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Climate Risk Management

Australian agriculture operates under uncertain climatic and market conditions. Farmers in Australia face highly variable climatic conditions, including drought, which can adversely affect their productivity. Indeed, the primary factors that influence farming in Australia is rainfall during the growing season and adequate soil moisture at the time of planting. The amount of rainfall varies significantly from year to year, limiting the supply of water available for irrigation from rainwater that runs off the land and into catchments and underground. The rainfall fluctuates from year to year with natural variability and is unreliable with delayed onset of rainfall in some years affecting timely planting of crops. Over the past three decades, there have been several drought years recorded, which have had a significant impact on agricultural production and businesses.

During unfavourable weather and climatic conditions, farm mitigation strategies are implemented to minimise crop damage and loss. However, in the event of prolonged extreme drought conditions with limited resources, it will be difficult to mitigate the risk of crop loss. With the limitation to adaptation strategies at farms in extreme drought conditions, there is a need to explore alternative risk transfer solutions. Agricultural insurance is one of the financial risk transfer solutions in the event of adverse weather conditions to develop resilient climate risk management. 

Agricultural Insurance could play an important role in helping Australian farmers manage their climate risk. Insurance enables the transfer of weather risk away from agricultural households to the insurance sector. The development of innovative insurance products, which take the history of climate variability in each region into account, will enhance the capacity of growers and agribusinesses to mitigate climate change. Farm businesses will, therefore, be able to improve their climate risk management and adaptation capability and become more resilient to climate change. Traditional or indemnity based (also called multiperil crop insurance; MPCI) comprehensive crop insurance and parametric insurance methods are used in the agriculture sector. 

These indemnity-based crop can be quite costly and may take a considerable amount of time before the insured party receives payment. Additionally, issues with moral hazard and adverse selection often exist, making it difficult for insurers to accurately assess risk and set appropriate premiums. Moral hazard refers to the increased likelihood of a person taking risks when they know they are protected by insurance. Adverse selection, on the other hand, occurs when only high-risk individuals are willing to purchase insurance, which can drive up costs for everyone. Currently there are no MPCI sold in Australia. 

Parametric insurance is a type of insurance that is associated with a specific weather index, such as rainfall. In this case, if the rainfall readings fall below or exceed a previously agreed attachment point, claims are triggered, and the growers receive a predetermined payment. This approach eliminates the need for a lengthy loss adjustment process and enables the farmers to recover quickly from adverse weather conditions. Index-based insurance products can be developed for specific periods related to the crop growth cycle, considering the likely adverse weather effects on the crop. Additionally, the cost of the insurance policy premium is cheaper than the traditional crop insurance. Index insurance is an innovative approach to agriculture insurance that pays out benefits based on pre-agreed indicators (such as precipitation, temperature, soil moisture, etc), without requiring the insurance company to conduct loss assessment in the individual grower’s fields and timely payout after the event occurs. Overall, farmers can ensure their financial security by acquiring parametric insurance against severe weather events.

Example of index-based crop insurance: Cotton 

In this example, we examine the case of cotton grown in the Dalby area in the Darling Downs region of Queensland.  Cotton is extensively grown around Dalby, and two gins are located within a short distance of the town. We obtained a historic yield series for the 24 years from 1992 to 2015 and a daily rainfall data series for Dalby from the Bureau of Meteorology.

Analysis of these data shows a strong correlation between the yield of cotton in a given season and the total rainfall recorded during January and February of that season.  Figure 1 below enables a visual comparison between high/low and high/low yields.

In particular, it is clear that years in which the yield of cotton was markedly less than the long-term average of 1,180 kg/ha were characterised by low Jan/Feb rainfall.  These years were 1993, 1997, 2005, 2007, 2009, and 2014: 6 years out of 24 (25%).  Also, there were no years of low yields in which rainfall was not also low.

The average frequency of occurrence for poor crop yield of 1 year in 4 is rather high but is reflective of the natural variability of growing conditions in this region.  A conclusion of this analysis and these observations is that low yield can be attributed to low rainfall, regardless of other production factors and external influences.

On this basis, it would be feasible to design an index-based insurance product that is Figure 2 below shows the rainfall and a ‘strike’ level below which an index-based policy might payout.  In this instance, for illustrative purposes, the strike level has been set at 50% of the long-term average rainfall for January and February, which equates to approximately 80mm.

Figure 2. An illustration of rainfall and the selection of a trigger point

At this level of strike, it can be seen that the contract would have made payments in each of the low-yield years except for 2009.

