scholarly journals Real time implementation of agricultural contingency plans to cope with weather aberrations in Indian agriculture

MAUSAM ◽  
2021 ◽  
Vol 67 (1) ◽  
pp. 183-194
Author(s):  
CH. SRINIVASA RAO RAO ◽  
G. RAVINDRA CHARY ◽  
N. RANI ◽  
V. S. BAVISKAR
Keyword(s):  
Real Time ◽  
Extreme Events ◽  
Agricultural Production ◽  
Extreme Weather Events ◽  
Horticultural Crops ◽  
Indian Agriculture ◽  
Weather Events ◽  
Overall Stability ◽  
Droughts And Floods ◽  
Seasonal Droughts

Weather aberrations impact agriculture and allied sectors in one or other parts of the India round the year. Seasonal droughts and extreme weather events in 21st century have caused alarming losses not only in agricultural production but also horticulture, livestock, poultry and fisheries. ICAR-CRIDA, SAUs and DAC, MoA, GoI, prepared more than 580 district level agriculture plans within formation on contingency measures for sustaining higher agriculture production and to cope with extreme events. Real-time contingency planning (RTCP) is being conceptualized and implemented at micro level in farmers’ fields in this country. RTCP implementation during delayed onset of monsoon, seasonal droughts and floods resulted in better crop performance, higher agricultural production, better incomes and overall stability in house-hold livelihoods. In this paper, the real-contingency measures to cope with extreme events for management of horticultural crops, livestock, poultry and fisheries are proposed. Further, the preparedness for RTCP implementation with policy initiatives is also suggested.

The economic costs of extreme weather events: a hydrometeorological CGE analysis for Malawi

2011 ◽  
Vol 16 (2) ◽  
pp. 177-198 ◽  
Author(s):  
KARL PAUW ◽  
JAMES THURLOW ◽  
MURTHY BACHU ◽  
DIRK ERNST VAN SEVENTER
Keyword(s):  
Computable General Equilibrium ◽  
Computable General Equilibrium Model ◽  
Extreme Weather ◽  
Mitigation Strategies ◽  
Extreme Weather Events ◽  
Economic Losses ◽  
Historical Events ◽  
Weather Events ◽  
Repeated Sampling ◽  
Droughts And Floods

ABSTRACTExtreme weather events such as droughts and floods have potentially damaging implications for developing countries. Previous studies have estimated economic losses during hypothetical or single historical events, and have relied on historical production data rather than explicitly modeling climate. However, effective mitigation strategies require knowledge of the full distribution of weather events and their isolated effects on economic outcomes. We combine stochastic hydrometeorological crop-loss models with a regionalized computable general equilibrium model to estimate losses for the full distribution of possible weather events in Malawi. Results indicate that, based on repeated sampling from historical events, at least 1.7 per cent of Malawi's gross domestic product (GDP) is lost each year due to the combined effects of droughts and floods. Smaller-scale farmers in the southern region of the country are worst affected. However, poverty among urban and nonfarm households also increases due to national food shortages and higher domestic prices.

Major weather-related risks to crop performance along the Australian wheat belt for recent past and longer-term historical weather records

2021 ◽  
Author(s):  
Gennady Bracho Mujica ◽  
Peter Hayman ◽  
Victor Sadras ◽  
Bertram Ostendorf ◽  
Nicole Ferreira C. R. ◽  
...  
Keyword(s):  
Grain Yield ◽  
Extreme Events ◽  
Extreme Weather Events ◽  
Yield Reduction ◽  
Recent Past ◽  
Weather Extremes ◽  
Crop Failure ◽  
Weather Events ◽  
Australian Wheat ◽  
Historical Past

