Analysis of potential flood damage on crops at global scale

2020 ◽  
Author(s):  
Antonio Annis ◽  
Davide Danilo Chiarelli ◽  
Fernando Nardi ◽  
Maria Cristina Rulli
Keyword(s):  
Food Security ◽  
Flood Risk ◽  
Large Scale ◽  
Flood Hazard ◽  
Strong Support ◽  
Flood Damage ◽  
Natural Ecosystems ◽  
Remotely Sensed Data ◽  
Regulated Rivers ◽  
Cropland Area

<p>Most of the food production connected to crops is located in fluvial corridors because of their suitable morphology and fertile soils. The knowledge and large scale quantification of the agricultural resources at flood risk has a crucial importance for improving urban and regional planning. Recent advances in satellite derived products related to land use, digital terrain and hydrologic variables can give a strong support on extensive analyses on cropland areas in floodplains and their interactions with natural ecosystems and human activities. In this work, we present a global assessment of cropland at flood risk in terms of extension, productivity and the related calories adopting the Global Cropland Area Database (GCAD), the Global Floodplain Dataset (GFPLAIN250m), the Global flood hazard maps (GFHM) in conjunction with continental remotely-sensed data representing free flowing (versus artificially regulated) rivers and urban density maps. Spatially distributed and aggregated results of the research allow to identify the most critical areas in terms of food security and floods, thus allowing to support intervention strategies for food security management at large scale and for different socio-economic contexts.</p>

scholarly journals Raising risk preparedness by flood risk communication

2015 ◽  
Vol 15 (7) ◽  
pp. 1577-1595 ◽  
Author(s):  
E. Maidl ◽  
M. Buchecker
Keyword(s):  
Risk Communication ◽  
Flood Risk ◽  
Information Needs ◽  
Flood Hazard ◽  
Flood Damage ◽  
Communication Strategy ◽  
Special Focus ◽  
Risk Awareness ◽  
Local Authorities ◽  
Risk Preparedness

Abstract. During the last decade, most European countries have produced hazard maps of natural hazards, but little is known about how to communicate these maps most efficiently to the public. In October 2011, Zurich's local authorities informed owners of buildings located in the urban flood hazard zone about potential flood damage, the probability of flood events and protection measures. The campaign was based on the assumptions that informing citizens increases their risk awareness and that citizens who are aware of risks are more likely to undertake actions to protect themselves and their property. This study is intended as a contribution to better understand the factors that influence flood risk preparedness, with a special focus on the effects of such a one-way risk communication strategy. We conducted a standardized mail survey of 1500 property owners in the hazard zones in Zurich (response rate main survey: 34 %). The questionnaire included items to measure respondents' risk awareness, risk preparedness, flood experience, information-seeking behaviour, knowledge about flood risk, evaluation of the information material, risk acceptance, attachment to the property and trust in local authorities. Data about the type of property and socio-demographic variables were also collected. Multivariate data analysis revealed that the average level of risk awareness and preparedness was low, but the results confirmed that the campaign had a statistically significant effect on the level of preparedness. The main influencing factors on the intention to prepare for a flood were the extent to which respondents evaluated the information material positively as well as their risk awareness. Respondents who had never taken any previous interest in floods were less likely to read the material. For future campaigns, we therefore recommend repeated communication that is tailored to the information needs of the target population.

scholarly journals Towards risk-based flood management in highly productive paddy rice cultivation – concept development and application to the Mekong Delta

2018 ◽  
Vol 18 (11) ◽  
pp. 2859-2876 ◽  
Author(s):  
Nguyen Van Khanh Triet ◽  
Nguyen Viet Dung ◽  
Bruno Merz ◽  
Heiko Apel
Keyword(s):  
Land Use ◽  
Flood Risk ◽  
Large Scale ◽  
Flood Hazard ◽  
Mekong Delta ◽  
Flood Management ◽  
Paddy Rice ◽  
Rice Cultivation ◽  
Spatially Explicit ◽  
Risk Maps

