scholarly journals Exploring the link between drought indicators and impacts

2014 ◽  
Vol 2 (12) ◽  
pp. 7583-7620 ◽  
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.

scholarly journals Exploring the link between drought indicators and impacts

2015 ◽  
Vol 15 (6) ◽  
pp. 1381-1397 ◽  
Author(s):  
S. Bachmair ◽  
I. Kohn ◽  
K. Stahl
Keyword(s):  
Standardized Precipitation Index ◽  
Early Warning Systems ◽  
Drought Indices ◽  
Indicator Values ◽  
Drought Impact ◽  
Federal States ◽  
Drought Impacts ◽  
Drought Conditions ◽  
Drought Indicators ◽  
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 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.

scholarly journals Skill of large-scale seasonal drought impact forecasts

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.

scholarly journals Drought impact links to meteorological drought indicators and predictability in Spain

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.

Die Nichterfüllung der Beschäftigungspflichtquote schwerbehinderter Menschen – Eine empirische Untersuchung möglicher Ursachen auf Ebene der deutschen Bundesländer

2019 ◽  
Vol 68 (12) ◽  
pp. 973-998
Author(s):  
Melanie Borah ◽  
Kathrin Hahn ◽  
Andreas Knabe
Keyword(s):  
State Level ◽  
Disabled Persons ◽  
Federal State ◽  
Employment Rate ◽  
Disabled People ◽  
Multivariate Statistical ◽  
Empirische Untersuchung ◽  
Federal States ◽  
Statistische Analyse ◽  
German Federal States

Zusammenfassung Diese Studie untersucht Faktoren, die die teilweise starken Unterschiede in der Beschäftigungsquote Schwerbehinderter zwischen den deutschen Bundesländern im Zeitraum von 2003 bis 2015 erklären können. Sie legt dabei besonderen Wert auf die Situation in Sachsen-Anhalt, das in diesem Zeitraum die deutschlandweit niedrigste Beschäftigungsquote aufweist. Die multivariate statistische Analyse liefert Hinweise darauf, dass der Erfüllungsgrad der Beschäftigungspflichtquote nach § 154 SGB IX in stärkerem Ausmaß von soziodemografischen als von ökonomischen Strukturmerkmalen der Länder bestimmt wird. Als Hauptdeterminante tritt in dem hier spezifizierten Modell der Anteil der (registrierten) Schwerbehinderten an der Gesamtbevölkerung hervor. Abstract: Non-Compliance With The Compulsory Employment Quota Of Severely Disabled People – An Empirical Investigation Of Potential Causes At The German Federal State Level This paper examines factors that can explain substantial differences in the employment rate of severely disabled people between the German federal states from 2003 to 2015. It puts special emphasis on the situation in Saxony-Anhalt, which had the lowest employment rate of disabled persons nationwide during this time. The multivariate statistical analysis provides evidence that the degree of compliance with the compulsory employment quote is determined by socio-demographic rather than economic characteristics of the states. Within the specified model, the main determinant of the employment rate appears to be the share of (registered) severely disabled people in the population.

The 2030 Agenda for Sustainable Development at state level: the case of Hesse

2021 ◽  
Vol 30 (3) ◽  
pp. 156-160
Author(s):  
Christian Hey
Keyword(s):  
Sustainable Development ◽  
Development Policy ◽  
State Level ◽  
Federal State ◽  
The Political ◽  
Science Literature ◽  
Sustainability Transformation ◽  
Federal States ◽  
2030 Agenda

The role of the federal states (Länder) in Germany’s sustainability transformation has received comparatively little attention in the political science literature. This article examines the contributions, capacities and competencies of the Länder in relation to Germany’s sustainability transformation with a focus on the role of Hesse. Hesse is a particularly interesting federal state to consider as it introduced a differentiated and demanding sustainable development policy already in 2008.

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

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.

scholarly journals Moving from drought hazard to impact forecasts

2019 ◽  
Vol 10 (1) ◽  
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.

