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Hazard assessment on drought disaster is of great significance for improving drought risk management. Due to the complexity and uncertainty of the drought disaster, the index values have some grey multi-source heterogeneous characteristics. The purpose of this paper is to construct a grey projection incidence model (GPIM) to evaluate the hazard of the drought disaster characterised by the grey heterogeneity information.

First, the index system of the drought hazard risk is established based on the formation mechanism of the drought disaster. Then, the GPIM for the heterogeneous panel data is constructed to assess drought hazard of five cities in Henan Province. Subsequently, based on the assessment results, the grey clustering model is employed for the regional division.

The findings demonstrate that five cities in central Henan Province are divided into three categories, which correspond to three different risk grades, respectively. With respect to different drought risk areas, corresponding countermeasures and suggestions are proposed.

This paper provides a practical and effective new method for the hazard assessment on drought disaster. Meanwhile, these countermeasures and suggestions can help policy makers to improve the efficiency of drought resistance work and reduce the losses caused by drought disasters in Henan Province.

This paper proposes a new GPIM which resolves the assessment problems of the uncertain systems with grey heterogeneous information, such as real numbers, interval grey numbers and three-parameter interval grey numbers. It not only expands the application scope of the grey incidence model, but also enriches the research of panel data.

The purpose of this paper is to establish a two-stage grey cloud clustering model to assess the drought risk level of 18 prefecture-level cities in Henan Province.

The clustering process is divided into two stages. In the first stage, grey cloud clustering coefficient vectors are obtained by grey cloud clustering. In the second stage, with the help of the weight kernel clustering function, the general representation of the weight vector group of kernel clustering is given. And a new coefficient vector of kernel clustering that integrates the support factors of the adjacent components was obtained in this stage. The entropy resolution coefficient of grey cloud clustering coefficient vector is set as the demarcation line of the two stages, and a two-stage grey cloud clustering model, which combines grey and randomness, is proposed.

This paper demonstrates that 18 cities in Henan Province are divided into five categories, which are in accordance with five drought hazard levels. And the rationality and validity of this model is illustrated by comparing with other methods.

This paper provides a practical and effective new method for drought risk assessment and, then, provides theoretical support for the government and production departments to master drought information and formulate disaster prevention and mitigation measures.

The model in this paper not only solves the problem that the result and the rule of individual subjective judgment are always inconsistent owing to not fully considering the randomness of the possibility function, but also solves the problem that it’s difficult to ascertain the attribution of decision objects, when several components of grey clustering coefficient vector tend to be balanced. It provides a new idea for the development of the grey clustering model. The rationality and validity of the model are illustrated by taking 18 cities in Henan Province as examples.

The purpose of this paper is to apply the concept of “Interconnected Geoscience” to a disaster and risk reduction (DRR) case study at SECMOL College, near Leh, Ladakh, N. India. Interconnected geoscience is a model that advocates holistic approaches to geoscience for development. This paper reports research/practical work with Ladakhi students/staff, undertaking community-oriented DRR exercises in hazard awareness, DRR themed village/college mapping, vulnerability assessments and DRR management scenario development. The geoscientific hazard analysis work is published within a separate sister paper, with results feeding into this work. This work addresses aspects of, and contributes to, the DRR research(science)-policy-interface conversation.

Interconnected geoscience methodologies for DRR here are: the application of geoscience for hazard causality, spatial distribution, frequency and impact assessment, for earthquakes, floods and landslides, within the SECMOL area; the generation of community-developed DRR products and services of use to a range of end-users; the development of a contextual geoscience approach, informed by social-developmental-issues; and the active participation of SECMOL students/teachers and consequent integration of local world-views and wisdom within DRR research. Initial DRR awareness levels of students were assessed with respect to earthquakes/floods/landslides/droughts. Following hazard teaching sessions, students engaged in a range of DRR exercises, and produced DRR themed maps, data, tables and documented conversations of relevance to DRR management.

Students levels of hazard awareness were variable, generally low for low-frequency hazards (e.g. earthquakes) and higher for hazards such as floods/landslides which either are within recent memory, or have higher frequencies. The 2010 Ladakhi flood disaster has elevated aspects of flood-hazard knowledge. Landslides and drought hazards were moderately well understood. Spatial awareness was identified as a strength. The application of an interconnected geoscience approach immersed within a student+staff college community, proved to be effective, and can rapidly assess/build upon awareness levels and develop analytical tools for the further understanding of DRR management. This approach can assist Ladakhi regional DRR management in increasing the use of regional capability/resources, and reducing the need for external inputs.