Abstract. Flooding is an imminent natural hazard threatening most river deltas, e.g. the Mekong Delta. An appropriate flood management is thus required for a sustainable development of the often densely populated regions. Recently, the traditional event-based hazard control shifted towards a risk management approach in many regions, driven by intensive research leading to new legal regulation on flood management. However, a large-scale flood risk assessment does not exist for the Mekong Delta. Particularly, flood risk to paddy rice cultivation, the most important economic activity in the delta, has not been performed yet. Therefore, the present study was developed to provide the very first insight into delta-scale flood damages and risks to rice cultivation. The flood hazard was quantified by probabilistic flood hazard maps of the whole delta using a bivariate extreme value statistics, synthetic flood hydrographs, and a large-scale hydraulic model. The flood risk to paddy rice was then quantified considering cropping calendars, rice phenology, and harvest times based on a time series of enhanced vegetation index (EVI) derived from MODIS satellite data, and a published rice flood damage function. The proposed concept provided flood risk maps to paddy rice for the Mekong Delta in terms of expected annual damage. The presented concept can be used as a blueprint for regions facing similar problems due to its generic approach. Furthermore, the changes in flood risk to paddy rice caused by changes in land use currently under discussion in the Mekong Delta were estimated. Two land-use scenarios either intensifying or reducing rice cropping were considered, and the changes in risk were presented in spatially explicit flood risk maps. The basic risk maps could serve as guidance for the authorities to develop spatially explicit flood management and mitigation plans for the delta. The land-use change risk maps could further be used for adaptive risk management plans and as a basis for a cost–benefit of the discussed land-use change scenarios. Additionally, the damage and risks maps may support the recently initiated agricultural insurance programme in Vietnam.

scholarly journals Large-scale application of the flood damage model RAilway Infrastructure Loss (RAIL)

2016 ◽  
Vol 16 (11) ◽  
pp. 2357-2371 ◽  
Author(s):  
Patric Kellermann ◽  
Christine Schönberger ◽  
Annegret H. Thieken
Keyword(s):  
Risk Management ◽  
Risk Aversion ◽  
Flood Risk ◽  
Structural Damage ◽  
Large Scale ◽  
Damage Model ◽  
Flood Damage ◽  
Railway Infrastructure ◽  
Increased Risk ◽  
The Impact

Abstract. Experience has shown that river floods can significantly hamper the reliability of railway networks and cause extensive structural damage and disruption. As a result, the national railway operator in Austria had to cope with financial losses of more than EUR 100 million due to flooding in recent years. Comprehensive information on potential flood risk hot spots as well as on expected flood damage in Austria is therefore needed for strategic flood risk management. In view of this, the flood damage model RAIL (RAilway Infrastructure Loss) was applied to estimate (1) the expected structural flood damage and (2) the resulting repair costs of railway infrastructure due to a 30-, 100- and 300-year flood in the Austrian Mur River catchment. The results were then used to calculate the expected annual damage of the railway subnetwork and subsequently analysed in terms of their sensitivity to key model assumptions. Additionally, the impact of risk aversion on the estimates was investigated, and the overall results were briefly discussed against the background of climate change and possibly resulting changes in flood risk. The findings indicate that the RAIL model is capable of supporting decision-making in risk management by providing comprehensive risk information on the catchment level. It is furthermore demonstrated that an increased risk aversion of the railway operator has a marked influence on flood damage estimates for the study area and, hence, should be considered with regard to the development of risk management strategies.

scholarly journals Assessment of Flood Hazard and Agriculture Damage Under Climate Change in the Bagmati River Basin of Nepal

2019 ◽  
Vol 8 (2) ◽  
pp. 55-69 ◽  
Author(s):  
Badri Bhakta Shrestha
Keyword(s):  
River Basin ◽  
Flood Risk ◽  
Damage Assessment ◽  
Growth Stage ◽  
Flood Hazard ◽  
Flood Damage ◽  
Flood Risk Management ◽  
Flood Inundation ◽  
Flood Hazards ◽  
Bagmati River

