Characterizing and explaining spatio-temporal variation of water quality in a highly disturbed river by multi-statistical techniques

Abstract

Assessing the spatio-temporal variations of surface water quality is important for water environment management. In this study, surface water samples are collected from 2008 to 2015 at 17 stations in the Ying River basin in China. The two pollutants i.e. chemical oxygen demand (COD) and ammonia nitrogen (NH3-N) are analyzed to characterize the river water quality. Cluster analysis and the seasonal Kendall test are used to detect the seasonal and inter-annual variations in the dataset, while the Moran’s index is utilized to understand the spatial autocorrelation of the variables. The influence of natural factors such as hydrological regime, water temperature and etc., and anthropogenic activities with respect to land use and pollutant load are considered as driving factors to understand the water quality evolution. The results of cluster analysis present three groups according to the similarity in seasonal pattern of water quality. The trend analysis indicates an improvement in water quality during the dry seasons at most of the stations. Further, the spatial autocorrelation of water quality shows great difference between the dry and wet seasons due to sluices and dams regulation and local nonpoint source pollution. The seasonal variation in water quality is found associated with the climatic factors (hydrological and biochemical processes) and flow regulation. The analysis of land use indicates a good explanation for spatial distribution and seasonality of COD at the sub-catchment scale. Our results suggest that an integrated water quality measures including city sewage treatment, agricultural diffuse pollution control as well as joint scientific operations of river projects is needed for an effective water quality management in the Ying River basin.

Temporal and Vertical Relations between Various Environmental Factors in the Largest Lake of Łęczna-Włodawa Lake District (Eastern Poland)

“…An influence of inter-annual distribution of precipitation and air temperature on environmental factors was observed. A clear separation of each year's data, indicating various physical and chemical condition of lake waters, resulted from highly different weather conditions, which is supported by previous findings of Sass et al [20], Liu et al [30], and Jeppesen et al [31]. Significant seasonal differences found in our study in water quality parameters have also been lastly reported in other Łęczna-Włodawa lakes [32] as well as in other temperate lakes [33].…”

Landuse and surface water quality in an emerging urban city

“…Taking into cognizance the intricate spatial and temporal variation in water quality, two prominent types of information required for an effective management of river water quality have been identified. These are spatial and temporal characteristics of the pollutants and information that relates to the propelling factors influencing the water quality (Ifabiyi 2000;Liu et al 2016;Fashae et al 2017a;Olusola et al 2017). In recent years, there has been a rapid declining availability of usable fresh water in terms of water quality and quantity due to unsustainable landuse practices (Ngoye and Machiwa 2004).…”

Application of positive matrix factorization to identify potential sources of water quality deterioration of Huaihe River, China

“…Irrigation tailwater discharges due to conventional irrigation system in the study area deteriorate surface water quality via nutrient loss with soil erosion (Yu et al 2016). Furthermore, seasonal first flush of rainfall is the second potential cause of water quality degradation (Liu et al 2016). Late spring rainfall, after long dry season, drains fertilizers and pesticides to nearby watercourses which degrade surface water quality (Liu et al 2017).…”