Exploring the link between drought indicators and impacts

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.

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Exploring the link between drought indicators and impacts

Natural Hazards and Earth System Sciences Discussions ◽

10.5194/nhessd-2-7583-2014 ◽

2014 ◽

Vol 2 (12) ◽

pp. 7583-7620 ◽

Cited By ~ 1

Author(s):

S. Bachmair ◽

I. Kohn ◽

K. Stahl

Keyword(s):

State Level ◽

Early Warning Systems ◽

Drought Indices ◽

Federal State ◽

Drought Impact ◽

Federal States ◽

Drought Conditions ◽

Drought Indicators ◽

Ground Truthing ◽

Impact Data

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 the sparse and patchy data for ground truthing hydro-meteorologic variables. 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 as well as streamflow and groundwater level percentiles were selected. Linkage was assessed though data visualization and correlation analysis between monthly timeseries of indicator–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. While several commonalities could be identified regarding "best" indicator, indicator metric, and time-scale of climatic anomaly, 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 associated with drought impact onset, we found that no single "best" threshold value can be identified but impacts occur within a range of indicator values. 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 ground truthing hydro-meteorologic variables with text-based impact reports and highlights the value of impact reporting as a tool for monitoring drought conditions.

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Skill of large-scale seasonal drought impact forecasts

Natural Hazards and Earth System Science ◽

10.5194/nhess-20-1595-2020 ◽

2020 ◽

Vol 20 (6) ◽

pp. 1595-1608

Author(s):

Samuel J. Sutanto ◽

Melati van der Weert ◽

Veit Blauhut ◽

Henny A. J. Van Lanen

Keyword(s):

Machine Learning ◽

Logistic Regression ◽

Large Scale ◽

Standardized Precipitation Index ◽

Early Warning Systems ◽

Learning Approaches ◽

Discriminative Ability ◽

Drought Impact ◽

Drought Impacts ◽

Impact Data

Abstract. Forecasting of drought impacts is still lacking in drought early-warning systems (DEWSs), which presently do not go beyond hazard forecasting. Therefore, we developed drought impact functions using machine learning approaches (logistic regression and random forest) to predict drought impacts with lead times up to 7 months ahead. The observed and forecasted hydrometeorological drought hazards – such as the standardized precipitation index (SPI), standardized precipitation evaporation index (SPEI), and standardized runoff index (SRI) – were obtained from the The EU-funded Enhancing Emergency Management and Response to Extreme Weather and Climate Events (ANYWHERE) DEWS. Reported drought impact data, taken from the European Drought Impact Report Inventory (EDII), were used to develop and validate drought impact functions. The skill of the drought impact functions in forecasting drought impacts was evaluated using the Brier skill score and relative operating characteristic metrics for five cases representing different spatial aggregation and lumping of impacted sectors. Results show that hydrological drought hazard represented by SRI has higher skill than meteorological drought represented by SPI and SPEI. For German regions, impact functions developed using random forests indicate a higher discriminative ability to forecast drought impacts than logistic regression. Moreover, skill is higher for cases with higher spatial resolution and less lumped impacted sectors (cases 4 and 5), with considerable skill up to 3–4 months ahead. The forecasting skill of drought impacts using machine learning greatly depends on the availability of impact data. This study demonstrates that the drought impact functions could not be developed for certain regions and impacted sectors, owing to the lack of reported impacts.

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Drought impact links to meteorological drought indicators and predictability in Spain

10.5194/hess-2021-209 ◽

2021 ◽

Author(s):

Herminia Torelló-Sentelles ◽

Christian Franzke

Keyword(s):

