Assessment of sediment deposition rate in Bargi Reservoir using digital image processing

Goel, Manmohan Kumar; Jain, Sharad K.; Agarwal, Pushpendra K.

doi:10.1080/02626660209493024

Cited by 52 publications

(35 citation statements)

References 2 publications

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“…The Satellite Remote Sensing (SRS) method for assessment of reservoir sedimentation is based on the fact, that, the water spread area of reservoir at various elevations keeps on decreasing due to sedimentation. These techniques have been used in various studies for example, Goel et al (2002) used digital imagery processing to assess sediment deposition rate in the Bargi Reservoir, Narasayya et al (2005) also used this technique to assess sedimentation in the Srisailam Reservoir located in Andhra Pradesh State of India. Light Detection and Ranging (LIDAR) is another technique that provide fairly accurate land surface altitude similar to the way an echo-sounder operates.…”

Section: Remote Sensing Methodsmentioning

confidence: 99%

Understanding Sedimentation Process in the Makoye Reservoir of Southern Zambia

Muchanga¹

2017

JGES

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Reservoir sedimentation is one of the problems facing managers of small reservoirs (with ≤5m height of embankment). The main methods used to understand sedimentation process in the Makoye reservoir included sediment coring, onsite measurements using Sedimeter SM3A, use of Elevation Change Method (EMC), laboratory analysis of sediment core, 3D Spatial Analyst Tools (3DSATs) in ArcGIS 10.3 as well as mathematical models. The reservoir had been silting at a significant rate of 3,112.97 m 3 yr -1 leading to average accumulation of 87,163 m 3 of sediment, which had eventually reduced the reservoir's storage capacity by 53.5%. The EMC methods also revealed that Makoye reservoir tapped 79,749.38 m 3 of sediment giving rise to the between method average sediment volume of 83,456.26 m 3 . Reservoir's useful life was found to be 24 years. Results from Sedimeter SM3A showed that a total depth of 0.688cm of sediment had accumulated during a period of 309 hours in the 2015/2016 rainy season as compared to 1.56 cm in the 2016/2017 rainy season. The long term average depth of sediment was found to be 2.4 cm. It was concluded that sedimentation in the Makoye Reservoir is a serious problem which may lead to complete loss of reservoir storage capacity.Keywords: Sedimentation rate, reservoir capacity, Sediment yield, Useful life, Sedimeter-SM3A BackgroundReservoir sedimentation is one of the problems facing managers of small reservoirs (with ≤5m height of embankment) (Nissen-Petersen, 2006) and, it has persisted in literature (Meade, 1982;Walling, 1988;Sichingabula, 1997;Collins and Walling, 2004;Lu et al., 2013;Sichingabula et al., 2014;Chomba and Sichingabula, 2015) such that it still needs further studies particularly in Zambia where sediment data is quite scanty. Due to very low velocity (<0.035ms -1 ) of water in reservoirs, they tend to be very efficient sediment traps leading to untimely loss of reservoirs' useful life, storage capacity as well as reduced water quantity and quality (Lu et al., 2013). Rainfall, runoff and river channel erosion provide a continuous supply of sediment that is finally deposited into reservoirs, if sediment inflow is large relative to the reservoir storage capacity, then the useful life of the reservoir may be drastically shortened (Randle et al., 2008). Collins and Walling (2004) noted that information on sedimentation is an important data requirement for reconstructing historical catchment erosion patterns and assist in the interpretation of sediment loads in small reservoirs. Moreover, the capacity to manage current and predicted sedimentation problems depends, in part, upon an improved understanding of sediment load (Collins and Walling, 2004). This study aimed at determining quantity of sediment and rate of sedimentation in the Makoye reservoir.