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

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

<p>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.  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 (R<sub>ECO</sub>), 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 R<sub>ECO</sub> 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.</p>

Education of Refugee Adolescents at the End of Secondary School: The Role of Educational Policies, Individual and Family Resources

Soziale Welt ◽  
2020 ◽  
Vol 71 (1-2) ◽  
pp. 160-200
Author(s):  
Gisela Will ◽  
Christoph Homuth
Keyword(s):  
Educational System ◽  
Educational Achievement ◽  
State Level ◽  
Federal State ◽  
Lower Grade ◽  
Ethnic Inequality ◽  
Post Traumatic Stress ◽  
Individual Level ◽  
Federal States ◽  
German Federal States

In the recent wave of refugee immigration to Germany, many children and adolescents were among the migrants. Their integration into the German educational system will be a major challenge for the years and decades to come. The paper’s aim is to examine both general and refugee-specific mechanisms that likely explain ethnic and social inequality in education among refugee adolescents. The study is based on ReGES (Refugees in the German Educational System) data collected in five German federal states. Our results show that refugee adolescents attend lower grade levels and lower school types than the general pupil population in Germany. We further posit that established mechanisms to explain social and ethnic inequality are also applicable to refugee adolescents. Among refugee-specific aspects, we identify factors at the federal state level that influence the school placement of young refugees. Furthermore, at the individual level, post-traumatic stress disorder is associated with differences in educational achievement among refugee students.

scholarly journals Development of the reproduction number from coronavirus SARS-CoV-2 case data in Germany and implications for political measures

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Sahamoddin Khailaie ◽  
Tanmay Mitra ◽  
Arnab Bandyopadhyay ◽  
Marta Schips ◽  
Pietro Mascheroni ◽  
...  
Keyword(s):  
Structural Changes ◽  
Reproduction Number ◽  
National Level ◽  
Transmission Dynamics ◽  
Federal State ◽  
Parameter Estimates ◽  
Time Varying ◽  
Short Term ◽  
Robert Koch Institute ◽  
Federal States

Abstract Background SARS-CoV-2 has induced a worldwide pandemic and subsequent non-pharmaceutical interventions (NPIs) to control the spread of the virus. As in many countries, the SARS-CoV-2 pandemic in Germany has led to a consecutive roll-out of different NPIs. As these NPIs have (largely unknown) adverse effects, targeting them precisely and monitoring their effectiveness are essential. We developed a compartmental infection dynamics model with specific features of SARS-CoV-2 that allows daily estimation of a time-varying reproduction number and published this information openly since the beginning of April 2020. Here, we present the transmission dynamics in Germany over time to understand the effect of NPIs and allow adaptive forecasts of the epidemic progression. Methods We used a data-driven estimation of the evolution of the reproduction number for viral spreading in Germany as well as in all its federal states using our model. Using parameter estimates from literature and, alternatively, with parameters derived from a fit to the initial phase of COVID-19 spread in different regions of Italy, the model was optimized to fit data from the Robert Koch Institute. Results The time-varying reproduction number (Rt) in Germany decreased to <1 in early April 2020, 2–3 weeks after the implementation of NPIs. Partial release of NPIs both nationally and on federal state level correlated with moderate increases in Rt until August 2020. Implications of state-specific Rt on other states and on national level are characterized. Retrospective evaluation of the model shows excellent agreement with the data and usage of inpatient facilities well within the healthcare limit. While short-term predictions may work for a few weeks, long-term projections are complicated by unpredictable structural changes. Conclusions The estimated fraction of immunized population by August 2020 warns of a renewed outbreak upon release of measures. A low detection rate prolongs the delay reaching a low case incidence number upon release, showing the importance of an effective testing-quarantine strategy. We show that real-time monitoring of transmission dynamics is important to evaluate the extent of the outbreak, short-term projections for the burden on the healthcare system, and their response to policy changes.

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