Quantifying the impact of human activities on water quality based on spatialization of social data: a case study of the Pingzhai Reservoir Basin

2020 ◽  
Vol 20 (2) ◽  
pp. 688-699 ◽  
Author(s):  
Yongrong Zhang ◽  
Zhongfa Zhou ◽  
Haotian Zhang ◽  
Yusheng Dan

Abstract In water pollution source research, it is difficult to quantify the impact of human activities on water quality. Based on pollution load theory and the concept of spatialization of social data, this study integrates land-use type, slope gradient, and spatial position, and uses the contribution of human activities to quantify the impact of farmland fertilizers, livestock and poultry wastes, and human domestic pollution on water quality in the study area. The results show that livestock manure is the largest source of total phosphorus (TP) and total nitrogen (TN) discharges in the research area, and domestic pollution is the largest source of chemical oxygen demand (COD) discharges. The total equal standard pollution load (as well as the load of each pollution source and its pollutant amount) is the highest in the Nayong River Basin and the lowest in the Baishui River Basin. The contributions of human activities to TP and TN have similar spatial distributions. The impact of human activities on COD discharge is minimal. The quantitative results of this model are basically consistent with the actual conditions in the Pingzhai Reservoir Basin, which suggests that the model reasonably reflects the impact of human activities on the water environment of the basin.

Author(s):  
Srimanti Duttagupta ◽  
Soumendra N. Bhanja ◽  
Avishek Dutta ◽  
Soumyajit Sarkar ◽  
Madhumita Chakraborty ◽  
...  

The 2020 COVID-19 pandemic has not only resulted in immense loss of human life, but it also rampaged across the global economy and socio-cultural structure. Worldwide, countries imposed stringent mass quarantine and lockdowns to curb the transmission of the pathogen. While the efficacy of such lockdown is debatable, several reports suggest that the reduced human activities provided an inadvertent benefit by briefly improving air and water quality. India observed a 68-days long, nation-wide, stringent lockdown between 24 March and 31 May 2020. Here, we delineate the impact of the lockdown on groundwater and river sourced drinking water sustainability in the arsenic polluted Ganges river basin of India, which is regarded as one of the largest and most polluted river basins in the world. Using groundwater arsenic measurements from drinking water wells and water quality data from river monitoring stations, we have studied ~700 km stretches of the middle and lower reaches of the As (arsenic)-polluted parts of the river for pre-lockdown (January–March 2020), syn-lockdown (April–May), and post-lockdown periods (June–July). We provide the extent of As pollution-free groundwater vis-à-vis river water and examine alleviation from lockdown as an opportunity for sustainable drinking water sources. The overall decrease of biochemical oxygen demand (BOD) and chemical oxygen demand (COD) concentrations and increase of pH suggests a general improvement in Ganges water quality during the lockdown in contrast to pre-and-post lockdown periods, potentially caused by reduced effluent. We also demonstrate that land use (agricultural/industrial) and land cover (urban-periurban/rural) in the vicinity of the river reaches seems to have a strong influence on river pollutants. The observations provide a cautious optimistic scenario for potentially developing sustainable drinking water sources in the arsenic-affected Ganges river basin in the future by using these observations as the basis of proper scientifically prudent, spatially adaptive strategies, and technological interventions.


Author(s):  
Jiangang Lu ◽  
Haisheng Cai ◽  
Xueling Zhang ◽  
Yanmei Fu

Abstract Changes in human-dominated spatial patterns of land use are the main driving factors of water quality evolution in watersheds, and the quantitative impact of land use changes on water quality is currently a focus of lake ecology research. Using the Junshan Lake Basin as a study area, this paper quantitatively analyzes the response relationships between the water quality parameters, land use, and socio-economic factors in the study area from 2005 to 2019 and predicts the water quality in 2035 based on land and space planning scenarios. The results show the following. (1) The land use structure of the Junshan Lake Basin has changed significantly over the last 15 years. The basic trend is an increase in settlement and wetland areas in the basin and a decrease in water, cropland, forest, and grassland areas. (2) Settlement areas play the role of a ‘source’ for the total phosphorus (TP) and ammonium-nitrogen (NH3-N) pollution load, and cropland areas play the role of a ‘sink’ for the TP, NH3-N, and chemical oxygen demand (CODMn) pollution load. (3) The main land use type in the Junshan Lake Basin is cropland, which accounts for more than 40% of the total, and the water quality in the lake is affected not only by non-point source pollution but also by the regional Gross Domestic Product (GDP), total population, and per capita disposable income. According to the water quality prediction and analysis, the concentrations of TN and TP in Junshan Lake will meet the Class IV water quality standard in 2035, and the concentrations of dissolved oxygen (DO) and CODMn will meet the Class II standard. This study is significant for the management and control of the water environment in the Junshan Lake Basin.


Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6911
Author(s):  
Jing Zhao ◽  
Fujie Zhang ◽  
Shuisen Chen ◽  
Chongyang Wang ◽  
Jinyue Chen ◽  
...  

Accurate and quantitative assessment of the impact of natural environmental changes and human activities on total suspended solids (TSS) concentration is one of the important components of water environment protection. Due to the limits of traditional cross-sectional point monitoring, a novel water quality evaluation method based on the Markov model and remote sensing retrieval is proposed to realize the innovation of large-scale spatial monitoring across administrative boundaries. Additionally, to explore the spatiotemporal characteristics and driving factors of TSS, a new three-band remote sensing model of TSS was built by regression analysis for the inland reservoir using the synchronous field spectral data, water quality samples and remote sensing data in the trans-provincial Hedi Reservoir in the Guangdong and Guangxi Provinces of South China. The results show that: (1) The three-band model based on the OLI sensor explained about 82% of the TSS concentration variation (R2=0.81, N=34,  p value<0.01) with an acceptable validation accuracy (RMSE=6.24 mg/L,MRE=18.02%, N=15), which is basically the first model of its kind available in South China. (2) The TSS concentration has spatial distribution characteristics of high upstream and low downstream, where the average TSS at 31.54 mg/L in the upstream are 2.5 times those of the downstream (12.55 mg/L). (3) Different seasons and rainfall are important factors affecting the TSS in the upstream cross-border area, the TSS in the dry season are higher with average TSS of 33.66 mg/L and TSS are negatively correlated with rainfall from upstream mankind activity. Generally, TSS are higher in rainy seasons than those in dry seasons. However, the result shows that TSS are negatively correlated with rainfall, which means human activities have higher impacts on water quality than climate change. (4) The Markov dynamic evaluation results show that the water quality improvement in the upstream Shijiao Town is the most obvious, especially in 2018, the improvement in the water quality level crossed three levels and the TSS were the lowest. This study provided a technical method for remote sensing dynamic monitoring of water quality in a large reservoir, which is of great significance for remediation of the water environment and the effective evaluation of the river and lake chief system in China.


1974 ◽  
Vol 9 (1) ◽  
pp. 25-29
Author(s):  
M. B. Bayer

Abstract This paper describes a method of applying probabilistic DO (dissolved oxygen) and BOD (biochemical oxygen demand) standards in river basin water quality models. Maximum likelihood estimators for the DO and BOD concentrations variances for each reach are used to obtain a lower bound for BOD so that the probability of violating specified DO and BOD standards is less than Θ per cent in any reach. These boundary values for DO and BOD concentrations are incorporated into a nonlinear water quality optimization model for finding the minimum cost set of wastewater treatment plant efficiencies required to meet DO and BOD standards. The method also provides the minimum DO concentration and the maximum BOD concentration which may be expected to occur 1-Θ of the time for any reach.


1989 ◽  
Vol 21 (12) ◽  
pp. 1821-1824
Author(s):  
M. Suzuki ◽  
K. Chihara ◽  
M. Okada ◽  
H. Kawashima ◽  
S. Hoshino

A computer program based on expert system software was developed and proposed as a prototype model for water management to control eutrophication problems in receiving water bodies (Suzuki etal., 1988). The system has several expert functions: 1. data input and estimation of pollution load generated and discharged in the river watershed; 2. estimation of pollution load run-off entering rivers; 3. estimation of water quality of receiving water bodies, such as lakes; and 4. assisting man-machine dialog operation. The program can be used with MS-DOS BASIC and assembler in a 16 bit personal computer. Five spread sheets are utilized in calculation and summation of the pollutant load, using multi-windows. Partial differential equations for an ecological model for simulation of self-purification in shallow rivers and simulation of seasonal variations of water quality in a lake were converted to computer programs and included in the expert system. The simulated results of water quality are shown on the monitor graphically. In this study, the expert system thus developed was used to estimate the present state of one typical polluted river basin. The river was the Katsura, which flows into Lake Sagami, a lake dammed for water supply. Data which had been actually measured were compared with the simulated water quality data, and good agreement was found. This type of expert system is expected to be useful for water management of a closed water body.


