Determination of error in individual discharge measurements

Sauer, Vernon B.; Meyer, R.W.

doi:10.3133/ofr92144

Cited by 216 publications

(199 citation statements)

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“…We believe this to be a conservative estimate of relative errors because both parameters were calculated using measured streamflow data. Errors in Q Stream measurements were assumed to be 5%, which is also a conservative estimate [Sauer and Meyer, 1992]. Table 1).…”

Section: Methodsmentioning

confidence: 99%

Quantifying watershed‐scale groundwater loading and in‐stream fate of nitrate using high‐frequency water quality data

Miller

Tesoriero

Capel

et al. 2016

Water Resources Research

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We describe a new approach that couples hydrograph separation with high-frequency nitrate data to quantify time-variable groundwater and runoff loading of nitrate to streams, and the net in-stream fate of nitrate at the watershed scale. The approach was applied at three sites spanning gradients in watershed size and land use in the Chesapeake Bay watershed. Results indicate that 58-73% of the annual nitrate load to the streams was groundwater-discharged nitrate. Average annual first-order nitrate loss rate constants (k) were similar to those reported in both modeling and in-stream process-based studies, and were greater at the small streams (0.06 and 0.22 day 21 ) than at the large river (0.05 day 21 ), but 11% of the annual loads were retained/lost in the small streams, compared with 23% in the large river. Larger streambed area to water volume ratios in small streams results in greater loss rates, but shorter residence times in small streams result in a smaller fraction of nitrate loads being removed than in larger streams. A seasonal evaluation of k values suggests that nitrate was retained/lost at varying rates during the growing season. Consistent with previous studies, streamflow and nitrate concentrations were inversely related to k. This new approach for interpreting high-frequency nitrate data and the associated findings furthers our ability to understand, predict, and mitigate nitrate impacts on streams and receiving waters by providing insights into temporal nitrate dynamics that would be difficult to obtain using traditional field-based studies.

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Section: Methodsmentioning

confidence: 99%

Quantifying watershed‐scale groundwater loading and in‐stream fate of nitrate using high‐frequency water quality data

Miller

Tesoriero

Capel

et al. 2016

Water Resources Research

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“…1c, d). The accuracy of this gauge was not specifically assessed, but is estimated to have a maximum error of ± 8% (Sauer and Meyer 1992). The current study covers a period of just over 2 years, from July 2014 (3 months before the reconnection of Ben Gill) until August 2016.…”

Section: Discharge and Flow Conditionsmentioning

confidence: 99%

“…The first source of error is the one associated with the turbidity sensors (E S ), for which the accuracy provided by the manufacturer was used (± 2%). Second, errors associated with the measurement of discharge (E Q ) were considered, following Sauer and Meyer (1992), as being of ± 8%. Finally, the last source of error identified stemmed from the empirical NTU-SSC relationship (i.e.…”

Section: Suspended Sedimentmentioning

confidence: 99%

Asynchronicity of fine sediment supply and its effects on transport and storage in a regulated river

