NH9.6

Drought has a strong subjective component, incorporating an expectation about how much water there “should” be. Impacts of drought are the downstream effects of a phenomenon that is difficult to bound in space and time, but that propagates through sectors and ecosystems. Data on drought losses with a monetary value, such as commodity crops or energy production, are most readily available. Data on changes to ecosystems and other less coordinated economic activities are harder to find. The Drought Impacts Toolkit (droughtimpacts.unl.edu) curates many sources of drought-impact information. Tools hosted on the site focus on gathering and mapping what people are saying about drought via news stories, social media, crowdsourcing and citizen science. These map layers are independently informative and collectively contribute to a convergence of evidence approach to assessing drought impacts. Each represents a channel of information that captures different sets of motivations and describes drought’s effects at different temporal and spatial resolutions. Quantifying the volume of information on each channel over time -- “chatter” -- provides insight into rising and falling levels of awareness or concern about drought. Analysis of and familiarity with the relationships between what is being said on different channels and at what rates, and how they do and don’t coincide with physical phenomena, is a useful diagnostic approach. It may provide early warning of emerging drought or drought impacts, insights into how people experience the effects of drought from one place to another, underlying vulnerabilities, and potential solutions.

How to cite: Smith, K. H.: Tuning in to drought chatter: Detecting deviation from expectation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8875, https://doi.org/10.5194/egusphere-egu22-8875, 2022.

Despite the scientific progress in drought forecasting, it remains challenging to accurately predict the corresponding impact of a drought event. This is due to the unexplored relationships between (multiple) drought indicators and the impacts across spatiotemporal scales. In this study, we unravel these relationships by analysing the impacts of the severe 2018-2019 drought event in Central Europe. We calculated the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evaporation Index (SPEI) over various accumulation periods, and related the indicators to losses from the European Drought Impact Report Inventory (EDII)¹ with a focus on agriculture and water supply. An initial assessment was performed by correlating monthly time series of the drought indicators and the impact data at the EU NUTS1 region level. We further used a Random Forest Model to measure the predictive power of the drought indicators for those impacts.

Our findings reveal significant relationships between the drought indicators and the impacts over different accumulation periods. The analysis also detects region-specific and time-variant differences during the 2018–2019 Central European drought event. As such, our work provides a new framework to unravel the drought indicators-impacts dependencies. In addition, it emphasizes the need to leverage available impact data to increase the capacity to forecast the drought impacts.

How to cite: Shyrokaya, A., Di Baldassarre, G., Messori, G., Pechlivanidis, I., Pappenberger, F., and Cloke, H.: Comparing drought indicators and negative impacts for the 2018–19 Central European drought event, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4218, https://doi.org/10.5194/egusphere-egu22-4218, 2022.

The term ‘flash drought’ has become increasingly prevalent in scientific discourse and research on the topic is growing. The corresponding increase in flash drought publications typically presents definitions, mechanisms, detection and monitoring, and forecasting. However, many aspects of flash droughts are less well understood, such as flash drought impacts, especially the socioeconomic and environmental impacts.

Flash droughts tend to be defined from a hydrometeorological perspective as events of rapid onset, rapid intensification, low precipitation and soil moisture, and high temperature. Yet there are similar, often locally named, phenomena around the world with their own specific characteristics and impacts that could be considered flash droughts. Such events may not match literature or index-specific definitions of flash drought, for example due to their very short duration or anthropogenic drivers. Consequently, they may go undetected or unpredicted in the increasingly common global flash drought products and may not be considered in flash drought research.

We, the co-authors (a sub-section of the Panta Rhei ‘Drought in the Anthropocene’ working group), conducted a survey among peers to collect cases from around the world of alternative names, characteristics and impacts of flash droughts. Many regions were represented in the responses and local nomenclature for flash drought-like events were identified, in particular from Brazil, South Asia, Sub-Saharan Africa and Central America.

Maps of flash drought hotspots based on hydrometeorological indices often do not indicate whether anything adverse was experienced on the ground, or overemphasise occurrence where events are unlikely. Therefore, we utilised the survey findings and subsequent investigations to ‘ground truth’ a flash drought hotspots map. We related hotspots to published case studies of drought impacts or existence of local terms for flash droughts. However, mismatches occurred suggesting there are regions potentially experiencing flash droughts that are either not represented in our survey nor in the literature or there are inaccuracies in flash drought hotspot identification.

