Spatial pattern assessment of river water quality: implications of reducing the number of monitoring stations and chemical parameters

Abstract

The Tamsui River basin is located in Northern Taiwan and encompasses the most metropolitan city in Taiwan, Taipei City. The Taiwan Environmental Protection Administration (EPA) has established 38 water quality monitoring stations in the Tamsui River basin and performed regular river water quality monitoring for the past two decades. Because of the limited budget of the Taiwan EPA, adjusting the monitoring program while maintaining water quality data is critical. Multivariate analysis methods, such as cluster analysis (CA), factor analysis (FA), and discriminate analysis (DA), are useful tools for the statistically spatial assessment of surface water quality. This study integrated CA, FA, and DA to evaluate the spatial variance of water quality in the metropolitan city of Taipei. Performing CA involved categorizing monitoring stations into three groups: high-, moderate-, and low-pollution areas. In addition, this categorization of monitoring stations was in agreement with that of the assessment that involved using the simple river pollution index. Four latent factors that predominantly influence the river water quality of the Tamsui River basin are assessed using FA: anthropogenic pollution, the nitrification process, seawater intrusion, and geological and weathering processes. We plotted a spatial pattern using the four latent factor scores and identified ten redundant monitoring stations near each upstream station with the same score pattern. We extracted five significant parameters by using DA: total organic carbon, total phosphorus, As, Cu, and nitrate, with spatial variance to differentiate them from the polluted condition of the group obtained by using CA. Finally, this study suggests that the Taiwan EPA can adjust the surface water-monitoring program of the Tamsui River by reducing the monitoring stations to 28 and the measured chemical parameters to five to lower monitoring costs.

The Wabash Sampling Blitz: A Study on the Effectiveness of Citizen Science

“…The cluster results also can be used by WREC to determine which sites need no further testing given a shortage of volunteers or a reduction in budget (Wang et al 2014). Lastly, this cluster analysis demonstrates how volunteercollected and tested data (transparency, temperature, pH) can be used along with volunteer-collected and labtested data (nutrients, DOC) to perform more complex and informative analyses of water quality data.…”

“…Cluster analysis is a multivariate statistical technique that can aid in interpreting very large datasets by grouping objects (e.g., sampling sites) with similar characteristics together, and is a common tool used in riverine systems (Bierman et al 2011). While many studies have used cluster analysis techniques to interpret water chemistry data (Alberto et al 2001;Daughney et al 2012;Güler et al 2002;Kim et al 2005;Mavukkandy et al 2014;Najar et al 2012;Pati et al 2014;Shrestha and Kazama 2007;Simeonov et al 2003;Singh et al 2004;Singh et al 2005;Templ et al 2008;Wang et al 2013;Wang et al 2014), none of these studies were conducted as part of a citizen science effort or used data collected by citizen science volunteers. Six variables that had the most data available were used in the cluster analyses.…”

Using probability-based spatial estimation of the river pollution index to assess urban water recreational quality in the Tamsui River watershed

“…The rivers in the densely populated regions, such as those near monitoring stations DH6, DH7, XD8, TS1, and TS2, were the severely polluted (Fig. 1) because of large amounts of household sewage and industrial wastewater leachate (Wang et al 2014). Because of seawater dilution and river self-purification (Wei et al 2009), the water quality at the surrounding Tamsui River mouth was improved from moderately polluted to nonpolluted at monitoring stations such as TS3 and TS4.…”

“…Table 3 lists the ratios of the assigned category length to total length. The severely polluted RPI category was mainly located along the Dahan Stream and Tamsui River between the convergences with the Shanxia Stream and Keelung River, where household sewage and industrial wastewater were substantial (Wang et al 2014). After the rain season began, the size of the severely polluted category was reduced because of flushing.…”

“…Therefore, the Taiwan government has implemented a long-term plan to remediate the water quality in the Tamsui River watershed since 1988. The river water quality has been improved markedly by the building of sewage and wastewater treatment systems, promulgation of a strict effluent standard, relocation of livestock farms, and removal of open garbage dumping sites (Wang et al 2014). Furthermore, because urban green lands and parks have been considerably limited after urbanization, the government has established numerous recreational facilities, such as riverbank parks and ferry and yacht piers, along the banks of the Tamsui River and its tributaries.…”