Vulnerability and its discontents: the past,present, and future of climate change vulnerability research

The agri-food sector must adapt to changes in climate variability, while also helping to mitigate climate change. Measures termed ‘triple-win’ mitigate and adapt to climate change, while also improving soil health, thereby increasing yields. These measures might appear to be the easiest to implement, but in practice, barriers prevent full realisation. This study aims to move beyond previous research efforts that identify and categorise barriers by (i) revealing hidden barriers, (ii) understanding the interactions between barriers and (iii) exploring ways to address barriers. A case study focusing on crop rotation as a triple-win strategy in Ukraine demonstrates how a participant-driven iterative research approach can achieve these objectives. During semi-structured interviews with farmers and stakeholders, crop rotation emerged as an area of considerable dissensus with stakeholders commonly citing the greedy behaviour of producers as the problem. Further discussion indicated that the political economy of Ukraine caused financial constraints for producers and Q methodology allowed for additional clarity on the opposing views of crop rotation. Three factors emerged: producer insecurity, national insecurity and business insecurity. These three perspectives reveal contrasting priorities with producer insecurity and business insecurity concerned with the conditions under which producers must operate, while national insecurity has a focus on improving agricultural production to benefit the nation. Consensus statements across all factors could provide first steps to addressing barriers and an opportunity to open discussions amongst stakeholders. Finally, barriers arising from political processes demonstrate that climate policy needs to be integrated with other sector-specific policy decisions.     

Multiple prediction using the homeomorphic-imaging technique

A new method for predicting different kinds of multiples and peg-leg reflections in unstacked seismic data is discussed. The basis for this method is the fact that kinematic properties of multiples can be represented as a combination of kinematic properties of primary reflections. The prediction is made using a two-step process. In the first step, the values for the angle of emergence and radius of curvature of the wavefront for primary reflections from ‘multiple-generating’ interfaces are obtained. These parameters are estimated directly from unstacked data for every source point using the homeomorphic-imaging technique. The second step consists of prediction of multiples from primary reflections that satisfy a so-called ‘multiple condition’. This condition is the equality of the absolute values of the angles of emergence calculated from the first step. This method is effective even in complex media and information on the subsurface geology is not required. The parameters are estimated directly from the unstacked data and do not require any computational efforts such as in wavefield extrapolation of data.     

Shallow velocity–depth model imaging by refraction tomography1

A tomographic imaging technique combined with coherence inversion is proposed for constructing a near-surface model from refraction events. A model obtained from coherence inversion serves as a good background model for the tomographic reconstruction. A simultaneous iterative reconstruction technique (SIRT) algorithm was used for this purpose. This is a simple algorithm and can be easily adapted to irregular acquisition geometry and limited angular aperture. Using synthetic data it was shown that the proposed procedure can be used for determination of local velocity anomalies in a shallow subsurface. The technique was also tested on a real data set.