Displays

During 2018-2019 Germany experienced a severe drought which affected 90% of its territory, especially the North and the East. Its consequences have been far-reaching for agriculture, forestry and aquatic ecosystems. Low water levels, including at the Rhine, impaired waterborne transportation, which led to increased energy prices. Furthermore, nuclear power stations lowered their production or shut down and hydropower and industrial outcomes were reduced. Despite these consequences, the inter-sectoral effects of the 2018-2019 German drought are still largely unexplored due to the inherent complexity in their assessment.

This study seeks to close this gap by providing a methodology for characterizing drought impacts and its interdependencies at the district level. The proposed approach allows understanding the compounding and cascading consequences of long-term droughts as a socio-economic and ecosystem disturbance. To this end, we conducted a comprehensive analysis of the 2018-2019 drought impacts across Germany based on a quantitative content analysis of 5.074 newspaper articles published between April 2018 and August 2019. A total of 4.878 unique impacts within 25 sub-categories were identified. These were then analyzed over time and space, aiming to identify emerging trends. Additionally, network analysis was employed to better understand the dynamics and interrelationships between the cross-sectoral impacts. Validation was conducted by carrying out a correlation analysis between the obtained results and the monthly soil moisture index, crop losses statistics and the population drought awareness.

The developed coding system was in 95.4% of the cases accurate, meaning that the proposed approach can provide reliable information for classifying a large amount of data. Results highlight the complex nature of assessing drought impacts, describing the propagation of drought and related direct and indirect impacts across various sectors. Overall, agriculture was severely affected in most of the districts in 2018 whereas impacts on forestry were predominant in 2019. As expected, the reduction of crop productivity was closely interlinked with impacts such as early harvesting of crops, shortage of feed, reduction of livestock, economic losses and need for government assistance. The frequency of the impacts varied regionally, with losses to industry concentrated in Nordrhein-Westfalen and impacts to livestock farming concentrated in Sachsen-Anhalt. To the best of our knowledge, the collected and analyzed impact report data constitutes the first attempt to quantify the cascading effects of drought impacts across NUTS 3 regions. The proposed methodology can be applied to other study areas and results can support policy-planning and inform drought impacts forecasting.

How to cite: Madruga de Brito, M. and Kuhlicke, C.: Cascading effects of the 2018-2019 German drought: empirical evidence from media reports, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9499, https://doi.org/10.5194/egusphere-egu2020-9499, 2020.

An increasing number of mega-cities, such as Cape Town and São Paulo, are confronted with increasing 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, such as drinking water supply, industry, energy production, agriculture, and nature.

Here, we present the WaterLOUPE approach (https://deltares.nl/waterloupe) to estimating water scarcity risk for mega-cities and their surrounding catchment that combines the global model PCR-GLOBWB and global datasets (e.g. Shared Socioeconomic Pathways and OECD Economic Outlook) with local datasets and local expert knowledge. Data and models provide the required information to estimate the water scarcity hazard, level of exposure of the relevant sectors and their vulnerability. With our approach we estimate sector-specific risks at the spatial scale of sub-catchments or municipalities. Moreover, the water scarcity risk is provided both for the current situation and future climatic and socio-economic scenarios.

Our approach has been tested, both technically and through stakeholder workshops, in several case studies (São Paolo, Cape Town, Cali, and Tel Aviv-Yafo). The results of our sector-specific water scarcity risk calculations have shown to reflect the local situation of water users in mega-cities very well. As such, the outcomes of the approach have provided a useful knowledge base that enables stakeholders in the catchment to discuss water scarcity risk, which is a first step to collaboration on mitigation and adaptation strategies to decrease water scarcity risks in mega-cities.

Overall, it can be concluded that although climate change tends to decrease water availability, the main drivers of the water scarcity risk are socioeconomical and are related to the strong growth of water demand and the high vulnerability of specific water users. Generally, it was found that water scarcity risks for poor households, small scale farmers, local businesses and nature are relatively high, also under moderate drought conditions. On the other hand, the risks for industries and non-poor households are low to moderate even in more drought prone areas or periods. In most cases the level of water scarcity risk is expected to increase in the future, underlining the urgency for mega-cities to develop actionable and inclusive strategies to mitigate and adapt to the new normal of increasing water stress.

How to cite: Hendriks, D., Vermooten, S., van Aalst, M., Mulder, N., Morales Irato, D., Hüsken, L., and Faneca Sànchez, M.: Combining global and local models and data for sector-specific water scarcity risk assessments in mega-cities, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20505, https://doi.org/10.5194/egusphere-egu2020-20505, 2020.