et al. 2018

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Purpose A disconnected ephemeral tributary was reconnected to the regulated River Ehen (NW England) as part of a river restoration initiative, providing a renewed delivery of sediment to a highly stable and armoured channel. This paper (1) assesses spatial and temporal dynamics of suspended and stored sediments in the Ehen, (2) characterises the composition of stored sediment, (3) develops fine sediment budgets for downstream river reaches, and (4) assesses the controls on the storage of fine sediment in the riverbed. Materials and methods A 3-km study section in the upper part of the River Ehen was divided into two reaches. Suspended sediments were monitored at the downstream limits of each reach over a 2-year period. In-channel storage was measured in three morphological units within the upper reach, on 13 occasions over the same period. Samples were used to assess changes in volumes of stored fine sediment, as well as the grain sizes and organic content of the material. A time-lapse camera facing the confluence of the tributary was used to conceptualise different flow scenarios. These scenarios reflect the degree of synchronicity between flows in the main-stem and those in the tributary. Fine sediment budgets were developed for each reach to assess the relative contribution of different sources of sediment. Results and discussion The reconnection significantly affected suspended sediment loads in the Ehen. Bed storage increased twofold, with changes most evident in the slow-flowing morphological unit. Changes in the composition of stored sediment were less marked than changes in the quantity of material. Changes in bed storage were controlled by the degree of synchronicity between flows in the Ehen and those in the newly reconnected tributary. Results show that three generalised flow scenarios occur, with total asynchronicity between flows in the tributary and the Ehen being responsible for the main episodes of fine sediment deposition. Overall, the estimated sediment budgets provide insights into the importance of non-perennial sources of sediment in supply-limited systems such as the Ehen. Although bed storage values are within the range of those published for UK rivers, the increase observed since the reconnection, together with the persistence of a static pavement, highlights the ecologically critical conditions of the regulated main-stem River Ehen. Conclusions Intermittent sources control fine sediment transport dynamics in the upper River Ehen. In this regulated river, ongoing deposition associated with increased low-and medium-sized flow events exerts more of a control on bed storage than large but rare floods. Management actions to limit delivery of material from lateral sources could help prevent further deterioration of habitat conditions for biota sensitive to fine sediment. Given the ongoing adjustment in the newly reconnected tributary, continued monitoring is needed to capture further morphosedimentary response in the main-stem.

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“…1). The error in the Puerto Rico Q data is estimated to be 3-6 % (Sauer and Meyer, 1992). The cumulative error in annual P , PET, and Q was quantified bŷ σÂ (Eq.…”

Section: Potential Explanations For the Lack Of Relationshipsmentioning

confidence: 99%

The impact of forest regeneration on streamflow in 12 mesoscale humid tropical catchments

Beck

Bruijnzeel

Dijk

et al. 2013

Hydrol. Earth Syst. Sci.

106

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Abstract. Although regenerating forests make up an increasingly large portion of humid tropical landscapes, little is known of their water use and effects on streamflow (Q). Since the 1950s the island of Puerto Rico has experienced widespread abandonment of pastures and agricultural lands, followed by forest regeneration. This paper examines the possible impacts of these secondary forests on several Q characteristics for 12 mesoscale catchments (23-346 km 2 ; mean precipitation 1720-3422 mm yr −1 ) with long (33-51 yr) and simultaneous records for Q, precipitation (P ), potential evaporation (PET), and land cover. A simple spatially-lumped, conceptual rainfall-runoff model that uses daily P and PET time series as inputs (HBV-light) was used to simulate Q for each catchment. Annual time series of observed and simulated values of four Q characteristics were calculated. A least-squares trend was fitted through annual time series of the residual difference between observed and simulated time series of each Q characteristic. From this the total cumulative change (Â) was calculated, representing the change in each Q characteristic after controlling for climate variability and water storage carry-over effects between years. Negative values ofÂ were found for most catchments and Q characteristics, suggesting enhanced actual evaporation overall following forest regeneration. However, correlations between changes in urban or forest area and values ofÂ were insignificant (p ≥ 0.389) for all Q characteristics. This suggests there is no convincing evidence that changes in the chosen Q characteristics in these Puerto Rican catchments can be ascribed to changes in urban or forest area. The present results are in line with previous studies of mesoand macro-scale (sub-)tropical catchments, which generally found no significant change in Q that can be attributed to changes in forest cover. Possible explanations for the lack of a clear signal may include errors in the land cover, climate, Q, and/or catchment boundary data; changes in forest area occurring mainly in the less rainy lowlands; and heterogeneity in catchment response. Different results were obtained for different catchments, and using a smaller subset of catchments could have led to very different conclusions. This highlights the importance of including multiple catchments in land-cover impact analysis at the mesoscale.

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Determination of error in individual discharge measurements

Cited by 216 publications

References 0 publications

Quantifying watershed‐scale groundwater loading and in‐stream fate of nitrate using high‐frequency water quality data

Quantifying watershed‐scale groundwater loading and in‐stream fate of nitrate using high‐frequency water quality data

Asynchronicity of fine sediment supply and its effects on transport and storage in a regulated river

The impact of forest regeneration on streamflow in 12 mesoscale humid tropical catchments

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