Aiping Huang
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Aiping Huang has a total of 23 co-authors. Here are the top co-authors by number of shared publications:
- Fei Dong
State Key Laboratory of Water Cycle and Water Security, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
4 shared publications - Xiaobo Liu
State Key Laboratory of Water Cycle and Water Security China Institute of Water Resources and Hydropower Research Beijing China
4 shared publications - Xiaochen Yang
State Key Laboratory of Water Cycle and Water Security, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
3 shared publications - Yang Lei
College of Ecology and Natural Resources Environment, Dezhou University, Dezhou 253023, China
3 shared publications - Bing Ma
State Key Laboratory of Water Cycle and Water Security, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
2 shared publications - Wenqi Peng
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin China Institute of Water Resources and Hydropower Research Beijing China
2 shared publications
Latest Publications
- Open Access
A Holistic Assessment of Water Quality in the Lake and Rivers of Lake Chaohu Basin, China
The Lake Chaohu Basin (LCB) represents a focal point for water pollution control in China, and its water quality status has drawn substantial attention. We conducted a holistic assessment of water quality using the water quality index (WQI) in the LCB based on monthly measurements of 13 water quality parameters at 16 stations during 2016–2020. We observed a general upward trend in the annual average WQI for Lake Chaohu, suggesting an improvement in water quality. A notable shift in the spatial pattern of water quality was observed. The annual average WQI for inflowing rivers also exhibited an overall upward trend. The WQIs of the lake and inflowing rivers, particularly in the western lake, exhibited a significant positive correlation, suggesting that the water quality of the inflowing rivers is a crucial factor influencing the water quality of Lake Chaohu. The crucial water quality parameters influencing the WQI of the LCB included ammonia nitrogen, total phosphorus, total nitrogen, dissolved oxygen, and permanganate index, which were used to construct a minimum WQI (WQImin). The WQImin showed outstanding performance in the LCB. The findings of this study could deepen the understanding of water quality patterns and the response of lake water quality to inflowing river water quality within lake-type basins.
Open AccessA Holistic Assessment of Water Quality in the Lake and Rivers of Lake Chaohu Basin, China
The Lake Chaohu Basin (LCB) represents a focal point for water pollution control in China, and its water quality status has drawn substantial attention. We conducted a holistic assessment of water quality using the water quality index (WQI) in the LCB based on monthly measurements of 13 water quality parameters at 16 stations during 2016–2020. We observed a general upward trend in the annual average WQI for Lake Chaohu, suggesting an improvement in water quality. A notable shift in the spatial pattern of water quality was observed. The annual average WQI for inflowing rivers also exhibited an overall upward trend. The WQIs of the lake and inflowing rivers, particularly in the western lake, exhibited a significant positive correlation, suggesting that the water quality of the inflowing rivers is a crucial factor influencing the water quality of Lake Chaohu. The crucial water quality parameters influencing the WQI of the LCB included ammonia nitrogen, total phosphorus, total nitrogen, dissolved oxygen, and permanganate index, which were used to construct a minimum WQI (WQImin). The WQImin showed outstanding performance in the LCB. The findings of this study could deepen the understanding of water quality patterns and the response of lake water quality to inflowing river water quality within lake-type basins.