Drought risk refers to the potential losses imposed by a drought event, and it is generally characterized as a function of vulnerability, hazard, and exposure. Here, we assess drought risk at a national level across Africa by considering climate change, population growth, and socioeconomic vulnerabilities. Drought vulnerability is quantified using a rigorous multi-dimensional framework based on 28 factors from six different sectors of economy, energy and infrastructure, health, land use, society, and water resources. Various analyses are conducted to assess the reliability and accuracy of the proposed drought vulnerability index (DVI). A multi-model and multi-scenario framework is employed to quantify drought hazard using a multitude of regional climate models. Drought risk is then assessed for 2 climate emission pathways (RCP4.5 and RCP8.5), 3 population scenarios, and 3 future vulnerability scenarios in each country during 2010-2100. Drought risk ratio is calculated for each scenario, and the role of each component (i.e. hazard, vulnerability, and exposure) is identified, and the associated uncertainties are also characterized. Results show that drought risk is expected to increase in future across Africa with varied rates for different models and scenarios. Although northern African countries indicate aggravating drought hazard, drought risk ratio is found to be highest in central African countries as a consequent of unprecedented vulnerability and population rise in the region. Results indicate that controlling the population growth is imperative for mitigating drought risk since it improves socioeconomic vulnerability and reduces potential exposure to drought. Meanwhile, climate change will considerably exacerbate drought and heat-stress hazards. Our findings show that global warming will escalate heat-stress mortality risk across Central Africa to unprecedented levels. It is revealed that unfortunately, the poorest countries (that have least contribution to climate change) are expected to be most impacted, and they will experience markedly higher risk ratios compared to the wealthier nations.

How to cite: Ahmadalipour, A. and Moradkhani, H.: Drought and heat-stress mortality risks: Assessing the role of climate change, socioeconomic vulnerabilities, and population growth, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21415, https://doi.org/10.5194/egusphere-egu2020-21415, 2020.

Numerous drought indices assess only hazard; however, very few indices take account into potential vulnerability and risk. Even though drought is one of the natural disasters that affect the socio-economic sphere, these indices do not reflect social capabilities. As an alternative, we proposed Drought Risk Index (DRI) developed by combining frameworks from Intergovernmental Panel on Climate Change(IPCC) and World Risk Index(WRI). DRI consists of three components such as Hazard, Exposure, Capacity. Hazard represents the reason factor causing damage and computed mainly by climate characteristics (e.g. monthly precipitation) while Exposure considers the objects exposed to disaster and calculates by the amount of the water demand (agricultural, industrial, and municipal sectors). In the case of Capacity, it indicates the ability of society to prepare or handle disasters and subdivides into adaptive and coping capacities; the adaptive capacity is calculated by institutional & financial abilities, and coping capacity by water resource facilities and response abilities. The proposed framework for DRI was tested under the specific focus on the local scale comparison of drought risk as a disaster at the Korean Peninsula. We aim at providing the basic tools for national drought management policies and plans.

How to cite: Jee, H., Kim, H., Kim, D., Kang, T.-H., and Kim, Y.-O.: Development of Drought Risk Assessment Index for Local Comparisons, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21757, https://doi.org/10.5194/egusphere-egu2020-21757, 2020.

Do droughts have a causal effect on economic development? Based on meteorological observations, I construct a global data set of drought events occurring in 183 countries over the period 1960-2018. Identifying the drought exposure for each of earth’s 0.5° x 0.5° grid cell, I maintain the local information of drought shocks which economic agents experience. To identify the causal impact of droughts on long-run economic growth, I model economic growth as an impulse-response function in contemporaneous and historical area-averaged drought exposure. Exploiting the random natural variation in weather realizations as the source for exogenous within-country variation in drought exposure, I find that higher drought exposure causes slower economic development in poor, but not in rich, countries. National incomes in poor countries decline and keep declining 16 years following a drought. Specifically, a one standard deviation increase in drought exposure lowers GDP p.c. by 1.1 percentage points 16 years later. To understood why populations successfully adapt to climatic hazards in some dimensions and fail in others and which factors contribute to (successful) adaptation, I examine through which channels droughts affect economic development and estimate the extent of adaptation to drought.

How to cite: Marbler, A.: Drying Development – The Causal Effect Droughts on (Long-Term) Economic Growth, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21683, https://doi.org/10.5194/egusphere-egu2020-21683, 2020.

