scholarly journals Drought Early Warning and the Timing of Range Managers’ Drought Response

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Tonya R. Haigh ◽  
Jason A. Otkin ◽  
Anthony Mucia ◽  
Michael Hayes ◽  
Mark E. Burbach
Keyword(s):  
Early Warning ◽  
Protective Action ◽  
Rangeland Management ◽  
Environmental Cues ◽  
Protective Action Decision Model ◽  
Improved Outcomes ◽  
Drought Early Warning ◽  
One Year ◽  
On Farm ◽  
Agricultural Landowners

The connection between drought early warning information and the timing of rangeland managers’ response actions is not well understood. This study investigates U.S. Northern Plains range and livestock managers’ decision-making in response to the 2016 flash drought, by means of a postdrought survey of agricultural landowners and using the Protective Action Decision Model theoretical framework. The study found that managers acted in response to environmental cues, but that their responses were significantly delayed compared to when drought conditions emerged. External warnings did not influence the timing of their decisions, though on-farm monitoring and assessment of conditions did. Though this case focused only on a one-year flash drought characterized by rapid drought intensification, waiting to destock pastures was associated with greater losses to range productivity and health and diversity. This study finds evidence of unrealized potential for drought early warning information to support proactive response and improved outcomes for rangeland management.

scholarly journals Determinant Factors in Personal Decision-Making to Adopt COVID-19 Prevention Measures in Chile

2021 ◽  
Vol 18 (15) ◽  
pp. 8131
Author(s):  
Karina Fernanda Gonzalez ◽  
Maria Teresa Bull ◽  
Sebastian Muñoz-Herrera ◽  
Luis Felipe Robledo
Keyword(s):  
Decision Making ◽  
Decision Model ◽  
Protective Action ◽  
Prevention Measures ◽  
Protective Measures ◽  
Protective Action Decision Model ◽  
Exploratory Survey ◽  
Relevant Variables ◽  
Personal Decision ◽  
Action Decision

The pandemic has challenged countries to develop stringent measures to reduce infections and keep the population healthy. However, the greatest challenge is understanding the process of adopting self-care measures by individuals in different countries. In this research, we sought to understand the behavior of individuals who take self-protective action. We selected the risk homeostasis approach to identify relevant variables associated with the risk of contagion and the Protective Action Decision Model to understand protective decision-making in the pandemic. Subsequently, we conducted an exploratory survey to identify whether the same factors, as indicated in the literature, impact Chile’s adoption of prevention measures. The variables gender, age, and trust in authority behave similarly to those found in the literature. However, socioeconomic level, education, and media do not impact the protection behaviors adopted to avoid contagion. Furthermore, the application of the Protective Action Decision Model is adequate to understand the protective measures in the case of a pandemic. Finally, women have a higher risk perception and adopt more protective measures, and in contrast, young people between 18 and 30 years of age are the least concerned about COVID-19 infection.

scholarly journals Heat adaptation measures in private households: an application and adaptation of the protective action decision model

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Sabrina Katharina Beckmann ◽  
Michael Hiete ◽  
Michael Schneider ◽  
Christoph Beck
Keyword(s):  
Regression Analysis ◽  
Decision Model ◽  
Protective Action ◽  
Hierarchical Regression ◽  
Adaptation Measures ◽  
Heat Adaptation ◽  
Private Households ◽  
Protective Action Decision Model ◽  
Heat Risk ◽  
Action Decision

AbstractExtreme heatwaves will occur more frequently and with higher intensity in future. Their consequences for human health can be fatal if adaptation measures will not be taken. This study analyses factors related to heat adaptation measures in private households in Germany. During the summer months of 2019, indoor temperatures were measured in over 500 private households in the City of Augsburg, Germany, accompanied by a survey to find out about heat perception and adaptation measures. Hypotheses deducted from the Protective Action Decision Model were tested using one-way ANOVAs, regression analysis and in the end a multiple hierarchical regression model. The results of the hypotheses tested imply an influence of knowledge and heat risk perception of heat adaptation behaviour and an influence of age on heat risk perception. The results of the regression model show an influence of the efficacy-related attribute, of age, indoor temperature, subjective heat stress and health implications to heat adaptation behaviour. In the end, this study proposes adjustments to the PADM according to the results of the hierarchical regression analysis.

scholarly journals Exploring drought vulnerability in Africa: an indicator based analysis to inform early warning systems

2013 ◽  
Vol 10 (10) ◽  
pp. 12217-12254 ◽  
Author(s):  
G. Naumann ◽  
P. Barbosa ◽  
L. Garrote ◽  
A. Iglesias ◽  
J. Vogt
Keyword(s):  
Sensitivity Analysis ◽  
Early Warning ◽  
Natural Capital ◽  
Early Warning Systems ◽  
Composite Indicator ◽  
Warning Systems ◽  
Drought Vulnerability ◽  
Country Level ◽  
Vulnerability Indicator ◽  
Drought Early Warning