How to cite: Walker, D. W., Vergopolan, N., Cavalcante, L., Almagro, A., Apurv, T., Kingston, D. G., Roy, T., Smith, K. H., and Wanders, N.: Flash droughts: bridging the understanding between physical definitions and societal impacts, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11138, https://doi.org/10.5194/egusphere-egu22-11138, 2022.

Effective Drought Index (EDI) was proposed to monitor daily propagations of an emerging drought. The EDI, like other drought indices, uses the last 30 years of the daily precipitation record for the reference period for effective precipitation (EP) climatology, resulting that the drought characteristics can be solely estimated by a recent climatology. To overcome this weakness, this study proposes a self-calibrating EDI, a modified EDI with time-varying EP climatology via the 30-year moving time windows. In this study, the scEDI is calculated from the 240-year daily precipitation records (1777–2020) in Seoul, the south Korean Peninsula, and is compared with and the EDIs with different reference periods. The scEDI successfully adapts multi-decadal variability of precipitation, leading to robust (temporally consistent) estimates of drought severity while the EDIs, particularly with the 1885–1915 (dry) and 1990–2020 (wet) reference periods, over- and under-estimate drought severity, respectively. Furthermore, the droughts estimated by the scEDI are compared with the drought damage records in the Annals of the Joseon Dynasty (1778–1907) and the recent search frequency about droughts in Google and NAVER portals (2016–18) to investigate scEDI threshold values that is linked to actual socioeconomic impacts or favorable drought stages for a high level of drought awareness. Results confirmed that -1.0  and -2.0 of the scEDI can be good threshold values to detect severe droughts that cause socioeconomic impacts for agrarian and industrial societies, respectively. It is also found that the persistent and recovery stage of recent droughts surged the Internet search activities while public interest in drought was low during the onset stage. The findings of this study suggest that the importance of self-calibrating on improving the EDI-based drought assessment.

How to cite: Park, C.-K. and Kam, J.: Impact of Self-Calibrating on the Effective Drought Index: A Case Study of the south Korean Peninsula, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10959, https://doi.org/10.5194/egusphere-egu22-10959, 2022.

Changes in climate and socio-economic conditions can induce water stress and threaten water security. India is an agriculture-dependent, densely-populated country undergoing rapid societal developments. For proper mitigation and adaptation planning in India, it is, therefore, important to assess how drought hazard, vulnerability and risk would evolve in future. Earlier studies present projected drought risk over India based on frequency analysis and/or hazard assessment alone. This study investigates future evolution of drought risk integrating vulnerability and hazard information at a country-wide scale under the mitigation (RCP2.6) and medium stabilization (RCP6.0) climate scenarios in combination with Shared Socio-economic Pathway middle-of-the-road (SSP2) socio-economic condition. A multivariate standardized drought index (MSDI) based on joint deficits of precipitation and soil moisture is chosen to characterize droughts. Drought vulnerability is assessed by the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method, a robust multi-criteria decision-making technique, considering indicators that represent exposure, adaptive capacity and sensitivity.  Though there is a reduction in areal extent of high or very high drought hazard classes in the country by approximately 7% in future, possibly due to projected rise in precipitation, the area under high or very high drought vulnerability classes increases by 33% in the worst-case scenario. Parts of West Rajasthan, Odisha, Haryana and West Uttar Pradesh are found to be high risk under all scenarios. Bivariate choropleth plots show that future drought risk is more significantly driven by changes in vulnerability resulting from societal developments rather than climate-induced changes in drought hazard. The present study can aid the administrators, policy makers and drought managers in formulating decision support systems for effective drought management.

How to cite: Venkataswamy, S. and Mondal, A.: Evolution of multivariate drought hazard, vulnerability and risk in India under climate change, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-249, https://doi.org/10.5194/egusphere-egu22-249, 2022.

