant source identification, classification, and transport simulation

Cited by 5 publications

References 114 publications

Implementation of a Far-Field Water Quality Model for the Simulation of Trace Elements in an Eastern Mediterranean Coastal Embayment Receiving High Anthropogenic Pressure

Implementation of a Far-Field Water Quality Model for the Simulation of Trace Elements in an Eastern Mediterranean Coastal Embayment Receiving High Anthropogenic Pressure

A hybrid approach to improvement of watershed water quality modeling by coupling process–based and deep learning models

A real-time simulation model of water quality with the impact of internal pollution for water source reservoir

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