Rural migration responses to drought are complex, context specific, and multi-directional. Migration is one of many possible adaptive responses to drought, and is typically initiated only after other, less disruptive strategies have been attempted. The potential for drought to stimulate migration or displacement is inversely related to the range of alternative adaptation options available to households, and is lowered through coordinated vulnerability-reduction mechanisms such as institutional water-management regimes and crop insurance programs. When drought-related migration does occur, it tends to flow along pre-existing social networks to known destinations, which are usually urban centres within the same state/country or in contiguous ones. Using a mixed-methods approach that combines geospatial tools, quantitative methods (i.e. random forest and spatial regression) and qualitative data gathered through archival research and local interviews, we have generated detailed models of the changing influence over time of drought on rural population patterns on the North American Great Plains. In this presentation we highlight key findings from our work, describe data needs and limitations, discuss the predictive power of various quantitative methods, identify non-climatic variables that mediate migration outcomes, and emphasize the importance of mixed-methods approaches.

How to cite: McLeman, R., Grieg, C., Heath, G., and Fontanella, F.: Detection of drought-related human migration and population change on the North American Great Plains, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2096, https://doi.org/10.5194/egusphere-egu2020-2096, 2020.

Droughts affect all the socio-economic sectors and can have negative impacts on the environment. They are expected to increase in frequency and severity due to climate change, which makes their effective management a policy priority. Drought Management Plans (DMPs) are considered to be a key instrument to deal with drought in a proactive way, as they establish a framework for coordinated action when drought sets in. The development of DMPs is still incipient worldwide and the evaluation of their quality and performance is still very limited. In Spain, DMPs at river basin level were first approved in 2007. Following the legal obligation set in the Spanish law, those DMPs were revised after 10 years and a new version was approved in 2018. In order to analyze the adequacy, pertinence and utility of those plans, we developed a protocol based on content analysis for evaluating the DMPs of the eight river basins that are managed by the Spanish Central Government. We set the evaluation criteria using official guidelines and scientific literature on drought preparedness and we compared the first and the second round of DMPs to identify the main improvements, gaps and challenges. The comparison was both qualitative and quantitative, through the establishment of quality criteria/indicators.

The analysis showed that the scope and content of the DMPs is more homogeneous and consistent in 2018 than in 2007. Some aspects have clearly improved between the two planning periods, like the distinction between drought and water scarcity, the definition of indices to trigger different levels of drought alert and the inclusion of measures for drought management and coordination. Other issues still need further improvements, especially those related to the analysis of drought impacts, the assessment of vulnerability and the ex-post evaluation of DPM performance.

The DMPs developed for the Júcar and Segura river basins, both located in the Mediterranean region and prone to severe droughts, received the highest score according to our assessment criteria. All the DMPs show some improvements between 2007 and 2018, but the largest increase corresponds to the Duero river basin while the least is for the Júcar.

How to cite: Urquijo Reguera, J., Gómez Villarino, M. T., and De Stefano, L.: Drought Management Plans in Spain: Are we improving the way we manage drought? , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21519, https://doi.org/10.5194/egusphere-egu2020-21519, 2020.

Drought is a recurrent global phenomenon considered one of the most complex hazards with manifold impacts on communities, ecosystems, and economies. While many sectors are affected by drought, agriculture’s high dependency on water makes it particularly susceptible to droughts, threatening the livelihoods of many, and hampering the achievement of the Sustainable Development Goals. Identifying pathways towards more drought resilient societies by analyzing the drivers and spatial patterns of drought risk is of increasing importance for the identification, prioritization and planning of risk reduction, risk transfer and adaptation options. While major progress has been made regarding the mapping, prediction and monitoring of drought events at different spatial scales (local to global), comprehensive drought risk assessments that consider the complex interaction of drought hazards, exposure and vulnerability factors are still the exception.

Here, we present, for the first time, a global-scale drought risk assessment at national level for both irrigated and rain-fed agricultural systems. The analysis integrates (1) composite drought hazard indicators based on historical climate conditions (1980-2016), (2) exposure data represented by the harvest area of irrigated and rainfed systems, and (3) an expert-weighted set of social-ecological vulnerability indicators. The latter were identified through a systematic review of literature (n = 105 peer-reviewed articles) and expert consultations (n = 78 experts). This study attempted to characterize the average drought risk for the whole study period.

Results show that drought risk of rain-fed and irrigated agricultural systems display different heterogeneous patterns at the global level with higher risk for southeastern Europe, as well as northern and southern Africa. The vulnerability to drought highlights the relevance to increase the countries’ coping capacity in order to reduce their overall drought risk. For instance, the United States, which despite being highly exposed to drought hazard, has low socio-ecological susceptibility and sufficiently high coping capacities to reduce the overall drought risk considerably. When comparing irrigated and rain-fed drought hazard/exposure, there are significant regional differences. For example, the northern part  of Central Africa and South America have low hazard/exposure levels of irrigated crops, resulting in a low total risk, although high vulnerability characterize these regions. South Africa, however, has a high amount of rain-fed crops exposed to drought, but a lower vulnerability compared to other African countries. Further, the drivers of drought risk vary substantially across and within countries, calling for spatially targeted risk reduction and adaptation options.

