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Abstract. Current drought monitoring and early warning systems use different indicators for monitoring drought conditions and apply different indicator thresholds and rules for assigning drought intensity classes or issue warnings or alerts. Nevertheless, there is little knowledge on the meaning of different hydro-meteorologic indicators for impact occurrence on the ground. To date, there have been very few attempts to systematically characterize the indicator–impact relationship owing to sparse and patchy data on drought impacts. The newly established European Drought Impact report Inventory (EDII) offers the possibility to investigate this linkage. The aim of this study was to explore the link between hydro-meteorologic indicators and drought impacts for the case study area Germany and thus to test the potential of qualitative impact data for evaluating the performance of drought indicators. As drought indicators two climatological drought indices – the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) – as well as streamflow and groundwater level percentiles were selected. Linkage was assessed though data visualization, extraction of indicator values concurrent with impact onset, and correlation analysis between monthly time series of indicator and impact data at the federal state level, and between spatial patterns for selected drought events. The analysis clearly revealed a significant moderate to strong correlation for some states and drought events allowing for an intercomparison of the performance of different drought indicators. Important findings were strongest correlation for intermediate accumulation periods of SPI and SPEI, a slightly better performance of SPEI versus SPI, and a similar performance of streamflow percentiles to SPI in many cases. Apart from these commonalities, the analysis also exposed differences among federal states and drought events, suggesting that the linkage is time variant and region specific to some degree. Concerning "thresholds" for drought impact onset, i.e. indicator values concurrent with past impact onsets, we found that no single "best" threshold value can be identified but impacts occur within a range of indicator values. Nevertheless, the median of the threshold distributions showed differences between northern/northeastern versus southern/southwestern federal states, and among drought events. While the findings strongly depend on data and may change with a growing number of EDII entries in the future, this study clearly demonstrates the feasibility of evaluating hydro-meteorologic variables with text-based impact reports and highlights the value of impact reporting as a tool for monitoring drought conditions.

Abstract
Weather index insurance is a popular means of mitigating agricultural risks. Drought is a significant cause of lost agricultural production, and so precipitation index–based plans are common. Simple "percent of normal" indices are often used because they are easy to calculate and communicate to policyholders. However, the ability of such indices to reflect production losses is limited, reducing the ability of insurance to efficiently mitigate risk. This is especially true in rangeland livestock production given the cumulative effects of rainfall and other factors on range production and the complex relationships between range and livestock weight gain, which is the rancher's main product and source of income. More sophisticated drought indices incorporate the complexities of drought into their design and would, in theory, serve as more appropriate payment triggers. This study uses a suite of drought indices to test correlation with production and the behavior of insurance based on those indices. Payout patterns based on each index were simulated within the actuarial framework of a precipitation-based insurance program aimed at livestock producers. Results were compared with the program's precipitation index, showing that drought indices have higher correlations with range production, a tendency to incentivize growing-season protection, more even geographic distributions of risk, reduced policyholder ability to seek higher payments through strategic coverage choices, and increased provider ability to adjust payment patterns to reduce the risk of nonpayment given loss.

Purpose– The purpose of this paper is to identify, analyse and document local traditional indicators used in drought forecasting in the Mzingwane Catchment and to assess the possibility of integrating traditional rainfall forecasting, using the local traditional indicators, with meteorological forecasting methods.Design/methodology/approach– Self-administered structured questionnaires were conducted on 101 respondents in four districts of the Mzingwane Catchment area, namely, Beitbridge, Mangwe, Esighodini and Mwenezi from February to August 2012. In addition, key informant interviews and focus group discussions were also used in data collection and the collected data were analysed for drought history and demographics; drought adaptation and the use of drought forecasting methods in the catchment using Statistical Package for Social Science.Findings– The paper reveals the growing importance of precipitation forecasts among Mzingwane communities, particularly the amount, timing, duration and distribution of rainfall. Rainfall was cited as the major cause of drought by 98 per cent of the respondents in the catchment. Whilst meteorological rainfall forecasts are available through various channels, they are not readily accessible to rural communities. Furthermore, they are not very reliable at local level. The paper shows that communities in the Mzingwane Catchment still regard local traditional knowledge forecasting as their primary source of weather forecasts. The paper finds that plant phenology is widely used by the local communities in the four districts for drought forecasting. Early and significant flowering of Mopane trees (Colophospermum mopane) from September to December has been identified to be one of the signals of poor rainfall season in respect to quantity and distribution and subsequent drought. Late and less significant flowering of Umtopi trees (Boscia albitrunca) from September to December also signals a poor rainfall season.Originality/value– The paper fulfils an identified need to study and document useful traditional drought indicators. Furthermore, the paper provides a platform for possible integration of traditional drought forecasting and meteorological forecasting and ensure sustainable rural livelihood development. The paper is useful to both meteorological researchers and resource-constrained communities in Mzingwane Catchment.