Droughts have huge negative impacts on livelihoods and economies throughout the world, and climate change is expected to increase their future frequency and severity. For an effective drought management, drought risk assessment is considered of major importance. However, despite the high number of studies, shared and clear guidelines to perform drought risk assessments are missing, undermining the overall reliability of this procedure. A significant limitation common to most drought risk assessments is the lack of any form of validation. Moreover, checking the robustness of the assessment tools is of paramount importance, but appropriate data are usually not available for external validation; hence, internal validations are in many cases the only option. For this scope, we propose a simple but robust uncertainty analysis, using the methodology presented in the “Handbook on constructing composite indicators” of OECD (2008). An additional deficiency of most drought risk assessments is the missing link between the results and possible adaptation strategies. To address this limitation, we propose to use archetype analysis, which is an emerging approach for identifying recurrent patterns within cases and supporting a context-specific generalization of insights.  

The innovations introduced were applied to a drought risk assessment performed for the agricultural systems of five coastal watersheds of central and southern Tuscany, Italy. These watersheds are particularly prone to drought impacts because of the high concurrent water demand for domestic and agricultural uses during the summer months. To allow a better discretization, municipalities were selected as units of analysis. A total of 42 indicators were used to represent drought hazard, exposure, and vulnerability. Multiple drought hazard indicators were selected to estimate both past and future drought hazards, using ready-to-use data from public institutions. Overall, the southern part of Tuscany showed to be the most at risk, in particular the Grosseto province. For the robustness evaluation, we (1) excluded individual exposure and vulnerability indicators, (2) included the excluded indicators with the multicollinearity analysis, (3) assigned different weights, and (4) used an alternative aggregation method to calculate the composite risk indicator. Results in terms of average shifts in rankings and new rankings assigned revealed that the most uncertain parts were the selection of exposure indicators and the assignment of weights, but overall, the rankings were confirmed. The archetype analysis yielded as result seven clusters of municipalities; their characteristics were analysed and tailored adaptation strategies were proposed according to their specific drought risk profiles.

How to cite: Villani, L., Castelli, G., Piemontese, L., Penna, D., and Bresci, E.: Introducing robustness evaluation and archetype analysis in drought risk assessments, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2675, https://doi.org/10.5194/egusphere-egu22-2675, 2022.

The different existing frameworks of Water Accounting (WA) techniques have proven to be useful tools for managing water in situations of water scarcity. The indices derived from WA procedures typically focus at informing decisions related to two different targets. A first group focuses on estimating water availability in different parts of a river basin. A second group focuses on the effects of human activities (interventions) on the water balance. Both are precious tools for decision making when the water is even scarcer, like in drought situations. However, their frameworks remain limited for an application to drought and drought impacts as it eludes many specificities proper to droughts. The aim of our study is to explore how WA techniques and indices can thus be adapted for integrated drought management. We based our approach on the water-balance data from the Banabuiú River Basin located in the semi-arid and drought-prone Northeast of Brazil. This area is the place of varied agricultural activities, rainfed or irrigated from a dense network of reservoirs. Droughts, from flash droughts to sometimes pluriannual, can affect the water balance of those reservoirs and the basin, and pose a challenge to meet all the agricultural needs. We direct our results towards the investigation of spatiotemporal scale issues. Indeed, water balance assessments often do not consider spatial variations in a river basin area and only report average annual situations. However, the duration of droughts or their impacts can extend beyond this reference period until sometimes becoming persistent to the system. The same applies for spatial-scale issues. Actions and processes happening at different physical scales and levels, inside and outside the basin, can modify the water balance. By addressing these spatiotemporal complexities, we aim to develop indices that will account for the human activities and enable to better inform decisions for integrated drought management.

How to cite: Kchouk, S., Ribeiro Neto, G., Cavalcante, L., Melsen, L., Walker, D., Sonsol Gondim, R., and van Oel, P.: Accounting for spatiotemporal complexities of drought in water accounting to inform integrated drought management, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12922, https://doi.org/10.5194/egusphere-egu22-12922, 2022.

In the past decade, several efforts have been made to project armed conflict risk into the future. However all of these approaches neglected the impact of hydrological extremes, specifically drought, on potential conflicts. This study broadens current approaches by presenting a first-of-its-kind application of machine learning (ML) methods to project sub-national armed conflict risk over the African continent along three Shared Socioeconomic Pathway (SSP) scenarios and three Representative Concentration Pathways towards 2050 including hydrological feedbacks.