A typical index-based insurance product for cotton

In this example (Figure 3), the development of drought insurance products is explained step by step. In this example, the rainfall parameter is used to develop the low rainfall index insurance prototype. Firstly, choose the attachment value (50 mm) and limit value (0 mm), and the tick value is calculated (1000 AUD). In step 2, historical rainfall is assessed for Dalby to find out the number of years that received lower rainfall than 50 mm. Further in step 3, the payouts are calculated for the low rainfall received years in 2005, 2007, and 2014.

Figure 3. An illustration of drought insurance prototype development.

Drought Insurance tool

The Centre for Applied Climate Sciences (CACS) at 黑料吃瓜网 has developed a drought insurance tool to help farmers and other stakeholders estimate drought insurance premiums and learn about risk and risk transfer solutions. This tool allows users to select a location and choose rainfall thresholds for a specific period to determine the drought risk. The tool then calculates location-specific insurance premiums and payouts based on the selected months and level of rainfall threshold.View the is at the Centre for Applied Climate Sciences (CACS)^[1] .

For example, in below Figure 4 for Dalby, the rainfall threshold is used to develop an index-based drought insurance product. The selected period is November and December months with a rainfall threshold of 80 mm (attachment) to 0 mm (limit), and a tick value is 10. The estimated premium ranges from $106.48 to $143.46 with the respective rate online of 13.31% and 17.93%. Seven payouts would have occurred from 1990 to 2020 with the payout ranging from $9 to $552 for policy insured.

 

Figure 4. An example showing drought insurance premium estimate for the rainfall threshold of 80 mm and coverage months of Nov and Dec.

Summary

The drought insurance tool is designed to help producers mitigate the financial risks associated with droughts. It allows them to select a threshold and payout that aligns with their risk appetite and helps them manage their exposure to financial loss. Essentially, the producers can set a threshold for the level of drought that they are willing to tolerate before they receive a payout. The payout amount is also customizable, so they can choose the amount they want to receive if the drought exceeds the threshold they set. This flexibility in selecting the threshold and payout ensures that producers can tailor their insurance coverage to their specific needs and risk tolerance. 

Glossary 

• Attachment point: is a phrase commonly used in the insurance industry. It refers to the specific point at which an insurance policy kicks in and starts to provide coverage for any loss. This attachment point can either be a specific dollar amount for a claim or a particular level of loss experience that triggers the coverage.
• Limit: The insurance limit is the maximum amount your insurer may pay out for a claim, as stated in the policy.
• Tick Value: The tick value is the dollar amount of such a change for each unit.
• Coverage: A coverage period refers to the period during which an insurance policy provides protection to the policyholder.

[1] The funding to develop this tool was provided by the Department of Agriculture and Fisheries, Queensland, under the Drought and Climate Adaptation Program (DCAP)

Background: Chronic groundwater decline reported in many agricultural landscapes of Australia and the world. Groundwater is often seen as a reliable water source during drought and periods of decreased surface water availability. During these periods the extraction rates may exceed recharging, there is increasing concern that under climate change or unsustainable rates of extraction the groundwater level tends to decrease. In addition, groundwater provides potential support to livestock and irrigated production systems. Therefore, it is necessary to continuously monitor the groundwater recharge across landscapes and vulnerable regions.  With this background we planned to study the groundwater level and bore hole drill depth and distribution across the Southern Queensland and Northern New South Wales (SQNNSW) Innovation Hub region.

Methodology and Data: The historical data sets for ground water and bore drill depth is collected from the Australian Groundwater Explorer, Bureau of Meteorology for the period of 1991 to 2022. The data analytics performed for the regions covered by SQNNSW Hub regions, Australia. For region-wise better understanding and visualization the groundwater and bore drill depth are presented in maps and charts.

Australian Groundwater Explorer tool consists of:

• Historical and present groundwater level data for the reference monitoring bores and other drill bores in Australia
• Provides information on number of bores drilled and drill depth yearly and region wise
• Bore purpose and exploration
• Easy understanding of the trend charts and distribution maps

Distribution of bore depth across the SQNNSW Hub region: The actual bore drill depth in meters and location identification with co-ordinates (Latitude and longitude), past 20-years data for the period of 2001 to 2020 is used for plotting and preparing distribution map across the SQNNSW Hub region. Some of parts of Goondiwindi, Balonne, Western Downs, Maranoa, Backall Tambo, Longreach and Winton in Southern Queensland, Moree plains and Walgett in Northern New South Wales have higher bore drill depths to reach groundwater supplies.

