Reservoir Sedimentation Rates in the Little Washita River Experimental Watershed, Oklahoma: Measurement and Controlling Factors

Moriasi, Daniel N.; Steiner, Jean L.; Duke, Sara E.; Starks, Patrick J.; Verser, Alan J.

doi:10.1111/1752-1688.12658

Cited by 14 publications

(20 citation statements)

References 26 publications

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“…Cross and Moore () and Furnans and Austin () reported closer transect spacing during a bathymetric survey of waterbodies improved the confidence and accuracy of the estimated water volume. According to Moriasi, Steiner, Duke, Starks, and Verser (), the volume estimated from the 2016 study could have higher accuracy since bathymetric water volume measurements using APS usually have an error value of ± 4.2%.…”

Section: Resultsmentioning

confidence: 99%

“…Cross and Moore (2014) and Furnans and Austin (2008) reported closer transect spacing during a bathymetric survey of waterbodies improved the confidence and accuracy of the estimated water volume. According to Moriasi, Steiner, Duke, Starks, and Verser (2018), the volume estimated from the 2016 study could have higher accuracy since bathymetric water volume measurements using APS usually have an error value of ± 4.2%. Thompson and Dodson (1963) and Ase et al (1986) did not specify whether the volumes observed in their studies represented only Lake Naivasha or the combined volume of Lake Naivasha and Lake Oloiden, thereby limiting the comparison of their findings with those of the 2016 survey.…”

Section: Lake Naivasha Volumementioning

confidence: 99%

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Bathymetric survey of Lake Naivasha and its satellite Lake Oloiden in Kenya; using acoustic profiling system

et al. 2018

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Lakes and reservoirs play important roles as freshwater sources for domestic, industrial, agricultural, fisheries and recreational purposes. However, for the lakes to be sustainably exploited, there is need to understand their bathymetric characteristics by conducting bathymetric surveys. This aids in generating information that can guide lakes stakeholders and managers in establishing the volume of available water. It is recommended, therefore, that bathymetric surveys be conducted at ten‐year intervals. Such continuous bathymetric information is lacking in many lakes, especially in developing countries. One example is Lake Naivasha in Kenya, which is largely exploited for various socio‐economic purposes. Despite its importance, its most recent published bathymetric data were collected in 1991. The goal of the present study, therefore, was to conduct a bathymetric survey of Lake Naivasha and its satellite Lake Oloiden, using an Acoustic Profiling System (APS) to generate Depth–Area–Volume relationships for the lakes. The survey results indicate the in the year 2016 mean depth, volume and surface area of the lake were 4.68 m, 722 × 106 m3 and 154.17 × 106 m2, respectively. Because of limited information from the 1991 survey, the 2016 survey results were comparable with those of 1983. The difference in the lakes mean, and maximum depth for the 1983 and 2016 survey was less by 0.23 and 2 m, respectively. This could be an indicator the lake is being affected by anthropogenic activities or environmental changes. The established Depth–Area–Volume relationships are crucial since they provide invaluable information to lake and water resources managers for making informed decisions regarding management of the lake's water resources.

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Section: Resultsmentioning

confidence: 99%

Section: Lake Naivasha Volumementioning

confidence: 99%

Bathymetric survey of Lake Naivasha and its satellite Lake Oloiden in Kenya; using acoustic profiling system

et al. 2018

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“…The volumetric lake sedimentation rate (LaSR) was determined from the sediment volume calculated for the 0–20, 20–50 and 0–50 periods. The LaSR was calculated using Equation , which was adopted from Moriasi, Steiner, Duke, Starks, and Verser (),

LaSR = \frac{SV}{Yrs}

where LaSR = volumetric lake sedimentation rate (m 3 /year); SV = sediment volume (m 3 ); and Yrs = number of years under consideration (20, 30, 50 years). Because Lake Naivasha is a natural waterbody, the original volume was not known.…”