Random Forest ◽

Meteorological Drought ◽

Hydrological Drought ◽

Random Forest Model ◽

The Arctic ◽

Drought Impact ◽

Forest Model ◽

Drought Impacts ◽

Drought Indicators ◽

Impact Data

Abstract. Drought affects many regions worldwide and future climate projections imply that drought severity and frequency will increase. Hence, the impacts of drought on the environment and society will also increase considerably. Monitoring and early warning systems for drought rely on several indicators; however, assessments on how these indicators are linked to impacts are still lacking. Here, we explore the links between different drought indicators and drought impacts within six sub- regions in Spain. We used impact data from the European Drought Impact Report Inventory database, and provide a new case study to evaluate these links. We provide evidence that a region with a small sample size of impact data can still provide useful insights regarding indicator-impact links. As meteorological drought indicators, we use the Standardised Precipitation Index and the Standardised Precipitation-Evapotranspiration Index, as agricultural and hydrological drought indicators we use a Standardised Soil Water Index and, a Standardised Streamflow Index and a Standardised Reservoir Storage Index. We also explore the links between drought impacts and teleconnection patterns and surface temperature by conducting a correlation analysis and then test the predictability of drought impacts using a Random Forest model. Our results show meteorological indices are best linked to impact occurrences overall, and at long time scales between 15 and 33 months. However, we also find robust links for agricultural and hydrological drought indices, depending on the sub-region. The Arctic Oscillation, Western Mediterranean Oscillation and the North Atlantic Oscillation at long accumulation periods (15 to 48 months), are top predictors of impacts in the northwest and northeast regions, the Community of Madrid, and the south regions of Spain respectively. We also find links between temperature and drought impacts. The Random Forest model produces skilful models for most sub- regions. When assessed using a cross-validation analysis, the models in all regions show precision, recall, or R2 values higher than 0.97, 0.62 and 0.68 respectively. Since we find the models to be skilful, we encourage other types of impact data to be used to investigate these links and to predict drought impacts.

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Overcoming the complexity of drought by phasing drought triggers; a case study of Zimbabwe

10.5194/egusphere-egu21-15974 ◽

2021 ◽

Author(s):

Marijke Panis ◽

Aklilu Teklesadik ◽

Mark Powell ◽

Richard Muchena ◽

David Muchatiza

Keyword(s):

Lead Time ◽

Standardized Precipitation Index ◽

Primary Source ◽

Growing Season ◽

Crop Losses ◽

Drought Impact ◽

Drought Impacts ◽

Early Action ◽

Drought Indicators ◽

The Impact

Historically droughts are one of the natural hazards in Zimbabwe with a significant impact on community resilience and threaten the livelihood of already vulnerable people. Agricultural activities are the primary source of income, where the dominant rain-fed agriculture is exceptionally vulnerable to climate extremes, reducing the country's agricultural productivity. The Zimbabwe Red Cross targets crop losses as the drought impact to prioritize in the drought impact-based forecasting system.The Impact-based Forecasting project in Zimbabwe aims to reduce the impact of drought (crop losses) to the community by implementing early actions within sufficient operational lead time. Drought is a slow-onset disaster, and its impact is felt and visible at different moments &#160;the seasonal calendar. This drought impact can be categorized into primary- and secondary impacts. Primary drought impacts are directly linked to rainfall scarcity, such as reduced crop yield and water scarcity. Secondary drought impacts are directly connected to dry conditions, such as food insecurity and epidemics. These temporal differences of impacts ask for drought triggers at various moments in the calendar, leading to a more segmented approach. The segmented approach makes it possible to design the trigger in a way that the drought indicators best linked to the operational early action at that lead time. The first phase has the longest lead time in predicting the impact of a drought using a global climatological indicator (ENSO) first to identify the probability of an El Ni&#241;o/La Ni&#241;a year to develop into the next growing season. Secondly, the FEWSNET Food Security Seasonal Outlook can be used as a predictor of the impact of an upcoming drought and of the population exposed to an IPC-Class 3 level. The last phase exists of monitoring biophysical drought indicators over the growing season to predict accurately the effect of a drought with the shortest lead time. The aim of phasing the trigger methodology is to activate low-cost actions when the uncertainty of the impact of a drought is relatively high. By adding more seasonal information to the trigger model over time, the predictive uncertainty reduces.As a result, the drought trigger methodology we designed can drive the discussion and be the evidence base on the selection of early actions to reduce drought impacts. Next steps in the development of the system are to calculate the forecast skill of the biophysical indicators such as standardized precipitation index (SPI) and Vegetation Condition Index (VCI) soil moisture? linked to the identified prioritized drought impacts and to select corresponding early actions.

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A review of drought indices: predominance of drivers over impacts and the importance of local context

10.5194/nhess-2021-152 ◽

2021 ◽

Author(s):

Sarra Kchouk ◽

Lieke A. Melsen ◽

David W. Walker ◽

Pieter R. van Oel

Keyword(s):

Scientific Literature ◽

Geographic Area ◽

Early Warning Systems ◽

Sub Saharan Africa ◽

Local Context ◽

Drought Indices ◽

Drought Event ◽

Human Welfare ◽

Drought Impact ◽

Drought Impacts

Abstract. Drought monitoring and Early Warning Systems (DEWS) 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 are less monitored or even not included in DEWS. Therefore, the likelihood of experiencing drought 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 drought impact. 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 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 drought-impacts studies 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 DEWS, we argue in favour of additional consideration of drought impact indices oriented towards sustainable development and human welfare.

