<p>Droughts are known to be one of the most damaging and costly natural hazards as a result of their large spatial scale, creeping nature and long duration. They have widespread primary and secondary impacts, and as such, proactive drought management is crucial to mitigate those impacts. In order to do so, it is crucial to understand the drought risk in terms of the characteristics of the drought hazard, who or what is exposed to the drought hazard, and who (or what) is vulnerable to the effects of drought. Drought mitigation, adaptation and management was adopted as one of five strategic objectives under the United Nations Convention to Combat Desertification (UNNCD) 2018-2030 Strategic Framework. Country Parties to the UNCCD agreed a monitoring framework and a range of indicators in order to track progress towards this objective.</p><p>Here we present new guidance created to help Parties to the UNCCD report on their progress towards Strategic Objective 3 ‘To mitigate, adapt to, and manage the effects of drought in order to enhance resilience of vulnerable populations and ecosystems’. Progress is monitored using three indicators, characterising the three fundamental components of risk: drought hazard, exposure to drought and vulnerability to drought. The three indicators, as agreed by Parties to the UNCCD, are:</p><ul><li>Trends in the proportion of land under drought over the total land area,</li> <li>Trends in the proportion of the total population exposed to drought, and</li> <li>Trends in the degree of drought vulnerability.</li> </ul><p>Acknowledging the need for global applicability, the methods recommended to calculate these three indicators balance state-of-the-art science with relative simplicity, whilst also meeting the requirements set out in official UNCCD Decisions, guidelines of the World Meteorological Organization, and where possible utilising datasets used for other reporting activities (e.g. the Sustainable Development Goals).</p><p>The recommended methods for each indicator are illustrated using contrasting case studies from the UK and Thailand, utilising the recommended globally available datasets to calculate the three indicators listed above. In-country data are also used, where available, to calculate the indicators, highlighting the benefits of increased spatial resolution, and/or sensitivity to assessing changes in drought hazard, exposure or vulnerability over time. Finally, opportunities for the future of national reporting on drought risk are discussed.</p>

Abstract. 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’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.

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<p>Thailand has already been experiencing an increase in severity and duration of its droughts as a consequence of the changing climate. Developing a reliable drought monitoring and early warning system (DMEWS) is an integral part of strengthening a country’s resilience to droughts. However, for DMEWS to be useful for stakeholders, the indicators they monitor should be translatable to potential drought impacts on the ground and, ideally, inform mitigating actions. Here, we analyse these drought indicator-to-impact relationships in Thailand, using a novel combination of correlation analysis and random forest modelling. In the correlation analysis, we study the link between meteorological drought indicators and high-resolution remote sensing vegetation indices used as proxies for general crop health and forest growth. Our analysis shows that these links vary greatly depending on land use (cropland vs. forest), season (wet vs. dry) and region (north vs. south). The random forest models built to estimate regional crop productivity provided a more in-depth analysis of the crop- and region-specific value of different drought indicators. The results highlighted seasonal patterns of drought vulnerability for individual crops, usually linked to their growing season, although the effect was somewhat masked in irrigated regions (North). This new high-resolution knowledge of crop- and region-specific indicator-to-impact links can be used as the basis of targeted mitigation actions in an improved DMEWS in Thailand. In addition, the framework developed here can be applied elsewhere in the Southeast Asia region, as well as other drought-vulnerable areas internationally, in particular those that are data sparse.  </p>

<p>Droughts are known to be one of the most damaging and costly natural hazards as a result of their large spatial scale, creeping nature and long duration. They have widespread primary and secondary impacts, and as such, proactive drought management is crucial to mitigate those impacts. In order to do so, it is crucial to understand the drought risk – i.e. the characteristics of the drought hazard, who or what is exposed to the drought hazard, and who (or what) is vulnerable to the effects of drought. Drought mitigation is one of five strategic objectives under the United Nations Convention to Combat Desertification (UNCCD) 2018-2030 Strategic Framework, under which a monitoring framework and a range of indicators was agreed by country Parties to the UNCCD.</p><p>Here we present new guidance created to help Parties to the UNCCD report on their progress towards Strategic Objective 3 ‘To mitigate, adapt to, and manage the effects of drought in order to enhance resilience of vulnerable populations and ecosystems’. Progress is monitored using three indicators, capturing the three fundamental components of risk: drought hazard, exposure to drought and vulnerability to drought. The three indicators, as agreed by Parties to the UNCCD, are:</p><ul><li>Trends in the proportion of land under drought over the total land area,</li> <li>Trends in the proportion of the total population exposed to drought, and</li> <li>Trends in the degree of drought vulnerability.</li> </ul><p>Acknowledging the need for global applicability, the methods recommended to calculate these three indicators balance state-of-the-art science with relative simplicity, whilst also meeting the requirements set out in official UNCCD Decisions, guidelines of the World Meteorological Organization, and where possible utilising datasets used for other reporting activities (e.g. the Sustainable Development Goals). The methods for each indicator are illustrated using contrasting case studies, highlighting the flexibility of the approaches recommended, as well as opportunities for the future of national reporting on drought risk.</p>