- 24 March 2025
- Published by Springer Nature in Water Resources Management
- Vol. 39 (7) , 3015-3030
Water Quality Prediction Method Coupling Mechanism Model and Machine Learning for Water Diversion Projects with a Lack of Data
- 24 March 2025
- Published by Springer Nature in Water Resources Management
- Vol. 39 (7) , 3015-3030
Water Quality Prediction Method Coupling Mechanism Model and Machine Learning for Water Diversion Projects with a Lack of Data
- Open Access
Research on Water Quality Assessment Using the Water Quality Index for the Eastern Route of the South-to-North Water Diversion Project
The South-to-North Water Diversion Project’s Eastern Route (SNWDPC-ER) has drawn a lot of attention as one of China’s most significant water diversion projects. This study calculated the water quality index (WQI) to analyze the spatial and temporal characteristics of water quality in the study area as well as the effects of water diversion, and developed the minimum water quality index (WQImin) model based on stepwise multiple linear regression, using data from 56 monitoring stations along the delivery canal of the SNWDPC-ER (the SNWDPC-delivery ER’s canal) from 2014 to 2018. Here are the findings: (1) The water quality state was rated as “good” and the annual average value of WQI climbed year over year along with improvements in water quality. (2) There was a clear difference in water quality across time and space, with autumn having better water quality than other seasons and the south having better water quality than the north. (3) Water quality is impacted by water diversion; throughout the era of diversion, water quality was steadier. (4) The weighted WQImin model, which is a quick and inexpensive way to assess water quality, can be used to evaluate the water quality in the SNWDPC-delivery ER’s canal. The model’s parameters are DO, NH3-N, BOD5, and TN.
Open AccessResearch on Water Quality Assessment Using the Water Quality Index for the Eastern Route of the South-to-North Water Diversion Project
The South-to-North Water Diversion Project’s Eastern Route (SNWDPC-ER) has drawn a lot of attention as one of China’s most significant water diversion projects. This study calculated the water quality index (WQI) to analyze the spatial and temporal characteristics of water quality in the study area as well as the effects of water diversion, and developed the minimum water quality index (WQImin) model based on stepwise multiple linear regression, using data from 56 monitoring stations along the delivery canal of the SNWDPC-ER (the SNWDPC-delivery ER’s canal) from 2014 to 2018. Here are the findings: (1) The water quality state was rated as “good” and the annual average value of WQI climbed year over year along with improvements in water quality. (2) There was a clear difference in water quality across time and space, with autumn having better water quality than other seasons and the south having better water quality than the north. (3) Water quality is impacted by water diversion; throughout the era of diversion, water quality was steadier. (4) The weighted WQImin model, which is a quick and inexpensive way to assess water quality, can be used to evaluate the water quality in the SNWDPC-delivery ER’s canal. The model’s parameters are DO, NH3-N, BOD5, and TN.
- Open Access
Sub-Watershed Parameter Transplantation Method for Non-Point Source Pollution Estimation in Complex Underlying Surface Environment
The prevention and control of non-point source pollution is an important link in managing basin water quality and is an important factor governing the environmental protection of watershed water in China over the next few decades. The control of non-point source pollution relies on the recognition of the amount, location, and influencing factors. The watershed nonpoint source pollution mechanism model is an effective method to address the issue. However, due to the complexity and randomness of non-point source pollution, both the development and application of the watershed water environment model have always focused on the accuracy and rationality of model parameters. In this pursuit, the present study envisaged the temporal and spatial heterogeneity of non-point source pollution caused by the complex underlying surface conditions of the watershed, and the insufficient coverage of hydrological and water quality monitoring stations. A refined watershed non-point source pollution simulation method, combining the Monte Carlo analytic hierarchy process (MCAHP) and the sub-watershed parameter transplantation method (SWPT), was established on the basis of the migration and transformation theory of the non-point source pollution, considering the index selection, watershed division, sub-watershed simulation, and parameter migration. Taking the Erhai Lake, a typical plateau lake in China, as the representative research object, the MCAHP method effectively reduced the uncertainty of the weights of the watershed division indexes compared to the traditional AHP method. Furthermore, compared to the traditional all watershed parameter simulation (AWPS) approach, the simulation accuracy was improved by 40% using the SWPT method, which is important for the prevention and control of non-point source pollution in large-scale watersheds with significant differences in climatic and topographic conditions. Based on the simulation results, the key factors affecting the load of the non-point source pollution in the Erhai watershed were identified. The results showed that the agricultural land in Erhai Lake contributed a majority of the load for several reasons, including the application of nitro phosphor complex fertilizer. Among the different soil types, paddy soil was responsible for the largest pollution load of total nitrogen and total phosphorus discharge into the lake. The zones with slopes of 0–18° were found to be the appropriate area for farming. Our study presents technical methods for the assessment, prevention, and control of non-point source pollution load in complex watersheds.