Assessment of flood hazard and damage is a prerequisite for flood risk management in the river basins. The mitigation plans for flood risk management are mostly evaluated in quantified terms as it is important in decision making process. Therefore, analysis of flood hazards and quantitative assessment of potential flood damage is very essential for mitigating and managing flood risk. This study focused on assessment of flood hazard and quantitative agricultural damage in the Bagmati River basin including Lal Bakaiya River basin of Nepal under climate change conditions. Flood hazards were simulated using Rainfall Runoff Inundation (RRI) model. MRI-AGCM3.2S precipitation outputs of present and future climate scenarios were used to simulate flood hazards, flood inundation depth, and duration. Flood damage was assessed in the agricultural sector, focusing on flood damage to rice crops. The flood damage assessment was conducted by defining flood damage to rice crops as a function of flood depth, duration, and growth stage of rice plants and using depth-duration-damage function curves for each growth stage of rice plants. The hazard simulation and damage assessment were conducted for 50- and 100-year return period cases. The results show that flood inundation area and agricultural damage area may increase in the future by 41.09 % and 39.05 % in the case of 50-year flood, while 44.98 % and 40.76 % in the case of 100-year flood. The sensitivity to changes in flood extent area and damage with the intensity of return period was also analyzed.

Rapid Global Exposure Assessment for Extreme River Flood Risk Under Climate Change

2016 ◽  
Vol 11 (6) ◽  
pp. 1128-1136 ◽  
Author(s):  
Youngjoo Kwak ◽  
◽  
Yoichi Iwami ◽  
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Flood Risk ◽  
Large Scale ◽  
Flood Hazard ◽  
Data Availability ◽  
Flood Risk Assessment ◽  
Daily Data ◽  
Extreme Flood ◽  
River Flood

Globally, large-scale floods are one of the most serious disasters, considering increased frequency and intensity of heavy rainfall. This is not only a domestic problem but also an international water issue related to transboundary rivers in terms of global river flood risk assessment. The purpose of this study is to propose a rapid flood hazard model as a methodological possibility to be used on a global scale, which uses flood inundation depth and works reasonably despite low data availability. The method is designed to effectively simplify complexities involving hydrological and topographical variables in a flood risk-prone area when applied in an integrated global flood risk assessment framework. The model was used to evaluate flood hazard and exposure through pixel-based comparison in the case of extreme flood events caused by an annual maximum daily river discharge of 1/50 probability of occurrence under the condition of climate change between two periods, Present (daily data from 1980 to 2004) and Future (daily data from 2075 to 2099). As preliminary results, the maximum potential extent of inundation area and the maximum number of affected people show an upward trend in Present and Future.

scholarly journals Review Article: Validation of flood risk models: current practice and innovations

2017 ◽  
Author(s):  
Daniela Molinari ◽  
Karin De Bruijn ◽  
Jessica Castillo ◽  
Giuseppe T. Aronica ◽  
Laurens M. Bouwer
Keyword(s):  
Flood Risk ◽  
Flood Hazard ◽  
Flood Damage ◽  
Quality Data ◽  
Risk Models ◽  
Risk Modelling ◽  
Risk Estimates ◽  
Models Validation ◽  
Benchmark Solutions ◽  
Research Recommendations

Abstract. Although often neglected, model validation is a key topic in flood risk analysis, as flood risk estimates are characterised by significant levels of uncertainty. In this paper, we discuss the state of art of flood risk models validation, as concluded from the discussion among more than 50 experts at two main scientific events. The events aimed at identifying policy and research recommendations towards promoting more common practice of validation, and an improvement of flood risk models reliability. We pay specific attention to the different components of the risk modelling chain (i.e. flood hazard, defence failure and flood damage analysis) as well as to their role into risk estimates, to highlight specificities and commonalities with respect to implemented techniques and research needs. The main conclusions from this review can be summarised as the need of higher quality data to perform validation and of benchmark solutions to be followed in different contexts, along with a greater involvement of end-users in the debate on flood risk models validation.

scholarly journals Large Scale Flood Risk Mapping in Data Scarce Environments: An Application for Romania

Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1834 ◽  
Author(s):  
Raffaele Albano ◽  
Caterina Samela ◽  
Iulia Crăciun ◽  
Salvatore Manfreda ◽  
Jan Adamowski ◽  
...  
Keyword(s):  
Land Use ◽  
Flood Risk ◽  
Large Scale ◽  
Binary Classification ◽  
Depth Map ◽  
Return Time ◽  
Flood Damage ◽  
Landsat 8 ◽  
Machine Learning Classification ◽  
Cost Efficient

