Integrated Seismic Risk Assessment in Nepal

As Nepal is at high risk of earthquakes, the district-wide (VDC/Municipality level) study has been performed for vulnerability assessment of seismic-hazard, and the hazard-risk study is incorporated with social conditions as it has become a crucial issue in recent years. There is an interrelationship between hazards, physical risk, and the social characteristics of populations which are significant for policy-makers and individuals. Mapping the spatial variability of average annual loss (seismic risk) and social vulnerability discretely does not reflect the true nature of parameters contributing to the earthquake risk, so when the integrated risk is mapped, such combined spatial distribution becomes more evident. The purpose of this paper is to compute the risk analysis from the exposure model of the country using OpenQuake and then integrate the results with socio-economic parameters. The methodology of seismic-risk assessment and the way of combining the results of the physical risk and socio-economic data to develop an integrated vulnerability score of the regions has been described. This study considers all 75 districts and corresponding VDC/Municipalities using the available census. The combined vulnerability score has been developed and presented by integrating earthquake risk and social vulnerability aspects of the country and represented in form of the map produced using ArcGIS 10. The knowledge and information of the relationship between earthquake hazards and the demographic characteristics of the population in the vulnerable area are imperative to mitigate the local impact of earthquakes. Therefore, we utilize social vulnerability study as part of a comprehensive risk management framework to recuperate and recover from natural disasters.

Multi-risk assessment in a historical city

Natural hazards pose a significant threat to historical cities which have an authentic and universal value for mankind. This study aims at codifying a multi-risk workflow for seismic and flood hazards, for site-scale applications in historical cities, which provides the Average Annual Loss for buildings within a coherent multi-exposure and multi-vulnerability framework. The proposed methodology includes a multi-risk correlation and joint probability analysis to identify the role of urban development in re-shaping risk components in historical contexts. The workflow is unified by exposure modelling which adopts the same assumptions and parameters. Seismic vulnerability is modelled through an empirical approach by assigning to each building a vulnerability value depending on the European Macroseismic Scale (EMS-98) and modifiers available in literature. Flood vulnerability is modelled by means of stage-damage curves developed for the study area and validated against ex-post damage claims. The method is applied to the city centre of Florence (Italy) listed as UNESCO World Heritage site since 1982. Direct multi-hazard, multi-vulnerability losses are modelled for four probabilistic scenarios. A multi-risk of 3.15 M€/year is estimated for the current situation. In case of adoption of local mitigation measures like floodproofing of basements and installation of steel tie rods, multi-risk reduces to 1.55 M€/yr. The analysis of multi-risk correlation and joint probability distribution shows that the historical evolution of the city centre, from the roman castrum followed by rebuilding in the Middle Ages, the late XIX century and the post WWII, has significantly affected multi-risk in the area. Three identified portions of the study area with a different multi-risk spatial probability distribution highlight that the urban development of the historical city influenced the flood hazard and the seismic vulnerability. The presented multi-risk workflow could be applied to other historical cities and further extended to other natural hazards.

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.

A Performance-Based Approach to Quantify Atmospheric River Flood Risk

Atmospheric rivers (ARs) are a class of meteorologic phenomena that cause significant precipitation and flooding on the US West Coast. This work presents a new Performance-based Atmospheric River Risk Analysis (PARRA) framework that adapts existing concepts from probabilistic risk analysis and performance-based engineering for application in the context of AR-driven fluvial flooding. The PARRA framework is a chain of physically based models that link the atmospheric forcings, hydrologic impacts, and economic consequences of AR-driven fluvial flood risk together at consistent “pinch point” variables. Organizing around these pinch points makes the framework modular, in that models between pinch points can be updated without affecting the rest of the model chain, and it produces a probabilistic result that quantifies the uncertainty in the underlying system states. The PARRA framework can produce results beyond analyses of individual scenario events and can look towards prospective assessment of events or system changes that have not been seen in the historic record. The utility of the PARRA framework is demonstrated through a series of analyses in Sonoma County, California. Evaluation of a February 2019 case study AR event shows that the individual component models produce simulated distributions that capture the observed precipitation, streamflow, inundation, and damage. The component models are then run in sequence to generate a first-of-its-kind AR flood loss exceedance curve for Sonoma County. The prospective capabilities of the PARRA framework are presented through the evaluation of a hypothetical mitigation action. It was found elevating 150 homes, selected based on their proximity to the Russian River, was able to reduce the average annual loss by half. The loss results from the mitigated building portfolio are compared against the original case. While expected benefits were minimal for the smallest events, the larger, more damaging ARs were expected to see loss reductions of approximately $50 million per event. These results indicate the potential of the PARRA framework for examining other changes to flood risk at the community level, including future changes to the hazard, through climate change; exposure, through development; and/or vulnerability, through flood mitigation investments.

