Agricultural drought hazard analysis during 1980-2008: a global perspective

2015 ◽  
Vol 36 (1) ◽  
pp. 389-399 ◽  
Author(s):  
Guangpo Geng ◽  
Jianjun Wu ◽  
Qianfeng Wang ◽  
Tianjie Lei ◽  
Bin He ◽  
...  
Keyword(s):  
Hazard Analysis ◽  
Global Perspective ◽  
Agricultural Drought ◽  
Drought Hazard

Development of a Next Generation Drought Index: combining multiple global and local data sources to enable detection of sector-specific drought impacts

2021 ◽  
Author(s):  
Dimmie Hendriks ◽  
Pieter Hazenberg ◽  
Jonas Gotte ◽  
Patricia Trambauer ◽  
Arjen Haag ◽  
...  
Keyword(s):  
Drought Index ◽  
Agricultural Drought ◽  
Data Sources ◽  
Drought Indices ◽  
Next Generation ◽  
Hazard Indices ◽  
Local Data ◽  
Drought Impacts ◽  
Drought Hazard ◽  
Impact Data

<p>An increasing number of regions and countries are confronted with 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. In order to prevent big drought impacts, such as agricultural damage and food insecurity, timely and focused drought mitigation measures need to be carried out. To enable this, the detection of drought and its sector-specific risks at early stages needs to be improved. One of the main challenges is to develop compound and impact-oriented drought indices, that make optimal use of innovative techniques, satellite products, local data and other big data sets.</p><p>Here, we present the development of a Next Generation Drought Index (NGDI) that combines multiple freely available global data sources (eg. ERA5, MODIS, PCR-GLOBWB) to calculate a range of relevant drought hazard indices related to meteorological, hydrological, soil moisture and agricultural drought (eg. SPI, SPEI, SRI, SGI, VCI). The drought hazard indices are aggregated at district level, while considering the percentage area exposure of the drought impacted sector (exposure). In addition, the indices are enriched with local and national scale drought impact information (eg. online news items, social media data, EM-DAT database, GDO Drought news, national drought reports). Results are presented at sub-national scales in interactive spatial and temporal views, showing the combined drought indices and impact data.</p><p>The NGDI approach is being tested for the agricultural sector in Mali, a country with a vulnerable population and economy that faces frequent dry spells which heavily impact the functioning of the important agricultural activities that sustain a large part of the population. The computed drought indices are compared with local drought data and an analysis is made of the cross-correlations between the indices within the NGDI and collected impact data.</p><p>We aim at providing the NGDI information to a broad audience as well as co-creation of further NGDI developments. Hence, we would like to reach out to interested parties and identify collaboration opportunities.</p>

scholarly journals Probabilistic modelling of the dependence between rainfed crops and drought hazard

2019 ◽  
Author(s):  
Andreia F. S. Ribeiro ◽  
Ana Russo ◽  
Célia M. Gouveia ◽  
Patrícia Páscoa ◽  
Carlos A. L. Pires
Keyword(s):  
Probability Distributions ◽  
Joint Probability ◽  
Agricultural Drought ◽  
Extreme Weather Events ◽  
Drought Risk ◽  
Crop Loss ◽  
Archimedean Copulas ◽  
Drought Hazard ◽  
Drought Conditions ◽  
Joint Probability Distributions

Abstract. Extreme weather events, such as droughts, have been increasingly affecting the agricultural sector causing several socio-economic consequences. The growing economy requires improved assessments of drought-related impacts in agriculture, particularly under a climate that is getting drier and warmer. This work proposes a probabilistic model which intends to contribute to the agricultural drought risk management in rainfed cropping systems. Our methodology is based on a bivariate copula-approach using Elliptical and Archimedean copulas, which application is quite recent in agrometeorological studies. In this work we use copulas to model joint probability distributions describing the amount of dependence between drought conditions and crop anomalies. Afterwards, we use the established copula models to simulate pairs of yield anomalies and drought hazard, preserving their dependence structure, to further estimate the probability of crop-loss. In the first step, we analyse the probability of crop-loss without distinguishing the class of drought, and in a second step we compare the probability of crop-loss under drought and non-drought conditions. The results indicate that, in general, Archimedean copulas provide the best statistical fits of the joint probability distributions, suggesting a dependence among extreme values of rainfed cereal yield anomalies and drought indicators. Moreover, the estimated conditional probabilities suggest that the likelihood of crop-loss under dry conditions is higher than under non-drought conditions. From an operational point of view, the results aim to contribute to the decision-making process in agricultural practices.