Large-scale flood risk assessment is essential in supporting national and global policies, emergency operations and land-use management. The present study proposes a cost-efficient method for the large-scale mapping of direct economic flood damage in data-scarce environments. The proposed framework consists of three main stages: (i) deriving a water depth map through a geomorphic method based on a supervised linear binary classification; (ii) generating an exposure land-use map developed from multi-spectral Landsat 8 satellite images using a machine-learning classification algorithm; and (iii) performing a flood damage assessment using a GIS tool, based on the vulnerability (depth–damage) curves method. The proposed integrated method was applied over the entire country of Romania (including minor order basins) for a 100-year return time at 30-m resolution. The results showed how the description of flood risk may especially benefit from the ability of the proposed cost-efficient model to carry out large-scale analyses in data-scarce environments. This approach may help in performing and updating risk assessments and management, taking into account the temporal and spatial changes in hazard, exposure, and vulnerability.

scholarly journals Integrating large-scale hydrology and hydrodynamics for nested flood hazard modelling from the mountains to the coast

2019 ◽  
Author(s):  
Jannis M. Hoch ◽  
Dirk Eilander ◽  
Hiroaki Ikeuchi ◽  
Fedor Baart ◽  
Hessel C. Winsemius
Keyword(s):  
Flood Risk ◽  
Large Scale ◽  
Management Practices ◽  
Flood Hazard ◽  
Hydrologic Model ◽  
Model Coupling ◽  
Coupled Models ◽  
Critical Success ◽  
Inundation Modelling ◽  
Flood Simulations

Abstract. Fluvial flood events were, are, and will remain a major threat to people and infrastructure. Typically, flood hazard is driven by hydrologic or river routing and floodplain flow processes. Since they are often simulated by different models, coupling these models may be a viable way to increase the physicality of simulated inundation estimates. To facilitate coupling different models and integrating across flood hazard processes, we here present GLOFRIM 2.0, a globally applicable framework for integrated hydrologic-hydrodynamic modelling. We then tested the hypothesis that smart model coupling can advance inundation modelling in the Amazon and Ganges basins. By means of GLOFRIM, we coupled the global hydrologic model PCR-GLOBWB with the hydrodynamic models CaMa-Flood and LISFLOOD-FP. Results show that replacing the kinematic wave approximation of the hydrologic model with the local inertia equation of CaMa-Flood greatly enhances accuracy of peak discharge simulations as expressed by an increase of NSE from 0.48 to 0.71. Flood maps obtained with LISFLOOD-FP improved representation of observed flood extent (critical success index C = 0.46), compared to downscaled products of PCR-GLOBWB and CaMa-Flood (C = 0.30 and C = 0.25, respectively). Results confirm that model coupling can indeed be a viable way forward towards more integrated flood simulations. However, results also suggest that the accuracy of coupled models still largely depends on the model forcing. Hence, further efforts must be undertaken to improve the magnitude and timing of simulated runoff. Besides, flood risk is, particularly in delta areas, driven by coastal processes. A more holistic representation of flood processes in delta areas, for example by incorporating a tide and surge model, must therefore be a next development step of GLOFRIM, making even more physically-robust estimates possible for adequate flood risk management practices.

Large Scale Flood Damage Mapping: the case study of Romania Country

2020 ◽  
Author(s):  
Raffaele Albano ◽  
Aurelia Sole ◽  
Salvatore Manfreda ◽  
Caterina Samela ◽  
Iulia Craciun ◽  
...  
Keyword(s):  
Machine Learning ◽  
Land Use ◽  
High Resolution ◽  
Flood Risk ◽  
Large Scale ◽  
Flood Damage ◽  
Emergency Operations ◽  
Hazard Exposure ◽  
Cost Efficient ◽  
Damage Mapping

