Monte Carlo analysis of the effect of spatial distribution of storms on prioritization of flood source areas

Saghafian, Bahram; Golian, Saeed; Elmi, Mohammad; Akhtari, Rouhangiz

doi:10.1007/s11069-012-0537-2

Cited by 15 publications

(7 citation statements)

References 18 publications

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“…LULC change is considered as the single most crucial variable of global change and is as large as that associated with the climate change, having a significant impact on the environment (Gujree et al 2017), due to which inventory, assessment, and monitoring of LULC change provides a vital input to environmental decision-making (Meraj et al 2013) and are crucial for further understanding and modeling of change mechanism at different scales (Van De Wiel et al 2011;Altaf et al 2014). Many urban land use studies have used satellite images to generate accurate urban land use maps and also detected changes in urban land use/land cover (Javed et al 2009;Chen et al 2011;Saghafian et al 2013;Badar et al 2013a, b;Valipour 2015;Taloor et al 2020). The short-and long-term monitoring of LULC change is vital in establishing links between policy decision-making, regulatory actions, and subsequent land use planning activities for the management of natural resources (Mosbahi et al 2012;Trabucchi et al 2013;Jang et al 2013).…”

Section: Introductionmentioning

confidence: 99%

Assessing the impact of land use and land cover dynamics on water quality of Dal Lake, NW Himalaya, India

Rather

Dar

2020

Appl Water Sci

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A dynamic process like land use, if anthropogenically unsustainable, adversely affects the well-being of the land system. Worldwide, water bodies are facing imminent threat due to unsustainable anthropogenic activities. Water quality and ecology are the two characteristics of water bodies, if not preserved, shall have a direct consequence on the well-being of the human systems. Hence it is essential to understand the causes and consequences of the deteriorating water body systems. The condition is particularly grim in Himalayan water body ecosystems, where unplanned and unchecked urbanization has threatened their very existence. In the present study, the dynamics of land use/land cover (LULC) and its impact on the water quality of Dal Lake in Kashmir Himalaya, India has been assessed. We carried out a detailed study wherein changing LULC is analyzed against the deteriorating trophic status of the Dal Lake using time-series of satellite imagery of the lake’s catchment and its water quality data. Results indicated that the water quality of Dal Lake has remarkably deteriorated due to increased nutrient and sediment loads from the catchment, attributed to significant anthropogenic activities in the catchment. Due to unprecedented LULC changes in the catchment, the forest class shows a significantly negative change since the last four decades (1980–2018), corroborating with the ongoing deterioration of physicochemical characteristics of the lake. The analysis shows an increase in all the agents of eutrophication, such as NO3–N, TP, and COD, from 1990 to 2018. The decrease in forest, agriculture, and floating gardens was observed to show a significant negative correlation with the increase in the decadal average values of the COD, NO3–N, and TP for the same corresponding period. Similarly, a positive correlation was found between the increase in built-up, aquatic vegetation, bare surfaces, and these water quality parameters, establishing a strong relationship between the deteriorating condition of the lake and changing LULC. Our findings indicate that changing LULC of the lake’s catchment is one of the critical factors that has significantly contributed toward the deteriorating ecology and water quality of the Dal Lake. This study shall contribute toward the development of the robust conservation strategy in order to save this urban lake from its untimely death.

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Section: Introductionmentioning

confidence: 99%

Assessing the impact of land use and land cover dynamics on water quality of Dal Lake, NW Himalaya, India

Rather

Dar

2020

Appl Water Sci

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“…Many studies have confirmed that the spatial rainfall pattern significantly governs the flood characteristics [20]. Therefore, determining the flood response, magnitude, and frequency from rainfall is necessary for selection of the best management practices [21].…”

