In 2018, a dance video featuring two young girls against a backdrop of pink water lilies went viral on TikTok. Captioned ‘Malarikkal Ambal Padam’, the video brought unexpected attention to a village in Kerala’s Kottayam district. What was once primarily an agricultural landscape soon began attracting visitors eager to see the seasonal flowering for themselves, recalls Lijo John, a resident of Malarikkal.

The spot, locally known as J Block 9000, gradually emerged as a tourist destination. Visitors from across Kerala, followed by tourists from other states, began arriving to see the pink flowers covering the flooded paddy fields. Over the years, the annual bloom has become an important source of seasonal income for the village.

The economic impact has been considerable. Local estimates suggest that Malarikkal generated around 6 crore rupees in tourism revenue over four months in 2026. Nearly 200 boat operators offer rides through the flowering fields, while shopkeepers and flower sellers also benefit from the seasonal rush. One boat operator reportedly earned around 3 lakh rupees from boat services during the season, while local accounts indicate that several others made at least 2 lakh rupees. Land prices have also increased, with an acre reportedly valued at around 15 lakh rupees.

The annual flowering season has grown into a major local attraction, prompting the organisation of a dedicated tourism festival. The Malarikkal Water Lily Fest was inaugurated on August 8, 2023, by Kottayam District Police Chief K. Karthik. It was organised by Thiruvarppu Grama Panchayat, the Malarikkal Tourism Council and other local stakeholders.

The flowers are best viewed between 6 am and 9 am, when they are fully open. The flowering season generally lasts from July to October, when the paddy fields remain flooded between cultivation cycles. But the flowers that have brought Malarikkal economic recognition have also raised ecological concerns. A study published in Plant Science Today identifies the pink-flowered water lily spreading across Malarikkal as Nymphaea rubra Roxb. ex Andrews. Researchers have examined its growth, reproduction and spread across the region’s paddy fields.

An earlier ecological investigation by the Jawaharlal Nehru Tropical Botanic Garden and Research Institute (JNTBGRI), however, examined a different pink water lily in another part of Kuttanad. It identified the plant as Nymphaea × omarana, a hybrid water lily. Although both plants belong to the water lily group and produce pink flowers, they have different scientific identities.

An agricultural landscape under pressure

According to Lijo John, one of the landowners of the area, Malarikkal’s 1,850 acres of paddy fields are owned by around 650 individuals. Water lilies grow during the interval between paddy cultivation cycles, spreading across the flooded fields when rice is not being cultivated. Once the flowering season ends, the fields must be prepared for the next agricultural cycle. This creates a practical challenge for landowners and those involved in tourism. Boat rides, for instance, are not permitted in every field.

“There is a field nearby called Thiruvaikkiri. Boats are not allowed there now. Once the water in the field is drained, riding a boat through the field is harmful for the plot,” says Restin K Mathew, a boat operator and Malarikkal resident.

Such restrictions reflect the continuing agricultural importance of these fields. Even as tourism provides seasonal income, the land must remain suitable for paddy cultivation. Tourist activities therefore have to accommodate the requirements of farming. The ecological concerns extend beyond the immediate effects of tourism. The 2026 study, titled Drivers of invasion: The spread of pink-flowered Nymphaea rubra Roxb. ex Andrews in paddy ecosystems of Kuttanad, South India, examines the growth and spread of Nymphaea rubra in Malarikkal.

Published in Plant Science Today, the research examines the plant’s growth patterns and reproductive behaviour in the region’s paddy fields. Field observations conducted in J Block 9000 between June and September 2024 helped researchers study its growth under different water conditions.

The study estimates that the plant produces approximately 65,300 kg of fresh biomass per hectare. It also identifies seeds as the primary means of propagation in the fields, with water helping disperse them. The researchers found that water depth influenced the plant’s growth and flowering, with shallow conditions favouring greater leaf and flower production.

Native aquatic plants face competition

Titled The Pink Bloom of Kuttanadu: An Ecological Investigation, the study was undertaken with support from the Kerala State Biodiversity Board. It identified N. × omarana as an introduced horticultural hybrid suspected to have escaped from nurseries into natural wetlands. Field surveys found it widely distributed across Kuttanad, particularly in inland waterways and paddy fields. The study also recorded reports of the plant in Kozhikode.