Not Available ; In 2012, the Commission carried out an overall evaluation of the policy on water scarcity and droughts introduced in the 2007 Communication. The evaluation focused on the integration of water scarcity and drought issues in the first (2009) River Basin Management Plans (RBMPs) with the aim of identifying gaps in EU drought policy and improving its implementation (the EU Water Framework Directive (WFD) requires RMBPs but not DMPs). The results revealed that the development and implementation of DMPs, and their inclusion within RBMPs, remains limited, and that countries should therefore try to integrate DMPs into the second versions of their RBMPs for 2015. Evaluation results were embedded in the Commission document, A Blueprint to Safeguard Europe's Water (hereinafter Blueprint), adopted in 2012 (COM (2012) 673 final). Regarding water scarcity and drought in the Central and Eastern European (CEE) region, the United Nations Convention to Combat Desertification (UNCCD, 1994) found that the region suffers from "soil degradation and desertification". Although both processes vary considerably from country to country, the vulnerability of the region to this hazard is evident and estimated to be increasing (UNCCD). In 2013, the Global Water Partnership (GWP) and World Meteorological Organization (WMO) launched a joint Integrated Drought Management Programme (IDMP) to improve the monitoring and prevention of droughts. In the same year, the Global Water Partnership (GWP) for CEE launched the IDMP at the CEE regional level (IDMP CEE). The aim of the IDMP CEE is "to support stakeholders at all levels by providing them with policy and management guidance through globally coordinated generation of scientific information and sharing best practices and knowledge for integrated drought management". During Phase 1 of the IDMP CEE, the overall drought situation in the 10 CEE countries of Bulgaria, Czech Republic, Hungary, Lithuania, Moldova, Poland, Romania, Slovakia, Slovenia, and Ukraine was analysed. The results confirmed that drought and water scarcity issues were widely recognized as a relevant phenomenon in the CEE region. (See Inception report for the GWP CEE part of the WMO/GWP Integrated Drought Management Programme, J. Kindler, D. Thalmeinerova, 2012) Following up on this first phase, Activity 1.2 of the IDMP CEE assessed the integration of drought issues into the first RBMPs. The results of a questionnaire survey, completed by the ten CEE countries listed above, and summarised in the Report on review of the current status of implementation of the drought management plans and measures (Fatulova, 2014), showed that the actual situation for DMP development within the region is unsatisfactory. The majority of the countries had not produced a DMP in accordance with the general WFD guidelines provided in the WFD Technical report Drought Management Plan Report Including Agricultural, Drought Indicators and Climate Change Aspects (hereinafter the Report 2007). Furthermore, substantial shortcomings were found in the implementation of all key elements of the DMPs, namely, indicators and thresholds establishing different drought stages, measures to be taken in each drought stage, and the organizational framework for drought management. (Note that while neither Moldova nor Ukraine are part of the EU, both are part of the GWP CEE region and are EU accession countries, and both expressed their interest to join this programme and prepare DMPs according to the WFD.) ; Not Available