Section: Methodsmentioning

confidence: 99%

Sediment distribution and accumulation in Lake Naivasha, Kenya over the past 50 years

et al. 2019

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Although surface waterbodies are water sources for socio‐economic activities and ecosystems, their functions are threatened by sedimentation. Sedimentation of lakes and reservoirs can result in a loss of storage capacity and altered water quality. The present study assessed the sedimentation status of Lake Naivasha, Kenya, based on sediment distribution and accumulation over the past 50 years, using a Bathymetric Survey System (BSS). The BSS uses multi‐frequency Acoustic Profiling System (APS) to map recently deposited sediments. Sediment core samples were collected with a vibe‐ coring device and dated. Sediment layers corresponding to a period of the past 20 and 50 years were identified. Sediment cores and acoustic images were subsequently used to determine sediment thickness within the lake. The collected depth data from multi‐frequency APS, and dated cores were processed in DepthPic and Surfer software. The sediment depth was extracted in DepthPic, while the sediment volume and distribution were generated from Surfer software. The results from present study indicated that sediment distribution varied from one part of the lake to another for the past 20 and 50 years. High sediment thickness observed in the south‐west and eastern parts of the lake. Between 1996–2016 and 1966–2016 periods, the maximum accumulated sediment thickness was found to be about 0.55 and 1.9 m, with an average sediment thickness of 0.25 and 0.56 m, respectively. The mean sediment load corresponding to the 1966–1996 and 1996–2016 periods was 2.78 × 105 and 4.61 × 105 t/year, respectively. It was found that sediment load into Lake Naivasha has been increasing in the recent past. Based on the present the study, it was found that combined use of BSS, sediment cores and dating can be adopted in many lakes and reservoirs to determine sediment thicknesses even where no prior bathymetric surveys exist for comparison.

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“…Research Center Walnut Gulch Moran, Emmerich, et al (2009), Moran, Hutchinson, et al (2009) www.tucson.ars. ag.gov/dap/ -Semiarid and monsoon influenced precipitation, runoff, and erosion -Influent hydrologic processes and instrumentation (Goodrich et al, 1997;Osborn et al, 1980;Paige et al, 2003;Polyakov et al, 2010;Renard et al, 2008;Smith et al, 1982 (Bosch et al, 2007(Bosch et al, , 2017Hubbard et al, 2004;Lowrance et al, 1984 (Garbrecht & Starks, 2009;Moriasi et al, 2018;Schoof et al, 1987;Van Liew et al, 2003)…”

Section: Southwest Watershedmentioning

confidence: 99%

The USDA‐ARS Experimental Watershed Network: Evolution, Lessons Learned, Societal Benefits, and Moving Forward

Goodrich

Heilman

Anderson³

et al. 2021

Water Resources Research

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The U.S. Department of Agriculture‐Agricultural Research Service's (ARS) Experimental Watershed Network grew from Dust Bowl era efforts of the Soil Conservation Service in the mid‐1930s with the establishment of small experimental watersheds. In the 1950s, five watershed research centers with intensively instrumented watersheds at the scale of 100 to 700 km2 were established. Primary network research objectives were to quantify on‐site and downstream effects of conservation practices and develop rainfall‐runoff relationships for design of water conservation structures. With passage of the Clean Water Act in 1972, research objectives have evolved to add a variety of observations relevant to the water quality issues. Many of the watersheds within the network have served, and continue to serve, as core validation sites for satellite sensors. As a result of the network's long history and intensive monitoring, coupled with mission‐driven research, a deep knowledge base of watershed processes has been developed. This has led to the extensive development and validation of numerous watershed models that are in widespread use today. The visionary investments in building and maintaining this network and associated scientific investigations for more than half a century have not only resulted in numerous high‐impact research accomplishments but also a wide array of accomplishments that directly benefit society. The ARS Experimental Watersheds formed the core of the Conservation Effects Assessment Project (CEAP) as well as the recently established Long‐Term Agroecosystem Research (LTAR) network. LTAR will expand the mission of the ARS Watersheds Network to include agricultural intensification, maintaining or improving ecosystem services while enhancing rural prosperity.

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Reservoir Sedimentation Rates in the Little Washita River Experimental Watershed, Oklahoma: Measurement and Controlling Factors

Cited by 14 publications

References 26 publications

Bathymetric survey of Lake Naivasha and its satellite Lake Oloiden in Kenya; using acoustic profiling system

Bathymetric survey of Lake Naivasha and its satellite Lake Oloiden in Kenya; using acoustic profiling system

Sediment distribution and accumulation in Lake Naivasha, Kenya over the past 50 years

The USDA‐ARS Experimental Watershed Network: Evolution, Lessons Learned, Societal Benefits, and Moving Forward

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