A considerable amount of the required information in risk and emergency management is geographical, but this information does not always reach the right actors at the right time, so how can geographical information be organised in such a way that it supports risk and emergency management more effectively? The answer requires a conceptualisation of risk and emergency management practices resulting in the network-centric concept, which implies that those involved in risk and emergency management are connected and that they have the capability to share and access information. The concept was made operational through the development of an information system and the exchange of geographical information within the system was facilitated by the use of peer-to-peer networking in combination with a client server network. On the application level, the information was presented in both map and text forms to support the exchange of information between actors. This way of organising geographical information and technology leads to improved information and communication, better situational awareness and faster decisionmaking.
MULTIFILE
Few studies have investigated staying intentions and house attachment of residents who are confronted with physical damage to their dwelling in a risk area. This paper examines whether and how homeowners who are confronted with human-induced risks and the consequences of gas extraction in the Dutch Groningen rural earthquake region are attached to their damaged dwellings and why they stay. A content analysis was performed on 92 published interviews with homeowners of damaged dwellings. Additionally, three semi-structured interviews were held with key journalists and a homeowner. The results show that the homeowners’ staying intentions are interrelated with their house attachment; moreover, their awareness of their house attachment arises precisely because of the damage. We identify five subdimensions of physical and social house attachment, related to family history, heritage, (agricultural) business, personal refurbishment, and cohabiting family members, which make homeowners want to stay. The family history is especially mentioned by mid-to-later life homeowners, while some younger homeowners emphasize social house attachment to their children.We conclude that a homeowner's decision to stay in a damaged dwelling is a continuous cycle of reconsideration and renegotiation, punctuated by potential new risks and damages influencing the house attachment and staying intentions. Based on the found dimensions of house attachment, policymakers in risk areas could apply different approaches to homeowners in case of damage repair, rebuilding, or relocation plans, as homeowners - even those with damaged dwellings - may prefer to stay.
In Eastern Africa, increasing climate variability and changing socioeconomic conditions are exacerbating the frequency and intensity of drought disasters. Droughts pose a severe threat to food security in this region, which is characterized by a large dependency on smallholder rain-fed agriculture and a low level of technological development in the food production systems. Future drought risk will be determined by the adaptation choices made by farmers, yet few drought risk models … incorporate adaptive behavior in the estimation of drought risk. Here, we present an innovative dynamic drought risk adaptation model, ADOPT, to evaluate the factors that influence adaptation decisions and the subsequent adoption of measures, and how this affects drought risk for agricultural production. ADOPT combines socio-hydrological and agent-based modeling approaches by coupling the FAO crop model AquacropOS with a behavioral model capable of simulating different adaptive behavioral theories. In this paper, we compare the protection motivation theory, which describes bounded rationality, with a business-as-usual and an economic rational adaptive behavior. The inclusion of these scenarios serves to evaluate and compare the effect of different assumptions about adaptive behavior on the evolution of drought risk over time. Applied to a semi-arid case in Kenya, ADOPT is parameterized using field data collected from 250 households in the Kitui region and discussions with local decision-makers. The results show that estimations of drought risk and the need for emergency food aid can be improved using an agent-based approach: we show that ignoring individual household characteristics leads to an underestimation of food-aid needs. Moreover, we show that the bounded rational scenario is better able to reflect historic food security, poverty levels, and crop yields. Thus, we demonstrate that the reality of complex human adaptation decisions can best be described assuming bounded rational adaptive behavior; furthermore, an agent-based approach and the choice of adaptation theory matter when quantifying risk and estimating emergency aid needs.
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Due to the existing pressure for a more rational use of the water, many public managers and industries have to re-think/adapt their processes towards a more circular approach. Such pressure is even more critical in the Rio Doce region, Minas Gerais, due to the large environmental accident occurred in 2015. Cenibra (pulp mill) is an example of such industries due to the fact that it is situated in the river basin and that it has a water demanding process. The current proposal is meant as an academic and engineering study to propose possible solutions to decrease the total water consumption of the mill and, thus, decrease the total stress on the Rio Doce basin. The work will be divided in three working packages, namely: (i) evaluation (modelling) of the mill process and water balance (ii) application and operation of a pilot scale wastewater treatment plant (iii) analysis of the impacts caused by the improvement of the process. The second work package will also be conducted (in parallel) with a lab scale setup in The Netherlands to allow fast adjustments and broaden evaluation of the setup/process performance. The actions will focus on reducing the mill total water consumption in 20%.