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Section: Remote Sensing Methodsmentioning

confidence: 99%

Understanding Sedimentation Process in the Makoye Reservoir of Southern Zambia

Muchanga¹

2017

JGES

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“…With the advent of remote sensing technology supported by cyclic satellites, monitoring reservoirs by means of satellite images has become very convenient and far less expensive (Wang and Li, 1998; Goel et al , 2002; Marcus and Fonstad, 2008). Meanwhile, real‐time technology allows for large‐scale observation and calculation at different scales, ranging from a single reservoir to global.…”

Section: Introductionmentioning

confidence: 99%

Delineation of reservoirs using remote sensing and their storage estimate: an example of the Yellow River basin, China

Ran

2011

Hydrological Processes

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Abstract:Reservoirs are an integral component of water resources planning and management. Periodic and accurate assessment of the water storage change in reservoirs is an extraordinarily important aspect for better watershed management and water resources development. In view of the shortcomings of conventional approaches in locating reservoirs' spatial location and quantifying their storage, the remote sensing technique has several advantages, either for a single reservoir or for a group of reservoirs. The satellite-based remote sensing data, encompassing spatial, spectral and temporal attributes, can provide high-resolution synoptic and repetitive information with short time intervals on a large scale. Using remote sensing images in conjunction with Google Earth and field check of representative reservoirs, the spatial distribution of constructed reservoirs in the Yellow River basin was delineated, and their storage volume and the residence time of the stored water were estimated. The results showed that 2816 reservoirs were extracted from the images, accounting for 89Ð5% of the registered total. All large-and medium-sized reservoirs were extracted while small reservoirs may not be extracted due to coarse resolution and cloud-cover shadows. An empirical relationship between the extracted water surface area and the compiled storage capacity of representative reservoirs was developed. The water storage capacity was estimated to be 66Ð71 km 3 , about 92Ð7% of the total storage capacity reported by the authority. Furthermore, the basin was divided into 10 sub-basins upon which the water's residence time was analysed. The water discharge in the basin has been greatly regulated. The residence time has surged to 3Ð97 years in recent years, ranking the Yellow River in the top three of the list in terms of residence time and flow regulation among large river systems in the world. It is expected that it will be further extended in future owing to decreasing water discharge and increasing reservoir storage capacity.

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“…There are several methods which have been used in past to determine the amount of sediment in reservoirs, such as hydrography (Furnans and Austin 2008), mathematical and computer models (Jothiprakash and Garg 2009;Mueller et al 2010;Wu et al 2012), hydrometry (Heidarnejad et al 2006), bathymetric survey (Haregeweyn et al 2012) and remote sensing (Goel et al 2002). But due to the differences in technique and environmental conditions; a comprehensive, precise, and economic method cannot be recommended.…”

Section: Introductionmentioning

confidence: 99%

Identification and management of critical erosion watersheds for improving reservoir life using hydrological modeling

Kumar

Raghuwanshi

Mishra

2015

Sustain. Water Resour. Manag.

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Sustainable management of water resources requires identification and management of critical erosion areas for reducing the reservoir sedimentation. A processbased distributed model SWAT (Soil and Water Assessment Tool) was used to identify critical erosion watersheds in Damodar catchment and tested soil and water management strategy to reduce sediment transport to reservoirs for improving their useful life. The model was calibrated and validated using measured runoff and sediment yield from two watersheds and two reservoir inflows. The validated model was also tested for its appropriateness by comparing the identified critical erosion area of the catchment with the erosion map prepared by Soil Conservation Department (SCD), Damodar Valley Corporation (DVC). The results show that the critical erosion area identified using modeling results matched spatially well with the DVC manually prepared area. Further, the validated model has been used to simulate the sedimentation in the reservoirs. The simulated sedimentation rate is 1.12 and 3.65 Mm 3 /year, respectively, for Konar and Panchet reservoirs for the studied period (1997)(1998)(1999)(2000)(2001), which is reduced to 0.98 and 1.80 Mm 3 /year, respectively, when the critical watersheds are treated with conservation measures. As a result of model identified and implemented management strategy, Konar and Panchet reservoirs will have an additional useful life of 8 and 85 years, respectively. Results show a successful incorporation of distributed hydrological modeling for identifying critical watersheds, developing effective management strategy for controlling soil erosion, reducing reservoir sedimentation and improving their useful life.

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Assessment of sediment deposition rate in Bargi Reservoir using digital image processing

Cited by 52 publications

References 2 publications

Understanding Sedimentation Process in the Makoye Reservoir of Southern Zambia

Understanding Sedimentation Process in the Makoye Reservoir of Southern Zambia

Delineation of reservoirs using remote sensing and their storage estimate: an example of the Yellow River basin, China

Identification and management of critical erosion watersheds for improving reservoir life using hydrological modeling

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