<p>Extreme events, such as drought, heat and/or frost are among the major weather-related causes of yield reduction and crop failure worldwide. Changes in the frequency and intensity of such weather extremes affect the shape and scale of yield distributions. Wheat growers, in Australia, are particularly vulnerable to climate due to its high variability. Risks of both, extremely high or low temperatures and water stress occurring simultaneously or at different crop stages within the growing season (May-October, e.g. frost mid-season, drought during the season and heat towards the end) often lead to yield reductions, or sometimes even to crop failure. In this study, we focused on assessing the frequency and impact of these relevant extreme weather events (i.e. drought, heat and frost) affecting wheat production in Australia. Specifically, we used a widely used and calibrated crop model (APSIM) to simulate wheat grain yield, and determine probability density functions (PDFs) of grain yield and crop failure. Chances of crop failure due to these extreme events are explored for the recent past (1991-2020) and the longer-term historical past (1901-1990). Key adaption strategies to minimise the impacts of these extreme events, and reduce crop failure risk are assessed in this study, including early sowing and cultivar choice. Our findings are in line with recent studies, indicating that drought and heat are major risk factors contributing to reduced yields or crop failure. However, due to the timing, frequency and impacts of frost events on wheat productivity, frost also remains a relevant risk for the wheat industry in Australia.</p>

scholarly journals Impacts of compound extreme weather events on ozone in the present and future

2018 ◽  
Author(s):  
Junxi Zhang ◽  
Yang Gao ◽  
Kun Luo ◽  
L. Ruby Leung ◽  
Yang Zhang ◽  
...  
Keyword(s):  
Extreme Events ◽  
Heat Waves ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Low Wind Speed ◽  
Weather Events ◽  
The Us ◽  
The Future ◽  
Compound Events ◽  
Ozone Episodes

Abstract. The Weather Research and Forecasting model with Chemistry (WRF/Chem) was used to study the effect of extreme weather events on ozone in US for historical (2001–2010) and future (2046–2055) periods under RCP8.5 scenario. During extreme weather events, including heat waves, atmospheric stagnation, and their compound events, ozone concentration is much higher compared to non-extreme events period. A striking enhancement of effect during compound events is revealed when heat wave and stagnation occur simultaneously and both high temperature and low wind speed promote the production of high ozone concentrations. In regions with high emissions, compound extreme events can shift the high-end tails of the probability density functions (PDFs) of ozone to even higher values to generate extreme ozone episodes. In regions with low emissions, extreme events can still increase high ozone frequency but the high-end tails of the PDFs are constrained by the low emissions. Despite large anthropogenic emission reduction projected for the future, compound events increase ozone more than the single events by 10 % to 13 %, comparable to the present, and high ozone episodes are not eliminated. Using the CMIP5 multi-model ensemble, the frequency of compound events is found to increase more dominantly compared to the increased frequency of single events in the future over the US, Europe, and China. High ozone episodes will likely continue in the future due to increases in both frequency and intensity of extreme events, despite reductions in anthropogenic emissions of its precursors. However, the latter could reduce or eliminate extreme ozone episodes, so improving projections of compound events and their impacts on extreme ozone may better constrain future projections of extreme ozone episodes that have detrimental effects on human health.

scholarly journals Vpliv namakanja v kombinaciji s tehnologijo nege ledine na razporeditev, migracijo ter vsebnost nitrata in bakra v tleh oljčnih nasadov

2018 ◽  
Vol 111 (2) ◽  
pp. 393
Author(s):  
Maja PODGORNIK
Keyword(s):  
Agricultural Production ◽  
Climatic Changes ◽  
Extreme Weather Events ◽  
Negative Effects ◽  
Applied Water ◽  
Soil Cultivation ◽  
Technical Management ◽  
Weather Events ◽  
Decomposition Of Organic Matter ◽  
Olive Groves

