An innovative methodology for the prioritization of sub-catchments for flood control

Roughani, Mohammad; Ghafouri, M.

doi:10.1016/j.jag.2006.06.001

Cited by 29 publications

(18 citation statements)

References 5 publications

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“…At Linstock, the RMSE error is ±0.32 m and the NashSutcliffe coefficient is 0.96, while the prediction of the peak stage has an error of -3.56% and 5.3% in terms of magnitude and timing respectively. These are all within cited recommended limits of model performance (Roughani et al 2007;Wu and Johnston, 2008). However, any error in water level gives larger errors in predicted damages that will occur from flooding.…”

Section: Goodness Of Fit Statistics For Steps In Model Developmentsupporting

confidence: 64%

“…The performance of the calibrated Eden iSIS model at three gauging stations is shown in Table 6.16. Overall, the performance of the model is good, with errors within the range found in the literature (Roughani et al, 2007;Wu and Johnston, 2008). However, the model performs less well at Linstock gauging station.…”

Section: Spatial Downscaling Of Catchment Scale Flood Risk -Hydraulicsupporting

confidence: 64%

“…In terms of timing the peaks are quite well predicted, with an error of 0.5 hours (0.93%) and -0.25 hours (0.25%) for the first and second peaks respectively. The Nash-Sutcliffe coefficient of the Eamont model is 0.81 and the RMSE is ±0.034, which are within recommended limits found in the literature (Roughani et al 2007;Wu and Johnston, 2008). Values of >0.65 are thought to be acceptable in hydraulic and hydrological models (Rouhani et al, 2007;Wu and Johnston, 2008).…”

Section: Figure 924 Elevation-area Relationship For Different Reservsupporting

confidence: 58%

“…This was because the flows from these tributaries reached the catchment outlet before the contributions from the other tributaries arrived. Roughani et al (2007) also found that changes in tributaries close to the catchment outlet have the least impact on downstream flooding.…”

Section: Pc1mentioning

confidence: 84%

“…Saghafian and Khosroshahi (2005) identified flood source areas through a combined hydrological-hydraulic modelling approach, whereby tributary inputs were sequentially turned off and the impact downstream assessed through hydrograph change. Roughani et al, (2007) prioritised sub-catchments through changing the contribution of each tributary, also using a modelling approach.…”

Section: ) To Determine Which Areas (Sub-catchments) Of the Catchmenmentioning

confidence: 99%

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Rural land management impacts on catchment scale flood risk

Pattison¹

2010

Role of Hydrology in Managing Consequences of a Changing Global Environment

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The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-pro t purposes provided that:• a full bibliographic reference is made to the original source• a link is made to the metadata record in Durham E-Theses• the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full Durham E-Theses policy for further details. Most approaches to this problem aim to upscale from individual grid cells to whole catchments, something that restricts the complexity of possible process representation, produces models that may not be parsimonious with the data needed to calibrate them and, faced with data uncertainties, provides computational limitations on the extent to which model uncertainty can be fully explored. Rather than upscaling to problems of concern, this thesis seeks to downscale from locations of known flood risk, as a means of identifying where land use management changes might be beneficial and then uses numerical modelling to identify the kinds of management changes required in those downscaled locations. Thus, the aim of this thesis is to test an approach to understanding the impacts of rural land management upon flood risk based upon catchment-to-source downscaling.This thesis uses the case study of the River Eden catchment (2400 km 2 ) as a test (1) it was shown to have a significant impact on downstream flood risk; and (2) it had range of data and information needed for modelling land use changes.The second part of this thesis explored the land management scenarios that could be used to reduce flood risk at the catchment scale. The scenarios to be tested were determined through a stakeholder participation approach, whereby workshops were held to brainstorm and prioritise land management options, and then to identify specific locations within the Eamont sub-catchment where they could tested. There were two main types of land management scenarios chosen: (1) landscape-scale changes, including afforestation and compaction; and (2) corresponding to a 5.8% decrease in peak discharge. A key conclusion is that land management practices have been shown to have an effect on catchment scale flooding, even for extreme flood events. However, the effect of land management scenarios are both spatially and temporally dependent i.e. the same land management practice has different effects depending on where it is implemented, and when implemented in the same location has different effects on different flood events.

