Towards a new drinking water resource classification approach at a river basin scale

2012 ◽  
Vol 12 (6) ◽  
pp. 727-736
Author(s):  
S. Piel ◽  
E. Baurès ◽  
S. Masclet ◽  
J. Perot ◽  
O. Thomas

This study proposes a new approach for improving resource quality management, monitoring and treatment plant management, whatever the environmental and climatic stressors. First trend analysis of water quality at a river basin scale, based on historical water quality data and multivariate exploitation (principal component analysis, PCA), led to a classification of the monitoring stations with regard to the main pressures (land use, urbanization and hydroclimatic impacts). This method was applied to the Vilaine's watershed, the largest river basin in Brittany, western France, and one which is under agricultural and urban pressure. A complementary research using a UV index was proposed for the evaluation of spatial and temporal variations of water quality. This approach may be considered as a useful and relevant tool to quickly assess the variation of water quality and the main explanatory factors. It also points out monitoring stations under specific stressors considered as outliers regarding UV parameters. Finally, PCA and UV index give complementary results. PCA allows factors influencing drinking water resource to be highlighted and the UV index allows global water quality under specific times and impacts to be reflected.

2011 ◽  
Vol 14 (1) ◽  
pp. 16-28
Author(s):  
Long Ta Bui ◽  
Truong Duy Cao ◽  
Huong Thi My Hoang

Recently, due to the impact of natural factors and human activities, the water quality in several basins in Vietnam has been seriously degraded. Pressing issues happening in the entire river basin-scale is polluted by waste from urban and industrial areas, oil spills and waste management. So far the system of policies and legal documents relating to protection of water quality basin is still missing and not synchronized, ensure funding for activities to protect water quality basin not meeting actual requirements. In particularly, there is no information data system to cater for the management of basin water quality which is the core of the problem of environmental protection of river basins. The main reason that make pollution happened at the entire river basin scale is bad waste management. which partly due to the lack of a good system of technical data and legal documents related to protection of river basin water quality. In this paper, we present research results from the process of building model for management and information sharing of environmental water quality at Dong Nai river basin.


1997 ◽  
Vol 12 (4) ◽  
pp. 275-284 ◽  
Author(s):  
Ari Jolma ◽  
Carlo De Marchi ◽  
Mark Smith ◽  
B.J.C. Perera ◽  
László Somlyódy

2021 ◽  
Vol 13 (11) ◽  
pp. 6318
Author(s):  
Rafael Rodríguez ◽  
Marcos Pastorini ◽  
Lorena Etcheverry ◽  
Christian Chreties ◽  
Mónica Fossati ◽  
...  

The monitoring of surface-water quality followed by water-quality modeling and analysis are essential for generating effective strategies in surface-water-resource management. However, worldwide, particularly in developing countries, water-quality studies are limited due to the lack of a complete and reliable dataset of surface-water-quality variables. In this context, several statistical and machine-learning models were assessed for imputing water-quality data at six monitoring stations located in the Santa Lucía Chico river (Uruguay), a mixed lotic and lentic river system. The challenge of this study is represented by the high percentage of missing data (between 50% and 70%) and the high temporal and spatial variability that characterizes the water-quality variables. The competing algorithms implement univariate and multivariate imputation methods (inverse distance weighting (IDW), Random Forest Regressor (RFR), Ridge (R), Bayesian Ridge (BR), AdaBoost (AB), Hubber Regressor (HR), Support Vector Regressor (SVR) and K-nearest neighbors Regressor (KNNR)). According to the results, more than 76% of the imputation outcomes are considered “satisfactory” (NSE > 0.45). The imputation performance shows better results at the monitoring stations located inside the reservoir than those positioned along the mainstream. IDW was the model with the best imputation results, followed by RFR, HR and SVR. The approach proposed in this study is expected to aid water-resource researchers and managers in augmenting water-quality datasets and overcoming the missing data issue to increase the number of future studies related to the water-quality matter.


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.


1991 ◽  
Author(s):  
Patrick Edelmann ◽  
Julie Altamore Scaplo ◽  
Don Anthony Colalancia ◽  
Brian B. Elson

Sign in / Sign up

Export Citation Format

Share Document