The more frequent and intense extreme weather events (higher temperatures – the intensity and frequency of heat weaves, more and longer periods of drought) and weather-related diseases and pests, that have caused the greatest damage to olive production in the recent years, are a warning that urgent changes to Slovenian olive culture are needed. Due to the realisation that adaptations of agricultural production to climatic changes can have negative effects on the environment (water, soil), we conducted an experiment to determine the actual effect of adaptations of agro-technical management on the dynamics of nitrate and copper in the soil. The results of the study have shown that irrigation in combination with the technology of soil cultivation have effect on the allocation, migration and content of nitrate and copper in the soil of olive groves. Along with the fact that applied water allows the undisturbed absorption of nutrients into the plant, it can also improve the conditions for mineralisation and decomposition of organic matter, which is heavily dependent on the type of soil cultivation.

scholarly journals Assessing the impacts of extreme weather events on potable water quality: the value to managers of a highly participatory, integrated modelling approach

2018 ◽  
Vol 2 (1) ◽  
pp. 9-24
Author(s):  
Edoardo Bertone ◽  
Oz Sahin ◽  
Russell Richards ◽  
Anne Roiko
Keyword(s):  
Water Quality ◽  
Decision Support ◽  
Extreme Events ◽  
Drinking Water Treatment ◽  
Extreme Weather ◽  
Integrated Modelling ◽  
Extreme Weather Events ◽  
Weather Events ◽  
Sd Model

Abstract A decision support tool was created to estimate the treatment efficiency of an Australian drinking water treatment system based on different combinations of extreme weather events and long-term changes. To deal with uncertainties, missing data, and nonlinear behaviours, a Bayesian network (BN) was coupled with a system dynamics (SD) model. The preliminary conceptual structures of these models were developed through stakeholders' consultation. The BN model could rank extreme events, and combinations of them, based on the severity of their impact on health-related water quality. The SD model, in turn, was used to run a long-term estimation of extreme events' impacts by including temporal factors such as increased water demand and customer feedback. The integration of the two models was performed through a combined Monte Carlo–fuzzy logic approach which allowed to take the BN's outputs as inputs for the SD model. The final product is a participatory, multidisciplinary decision support system allowing for robust, sustainable long-term water resources management under uncertain conditions for a specific location.

scholarly journals Extreme Weather Events and Its Impacts on Rice Production in Coastal Odisha Region of India

2021 ◽  
Author(s):  
S Vijayakumar ◽  
A.K. Nayak ◽  
N. Manikandan ◽  
Suchismita Pattanaik ◽  
Rahul Tripathi ◽  
...  
Keyword(s):  
Grain Yield ◽  
Extreme Events ◽  
Heavy Precipitation ◽  
Extreme Weather ◽  
Significant Trend ◽  
Extreme Weather Events ◽  
Positive Trend ◽  
Rice Grain ◽  
Weather Events ◽  
Precipitation And Temperature

Abstract The study investigates trend in extreme daily precipitation and temperature over coastal Odisha, India. 18 weather indices (8 related to temperature and 10 related to rainfall) were calculated using RClimDex software package for the period 1980–2010 . Trend analysis was carried out using linear regression and non-parametric Mann-Kendall test to find out the statistical significance of various indices. Results indicated, a strong and significant trend in temperature indices while the weak and non-significant trend in precipitation indices. The positive trend in Tmax mean, Tmin mean, TN90p (warm nights), TX90p (warm days), diurnal temperature range (DTR), warm spell duration indicator (WSDI), consecutive dry days (CDD) indicates increasing the frequency of warming events in coastal Odisha. Similarly, positive trend in highest maximum 1-day precipitation (RX1), highest maximum 2 consecutive day precipitation (RX2), highest maximum 3 consecutive day precipitation (RX3), highest maximum 5 consecutive day precipitation (RX5), number of heavy precipitation days (≥64.5mm), number of very heavy precipitation days (≥124.5mm) and negative trend in the number of rainy days (R2.5mm), consecutive wet days (CWD) indicate changes toward the more intense and poor distribution of precipitation in coastal Odisha. The combined effect of precipitation and temperature extreme events showed negative effects on rice grain yield. With the increasing number of extreme events there was sharp decline in rice grain yield was observed in the same year in all the coastal districts. This study emphasizes the need for new technology/management practice to minimize the impacts of extreme weather events on rice yield.

