Dealing with flood hazard and risk requires approaches rooted in both natural and social sciences, which provided the nexus for the ongoing debate on socio-hydrology. Various combinations of non-structural and structural flood risk reduction options are available to communities. Focusing on flood risk and the information associated with it, developing risk management plans is required but often overlooks public perception of a threat. The perception of risk varies in many different ways, especially between the authorities and the affected public. It is because of this disconnection that many risk management plans concerning floods have failed in the past. This paper examines the private adaptation capacity and willingness with respect to flooding in two different catchments in Greece prone to multiple flood events during the last 20 years. Two studies (East Attica and Evros) were carried out, comprised of a survey questionnaire of 155 and 157 individuals, from a peri-urban (East Attica) and a rural (Evros) area, respectively, and they focused on those vulnerable to periodic (rural area) and flash floods (peri-urban area). Based on the comparisons drawn from these responses, and identifying key issues to be addressed when flood risk management plans are implemented, improvements are being recommended for the social dimension surrounding such implementation. As such, the paper contributes to the ongoing discussion on human–environment interaction in socio-hydrology.

Many West African farmers are struggling to cope with changing weather and climatic conditions. This situation limits farmers’ ability to make optimal decisions for food and income security. Developing more useful and accessible weather and climate information services (WCIS) can help small-scale farmers improve their adaptive capacity. The literature suggests that such WCIS can be achieved if forecast information is produced jointly by farmers and scientists. To test this hypothesis and derive design requirements for effective WCIS, we evaluated the outcomes of an experimental coproduction of weather forecasts in Ada, Ghana. The experiment involved a user-driven design and testing of information and communications technology (ICT)-based digital (smartphones and apps) and rainfall monitoring tools by 22 farmers. They collected data and received weather forecasts during the 2018/2019 study period. The results showed a positive evaluation of the intervention, expressed by the level of engagement, the increase in usability of the tools and understanding of forecast uncertainty, outreach capacity with other farmers, and improved daily farming decisions. The success of the intervention was attributed to the iterative design process, as well as the training, monitoring, and technical support provided. We conclude that the application of modern technology in a coproduction process with targeted training and monitoring can improve smallholder farmers’ access to and use of weather and climate forecast information.

The MIKE SHE model is able to simulate the entire stream flow which includes direct and basic flow. Many models either do not simulate or use simplistic methods to determine the basic flow. The MIKE SHE model takes into account many hydrological data. Since this study was directed towards the simulation of surface runoff and infiltration into saturated and unsaturated zone, the MIKE SHE is an appropriate model for reliable conclusions. In the current research, the MIKE SHE model was used to simulate runoff in the area of Sperchios River basin. Meteorological data from eight rainfall stations within the Sperchios River basin were used as inputs. Vegetation as well as geological data was used to perform the calibration and validation of the physical processes of the model. Additionally, ArcGIS program was used. The results indicated that the model was able to simulate the surface runoff satisfactorily, representing all the hydrological data adequately. Some minor differentiations appeared which can be eliminated with the appropriate adjustments that can be decided by the researcher′s experience.

The agriculture sector is vital to the world's economy and weather and climate are key drivers that affect the productivity and profitability of agricultural systems. At the same time, weather-related risks pose significant challenges to farmers' livelihoods. Although scientific weather forecast (SFK) is available, many farmers, especially in the Global South, have limited access to this information, and they rely on local forecast knowledge (LFK) to make farming decisions. Many studies also recognize the value of combining both forecasting systems; yet, unlike SFK which is readily available, indicators for LFK needs to be collected first. Therefore, this study identifies and documents the spatial distribution of LFK use for agriculture across the globe through a systematic literature review. Results show that a high number of LFK regions with a total of around 1350 local environmental indicators were found in Africa and Asia and less in South and North America. The low usability of scientific weather forecasts is perceived as the main reason farmers use LFK instead of SFK, yet the accessibility of LFK both for scientists and users, needs to be improved. Indicators based on animals and meteorology appeared to be more frequently used for weather predictions than plant- and astronomy-based indicators. Digitalizing the LFK inventory and collecting more detailed information about the regions where LFK was identified could promote and foster research on integrating scientific and local forecasting systems. This study will draw attention to the importance of LFK in weather forecasting, maintain this knowledge and enhance it.