We specifically assessed the role of hydro-climatic indicators as drivers of armed conflict. Overall, their importance is limited compared to main conflict predictors but results suggest that changing climatic conditions may both increase and decrease conflict risk, depending on the location: in Northern Africa and large parts of Eastern Africa climate change increases projected conflict risk whereas for areas in the West and northern part of the Sahel shifting climatic conditions may reduce conflict risk.

With our study being at the forefront of ML applications for conflict risk projections, we identify various challenges for this arising scientific field. A major concern is the limited selection of relevant quantified indicators for the SSPs at present. Specifically, the links between drought and conflicts are mostly region specific and not necessarily well reflected in the available data. Nevertheless, ML models such as the one presented here are a viable and scalable way forward in the field of armed conflict risk projections, and can help to inform the policy-making process with respect to climate security under changing hydroclimatic conditions.

How to cite: Wanders, N., Hoch, J., de Bruin, S., van Beek, R., Buhaug, H., and von Uexkull, N.: Unravelling the complex interplay between drought and conflict, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3438, https://doi.org/10.5194/egusphere-egu22-3438, 2022.

Drought is one of the most complex hydrological and climate disasters, causing damage to ecosystem structure and function. Ecosystem resilience is considered a key concept for understanding and describing the response of ecosystems to drought. Recovery time, as an important measure of resilience, has been widely used to assess ecosystem resilience to drought, but there is a deficiency in distinguishing the difference in recovery time under various drought intensities. On the basis of the existing assessment of drought resilience based on recovery time, we defined a new resilience indicator using an exponentially fitted curve to characterize the relationship between drought intensity and the corresponding recovery time, and the resilience was quantified by the curve area. Resistance represents the capacity of ecosystems to remain stable during droughts, and we quantified the resistance indicator by the ratio of the frequency of no vegetation loss during drought to drought frequencies. Our results showed that the ecosystem resilience to drought increased from arid to sub-humid regions in China’s dryland, and resistance was the lowest in the semiarid region. There was a trade-off between resilience and resistance: grassland had higher resilience and lower resistance than forestland. Drought memory contributed to the high resilience in the case of high drought frequency. These findings enriched the identification of the resilience of ecosystems to drought and the relationship between resilience and resistance and drought frequency in drylands.

How to cite: Yao, Y.: Evaluation of ecosystem resilience to drought based on drought intensity and recovery time, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1958, https://doi.org/10.5194/egusphere-egu22-1958, 2022.

The increasing drought with rapid onset in a warming climate arouses wide concerns due to its enormous impacts on the terrestrial ecosystem. Despite the duration of flash drought is relatively short ranging from several weeks to months, its legacy effects on the terrestrial ecosystem may remain even after flash drought. Here we use remote sensing observations of Solar-Induced chlorophyll Fluorescence (SIF) and Gross Primary Productivity (GPP) and a land surface model to investigate the negative impacts and legacy effects of flash drought on terrestrial ecosystem productivity. The decline and recovery in observed and modeled terrestrial ecosystem productivity caused by flash drought are more rapid over drier regions, showing lower drought resistance and higher drought recovery. For wetter regions, GPP and SIF over wetter regions show higher drought resistance, whereas they are still lower within 15 days after flash drought compared with their pre-drought level. The resistance of terrestrial ecosystem productivity shows a significant increasing trend during recent decades, which is possibly related to the increased vegetation growth. The legacy effects of flash drought over wetter regions highlight the importance of drought monitoring and forecasting over humid or semi-humid regions

How to cite: Zhang, M. and Yuan, X.: Response and recovery of terrestrial ecosystem productivity to flash drought over China under climate change, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11831, https://doi.org/10.5194/egusphere-egu22-11831, 2022.

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.

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:

• Trends in the proportion of land under drought over the total land area,
• Trends in the proportion of the total population exposed to drought, and
• Trends in the degree of drought vulnerability.

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 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.

How to cite: Barker, L., Rickards, N., Sarkar, S., Hannaford, J., Magee, E., and Rees, G.: Supporting national reporting of drought hazard, exposure and vulnerability to track progress in drought adaptation, mitigation and management, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12278, https://doi.org/10.5194/egusphere-egu22-12278, 2022.