Section: Introductionmentioning

confidence: 99%

“…The implementation and cost of structural and non-structural flood measures in large flood-prone non-perennial river basins are challenging issues. One way to deal with this is to minimize the cost of flood damages by considering downstream flood-threatened areas with the most sensitive subbasins instead of the entire basin [12,20,22]. For this, Saghafian and Khosroshahi (2005) proposed a Unit Flood Response (UFR) approach to identify and rank flood-threatened subbasins in quantitative terms related to flood source area.…”

Section: Introductionmentioning

confidence: 99%

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Climate Change Impact on Flood Frequency and Source Area in Northern Iran under CMIP5 Scenarios

Maghsood

Moradi

Bavani

et al. 2019

Water

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This study assessed the impact of climate change on flood frequency and flood source area at basin scale considering Coupled Model Intercomparison Project phase 5 General Circulation Models (CMIP5 GCMs) under two Representative Concentration Pathways (RCP) scenarios (2.6 and 8.5). For this purpose, the Soil and Water Assessment Tool (SWAT) hydrological model was calibrated and validated for the Talar River Basin in northern Iran. Four empirical approaches including the Sangal, Fill–Steiner, Fuller, and Slope-based methods were used to estimate the Instantaneous Peak Flow (IPF) on a daily basis. The calibrated SWAT model was run under the two RCP scenarios using a combination of twenty GCMs from CMIP5 for the near future (2020–40). To assess the impact of climate change on flood frequency pattern and to quantify the contribution of each subbasin on the total discharge from the Talar River Basin, Flood Frequency Index (FFI) and Subbasin Flood Source Area Index (SFSAI) were used. Results revealed that the projected climate change will likely lead to an average discharge decrease in January, February, and March for both RCPs and an increase in September and October for RCP 8.5. The maximum and minimum temperature will likely increase for all months in the near future. The annual precipitation could increase by more than 20% in the near future. This is likely to lead to an increase of IPF. The results can help managers and policy makers to better define mitigation and adaptation strategies for basins in similar climates.

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“…The UFR framework has additionally been used to show the importance of spatial variability in rainfall when investigating FSAs. The impact of spatial rainfall on the flood index of sub-catchments was further examined through Monte Carlo analysis (Saghafian et al 2013). The simulation and analyses concluded that the use of spatially varied rainfall has a significant impact on the prioritisation of FSAs.…”

Section: Flood Index Categorisaɵonmentioning

confidence: 99%

A review of modelling methodologies for flood source area (FSA) identification

et al. 2021

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Flooding is an important global hazard that causes an average annual loss of over 40 billion USD and affects a population of over 250 million globally. The complex process of flooding depends on spatial and temporal factors such as weather patterns, topography, and geomorphology. In urban environments where the landscape is ever-changing, spatial factors such as ground cover, green spaces, and drainage systems have a significant impact. Understanding source areas that have a major impact on flooding is, therefore, crucial for strategic flood risk management (FRM). Although flood source area (FSA) identification is not a new concept, its application is only recently being applied in flood modelling research. Continuous improvements in the technology and methodology related to flood models have enabled this research to move beyond traditional methods, such that, in recent years, modelling projects have looked beyond affected areas and recognised the need to address flooding at its source, to study its influence on overall flood risk. These modelling approaches are emerging in the field of FRM and propose innovative methodologies for flood risk mitigation and design implementation; however, they are relatively under-examined. In this paper, we present a review of the modelling approaches currently used to identify FSAs, i.e. unit flood response (UFR) and adaptation-driven approaches (ADA). We highlight their potential for use in adaptive decision making and outline the key challenges for the adoption of such approaches in FRM practises.

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Monte Carlo analysis of the effect of spatial distribution of storms on prioritization of flood source areas

Cited by 15 publications

References 18 publications

Assessing the impact of land use and land cover dynamics on water quality of Dal Lake, NW Himalaya, India

Assessing the impact of land use and land cover dynamics on water quality of Dal Lake, NW Himalaya, India

Climate Change Impact on Flood Frequency and Source Area in Northern Iran under CMIP5 Scenarios

A review of modelling methodologies for flood source area (FSA) identification

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