Open AccessSub-Watershed Parameter Transplantation Method for Non-Point Source Pollution Estimation in Complex Underlying Surface Environment
The prevention and control of non-point source pollution is an important link in managing basin water quality and is an important factor governing the environmental protection of watershed water in China over the next few decades. The control of non-point source pollution relies on the recognition of the amount, location, and influencing factors. The watershed nonpoint source pollution mechanism model is an effective method to address the issue. However, due to the complexity and randomness of non-point source pollution, both the development and application of the watershed water environment model have always focused on the accuracy and rationality of model parameters. In this pursuit, the present study envisaged the temporal and spatial heterogeneity of non-point source pollution caused by the complex underlying surface conditions of the watershed, and the insufficient coverage of hydrological and water quality monitoring stations. A refined watershed non-point source pollution simulation method, combining the Monte Carlo analytic hierarchy process (MCAHP) and the sub-watershed parameter transplantation method (SWPT), was established on the basis of the migration and transformation theory of the non-point source pollution, considering the index selection, watershed division, sub-watershed simulation, and parameter migration. Taking the Erhai Lake, a typical plateau lake in China, as the representative research object, the MCAHP method effectively reduced the uncertainty of the weights of the watershed division indexes compared to the traditional AHP method. Furthermore, compared to the traditional all watershed parameter simulation (AWPS) approach, the simulation accuracy was improved by 40% using the SWPT method, which is important for the prevention and control of non-point source pollution in large-scale watersheds with significant differences in climatic and topographic conditions. Based on the simulation results, the key factors affecting the load of the non-point source pollution in the Erhai watershed were identified. The results showed that the agricultural land in Erhai Lake contributed a majority of the load for several reasons, including the application of nitro phosphor complex fertilizer. Among the different soil types, paddy soil was responsible for the largest pollution load of total nitrogen and total phosphorus discharge into the lake. The zones with slopes of 0–18° were found to be the appropriate area for farming. Our study presents technical methods for the assessment, prevention, and control of non-point source pollution load in complex watersheds.
- Open Access
- 1 July 2021
- Published by IOP Publishing in IOP Conference Series: Earth and Environmental Science
- Vol. 826 (1) , 012021
Study on effect of different reservoir water diversion modes on river water quality improvement
Urban river water pollution is a serious environmental issue and tends to become worse. One of the key measures to improve urban river water quality is to divert water from upstream reservoir to downstream river course to flush pollutant. In this paper, a one-dimensional hydrodynamic and water quality model of Hun River network was developed based on HEC-RAS model. Different reservoir water diversion modes for sewage discharge were simulated and their effect on the water quality improvement of downstream river course was analysed. The results show that under different diversion flow rates, the larger the diversion flow rate, the better the effect on water quality improvement, and that when total water diversion volume is fixed, the effect of long-term diversion with a low flow rate is better than that of short-term diversion with a high flow rate on downstream water quality improvement. The research results can provide scientific support for optimization of the operation of water diversion from reservoir for sewage discharge.
- 1 July 2021
- Published by IOP Publishing in IOP Conference Series: Earth and Environmental Science
- Vol. 826 (1) , 012021
Open AccessStudy on effect of different reservoir water diversion modes on river water quality improvement
Urban river water pollution is a serious environmental issue and tends to become worse. One of the key measures to improve urban river water quality is to divert water from upstream reservoir to downstream river course to flush pollutant. In this paper, a one-dimensional hydrodynamic and water quality model of Hun River network was developed based on HEC-RAS model. Different reservoir water diversion modes for sewage discharge were simulated and their effect on the water quality improvement of downstream river course was analysed. The results show that under different diversion flow rates, the larger the diversion flow rate, the better the effect on water quality improvement, and that when total water diversion volume is fixed, the effect of long-term diversion with a low flow rate is better than that of short-term diversion with a high flow rate on downstream water quality improvement. The research results can provide scientific support for optimization of the operation of water diversion from reservoir for sewage discharge.