Review of Mathematical Models of Water Quality

Ziemińska‐Stolarska, Aleksandra; Skrzypski, J.

doi:10.2478/v10216-011-0015-x

Cited by 19 publications

(27 citation statements)

References 10 publications

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“…Water is one of the key elements of the environment that determines the survival of life and restricts the socio-economic growth of the people (Stolarska & Skrzypski, 2012). Overseas and inland surface and sub-surface water systems play an incredible role in everyday life activities mainly for drinking, agricultural, industrial, recreational, and other public uses.…”

Section: Introductionmentioning

confidence: 99%

“…Some industrial, agricultural, and human activities have a serious effect on ecological diversity. In addition, surface water quality depends on natural phenomena; the quality of water in lakes and dams is suffering from incessant degradation due to natural processes resulting from eutrophication and anthropogenic causes (Stolarska & Skrzypski, 2012).…”

Section: Introductionmentioning

confidence: 99%

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Overview of water quality modeling

Ejigu

2021

Cogent Engineering

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Due to population growth, urbanization, and industrialization, water demands have increased, and the quality of water is degraded. Water quality modeling is a significant tool that aids managers and policymakers in multiscale integrated water resources and environmental management. However, water quality modeling is challenging due to several constraints. The modern application of modeling is essentially utilized by the need to comply with rules and regulations. In view of this, water quality modeling requires the standardization of models, identification of common features of models, the hotspots of pollution, and the current state of policy-relevant models. This review presents an overview of water quality modeling and major models frequently applied for water quality assessment at the catchment and at waterbody scales. This review is intended to highlight the applicability of certain water quality models, and the state of water quality modeling, model classification, and uncertainties. Water quality models are described and selected based on their applicability, strengths, weaknesses, and intended use. Some models are applicable for the specific waterbodies, simulate selected water quality parameters, have uncertainties, are not commercially available, require skilled model users, and have huge data requirements. When selecting suitable models, it is recommended to consider the availability of data, model complexity, and type of waterbody, and intended objectives to be modeled.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Overview of water quality modeling

Ejigu

2021

Cogent Engineering

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“…Water resources management requires constant monitoring of quality and quantity and proper assessment and management of watershed is the basis for conservation and rational utilization. Environmental policy decisions and successful management execution needs robust methods for assessing the hydrology and contribution of point and diffuse pollution sources to water quality problems, and also for assessing the estimated and achieved compliance with the desired watershed hydrology and water quality management objectives [1][2][3] . Surface, subsurface and groundwater quality is controlled by different key factors such as land use, water management and agricultural practices, diffuse and point emission sources, lithology, and geological structures of the aquifer [4][5][6][7] .…”

Section: Introductionmentioning

confidence: 99%

Suitability of common models to estimate hydrology and diffuse water pollution in North-eastern German lowland catchments with intensive agricultural land use

Waseem

Kachholz

Tränckner

2018

Front. Agr. Sci. Eng.

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Various process-based models are extensively being used to analyze and forecast catchment hydrology and water quality. However, it is always important to select the appropriate hydrological and water quality modeling tools to predict and analyze the watershed and also consider their strengths and weaknesses. Different factors such as data availability, hydrological, hydraulic, and water quality processes and their desired level of complexity are crucial for selecting a plausible modeling tool. This review is focused on suitable model selection with a focus on desired hydrological, hydraulic and water quality processes (nitrogen fate and transport in surface, subsurface and groundwater bodies) by keeping in view the typical lowland catchments with intensive agricultural land use, higher groundwater tables, and decreased retention times due to the provision of artificial drainage. In this study, four different physically based, partially and fully distributed integrated water modeling tools, SWAT (soil and water assessment tool), SWIM (soil and water integrated model), HSPF (hydrological simulation program-FORTRAN) and a combination of tools from DHI (MIKE SHE coupled with MIKE 11 and ECO Lab), have been reviewed particularly for the Tollense River catchment located in North-eastern Germany. DHI combined tools and SWAT were more suitable for simulating the desired hydrological processes, but in the case of river hydraulics and water quality, the DHI family of tools has an edge due to their integrated coupling between MIKE SHE, MIKE 11 and ECO Lab. In case of SWAT, it needs to be coupled with another tool to model the hydraulics in the Tollense River as SWAT does not include backwater effects and provision of control structures. However, both SWAT and DHI tools are more data demanding in comparison to SWIM and HSPF. For studying nitrogen fate and transport in unsaturated, saturated, and river zone, HSPF was a better model to simulate the desired nitrogen transformation and transport processes. However, for nitrogen dynamics and transformations in shallow streams, ECO Lab had an edge due its flexibility for inclusion of user-desired water quality parameters and processes. In the case of SWIM, most of the input data and governing equations are similar to SWAT but it does not include water bodies (ponds and lakes), wetlands and drainage systems. In this review, only the processes that were needed to simulate the Tollense River catchment were considered, however the resulted model selection criteria can be generalized to other lowland catchments in Australia, North-western Europe and North America with similar complexity.

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“…The aim of modeling surface water quality is to construct a mathematical model of a stream (flowing water), making it possible to track changes in water quality according to the initial and boundary conditions of the simulation. Modeling of water quality problems allows analysis of phenomena and the dependencies between them in order to predict and quantify the effects of changes in the aquatic environment (Ziemińska-Stolarska and Skrzypski, 2012). Since the 1970 s, some large shallow lakes with problems of cultural eutrophication, such as Lake Erie (North America) and Taihu Lake (China), have been modeled extensively to assess lake-wide responses to increasing external nutrient load and to analyze internal nutrient processing within the lake (Bertram, 1993).…”

Section: Introductionmentioning

confidence: 99%