Findings from this study underline the relevance of analyzing drought risk from a holistic and integrated perspective that brings together data from different sources and disciplines and based on a spatially explicit approach. Being based on open-source data, the approach allows for reproduction in varying regions and for different spatial scales, and can serve as a blueprint for future drought risk assessments for other affected sectors, such as water supply, tourism, or energy. By providing information on the underlying drivers and patterns of drought risk, this approach supports the identification of priority regions and provides entry points for targeted drought risk reduction and adaptation options to move towards resilient agricultural systems.

How to cite: Meza, I., Siebert, S., Döll, P., Kusche, J., Herbert, C., Eyshi Rezaei, E., Nouri, H., Gerdener, H., Popat, E., Frischen, J., Naumann, G., Vogt, J. V., Walz, Y., Sebesvari, Z., and Hagenlocher, M.: A spatially explicit assessment of drought risk for irrigated and rainfed agricultural systems at the global scale, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19544, https://doi.org/10.5194/egusphere-egu2020-19544, 2020.

This study is aimed to establish an approach for estimating drought vulnerability using multi criterion decision making methods. Drought has spatially wide-ranging effects, its duration is difficult to predict, and long-lasting damages. For this reason, the conversion of drought damage into an amount of money or physical quantity is difficult. Accordingly, policy makers and researchers have difficulty in securing grounds for determining countermeasures against drought disasters. Thus, to determine drought vulnerability, factors with long-term impact on social and economics need to be taken into account. The evaluation approach consisted of three stages: evaluation factor and weight identification, database construction, evaluation data and weight combination. In this study, the factors to assessing drought vulnerability was identified using Delphi method, and the drought vulnerability was determined by the TOPSIS method which is a widely used MCDM method.

How to cite: Lee, G., Jun, K. S., and Kwon, M.: An approach to assess drought vulnerability with multi criteria analysis , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7556, https://doi.org/10.5194/egusphere-egu2020-7556, 2020.

This abstract is for SUPPORT APPLICATION.

Drought is the most significant stress that reduces crop yield, hence, agricultural irrigation is the major consumer of freshwater worldwide. There is everlasting need to improve irrigation applications in order to increase water use efficiency and save water. Conventional methods to estimate crop water status and within-field variability are precise, yet, highly demanding for time and manpower. Remote sensing in the reflective and the emissive spectrum with unmanned aerial vehicle (UAV) holds potential to detect drought stress by observing canopy status over a larger area. A common method to detect drought stress using UAV thermal imagery is the Crop Water Stress Index (CWSI), which does needs improvement and parametrization for cereal crops such as winter wheat.
Field experiment with winter wheat was performed in 24 plots (30 m x 30 m) under three different irrigation regimes in 2018 (drought year) and 2019 (normal year) in Denmark. Thermal and multispectral data on UAV scale were collected during the growth period. Plant physiology, i.e., stomatal conductance, leaf water potential and canopy cover was measured, in addition to soil water content. Crop water deficit was estimated through comparison of the variability of canopy temperature and plant physiological changes. The resulting correlation pointed on clear possibility to quantify crop water status using thermal data, which is useful to develop a site-specific application of irrigation. Further work involves parameterization of CWSI and calculation of and comparison with other indices to test for improvements.

How to cite: Antoniuk, V., Peng, J., Manevski, K., Sørensen, K. K., Larsen, R., and Andersen, M. N.: Understanding drought stress in winter wheat using UAV thermal and multispectral data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1204, https://doi.org/10.5194/egusphere-egu2020-1204, 2020.