Optimization of corn commodity Warehouse Receipt System (WRS) in South Sulawesi based on system dynamics

The purpose of this research is to study various factors that influence farmers in using the warehouse receipt system (WRS) and to apply the warehouse receipt system policy scenario in South Sulawesi. The method used is a dynamic system. The simulation results of the actual model type are that the income obtained from the actual (existing) model using WRS is higher than the direct income (selling corn directly) without entering the warehouse (WRS), as well as real income (where 100% of the corn that is produced) entered the warehouse immediately sold at the time without any delay in selling). The ideal type of warehouse receipt system shows the result that there is a difference in income (lost profit/benefit loss) if it does not optimize the existence of the warehouse, in other words, the average annual loss of income is 113.5 billion. The model shows that by delaying the sale, the profit difference (difference in income) is obtained from 38.35 billion to 189.77 billion or an average of 113.5 billion per year. The scenario model was developed with the consideration of optimizing the ideal model, namely optimizing the difference in income obtained from selling delays of 30% with a strategy of increasing agricultural productivity through increasing farmer productivity, which can be done in various ways such as training, socialization, education, institutional Warehouse receipt systems must carry out changes to increase productivity and performance in the field, build strong stakeholder support between local and central government

Impacts on catastrophe risk assessments from multi-segment and multi-fault ruptures in the UCERF3 model

The Uniform California Earthquake Rupture Forecast Version 3 (UCERF3) relaxes fault segmentation, allowing multi-segment and multi-fault ruptures through fault-to-fault “jumps,” with lengths up to ∼1200 km along the San Andreas Fault. Local faults are also highly interconnected, including ruptures on the order of hundreds of kilometers. These prescribed long ruptures did not exist in older models. Longer ruptures produce larger aggregate loss estimates for geographically dispersed assets (portfolios) due to the wider areas that are affected by strong ground shaking. In this study, we model probabilistic earthquake losses of a hypothetical state-wide building portfolio in California. We develop risk deaggregation methods to identify multi-segment and multi-fault ruptures that contribute significantly to high portfolio-wide risks. Three risk measures that are commonly used in risk management decisions are examined: Average Annual Loss (AAL), Return Period Loss (RPLα), and Tail Conditional Expectation (TCEα), for an annual exceedance probability “α,” or corresponding return period “1/α.” Our results show that while the super long ruptures (>500 km) contribute modestly (∼7%) to the portfolio AAL estimate, they contribute more significantly to portfolio catastrophe risk estimates. Specifically, at a 250 year return period, these long ruptures contribute about 26% and 32% to RPL250 and TCE250 estimates, respectively. At a 500-year return period, the corresponding contributions reach about 35% and 39%. Ruptures that connect complex fault systems are also found to be highly influential to estimated portfolio risks. At a 500-year return period, a mere six rupture groups contribute nearly 70% to the RPL500 estimate. Due to the importance of the UCERF3 model to many risk management and public policy decisions, a critical examination of the limit and uncertainty of fault connectivity and rupture lengths of future earthquakes, as well as their impacts on catastrophe risk assessments, is warranted in future model updates.