<p>A large-scale flood risk analysis that properly evaluates and quantifies the three components of risk (hazard, exposure and vulnerability) is essential in order to support national and global policies, emergency operations and land use management. For example, governments can use risk information for the prioritisation of investments to implement measures for flood damage reduction, for emergency operations and for land-use policies, while reinsurance companies can improve the estimation of the flood risk-based insurance premiums.</p><p>Nevertheless, limits in time and data represent significant limitation this kind of applications: i) the significant amount of data and parameters required for the calibration and validation of traditional model; ii) the moderate/coarse resolution of data available at global scale and the sparse availability of high-resolution data that may affect the accuracy of analysis results; iii) the high cost and computational demand of hydraulic models. However, the growing availability of data from new technologies of Earth observation (EO) and environmental monitoring combined with the advances in newly developed algorithms (e.g. machine learning) have extended the range of possibilities for geoscientists, updating and re-inventing the way highly resource- and data-intensive processes, such as risk management and communication, are carried out.</p><p>The present study proposes a cost-efficient method for large-scale analysis and mapping of direct economic flood damage at medium resolution in data-scarce environments. The proposed methodological framework consists of three main stages. The first step concerns the derivation of a water depth map through a Digital Elevation Model (30m resolution)-based geomorphic method that uses supervised linear binary classification. The second step aims to realize an exposure map on the basis of a supervised land use classification through the use of a machine learning technique: the information extracted from Landsat-8 remotely sensed optical images were utilized in combination with the discontinuous (i.e. available for a few large cities in Europe) existing high-resolution Urban-Atlas land use maps in order to obtain a land-use map with a resolution of 30 m. Finally, the flood economic damage mapping was carried out using the results of the two previous steps in a GIS algorithm, developed by authors, based on the vulnerability (depth-damage) curves method. The proposed integrated framework has been tested in Romania for a 100-years return time event. The resulting map (at 30 m resolution) covers the entire Romanian territory including minor order rivers, which are often neglected in large-scale analyses.</p><p>The demonstrative application shows how the description of flood risk may particularly benefit from the integrated use of geomorphic methods, machine learning algorithms and EO freely available monitoring data. The ability of the proposed cost-efficient model to carry out high-resolution and large-scale analyses in data-scarce environments allows performing future risk assessments keeping abreast of temporal and spatial changes in terms of hazard, exposure and vulnerability.</p><p><em>Acknowledgement: This work was carried out during the tenure of an ERCIM ‘Alain Bensoussan’ Fellowship Programme.</em></p>

scholarly journals Assessing Cropland Area in West Africa for Agricultural Yield Analysis

2018 ◽  
Vol 10 (11) ◽  
pp. 1785 ◽  
Author(s):  
Kaboro Samasse ◽  
Niall Hanan ◽  
Gray Tappan ◽  
Yacouba Diallo
Keyword(s):  
Food Security ◽  
Land Cover ◽  
West Africa ◽  
Spatial Resolution ◽  
Crop Production ◽  
Agricultural Landscape ◽  
Agricultural Land ◽  
Remotely Sensed Data ◽  
Cropland Area ◽  
Western Sahel

Accurate estimates of cultivated area and crop yield are critical to our understanding of agricultural production and food security, particularly for semi-arid regions like the Sahel of West Africa, where crop production is mainly rain-fed and food security is closely correlated with the inter-annual variations in rainfall. Several global and regional land cover products, based on satellite remotely-sensed data, provide estimates of the agricultural land use intensity, but the initial comparisons indicate considerable differences among them, relating to differences in the satellite data quality, classification approaches, and spatial and temporal resolutions. Here, we quantify the accuracy of available cropland products across Sahelian West Africa using an independent, high-resolution, visually interpreted sample dataset that classifies all points across West Africa using a 2-km sample grid (~500,000 points for the study area). We estimate the “quantity” and “allocation” disagreements for the cropland class of eight land cover products in five Western Sahel countries (Burkina Faso, Mali, Mauritania, Niger, and Senegal). The results confirm that coarse spatial resolution (300 m, 500 m, and 1000 m) land cover products have higher disagreements in mapping the fragmented agricultural landscape of the Western Sahel. Earlier products (e.g., GLC2000) are less accurate than recent products (e.g., ESA CCI 2013, MODIS 2013 and GlobCover 2009). We also show that two of the finer spatial resolution maps (GFSAD30, and GlobeLand30) using advanced classification approaches (random forest, decision trees, and pixel-object combined) are currently the best available products for cropland identification. However, none of the eight land cover databases examined is consistent in reaching the targeted 75% accuracy threshold in the five Sahelian countries. The majority of currently available land cover products overestimate cultivated areas by an average of 170% relative to the cropland area in the reference data.

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