By an additional 83 million people to the world’s population every day, the global population is expected to reach about 9.8 billion by 2050. Feeding these billions is one of the challenges of this century, and extreme events like droughts bring more complexity to the challenge of global food security. Previous agricultural drought studies on the regional or national scale revealed that drought affects specific crops differently; however, these studies are limited to a few major crops or specific regions. Here we analyse for the first time, to our knowledge, crop responses to drought for 25 rainfed crops on a global scale and differentiate crop responses to aridity and drought for thirty years (1986-2016). We use actual and potential crop evapotranspiration calculated by the Global Crop Water Model (GCWM) and develop the two indicators of Crop Drought Index (CDI) and Aridity Index (AI) to investigate the effect of water stress on crop production worldwide. We show crops’ behaviours in extreme drought events differ in time and space. Years with the most severe drought events also differed for the specific crops. To interpret the impacts of drought and aridity on individual crops in specific locations, and avoid any misperception on their potential damages, we map crop-specific AI and crop-specific CDI of all 25 crops during the study period. We compare the spatio-temporal variation of CDI against a global map of AI for each crop to reflect different impacts of long-term water stress experience (aridity) against extreme events (drought). We learn different crops have different responses to aridity and drought. Our findings are of critical importance for drought-resilient agricultural plans and may help to guide the implementation of food security and food aid strategies.

How to cite: Nouri, H., Eyshi Rezaei, E., and Siebert, S.: Drought impact assessments for crop production need to be crop-specific, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5453, https://doi.org/10.5194/egusphere-egu2020-5453, 2020.

Rice is a staple food in the North and South Koreas. Rice yield is closely related to water supply including irrigation, precipitation, and soil water. Drought typically occurs due to the lack of precipitation, and prolonged drought leads to the decrease of soil water, which results in plant water stress. Drought monitoring is crucial for agricultural mitigation because it enables us to estimate rice production in a timely manner. The purpose of this study is to suggest an optimal drought index for monitoring agricultural drought over North and South Koreas. Although North and South Koreas have similar climate conditions, they have different levels of infrastructure for agriculture such as irrigation facilities. In this study, nine satellite-based drought indices were used and evaluated based on in situ measurements at weather stations including Standardized Precipitation Index (SPI) and rice yield. Drought indices were calculated using the Global Land Data Assimilation System (GLDAS) soil moisture, Tropical Rainfall Measuring Mission (TRMM) precipitation, Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI). Since various drought indices have been developed with their own purpose, considering the characteristics of the study area under investigation, their applications for other regions are relatively limited. Thus, comparison of various drought indices is needed to identify an optimal drought index for a certain area. The measurable objectives of this research were to 1) compare the characteristics of drought depending on the properties of drought indices such as temperature, vegetation, precipitation, and soil moisture and 2) evaluate various drought indices using SPIs and rice yield data. The performance of the drought indices was evaluated using correlation coefficient values (R) for reference data (i.e., SPI and rice yield). As expected, drought indices including NDVI showed positive relationships with rice yield in both regions (averaged R=0.37). Meanwhile, temperature based drought indices showed negative relationships with rice yield in both regions because high temperature means high solar radiation, which is essential to rice production. While the correlation coefficient between precipitation based indices and rice yield was positive in North Korea (averaged R=0.34), it was negative in South Korea (averaged R=-0.26). The opposite pattern by area is because South Korea (117,457 irrigation Canals) has more artificial controls over agricultural land such as irrigation facilities and reservoirs than North Korea (51,400 irrigation Canals).

How to cite: Park, S., Yeom, J., Lee, J., Lee, J., Im, J., Lee, H., Kim, H., and Chae, T.-B.: Sensitivity analysis of drought indices under substantially different agricultural systems in North and South Koreas, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8491, https://doi.org/10.5194/egusphere-egu2020-8491, 2020.

Droughts affect more people around the world than any other natural hazard and are projected to intensify due to climate change. Droughts have traditionally been divided into four broad categories: socio-economic, meteorological, agricultural, and hydrological. While the common cause for drought is abnormally low precipitation, different drought types may be caused by other factors, such as increased evaporation or anthropogenic influence.

The different drought types are often studied separately, but they are not independent of each other and they often co-occur. We quantify the co-occurrence of meteorological, agricultural, and hydrological droughts at global scale, to our knowledge for the first time. We use the 3-month Standardised Precipitation and Evaporation Index (SPEI), 1-month Soil Moisture Anomaly (SMA) and 3-month Standardised Streamflow Index (SSI) as proxies for meteorological, agricultural, and hydrological droughts, respectively. We compute the drought indices for globally at sub-basin scale for years 1981-2010, using the newly published HydroATLAS level 8 catchments (average size of approximately 750 km²) as spatial units. Each unique meteorological, agricultural, and hydrological drought event is characterised by the commonly used duration, intensity and severity metrics. The co-occurrence of different severe drought events is defined by using the spatial and temporal intersection of the identified events. We analyse the co-occurrence of severe drought events using Association Rules data mining method in order to quantify the relationship between the drought types, and their co-occurrence.

