Unveiling the Spatial Distribution and Temporal Trends of Total Phosphorus in the Yangtze River: Towards a Predictive Time-Series Modeling for Environmental Management DOI Creative Commons
Tianqi Ma,

Xing Chen,

Fazhi Xie

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 25, 2024

Abstract The accurate prediction of total phosphorus in water quality is crucial for monitoring ecosystem stability and eutrophication status. However, the distribution natural environmental data such as (TP) often undergoes complex changes over time. Stable reliable predictive outcomes not only necessitate a degree periodicity within data, but also require that TP models exhibit strong adaptability to random fluctuations drifts data. Therefore, adapting accommodate presents challenge. This study provides detailed description spatiotemporal variations Yangtze River from 2019 2023. Utilizing cleaning mining techniques, time series were analyzed generate dataset, with particular emphasis on investigating fluctuations. By comparing various forecasting models, MTS-Mixers was ultimately selected experimental baseline model, different modes employed prediction. results demonstrate model maintains relatively high accuracy 20 steps. research findings offer comprehensive River, provide effective methods tools management. They serve scientific basis protection improvement Basin, facilitating formulation implementation relevant policies advancing sustainable development environment. Furthermore, confirms applicability machine learning hydrological forecasting, which can be utilized addressing changes. Future directions include ensuring critical exploring time-domain sub-band reconstruction better understand frequency characteristics revealing hidden information features.

Language: Английский

Effects of land use patterns on seasonal water quality in Chinese basins at multiple temporal and spatial scales DOI Creative Commons

Xinchen Yao,

Chunfen Zeng,

Xuejun Duan

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 166, P. 112423 - 112423

Published: July 29, 2024

Diverse land use patterns exhibit varying effects on water quality across different seasons and spatial scales. However, current studies the correlation between in single small-scale basins no longer meet needs of regional coordinated development. Simultaneous comparative analysis multiple large-scale can promote environmental protection basins, but there is currently limited relevant research. In this study, data from 86 sampling points seven major river China were analyzed. Multivariate statistical redundancy (RDA) employed to investigate influence at The results indicated notable differences various locations. Except for higher pH permanganate index (COD) concentrations wet season Songhua River Basin COD Pearl Basin, all parameters other are dry season. PH exhibited considerable variations within while dissolved oxygen (DO) ammonia nitrogen (NH4+-N) showed smaller variations. RDA that had a more pronounced effect during Yangtze, Liao Basins, impact was greater four Yellow, Huai, Hai Basins. At scale, 2000 m buffer zone most significant 1000 greatest Huai For Yellow 500 season, respectively. research findings offer scientific foundation development basin-specific management policies measures multi-scale perspective.

Language: Английский

Citations

4
Time Series Analysis for the Adaptive Prediction of Total Phosphorus in the Yangtze River: A Machine Learning Approach DOI Open Access
Tianqi Ma,

Xing Chen

Water, Journal Year: 2025, Volume and Issue: 17(4), P. 603 - 603

Published: Feb. 19, 2025

Accurate prediction of total phosphorus (TP) in water quality is critical for monitoring ecosystem stability and eutrophication status. However, the distribution natural environmental data such as tends to undergo complex changes over time. Stable reliable results not only require a certain degree periodicity but also that TP model be highly adaptable random fluctuations distributional drifts data. Therefore, it challenge adapt models drift In this study, spatial temporal variations Yangtze River from 2019 2023 were described detail. Using mining techniques, time series analyzed generate forecast dataset focusing on fluctuations. By comparing various models, MTS-Mixers was finally selected experimental baseline different modes used prediction. The show after parameter adjustment, can achieve high accuracy (MAE: 0.145; MSE: 0.277), which guarantee at 20 steps. These research comprehensively reliably predicted provided effective methods tools management. They provide scientific basis protection improvement Basin help formulation implementation relevant policies promote sustainable development environment. addition, study confirms applicability machine learning hydrological responding changes.

