What is the evidence linking financial assistance for drought-affected agriculture and resilience in tropical Asia? a systematic review

Agriculture is sensitive to drought and associated social, environmental and economic impacts. Finance-based interventions aim to support farmers affected by drought; however, the extent to which such tools encourage resilience to this natural hazard is unclear. This paper systematically reviews evidence on links between financial interventions to mitigate drought-related impacts and adaptation towards longer-term resilience. We focus on tropical Asia where agriculture contributes significantly to national economies and is a primary source of livelihood in a region subject to high climate variability and episodic drought. Guided by Population, Intervention, Comparator and Outcome criteria, we identify and review 43 regionally specific articles that describe a range of financial interventions. Through thematic synthesis, we document the interventions’ associations with micro-level and macro-level outcomes. The results reveal how some interventions helped sustain household incomes and crop yield (e.g. through farm investments that increased productivity) through drought, whilst others encouraged adaptive behaviours. At a macro-level, there were challenges associated with government budgets and scheme administration, with the longevity of many schemes difficult to sustain. From fragmented evidence, this review reasons that there can be challenging policy trade-offs for institutions between supporting livelihoods and economic growth whilst also protecting the environment—highlighting the interdependence of systems’ resilience and variability in actors’ capacity to adapt. Low-regret interventions that integrate existing community adaptive practices, engage with farmers’ needs and prioritise extension support may encourage more desirable counteractions to drought; however, further research is needed to establish the role of such interventions.Natural Environment Research Council (NERC):NE/S003223/1. Global Challenges Research Fund QR 2020/2

Which factors determine adaptation to drought amongst farmers in Northern Thailand? Investigating farmers’ appraisals of risk and adaptation and their exposure to drought information communications as determinants of their adaptive responses

Drought communications constitute an important source of learning about climate risks and responses that can assist adaptation decision-making amongst those whose livelihoods are threatened by drought. This paper applies Protection Motivation Theory to explore associations between drought communications and attitudes towards drought risk and adaptation amongst farmers in Northern Thailand. The analysis reveals links between drought communications, farmers’ adaptation appraisal, and their adaptation decisions, whilst links with risk appraisal are minimal. The results highlight positive feedbacks between adaptation experience and appraisal and reveal a weak negative relationship between risk appraisal and adaptation appraisal. The findings imply benefits to framing drought communications in terms of the efficacy and attainability of suitable adaptations, rather than simply highlighting drought risks or providing drought warnings, to best enable farmers to build drought resilience

The contribution of a catchment-scale advice network to successful agricultural drought adaptation in Northern Thailand

The intensification of drought affects agricultural production, leading to economic losses, environmental degradation and social impacts. To move toward more resilient system configurations requires understanding the processes that shape farmers' adaptation amidst complex institutional contexts. Social networks are an important part of collective action for supporting adaptive capacity and there are continuing calls to strengthen network connectivity for agricultural governance under the impacts of climate change. Through a survey of 176 farmers in northern Thailand, we explore the extent to which the characteristics of information shared in a catchment advice network are associated with adaptations. Statistical analyses reveal the perceived efficacy of communications as well as farmers’ relative closeness in the advice network to be positively associated with adaptation to drought. We identify a capacity for local actors to bridge information bottlenecks in the network and opportunities for institutions to enhance their dissemination of information to reach less networked farmers. We find that not all adaptations are perceived as effective against future drought and infer opportunities to support engagement with extension services, encourage the sharing of local knowledge and experience and devise policy and interventions to strengthen advice networks for more resilient agricultural systems

Indicator-to-impact links to help improve agricultural drought preparedness in Thailand

Droughts in Thailand are becoming more severe due to climate change. Developing a reliable Drought Monitoring and Early Warning System (DMEWS) is essential to strengthen a country&rsquo;s resilience to droughts. However, for a DMEWS to be valuable, the drought indicators it provides stakeholders must have relevance to tangible impacts on the ground. Here, we analyse drought indicator-to-impact relationships in Thailand, using a combination of correlation analysis and machine learning techniques (random forest). In the correlation analysis, we study the link between meteorological drought indicators and high-resolution remote sensing vegetation indices used as proxies for crop-yield and forest-growth impacts. Our analysis shows that this link varies depending on land use, season, and region. The random forest models built to estimate regional crop productivity allow a more in-depth analysis of the crop-/region-specific importance of different drought indicators. The results highlight seasonal patterns of drought vulnerability for individual crops, usually linked to their growing season, although the effects are somewhat attenuated in irrigated regions. Integration of the approaches provides new detailed knowledge of crop-/region-specific indicator-to-impact links, which can form the basis of targeted mitigation actions in an improved DMEWS in Thailand, and could be applied in other parts of Southeast Asia and beyond.</p

Wave Energy Potential and Simulation on the Andaman Sea Coast of Thailand

Ocean wave energy is an interesting renewable energy because it will never run out and can be available all the time. If the wave energy is to be used, then the feasibility study of localized wave potential has to be studied. This goal is to study the potential of waves in the Andaman Sea. The Simulating WAves Nearshore (SWAN) model was used to calculate the significant wave heights, which were validated with the measurement data of the Jason-2 satellite. The coastal area of Phuket and Phang Nga provinces are suitable locations for studying wave energy converters because they have high significant wave height. Moreover, this study used computational fluid dynamics (CFD) for the simulation of wave behavior in accordance with wave parameters from the SWAN model. The wave height simulated from CFD was validated with linear wave theory. The results found that it was in good agreement with linear wave theory. It can be applied for a simulation of the wave energy converter

Performance of Global Climate Model (GCMs) for Wind Data Analysis

The surface wind speed is an important climate variable for study of ocean wave energy and coastal erosion. The wind speed and wave height variations are caused by global warming. In the future, climate change impacts on changes of direction and wind speed which affect on wave height and wave period. The global climate model (GCMs) were developed by various institutions so each GCM has different GCM output. Then, the aim of this study is to evaluation the performance of GCMs for wind speed analysis in the area of Gulf of Thailand and Andaman Sea. In this study, the daily wind speed data was analyzed with a total of 15 GCMs and daily wind speed data of NCEP-NCAR was used as observation data to compare with wind speed data from GCMs over the period 1986-2005 (20 years). Moreover, the wind speed data was evaluated by efficiency coefficient which are root mean square error (RMSE) and mean absolute error (MAE). It was found tht MRI-CGCM3, GFDL-ESM2M, IPSL-CM5A-LR, and IPSL-CM5A-MR are consistent with the most of observation data from NCEP-NCAR