Water quality modelling of Jadro spring.

PubMed

Margeta, J; Fistanic, I

2004-01-01

Management of water quality in karst is a specific problem. Water generally moves very fast by infiltration processes but far more by concentrated flows through fissures and openings in karst. This enables the entire surface pollution to be transferred fast and without filtration into groundwater springs. A typical example is the Jadro spring. Changes in water quality at the spring are sudden, but short. Turbidity as a major water quality problem for the karst springs regularly exceeds allowable standards. Former practice in problem solving has been reduced to intensive water disinfection in periods of great turbidity without analyses of disinfection by-products risks for water users. The main prerequisite for water quality control and an optimization of water disinfection is the knowledge of raw water quality and nature of occurrence. The analysis of monitoring data and their functional relationship with hydrological parameters enables establishment of a stochastic model that will help obtain better information on turbidity in different periods of the year. Using the model a great number of average monthly and extreme daily values are generated. By statistical analyses of these data possibility of occurrence of high turbidity in certain months is obtained. This information can be used for designing expert system for water quality management of karst springs. Thus, the time series model becomes a valuable tool in management of drinking water quality of the Jadro spring.

Community structure of aquatic insects in the karstic Jadro River in Croatia.

PubMed

Rađa, Biljana; Santić, Mate

2014-04-19

This study focused on the aquatic insect community in the longitudinal gradient and temporal scales of the Jadro River. The river was sampled for a period of ten years (2000- 2010), four times per year through the various seasons, along the river course. Sampling stations were selected in the upper, middle, and downstream parts of the river. A total of 21,852 specimens of aquatic insects belonging to six orders were obtained. The species determination confirmed 27 different species in the river. The data were analyzed by the multivariate methodologies of correspondence analysis and cluster analysis (unweighted pair group method with arithmetic mean) using the similarity index of Morosita for all ten years. Canonical correspondence analysis was applied to the data to check which of the mesured physicochemical variables significantly explained community variation. According to those data, significant variables for the upper station were water temperature and dissolved oxygen, and chlorides was the significant variable for the lower stations. This is an open access paper. We use the Creative Commons Attribution 3.0 license that permits unrestricted use, provided that the paper is properly attributed.