scholarly journals DROUGHT HAZARD CHARACTERISTIC USING SOIL MOISTURE DEFICIT INDEX MODELLING

2018 ◽  
Vol 5 (1) ◽  
pp. 91
Author(s):  
Lulu Mari Fitria ◽  
Septiana Fathurrohmah
Keyword(s):  
Soil Moisture ◽  
Standardized Precipitation Index ◽  
Hydrological Drought ◽  
Agricultural Drought ◽  
Extreme Condition ◽  
Hazard Mapping ◽  
Soil Moisture Deficit ◽  
Positive Correlation ◽  
Drought Hazard ◽  
Moisture Deficit

Drought happen when the rainfall decreases in the extreme condition for long period of  time (above normal). Drought hazard mapping can be analyzed by various approaches, like environmental approach, ecological approach, hydrological approach, meteorological approach, geological approach, agricultural approach, and many other. Meteorological, Climatological, and Geophysical Agency (in Indonesia a.k.a BMKG) measures the drought hazard by utilizing Standardized Precipitation Index (SPI)The comparison of rainfall rate through SPI has positive correlation with  drought type, for example SPI 3 indicates agricultural drought; while SPI 6, SPI 9 and SPI 12 indicate  hydrological drought. The analysis of drought hazard level also can be done using soil moisture level measurement. Soil moisture is the result of water shortages in the hydroclimatological concept. Soil moisture analysis utilizes several influenced variables, such as soil water, precipitation, evapotranspiration, and percolation. Each of variables was analyzed using GIS as a method of soil moisture modeling. Drought index level analysis is using soil moisture deficit index, which indicates that drought occurs if the index score less than (-0.5). Some assumptions used in this modeling are both SMDI modeling using WHC (Water Holding Capacity) and  without using WHC. This modeling used medium term analysis during 2007-2012 to prove the occurrence of extreme drought on 2009 and 2012 for measurement of drought level in agriculture area. Based on SMDI, it is known that the dangers of SMDI drought have positive correlation to SPI 3, SPI 6, SPI 9, and SPI 12, where SPI is in accordance with the interpretation of meteorolgy, agriculture, and hydrological drought indices.

scholarly journals Assessment of Agricultural Drought Risk in the Lancang-Mekong Region, South East Asia

2020 ◽  
Vol 17 (17) ◽  
pp. 6153
Author(s):  
Lei Zhang ◽  
Wei Song ◽  
Wen Song
Keyword(s):  
Agricultural Production ◽  
Agricultural Drought ◽  
Mekong River ◽  
Drought Risk ◽  
Crop Water Stress Index ◽  
Drought Vulnerability ◽  
Mekong Region ◽  
Drought Hazard ◽  
South Central ◽  
High Hazard

Natural disasters worldwide regularly impact on human activities. As a frequently occurring natural disaster, drought has adverse impacts on agricultural production. The Lancang-Mekong River is a transnational river running through China and five Southeast Asian countries and it is a vital water resource for irrigation in the region. Drought in the Lancang-Mekong Region (LMR) has occurred frequently in recent years. Assessing the risk of drought in the region is essential for rational planning of agricultural production and formulation of drought relief measures. In this study, an assessment of drought risk has been achieved by combining the hazard and vulnerability assessments for drought. The assessment of the drought hazard depends mainly on the standardized precipitation index (SPI). The assessment of drought vulnerability takes into account various indicators such as climatic factors (e.g., crop water stress index), soil factors (e.g., available water capacity), and irrigation factors (e.g., irrigation support). The results reveal that: (1) Drought distribution in the LMR is characterized by a spreading of the drought to countries along the middle and lower reaches of the Mekong River. Countries located in the middle and lower reaches of the Mekong River are more prone to drought. Laos, Thailand, and Cambodia are the regions with higher and high-drought risk levels. (2) The spatial distributions for the drought hazard and the drought vulnerability in the LMR exhibit significant differences as evidenced in the mapping results. High-hazard and high-vulnerability areas are mainly distributed in the middle LMR, and the middle to higher hazard areas and the middle to higher vulnerability areas are mainly distributed in the south-central LMR, while the low-hazard areas and the low-vulnerability areas are mainly in the north. (3) The majority of planting areas for sugarcane, rice, and cassava are located in the high-hazard areas. The distributions of drought-prone and high-hazard areas also correspond to the main agricultural areas in the LMR.

scholarly journals Study on the drought risk of maize in the farming-pastoral ecotone in Northern China based on physical vulnerability assessment

