Hydrological data monitoring for urban stormwater drainage systems

Maheepala, U.K; Takyi, Andrews K.; Perera, B. J. C

doi:10.1016/s0022-1694(01)00342-0

Cited by 35 publications

(23 citation statements)

References 1 publication

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“…In addition, although there is spatial variability in many factors that influence the production of runoff (e.g. infiltration of rainfall into soil layers) the variability is often difficult to quantify spatially (Maheepala et al, 2001) and as a result many factors are estimated for land use types rather than spatially. Therefore in urban areas a distributed model may often incorporate some data which are lumped or aggregated rather than distributed.…”

Section: The Roles and Design Of Hydrological Modelsmentioning

confidence: 99%

Identification and quantification of the hydrological impacts of imperviousness in urban catchments: A review

Jacobson

2011

Journal of Environmental Management

470

233

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Section: The Roles and Design Of Hydrological Modelsmentioning

confidence: 99%

Identification and quantification of the hydrological impacts of imperviousness in urban catchments: A review

Jacobson

2011

Journal of Environmental Management

470

233

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“…On the other hand, if there are no rainy areas smaller than a radar pixel, it is possible that a rain gauge included in that pixel does not detect rainfall, even though the relative radar rainfall value is greater than zero (Villarini et al, 2008a). Moreover, during the warm season, when convective events occur, rain gauges could not detect rainfall, depending on the non-uniform density of the rain gauge network and on the small extension of precipitation areas (Maheepala et al, 2001). Therefore, homologues pairs with at least an intensity value different from zero, in corresponding radar and rain gauge time series, are useful for highlighting the differences between radar estimates and rain gauge measurements.…”

Section: Radar Datamentioning

confidence: 99%

On precipitation measurements collected by a weather radar and a rain gauge network

Sebastianelli

Russo

Napolitano

et al. 2013

Nat. Hazards Earth Syst. Sci.

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Abstract. Many phenomena (such as attenuation and range degradation) can influence the accuracy of rainfall radar estimates. They introduce errors that increase as the distance from radar increases, thereby decreasing the reliability of radar estimates for applications that require quantitative precipitation estimation. The present paper evaluates radar error as a function of the range, in order to correct the rainfall radar estimates. The radar is calibrated utilizing data from the rain gauges. Then, the G/R ratio between the yearly rainfall amount measured in each rain gauge position during 2008 and the corresponding radar rainfall amount is calculated against the slant range. The trend of the G/R ratio shows two behaviours: a concave part due to the melting layer effect close to the radar location and an almost linear, increasing trend at greater distances. A best fitting line is used to find an adjustment factor, which estimates the radar error at a given range. The effectiveness of the methodology is verified by comparing pairs of rainfall time series that are observed simultaneously by collocated rain gauges and radar. Furthermore, the variability of the adjustment factor is investigated at the scale of event, both for convective and stratiform events. The main result is that there is not a univocal range error pattern, as it also depends on the characteristics of the considered event. On the other hand, the adjustment factor tends to stabilize itself for time aggregations of the order of one year or greater.

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“…These catchments were monitored for rainfall and runoff by Victoria University over a 4-year period from 1996. The data acquisition programme is described in detail in Maheepala et al (2001).…”

Section: Study Catchments and Datamentioning

confidence: 99%

Regionalisation of impervious area parameters of urban drainage models

Dayaratne

Perera

2008

Urban Water Journal

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Stormwater drainage models are increasingly being used in design and analysis of urban drainage systems. If these models are to be used for ungauged drainage systems for which no storm and corresponding flow data are available, then the model parameters have to be estimated through regional equations. These regional equations define the model parameters via measurable catchment properties. In this study, regional equations of two impervious area parameters, namely directly connected impervious area percentage (DCIA) and its depression storage (DS i ), were developed for use in urban drainage models, using 15 gauged urban catchments in Melbourne Metropolitan area (Australia). The 'small' storm events of these gauged catchments were first used to calibrate the impervious area parameters, since the 'small' storm events produce runoff only from the impervious areas. These calibrated impervious area model parameters were then analysed with several measurable catchment properties to derive the regional equations. The results of the study revealed that DCIA was depended only on household density of the catchment, while DS i was not correlated with any of the catchment properties analysed.

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Hydrological data monitoring for urban stormwater drainage systems

Cited by 35 publications

References 1 publication

Identification and quantification of the hydrological impacts of imperviousness in urban catchments: A review

Identification and quantification of the hydrological impacts of imperviousness in urban catchments: A review

On precipitation measurements collected by a weather radar and a rain gauge network

Regionalisation of impervious area parameters of urban drainage models

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