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Section: Goodness Of Fit Statistics For Steps In Model Developmentsupporting

confidence: 64%

Section: Spatial Downscaling Of Catchment Scale Flood Risk -Hydraulicsupporting

confidence: 64%

Section: Figure 924 Elevation-area Relationship For Different Reservsupporting

confidence: 58%

Section: Pc1mentioning

confidence: 84%

Section: ) To Determine Which Areas (Sub-catchments) Of the Catchmenmentioning

confidence: 99%

See 3 more Smart Citations

Rural land management impacts on catchment scale flood risk

Pattison¹

2010

Role of Hydrology in Managing Consequences of a Changing Global Environment

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Evaluation of floodplain variability considering impacts of climate change

Karamouz

Noori

Moridi

et al. 2010

Hydrological Processes

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Abstract:In this study, an approach is presented for handling hydraulic uncertainties in the prediction of floodplain. Different factors affect river flood characteristics. Furthermore, the high changeability of flooding conditions leads to high variability of the inundation.River morphology is one of the most effective factors in river flood characteristics. This factor is influenced by sedimentation and erosion in the river cross sections, which affects the discharge variation. The depth and the width of the river cross section lead to an increase or decrease in the river flow path. This results in changes in the extent of the floodplain based on the generated rainfall. The inundated region boundaries are determined by utilizing the mean first-order second-moment analysis. The proposed method is applied to the Kajoo River in the south-eastern part of Iran. Determination of floodplain uncertainty is a damage-reduction policy in this region. Also, it is useful to prepare the necessary activities for overcoming the flood hazards.Climate change is the second effective factor on the floodplain uncertainties. Climate change affects the magnitude, extent and depth of inundation and it may intensify the flood problem. Therefore, the future rainfall pattern of the study area under climate change is simulated to evaluate its impacts on the river flow characteristic. Subsequently, a hydraulic routing model is used to determine floodplain. Finally, the copula function is used to estimate the joint probability of the changes in the inundation area due to changes in river morphology and the rainfall changes due to impacts of climate change.Results show that the uncertainties of the extent of floodplain are affected by climate change and river morphology, leading to noticeable changes in the magnitude and frequency of floods. Evaluating these impacts and estimating corresponding river discharges will help in the study of river dynamics, and will also contribute towards devising effective mitigation and management strategies.

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Application of NEXRAD precipitation data for assessing the implications of low development practices in an ungauged basin

Aryal,

Kalra

2023

River

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Hydrologic analysis in watersheds lacking rain gauge stations has been a challenge and even those with stations that do not contain the required amount of data create problems in model verification. So, the study integrates the Next Generation Weather RadarIII precipitation data and the Personal Computer Storm Water Management Model (PCSWMM) for evaluating the model's effectiveness. The study further integrates 100‐year return period precipitation intensity and PCSWMM to generate a one‐dimensional flood risk zone map, which shows the major sub‐catchments under risk zones. Based on the identification of risk zones from PCSWMM, three different low‐impact developments (LIDs), street plants, infiltration trenches, and green roofs are applied independently and uniformly to compare the decrease in flow. Thereafter, the prioritized list of critical sub‐catchments from hydraulic modeling is compared with the compromise programming method, an approach for studying the decrement in flow by increasing LID application (infiltration trench) in the first five critical sub‐catchments, suggesting planners and researchers identify the most critical sub‐catchments and develop future potential strategies.

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An innovative methodology for the prioritization of sub-catchments for flood control

Cited by 29 publications

References 5 publications

Rural land management impacts on catchment scale flood risk

Rural land management impacts on catchment scale flood risk

Evaluation of floodplain variability considering impacts of climate change

Application of NEXRAD precipitation data for assessing the implications of low development practices in an ungauged basin

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