One of the major concerns identified by the investigation is the displacement of native aquatic vegetation. The study identifies two native water lily species in the region, Nymphaea pubescens and Nymphaea nouchali, whose survival could be threatened by the spread of N. × omarana.

Lotus (Nelumbo nucifera), once common in Kuttanad, has also become increasingly restricted. According to the investigation, it is now almost confined to certain cultivated ponds. The large leaves of N. × omarana form dense layers across water bodies, limiting the amount of sunlight reaching the water. This can alter conditions for algae and other aquatic organisms that depend on these habitats.

The investigation also records reduced natural water flow in affected parts of Kuttanad. Interactions with local residents revealed that the spread of the hybrid water lily had coincided with the accumulation of sludge and decaying plant material, contributing to deteriorating water quality. Traditional water transportation has also reportedly been affected.

The researchers raise concerns about methane production from accumulated decaying vegetation. The extensive foliage is also reported to reduce evaporation, potentially influencing local humidity. These effects require further field measurements to establish their extent. The plant’s resistance to eradication efforts adds to the challenge of controlling its spread. These findings relate to the hybrid water lily examined in the JNTBGRI investigation.

The Ecological Questions Surrounding Its Removal

At Malarikkal, the water lilies are cleared after the flowering season to prepare the fields for the next paddy cycle. According to landowner Lijo John, herbicides are used to eliminate the plants. This raises another set of environmental questions. The ecological impact of the plant’s growth needs to be considered alongside the possible consequences of the methods used to remove it.

The chemicals involved, their concentrations, application methods and the possibility of residues entering the water require further investigation. Their potential effects on fish, aquatic insects, other plants and water quality are particularly relevant in a landscape where agricultural activity and aquatic life share the same water bodies.

Local fish varieties include cheru meen, varaal, vaala and kaari. Whether the seasonal growth of the lilies or the herbicides used to remove them affects these fish populations remains unknown. The available research does not provide measurements of pesticide residues, dissolved oxygen levels or changes in fish populations in Malarikkal.

A site-specific assessment would help establish these effects. Monitoring water quality and aquatic biodiversity during the flowering, plant-removal and cultivation periods could provide a clearer picture of the changes taking place in the fields.

Exploring Alternative Uses For the Water Lily

The economic value of the flowering season makes the management of the water lilies more complicated. The plants now support a tourism economy that provides income to boat operators, shopkeepers and other local businesses. Finding ways to manage their spread while accounting for these livelihoods is an important part of the challenge.

Dr E. A. Siril, Professor and Head of the Department of Botany at the University of Kerala’s Kariavattom campus, is exploring the possibility of developing value-added products from water lilies. The research examines the use of the plant in products such as herbal tea, face wash, incense sticks, leaf plates and soap. Samples have been collected from Attingal and nearby locations to assess their suitability.

“Our study is about making value-added products from water lilies. Herbal tea, facewash etc. As far as we have considered it is economically viable as well. We collected samples from Attingal and nearby places. So far they are going good,” says Siril.

The plant’s seasonal availability, however, poses a challenge for commercial production. “The only problem regarding its economic viability is that it is a seasonal plant. Its unavailability in other seasons can affect the production,” he says. Siril believes that alternative uses could help derive economic value from the plant while addressing concerns about its invasive growth.

“As this is an invasive species, and they generate a lot of income through tourism, what we need to look at is other such alternative methods where we can put them into use,” he says.

The product-development work is still at an exploratory stage. Its commercial viability, production capacity and ability to utilise substantial quantities of harvested plant material will need to be established before it can contribute meaningfully to managing the plants’ spread.

Protecting the Wetland Without Overlooking Livelihoods

Malarikkal’s landowners have reservations about greater government intervention in the fields. Some consider the land private property and are concerned that additional regulations could interfere with how they manage cultivation and tourism.

This presents a challenge for wetland conservation. The fields support agricultural activity, provide seasonal tourism income and form part of the wider Kuttanad wetland ecosystem. Any effort to manage the spread of the water lilies must account for all three. The ecological investigations highlight the need for a better understanding of the plants’ spread and their effects on Kuttanad’s wetlands. For Malarikkal, this would involve examining seasonal changes in native aquatic vegetation, water quality and biodiversity, alongside the effects of clearing the plants before cultivation resumes.

The pink bloom has given Malarikkal a new economic identity. Its future, however, remains closely tied to the health of the paddy fields and the wetland ecosystem that sustains them. Understanding the ecological consequences of the flowering, tourism activities and plant-removal practices will be essential to managing this landscape without undermining the livelihoods it now supports.