Our results indicate that the global average probability of co-occurrence of all three drought types in a single drought event is 30%. The probability of the occurrence of a single drought type is 61% (SMA), 64% (SPEI) and 69% (SSI) of all unique drought events. However, these figures vary considerably between continents. Interestingly, we find that SMA and SPEI are poor predictors to SSI, which might be attributed to the different nature of the processes, as streamflow is affected by upstream conditions. Precipitation and soil moisture are more local processes with weaker links to anthropogenic influence, irrigated areas being an obvious exception. We also detect an increasing global trend in severe drought events and the co-occurrence of drought types. Our results, however, are likely sensitive to the chosen indices, thresholds and the definition of co-occurrence, thus further studies are needed.

We argue that quantifying the co-occurrence of different drought types provides important information for early warning systems and drought management planning. It may also be useful for the development of comprehensive composite drought indicators. Understanding the linkages between drought types may support longer-term, proactive drought management planning that is better tailored to regional climates.

How to cite: Ahopelto, L., Kallio, M., Heino, M., Kinnunen, P., Fallon, A., and Kummu, M.: Quantifying the co-occurrence of hydrological, meteorological, and agricultural droughts on a global scale, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7960, https://doi.org/10.5194/egusphere-egu2020-7960, 2020.

A variety of drought indices have been constructed to monitor agricultural drought using ground and satellite data. Our study aimed to evaluate the performance of drought indices to indicate agricultural drought in China. Seven drought indices of four types were selected over the main agricultural regions of China: indices based on regular meteorological data (DI_met), indices based on vegetation index (DI_vi), indices based on soil moisture (DI_sm), and synthesized indices (DI_syn). The independent reference data used here included three aspects: soil moisture, vegetation photosynthesis and crop yield data. The latter two reference datasets were selected to check drought impact on agriculture. Drought indices with short timescales are more sensitive to topsoil moisture. Drought indices have different abilities to capture vegetation photosynthesis condition during the growing season. Expect for the Yangtze region and North China region during the wheat growing season, the DI_met and DI_syn show significant positive correlations with the sun-induced chlorophyll fluorescence (SIF), while the other drought indices have weaker or no correlations. For crop yield, the prediction ability of the drought indices show a similar pattern with the results for vegetation photosynthesis but with relatively large uncertainty. Generally, our study show that DI_met have better or equivalent performance than that of the other types of drought indices, and DI_syn show the widest applicability. Our study may shed light on agricultural drought research in the future.

How to cite: Zhao, Z. and Wang, K.: Capability of existing drought indices in reflecting agricultural drought in China, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8845, https://doi.org/10.5194/egusphere-egu2020-8845, 2020.

This study presents a new methodology for spatially explicit and globally applicable drought hazard, vulnerability and risk modelling. We focused on agricultural droughts since this sector affects the food security and livelihood situation of the often most vulnerable communities especially in developing countries. Despite recent advances in drought modeling, coherent and spatially explicit information on drought hazard, vulnerability is still lacking over wider areas. In this study a spatially explicit inter-operational drought hazard, vulnerability and risk modeling framework was investigated for agricultural land, grassland and shrubland areas. The developed drought hazard model operates on a higher spatial resolution than most available global drought models while also being scalable to other regions. Initially, a logistic regression model was developed to predict drought hazard for rangelands and cropland in the USA. The model results showed a good spatiotemporal agreement within the cross-verification with the United States Drought Monitor (USDM), using visual interpretation. Subsequently, the explicit and accurate drought hazard model was transferred and calibrated for South Africa and Zimbabwe, where a simplified drought risk indicator was calculated by the combination of drought hazard and drought vulnerability. The drought hazard model used time series crop yields data from the Food and Agriculture Organization Corporate Statistical Database (FAOSTAT) and biophysical predictors from satellite remote sensing (SPI, NDII, NDVI, LST, albedo). The McFadden’s Pseudo R² value of 0.17 indicated a good model fit for drought hazard in South Africa. Additionally, the plausibility of the model results in Southern Africa was evaluated by using regional climate patterns, published drought reports and through visual comparison to a global drought risk model and food security classification data. Drought risk and vulnerability were also assessed for Southern Africa and could be mapped in a spatially explicit manner, showing, for example, lower drought risk and vulnerability over irrigated areas. This developed modeling framework can be applied globally, since it uses globally available datasets and therefore can be easily modified to account for country-specific conditions. Additionally, it can also capture regional drought patterns on a higher spatial resolution than other existing global drought models. This model addressed the gap between global drought models, that cannot accurately capture regional droughts, and sub-regional models that may be spatially explicit but not spatially coherent. The approach of this study can potentially be used to identify risk and priority areas and possibly in an early warning capacity while enhancing existing drought monitoring routines, drought intervention strategies and the implementation of preparedness measures.  

