Scoping the role of agriculture in sustainable flood management

Kenyon, Wendy; Hill, Gary W.; Shannon, Peter

doi:10.1016/j.landusepol.2007.09.003

Cited by 68 publications

(42 citation statements)

References 11 publications

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“…This integrated approach is also reflected in the 2007 European Directive on the Assessment and Management of Floods: in addition to the assessment and mapping of flood hazards and flood risks, it recommends the use of Flood Risk Management Plans which include nonstructural protection measures, for example the restoration of floodplains and wetlands (Directive 2007/60/EC, Evers 2008, Kenyon et al 2008). …”

Section: Introductionmentioning

confidence: 99%

“…Different authors have discussed the impact of flood storage policies in England and Scotland (Johnson et al 2007; Kenyon et al 2008;Morris et al 2008 andPosthumus et al 2008) or the impact of more natural flood prevention policies in Europe (Evers 2008, Hansson et al 2008, Moss and Monstadt 2008. Morris et al propose an evaluation method to measure the impact of the creation of washland on agricultural activity.…”

Section: Introductionmentioning

confidence: 99%

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Risk-sharing policies in the context of the French Flood Prevention Action Programmes

Erdlenbruch

Thoyer

Grelot

et al. 2009

Journal of Environmental Management

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This article analyzes the consequences for risk distribution of the French Flood Prevention Action Programme (PAPI). By redirecting floods from the most vulnerable to the least vulnerable areas, PAPIs expose farmers to greater flood risks. This has led local water management institutions to introduce compensation payments. The article outlines the results of an exhaustive survey of all PAPI programmes in France, which examined the way the compensation policies are set up locally. Results of the survey showed that the proposed policies may be financially non-viable. Several more viable risk-sharing solutions are then discussed, involving insurance schemes, state intervention and local institutions

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Risk-sharing policies in the context of the French Flood Prevention Action Programmes

Erdlenbruch

Thoyer

Grelot

et al. 2009

Journal of Environmental Management

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“…The intensification of agriculture over the past 15-20 years has coincided with a rise in flood risk (Kenyon et al, 2008). It has been hypothesised that the two events are linked, through the reduction of infiltration, leading to increased runoff.…”

Section: Arable Agriculturementioning

confidence: 99%

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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“…The estimated loss caused by the flood compared to all other disasters is about 40%. Floods occur frequently, affecting large areas [5]. To anticipate floods and impacts, appropriate techniques should be developed for flood prediction [10].…”

Section: Introductionmentioning

confidence: 99%

Backpropagation Neural Network Algorithm for Water Level Prediction

Subianto¹,

Suryono²,

Suseno³

2018

IJCA

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Floods cause economic losses, even cause loss of life. To anticipate floods and the impacts, flood prediction including early warning systems should be developed using appropriate techniques. The aim of this research is to apply the back propagation neural network algorithm for water level prediction and produce web-based flood prediction information system. The system is built using a back propagation neural network algorithm. This algorithm has 3 stages in the training process, which are forward feed, calculation, and back propagation. The used data is derived from the physics laboratory of Diponegoro University. This study concludes that the application of back propagation neural network algorithm for flood prediction can produce an accurate prediction. Therefore, this can be a reference for predicting floods significantly based on water levels in certain places. In this study obtained MSE at the first iteration of 0.0142, the smallest MSE that meets the limit of threshold of 0.000002420 and data accuracy of 98.66%. This means that generally, the back propagation neural networks application produce accurate water level prediction, which is close to the actual data.

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Scoping the role of agriculture in sustainable flood management

Cited by 68 publications

References 11 publications

Risk-sharing policies in the context of the French Flood Prevention Action Programmes

Risk-sharing policies in the context of the French Flood Prevention Action Programmes

Rural land management impacts on catchment scale flood risk

Backpropagation Neural Network Algorithm for Water Level Prediction

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