A series of recommendations for the DRR geoscience/research-policy-practice area include: adopting an “interconnected geoscience” approach to DRR research, involving scientific inputs to DRR; using and developing local capability and resources for Ladakhi DRR policy and practice; using/further-developing DRR exercises presented in this paper, to integrate science with communities, and further-empower communities; taking account of the findings that hazard awareness is variable, and weak, for potentially catastrophic hazards, such as earthquakes, when designing policy and practice for raising DRR community awareness; ensuring that local values/world views/wisdom inform all DRR research, and encouraging external “experts” to carefully consider these aspects within Ladakh-based DRR work; and further-developing DRR networks across Ladakh that include pockets of expertise such as SECMOL.

The term “interconnected geoscience” is highly novel, further developing thinking within the research/science-policy-practice interface. This is the first time an exercise such as this has been undertaken in the Ladakh Himalaya.

Chronicles and literary records show that Sri Lanka has been affected by various natural disasters from time to time in the past, as it is now. The sea surge/coastal flooding during King Kelani Tissa's reign, around 190 BC could have been a tsunami. A severe drought and famine known as Beminitiya Seya occurred during the intermittent reign of the Brahmin King Thiya (Tissa) and King Valagamba (89–77 BC). There are also references to droughts prior to this, namely, Akkakayika Seya (it is said that about 24,000 monks died and others left the country, and some of those who remained survived by eating kara leaves). Subsequently, this led King Valagamba to undertake to record the sayings of the Buddha (Tripitaka) for posterity. Duttagamini (161–137 BC), Ekanalika Seya during the reign of King Kunchanaga (187–189 AD) and others, none of which had been as severe as Beminitiya Seya. Apart from these extreme hazard events other incidents have been reported, including the flooding incidents during the British rule (National Disaster Management Plan, 2007).

Climate change, deforestation and hydropower dams are contributing to environmental change in the Lower Mekong River region, the combined effects of which are felt by many rural Cambodians. How people perceive and manage the effects of environmental change will influence future adaptation strategies. The objective of this research was to investigate whether the use of a low-cost, explicitly spatial method (participatory mapping) can help identify locally relevant opportunities and challenges to climate change adaptation in small, flood-prone communities. Four villages along the banks of the Mekong River in Kratie Province, Cambodia, were the subject of this research. To identify perceived environmental hazards and adaptive responses, eight workshops were conducted using focus-group interviews and participatory mapping. The communities’ responses highlight the evolving nature of environmental hazards, as droughts increase in perceived importance while the patterns of wet season flooding were also perceived to be changing. The attribution of the drivers of these hazards was strongly skewed towards local factors such as deforestation and less towards regional or global drivers affecting the hydrology of the Mekong and climate patterns. Combining participatory mapping with focus-group interviews allowed a greater depth of understanding of the vulnerabilities and opportunities available to communities than reliance on a single qualitative method. The study highlights the potential for a bottom-up transfer of information to strengthen existing climate change policies and tailor adaptation plans to local conditions.

The recently released fifth IPCC report indicates a high agreement among global actors on the need to integrate climate change adaptation (CCA) and disaster risk reduction (DRR). However, there remains little local level evidence on how DRR and CCA could be linked, the sorts of adjustments that are required for the two concepts to be integrated and the challenges ahead. This paper aims to provide an empirical insight on the possible links and departures between DRR and CCA.

The study used a qualitative case study approach to excavate lessons from an existing DRR intervention for CCA using a local-level adaptive capacity assessment framework as a normative criteria. Data was collected both from primary and secondary sources. The primary data collection involved the use of participatory rural appraisal techniques with village communities in Chifra District, Afar Regional State, Ethiopia.

The findings showed that the DRR interventions studied addressed parts of the elements of adaptive capacity at the local level. The findings also showed the limitation of the DRR intervention, which could be attributed to both the nature of the DRR interventions in general and implementation problems of the case study intervention in particular. The limitations show cases where full integration of DRR with CCA could be challenging.

The paper argues why the two approaches may not be integrated fully and also shows the need to focus on the design of DRR interventions in achieving both short-term (reducing disaster risks) and long-term objectives (enhancing adaptive capacity).