Figure 1: Map showing distribution of bore depth across the SQNNSW Hub region.

Cross-reference and link: For more information on the Groundwater, visit the online .

Download the factsheet with more detailed information.

The macadamia industries in Australia have faced severe water shortages in recent years (Deo et al., 2017), and it is likely to be exacerbated by climate change which will trigger drought as a recurrent and inevitable problem in Australian agriculture (Jiang et al., 2020; Paudel et al., 2021). Drought is considered one of the major abiotic stresses that can limit macadamia productivity, particularly in areas with limited availability of fresh water for irrigation. In order to comprehend the drought resiliency in the macadamia industries it is therefore required that the growers consider potential risks associated with climate extremes related to water availability when planning to expand the macadamia industry. However, the current state of understanding of the water requirement for macadamia is very limited upon few studies have been conducted in Australia (Stephenson et al., 2003; Gush and Taylor, 2014) which demonstrated that water use dynamics of the macadamia trees at the orchard level are influenced by several management practices such as spacing, pruning, fertilizer application, and other soil properties. Thus, it is essential to understand the potential water requirement for different critical stages of macadamia trees which could encourage the growers to adopt innovative cultivation strategies for saving and judicious use of water (Toscano et al., 2022). 

This facts sheet will provide hands-on information of the climatic requirements of growing macadamia particularly focusing on water/irrigation requirements in macadamia orchards and different management strategies to better prepare for upcoming drought conditions as well as on-farm management strategies to overcome the drought impacts.

Download the factsheet.

Download the Macadamia water management decision support tool for SQNNSW Innovation Hub region. 

This is a review and illustrations of the Bureau of Meteorology (BOM) forecasts for Southern Queensland and Northern New South Wales Drought Innovation Hub regions (SQNNSW Hub) and farm management strategies. This outlook describes a better understanding of the Bureau of Meteorology (BOM), Australia for short-term weather forecasts and seasonal outlooks for SQNNSW Hub regions.

Note: The rainfall values are in millimetre (mm) and temperature values are in degree Celsius (OC). The technical term “Chance of rainfall” means the likelihood of the selected location receiving more than the minimum measurable amount of rainfall (0.2 mm) over the 24 hours from midnight to midnight. For example, a 50% chance of exceeding (more than) means that there is a 50% chance during the forecasted period of getting the stated amount of rainfall or more, .

Regional Agri Weather Outlook consists of

• Weekly rainfall forecasts and analysisWeekly temperature forecasts and analysis
• Analysis and review of seasonal forecast for short- and long-term periods
• Monthly rainfall comparison and review for the SQNNSW Hub region
• The weather trend charts and distribution maps
• Planting guide based on seasonal weather forecasts
• Broadacre crop calendars for QLD and NSW

For more information: Climate information using the ,The Australian Bureau of  Agricultural and Resource Economics and Science (ABARES), Cropping calendars for natural resource management regions of Australia - Metadata crop calendars.

Download the fact sheet with more detailed information.

This station tool is the online version tool developed by the Centre for Applied Climate Sciences, 黑料吃瓜网 to support the agriculture industry in better climate risk management. These tools provide the ability to analyse rainfall and other climate variables at selected individual locations.

Station tools analysis includes:

• Climate Analysis: This tool provides analysis of rainfall and other climate variables at individual locations and, a comparison of historical and seasonal patterns to support a better understanding of the weather conditions for improved farm management decisions.
• Drought Analysis: This tool provides indicators to classify the severity of the drought conditions in the past and present for a region.
• Climate Change: This tool provides analysis of past, present, and future climate changes arising from natural, unforced variability or changes. The spatial effect is analysed for number of climate variables e.g., dry days, min and max temperature.

Example: Dalby, Queensland

The Dalby at a glance

Dalby region is located on the rich soils of the Darling Downs, the region is well-known as a rich agricultural production, cultivating broadacre crops namely cotton, wheat, sorghum, sunflower, corn, chickpeas and many other crops. Dalby has a humid subtropical climate, is hotter and less humid in summer and colder and drier in winter. The majority of the rainfall is received in the summer months. In the recent past 30-year period, the region has noticed declining rainfall and experienced moderate to extreme drought.

Climate Analysis 

In the last 30 years in Dalby

• Annual rainfall received marginally decreased
• Experienced more hot days
• Number of dry days increased
• Has experienced a greater number of frost days
• Experienced extreme dry conditions in 2023 and severe dry in 2020 and 2007.