How to cite: Schwarz, M., Landmann, T., Cornish, N., Wetzel, K.-F., Siebert, S., and Franke, J.: A Spatially Transferable Drought Hazard and Drought Risk Modeling Approach Based on Remote Sensing Data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8986, https://doi.org/10.5194/egusphere-egu2020-8986, 2020.

Recently, climate change due to global warming has been frequented by large-scale weather disasters that have not been experienced in the past. Among various weather disasters, drought is one of the representative weather disasters in Korea recently along with heavy rains. In the case of drought, it occurs in a wide range in the short term and long term, and it is difficult to identify specific occurrence times, places, and causes, and damage and influence are enormous.

In the past, the Republic of Korea has been prepared with non-structural measures such as securing irrigation water for drought restoration, developing emergency management, and developing a drought information system based on drought index. The reduction measures for drought degradation were mainly used by Palmer Draught Severity Index (PDSI), Standardized Precision Index (SPI), Crop Moisture Index (CMI), Crop Specific Drug Index (CMI), and Profication (DICS Index), and Survey.

In this study, we intend to establish standards for reducing drought damage by investigating and analyzing drought damage characteristics in Korea. In the past, drought damage in Korea occurred in agriculture, living and industry, and the ministry manages and stores the data on drought damage. The drought damage in South Korea from 1965 to 2018 occurred a total of 204 times, mostly in South Gyeongsang and South Jeolla provinces, rather than in special cities and metropolitan cities. The purpose of this study is to analyze the characteristics of drought damage in Korea and establish the measures to reduce mega drought.

Acknowledges : This research was supported by a grant(2019-MOIS31-010) from Fundamental Technology Development Program for Extreme Disaster Response funded by Korean Ministry of Interior and Safety(MOIS).

How to cite: MooJong, P., Youngseok, S., Heesup, L., and Juhyeok, P.: A Study on the Establishment of Criteria for Reduction measures of Mega Drought in Korea, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11950, https://doi.org/10.5194/egusphere-egu2020-11950, 2020.

Due to the effects of extreme weather conditions, extreme disasters such as floods and droughts are becoming more frequent worldwide.

In particular, drought is one of the long-term disasters unlike floods, with the greatest damage occurring in the agricultural sector in the event of a drought disaster.

This study investigated and analyzed the history of drought damage in Korea in the past, how the government responded to drought, and how to calculate the amount of drought damage in agriculture.

Based on the survey and analysis data, the methods for calculating agricultural drought damage in the past were supplemented, and realistic and practical methods for calculating agricultural drought damage were developed in consideration of regional characteristics in future drought disasters.

This research was supported by a grant(2019-MOIS31-010) from Fundamental Technology Development Program for Extreme Disaster Response funded by Korean Ministry of Interior and Safety(MOIS).

How to cite: Heesup, L. and moojong, P.: Development of Agricultural Damage Estimation Technique Considering Regional Characteristics, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12413, https://doi.org/10.5194/egusphere-egu2020-12413, 2020.

In recent years, the number of extreme disasters such as floods, droughts, and heat waves worldwide has been increasing. In the case of droughts, it is most important to manage water that is most closely related to human life in the event of a disaster and to anticipate and respond to damage in advance.

In this study, the methods for calculating domestic and foreign life and industrial water damage were reviewed, and the methods for estimating the amount of drought damages were developed so that local disaster managers could make decisions in the event of a drought, based on the living and industrial water data, which contained quantitative data.

How to cite: Park, J. and Park, M.: Development of a Drought Damage Estimation Technique for Living and Industrial Water Using Water Estimation Technique, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12471, https://doi.org/10.5194/egusphere-egu2020-12471, 2020.

