Priority Pollutants Monitoring and Water Quality Assessment in the Siret River Basin, Romania

The Integrated Water Resources Management regulations aim to ensure a good status of surface water quality and its sustainable use. Water quality monitoring of various water users supports the identification of pollution sources and their environmental impacts. The priority pollutants generated by wastewater discharges from municipal, industrial wastewater treatment plants or agricultural areas are of great interest due to their eco-toxicological effects and bio-accumulative properties. The aim of this study was to monitor the priority organic and inorganic pollutants from the Siret River basin, in Romania, with the purpose of assessing the surface water quality status and evaluating it by the Water Quality Index (WAWQI) method. The monitoring of inorganic priority pollutants (e.g., As, Cd, Hg, Ni, Pb) and organic priority pollutants (e.g., Naphthalene, Anthracene, Phenanthrene, Fluoranthene, Benzo(a)anthracene, Benzo(b)fluoranthene, Benzo(k)fluoranthene, Benzo(a)pyrene, Benzo(ghi)perylene, Indeno(1,2,3-cd)pyrene, α, β, and γ-Hexachlorocyclohexane, and Di-2-ethyl-hexyl-phthalate) was conducted within the Siret River basin, during the period 2015–2020. With this purpose, 21 sampling points (18 river sections and 3 lakes) were considered to assess the water quality. The results of this study proved that the water quality within the Siret River basin is generally classified in the 2nd or 3rd class. The spatial distribution of the water quality index values, using ARCGIS, also highlighted the fact that the water quality is mostly unsuitable for drinking water supplies, being influenced by the quality of its main tributaries, as well as by the effluent of wastewater treatment plants.

Wetland Ecosystem Monitoring Through Water Quality Perspectives

Water quality monitoring is an important tool in determining the safety and suitability of water for various desired and intended uses. The procedures involved in the evaluation of water quality are numerous and multifaceted. Therefore, taking into consideration the specific objectives of water quality monitoring, sampling design is of vital importance. Most of the physical parameters of water quality are determined via in-situ measurements using modern testing equipment/field testing kits. Although there are some good field-based sensors that are being used for evaluation of water quality, the chemical parameters traditionally are mostly analyzed through laboratory-based experiments. This chapter is aimed to offer an inclusive knowledge and insights on the importance and assessment of physico-chemical parameters that are of high priority for monitoring the water quality of wetlands.

Spatiotemporal Evaluation of Eutrophication State in The Hammar Marsh Using A Satellite-Based Model

Water pollution is now a major threat to the existence of living beings. Accordingly, Water quality monitoring is an important activity toward restoring water quality. As wetland eutrophication is one of the essential ecosystem elements, devastation of this element is a significant issue. The Trophic State Index (TSI) provides information about trophic condition of water bodies. This paper aims to conduct spatiotemporal monitoring for the eutrophication of the west part of Al-Hammar Marsh for the period 2013-2020. To this end, a satellite-based TSI computation model was developed and implemented by using a series of OLI Landsat satellite images. The results showed that there was no improvement in the eutrophication state in the marsh, the percentage of the low class of TSI decreased in 2015 and 2018 to 7.9% and 2.6% and increased in 2017 and 2020 to 39.8%, and 56.3%. In general, the TSI was in the poor class in all the considered periods. Fluctuation of quantity and quality of the inflow prevents restoring the eutrophication of the marsh because this process requires stability in the levels of inundation above the critical limits for the water depth and periods. Therefore, it is necessary to find suitable alternatives to provide water drainage in quantities and quality that ensure the sustainability of the marsh ecosystem.

The Dynamic Detection of Water Quality Monitoring and Pollution Prevention and Control

With the development of society, the material living standard of our people has been significantly improved, but we sacrificed the environment in the course of development, which led to the current number of environmental problems in our country is particularly large, so that now we need to pick up the tone of protecting the environment, so now the overall tone of the country is to protect the environment, adhere to the green water green mountain is the basic strategy of Jinshan Yinshan, play a good pollution prevention and control of the three major battles, care for the environment, protect the environment. And in the environment water is the most important, it carries everything, the purpose of this paper is to study based on water quality monitoring and pollution prevention and control of dynamic detection technology. In order to conduct the experiment better, after consulting the literature on water quality monitoring and pollution prevention and control, and dynamic detection technology, we used a variety of algorithms to construct a corresponding dynamic detection technology system to monitor water quality and conduct real-time surveys of pollutants, and obtain relevant experimental data to complete the experiment. The experimental results show that the improved adaptive parameter DBSCAN clustering algorithm is better than the AdaBoost algorithm and the genetic algorithm, so we finally choose to build a dynamic detection technology system using the improved adaptive parameter DBSCAN clustering algorithm.

The structure community of zooplankton and environmental conditions of the Kalimireng River estuary, Gresik, East Java

Water quality monitoring is a key component in the management of these important water resources and ecosystems. Biological indicators can be monitored continuously and are easy instructions for monitoring the occurrence of pollution. One of the biological parameters that can be used as a marker of environmental conditions is plankton. zooplankton can be used as study material to determine the quality and water productivity. The method used in this research is descriptive to determine the water quality condition in the estuary of the Kalimireng river biologically through the identification and characterization of zooplankton. Observations of plankton identification, plankton abundance, dominance index, and characterization of zooplankton were analyzed by fluorescence microscope observation. Three species of zooplankton were found in the waters of the Kalimireng estuary, Leptodiaptomus sp., Canthocamptus staphylinus, and Diaphanosoma bracyurum. Zooplankton is more abundant in water conditions at high tide compared to water conditions at low tide. At high tide, the highest abundance value was obtained at the station I at week 3, 843 ind/mL. At low tide, the highest abundance value was obtained at the station I at week 2,251 ind/L. The highest Dominance Index (D) at tidal water conditions is shown at station 2. This indicates that there is a community that dominates at that station.

Development and Implementation of Water Quality Assessment Monitoring (WQAM) System using the Internet of Things (IoT) in Water Environment

Water quality monitoring (WQM) system is widely being explored as it is needed to prevent the problem of water contamination worldwide. Nowadays, there are various studies on WQM system that are being integrated with Internet of Things (IoT) concept for Wireless Sensor Network (WSN) technology implementation to get real time data measurement. Traditional ways of collecting the data are more time consuming and they lack real time changes in the quality of water. This paper presents the development and implementation of Water Quality Assessment and Monitoring (WQAM) system. The system development used WiFi enabled microcontroller to connect with the IoT environment and store the data in the IoT cloud server. The microcontroller used is Arduino UNO that interacts with three types of sensor probes which are pH, turbidity and temperature probe. All the data measurements is transferred using a WiFi module which is ESP8266. The IoT cloud used to utilize the data frame is ThingSpeak. This system was implemented on Bandar Perda Lake and Derhaka River in Pulau Pinang with two systems implemented at each location. The sensors were placed on the water surface for more accurate measurements. This system continuously measures the readings of pH, turbidity dan temperature on the lake/river for every 1 hour. Twenty readings were taken for every 1 hour within the first 20 minutes with 1 minute interval and the readings were stored in the IoT cloud server. The readings are accessible via ThingSpeak GUI. In conclusion, this system would benefit the authorities to take advantage of using the WQAM system with the aid of the IoT that is less time consuming, less cost and more reliable in real time data reading.