Weather and climate in the Dalby region
The regional seasonal climate patterns and knowledge play a very important role for primary growers to make decisions supporting their farm business activities. The purpose of this toolkit is to provide regions climate patterns and an understanding of the changes that occurred in the recent past. This information can help in discussion support for the producers and regional communities to make improved informed decisions for their farm strategies and agribusiness industry.

Annual rainfall in Dalby has been comparatively reduced
Annual rainfall in the Dalby region has marginally declined, with observed rainfall recording an average of 588 mm in the past 30-years (1992-2023) and 713 mm in the previous 30-years (1962-1991). The charts show annual rainfall (black line) and trend (yellow line) for Dalby.

Figure 1: Comparison of annual rainfall (mm) 1992-2023 at Dalby post office.

The monthly average rainfall charts for Dalby show a decrease in rainfall amount in all the months except February in the past 30-years period (1992-2023) compared to the previous 30-years period 1962-1991. While March to September monthly averages recorded a significant decrease in the past 30-years period. However, there is only a marginal decrease in growing season rainfall (October to March) for the Dalby region.

Figure 2: Comparison of 30-year average monthly rainfall (mm) for the period (a) 1992-2023 and (b) (1962-1991) at Dalby post office.

Cross-reference: For more information on the latest observations and statistical analysis behind these changes, visit the , Centre for Applied Climate Sciences (CACS).

Minimum temperature (Tmin) in the Dalby has been slightly increased

Figure 3: Comparison of minimum temperature in the 30-years period, 1992-2023 at Dalby post office.

Seasonal minimum temperature comparison

The monthly average Tmin charts for Dalby show a decrease in Tmin in the past 30-years period (1992-2023) compared to the previous 30-years period 1962-1991. All the months of January to December recorded a marginal decrease in Tmin in the past 30-years period for the Dalby region.

Figure 4: Comparison of monthly minimum temperature (OC) for the period (a) 1992-2023 and (b) (1962-1991) at Dalby post office.

Cross-reference: For more information on the latest observations and statistical analysis behind these changes, visit the historical averages maximum temperature and monthly averages plot in CACS, Unisq Australia website h

Maximum temperature in the Dalby has been slightly increased

Overall Tmax in the Dalby region has been marginally increased, observed Tmax recorded an average of 26.9 OC in the past 30-years (1992-2023) and 26.0 OC in the previous 30-years (1962-1991). The chart shows the annual Tmax (black line) and trend (yellow line) for Dalby.

Seasonal maximum temperature comparison
The monthly average Tmax charts for Dalby show a significant increase in Tmax in the past 30-years period (1992-2023) compared to the previous 30-years period 1962-991. While all the months from January to December recorded an increase in Tmax in the past 30-years period, January, August, and September months recorded the highest increase (> 1 OC) in the Dalby region.

 

Figure 6: Comparison of monthly maximum temperature (OC) for the period (a) 1992-2023 and (b) (1962-1991) at Dalby post office.

Cross-reference: For more information on the latest observations and statistical analysis behind these changes, visit the  in Centre of Applied Climate Science, 黑料吃瓜网 Australia website.

The below drought index chart shows extreme dry conditions experienced in September 2023 for the Dalby region. The analysis indicates severe dry conditions in 2007 and 2020, and moderately dry in 2014 for the same period.

 
Cross-reference: For more information on the drought analysis and index, visit the in Centre of Applied Climate Science, 黑料吃瓜网 Australia website.

Climate Change

Dry days

The charts show the annual number of dry days (median in black line) with a yearly running average. The Dalby region experienced 282 dry days per year between 2000-2019 and 261 dry days per year between 1980-1999. The projected values are expected to be an average of 208 dry days per year between 2040-2069 (range of 131-267 days) and 115 days per year between 2070-2099 (range of 130-276 days).

Maximum Temperature

The charts show the annual number of days above 35 OC (median in black line) with a yearly running average, Dalby region experienced 35 days per year above 35 OC between 2000-2019 and 22 days per year between 1980-1999. The projected values are expected to be an average of 111 days per year above 35 OC between 2040-2069 and 115 days per year between 2070-2099.

 
Minimum Temperature

The chart shows the annual number of days below 2 OC (median in black line) with a yearly running average, Dalby region experienced 33 days per year below 2 OC between 2000-2019 and 25 days per year between 1980-1999. The projected values are expected to be an average of 4 days per year below 2 OC between 2040-2069 and 2 days per year between 2070-2099.



Cross-reference: For more information on climate change and future projections, visit the in Centre of Applied Climate Science, 黑料吃瓜网 Australia website.