Abstract. Drought management frameworks are dependent on methods for monitoring and prediction, but quantifying the hazard alone is arguably not sufficient; the negative consequences that may arise from a lack of precipitation must also be predicted if droughts are to be better managed. However, the link between drought intensity, expressed by some hydrometeorological indicator, and the occurrence of drought impacts has only recently begun to be addressed. One challenge is the paucity of information on ecological and socioeconomic consequences of drought. This study tests the potential for developing empirical drought impact functions based on drought indicators (Standardized Precipitation and Standardized Precipitation Evaporation Index) as predictors and text-based reports on drought impacts as a surrogate variable for drought damage. While there have been studies exploiting textual evidence of drought impacts, a systematic assessment of the effect of impact quantification method and different functional relationships for modeling drought impacts is missing. Using Southeast England as a case study we tested the potential of three different data-driven models for predicting drought impacts quantified from text-based reports: logistic regression, zero-altered negative binomial regression (hurdle model), and an ensemble regression tree approach (random forest). The logistic regression model can only be applied to a binary impact/no impact time series, whereas the other two models can additionally predict the full counts of impact occurrence at each time point. While modeling binary data results in the lowest prediction uncertainty, modeling the full counts has the advantage of also providing a measure of impact severity, and the counts were found to be reasonably predictable. However, there were noticeable differences in skill between modeling methodologies. For binary data the logistic regression and the random forest model performed similarly well based on leave-one-out cross validation. For count data the random forest outperformed the hurdle model. The between-model differences occurred for total drought impacts and for two subsets of impact categories (water supply and freshwater ecosystem impacts). In addition, different ways of defining the impact counts were investigated and were found to have little influence on the prediction skill. For all models we found a positive effect of including impact information of the preceding month as a predictor in addition to the hydrometeorological indicators. We conclude that, although having some limitations, text-based reports on drought impacts can provide useful information for drought risk management, and our study showcases different methodological approaches to developing drought impact functions based on text-based data.

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
provided to 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- and 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- and 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 to other parts of Southeast Asia and beyond.

Imprecise in space-time and with damaging effects, drought as a historical-natural phenomenon of high complexity has been afflicting the population of the Seridó Potiguar Region, located in the state of Rio Grande do Norte, Northeast Brazil. For centuries, the region, of state relevance, is part of the Brazilian semiarid region. This reality produces socio-spatial, socio-economic, and political-institutional conflicts. Considering this, and the fact that drought in the 21st century continues to reach disastrous proportions and cause harm to human systems, this research aimed to offer a partial overview of the socio-environmental vulnerability of the Seridó region to drought, focusing on seven key municipalities: Bodó, Caicó, Currais Novos, Ipueira, Jardim de Piranhas, Jucurutu, and Parelhas. The Drought Vulnerability Index (DVI) was applied to these municipalities, composed of the sub-indices of Exposure, Susceptibility, and Adaptive Capacity, based on socio-economic and physical-environmental variables, which were calculated, classified, and cartographically represented using the RGB color composition. After analyzing the results, it was found that the municipalities ranged from low to moderate vulnerability, which can be justified by the compensation between the variables themselves and the good indicators regarding social assistance, mixed economy, hydraulic infrastructure, and means of coping with the semiarid region.

Abstract. Drought monitoring and early warning systems (DEWSs) are
seen as helpful tools to tackle drought at an early stage and reduce the
possibility of harm or loss. They usually include indices attributed to
meteorological, agricultural and/or hydrological drought: physically based
drought drivers. These indices are used to determine the onset, end and
severity of a drought event. Drought impacts, like water and food
securities, are less monitored or even not included in DEWSs. Therefore, the
likelihood of experiencing these impacts is often simply linearly linked to
drivers of drought. The aim of this study is to evaluate the validity of the
assumed direct linkage between drivers of drought and water and food
insecurity impacts of drought. We reviewed scientific literature on both
drivers and impacts of drought. We conducted a bibliometric analysis based
on 5000+ scientific studies in which selected drought indices (drivers)
and drought-related water and food insecurities (impacts) were mentioned in
relation to a geographic area. Our review shows that there is a tendency in
scientific literature to focus on drivers of drought, with the preferred use
of meteorological and remotely sensed drought indices. Studies reporting
drought impacts are more localised, with relatively many studies focusing on
sub-Saharan Africa and Australasia for impacts with regard to food security
and water security, respectively. Our review further suggests that studies
of food and water insecurity impacts related to drought are dependent on
both the physical and human processes occurring in the geographic area, i.e.
the local context. With the aim of increasing the relevance and utility of
the information provided by DEWSs, we argue in favour of additional
consideration of drought impact indices oriented towards sustainable
development and human welfare.

