Monitoring and modelling mining impacts on water quality in Chindwin River Basin, Myanmar

Author(s):  
Thanapon Piman ◽  
Chayanis Krittasudthacheew ◽  
Shakthi K. Gunawardanaa ◽  
Sangam Shresthaa

<p>The Chindwin River, a major tributary of the Ayeyarwady River in Myanmar, is approximately 850 km long with a watershed area of 115,300 km<sup>2</sup>. The Chindwin River is essential for local livelihoods, drinking water, ecosystems, navigation, agriculture, and industries such as logging and mining. Over the past two decades, Myanmar’s rapid economic development has resulted in drastic changes to socio-economic and ecological conditions in the basin. Water users in the basin reported that there is a rapid extension of gold and jade mining and they observed a noticeable decline in water quality along with increased sedimentation and turbidity. So far, however, Myanmar has not undertaken a comprehensive scientific study in the Chindwin River Basin to assess water quality and sources of water pollution and to effectively address issues of river basin degradation and concerns for public health and safety. This study aims to assess the status of water quality in the Chindwin River and the potential impact of mining activities on the water quality and loading through monitoring program and modeling approach. 17 locations in the upper, middle and lower parts of the Chindwin River Basin were selected for water quality monitoring. These sites are located near Homalin, Kalewa, Kani and Monywa townships where human activities and interventions could affect water quality. Water quality sampling and testing in the Chindwin River was conducted two times per year: in the dry season (May-June) and in the wet season (September-October) during 2015-2017. We monitored 21 parameters including heavy metals such as Lead (Pb), Mercury (Hg), Copper (Cu) and Iron (Fe). The observed values of Mercury in Uru River in the upper Chindwin River Basin which located nearby gold mining sites shown higher than the WHO drinking standard. This area also has high values of turbidity and Total Suspended Solid. The SHETRAN hydrological model, PHREEQC geochemical model and LOADEST model were used to quantify the heavy metal loads in the Uru River. Results from scenario analysis indicate an increase in Arsenic and Mercury load under increment of concentration due to expansions in mining areas. In both baseline and future climate conditions, the Uru downstream area shows the highest load effluent in both Arsenic and Mercury. These heavy metal loads will intensify the declining water quality condition in Chindwin River and can impact negatively on human health who use water for drinking. Therefore, we recommend that water quality monitoring should continue to provide scientific-evidence for decision-makers to manage water quality and mining activities properly.  Water treatment systems for drinking water are required to remove turbidity, Total Suspended Solid, and Mercury from raw water sources. Raising awareness of relevant stakeholders (local people, farmers, private sectors, etc.) is necessary as many people living in the Chindwin River Basin are using water directly from the river and other waterways without proper water treatment.</p>

2021 ◽  
Vol 9 ◽  
Author(s):  
Anna E. Windle ◽  
Greg M. Silsbe

Unoccupied aircraft systems (UAS, or drones) equipped with off-the-shelf multispectral sensors originally designed for terrestrial applications can also be used to derive water quality properties in coastal waters. The at-sensor total radiance a UAS measured constitutes the sum of water-leaving radiance (LW) and incident radiance reflected off the sea surface into the detector’s field of view (LSR). LW is radiance that emanates from the water and contains a spectral shape and magnitude governed by optically active water constituents interacting with downwelling irradiance while LSR is independent of water constituents and is instead governed by a given sea-state surface reflecting light; a familiar example is sun glint. Failure to accurately account for LSR can significantly influence Rrs, resulting in inaccurate water quality estimates once algorithms are applied. The objective of this paper is to evaluate the efficacy of methods that remove LSR from total UAS radiance measurements in order to derive more accurate remotely sensed retrievals of scientifically valuable in-water constituents. UAS derived radiometric measurements are evaluated against in situ hyperspectral Rrs measurements to determine the best performing method of estimating and removing surface reflected light and derived water quality estimates. It is recommended to use a pixel-based approach that exploits the high absorption of water at NIR wavelengths to estimate and remove LSR. Multiple linear regressions applied to UAS derived Rrs measurements and in situ chlorophyll a and total suspended solid concentrations resulted in 37 and 9% relative error, respectively, which is comparable to coastal water quality algorithms found in the literature. Future research could account for the high resolution and multi-angular aspect of LSR by using a combination of photogrammetry and radiometry techniques. Management implications from this research include improved water quality monitoring of coastal and inland water bodies in order to effectively track trends, identify and mitigate pollution sources, and discern potential human health risks.