scholarly journals Awareness of climate change's impacts and motivation to adapt are not enough to drive action: A look of Puerto Rican farmers after Hurricane Maria

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0244512
Author(s):  
Luis Alexis Rodríguez-Cruz ◽  
Meredith T. Niles
Keyword(s):  
Climate Change ◽  
Puerto Rican ◽  
Adaptive Capacity ◽  
Extreme Events ◽  
Structural Equation ◽  
Climate Adaptation ◽  
Psychological Distance ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Weather Events

Understanding how perceptions around motivation, capacity, and climate change’s impacts relate to the adoption of adaptation practices in light of experiences with extreme weather events is important in assessing farmers’ adaptive capacity. However, very little of this work has occurred in islands, which may have different vulnerabilities and capacities for adaptation. Data of surveyed farmers throughout Puerto Rico after Hurricane Maria (n = 405, 87% response rate) were used in a structural equation model to explore the extent to which their adoption of agricultural practices and management strategies was driven by perceptions of motivation, vulnerability, and capacity as a function of their psychological distance of climate change. Our results show that half of farmers did not adopt any practice or strategy, even though the majority perceived themselves capable and motivated to adapt to climate change, and understood their farms to be vulnerable to future extreme events. Furthermore, adoption was neither linked to these adaptation perceptions, nor to their psychological distance of climate change, which we found to be both near and far. Puerto Rican farmers’ showed a broad awareness of climate change’s impacts both locally and globally in different dimensions (temporal, spatial, and social), and climate distance was not linked to reported damages from Hurricane Maria or to previous extreme weather events. These results suggest that we may be reaching a tipping point for extreme events as a driver for climate belief and action, especially in places where there is a high level of climate change awareness and continued experience of compounded impacts. Further, high perceived capacity and motivation are not linked to actual adaptation behaviors, suggesting that broadening adaptation analyses beyond individual perceptions and capacities as drivers of climate adaptation may give us a better understanding of the determinants to strengthen farmers’ adaptive capacity.

Extreme Weather and Climate

2017 ◽  
Author(s):  
Friederike Otto
Keyword(s):  
Extreme Events ◽  
The United States ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Weather Event ◽  
Weather Forecasts ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Weather Events ◽  
Global Mean

Natural disasters and extreme weather events have been of great societal importance throughout history and often brought everyday life to a catastrophic halt, in a way sometimes comparable to wars and epidemics, only without the lead time. Extreme weather events with large impacts serve as an anchor point of the collective memory of the population in the affected area. Every northern German of the right age remembers the storm surge of 1962 and where they were at the time and has friends or family effected by the event. The “dust bowl” of the 1930s with extensive droughts and heat waves shaped the life of a generation in the United States, and the Sahel droughts in the 1960s and 1970s led to famine and dislocation of population on a massive scale the region arguably never quite recovered from. Hurricane Hyian in 2013 is said to have directly influenced the outcome of the annual Conference of the Parties (COP) United Nation Framework Convention for Climate Change Negotiations in Warsaw, leading to the inclusion of a mechanism to deal with loss and damage from climate-related disasters. Though earthquakes are still fairly unpredictable on short timescales, this is not the case for weather events. Weather forecasts today are so good that we normally know the time and location of the landfall of a hurricane within a 100-mile radius days in advance. Improvements in the prediction of slow-onset events such as droughts (which depend on the rainfall over a large region and whole season) are less striking but have still improved dramatically in the late 20th and early 21st centuries. One of the major reasons for the large increase in the accuracy of weather forecasts is the exponential increase in computing power, which allows scientists to predict and study extreme weather events using complex computer models, simulating possible weather events under certain conditions to understand the statistics of and physical mechanisms behind extreme events. Extreme events are by definition rare and thus impossible to understand from historical records of weather observation alone. Despite the progress on our understanding of and ability to predict extreme weather events, substantial uncertainties remain. Two aspects are of particular importance. Firstly, we know that the climate is changing, having observed almost a one-degree increase in global mean temperature. However, global mean temperature doesn’t kill anyone, extreme weather events do. Their frequency and intensity is changing and will continue to change, but the extent of these changes depends on a host of both global and local factors. Secondly, whether or not a rare weather event leads to extreme impacts depends largely on the vulnerability and exposure of the affected societies. If these are high, even a perfectly forecasted weather event leads to disaster.