2016 ◽  
Author(s):  
Zhiqiang Wang ◽  
Jingyi Jiang ◽  
Qing Ma
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Yield Loss ◽  
Northern China ◽  
Agricultural Drought ◽  
Drought Risk ◽  
Physical Vulnerability ◽  
Vulnerability Curve ◽  
Intensity Index ◽  
Drought Hazard

Abstract. Climate change is affecting every aspect of human activities, especially the agriculture. In China, extreme drought events caused by climate change have posed great threaten to food safety. In this work we aimed to study the drought risk of maize in the farming-pastoral ecotone in Northern China based on physical vulnerability assessment. The physical vulnerability curve was constructed from the relationship between drought hazard intensity index and yield loss rate. The risk assessment of agricultural drought was conducted from the drought hazard intensity index and physical vulnerability curve. Results of the drought hazard intensity index showed that the risk of agricultural drought displayed a negative correlation with the precipitation and kept rising from 1966 to 2011. Risk assessments of yield loss ratio shows that physical vulnerability curve has magnify and reduce function to drought hazard. So improving the capacity of maize to resist drought can help them adapt to drought hazard. In conclusion, the farming-pastoral ecotone in Northern China had great sensitivity to climate change and high probability for severe drought hazard. Risk assessment of physical vulnerability can help better understanding the physical vulnerability to agricultural drought and can also promote measurements to adapt to the climate change.

scholarly journals The drought risk of maize in the farming–pastoral ecotone in Northern China based on physical vulnerability assessment

2016 ◽  
Vol 16 (12) ◽  
pp. 2697-2711 ◽  
Author(s):  
Zhiqiang Wang ◽  
Jingyi Jiang ◽  
Qing Ma
Keyword(s):  
Climate Change ◽  
Yield Loss ◽  
Northern China ◽  
Agricultural Drought ◽  
Drought Risk ◽  
Physical Vulnerability ◽  
Vulnerability Curve ◽  
Intensity Index ◽  
Drought Hazard ◽  
Spring Maize

Abstract. Climate change is affecting every aspect of human activities, especially the agriculture. In China, extreme drought events caused by climate change have posed a great threat to food safety. In this work we aimed to study the drought risk of maize in the farming–pastoral ecotone in Northern China based on physical vulnerability assessment. The physical vulnerability curve was constructed from the relationship between drought hazard intensity index and yield loss rate. The risk assessment of agricultural drought was conducted from the drought hazard intensity index and physical vulnerability curve. The probability distribution of drought hazard intensity index decreased from south-west to north-east and increased from south-east to north-west along the rainfall isoline. The physical vulnerability curve had a reduction effect in three parts of the farming–pastoral ecotone in Northern China, which helped to reduce drought hazard vulnerability on spring maize. The risk of yield loss ratio calculated based on physical vulnerability curve was lower compared with the drought hazard intensity index, which suggested that the capacity of spring maize to resist and adapt to drought is increasing. In conclusion, the farming–pastoral ecotone in Northern China is greatly sensitive to climate change and has a high probability of severe drought hazard. Risk assessment of physical vulnerability can help better understand the physical vulnerability to agricultural drought and can also promote measurements to adapt to climate change.

Take a Fresh Look at Existing Hazard Analysis Data to Assess Safety Instrumented System Needs

2000 ◽  
Author(s):  
G. Bradley Chadwell
Keyword(s):  
Risk Assessment ◽  
Hazard Analysis ◽  
Analysis Data ◽  
Global Perspective ◽  
Capital Expenditures ◽  
Traditional Methods ◽  
Accident Scenario ◽  
Major Benefit ◽  
Reduce Risk ◽  
New Perspective

Abstract Many traditional methods for assessing Safety Instrumented Systems (SISs) focus on controlling individual hazards on a scenario-by-scenario basis. In these existing approaches, engineers use a hazard analysis, or other form of risk assessment, to evaluate each potential accident scenario to determine the need for a SIS. While comprehensive, such methods can result in more SISs being defined than are necessary. This paper describes an approach for SISs using existing hazard analysis data from a new perspective. The approach goes beyond traditional scenario-by-scenario methods by explicitly considering the process as a whole. A major benefit is the potential to optimize resources by identifying the minimum set of SISs required to address all the hazards present in the process. Hence, this method can reduce capital expenditures, as well as testing and inspection requirements. This paper discusses the practicalities of taking a global perspective of a process in defining SIS requirements. Additionally, the concept of Importance Measures, used for prioritizing efforts to control and reduce risk, is extended to prioritizing and optimizing SIS selection from a risk-based perspective.

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