Abstract. Drought vulnerability is a complex concept that includes both biophysical and socio-economic drivers of drought impact that determine capacity to cope with drought. In order to develop an efficient drought early warning system and to be prepared to mitigate upcoming drought events it is important to understand the drought vulnerability of the affected regions. We propose a composite Drought Vulnerability Indicator (DVI) that reflects different aspects of drought vulnerability evaluated at Pan-African level in four components: the renewable natural capital, the economic capacity, the human and civic resources, and the infrastructure and technology. The selection of variables and weights reflects the assumption that a society with institutional capacity and coordination, as well as with mechanisms for public participation is less vulnerable to drought; furthermore we consider that agriculture is only one of the many sectors affected by drought. The quality and accuracy of a composite indicator depends on the theoretical framework, on the data collection and quality, and on how the different components are aggregated. This kind of approach can lead to some degree of scepticism; to overcome this problem a sensitivity analysis was done in order to measure the degree of uncertainty associated with the construction of the composite indicator. Although the proposed drought vulnerability indicator relies on a number of theoretical assumptions and some degree of subjectivity, the sensitivity analysis showed that it is a robust indicator and hence able of representing the complex processes that lead to drought vulnerability. According to the DVI computed at country level, the African countries classified with higher relative vulnerability are Somalia, Burundi, Niger, Ethiopia, Mali and Chad. The analysis of the renewable natural capital component at sub-basin level shows that the basins with high to moderate drought vulnerability can be subdivided in three main different geographical regions: the Mediterranean coast of Africa; the Sahel region and the Horn of Africa; the Serengeti and the Eastern Miombo woodlands in eastern Africa. Additionally, the western part of the Zambezi basin, the south-eastern border of the Congo basin and the belt of Fynbos in the Western Cape should also be included in this category. The results of the DVI at the country level were compared with drought disasters information from the EM-DAT disaster database. Even if a cause effect relationship cannot be established between the DVI and the drought disaster database, a good agreement is observed between the drought vulnerability maps and the number of persons affected by droughts. These results are a valuable contribution to the discussion on how to assess drought vulnerability and should contribute to the development of drought early warning systems in Africa.

scholarly journals Facilitating the Use of Drought Early Warning Information through Interactions with Agricultural Stakeholders

2015 ◽  
Vol 96 (7) ◽  
pp. 1073-1078 ◽  
Author(s):  
Jason A. Otkin ◽  
Mark Shafer ◽  
Mark Svoboda ◽  
Brian Wardlow ◽  
Martha C. Anderson ◽  
...  
Keyword(s):  
Early Warning ◽  
Drought Early Warning

Southern Stem Rot Suppression On Peanut With The Insecticide Chlorpyrifos1

1986 ◽  
Vol 13 (1) ◽  
pp. 36-37 ◽  
Author(s):  
A. K. Hagan ◽  
J. R. Weeks ◽  
R. B. Reed
Keyword(s):  
Sclerotium Rolfsii ◽  
Stem Rot ◽  
Yield Response ◽  
Disease Loci ◽  
One Year ◽  
On Farm

Abstract Chlorpyrifos 15G(2.24 kg a.i./ha), PCNB 10G (11.2 kg a.i./ha), and PCNB 10G + chlorpyrifos 15G(11.2 + 2.24 kg a.i./ha) were compared for the suppression of southern stem rot caused by Sclerotium rolfsii Sacc. on peanut in on-farm trials on nine farms over three years (1982–1984). Chlorpyrifos, PCNB, and PCNB + chlorpyrifos significantly reduced loci counts all three years. PCNB + chlorpyrifos generally gave the best stem rot suppression and yield response, but there was little difference in disease loci counts between chlorpyrifos and PCNB. PCNB significantly increased yield over the control two years while chlorpyrifos increased yield only one year.

scholarly journals Recognizing the Famine Early Warning Systems Network: Over 30 Years of Drought Early Warning Science Advances and Partnerships Promoting Global Food Security

2019 ◽  
Vol 100 (6) ◽  
pp. 1011-1027 ◽  
Author(s):  
Chris Funk ◽  
Shraddhanand Shukla ◽  
Wassila Mamadou Thiaw ◽  
James Rowland ◽  
Andrew Hoell ◽  
...  
Keyword(s):  
Food Security ◽  
Early Warning ◽  
Warning System ◽  
Climate Extremes ◽  
Early Warning Systems ◽  
Food Prices ◽  
Humanitarian Assistance ◽  
Warning Systems ◽  
Recent Climate ◽  
Drought Early Warning