Pathways to sustaining tuna-dependent Pacific Island economies during climate change

Climate-driven redistribution of tuna threatens to disrupt the economies of Pacific Small Island Developing States (SIDS) and sustainable management of the world’s largest tuna fishery. Here we show that by 2050, under a high greenhouse gas emissions scenario (RCP 8.5), the total biomass of three tuna species in the waters of ten Pacific SIDS could decline by an average of 13% (range = −5% to −20%) due to a greater proportion of fish occurring in the high seas. The potential implications for Pacific Island economies in 2050 include an average decline in purse-seine catch of 20% (range = −10% to −30%), an average annual loss in regional tuna-fishing access fees of US$90 million (range = −US$40 million to –US$140 million) and reductions in government revenue of up to 13% (range = −8% to −17%) for individual Pacific SIDS. Redistribution of tuna under a lower-emissions scenario (RCP 4.5) is projected to reduce the purse-seine catch from the waters of Pacific SIDS by an average of only 3% (range = −12% to +9%), indicating that even greater reductions in greenhouse gas emissions, in line with the Paris Agreement, would provide a pathway to sustainability for tuna-dependent Pacific Island economies. An additional pathway involves Pacific SIDS negotiating within the regional fisheries management organization to maintain the present-day benefits they receive from tuna, regardless of the effects of climate change on the distribution of the fish.

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

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.

Humus condition under different systems of basic cultivation of dark gray forest soil

Studies, were conducted in a stationary experiment between 1988 and 2018 on dark gray forest heavy loam soil in Scientific Research Institute of Agriculture for Northern Trans-Ural Region - Branch of Federal State Institutions Federal Research Centre Tyumen Scientific Centre of Siberian Branch of the Russian Academy of Sciences. The aim of the study is to determine the effect of long-term (30 years) impact of different systems of basic cultivation of dark gray forest soils in the cultivation of grain crops on the humus content. Observations were made according to generally accepted methods during 6 rotations of grain and fallow crop rotation: bare fallow, winter rye, spring wheat, spring vetch, spring barley, unfolded in time and space. The impact of the combined system of tillage with alternation of plowing and no-tillage at 20-22 cm during 6 rotations of a 5-pole grain and steam crop rotation (30 years), increased the humus content in the 0-40 cm layer of dark gray forest soil compared with the initial content by 0.42%. The systems of main tillage - differentiated, without sowing, and mouldboard provided in general a relatively favorable dynamics of the humus state of the soil. The content of humus in the 0-40 cm layer of soil by differentiated and unswept systems during the study period remained close to the initial condition. По отвальной системе содержание гумуса снижалось на 0,22% или в среднем 0,37т/га в год. The greatest loss of humus in the 0-40 cm layer of soil by 0.80% in relation to the initial was the impact of surface treatment with annual discing BDT-2,5 (heavy disc harrows) on 10-12 cm or an average annual loss of 1.33 t / ha.

Energy and Exergy Assessment of S-CO2 Brayton Cycle Coupled with a Solar Tower System

In this research, we performed energy and exergy assessments of a solar driven power plant. Supercritical carbon dioxide (S-CO2) Brayton cycle is used for the conversion of heat to work. The plant runs on solar energy from 8 a.m. to 4 p.m. and to account for the fluctuations in the solar energy, the plant is equipped with an auxiliary heater operating on hot combustion gases from the combustion chamber. The capital city of Saudi Arabia (Riyadh) is chosen in this study and the solar insolation levels for this location are calculated using the ASHRAE clear-sky model. The solar collector (central receiver) receives solar energy reflected by the heliostats; therefore, a radially staggered heliostat field is generated for this purpose. A suite of code is developed to calculate various parameters of the heliostat field, such as optical efficiencies, intercept factors, attenuation factors and heliostat characteristic angles. S-CO2 Brayton cycle is simulated in commercial software, Aspen HYSYS V9 (Aspen Technology, Inc., Bedford, MA, USA). The cycle is mainly powered by solar energy but assisted by an auxiliary heater to maintain a constant net power input of 80 MW to the cycle. The heliostat field generated, composed of 1207 rows, provides 475 watts per unit heliostat’s area to the central receiver. Heat losses from the central receiver due to natural convection and radiation are significant, with an average annual loss of 10 percent in the heat absorbed by the receiver. Heat collection rate at the central receiver reveals that the maximum support of auxiliary heat is needed in December, at nearly 13% of the net input energy. Exergy analysis shows that the highest exergy loss takes place in the heliostat field that is nearly 42.5% of incident solar exergy.