scholarly journals Environmental prediction, risk assessment and extreme events: adaptation strategies for the developing world

2011 ◽  
Vol 369 (1956) ◽  
pp. 4768-4797 ◽  
Author(s):  
Peter J. Webster ◽  
Jun Jian
Keyword(s):  
Climate Change ◽  
Fresh Water ◽  
Extreme Events ◽  
Water Resource Management ◽  
Developing World ◽  
Rural Poverty ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Weather Events ◽  
Environmental Prediction

The uncertainty associated with predicting extreme weather events has serious implications for the developing world, owing to the greater societal vulnerability to such events. Continual exposure to unanticipated extreme events is a contributing factor for the descent into perpetual and structural rural poverty. We provide two examples of how probabilistic environmental prediction of extreme weather events can support dynamic adaptation. In the current climate era, we describe how short-term flood forecasts have been developed and implemented in Bangladesh. Forecasts of impending floods with horizons of 10 days are used to change agricultural practices and planning, store food and household items and evacuate those in peril. For the first time in Bangladesh, floods were anticipated in 2007 and 2008, with broad actions taking place in advance of the floods, grossing agricultural and household savings measured in units of annual income. We argue that probabilistic environmental forecasts disseminated to an informed user community can reduce poverty caused by exposure to unanticipated extreme events. Second, it is also realized that not all decisions in the future can be made at the village level and that grand plans for water resource management require extensive planning and funding. Based on imperfect models and scenarios of economic and population growth, we further suggest that flood frequency and intensity will increase in the Ganges, Brahmaputra and Yangtze catchments as greenhouse-gas concentrations increase. However, irrespective of the climate-change scenario chosen, the availability of fresh water in the latter half of the twenty-first century seems to be dominated by population increases that far outweigh climate-change effects. Paradoxically, fresh water availability may become more critical if there is no climate change.

Predicting Typhoon Morakot’s Catastrophic Rainfall with a Convection-Permitting Mesoscale Ensemble System

2010 ◽  
Vol 25 (6) ◽  
pp. 1816-1825 ◽  
Author(s):  
Fuqing Zhang ◽  
Yonghui Weng ◽  
Ying-Hwa Kuo ◽  
Jeffery S. Whitaker ◽  
Baoguo Xie
Keyword(s):  
Data Assimilation ◽  
Real Time ◽  
Weather Prediction ◽  
Numerical Weather Prediction Model ◽  
Decision Makers ◽  
Extreme Weather Events ◽  
Management Decision ◽  
Typhoon Morakot ◽  
Weather Events ◽  
Flooding Event

Abstract This study examines the prediction and predictability of the recent catastrophic rainfall and flooding event over Taiwan induced by Typhoon Morakot (2009) with a state-of-the-art numerical weather prediction model. A high-resolution convection-permitting mesoscale ensemble, initialized with analysis and flow-dependent perturbations obtained from a real-time global ensemble data assimilation system, is found to be able to predict this record-breaking rainfall event, producing probability forecasts potentially valuable to the emergency management decision makers and the general public. Since all the advanced modeling and data assimilation techniques used here are readily available for real-time operational implementation provided sufficient computing resources are made available, this study demonstrates the potential and need of using ensemble-based analysis and forecasting, along with enhanced computing, in predicting extreme weather events like Typhoon Morakot at operational centers.

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