Author(s):  
Yu.A. Novikova ◽  
I.O. Myasnikov ◽  
A.A. Kovshov ◽  
N.A. Tikhonova ◽  
N.S. Bashketova

Summary. Introduction: Drinking water is one of the most important environmental factors sustaining life and determining human health. The goal of the Russian Federal Clean Water Project is to improve drinking water quality through upgrading of water treatment and supply systems using advanced technologies, including those developed by the military-industrial complex. The most informative and reliable sources of information for assessing drinking water quality are the results of systematic laboratory testing obtained within the framework of socio-hygienic monitoring (SGM) and production control carried out by water supply organizations. The objective of our study was to formulate approaches to organizing quality monitoring programs for centralized cold water supply systems. Materials and methods: We reviewed programs and results of drinking water quality laboratory tests performed by Rospotrebnadzor bodies and institutions within the framework of SGM in 2017–2018. Results: We established that drinking water quality monitoring in the constituent entities of the Russian Federation differs significantly in the number of monitoring points (566 in the Krasnoyarsk Krai vs 10 in Sevastopol) and measured indicators, especially sanitary and chemical ones (53 inorganic and organic substances in the Kemerovo Region vs one indicator in the Amur Region). Discussion: For a more complete and objective assessment of drinking water quality in centralized cold water supply systems, monitoring points should be organized at all stages of water supply with account for the coverage of the maximum number of people supplied with water from a particular network. Thus, the number of points in the distribution network should depend, inter alia, on the size of population served. In urban settlements with up to 10,000 inhabitants, for example, at least 4 points should be organized while in the cities with more than 3,000,000 inhabitants at least 80 points are necessary. We developed minimum mandatory lists of indicators and approaches to selecting priority indices to be monitored at all stages of drinking water supply.


1989 ◽  
Vol 21 (12) ◽  
pp. 1877-1880 ◽  
Author(s):  
S. Saito ◽  
K. Hattori ◽  
T. Okumura

Outflows of organic halide precursors (OXPs) from forest regions were studied in relation to water quality monitoring in the Yodo River basin. Firstly, the contribution of outflows from forest regions relative to the total was roughly estimated. Then equations for flows of these substances were formulated, divided into four different subflow categories: precipitation; throughfall; surface soil layer; and, deep soil layer. Finally, annual outflow loads were calculated for a test forest area.


Author(s):  
Jose Simmonds ◽  
Juan A. Gómez ◽  
Agapito Ledezma

This article contains a multivariate analysis (MV), data mining (DM) techniques and water quality index (WQI) metrics which were applied to a water quality dataset from three water quality monitoring stations in the Petaquilla River Basin, Panama, to understand the environmental stress on the river and to assess the feasibility for drinking. Principal Components and Factor Analysis (PCA/FA), indicated that the factors which changed the quality of the water for the two seasons differed. During the low flow season, water quality showed to be influenced by turbidity (NTU) and total suspended solids (TSS). For the high flow season, main changes on water quality were characterized by an inverse relation of NTU and TSS with electrical conductivity (EC) and chlorides (Cl), followed by sources of agricultural pollution. To complement the MV analysis, DM techniques like cluster analysis (CA) and classification (CLA) was applied and to assess the quality of the water for drinking, a WQI.


Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 420 ◽  
Author(s):  
Thuy Hoang Nguyen ◽  
Björn Helm ◽  
Hiroshan Hettiarachchi ◽  
Serena Caucci ◽  
Peter Krebs

Although river water quality monitoring (WQM) networks play an important role in water management, their effectiveness is rarely evaluated. This study aims to evaluate and optimize water quality variables and monitoring sites to explain the spatial and temporal variation of water quality in rivers, using principal component analysis (PCA). A complex water quality dataset from the Freiberger Mulde (FM) river basin in Saxony, Germany was analyzed that included 23 water quality (WQ) parameters monitored at 151 monitoring sites from 2006 to 2016. The subsequent results showed that the water quality of the FM river basin is mainly impacted by weathering processes, historical mining and industrial activities, agriculture, and municipal discharges. The monitoring of 14 critical parameters including boron, calcium, chloride, potassium, sulphate, total inorganic carbon, fluoride, arsenic, zinc, nickel, temperature, oxygen, total organic carbon, and manganese could explain 75.1% of water quality variability. Both sampling locations and time periods were observed, with the resulting mineral contents varying between locations and the organic and oxygen content differing depending on the time period that was monitored. The monitoring sites that were deemed particularly critical were located in the vicinity of the city of Freiberg; the results for the individual months of July and September were determined to be the most significant. In terms of cost-effectiveness, monitoring more parameters at fewer sites would be a more economical approach than the opposite practice. This study illustrates a simple yet reliable approach to support water managers in identifying the optimum monitoring strategies based on the existing monitoring data, when there is a need to reduce the monitoring costs.


Desalination ◽  
2008 ◽  
Vol 226 (1-3) ◽  
pp. 306-320 ◽  
Author(s):  
Anastasia D. Nikolaou ◽  
Sureyya Meric ◽  
Demetris F. Lekkas ◽  
Vincenzo Naddeo ◽  
Vincenzo Belgiorno ◽  
...  

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