Significant relationships between drought indicators and impacts for the 2018–2019 drought in Germany

Shyrokaya, Anastasiya; Messori, Gabriele; Pechlivanidis, Ilias; Pappenberger, Florian; Cloke, Hannah L; Di Baldassarre, Giuliano

doi:10.1088/1748-9326/ad10d9

Cited by 4 publications

(3 citation statements)

References 65 publications

(60 reference statements)

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“…In addition, the analysis was conducted using a robust study design and model, that allowed us to accurately control for the effect of temperature. Furthermore, we used a robust and standard high resolution drought index to monitor drought events [75]. The SPEI has been extensively used in scientific literature, including epidemiological studies on drought and health [19,22,66].…”

Section: Discussionmentioning

confidence: 99%

Analyzing the effects of drought at different time scales on cause-specific mortality in South Africa

Salvador,

Nieto,

Kapwata

et al. 2024

Environ. Res. Lett.

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South Africa (SA) is highly vulnerable to the effects of drought on the environment, economy, and society. However, its effect on human health remains unclear. Understanding the mortality risk associated with different types of droughts in different population groups and by specific causes would help clarify the potential mechanisms involved. The study aims to comprehensively assess the effect of droughts of varying time scales on cause-specific mortality (all; infectious and parasitic; endocrine, nutritional, and metabolic; cardiovascular; respiratory) in SA (from 2009-2016) and identify more vulnerable profiles based on sex and age. We also evaluated the urbanicity and district-level socioeconomic deprivation as potential risk modifiers. We used a two-stage time-series study design, with the weekly Standardized Precipitation-Evapotranspiration Index (SPEI) calculated at 1, 6, 12, and 15 months of accumulation to identify droughts of different duration (SPEI1,6,12,15, respectively). We applied a quasi-Poisson regression adjusted by mean temperature to assess the association between each type of drought and weekly mortality in all district municipalities of SA, and then pooled the estimates in a meta-regression model. We reported Relative Risks (RRs) for one unit increase of drought severity. Overall, we found a positive association between droughts (regardless the time scale) and all causes of death analysed. The strongest associations were found for the drought events more prolonged (RR [95%CI]: 1.027 [1.018, 1.036] (SPEI1); 1.035 [1.021, 1.050] (SPEI6); 1.033 [1.008, 1.058] (SPEI12); 1.098 [1.068, 1.129] (SPEI15)) and respiratory mortality (RRs varied from 1.037 [1.021, 1.053] (SPEI1) to 1.189 [1.14, 1.241] (SPEI15)). An indication of greater vulnerability was found in younger adults for the shortest droughts, in older adults for medium-term and long-term droughts, and children for very long-term droughts. However, differences were not significant. Further evidence of the relevance of urbanicity and demographic and socioeconomic conditions as potential risk modifiers is needed.

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Section: Discussionmentioning

confidence: 99%

Analyzing the effects of drought at different time scales on cause-specific mortality in South Africa

Salvador,

Nieto,

Kapwata

et al. 2024

Environ. Res. Lett.

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“…This work developed a fusion-based one-month lead meteorological drought forecast model that incorporates multi-source features from satellite images and data products. The standardized precipitation evapotranspiration index (SPEI) was applied to capture drought characteristics in the study area [24,25]. The developed ST model integrates three algorithms, namely, extreme gradient boosting (XGBoost), random forest (RF), and light gradient boosting machine (LightGBM) to forecast the SPEI at the time scale of 12 months (SPEI-12).…”

Section: Introductionmentioning

confidence: 99%

A Novel Fusion-Based Methodology for Drought Forecasting

Zhang,

Loaiciga,

Sauter

2024

Remote Sensing

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Accurate drought forecasting is necessary for effective agricultural and water resource management and for early risk warning. Various machine learning models have been developed for drought forecasting. This work developed and tested a fusion-based ensemble model, namely, the stacking (ST) model, that integrates extreme gradient boosting (XGBoost), random forecast (RF), and light gradient boosting machine (LightGBM) for drought forecasting. Additionally, the ST model employs the SHapley Additive exPlanations (SHAP) algorithm to interpret the relationship between variables and forecasting results. Multi-source data that encompass meteorological, vegetation, anthropogenic, landcover, climate teleconnection patterns, and topological characteristics were incorporated in the proposed ST model. The ST model forecasts the one-month lead standardized precipitation evapotranspiration index (SPEI) at a 12 month scale. The proposed ST model was applied and tested in the German federal states of Brandenburg and Berlin. The results show that the ST model outperformed the reference persistence model, XGBboost, RF, and LightGBM, achieving an average coefficient of determination (R2) value of 0.845 in each month in 2018. The spatiotemporal Moran’s I method indicates that the ST model captures non-stationarity in modeling the statistical association between predictors and the meteorological drought index and outperforms the other three models (i.e., XGBoost, RF, and LightGBM). Global sensitivity analysis indicates that the ST model is influenced by a combination of environmental variables, with the most sensitive being the preceding drought indices. The accuracy and versatility of the ST model indicate that this is a promising approach for forecasting drought and other environmental phenomena.

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“…Some of these changes are not even reported as impact, but rather as a way of coping with drought. This makes relating drought impacts to drought hazard indicators challenging (Bachmair et al, 2016;Shyrokaya et al, 2024). A way to include social dynamics is to add vulnerability factors (Blauhut et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

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Van Loon

2024

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Significant relationships between drought indicators and impacts for the 2018–2019 drought in Germany

Cited by 4 publications

References 65 publications

Analyzing the effects of drought at different time scales on cause-specific mortality in South Africa

Analyzing the effects of drought at different time scales on cause-specific mortality in South Africa

A Novel Fusion-Based Methodology for Drought Forecasting

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