Ecological River Health Assessments Using Chemical Parameter Model and the Index of Biological Integrity Model

Abstract

River health is one of the important issues today because of various threats by multiple anthropogenic stressors that have long-term impacts on the physical habitats, biodiversity, ecological functions, and their services. The main objectives of this study is to diagnose the chemical and biological river health in the watershed of Geum River with regard to the chemical regimes (N, P) and fish community using multi-metric chemical pollution index (CPI), and the index of biotic integrity model (IBI), respectively. The empirical models of sestonic chlorophyll, nutrients (N, P), and nutrient ratios of N:P indicated that the watershed, including all sampling sites, was a phosphorus-limited system. Analysis of fish trophic and tolerance guilds showed that the omnivore fish species and tolerant fish species were dominant in the watershed, while the sensitive fish species decreased downstream because of nutrient enrichments (such as TN, TP) and organic matter pollutions (such as BOD, COD). The chemical model of CPI showed that 11 sampling sites were in the fair—good condition, and 8 sites were in poor—very poor condition. Species composition analysis indicated that Zacco platypus was most widely distributed in the watersheds and dominated the fish community. The biological health of the watershed, based on the multimetric IBI model, was in poor condition and was getting worse downstream. The degradation of the river health was matched with the chemical health and showed a decreased abundance of insectivores and sensitive fish species. The outcomes of the river health were supported by principal component analysis (PCA) and cluster analysis (CA) of fish model metrics and the physicochemical parameters. Overall, our study suggests that river health was directly influenced by the chemical pollutions of nutrients and organic matter inputs.

Application of Multivariate Statistical Techniques and Water Quality Index for the Assessment of Water Quality and Apportionment of Pollution Sources in the Yeongsan River, South Korea

“…The observed increase in the COD level appeared to be due to an increase in organic non-biodegradable substances driven by industrial growth and increasing population density, which led to continuous waste inputs into the river [29]. Previous studies have reported that high COD levels are caused by high levels of non-biodegradable organic wastewater, increased inputs of several non-point source pollutants such as humic substances during rainfall, and internal production by algae and aquatic plants [29,42,76]. As with the Yeongsan River, the concentrations of COD are increasing in the Nakong, Han, and Geum Rivers, while BOD is declining [12,42,77].…”

“…The resulting clusters of objects show high internal homogeneity (within the cluster) and high external heterogeneity (between clusters). One of the most common CA methods is Bray-Curtis similarity index clustering, which determines the level of similarity between any sample and the entire dataset and is usually illustrated as a dendrogram [42]. The dendrogram offers a visual depiction of the clustering processes and provides a simplified image of the groups and their proximity by dramatically reducing the dimensionality of the original data [6].…”

“…Previous studies have reported that high COD levels are caused by high levels of non-biodegradable organic wastewater, increased inputs of several non-point source pollutants such as humic substances during rainfall, and internal production by algae and aquatic plants [29,42,76]. As with the Yeongsan River, the concentrations of COD are increasing in the Nakong, Han, and Geum Rivers, while BOD is declining [12,42,77]. The CHL-a concentration in the river has been growing, and more frequent algal blooms have occurred in recent years.…”

An Assessment of Lake Ecology on the Basis of the Macrobenthos Multi-Metric Index (MMI) in 11 Lakes in the Western Region of Jilin, China

“…Previous studies have shown that biological indicators could be used for long-term aquatic ecosystem health assessment. For example, phytoplankton, macrobenthos, fish, and aquatic plants could be used for the characterization of ecosystem health [5][6][7][8]. As one of the most effective tools to characterize human disturbance, the multi-metric index has been widely used all over the world as a more reliable tool as compared to a single index assessment [9][10][11][12][13][14].…”

Ecosystem Health of the Beiyun River Basin (Beijing, China) as Evaluated by the Analytic Hierarchy Process Method

“…Scholars have carried out a lot of work in river health index system and its evaluation methods and applied them in various rivers, and obtained many successful experiences. HaRa et al (2019) used the chemical pollution index (CPI) and the index of biological integrity (IBI) to diagnose the chemical system (N, P) and the chemical and biological river health of fish in the Gemu River Basin. Zhang et al (2016) proposed a new concept of lake ecosystem health, a driver-pressure-state-impact-response (DPSIR) management framework, an indicator system of water quality, as well as ecological and socioeconomic criteria to evaluate the lake, Nansi Lake in China.…”