Australia frequently experiences extended periods of severe droughts which have a significant negative impact on populations and economy. To improve preparedness for drought, decision-support tools which provide comprehensive information about current dry conditions are essential. In this paper, we present a conceptual design for a Drought Risk Analyser (DRA) – web-based information App for drought risk mapping developed using geographic information system (GIS). The developed DRA is based on combining Drought Hazard/Vulnerability/Exposure Indices (DHI, DVI and DEI respectively) into a final Drought Risk Index (DRI) for total of 542 Local Government Areas (LGA) in Australia. Drought indicators selected to compute drought hazard – the Standardised Precipitation Index (SPI), the Vegetation Health Index (VHI) and Soil Moisture – were obtained through the World Meteorological Organization (WMO) Space-based Weather and Climate Extremes Monitoring (SWCEM) international initiative. Australian Bureau of Statistics (ABS) census data were used to develop the drought-related population vulnerability index – DVI. Australian national Digital Elevation Model and catchment scale land use data were used to calculate the DEI. Implemented functionality of the designed DRA is illustrated using a case study for the 2019 drought in Australia. The DRA App will be beneficial for Australian farmers and rural communities to assist with decision making, as well as for LGA planners to gain insights on current state of drought risk at both local and national levels. The developed methodology of using space-based observations for assessing drought hazard could be applied for developing similar web-based information tools in drought-prone areas of other countries.

Estimation of ecological drought vulnerability indicators is the important step for drought mitigation management. This article identified and estimated ecological drought vulnerability indicators among communal farmers in the Eastern Cape province of South Africa, using an ecological vulnerability index based on a household survey of 121 communal farmers. The results identified overgrazing, soil erosion, land degradation, surface and groundwater supply, and land use management as the main ecological vulnerability variables. The results showed that climate is not necessarily linked to ecological vulnerability. High rainfall districts in this study showed higher ecological vulnerability to drought because of poor planning and management of water supply, poor grazing practices and land management that leads to serious land degradation. The identification and analysis of ecological vulnerability indicators to drought would aid in reconsidering priorities for the government to implement appropriate policy measures in response to drought and suggest strategies to reduce drought vulnerability. Such policies and strategies will strengthen climate change adaptation and ensure ecological and climate sustainability that comply with the Millennium Development Goals set out by the United Nations in 2000 and the subsequent 2030 development agenda for the Sustainable Development Goals. ; https://doi.org/10.4102/jamba.v11i1.591

Estimation of ecological drought vulnerability indicators is the important step for drought mitigation management. This article identified and estimated ecological drought vulnerability indicators among communal farmers in the Eastern Cape province of South Africa, using an ecological vulnerability index based on a household survey of 121 communal farmers. The results identified overgrazing, soil erosion, land degradation, surface and groundwater supply, and land use management as the main ecological vulnerability variables. The results showed that climate is not necessarily linked to ecological vulnerability. High rainfall districts in this study showed higher ecological vulnerability to drought because of poor planning and management of water supply, poor grazing practices and land management that leads to serious land degradation. The identification and analysis of ecological vulnerability indicators to drought would aid in reconsidering priorities for the government to implement appropriate policy measures in response to drought and suggest strategies to reduce drought vulnerability. Such policies and strategies will strengthen climate change adaptation and ensure ecological and climate sustainability that comply with the Millennium Development Goals set out by the United Nations in 2000 and the subsequent 2030 development agenda for the Sustainable Development Goals. ; https://doi.org/10.4102/jamba.v11i1.591

Estimation of ecological drought vulnerability indicators is the important step for drought mitigation management. This article identified and estimated ecological drought vulnerability indicators among communal farmers in the Eastern Cape province of South Africa, using an ecological vulnerability index based on a household survey of 121 communal farmers. The results identified overgrazing, soil erosion, land degradation, surface and groundwater supply, and land use management as the main ecological vulnerability variables. The results showed that climate is not necessarily linked to ecological vulnerability. High rainfall districts in this study showed higher ecological vulnerability to drought because of poor planning and management of water supply, poor grazing practices and land management that leads to serious land degradation. The identification and analysis of ecological vulnerability indicators to drought would aid in reconsidering priorities for the government to implement appropriate policy measures in response to drought and suggest strategies to reduce drought vulnerability. Such policies and strategies will strengthen climate change adaptation and ensure ecological and climate sustainability that comply with the Millennium Development Goals set out by the United Nations in 2000 and the subsequent 2030 development agenda for the Sustainable Development Goals.