1998 ◽  
Vol 38 (10) ◽  
pp. 23-30
Author(s):  
Sarah Jubb ◽  
Philip Hulme ◽  
Ian Guymer ◽  
John Martin

This paper describes a preliminary investigation that identified factors important in the prediction of river water quality, especially regarding dissolved oxygen (DO) concentration. Intermittent discharges from combined sewer overflows (CSOs) within the sewerage, and overflows at water reclamation works (WRW) cause dynamic conditions with respect to both river hydraulics and water quality. The impact of such discharges has been investigated under both wet and dry weather flow conditions. Data collected from the River Maun, UK, has shown that an immediate, transient oxygen demand exists downstream of an outfall during storm conditions. The presence of a delayed oxygen demand has also been identified. With regard to modelling, initial investigations used a simplified channel and the Streeter-Phelps (1925) dissolved oxygen sag curve equation. Later, a model taking into account hydrodynamic, transport and dispersion processes was used. This suggested that processes other than water phase degradation of organic matter significantly affect the dissolved oxygen concentration downstream of the location of an intermittent discharge. It is proposed that the dynamic rate of reaeration and the sediment oxygen demand should be the focus of further investigation.


2011 ◽  
Vol 347-353 ◽  
pp. 1902-1905
Author(s):  
Hua Li You

Water is the basis of natural resources and strategic economic resources.Deteriorated water environment of streams in Shenzhen city could have a great impact on ecological safety, people's health,and economic development.Based on the data of field observation and Remote sensing (RS) image,integrated analysis of the water degradation causes,and the changes of biochemical oxygen demand in five days(BOD5)concentration by mathematical model were carried out,which is on basis of percentage of waste water disposal,fresh water transformation,and harbor excavation, respectively.The results show that degradation causes of water quality were resulted from waste water discharge, harbor construction,and ecological environment damage, which could lead to slowly water exchange. Accordingly,the pollution can be easily to store in the bay,which result in water quality changes.The most important improved countermeasure is the control of waste water, which could be had a great effectiveness to decrease pollution.In addition, fresh water must be supplied after polluted water was cut off,which can be better improvement for water quality.This would be extreme improvement for hydrological dynamics due to 15m harbor excavation,which can significantly reduce BOD5 concentration.The innovation points of this paper is to mathematical model,which is based on the basis of qualitative analysis.


Author(s):  
Takeshi Mizunoya ◽  
Noriko Nozaki ◽  
Rajeev Kumar Singh

AbstractIn the early 2000s, Japan instituted the Great Heisei Consolidation, a national strategy to promote large-scale municipal mergers. This study analyzes the impact that this strategy could have on watershed management. We select the Lake Kasumigaura Basin, the second largest lake in Japan, for the case study and construct a dynamic expanded input–output model to simulate the ecological system around the Lake, the socio-environmental changes over the period, and their mutual dependency for the period 2012–2020. In the model, we regulate and control the following water pollutants: total nitrogen, total phosphorus, and chemical oxygen demand. The results show that a trade-off between economic activity and the environment can be avoided within a specific range of pollution reduction, given that the prefectural government implements optimal water environment policies, assuming that other factors constraining economic growth exist. Additionally, municipal mergers are found to significantly reduce the budget required to improve the water environment, but merger budget efficiency varies nonlinearly with the reduction rate. Furthermore, despite the increase in financial efficiency from the merger, the efficiency of installing domestic wastewater treatment systems decreases drastically beyond a certain pollution reduction level and eventually reaches a limit. Further reductions require direct regulatory instruments in addition to economic policies, along with limiting the output of each industry. Most studies on municipal mergers apply a political, administrative, or financial perspective; few evaluate the quantitative impact of municipal mergers on the environment and environmental policy implications. This study addresses these gaps.


2018 ◽  
pp. 70-79 ◽  
Author(s):  
Le Viet Thang ◽  
Dao Nguyen Khoi ◽  
Ho Long Phi

In this study, we investigated the impact of climate change on streamflow and water quality (TSS, T-N, and T-P loads) in the upper Dong Nai River Basin using the Soil and Water Assessment Tool (SWAT) hydrological model. The calibration and validation results indicated that the SWAT model is a reasonable tool for simulating streamflow and water quality for this basin. Based on the well-calibrated SWAT model, the responses of streamflow, sediment load, and nutrient load to climate change were simulated. Climate change scenarios (RCP 4.5 and RCP 8.5) were developed from five GCM simulations (CanESM2, CNRM-CM5, HadGEM2-AO, IPSL-CM5A-LR, and MPI-ESM-MR) using the delta change method. The results indicated that climate in the study area would become warmer and wetter in the future. Climate change leads to increases in streamflow, sediment load, T-N load, and T-P load. Besides that, the impacts of climate change would exacerbate serious problems related to water shortage in the dry season and soil erosion and degradation in the wet season. In addition, it is indicated that changes in sediment yield and nutrient load due to climate change are larger than the corresponding changes in streamflow.


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