Integrated assessment of river health based on water quality, aquatic life and physical habitat

The health conditions of Liao River were assessed using 25 sampling sites in April 2005, with water quality index, biotic index and physical habitat quality index. Based on the method of cluster analysis （CA） for water quality indices, it revealed that heavily polluted sites of Liao River are located at estuary and mainstream. The aquatic species surveyed were attached algae and benthic invertebrates. The result showed that the diversity and biomass of attached algae and benthic index of biotic integrity （B-IBI） were degrading as the chemical and physical quality of water bodies deteriorating. Physiochemical parameters, BODs, CODcr, TN, TP, NH3-N, DO, petroleum hydrocarbon and conductivity, were statistically analyzed with principal component analysis and correlation analysis. The statistical results were incorporated into the integrated assessing water quality index, combining fecal coliform count, attached algae diversity, B-IBI and physical habitat quality score. A comprehensive integrated assessing system of fiver ecological health was established. Based on the systimetic assessment, the assessed sites are categorized into 9 ＂healthy＂ and ＂sub-healthy＂ sites and 8 ＂sub-sick＂ and ＂sick＂ sites.

Application of fish index of biological integrity(FIBI) in the Sanmenxia Wetland with water quality implications

Long-term changes of fish biotic integrity in the Sanmenxia Wetland,North China,since the 1950 s were assessed using the fish index of biological integrity（FIBI）. The water and sediment quality was evaluated by the water quality index（WQI） and sediment pollution index（SPI）. The results showed that FIBI continuously decreased from 46 to 20 during the past 5 decades,which indicated that the fish community state shifted from fair to very poor conditions,and damming by itself did not affect the fish biotic integrity. At the same time,WQI fell from 83 to 44.1,and SPI increased from 0.99 to 2.14 since the 1960 s,resulting from fast regional socio-economic development and insufficient wastewater treatment. Correlation analysis suggested that water quality significantly affected biotic integrity（r = 0.867,p 〈 0.05） through direct effects on the fish community. As a representative example of many wetlands in North China,our study clearly demonstrated that the biological integrity was degraded,induced both by water quality deterioration and sediment pollution,further driven by the contradiction between rapid development of regional economy and lagging development of sewage treatment facilities,which were thought to be the main factor responsible for the degradation of biological integrity.

Quantifying relations between altered hydrology and fish community responses for streams in Minnesota

Background:Altered hydrology is a stressor on aquatic life,but quantitative relations between specific aspects of streamflow alteration and biological responses have not been developed on a statewide scale in Minnesota.Best sub-sets regression analysis was used to develop linear regression models that quantify relations among five categories of hydrologic metrics(i.e.,duration,frequency,magnitude,rate-of-change,and timing)computed from streamgage records and six categories of biological metrics(i.e.,composition,habitat,life history,reproductive,tolerance,trophic)computed from fish-community samples,as well as fish-based indices of biotic integrity(FIBI)scores and FIBI scores normalized to an impairment threshold of the corresponding stream class(FIBI_BCG4).Relations between hydrology and fish community responses were examined using three hydrologic datasets that represented periods of record,long-term changes,and short-term changes to flow regimes in streams of Minnesota.Results:Regression models demonstrated significant relations between hydrologic explanatory metrics and fish-based biological response metrics,and the five regression models with the strongest linear relations explained over 70%of the variability in the biological metric using three hydrologic metrics as explanatory variables.Tolerance-based biological metrics demonstrated the strongest linear relations to hydrologic metrics.The most commonly used hydrologic metrics were related to bankfull flows and aspects of flow variability.Conclusions:Final regression models represent paired streamgage records and biological samples throughout the State of Minnesota and encompass differences in stream orders,hydrologic landscape units,and watershed sizes.Presented methods can support evaluations of stream fish communities and facilitate targeted efforts to improve the health of fish communities.Methods also can be applied to locations outside of Minnesota with continuous streamgage data and fish-community samples.