AbstractOn a planet with a population of more than 7 billion, how do we identify the millions of drought-afflicted people who face a real threat of livelihood disruption or death without humanitarian assistance? Typically, these people are poor and heavily dependent on rainfed agriculture and livestock. Most live in Africa, Central America, or Southwest Asia. When the rains fail, incomes diminish while food prices increase, cutting off the poorest (most often women and children) from access to adequate nutrition. As seen in Ethiopia in 1984 and Somalia in 2011, food shortages can lead to famine. Yet these slow-onset disasters also provide opportunities for effective intervention, as seen in Ethiopia in 2015 and Somalia in 2017. Since 1985, the U.S. Agency for International Development’s Famine Early Warning Systems Network (FEWS NET) has been providing evidence-based guidance for effective humanitarian relief efforts. FEWS NET depends on a Drought Early Warning System (DEWS) to help understand, monitor, model, and predict food insecurity. Here we provide an overview of FEWS NET’s DEWS using examples from recent climate extremes. While drought monitoring and prediction provides just one part of FEWS NET’s monitoring system, it draws from many disciplines—remote sensing, climate prediction, agroclimatic monitoring, and hydrologic modeling. Here we describe FEWS NET’s multiagency multidisciplinary DEWS and Food Security Outlooks. This DEWS uses diagnostic analyses to guide predictions. Midseason droughts are monitored using multiple cutting-edge Earth-observing systems. Crop and hydrologic models can translate these observations into impacts. The resulting information feeds into FEWS NET reports, helping to save lives by motivating and targeting timely humanitarian assistance.

Optimizing Earthquake Early Warning Alert Distance Strategies Using the July 2019 Mw 6.4 and Mw 7.1 Ridgecrest, California, Earthquakes

2020 ◽  
Vol 110 (4) ◽  
pp. 1872-1886 ◽  
Author(s):  
Jessie K. Saunders ◽  
Brad T. Aagaard ◽  
Annemarie S. Baltay ◽  
Sarah E. Minson
Keyword(s):  
Ground Motion ◽  
Early Warning ◽  
Ground Motions ◽  
Protective Action ◽  
Warning System ◽  
Prediction Equation ◽  
Earthquake Early Warning ◽  
Source Characterization ◽  
Earthquake Early Warning System ◽  
Alert Distance

ABSTRACT The ShakeAlert earthquake early warning system aims to alert people who experience modified Mercalli intensity (MMI) IV+ shaking during an earthquake using source estimates (magnitude and location) to estimate median-expected peak ground motions with distance, then using these ground motions to determine median-expected MMI and thus the extent of MMI IV shaking. Because median ground motions are used, even if magnitude and location are correct, there will be people outside the alert region who experience MMI IV shaking but do not receive an alert (missed alerts). We use 91,000 “Did You Feel It?” survey responses to the July 2019 Mw 6.4 and Mw 7.1 Ridgecrest, California, earthquakes to determine which ground-motion to intensity conversion equation (GMICE) best fits median MMI with distance. We then explore how incorporating uncertainty from the ground-motion prediction equation and the GMICE in the alert distance calculation can produce more accurate MMI IV alert regions for a desired alerting strategy (e.g., aiming to alert 95% of people who experience MMI IV+ shaking), assuming accurate source characterization. Without incorporating ground-motion uncertainties, we find MMI IV alert regions using median-expected ground motions alert fewer than 20% of the population that experiences MMI IV+ shaking. In contrast, we find >94% of the people who experience MMI IV+ shaking can be included in the MMI IV alert region when two standard deviations of ground-motion uncertainty are included in the alert distance computation. The optimal alerting strategy depends on the false alert tolerance of the community due to the trade-off between minimizing missed and false alerts. This is especially the case for situations like the Mw 6.4 earthquake when alerting 95% of the 5 million people who experience MMI IV+ also results in alerting 14 million people who experience shaking below this level and do not need to take protective action.

scholarly journals Drought Propagation Patterns under Naturalized Condition Using Daily Hydrometeorological Data

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Jianzhu Li ◽  
Yuangang Guo ◽  
Yixuan Wang ◽  
Shanlong Lu ◽  
Xu Chen
Keyword(s):  
Early Warning ◽  
Assessment Tool ◽  
Swat Model ◽  
Meteorological Drought ◽  
Threshold Level ◽  
Hydrological Drought ◽  
Propagation Pattern ◽  
Drought Early Warning ◽  
Hydrological Droughts

Drought propagation pattern forms a basis for establishing drought monitoring and early warning. Due to its regional disparity, it is necessary and significant to investigate the pattern of drought propagation in a specific region. With the objective of improving understanding of drought propagation pattern in the Luanhe River basin, we first simulated soil moisture and streamflow in naturalized situation on daily time scale by using the Soil and Water Assessment Tool (SWAT) model. The threshold level method was utilized in identifying drought events and drought characteristics. Compared with meteorological drought, the number of drought events was less and duration was longer for agricultural and hydrological droughts. The results showed that there were 3 types of drought propagation pattern: from meteorological drought to agricultural/hydrological drought (M-A/H), agricultural/hydrological drought without meteorological drought (NM-A/H), and meteorological drought only (M). To explain the drought propagation pattern, possible driven factors were determined, and the relations between agricultural/hydrological drought and the driven factors were built using multiple regression models with the coefficients of determination of 0.4 and 0.656, respectively. These results could provide valuable information for drought early warning and forecast.

Sign in / Sign up

Export Citation Format

Share Document