河流线型对河流自净能力的影响

为研究河流线型对河流自净能力的影响,选取5条具有不同河流线型的河涌进行研究,以弯曲度和分形维数表征河流线型,以TP、NH 3-N、NO 2-N、NO 3-N、COD Cr、TOC、DOC、叶绿素(Chlorophyll)和蓝绿藻藻蓝蛋白(BGA-PC)等9项水质指标沿程削减率表征河流自净能力,并分析各研究河段的悬浮微生物生物量和生物活性,探讨河流线型影响河流自净能力的作用机制。结果表明:多项水质指标沿程削减率随河流线型蜿蜒程度的增加而提升。在直立式浆砌石挡墙河段,河流线型通过提高悬浮微生物生物活性,进而增强河流自净能力,使TP、NH 3-N、NO 3-N、DOC、Chlorophyll和BGA-PC的沿程削减率显著提升;而在格宾石笼挡墙河段,河流线型通过增加悬浮生物生物量和提高生物活性,进而增强河流自净能力,使NO 2-N、COD Cr、TOC和DOC的沿程削减率显著提高。     

Factors influencing the sinuosity of Pannagon River, Kottayam, Kerala, India: An assessment using remote sensing and GIS

The present study was carried out to identify the factors influencing the sinuosity of the Pannagon river, using the IRS P6 LISS III data and Geographical Information System (GIS) on 1:50,000 scale. The river follows meandering course and exhibits a narrow, highly sinuous and incised channel. Several lines of evidence including satellite and topographic data, geological maps and field investigations and the generated themes on lithology, structure, geomorphology, slope, riparian vegetation and hydrology have analyzed to understand the controls on the channel morphology of the Pannagon river. The average of sinuosity index of the selected reaches in the river on 1967 was 1.6 and of 2004 was 1.8. The sinuous patches are more in the lower reaches of the river and most of the area comes under floodplain with thick column of alluvial deposits. The analysis shown that the style and degree of sinuosity of the Pannagon river depends on a number of geological factors, including tectonics and the riparian vegetation also plays a major role.     

Development of an empirical equation for the transverse dispersion coefficient in natural streams

In this study, a new empirical equation for the transverse dispersion coefficient has been developed based on the hydraulic and geometric parameters in natural streams using a regression technique. First, a total of 32 data sets in 16 streams were collected. Among those sets, 16 sets were used for deriving the new equation, and the other 16 sets were used for verifying the equation. Then, through dimensional analysis, it was found that the normalized transverse dispersion coefficient is associated with several parameters such as sinuosity, aspect ratio, and a friction term. The robust least square method was applied to estimate regression coefficients. The newly proposed equation was proven to be superior in explaining the dispersion characteristics of natural streams more precisely compared to the existing equations.