Process-based flood damage modelling relying on expert knowledge: a methodological contribution applied to agricultural sector

Flood damage assessment is crucial for evaluating flood management policies. In particular, properly assessing damage to the agricultural assets is important because they may have greater exposure and are complex economic systems. The modelling approaches used to assess flood damage are of several types and can be fed by damage data collected post-flood, from experiments or based on expert knowledge. The process-based models fed by expert knowledge are subject of research and also widely used in an operational way. Although identified as potentially transferable, they are in reality often case-specific and difficult to reuse in time (updatbililty) and space (transferability). In this paper, we argue that process-based models are not doomed to be context specific as far as the modelling process is rigorous. We propose a methodological framework aiming at verifying the conditions necessary to develop these models in a spirit of capitalisation by relying on four axes which are: i/ the explicitation of assumptions, ii/ the validation, iii/ the updatability, iv/ the transferability. The methodological framework is then applied to the model we have developed in France to produce national damage functions for the agricultural sector. We show in this paper that the proposed methodological framework allows an explicit description of the modelling assumptions and data used, which is necessary to consider a reuse in time or a transfer to another geographical area. We also highlight that despite the lack of feedback data on post-flood damages, the proposed methodological framework is a solid basis to consider the validation, transfer, comparison and capitalisation of data collected around process-based models relying on expert knowledge. In conclusion, we identify research tracks to be implemented to pursue this improvement in a spirit of capitalisation and international cooperation.

Urban Flood Management Under Changing Climate

Climate change and the associated phenomenon have put major cities and their surroundings at multi-dimensional risk patterns because of hazards, with flooding being a major hazard in the Asian Peninsula. With authorities such as National Disaster Management Authority, India reporting multiple urban local bodies to be under flood risk, it is essential to prioritize flood risk management in the urban planning process in India. Kochi, the commercial capital of Kerala, India has been frequently affected by flooding events. Various factors have been attributed to the flood risk of Kochi Corporation, which requires validation. Against this backdrop, the study focuses on comprehending significant factors attributed to the vulnerability of settlements in the study region and promoting a way forward based on lessons learned and good practices across the world. This is achieved by analyzing significant databases and computations using GIS. The research outcome would help define strategies for sustainable land-use-based development, promoting effective flood management in the Kochi urban area.

Regional Government Service Innovation Model in Disaster Mitigation

Indonesia has a geographical, geological, hydrological, and demographic situation prone to disasters with a relatively high frequency, thus requiring systematic, integrated, and coordinated disaster management. The disasters that occurred until 2020 were dominated by hydro-meteorological natural disasters such as floods, landslides, hurricanes, droughts to forests, and land fires (BNPB, 2021). The purpose of this study is to identify innovation models for regional government services in disaster mitigation. This study uses a qualitative descriptive method with data collection techniques, namely literature studies, FGDs, and interviews with related disaster mitigation innovations at the research location. The field findings illustrate that the SDIS innovation implemented by Sleman Regency is among the best innovations in handling volcanic eruptions. This innovation has been initiated since 2016 and continues to be refined. In the city of Semarang, specifically for flood disasters, the Early Warning System tool was installed at several points as the best innovation in flood management. However, difficulties were installing it at certain points due to geographical contours that were impossible. Meanwhile, for Sumedang Regency, their innovation through the SITABAH application still needs further development to become the best innovation in landslide mitigation due to limitations in infrastructure and human resources. In addition, the application is still one-way. Of the three disaster mitigation innovation models, the SDIS innovation is an innovation that has been successfully implemented by the Regional Disaster Management Agency of Sleman Regency. Especially on the "My distance and Merapi" feature, which can be accessed online, this innovation model can be replicated in other areas.

Effect of Hydrological Data on Flood Management in Urban Areas

Floods can occur due to rising water levels due to above-normal rainfall, changes in temperature, broken embankments/dams, rapid snowmelt, obstruction of water flow in other places, and putting people at risk of annual disasters due to flooding. The purpose of this study was to obtain a more detailed description of hydrological conditions so that flooding in the Bandar Lampung urban area can be optimally managed or controlled. The method used in flood control research is the analysis of the calculation of the average rainfall in the watershed, and the calculation of the planned discharge. The results of the analysis show that the existing drainage channels that have been carried out for each channel point have dimensions that are not large enough so that they are not sufficient to accommodate water runoff. so that for a 5-year discharge of 28.058 m3/s, the dimensions of the channel are 3 m wide and 2.6 m deep and for a 10-year discharge of 30.609 m3/s, the channel dimensions are 3.1 m wide and 2.7 m deep.

