Monitoring the Impact of Climate Adaptation Measures in agriculture, forests and cities

Summary

Climate change is exponentially increasing the intensity and frequency of extreme events. Climate adaptation has become a necessary strategy to prevent ecosystem deterioration, minimise disasters impact, and support improvements in the quality of human life.

Adaptation actions including reforestation (against forest fires), enforcing irrigation (drought) and increasing urban vegetation (heatwaves) are currently poorly mapped and quantified.

The main goal of the MICAM project is to leverage the long-term satellite data records generated via the ESA Climate Change Initiative (ESA CCI) to improve the monitor the effectiveness of climate change adaptation measures across agriculture, forestry, and urban environments. Assessing the effectiveness of these measures will be achieved through selected case studies as a first step towards upscaling the evaluation at global scale and provision of tools to measure preparedness of different ecosystems in the face of current - and future - climate challenges.

Project background

Weather- and climate-related extremes caused economic losses of assets estimated at EUR 822 billion during 1980 - 2024 in the European Union, with over EUR 208 billion (25%) just between 2021 and 2024¹. Human-induced climate change has unequivocally increased the frequency, intensity, and compounding risk of extreme weather events including droughts and wildfire ². At the global scale, climate change has already reduced yields of staple crops including maize, wheat, and soybeans, while future warming is expected to have severe impacts on crop production ^3,4. Climate-driven heatwaves compound localised urban microclimates, where dense configurations of concrete, asphalt, and lack of vegetation trap heat, to amplify the impact on densely-populated and heavily built cities⁵. Droughts cause water shortages and extreme heat stress on livestock and crops, together with land subsidence, seawater intrusion and ecosystems damage[[[CHECK]]]. In the 2008-2018 decade, FAO estimated an impact of 37 billion USD to global agriculture due to drought (82% of all drought impact worldwide)⁶.

The need for adaptation actions is highlighted by global and European policy mandates. The UN's Global Goal on Adaptation, with its targets and indicators, provides the international framework, to enhance adaptive capacity and reduce vulnerability worldwide⁷. This is reinforced by the 2021 EU Strategy on Adaptation to Climate Change, which commits the Union to becoming climate-resilient by 2050⁸. This EU strategy emphasises the need for smarter, faster, and more systemic adaptation through the use of better data and advanced risk assessment tools, including the wide evaluation of adaptation measures, including also potential downsides to ineffective measures and third-party consequences of the measures themselves.

Forest adaptation actions include species mixing, improved forest management plans, creating firebreaks, and managing harvests. Adaptation measures in agriculture include the efficiency increase of irrigation systems, increased groundwater pumping, switching crop types to more resilient and drought-tolerant species, use of small-scale water reservoirs and reuse of treated wastewater or brackish water. Urban contexts can also employ some adaptation strategies, like urban greenery, the use of climate-responsive materials, optimized urban form, and the inclusion of water bodies.

Evaluating the effectiveness of adaptation measures is hampered by scarcity of ground datasets, making it difficult to systematically track policy success or quantify impacts. EO can overcome this by providing objective, repeatable, and spatially distributed indicators across global water, carbon, and energy cycles to support Global Goal on Adaptation framework. But the use of remote sensing remains heavily one-sided, primarily deployed to detect foundational risks and plan strategies rather than to study the actual effects of implemented adaptations.

Existing observation records, such as European Space Agency Climate Change Initiative are valuable for providing the evidence record for key aspects of the Earth system but cannot directly observe certain variables such as groundwater or human health, and data resolution can, at times, be too coarse to resolve highly localised interventions.

To successfully monitor and evaluate adaptation, research is needed to identify complementary ground and satellite variables and indicators, improve the spatio-temporal resolution of climate records, and verify consistency among long-term trends.

Project goals and objectives

The main goal of the MICAM project is to leverage ESA CCI data products that address Essential Climate Variables (ECVs) for monitoring and quantifying the effectiveness of climate change adaptation measures and risk reduction across agriculture, forestry, and urban environments, through harmonised and scalable indicators to support global adaptation monitoring frameworks. MICAM aims at answering the following research questions:

1. How effective are the agriculture adaptation measures in mitigating drought and water scarcity impacts in the past two decades in the semi-arid context of Southern Europe and the Mediterranean?
2. How have forest management practices influenced fire frequency and severity, as well as ecosystem health and biodiversity in the past two decades across Europe?
3. How effective are urban adaptation measures in mitigating temperature extremes and improving human wellbeing during heatwaves in impacted cities?
4. How can CCI ECVs be enhanced to better address these questions and monitor and quantify the effects of such measures over time?
5. How will these adaptation strategies perform under future climate extremes? Is there a need to activate or increase adaptation measures in new areas that currently have none or only limited measures, due to the increased impact of climate change?

Specifically, the MICAM project aims at quantifying the effect on agriculture, forestry and urban environment of the adaptation measures adopted against their respective risks. Tailored indicators will be employed to describe the following adaptation measures and more: changes in crop water use and productivity and irrigation water availability (against drought and water stress); adaptive forest management and increase of ecosystem resilience (against wildfires); urban greenery and re-planning (against enhanced heatwave impacts on cities). After analysing these phenomena singularly, the goal will be to develop a strategy for scaling these indicators to the global scale, demonstrate the suitability and limitations in terms of accuracy, availability and spatio-temporal resolution of CCI ECVs in these kinds of applications.

Project plans

The MICAM objectives will be reached via four main tasks, breaking down the work as follows

Task 1

Assessment of the current state-of-the-art, the consolidation of project objectives, as well as the design of the requirements in terms of data needs, their uncertainty and the plans for indicators uncertainty evaluation.

Task 2

The collection and harmonisation of the necessary data, spanning across the large list of ESA CCI ECVs, and complementing them with additional ground information and model-derived data products. All the derived data will be collected in the MICAM database, containing data for indicators development and validation. The evaluation and validation using the ground and gridded datasets contained in the project database will be performed, based on traditional metrics such as correlation or mean absolute error.

Task 3

Scientific datasets will be used to address the research questions outlined above. The activities will focus on establishing a methodology for leveraging the MICAM database from Task 2 to derive the indicators that map the impacts of adaptation actions for forestry, agriculture and urban heat island contexts. Before being upscaled, the analyses will first be performed in the selected project case studies:

For forest management:

• the province of Soria (Spain);
• the region of Viseu Dão Lafões (Portugal);
• the alpine forests of Austria

For Agriculture:

• the Oum Er-Rbia river basin, with the Doukkala Irrigation Consortium (Morocco);
• the Puglia region (Italy)

For the urban environment

• Milan (Italy);
• Vitoria-Gasteiz (Spain);
• London (United Kingdom)

In these locations, territory-specific climate change adaptation measures are either active or yet to be implemented, allowing to disentangle the effect of the climate (past decades and future scenarios) from the effect of the interventions. After these analyses, indicator uncertainty will be assessed, together with future changes, based on the CMIP6 climate projections.

Task 4

A Scientific Roadmap will be developed, critically analysing project results and assessing the quality and limitations of the derived indicators to map adaptation measures in different contexts, highlighting the observational gaps in coverage, uncertainty, spatiotemporal resolution requirements and consistency of the ESA CCI ECVs to address the major scientific challenges. Task 4 will also provide a strategy to upscale the developed indicators to operationally map the benefits of the adaptation measures in forest, agricultural and city areas.