Integrated Evaluation of Uncertainty in Hydrological Data and Application in Flood Control Plan

Sago, Junzo

doi:10.3178/jjshwr.21.353

Cited by 5 publications

(3 citation statements)

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“…We estimated the uncertainty associated with IGF and ECI using standard techniques to calculate the propagation of uncertainty, that is, the square root of the sum of the squared uncertainties (Genereux et al., 2005):

{{\upvarepsilon }}_{\text{IGF}}=\sqrt{{{{\upvarepsilon }}_{\mathrm{P}}}^{2}+{{{\upvarepsilon }}_{\mathrm{Q}}}^{2}+{{{\upvarepsilon }}_{\text{ET}}}^{2}}

where ε IGF (mm) is the uncertainty of the IGF and ε P , ε Q , and ε ET are the ratios of the uncertainties of the observed values of P, Q, and ET, respectively; ε P was estimated from observational errors and spatial variation as 14%. The observational error of P was assumed to be approximately 10% for tipping masses (McMillan et al., 2012; Sago, 2008), and the spatial error was assumed to be approximately 10%. The source of ε Q was considered to be the errors in water level measurement and the water level‐discharge relationship equation.…”

Section: Methodsmentioning

confidence: 99%

“…where ε IGF (mm) is the uncertainty of the IGF and ε P , ε Q , and ε ET are the ratios of the uncertainties of the observed values of P, Q, and ET, respectively; ε P was estimated from observational errors and spatial variation as 14%. The observational error of P was assumed to be approximately 10% for tipping masses (McMillan et al, 2012;Sago, 2008), and the spatial error was assumed to be approximately 10%. The source of ε Q was considered to be the errors in water level measurement and the water level-discharge relationship equation.…”

Section: Uncertainty Of Igfmentioning

confidence: 99%

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Scale‐Dependent Inter‐Catchment Groundwater Flow in Forested Catchments: Analysis of Multi‐Catchment Water Balance Observations in Japan

Oda,

Iwasaki,

Egusa

et al. 2024

Water Resources Research

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Inter‐catchment groundwater flow (IGF) plays an essential role in streamflow generation and water quality in forested headwaters. Multiple factors are thought to contribute to IGF, including climate, topographical, and geological factors. However, studies have not clarified the relationships between IGF and catchment properties in the headwater catchments due to the lack of observational data at scales smaller than 100 ha. This study examined possible factors influencing IGF using random forest analysis based on annual water balance data from 152 forested catchments ranging from 0.09 to 9400 ha in Japan. The results showed that catchment scale had the greatest influence on IGF, and IGF tended to decrease with increasing catchment area at scales of less than 10 ha. The average IGF stabilized around zero in catchments greater than 10 ha. The averaged IGF trend with catchment scale indicated more outward groundwater flow in catchments smaller than 10 ha, but no relationship between IGF and catchment size in catchments larger than 10 ha. The variability in IGF decreased with catchment size and was lowest at 10–100 ha. The decrease in variability in catchments less than 100 ha was mainly due to river confluence and the increased variability in catchments larger than 100 ha indicated potential observation errors increase in catchments of this size.

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{{\upvarepsilon }}_{\text{IGF}}=\sqrt{{{{\upvarepsilon }}_{\mathrm{P}}}^{2}+{{{\upvarepsilon }}_{\mathrm{Q}}}^{2}+{{{\upvarepsilon }}_{\text{ET}}}^{2}}

Section: Methodsmentioning

confidence: 99%

Section: Uncertainty Of Igfmentioning

confidence: 99%

Scale‐Dependent Inter‐Catchment Groundwater Flow in Forested Catchments: Analysis of Multi‐Catchment Water Balance Observations in Japan

Oda,

Iwasaki,

Egusa

et al. 2024

Water Resources Research

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show abstract

“…If measurement uncertainty is evaluated in terms of relative error, the error of rainfall observations collected with a tipping bucket is about 10% and the error in discharge measurement is 13% (Sago, 2008); therefore, the error in discharge from Kawamata, which was the sum the reported discharge and water intake is estimated to be 16%. Meanwhile, the measurement error for annual loss, which was annual precipitation minus annual discharge ( P – Q ) was estimated to be 21% (Asano & Suzuki, 2021).…”

Section: Methodsmentioning

confidence: 99%

Lateral flow in bedrock dominates baseflow and flood flow in a catchment underlain with permeable sedimentary rock in the high‐relief Chichibu Mountains

Asano,

Kawasaki,

Takatoku

et al. 2023

Hydrological Processes

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Determining the mechanisms of runoff generation is essential to land and water resource conservation, but lateral flow processes in high‐relief mountain areas remain unclear due to the difficulty to observe and measure these processes. This study demonstrates that lateral flow in bedrock dominates both high and low flows in a catchment underlain with permeable sedimentary bedrock in the high‐relief Chichibu Mountains. Through measurement of precipitation, discharge, soil, and stream temperatures and tracers (SiO2 and δ18O) in the first‐order stream Bakemonozawa (0.51 km2) and comparison of its water balance with the nested Kawamata catchment (93.58 km2) i, we showed that 831–1012 mm/year or 47%–53% of annual precipitation leaked from Bakemonozawa. The streamflow was discharged from an average depth of 2.3 m or deeper, which were deeper than the measured deepest soil near the gauge. Furthermore, stream temperature decreased significantly during a large summer storm, demonstrating that the relative contribution of the deep bedrock flowpath increased. Large isotopic variation in precipitation was dampened in the stream, suggesting that most baseflow and some higher flows arose from groundwater storage with a constant isotopic ratio due to dispersion and mixing. The discharge–SiO2 relationship suggested at least two groundwater sources, namely, shallow and deep bedrock groundwater, with different runoff responses. Discharge increased dramatically when the catchment became wet, coinciding with the deep bedrock groundwater contribution. Further research is needed to clarify the hydrological characteristics of bedrock.

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Peak discharges per unit area increase with catchment area in a high-relief mountains with permeable sedimentary bedrock

Asano

Suzuki

Kawasaki

2022

Journal of Hydrology

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Integrated Evaluation of Uncertainty in Hydrological Data and Application in Flood Control Plan

Cited by 5 publications

References 0 publications

Scale‐Dependent Inter‐Catchment Groundwater Flow in Forested Catchments: Analysis of Multi‐Catchment Water Balance Observations in Japan

Scale‐Dependent Inter‐Catchment Groundwater Flow in Forested Catchments: Analysis of Multi‐Catchment Water Balance Observations in Japan

Lateral flow in bedrock dominates baseflow and flood flow in a catchment underlain with permeable sedimentary rock in the high‐relief Chichibu Mountains

Peak discharges per unit area increase with catchment area in a high-relief mountains with permeable sedimentary bedrock

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