Reservoir Sedimentation in India—Its Causes, Control, and Future Course of Action

Tejwani, K. G.

doi:10.1080/02508068408686525

Cited by 19 publications

(3 citation statements)

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“…Surveys on Indian reservoirs were reported that they receive on an average of about 200% more sediment than the design inflow. According to Tejwani (1984), "misuse and mismanagement" of the catchment area are the causes for higher rates of sedimentation. Reservoirs are effective traps for the incoming sediment loads.…”

Section: Introductionmentioning

confidence: 99%

Longitudinal heterogeneity of sediment characteristics during southwest monsoon season in hyper-eutrophic Krishnagiri reservoir, India

Sudha

Ambujam

2011

Environ Monit Assess

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Krishnagiri reservoir is a hyper-eutrophicated reservoir located in Krishnagiri district which is one of the drought-prone districts in Tamil Nadu, India. The reservoir water is being used for various purposes such as irrigation, drinking, fish rearing, livestock rearing, and recreation. Since there is no an evidence of investigation on bottom sediments in Krishnagiri reservoir, the present study was carried out during southwest monsoon season in 2008. This study examined the physical and chemical characteristics of the bottom sediments such as composition, redox potential, moisture content, organic carbon, organic matter, total phosphorus, and total iron at 15 locations in the reservoir. Phosphorus fractionation study was carried out to find out different fractions such as loosely adsorbed phosphorous, iron and aluminium-bound phosphorus, calcium-bound phosphorous, and organic phosphorous. Results indicated that there was spatial variation in the composition of sediments and low values of redox potential. The significant positive correlation exists between the organic carbon and organic phosphorus concentration. The lacustrine zone of the reservoir showed high accumulation of total phosphorus and total iron when compared to riverine and transition zones. This study concludes an allogenic origin of majority of inorganic phosphorus in the reservoir during the study period and this might have been derived from the catchment during the erosion process. The high concentration of surface sediment phosphorus clearly indicates a greater threat of eutrophication in Krishnagiri reservoir.

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Section: Introductionmentioning

confidence: 99%

Longitudinal heterogeneity of sediment characteristics during southwest monsoon season in hyper-eutrophic Krishnagiri reservoir, India

Sudha

Ambujam

2011

Environ Monit Assess

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“…The sedimentation has become a major problem in Indian Reservoirs due to various problem like population growth, agricultural activities, deforestation and poor soil conservation practices. A survey has revealed that an average of about 200 percent more sediment is received by Indian reservoirs than they are designed for inflow (Tejwani, 1984). Reduction in the reservoir capacity decreases reliability and flexibility of water supply.…”

Section: Introductionmentioning

confidence: 99%

Role of Sar Data in Water Body Mapping and Reservoir Sedimentation Assessment

Prasad

Garg

Thakur

2018

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Reservoir sedimentation is the major problem, due to it every year the reservoir capacity is lost to considerable amount. Surveying for assessment of the reservoir by conventional approach is time and money consuming. Geospatial technology provides ample opportunity in this field through the availability of high resolution satellite data from sensors such as Sentinel, Indian Remote Sensing Satellite, Landsat, and SPOT have been used to calculate the water spread area of the reservoir. However, due to presence of cloud in most of the optical data during onset of monsoon, the water spread at the lowest reservoir level could not be mapped. In turn the revised capacity or sedimentation is generally assessed between either below full reservoir level (FRL) or above maximum draw down level (MDDL). Nowadays, the microwave synthetic aperture radar (SAR) data at reasonable spatial resolution is available freely in public domain. Moreover, microwave data has capability to penetrate cloud and the information below cloud can easily be retrieved. To overcome the issues related to optical data, in the present study, the reservoir sedimentation for Ghataprabha reservoir was estimated using SAR data. Sentinel-1A data was used to delineate the water spread area for the water year of 2016–17. The original live storage capacity (1974) was estimated to be 1434.14Mm3 at FRL 662.940m by the authorities using the hydrographic survey during the commissioning of the reservoir in the year 1974. The live storage capacity was found out to be 1366.14Mm3 at FRL, however, as per original elevation-area-capacity curve the live capacity is around 1262.404Mm3 at 660.50m. Estimated live storage capacity from Remote sensing approach (2016–17) was assesses as 1182.5Mm3 at 660.51m. The storage capacity has reduced from 1262.40Mm3 (1974) to 1182.51Mm3 i.e. around 171.732Mm3. As per present analysis the rate of sedimentation is around 4Mm3/yr. It was realized that using the SAR microwave data, the revised capacity of the reservoir from its near MDDL to FRL could be assessed through remote sensing approach.

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“…The subsequent impacts, including loss of soil fertility, blocked transport corridors, river and reservoir sedimentation, deterioration of aquatic habitat and threat to human life, can have major social, economic and environmental repercussions (e.g. Larson and Albertin, 1984;Tejwani, 1984;Kessel, 1985;Dhital, 2003;López et al, 2003;Sidle and Ochiai, 2006). There is a strong interest, therefore, in ways of minimizing the increased landslide occurrence.…”

Section: Introductionmentioning

confidence: 99%

Modelling the effect of forest cover on shallow landslides at the river basin scale

Bathurst

Bovolo

Cisneros

2010

Ecological Engineering

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The potential for reducing the occurrence of shallow landslides through targeted reforestation of critical parts of a river basin is explored through mathematical modelling. Through the systematic investigation of land management options, modelling allows the optimum strategies to be selected ahead of any real intervention in the basin. Physically based models, for which the parameters can be evaluated using physical reasoning, offer particular advantages for predicting the effects of possible future changes in land use and climate. Typically a physically based landslide model consists of a coupled hydrological model (for soil moisture) and a geotechnical slope stability model, along with an impact model, such as basin sediment yield. An application of the SHETRAN model to the 65.8-km 2 Guabalcón basin in central Ecuador demonstrates a technique for identifying the areas of a basin most susceptible to shallow landsliding and for quantifying the effects of different vegetation covers on landslide incidence. Thus, for the modelled scenario, increasing root cohesion from 300 to 1500 Pa causes a two-thirds reduction in the number of landslides. Useful information can be obtained even on the basis of imperfect data availability but model output should be interpreted carefully in the light of parameter uncertainty.

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Reservoir Sedimentation in India—Its Causes, Control, and Future Course of Action

Cited by 19 publications

References 0 publications

Longitudinal heterogeneity of sediment characteristics during southwest monsoon season in hyper-eutrophic Krishnagiri reservoir, India

Longitudinal heterogeneity of sediment characteristics during southwest monsoon season in hyper-eutrophic Krishnagiri reservoir, India

Role of Sar Data in Water Body Mapping and Reservoir Sedimentation Assessment

Modelling the effect of forest cover on shallow landslides at the river basin scale

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