Novel micro‐insurance schemes are emerging to help the poor better deal with droughts and other disasters. Climate change is projected to increase the intensity and frequency of disasters and is already adding stress to actual and potential clients of these schemes. As well, insurers and reinsurers are increasingly getting worried about increasing claim burdens and the robustness of their pricing given changing risks. The purpose of this paper is to review and suggest ways to methodologically tackle the challenges regarding the assessment of drought risk and the viability of index‐based insurance arrangements in the light of changing risks and climate change.

Based on novel modeling approaches, the authors take supply as well as demand side perspectives by combining risk analysis with regional climate projections and linking this to household livelihood modeling and insurance pricing. Two important examples in Malawi and India are discussed, where such schemes have been or are about to be implemented.

The authors find that indeed micro‐insurance instruments may help low‐income farming households better manage drought risk by smoothing livelihoods and reducing debt, thus avoiding poverty traps. Yet, also many obstacles to optimal design, viability and affordability of these schemes, are encountered. One of those is climate change and the authors find that changing drought risk under climate change would pose a threat to the viability of micro‐insurance, as well as the livelihoods of people requesting such contracts.

The findings and suggestions may corroborate the case for donor support for existing or emerging insurance arrangements helping the poor better cope with climate variability and change. Furthermore, a closer linkage between climate and global change models with insurance and risk management models should be established in the future, which could be beneficial for both sides.

A core challenge of assessing regional agricultural drought vulnerability (RADV) is to reveal what vulnerability factors, under which kinds of synergistic combinations and at what strengths, will lead to higher vulnerability: namely, the influence patterns of RADV.

A two-phased grey rough combined model is proposed to identify influence patterns of RADV from a new perspective of learning and mining historical cases. The grey entropy weight clustering with double base points is proposed to assess degrees of RADV. The simplest decision rules that reflect the complex synergistic relationships between RADV and its influencing factors are extracted using the rough set approach.

The results exemplified by China's Henan Province in the years 2008–2016 show higher degrees of RADV in the north and west regions of the province, in comparison with the south and east. In the patterns with higher RADV, the higher proportion of agricultural population appears in all decision rules as a core feature. A smaller quantity of water resources per unit of cultivated land area and a lower adaptive capacity, involving levels of irrigation technology and economic development, present a significant synergistic influence relationship that distinguishes the features of higher vulnerability from those of the lower.

The proposed grey rough combined model not only evaluates temporal dynamics and spatial differences of RADV but also extracts the decision rules between RADV and its influencing factors. The identified influence patterns inspire managerial implications for preventing and reducing agricultural drought through its historical evolution and formation mechanism.

The chapter tries to trace the development of concept of urban ecosystem as a problem-solving approach for urban problems, including the unwarranted problems caused by climate change. Urban management has increasingly shifted from infrastructure-based to a more regional-based approach. There has been a shift in the domain of urban ecosystem as well, from the established urbanized area to the aggregation of urban and surrounding rural area. Also, urban-rural linkages are given more attention in resource management in urban areas, thereby reducing the overall risk due to climate change. The chapter provides examples and challenges of urban ecosystem management from across the world.

Natural hazards such as floods, wildfires and droughts disrupt communities, their economies and environments, and cost millions every year. The existing literature on hazard mitigation shows that community resilience is best achieved when mitigation strategies are integrated with land use and comprehensive planning. The purpose of this paper is to evaluate the strengths and weaknesses of hazard mitigation in local comprehensive plans.

The analysis uses a new plan evaluation protocol that integrates flood, wildfire and drought mitigation to evaluate the plans of the six largest and fastest growing counties in Arizona.

The study finds that counties do not plan equally well for all hazards, that they tend to plan better for droughts than wildfires and floods, and indicates the need to improve hazard information in plans to support the adoption of mitigation goals, objectives and strategies.

The research is based on a small sample of comprehensive plans. It focuses on the content of plans rather than the causes that may explain this content or the implementation of the strategies included in the plans. Future research will thus need to analyze larger numbers of plans to identify the determinants of the degree to which comprehensive plans integrate hazard mitigation; and evaluate whether strategies advanced in plans are integrated with other planning documents and implemented.

The paper makes recommendations to improve the plans evaluated and to guide planners as they develop or revise comprehensive plans in other jurisdictions subject to natural hazards.

The key methodological contribution of the paper is the new plan evaluation protocol designed to assess the wildfire, drought and flood mitigation provisions in comprehensive plans.