Modelling detention basins measured from high‐resolution light detection and ranging data

Wang, Lei; Yu, Jaehyung

doi:10.1002/hyp.8314

Cited by 12 publications

(7 citation statements)

References 28 publications

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“…QR due to projects observed in this study were well within the variability indicated in literature (0.3 % to 36 %) (Emerson et al 2005;Perez-Pedini et al 2005;Ravazzani et al 2014;Wang and Yu 2012). A strong dependency of QR on pre-event storage conditions (Ayalew et al 2013;Hancock et al 2010;Montaldo et al 2004), and precipitation intensity (Hancock et al 2010) were observed in this study.…”

Section: Discussionsupporting

confidence: 89%

Simulating the hydrologic impact of distributed flood mitigation practices, tile drainage, and terraces in an agricultural catchment

Thomas¹

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In 2008 flooding occurred over a majority of Iowa, damaging homes, displacing residents, and taking lives. In the wake of this event, the Iowa Flood Center (IFC) was charged with the investigation of distributed flood mitigation strategies to reduce the frequency and magnitude of peak flows in Iowa. This dissertation is part of the several studies developed by the IFC and focused on the application of a coupled physics based modeling platform, to quantify the coupled benefits of distributed flood mitigation strategies on the reduction of peak flows in an agricultural watershed. Additional investigation into tile drainage and terraces, illustrated the hydrologic impact of each commonly applied agricultural practice. The effect of each practice was represented in numerical simulations through a parameter adjustment. Systems were analyzed at the field scale, to estimate representative parameters, and applied at the watershed scale. The impact of distributed flood mitigation wetlands reduced peak flows by 4 % to 17 % at the outlet of a 45 km 2 watershed. Variability in reduction was a product of antecedent soil moisture, 24-hour design storm total depth, and initial structural storage capacity. The highest peak flow reductions occurred in scenarios with dry soil, empty project storage, and low rainfall depths. Peak flow reductions were estimated to dissipate beyond a total drainage area of 200 km 2 , approximately 2 km downstream of the small watershed outlet. A numerical tracer analysis identified the contribution of tile drainage to stream flow (QT/Q) which varied between 6 % and 71 % through an annual cycle. QT/Q responded directly to meteorological forcing. Precipitation driven events produced a strong positive logarithmic correlation between QT/Q and drainage area. The addition of precipitation into the system saturated near surface soils, increased lateral soil water v movement, and reduced the contribution of instream tile flow. A negative logarithmic trend in QT/Q to drainage area persisted in non-event durations. Simulated gradient terraces reduced and delayed peak flows in subcatchments of less than 3 km 2 of drainage area. The Hydrographs were shifted responding to rainfall later than non-terraced scenarios, while retaining the total volumetric outflow over longer time periods. The effects of dense terrace systems quickly dissipated, and found to be inconsequential at a drainage area of 45 km 2. Beyond the analysis of individual agricultural features, this work assembled a framework to analyze the feature at the field scale for implementation at the watershed scale. It showed large scale simulations reproduce field scale results well. The product of this work was, a systematic hydrologic characterization of distributed flood mitigation structures, pattern tile drainage, and terrace systems facilitating the simulation of each practices in a physically-based coupled surface-subsurface model.

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Section: Discussionsupporting

confidence: 89%

Simulating the hydrologic impact of distributed flood mitigation practices, tile drainage, and terraces in an agricultural catchment

Thomas¹

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“…This is important for wetland water body identification that is needed for flood mitigation (Huang and others, 2011), improving riparian channel environments (Hutton and Brazier, 2012), and defining storm water detention basins (Wang and Yu, 2012).…”

Section: Introductionmentioning

confidence: 99%

Lidar point density analysis: implications for identifying water bodies

Worstell¹,

Poppenga²,

Evans³

et al. 2014

Scientific Investigations Report

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“…Laser scanning in particular has enabled more accurate data gathering with decreased horizontal and vertical error and better availability of detailed spatial data. For example, airborne laser scanning (ALS) [1][2][3][4][5], ALS systems for bathymetric measurements [6], fixed-position terrestrial laser scanning (TLS) and mobile laser scanning (MLS), such as boat-and cart-based mobile mapping systems (BoMMS/CartMMS) [7,8], have shown new potential in fluvial research.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, the potential of high-resolution DTMs to represent linear anthropogenic features, such as depressions, and the use of these for more accurate flow pattern modelling in human modified landscapes [4] has been examined. Additionally, research concerning the effects of depressions on hydrologic models [5], the effects of the terrain slope [33], the effects of surface roughness [34,35] on depressions and also the impacts of grid size on hydrologic connectivity has been performed.…”

Section: Introductionmentioning

confidence: 99%

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Nationwide Digital Terrain Models for Topographic Depression Modelling in Detection of Flood Detention Areas

Vesakoski

Alho

Hyyppä

et al. 2014

Water

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Topographic depressions have an important role in hydrological processes as they affect the water balance and runoff response of a watershed. Nevertheless, research has focused in detail neither on the effects of acquisition and processing methods nor on the effects of resolution of nationwide grid digital terrain models (DTMs) on topographic depressions or the hydrological impacts of depressions. Here, we quantify the variation of hydrological depression variables between DTMs with different acquisition methods, processing methods and grid sizes based on nationwide 25 m × 25 m and 10 m × 10 m DTMs and 2 m × 2 m ALS-DTM in Finland. The variables considered are the mean depth of the depression, the number of its pixels, and its area and volume. Shallow and single-pixel depressions and the effect of mean filtering on ALS-DTM were also studied. Quantitative methods and error models were employed. In our study, the depression variables were dependent on the scale, area and acquisition method. When the depths of depression pixels were compared with the most accurate DTM, the maximum errors were OPEN ACCESSWater 2014, 6 272 found to create the largest differences between DTMs and hence dominated the amount and statistical distribution of the depth error. On the whole, the ability of a DTM to accurately represent depressions varied uniquely according to each depression, although DTMs also displayed certain typical characteristics. Thus, a DTM's higher resolution is no guarantee of a more accurate representation of topographic depressions, even though acquisition and processing methods have an important bearing on the accuracy.

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Modelling detention basins measured from high‐resolution light detection and ranging data

Cited by 12 publications

References 28 publications

Simulating the hydrologic impact of distributed flood mitigation practices, tile drainage, and terraces in an agricultural catchment

Simulating the hydrologic impact of distributed flood mitigation practices, tile drainage, and terraces in an agricultural catchment

Lidar point density analysis: implications for identifying water bodies

Nationwide Digital Terrain Models for Topographic Depression Modelling in Detection of Flood Detention Areas

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