Response of sediments and phosphorus to catchment characteristics and human activities under different rainfall patterns with Bayesian Networks

Jin, Guangqiu; Xu, Jing; Mo, Yuming; Tang, Hongwu; Wei, Tang; Wang, You‐Gan; Li, Ling

doi:10.1016/j.jhydrol.2020.124695

Cited by 19 publications

(3 citation statements)

References 97 publications

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“…Many studies have demonstrated that sediment and nutrient concentrations increase with land development (both agricultural and urban; Carpenter et al, 1998; Turner & Rabalais, 2003; Jin et al, 2020). Yet, most studies focus on either predominantly agricultural (Ford et al, 2018), predominantly urban (Hoellein et al, 2011), or mixed land cover watersheds (Richards et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

Land cover, stream discharge, and wastewater effluent impacts on baseflow sediment and nutrient concentrations in SW Ohio streams

Spahr,

Lazar,

Grudzinski

et al. 2024

River Research & Apps

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Elevated nutrient and suspended sediment concentrations often result in negative environmental impacts within freshwater environments. Studies that directly compare suspended sediment and bioavailable nutrients between predominantly agricultural and predominantly urban watersheds during baseflow conditions are largely lacking. The purpose of this study was to determine the impacts of land cover, stream discharge, and wastewater treatment plant (WWTP) discharge on nutrient and sediment concentrations, across a large land cover gradient in Southwest Ohio streams. Weekly baseflow samples were collected from eight streams over 1 year from November, 2016 through November, 2017. Total suspended sediment, nitrate, and phosphate concentrations were measured. Results indicate that agricultural land cover and WWTPs increase nitrate and phosphate concentrations in the study area. Total suspended sediment and nitrate concentrations increased with discharge, and discharge was a relatively weak predictor of phosphate concentrations. Seasonal water quality trends varied by parameter and land use also had unique impacts on seasonal water quality trends. Results suggest that to improve water quality in the study area, efforts should focus on improving WWTP effluent treatment and agricultural land management.

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Section: Introductionmentioning

confidence: 99%

Land cover, stream discharge, and wastewater effluent impacts on baseflow sediment and nutrient concentrations in SW Ohio streams

Spahr,

Lazar,

Grudzinski

et al. 2024

River Research & Apps

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“…Due to the complexity of hydrological processes in the catchment area and the complex relationships between the quantitative and qualitative variables of waters, Bayesian network models are also used. Using a Bayesian Network, complex processes can be described in a simple way and provide an approach to incorporate both quantitative and qualitative variables into a single model, as demonstrated by Xu et al ( 2019 ) and Jin et al ( 2020 ). In the Bayesian Networks, each variable only depends on its immediate parent variables, however the networks do not model temporal relationships between variables, meaning they only represent probabilistic relationships between a set of variables at some point in time.…”

Section: Introductionmentioning

confidence: 99%

Coupling ANFIS with ant colony optimization (ACO) algorithm for 1-, 2-, and 3-days ahead forecasting of daily streamflow, a case study in Poland

Aghelpour

Graf

Tomaszewski

2023

Environ Sci Pollut Res

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Finding an efficient and reliable streamflow forecasting model has always been an important challenge for managers and planners of freshwater resources. The current study, based on an adaptive neuro-fuzzy inference system (ANFIS) model, was designed to predict the Warta river (Poland) streamflow for 1 day, 2 days, and 3 days ahead for a data set from the period of 1993–2013. The ANFIS was additionally combined with the ant colony optimization (ACO) algorithm and employed as a meta-heuristic ANFIS-ACO model, which is a novelty in streamflow prediction studies. The investigations showed that on a daily scale, precipitation had a very weak and insignificant effect on the river’s flow variation, so it was not considered as a predictor input. The predictor inputs were selected by the autocorrelation function from among the daily streamflow time lags for all stations. The predictions were evaluated with the actual streamflow data, using such criteria as root mean square error (RMSE), normalized RMSE (NRMSE), and R2. According to the NRMSE values, which ranged between 0.016–0.006, 0.030–0.013, and 0.038–0.020 for the 1-day, 2-day, and 3-day lead times, respectively, all predictions were classified as excellent in terms of accuracy (prediction quality). The best RMSE value was 1.551 m3/s and the highest R2 value was equal to 0.998, forecast for 1-day lead time. The combination of ANFIS with the ACO algorithm enabled to significantly improve streamflow prediction. The use of this coupling can averagely increase the prediction accuracies of ANFIS by 12.1%, 12.91%, and 13.66%, for 1-day, 2-day, and 3-day lead times, respectively. The current satisfactory results suggest that the employed hybrid approach could be successfully applied for daily streamflow prediction in other catchment areas.

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“…Many small manufacturing units and their wastes are directly or indirectly thrown into the river, making Ganga even more polluted (Whitehead et al 2018;Hasan et al 2019). Furthermore, human-caused pollution and ine cient riverbank drainage from agricultural settings to the river create additional hazards to its water quality (Jin et al 2020). As a result, the Ganga River is experiencing severe environmental challenges for life sustenance, resulting in biological and hydrological cessation (Whitehead et al 2018; Uddin and Jeong, 2021).…”

Section: Introductionmentioning

confidence: 99%

The Ganga around Kolkata: How safe is the river on bio-physical criteria?

Nayek

Das

Pati

et al. 2023

Preprint

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The Ganga River basin is home to a diverse range of benthic flora and fauna. The Ganga River's health is deteriorating due to anthropogenic activities such as untreated garbage disposal, detergent and chemical contaminations, animal bathing, idol immersion, etc. The current study looks at the variations of zooplankton community assemblage in the Ganga River with diverse physical qualities from twelve locations along the river's southernmost stretch. Both banks of the river basin in the Indian state of West Bengal were considered for the study locations. All physical characteristics, such as water PH, conductivity, TDS, and salinity, except for the temperature, differ significantly between the study locations. There was an inverse relationship between physical factors and zooplankton abundance along the river. Cyclops and Daphnia were the most prevalent organisms identified in our study. The presence of industrial belts, large sewage systems, and human activities in the study sites was responsible for the fluctuating zooplankton diversity indices.

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Response of sediments and phosphorus to catchment characteristics and human activities under different rainfall patterns with Bayesian Networks

Cited by 19 publications

References 97 publications

Land cover, stream discharge, and wastewater effluent impacts on baseflow sediment and nutrient concentrations in SW Ohio streams

Land cover, stream discharge, and wastewater effluent impacts on baseflow sediment and nutrient concentrations in SW Ohio streams

Coupling ANFIS with ant colony optimization (ACO) algorithm for 1-, 2-, and 3-days ahead forecasting of daily streamflow, a case study in Poland

The Ganga around Kolkata: How safe is the river on bio-physical criteria?

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