Watershed Delineation of Rivers in Karaikal District using Remote Sensing and GIS Technique

Water carry nutrients to areas all around the earth. They play a most important part in the water cycle, acting as drainage channels for surface water. Rivers provide good habitat and food for many of the earth's organisms. The purpose of this study is to delineate the watersheds basin in the Karaikal district from Bhuvan and United States Geological Survey (USGS) website. Digital Elevation Model is the main data source for extracting hydrology data in ArcGIS. Model Builder was the key for creation of Flow Accumulation, Stream segment, pour point and contour has been prepared using surface tool in ArcGIS software. Watershed delineation map is obtained by integration of Flow Accumulation, Stream segment and Pour point. Watershed analysis provides catchment boundaries but also hydrological parameters useful for management programs.

The Water Pollution Control Planning Research in Lingyuan Stream Segment of Daling River

Through to analysis the influence of the effluent from the sewage treatment plant to the river water quality of Fangshen-Habaqi stream segment in lower reaches comprehensively, in order to achieve water pollution control and water function zone protection. This paper use QUAL2K model to simulate the influence to lower reaches water quality, and the simulation factor is BOD. The result showed that the downstream BOD concentration cannot reach the water quality standards Ⅲ. This paper provides some corresponding control measures, so as to provide the scientific basis of the water pollution control planning research.

Effects of sampling effort, assemblage similarity, and habitat heterogeneity on estimates of species richness and relative abundance of stream fishes

We estimated the sampling effort required to accurately estimate species richness and to detect changes in catch-per-unit-effort (CPUE) in four Great Plains, USA, streams. The number of sampled reaches (i.e., <1 km) required to estimate stream-segment (i.e., 20–28 km) species richness decreased with increased sampled reach length (i.e., 10, 20, 40, or 60 mean stream widths, MSW), whereas total sampling effort decreased with a greater number of shorter sampled reaches. Collecting all species in a stream segment required all sampled reaches (i.e., 10) of a length equal to 40 or 60 MSW. The number of stream reaches sampled with lengths equal to 40 MSW required to detect a 50% change in CPUE of common species (i.e., total abundance > 1% of total catch) with β = 0.80 ranged from 7 to 630 (mean = 99) and decreased with longer sampled reaches. A greater number of sampled reaches were needed to detect 90% of species richness and 25% changes in CPUE when Jaccard’s similarity of samples of stream fish assemblages and habitat heterogeneity was lower within streams. Our results suggest that homogeneous stream segments require more sampled reaches to characterize fish assemblages and monitor trends in fish abundance.

Sampling effort and fish species richness in small terra firme forest streams of central Amazonia, Brazil

Small streams are important components of the landscape in terra firme forests in central Amazonia and harbor a large number of fish species. Nevertheless, the lack of a common sampling protocol in studies of this ichthyofauna hinders comparisons among available results. This study evaluates how the length of stream reach sampled affects estimates of local fish species density in 1st, 2nd, and 3rd order streams, and proposes a mean minimum sampling length that best approximates the absolute number of species in a given stream segment. We sampled three streams in the Biological Dynamics of Forest Fragments Project's study sites, between May and August 2004. At each stream, one 1st order, one 2nd order, and one 3rd order segment was sampled. We sampled five 20-m reaches in each stream segment. Three to four people collected along each reach for 45 to 60 minutes. We used Jaccard's coefficient to estimate the similarity of species composition among stream reaches and segments. Estimates of species richness were obtained with Jackknife 1 and Bootstrap algorithms and species accumulation curves. We used simple linear regressions to look for relationships between species density and fish abundance and between species density and the volume of 100-m stream segments. Species density in 1st order stream reaches was slightly higher than in 2nd and 3rd order stream reaches, whereas fish abundance was apparently higher in 3rd order reaches. Similarity in fish species composition between 20-m reaches was low for all studied streams. Species density values in pooled 100-m stream segments represented 71.4% to 94.1% of the estimated values for these streams. Species density showed a direct relationship both with volume of the sampled stream segment and fish abundance. It seems plausible that larger streams contain a higher number of microhabitat types, which allow for the presence of more fish species per stream length. Based on the values of asymptotes and equations for species accumulation curves, the mean minimum sampling length that best estimates the absolute number of species in a stream segment is 180 m ± 20 sd for 1st order segments; 213 m ± 23 sd for 2nd order segments, and 253 m ± 30 sd for 3rd order stream segments.