Mathematical Model for the Simulation of Water Quality in Rivers Using the Vensim Ple® Software

Gonçalves, Julio Cesar Souza Inácio; Giorgetti, Marcius F.

doi:10.4090/juee.2013.v7n1.048063

Cited by 7 publications

(6 citation statements)

References 9 publications

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“…The mathematical models used for the simulation of water quality are useful in predicting environmental impacts from pollutants discharged into rivers (Sardinha et al, 2008;Pasquini, Formica, & Sacchi, 2012;Gonçalves & Giorgetti, 2013). These models are made up of parameters that, if poorly estimated, can reduce the accuracy of the produced results.…”

Section: Introductionmentioning

confidence: 99%

<b>Prediction of the longitudinal dispersion coefficient for small watercourses

et al. 2017

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ABSTRACT.Longitudinal dispersion coefficient (D L ) is considered an essential physical parameter to water quality modeling in rivers. Therefore, the estimation of this parameter with high accuracy guarantees the reliability of the results of a water quality model. In this study, the observed values of longitudinal dispersion coefficient are determined for natural streams (with discharge less than 2.84 m ), a partir de ensaios de campo de estímulo-resposta com traçador salino (cloreto de sódio) e do método da propagação (routing procedure), corrigido para considerar a perda do traçador. Adicionalmente, uma equação semiempírica de previsão de D L foi desenvolvida a partir da análise dimensional e da técnica de regressão linear múltipla. A equação desenvolvida foi comparada com cinco equações empíricas de predição de D L existentes na literatura. O r 2 da equação gerada foi de 0,87, o que sugere que esta equação é adequada para a estimativa de D L para os cursos d'água estudados. A equação produzida gerou melhores resultados do que as cinco equações retiradas da literatura, apresentando uma acurácia de 71%.Palavras-chave: coeficiente de dispersão longitudinal, rios, traçador salino.

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Section: Introductionmentioning

confidence: 99%

<b>Prediction of the longitudinal dispersion coefficient for small watercourses

et al. 2017

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“…In this research, Vensim has been used, which is one of the most widely used software for the modelling of complex systems, in general, and for water resources management in particular (i.e. Goncalves &Giorgetti, 2013 andAbadi Khalegh, Shamsai, &Goharnejad, 2015). The dynamic simulation model will be used to assess the change over time of the water balance as it is affected by changes in the governing variables, mainly population, temperature, and water supply and demand.…”

Section: Data Analysis and Methodologymentioning

confidence: 99%

Dynamic modelling of the climate change impact in the Conchos River basin water management

Austria

Hidalgo

Gómez

2019

Tecnol. cienc. agua

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In the last decades there have been some deficits in water deliveries that Mexico must make to the United States under the Water Treaty between the two countries. Population growth and the effects of climate change make possible foresee that the difficulties will increase in the future. This text analyzes the observed changes in rainfall in the basin, and a dynamic model is developed to estimate the effects of climate change on the water balance of the Conchos river basin, which contributes 87% of the amount of water established as Mexicans commitments in the Treaty. The results of three scenarios are shown and the effects on water availability in the basin are exposed. A sensitivity analysis is presented, with the Montecarlo method, regarding

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“…We used Vensim PLE software to establish a structure flow chart of the quantitative simulation of green spaces in Beijing's central district performed with an SD model ( Figure 3) [53]. The initial values of the main state variables in the model were derived from statistical data for the period 1992-2016.…”

Section: Construction Of a Causal Feedback Chart For Simulating Greenmentioning

confidence: 99%

Spatiotemporal Simulation of Green Space by Considering Socioeconomic Impacts Based on A SD-CA Model

Wang

et al. 2021

Forests

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Green space is an important part of composite urban spatial systems. Therefore, reasonable planning strategies based on scientifically sound predictions of temporal and spatial changes in green space are critical for maintaining urban ecological environments, ensuring the health of residents, and maintaining social stability. However, existing forecasting models discount the impacts of urban social economy on green space. To address this gap, we constructed a system dynamics and cellular automata (SD-CA) coupling model that integrated the socioeconomic system and generated multiple scenarios. The results showed that at the current pace of socioeconomic development, Beijing’s central district will experience an overall reduction in green space and a decline in its integrity and diversity by 2035. If the population of this area reaches 9.29 million by 2035 and the GDP maintains an average growth rate of 6.1%, the areas of various land types will exhibit little change by 2035, and green space will be optimized to a certain extent. However, if the study area’s population decreases to 8.59 million by 2035 and the average GDP growth rate drops to 4.9%, the fragmentation, connectivity, and diversity index of green space will all increase significantly by 2035, and green space will be clearly optimized. We propose scientifically grounded strategies for maximizing the ecological functions and economic benefits of green space through optimized green space patterns, considered from a policy-oriented perspective of promoting socioeconomic development.

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Mathematical Model for the Simulation of Water Quality in Rivers Using the Vensim Ple® Software

Cited by 7 publications

References 9 publications

<b>Prediction of the longitudinal dispersion coefficient for small watercourses

<b>Prediction of the longitudinal dispersion coefficient for small watercourses

Dynamic modelling of the climate change impact in the Conchos River basin water management

Spatiotemporal Simulation of Green Space by Considering Socioeconomic Impacts Based on A SD-CA Model

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