Model Comparisons Between Canonical Vine Copulas and Meta-Gaussian for Agricultural Drought Forecasting over China

Agricultural drought is caused by reduced soil moisture and precipitation and affects the growth of crops and vegetation, and in turn agricultural production and food security. For developing measures for drought mitigation, reliable agricultural drought forecasting is essential. In this study, we developed an agricultural drought forecasting model based on canonical vine copulas under three-dimensions (3C-vine model), in which the antecedent meteorological drought and agricultural drought persistence were utilized as predictors. Besides, the meta-Gaussian (MG) model was selected as a reference model to evaluate the forecast skill. The agricultural drought in August of 2018 was selected as a case study, and the spatial patterns of 1–3-month lead forecasts of agricultural drought utilizing the 3C-vine model resembled the corresponding observations, indicating the predictive ability of the model. The performance metrics (NSE, R2, and RMSE) showed that the 3C-vine model outperformed the MG model for August under diverse lead times. Also, the 3C-vine model exhibited excellent forecast skills in capturing the extreme agricultural drought over different selected typical regions. This study may help with drought early warning, drought mitigation, and water resources scheduling.

Drought Early Warning in Agri-Food Systems

Droughts will increase in frequency, intensity, duration, and spread under climate change. Drought affects numerous sectors in society and the natural environment, including short-term reduced crop production, social conflict over water allocation, severe outmigration, and eventual famine. Early action can prevent escalation of impacts, requiring drought early warning systems (DEWSs) that give current assessments and sufficient notice for active risk management. While most droughts are relatively slow in onset, often resulting in late responses, flash droughts are becoming more frequent, and their sudden onset poses challenging demands on DEWSs for timely communication. We examine several DEWSs at global, regional, and national scales, with a special emphasis on agri-food systems. Many of these have been successful, such as some of the responses to 2015–2017 droughts in Africa and Latin America. Successful examples show that early involvement of stakeholders, from DEWS development to implementation, is crucial. In addition, regional and global cooperation can cross-fertilize with new ideas, reduce reaction time, and raise efficiency. Broadening partnerships also includes recruiting citizen science and including seemingly subjective indigenous knowledge that can improve monitoring, data collection, and uptake of response measures. More precise and more useful DEWSs in agri-food systems will prove even more cost-effective in averting the need for emergency responses, improving global food security.

An Agro-Pastoral Phenological Water Balance Framework for Monitoring and Predicting Growing Season Water Deficits and Drought Stress

Sharing simple ideas across a broad community of practitioners helps them to work together more effectively. For this reason, drought early warning systems spend a considerable effort on describing how hazards are detected and defined. Well-articulated definitions of drought provide a shared basis for collaboration, response planning, and impact mitigation. One very useful measure of agricultural drought stress has been the “Water Requirement Satisfaction Index” (WRSI). In this study, we develop a new, simpler metric of water requirement satisfaction, the Phenological Water Balance (PWB). We describe this metric, compare it to WRSI and yield statistics in a food-insecure region (east Africa), and show how it can be easily combined with analog-based rainfall forecasts to produce end-of-season estimates of growing season water deficits. In dry areas, the simpler PWB metric is very similar to the WRSI. In these regions, we show that the coupling between rainfall deficits and increased reference evapotranspiration amplifies the impacts of droughts. In wet areas, on the other hand, our new metric provides useful information about water excess—seasons that are so wet that they may not be conducive to good agricultural outcomes. Finally, we present a PWB-based forecast example, demonstrating how this framework can be easily used to translate assumptions about seasonal rainfall outcomes into predictions of growing season water deficits. Effective humanitarian relief efforts rely on early projections of these deficits to design and deploy appropriate targeted responses. At present, it is difficult to combine gridded satellite-gauge precipitation forecasts with climate forecasts. Our new metric helps overcome this obstacle. Future extensions could use the water requirement framework to contextualize other water supply indicators, like actual evapotranspiration values derived from satellite observations or hydrologic models.

Evaluating the effects of human regulation on development and recovery characteristics of hydrological drought in a semi-arid area

<p>Understanding the impacts of human regulation on development and recovery characteristics of hydrological drought is crucial to detect the relationship between hydrological drought and the regional water cycle system. In this study the standardized streamflow index (SSI) which based on the observation and SWAT simulated runoff data were used to represent the hydrological drought under human disturbed and naturalized scenarios, respectively. Furthermore, the hydrological drought events under each scenario was divided into the development and recovery stages by the run theory. Comparing two scenarios under the stage Ⅰ (1980-1989) and stage Ⅱ (2007-2016), the human disturbed scenario presents a more severe hydrological drought than the naturalized scenario at stage Ⅱ. Our study further found that the reservoir operation was the irreplaceable factor that affected hydrological drought development and recovery in the study area. The reservoir has the strong ability to alleviate the long-duration hydrological droughts, however, the recovery ability of drought has been weakened. To be noticed that though the water intake from the river by the reservoir has been reduced, the drought alleviates ability of the reservoir still become weaker than prototype after working for 30 years. Therefore, as time goes on the effects of reservoir will become progressively more important. The results of our study could be a hint for policymakers and stakeholders to enhance the drought early warning and forecasting system to optimal reservoirs’ management at semi-arid areas.</p>

Selecting indicators of drought impacts: the importance of context

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

Fluctuating Rainfall, Persistent Food Crisis—Use of Rainfall Data in the Kenyan Drought Early Warning System

Early warning systems (EWSs) have been developed to trigger timely action to disasters, yet persistent humanitarian crises resulting from hazards such as drought indicate that these systems need improvements. We focus our research on the county of Turkana in Kenya, where drought repeatedly results in humanitarian crises, especially with regard to food insecurity. Focusing on the key elements of the Kenyan EWS, we ask two questions: firstly, what indicators, especially meteorological drought indicators, are used in the national biannual assessments conducted by the Kenyan National Drought Management Authority and monthly drought bulletins for Turkana? Secondly, are there differences in the methodology used for analysis of meteorological indicators in the different documents? Firstly, by utilizing a food systems framework, we conduct qualitative content analysis of the use of indicators in the documents; secondly, we analyze rainfall data and its use. The EWS relies primarily on food availability indicators, with less focus for food access and utilization. The biannual assessments and the country bulletins use different sets of rainfall data and different methodologies for establishing the climate normal, leading to discrepancies in the output of the EWS. We recommend further steps to be taken towards standardization of methodologies and cooperation between various institutions to ensure streamlining of approaches.

Lessons Learned from the 2017 Flash Drought across the U.S. Northern Great Plains and Canadian Prairies

The 2017 flash drought arrived without early warning and devastated the U.S. northern Great Plains region comprising Montana, North Dakota, and South Dakota and the adjacent Canadian Prairies. The drought led to agricultural production losses exceeding $2.6 billion in the United States, widespread wildfires, poor air quality, damaged ecosystems, and degraded mental health. These effects motivated a multiagency collaboration among academic, tribal, state, and federal partners to evaluate drought early warning systems, coordination efforts, communication, and management practices with the goal of improving resilience and response to future droughts. This essay provides an overview on the causes, predictability, and historical context of the drought, the impacts of the drought, opportunities for drought early warning, and an inventory of lessons learned. Key lessons learned include the following: 1) building partnerships during nondrought periods helps ensure that proper relationships are in place for a coordinated and effective drought response; 2) drought information providers must improve their understanding of the annual decision cycles of all relevant sectors, including, and beyond, direct impacts in agricultural sectors; and 3) ongoing monitoring of environmental conditions is vital to drought early warning, given that seasonal forecasts lack skill over the northern Great Plains.