Language: Английский

Citations

0
Seasonal dynamics of water quality in response to land use changes in the Chi and Mun River Basins Thailand DOI Creative Commons
Kwanchai Pakoksung, Nantawoot Inseeyong,

Nattawin Chawaloesphonsiya

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Feb. 27, 2025

The Chi and Mun River Basins, the primary tributary of Mekong Basin in Thailand, is undergoing significant land use changes that impact water quality. Understanding relationship between quality crucial for effective river basin management, providing insights applicable to global systems. While past studies have examined Basin, research specifically focusing on Chi-Mun remains limited. This study analyzes spatial temporal effects from 2007 2021 using change estimation, 11 parameters, redundancy analysis (RDA). Water samples were collected January, March, May, August across multiple years. Seasonal variations assessed, with dry season January March wet May August. Key findings include: (1) pH, Biochemical Oxygen Demand, Total Coliform Bacteria, Fecal Phosphorus, Nitrate Nitrogen, Ammonia-Nitrogen, Suspended Solids increased during season, while (2) Dissolved Oxygen, Electrical Conductivity, Quality Index higher season. (3) Land had a greater driven by runoff expanding urban agricultural areas declining paddy forest cover. (4) Forests aquatic improved quality, expansion contributed its deterioration. These underscore need sustainable management strategies balance regional development ecological conservation Basin.

Language: Английский

Citations

0
Characteristics of Phosphorus Distribution and Mechanisms of Phosphorus Release through Migration and Transformation in the Sediments of Deep-Water Reservoirs in Mountainous Areas DOI

Lingfeng Wang,

Feng Zhong, Haibo Li

et al.

Journal of environmental chemical engineering, Journal Year: 2025, Volume and Issue: unknown, P. 116907 - 116907

Published: May 1, 2025

Language: Английский

Citations

0
Unraveling the role of anthropogenic and hydrologic drivers with respect to the optical and molecular properties of dissolved organic matter and organic phosphorus in a P-contaminated river DOI

Zhanyao Shi,

Yao Du,

Hongni Liu

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 951, P. 175647 - 175647

Published: Aug. 22, 2024

Language: Английский

Citations

1
Impact of Land Use Change on Seasonal Water Quality, Case Study in Chi-Mun River Basin in Thailand DOI Creative Commons
Kwanchai Pakoksung, Nantawoot Inseeyong,

Nattawin Chawaloesphonsiya

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 16, 2024

Abstract This study investigates the correlation between land use changes and water quality in Chi-Mun River Basin, Thailand, from 2007 to 2021. It is first of its kind region Mekong providing critical insights for global river basin management. The research analyzes spatial temporal their multi-scale impacts on quality, utilizing change estimation, index analysis, redundancy analysis (RDA). results showed that stream variables displayed highly variations, with pH, Biochemical Oxygen Demand (BOD), Total Coliform Bacteria (TCB), Fecal (FCB), Phosphorus (TP), Nitrate Nitrogen (NO3-N), Ammonia-nitrogen (NH3-N), Suspended Solids (SS) all generally displaying higher levels wet season, while there were concentrations Dissolved (DO), Electrical Conductivity (EC), Water Quality Index (WQI) dry season. samples collected once January, March, May, August 2024. season represented May August, January March. total contribution patterns overall was stronger during shows a decline paddy forest areas alongside an expansion urban, agricultural, aqua agricultural land. significant seasonal forests bodies contributing purification, urban degraded quality. findings offer recommendations protection management policies align basin’s natural socio-economic characteristics, promoting coordinated regional development.

Language: Английский

Citations

0
Unveiling the Spatial Distribution and Temporal Trends of Total Phosphorus in the Yangtze River: Towards a Predictive Time-Series Modeling for Environmental Management DOI Creative Commons
Tianqi Ma,

Xing Chen,

Fazhi Xie

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 25, 2024

Abstract The accurate prediction of total phosphorus in water quality is crucial for monitoring ecosystem stability and eutrophication status. However, the distribution natural environmental data such as (TP) often undergoes complex changes over time. Stable reliable predictive outcomes not only necessitate a degree periodicity within data, but also require that TP models exhibit strong adaptability to random fluctuations drifts data. Therefore, adapting accommodate presents challenge. This study provides detailed description spatiotemporal variations Yangtze River from 2019 2023. Utilizing cleaning mining techniques, time series were analyzed generate dataset, with particular emphasis on investigating fluctuations. By comparing various forecasting models, MTS-Mixers was ultimately selected experimental baseline model, different modes employed prediction. results demonstrate model maintains relatively high accuracy 20 steps. research findings offer comprehensive River, provide effective methods tools management. They serve scientific basis protection improvement Basin, facilitating formulation implementation relevant policies advancing sustainable development environment. Furthermore, confirms applicability machine learning hydrological forecasting, which can be utilized addressing changes. Future directions include ensuring critical exploring time-domain sub-band reconstruction better understand frequency characteristics revealing hidden information features.

Language: Английский

Citations

0