The Brahmaputra River in Assam, India, characterized by high seasonal variability in flow, sediment transport, and channel configuration, experienced a secular period of aggradation from 1971 to 1979. The suspended load budget indicates an overall aggradation of the 607‐km Assam reach of the Brahmaputra by about 16 cm during that period, with about 70% of the suspended sediment inflow into the reach being retained in the channel. Expressed as a percentage of the change in storage for the different reaches, computed errors due to sampling variability in sediment discharge generally lie within about 5–15% and do not appear to be large enough to affect the conclusions drawn from the suspended load budget. For a 145‐km reach of the Brahmaputra, an alternative method based on measurement of channel cross sections suggests 21 cm of aggradation, somewhat more than estimated by the suspended load budget. Based on the suspended load carried by trans‐Himalayan rivers, the present rate of denudation of the eastern Himalayas is estimated to be 73–157 cm/103 years. The average rate for the last 2–3 million years, estimated from the volume of alluvial fill in the Brahmaputra valley in Assam, the sediment yield of the Himalayan rivers, and assuming a total yield to deposition ratio of 1.4 (present study), is 3 cm/103 years. The current high rate of denudation of the Himalayas may be attributed mainly to the rapid uplift of the mountain system, recent earthquake activity, and high susceptibility of geologic formations to erosion by running water coupled with the effectiveness of the monsoon rainfall regime.

The Kolong River of Nagaon district, Assam has been facing serious degradation leading to its current moribund condition due to a drastic human intervention in the form of an embankment put across it near its takeoff point from the Brahmaputra River in the year 1964. The blockage of the river flow was adopted as a flood control measure to protect its riparian areas, especially the Nagaon town, from flood hazard. The river, once a blooming distributary of the mighty Brahmaputra, had high navigability and rich riparian biodiversity with a well established agriculturally productive watershed. However, the present status of Kolong River is highly wretched as a consequence of the post-dam effects thus leaving it as stagnant pools of polluted water with negligible socioeconomic and ecological value. The Central Pollution Control Board, in one of its report has placed the Kolong River among 275 most polluted rivers of India. Thus, this study is conducted to analyze the seasonal water quality status of the Kolong River in terms of water quality index (WQI). The WQI scores shows very poor to unsuitable quality of water samples in almost all the seven sampling sites along the Kolong River. The water quality is found to be most deteriorated during monsoon season with an average WQI value of 122.47 as compared to pre-monsoon and postmonsoon season having average WQI value of 85.73 and 80.75, respectively. Out of the seven sampling sites, Hatimura site (S1) and Nagaon Town site (S4) are observed to be the most polluted sites.

The results presented in this study indicate the possibility of seasonal runoff prediction when satellite-derived basin snow-cover data are related to point source river discharge data for a number of years. NOAA-VHRR satellite images have been used to delineate the areal extent of snow cover for early April over the Indus and Kabul River basins in Pakistan. Simple photo-interpretation techniques, using a zoom transfer scope, were employed in transferring satellite snow-cover boundaries onto base map overlays. A linear regression model with April 1 through July 31 seasonal runoff (1974-1979) as a function of early April snow cover explains 73% and 82% of the variance, respectively, of the measured flow in the Indus and Kabul Rivers. The correlation between seasonal runoff and snow cover is significant at the 97% level for the Indus River and at the 99% level for the Kabul River. Combining Rango et al.'s (1977) data for 1969-73 with the above period, the April snow cover explains 60% and 90% of the variance, respectively, of the measured flow in the Indus and Kabul Rivers. In an attempt to improve the Indus relationship, a multiple regression model, with April 1 through July 31, 1969-79, seasonal runoff in the Indus River as a function of early April snow-covered area of the basin and concurrent runoff in the adjoining Kabul River, explains 79% of the variability in flow. Moreover, a significant reduction (27%) in the standard error of estimate results from using the multi-variate model. For each year of the study period, 1969-79, a separate multiple regression equation is developed dropping the data for the year in question from the data-base and using those for the rest of the years. The snow cover area and concurrent runoff data are then used to estimate the snowmelt runoff for that particular year.The difference between the estimated and observed dircharge values averaged over the 11 year study period is 10%. Satellite derived snow-covered area is the best available input for snowmelt-runoff estimation in remote, data sparse basins like the Indus and Kabul Rivers. The study has operational relevance to water resource planning and management in the Himalayan region.

Abstract:The Dhansiri River is a highly meandering river. Its Sinuosity Index has been evaluated using satellite imageries of 1999 and 2008 which varies from 1.22 to 4.91. The river acquires a meandering course as it flows through the alluvial plains of Assam and is responsible for frequent course change and shifting of banklines due to consistent bank erosion. The progressive gradual change of the meander bends has been observed by superimposing the river layers of 1999 and 2008 in GIS platform. The length of the river course in 2008 (307.74km) became shorter by 6.20 km than that in 1999(313.94km). In the present study it has been found that the total area lost as a result of erosion is 13.13834 sq km and the total area gained as a result of sediment deposition along its bank is 15.15894 sq km.

This study evaluates the estimates of seasonal snowmelt runoff in the Sutlej, Indus, Kabul and Chenab rivers derived from the model of snow cover area vs. runoff against those obtained from cross correlation of concurrent flows in the rivers. The concurrent flow correlation model explains more than 90 percent of the variability in flow of these rivers. Compared to this model, the model of snow-cover area vs. runoff explains less of the variability in flow. However, unlike the snow-cover model, the concurrent flow correlation model cannot be used for operational forecasting procedures. Where the strength of correlation is high, the concurrent flow correlation model has potential for use in retrospective analysis of flow for estimating missing data, extending time series and for evaluating estimates derived from other models. In the Himalayan basins under study and at least for the period under observation, the concurrent flow correlation model provides a set of results with which to compare the estimates from the snow cover model.