Evolution of Flood Defense Strategies: Toward Nature-Based Solutions

Flood defense strategies have evolved from hard-engineered systems to nature-based solutions that advocate for sustainability to meet today’s environmental, social, and economic goals. This paper aims to analyze the historical progression and evolutionary trends in flood control strategies that have led to nature-based solutions. An evaluative literature review was conducted to narrate the evolution of nature-based flood management approaches for different flood types, river floods, coastal floods, and stormwater run-offs. The analysis reflected three evolutionary trends: the transformation of hard measures to soft measures; secondly, the increase in society’s attention to ecosystems and their services; and, finally, divergence from single-function solutions to multi-function solutions. However, continuous monitoring and evaluation of the previous projects and adapting to the lessons learned are the key to progress towards sustainable flood management strategies and their societal acceptance.

Assessment of building damages and adaptation options under extreme flood scenarios in Shanghai

Plenty of various measures have been taken to mitigate flood losses in Shanghai over thousands of years, including the construction of sea dikes and floodwalls. However, the combined effects of intensified rainstorms, sea-level rise, land subsidence, and rapid urbanization are exacerbating extreme flood risks and potential flood losses in the fast-developing coastal city. In light of these changes, this article presents an assessment of possible exposure and damage losses of buildings in Shanghai (including residential, commercial, workplace, and industrial buildings). Based on extreme flood scenarios caused by storm surges, precipitation, and fluvial floods, current flood-defence standards will soon be overtaken. Further analyses show that the inundation area could reach 9 %, 16 %, 24 %, and 49 % of Shanghai (excluding the area of islands) under the 1/200, 1/500, 1/1000, and 1/5000-year flooding scenarios, respectively. This study finds, in terms of the total building damage, the 1/5000-year flood scenario damage is more than ten times the 1/200-year flood scenario. Accordingly, the average annual loss (AAL) of residential, commercial, office, and industrial buildings are 13.9, 2.3, 5.3, and 3.9 million USD. Specifically, among the 15 (non-island) districts in Shanghai, Pudong has the highest exposure and AAL at all the four flood scenarios, while the inner city (including seven districts) is also subject to extreme AAL of up to 40 % of its total building values. This study further addresses the possibilities of these extreme flood scenarios, and adaptation options such as: strategic urban planning, advanced building protections, and systematic flood management. Conclusions of the study provide information for scenario-based decision making and cost-benefit analysis for extreme flood risk management in Shanghai and is applicable to other similar coastal megacities.

Simulation-optimization framework in urban flood management for historic and climate change scenarios

A simulation-optimization framework is established by integrating Hydrologic Engineering Center Hydraulic Modeling System (HEC-HMS) for computation of runoff, siting tool EPA System for Urban Storm-water Treatment and Analysis INtegration (EPA-SUSTAIN) for placement of Best Management Practices (BMPs), and Binary Linear Integer Programming (BLIP) for runoff reduction. The framework is applied to an urban catchment, namely Greater Hyderabad Municipal Corporation (GHMC). The rainfall-runoff analysis was conducted for extreme rainfalls for historic (2016) and future events in 2050 and 2064 under Representative Concentration Pathways (RCPs) 6.0 and 8.5. The simulation-optimization approach in the historic scenario yielded 495,607 BMPs occupying 76.99 km2 resulting in runoff reduction of 21.54 mm (198.76–177.22 mm). Achieved runoff reduction is 38.72 (428.35–389.63 mm) and 55.03 (602.65–547.62 mm), respectively, for RCPs 6.0 and 8.5, which could meet the water demands of GHMC for 10.33 and 11.53 days. Impacts of 10 different BMP configurations of varying costs (10–70%) and pollutant load reductions (0–3%) on runoff reduction are accomplished as part of sensitivity analysis.