Drought is rarely associated with Alpine regions, but as documented in recent years droughts have caused a variety of impacts even in these humid mountain climates. Accordingly, a reduction of vulnerability to drought in Alpine and pre-Alpine regions is required in order to minimize future impacts from upstream to downstream areas and across political boundaries. Therefore, sound information of Alpine droughts as well as knowledge of their impacts is essential. But drought-specific data on the multiple economic losses in mountain regions are scarce and may differ from the usually assessed agriculturally-dominated lowlands. This study aims to clarify todays state of the art on drought impact information in Alpine regions and claims data needs for a comprehensive understanding of Alpine drought risk. More specifically, the objective is to systematically assess the differences of impacts specific to the Alpine region compared to non-Alpine regions. The hypothesis is that specific climate conditions due to the heterogeneous terrain and high altitudes determine the Alpine environment as well as the economical practices and societal adaptations, which differ strongly from lowlands. Subsequently, the sectoral-impacts in mountain regions might vary substantially, especially with regard to the onset and severity of impacts as well as their spatial and temporal extend. The European Drought Impact Report Inventory (EDII) compiles knowledge on the impacts of drought events across Europe from a variety of information sources based on more than 10,000 reported impacts. The current content of the EDIIs database was filtered to the Alpine Space region which make up about 15 % of all entries in all 15 main categories of the classification system. The main affected sectors are ‘agriculture and livestock farming’,’ ‘public water supply’ and ‘energy and industry’. The high proportion of impacts in the latter category is a main difference in the distribution of impacts compared to that of entire Europe. For the individual Alpine countries and regarding the detailed subtypes of the impacts, however, substantial variability was found among the different countries. To obtain a comprehensive risk assessment further research has to establish novel ways to collect more regional impact information for these strongly heterogeneous research areas, with respect to climate, topography and report languages.

How to cite: Stephan, R., Erfurt, M., Blauhut, V., and Stahl, K.: Drought impacts in Alpine regions – classifying and investigating the most affected sectors in heterogeneous mountain terrain , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1639, https://doi.org/10.5194/egusphere-egu2020-1639, 2020.

Unlike natural disasters such as typhoons, torrential rains and floods, drought is a disaster caused by long-term effects as well as short-term effects. The effect of drought is caused by damage from a short period of weeks to a long period of years, which causes extensive and enormous damage to agriculture, life, society and economy. In addition, the recent climate change has affected the frequency and scale of rainfall in the global temperature, so it is necessary to prepare measures against it.

The past studies on drought have been conducted using drought indexes such as agricultural, meteorological, and hydrological methods to evaluate drought. The representative drought indexes for each drought are Palmer Drought Severity Index (PDSI), Standardized Precipitation Index (SPI), Agricultural drought is Crop Moisture Index (CMI), Crop Specific Drought Index (CSDI), Hydrological drought is Surface Drought Water Supply Index (SWSI), Reclamation Drought Index (RDI) and so on are used. However, these drought indices are only used as a method of predicting the depth of drought, and do not give the actual number of drought occurrences.

In this study, we want to determine the frequency of Mega-drought occurrences in consideration of the drought damage characteristics that occurred worldwide from 1900 to 2018. The drought damages in the world were used by EM-DAT (the Emergency Events Database) which manages disaster data in CRED (Centre for Research on the Epidemiology of Disasters). Drought damages occurred in the world from 1900 to 2018 occurred more than once/years in 146 countries. The duration of drought persistence occurred in the country continuously for at least one to 17 years. The purpose of this study is to propose the criteria for mega drought by using the past victim data in connection with the incidence frequency.

Acknowledges : This research was supported by a grant(2019-MOIS31-010) from Fundamental Technology Development Program for Extreme Disaster Response funded by Korean Ministry of Interior and Safety(MOIS).

How to cite: Youngseok, S., Jinbok, K., Jongun, P., and Moojong, P.: A Study on the Estimation of the Occurrence Frequency of Mega-drought by the Characteristics of Drought Damage , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11927, https://doi.org/10.5194/egusphere-egu2020-11927, 2020.

Variations in forest net primary productivity (NPP) reflects the combined effects of key climate variables on ecosystem structure and function, especially on the carbon cycle. We performed risk analysis indicated by the magnitude of future negative anomalies in NPP in comparison with the natural interannual variability to investigate the impact of future climatic projections on forests in China. The analysis was conducted mainly based on modifying the Lund–Potsdam–Jena Dynamic Global Vegetation Model, which was driven by five general circulation models (GCMs) simulations. Results from the multi-model ensemble showed that climate change risk of decreases in forest NPP would be more significant in higher emission scenario in China. Under relatively low emission scenarios, the total area of risk was predicted to decline, while for RCP8.5, it was predicted to first decrease and then increase after the middle of 21st century. The rapid temperature increases predicted under the RCP8.5 scenario would be probably unfavorable for forest vegetation growth in the long term. High-level risk area was likely to increase except RCP2.6. The percentage area at high risk was predicted to increase from 5.39% (2021–2050) to 27.62% (2071–2099) under RCP8.5. Climate change risk to forests was mostly concentrated in southern subtropical and tropical regions, generally significant under high emission scenario of RCP8.5, which was mainly attributed to the intensified dryness in south China.

How to cite: Yin, Y., Ma, D., and Wu, S.: Future climate change risk to forests in China responding to intensified dryness, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21052, https://doi.org/10.5194/egusphere-egu2020-21052, 2020.