A global-scale relationship between crop yield anomaly and multiscalar drought index based on multiple precipitation data

Drought impact on crop production is well known as crop yield is strongly controlled by climate variation. Previous studies assessed the drought impact using a drought index based on a single input data set, while the variability of the drought index to the input data choice is notable. In this study, a drought index based on the Standardized Precipitation Index with multiple timescales using several global precipitation datasets was compared with the detrended anomaly based on the global dataset of historical yield for major crops over 1981-2016. Results show that the drought index based on the ensemble precipitation dataset correlates better with the crop yield anomaly than a single dataset. Based on the drought index using ensemble datasets, global crop areas significantly affected by drought during the study period were around 23, 8, 30, and 29% for maize, rice, soybean, and wheat, respectively, induced mainly by medium to longer drought timescale (5 – 12-months). This study indicates that most crops cultivated in dry regions were affected by droughts worldwide, while rice shows less correlation to drought as it is generally irrigated and cultivated in humid regions with less drought exposure. This study provides a valuable framework for data choices in drought index development and a better knowledge of the drought impact on agriculture using different timescales on a global scale towards understanding crop vulnerability to climate disruptions.

Threshold Response to Extreme Drought Shifts Inter-Tree Growth Dominance in Pinus sylvestris

Many studies quantify short-term drought impact on tree growth relative to pre-drought growth averages. However, fewer studies examine the extent to which droughts of differing severity differentially impact tree growth or shape stand dynamics. Focusing on three droughts in high and low density stands of Pinus sylvestris in Scotland, we calculated pre-drought growth averages using climatically standardized antecedent growth years to assess tree level drought and post-drought growth performance as percentage growth change (PGC). We then used mixed-effects models to understand how droughts of differing severity impact tree growth and calculated indices of growth dominance (Gd), size inequality (Si), and size asymmetry (Sa) to detect changes in stand structure. Mixed-effects model results indicate that the magnitude and duration of the growth reduction during and following the more extreme drought was significantly larger compared to less severe droughts, for which we found limited evidence of drought impact. While no changes in Si or Sa were noted following any drought, we found evidence of a difference in Gd after the most extreme drought in both stand densities indicative of a threshold response, with smaller trees contributing proportionally more to stand growth relative to their size. Under less severe droughts, inter-tree variability may have partially buffered against stand-level growth change, however, a small increase in drought severity was associated with a significant reduction in average tree growth, an increase in the number of trees growing at >2SD below pre-drought levels and a shift in Gd toward smaller trees, indicating that a drought severity threshold in P. sylvestris may have been exceeded.

A CONUS-wide Standardized Precipitation-Evapotranspiration Index for Major US Row Crops

Agricultural droughts afflicting the contiguous United States (CONUS) are serious and costly natural hazards. Widespread damage to a single cash crop may be crippling to rural communities that produce it. While drought is insidious in nature, drought indices derived from meteorological data and drought impact reports both provide essential guidance to decision makers about the location and intensity of developing and ongoing droughts. However, response to dry meteorological conditions is not consistent from one crop type to the next, making crop-specific drought appraisal difficult using weather data alone. Additionally, drought impact reports are often subjective, latent, or both. To rectify this, we developed drought indices using meteorological data, and phenological information for the row crops most commonly grown over CONUS: corn, soybeans, and winter wheat. These are referred to as crop-specific standardized precipitation-evapotranspiration indices (CSPEIs). CSPEIs correlate more closely with end-of-season yields than traditional meteorological indicators for the eastern two thirds of CONUS for corn, and offer an advantage in predicting winter wheat yields for the High Plains. CSPEIs do not always explain a higher fraction of variance than traditional meteorological indicators. In such cases, results provide insight on which meteorological indicators to use to most effectively supplement impacts information.

An inventory of Alpine drought impact reports to explore past droughts in a mountain region

Drought affects the European Alpine mountain region, despite a humid climate. Droughts' damaging character in the past and increasing probability in future projections call for an understanding of drought impacts in the mountain regions. The European Drought Impact report Inventory (EDII) collects text reports on negative drought impacts. This study presents a considerably updated EDII focusing on the Alpine region. This first version release of an Alpine Drought Impact report Inventory (EDIIALPS) classifies impact reports into categories covering various affected sectors and enables comparisons of the drought impact characteristics. We analysed the distribution of reported impacts on the spatial, temporal and seasonal scale and by drought type for soil moisture drought and hydrological drought. For the spatial analysis, we compared the impact data located in the Alpine region to the whole of Europe. Furthermore, we compared impact data between different climatic and altitudinal domains (the northern region vs. the southern region and the pre-Alpine region vs. the high-altitude region) and between the Alpine countries. Compared to the whole of Europe, in the Alpine region agriculture and livestock farming impacts are even more frequently reported, especially in the southern region. Public water supply is the second most relevant sector but overall less prominent compared to Europe, especially in spring when snowmelt mitigates water shortages. Impacts occur mostly in summer and early autumn, with a delay between those impacts initiated by soil moisture and those initiated by hydrological drought. The high-altitude region shows this delay the strongest. From 1975 to 2020, the number of archived reports increases, with substantially more impacts noted during the drought events of 1976, 2003, 2015 and 2018. Moreover, reported impacts diversify from agricultural dominance to multi-faceted impact types covering forestry, water quality, industry and so forth. Though EDIIALPS is biased by reporting behaviour, the region-specific results of negative drought impacts across the water-rich European mountain region demonstrate the need to move from emergency response to prevention and preparedness actions. These may be guided by EDIIALPS' insights to regional patterns, seasons and drought types.

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

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.

Identifying the Drought Impact Factors and Developing Drought Scenarios using the DSD Model

Due to climate change, droughts have become increasingly severe and frequent. Droughts do not simply create water scarcity but also various socio-economic issues. Therefore, it is necessary to manage droughts on the government level through water resource management policies that consider drought conditions. The drought characteristics within each administrative division need to be closely analyzed for effective policy. In this study, a drought impact factor analysis using the DSD model was presented as a method. Through the relationship between various hydrometeorological factors and drought index, the drought impact factor was identified for each area. For South Korea, meteorological factors have a greater impact on droughts than hydrological factors. Identified drought impact factors are analyzed depending on spatio-temporal variability to recognize the features in various aspects of droughts. For the temporal variability, water demand change and severe drought period are considered. Also, for the spatial variability, based on the type of water demand, administrative divisions are grouped into four zones and analyzed accordingly. Finally, a drought scenario based on identified drought impact factor was constructed to present the probable drought conditions in the future. Components of drought scenario reflect the organization of water resources within an area and it combine the each level of components. Through the constructed drought scenarios, it is possible to establish an effective policy for managing water resources considering the drought condition.

Drought impact links to meteorological drought indicators and predictability in Spain

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.

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

<p>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.</p><p>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  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 Niño/La Niña 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.</p><p>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.</p>