Author(s): Pattiyage I. A. Gomes; Onyx W. H. Wai
Linked Author(s): Onyx W.H. Wai, Pattiyage Ishan Ayantha Gomes
Keywords: Cell-in-series; Ecology; Mesoscale; Total variance; Water quality
Abstract: The commonly used sampling methods at equal segments, namely cell-in-series (CIS), andan approach based on functional classification of streams, namely mesoscale physical habitats (MPH), have been compared to evaluate the performance of sampling methods on spatiotemporal variation of stream water quality. Sampling was carried out in the Tseng LanShue stream (1-3 orders), during spring (dry) and summer (wet) in 2012. Each season observations were donefor two states: typical (no sever rainfalls); flushed (2-3 days after a severe rainfall). The response variables (chlorophyll-a, turbidity, dissolved oxygen, nitrate-nitrogen, nitrite-nitrogen, ammoniacal nitrogen and soluble reactive phosphorous) were checked against a group of hydro-environmental variables. These included: stream velocity, width and depth (and the derivatives), slope, bankfull dimensions, and substrate conditions. Relationships among variables were evidenced using redundancy analysis. In general, the water quality parameters showed an irregular variation in the longitudinal direction of the stream. Water quality and hydro-environmental variables based on the best two axes explained 41% of the total variance in response data for MPH approach in spring. For CIS it was 44% . However, in the flushed state these were observed to be 60% and 35% for MPH and CIS, respectively. Similar trend was observed in summer where explanatory power based on CIS was high for the typical state, but otherwise for the flushed state. Furthermore, the significant environmental variable (s) for the respective cases changed with the approach: substrate conditions for CIS; and stream width and its derivatives for MPH. This elucidates explanation and modelling of water quality of a stream is distinctive with the sampling methodas well as weather scenarios. Results elucidated MPH approach is more suitable than CIS as a modelling tool when the stream has less anthropogenic loads. We conclude that the explanatory powers of MPH and CIS approaches could be useful in providing a quantitative definition on what is really meant by a “pristine stream”.