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Moving from drought hazard to impact forecasts

Nature Communications ◽

10.1038/s41467-019-12840-z ◽

2019 ◽

Vol 10 (1) ◽

Cited By ~ 14

Author(s):

Samuel J. Sutanto ◽

Melati van der Weert ◽

Niko Wanders ◽

Veit Blauhut ◽

Henny A. J. Van Lanen

Keyword(s):

River Flow ◽

Meteorological Drought ◽

Early Warning Systems ◽

Drought Indices ◽

Warning Systems ◽

Drought Management ◽

Drought Impact ◽

Drought Impacts ◽

Drought Hazard ◽

Drought Early Warning

Abstract Present-day drought early warning systems provide the end-users information on the ongoing and forecasted drought hazard (e.g. river flow deficit). However, information on the forecasted drought impacts, which is a prerequisite for drought management, is still missing. Here we present the first study assessing the feasibility of forecasting drought impacts, using machine-learning to relate forecasted hydro-meteorological drought indices to reported drought impacts. Results show that models, which were built with more than 50 months of reported drought impacts, are able to forecast drought impacts a few months ahead. This study highlights the importance of drought impact databases for developing drought impact functions. Our findings recommend that institutions that provide operational drought early warnings should not only forecast drought hazard, but also impacts after developing an impact database.

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Quantifying the responses of ecosystem production and respiration to drought time scale, intensity, timing and lagged response: A FLUXNET synthesis

10.5194/egusphere-egu21-1841 ◽

2021 ◽

Author(s):

Wenzhe Jiao ◽

Lixin Wang

Keyword(s):

Ecosystem Respiration ◽

Gross Primary Production ◽

Multiple Time Scales ◽

Drought Indices ◽

Drought Severity ◽

Multiple Time ◽

Drought Impact ◽

Drought Impacts ◽

Drought Conditions ◽

Ecosystem Production

Drought is not only a multiscale (e.g., temporal, spatial) but also a multidimensional (e.g., onset, offset, duration, frequency, magnitude, intensity) phenomenon, and ecosystem production and respiration may respond to each drought dimension differently. &#160;Although multiple reports exist in literature on the drought impact on ecosystem productivity, it remains unclear how each component of drought impacts ecosystem gross primary production (GPP), ecosystem respiration (RECO), and net ecosystem exchange (NEE) and how the different drought dimensions interacted with each other on their impacts. In this study, we conducted a comprehensive drought impact assessment on forest GPP, NEE, and RECO including all the drought dimensions using FLUXNET observations and multiple time-scales of Standardized Precipitation-Evapotranspiration Index (SPEI). Our results indicated that while most earlier drought studies focused on simultaneous and post-drought conditions, the cumulative drought impacts and drought timing are more significantly impacting forest carbon uptake than simultaneous drought severity. Temporal standardization based meteorological drought indices could be used to accurately reflect plant water stress if antecedent and cumulative drought conditions are considered.

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Development of a Next Generation Drought Index: combining multiple global and local data sources to enable detection of sector-specific drought impacts

10.5194/egusphere-egu21-10886 ◽

2021 ◽

Author(s):

Dimmie Hendriks ◽

Pieter Hazenberg ◽

Jonas Gotte ◽

Patricia Trambauer ◽

Arjen Haag ◽

...

Keyword(s):

Drought Index ◽

Agricultural Drought ◽

Data Sources ◽

Drought Indices ◽

Next Generation ◽

Hazard Indices ◽

Local Data ◽

Drought Impacts ◽

Drought Hazard ◽

Impact Data

An increasing number of regions and countries are confronted with droughts as well as an increase in water demand. Inevitably, this leads to an increasing pressure on the available water resources and associated risks and economic impact for the water dependent sectors. In order to prevent big drought impacts, such as agricultural damage and food insecurity, timely and focused drought mitigation measures need to be carried out. To enable this, the detection of drought and its sector-specific risks at early stages needs to be improved. One of the main challenges is to develop compound and impact-oriented drought indices, that make optimal use of innovative techniques, satellite products, local data and other big data sets.Here, we present the development of a Next Generation Drought Index (NGDI) that combines multiple freely available global data sources (eg. ERA5, MODIS, PCR-GLOBWB) to calculate a range of relevant drought hazard indices related to meteorological, hydrological, soil moisture and agricultural drought (eg. SPI, SPEI, SRI, SGI, VCI). The drought hazard indices are aggregated at district level, while considering the percentage area exposure of the drought impacted sector (exposure). In addition, the indices are enriched with local and national scale drought impact information (eg. online news items, social media data, EM-DAT database, GDO Drought news, national drought reports). Results are presented at sub-national scales in interactive spatial and temporal views, showing the combined drought indices and impact data.The NGDI approach is being tested for the agricultural sector in Mali, a country with a vulnerable population and economy that faces frequent dry spells which heavily impact the functioning of the important agricultural activities that sustain a large part of the population. The computed drought indices are compared with local drought data and an analysis is made of the cross-correlations between the indices within the NGDI and collected impact data.We aim at providing the NGDI information to a broad audience as well as co-creation of further NGDI developments. Hence, we would like to reach out to interested parties and identify collaboration opportunities.

