Similarities among small watercourses based on multiparameter physico-chemical measurements

Abstract

With the introduction of the Water Framework Directive, the relative importance of smaller waterways increased. This statement is particularly true for Hungary, where water-quality monitoring of most smaller rivers only began 12 years ago. Due to their large number, and the lack of historical data concerning their state, systematic monitoring is a challenge. In the current study, 101 creeks are characterized on the one hand by 13 physico-chemical quality parameters (pH, electric conductivity, chloride ion concentration, dissolved oxygen, oxygen saturation, biochemical oxygen demand, chemical oxygen demand, total organic carbon, ammonium nitrogen, total inorganic nitrogen, total nitrogen, orthophosphate and total phosphorus), on the other hand by their watershed's relief, land use, and point sources' pollution indicators. Euclidean distance between water bodies (henceforth WBs) is calculated according to normalized physico-chemical monitoring values. They are grouped into clusters using the hierarchical clustering method. Watershed characteristics are used to explain the clustering via linear discriminant analysis. The investigation revealed that the main driver of cluster group creation is related to human impact: diffuse agricultural and point-source pollution. The first of the three clusters involved water bodies with low or no human impact; the second cluster contained those with medium-level anthropogenic disturbance, while waters with high pollution values formed the third cluster. Mean distance between heavily polluted waters was 1.5 times higher than that between those showing no or low disturbance, meaning that pristine waters are more similar to one another than polluted ones. The current number of samples per river is twice as high in cluster 1 as in cluster 3, revealing that there is room for optimization of the monitoring system. This contribution uses Hungary as a case study.

Predicting small water courses’ physico-chemical status from watershed characteristics with two multivariate statistical methods

“…The study presented in this paper is based on the physicochemical classification of the 2 nd river basin management plan of Hungary [40]. The classification was based on water quality measurements from years 2009 -2012 for following water quality variables: pH, electric conductivity, chloride ion concentration, dissolved oxygen, oxygen saturation, biochemical oxygen demand, chemical oxygen demand, total organic carbon, ammonium ion concentration, total inorganic nitrogen, total nitrogen, orthophosphate ion concentration, total phosphorus [17,41]. Only river water bodies classified with high reliability were included in the present study.…”

“…A plethora of studies reveal that there is an apparent link between a watershed's characteristics and it's water quality [15][16][17]. In the hypothetical case of having all the knowledge on the background factors and the processes, no monitoring would be needed.…”