Influence of land cover, proximity to streams and household topographical location on flooding impact in informal settlements in the Eastern Cape, South Africa

Dalu, Mwazvita T.B.; Shackleton, Charlie M.; Dalu, Tatenda

doi:10.1016/j.ijdrr.2017.12.009

Cited by 35 publications

(15 citation statements)

References 37 publications

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“…Due to climate change, droughts and floods have become more frequent in various parts of the world, of which some extreme cases result in loss of lives and properties (Dalu et al, 2018;Nchito 2007;Douglas et al, 2008;Turral et al, 2008;Bates et al, 2008;Gornall et al, 2010;Simane et al, 2016;Samu and Kentel, 2018;Kjeldsen et al, 2002). Floods are observed mostly as a result of extreme precipitation, tidal influences, or the release of a huge amount of water unexpectedly from a storage such as snowpacks or dams.…”

Section: Introductionmentioning

confidence: 99%

Pre-disaster planning and preparedness: drought and flood forecasting and analysis in Zimbabwe

Samu

Akıntuğ²

2020

WSA

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A situational analysis of future drought and flood impacts in Zimbabwe is outlined in this present study. The assessment under different scenarios is carried out using Aqueduct Global Flood Analyzer in which all the analyses are based on the gross domestic product (GDP), population, and the present and future (2030) urban damage. In this study, to effectively estimate future changes, three scenarios were employed, namely, IPCC Scenario A2, the Representative Concentration Pathways (RCP) scenario which represents climate change, and the Shared Socio-economic Pathways (SSP) scenario which represents socio-economic change. All these scenarios were employed from the Intergovernmental Panel on Climate Change 5th Assessment Report. To determine current mean monthly precipitation, 1981–2010 data were used and Meteonorm V7 software was employed for the generation of the mean monthly precipitation from 2011 to 2100. The level of flood protection employed is a 10-year one which is used to identify the population at risk, the effects of this event on the GDP and to determine the rate at which urban damage is happening. Utilizing Meteonorm V7 software, average monthly precipitation is predicted. This study determined that, in any year, the majority of Zimbabwe has a low to medium (2–3% probability) flood occurrence in which a 10-year flood has a 10% occurrence probability in any given year. If there is no flood protection employed, this 10-year flood could cause around 74.9 million USD affected GDP, 119 thousand affected population and 49.5 million USD urban damage. As much as it is impossible to eliminate drought and flood events, a diminution approach and proper planning and preparation before their occurrence reduce the economic and social losses.

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Section: Introductionmentioning

confidence: 99%

Pre-disaster planning and preparedness: drought and flood forecasting and analysis in Zimbabwe

Samu

Akıntuğ²

2020

WSA

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“…The catchments' delineations (Figure 1) were made with GIS software using digital elevation map data with a resolution of 30 m obtained using an advanced spaceborne thermal emission and reflection radiometer (ASTER) global digital elevation model (NASA/METI/AIST/Japan Spacesystems and US/Japan ASTER Science Team, 2009). Knowledge of land cover is of primary importance due to its impact on the genesis of floods (e.g., Abdulkareem, Sulaiman, Pradhan, & Jamil, 2018; Dalu, Shackleton, & Dalu, 2018; Estes et al, 2018).…”

Section: Methodsmentioning

confidence: 99%

Comparison of conceptual rainfall–runoff models in semi‐arid watersheds of eastern Algeria

Abdi

Meddi

2020

J Flood Risk Management

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The northeastern of Algeria is the rainiest region of the country, where regional catchments are often subject to devastating floods. To improve the management of water resources, there is a need to develop rainfall–runoff models. This study was conducted to propose an event‐based flood prediction model adapted to the region. Thereby, available rainfall–runoff data were used in several models to find the best one able to reproduce the flood hydrographs in three catchments. These models are based on the coupling of both production and transfer functions. For this purpose, five production functions were tested: the Soil Conservation Service–Curve Number (SCS‐CN) model, including three antecedent moisture conditions, and four modified Mishra and Singh models, incorporating antecedent moisture amounts. Three transfer functions were also tested: the Nash, Clark, and Weibull models. The tested models were all calibrated through a multi‐objective optimisation using the genetic algorithms method. It was found that the MMS models were better than the SCS‐CN method according to the performance criteria. Moreover, the proposed modified empirical equation (M4) improved runoff prediction. Furthermore, combined with the Nash model as a transfer function, the coupled model was found to be the best performing model, giving satisfactory results.

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“…The steeper a slope, the faster the surface flow and the greater potential to wash away soil particles. It was also stated by [12] that the slope factor has a great influence on the high surface runoff and causes flooding.…”

Section: Fig 4 Lcc Between 1985 and 2018 In Kuranji Watershedmentioning

confidence: 99%

The Dynamics of Land Cover Change and Causal Factors in the Kuranji Watershed

Putra¹

2021

GEOMATE

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Landcover changes (LCC) are one indicator of an increase in population in a watershed area that demands the provision of housing locations, road infrastructure, and productive land to meet the needs of life. LCC can positively impact the form of increased land use values and incomes, while also negative impacts in the form of erosion, landslides, and floods. The watershed area should have a balance in its development. This research is important as a first step in overcoming changes in land cover that can threaten the sustainability and sustainability of the Kuranji watershed. The aim of the study is to reveal the LCC from 1985 to 2018 and its causal factors in the Kuranji watershed. The methodology used is descriptive qualitative with 60 respondents. Data were obtained by interviewing respondents. Respondents are those having agricultural land and working in the agricultural sector and this research was carried out in 2019. The results showed an increase in the type of land cover of settlements and mixed gardens, while forests, rice fields and shrubs have decreased. The main factor influencing changes in land cover is economical (59%), followed by social factors (25%) and political factors (16%). It was also found that local wisdom of the Minangkabau culture was able to reduce LCC. In Minangkabau, the land owned by the community, in general, is a legacy from generation to generation that cannot be sold without significant reasons.

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Influence of land cover, proximity to streams and household topographical location on flooding impact in informal settlements in the Eastern Cape, South Africa

Cited by 35 publications

References 37 publications

Pre-disaster planning and preparedness: drought and flood forecasting and analysis in Zimbabwe

Pre-disaster planning and preparedness: drought and flood forecasting and analysis in Zimbabwe

Comparison of conceptual rainfall–runoff models in semi‐arid watersheds of eastern Algeria

The Dynamics of Land Cover Change and Causal Factors in the Kuranji Watershed

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