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Selecting indicators of drought impacts: the importance of context

10.5194/egusphere-egu21-1134 ◽

2021 ◽

Author(s):

Sarra Kchouk ◽

Pieter van Oel ◽

Lieke Melsen

Keyword(s):

Early Stage ◽

Contextual Information ◽

Geographic Area ◽

Early Warning Systems ◽

Sub Saharan Africa ◽

Drought Impacts ◽

Direct Linkage ◽

Drought Indicators ◽

Sub Saharan ◽

Drought Early Warning

Drought Early Warning Systems (DEWS) and Drought Monitoring Systems (DMS) are the principal tools used to tackle drought at an early stage and reduce the possibility of harm or loss. They are based on the use of drought indicators attributed to either : meteorological, agricultural and hydrological drought. This means that it is mostly hydro-climatic variables that are used to determine the onset, end and severity of a drought. &#160;Drought impacts are rarely continuously monitored or even not included in DEWS and DMS. In this configuration, the likelihood of experiencing impacts is linearly linked to the severity of climatic features only. The aim of our study is to question the direct linkage between the delivery of hydro-climatic information and the detection of drought impacts and their severity. We reviewed scientific literature on drought drivers and impacts and analyzed how these two compare. We conducted a bibliometric analysis based on 4000+ scientific studies sorted by geographic area in which selected (i) drought indicators and (ii) impacts of drought were mentioned. Our review points toward an attachment to a conceptual view of drought by the main and broader use of meteorological (computed and remotely sensed) drought indicators. Studies reporting impacts related to food and water securities are more localized, respectively in Sub-Saharan Africa and Australasia. This mismatch suggests a tendency to translate hydroclimatic indicators of drought directly into impacts while neglecting relevant local contextual information. With the aim of sharpening the information provided by DEWS and DMS, we argue in favor of an additional consideration of drought indicators oriented towards the SDGs.

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Finescale Evaluation of Drought in a Tropical Setting: Case Study in Sri Lanka

Journal of Applied Meteorology and Climatology ◽

10.1175/2008jamc1767.1 ◽

2009 ◽

Vol 48 (1) ◽

pp. 77-88 ◽

Cited By ~ 10

Author(s):

Bradfield Lyon ◽

Lareef Zubair ◽

Vidhura Ralapanawe ◽

Zeenas Yahiya

Keyword(s):

Sri Lanka ◽

Standardized Precipitation Index ◽

Meteorological Drought ◽

Drought Indices ◽

Drought Risk ◽

Mitigation And Adaptation ◽

Wide Range ◽

Drought Relief ◽

Drought Indicators ◽

The Standardized Precipitation Index

Abstract In regions of climatic heterogeneity, finescale assessment of drought risk is needed for policy making and drought management, mitigation, and adaptation. The relationship between drought relief payments (a proxy for drought risk) and meteorological drought indicators is examined through a retrospective analysis for Sri Lanka (1960–2000) based on records of district-level drought relief payments and a dense network of 284 rainfall stations. The standardized precipitation index and a percent-of-annual-average index for rainfall accumulated over 3, 6, 9, and 12 months were used, gridded to a spatial resolution of 10 km. An encouraging correspondence was identified between the spatial distribution of meteorological drought occurrence and historical drought relief payments at the district scale. Time series of drought indices averaged roughly over the four main climatic zones of Sri Lanka showed statistically significant (p < 0.01) relationships with the occurrence of drought relief. The 9-month cumulative drought index provided the strongest relationships overall, although 6- and 12-month indicators provided generally similar results. Some cases of appreciable drought without corresponding relief payments could be attributed to fiscal pressures, as during the 1970s. Statistically significant relationships between drought indicators and relief payments point to the potential utility of meteorological drought assessments for disaster risk management. In addition, the study provides an empirical approach to testing which meteorological drought indicators bear a statistically significant relationship to drought relief across a wide range of tropical climates.

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