The global average surface temperature between January and September 2026 was approximately 1.47°C above pre-industrial levels, according to the World Meteorological Organization’s (WMO) latest State of the Climate Update 2026. The past 12 years, from 2015 to 2026, are on track to be the warmest on record, as rising greenhouse gas concentrations continue to increase the amount of heat trapped in the Earth’s climate system. Reliable climate prediction is becoming need of the hour as scientists work to understand how continued warming could affect future weather patterns, ecosystems and human populations.

Understanding how different emissions pathways could influence future temperatures, rainfall and other climate conditions requires extensive computer modelling. However, running comprehensive Earth system models can take months for a single climate scenario, limiting how many possible futures scientists can examine.

Massachusetts Institute of Technology (MIT) have now developed a new artificial intelligence training technique that could reduce the computational effort involved in this process. Their method uses carefully generated synthetic data to train climate emulators, potentially reducing the number of full-scale climate model runs required from six or eight to just one. The researchers also report improved performance when these AI models are tested against emissions scenarios they have not encountered during training.

Climate Prediction: Why Climate Scientists Need Faster Models

Earth system models are among the most comprehensive tools used to project long-term changes in the climate. They simulate interactions between different components of the Earth system and help scientists estimate how temperature, rainfall and other climate variables could respond to changing greenhouse gas emissions. However, their computational demands are considerable. Running an ESM on a supercomputer can take months to produce a single future climate projection.

Climate emulators offer a faster alternative. They are trained to replicate the outputs of full-scale climate models and can produce simulations in seconds. This allows researchers to test thousands of emissions scenarios instead of relying on a limited number of computationally expensive runs. However, the reliability of these AI models depends heavily on the data used to train them.

Scientists commonly train climate emulators using six to eight future emissions scenarios based on realistic projections. Each scenario must first be processed through a full-scale Earth system model, making the preparation of training data both expensive and time-consuming. The MIT researchers found that this approach could also leave emulators struggling to predict scenarios that differ from the ones they encountered during training.

Training AI With Synthetic Climate Scenarios

To address this limitation, the researchers developed an algorithm that generates synthetic emissions scenarios specifically designed to improve an emulator’s predictive ability. Unlike conventional training datasets, these synthetic scenarios do not have to follow realistic patterns of future emissions. Instead, the algorithm identifies variations that help the AI model learn more about how the climate system responds to changing emissions.

The process begins with an initial climate scenario generated using a relatively fast and simple climate model. The researchers then compare the emulator’s predictions with the results of the Earth system model to measure its errors. The algorithm repeatedly adjusts the training data to reduce these errors. For example, it may introduce a sharp increase in carbon dioxide emissions around 2050 or a rapid reduction in methane emissions in 2037.

These changes produce emissions trajectories with rapid fluctuations, rather than the smoother patterns generally seen in conventional future projections. According to the researchers, these variations help the emulator capture more information about the overall climate system. An important advantage is that the method requires just one full-scale Earth system model run to generate the training data, compared with the six to eight runs typically needed for conventional approaches.

Why Adaptability Matters for Climate Policy

The ability to predict unfamiliar scenarios is particularly important when scientists assess the effects of specific climate policies. For instance, a government may introduce regulations to reduce one pollutant while emissions of other greenhouse gases continue to increase. Understanding how the climate responds to such an intervention requires models that can account for changes that may not follow conventional emissions projections.

The MIT researchers found that emulators trained using their technique could capture the effects of local pollution-control policies that reduce one pollutant while other emissions continue rising. The traditional emulators tested by the team failed to reproduce these outcomes. This could make the technique useful for evaluating targeted interventions and examining how different policy decisions influence future climate conditions.

Accurate climate projections also inform decisions beyond emissions policy, including planning for resilient power grids, protecting public health and safeguarding agricultural production. The research was led by Christopher Womack, a PhD graduate of MIT who is now a postdoctoral researcher at ETH Zurich. The team also included researchers from MIT’s Department of Earth, Atmospheric and Planetary Sciences, its Center for Sustainability Science and Strategy, and Imperial College London. Noelle E. Selin, professor at MIT and director of its Center for Sustainability Science and Strategy, was the senior author.

The researchers plan to test the technique using emissions scenarios generated by a full-scale Earth system model. They also intend to examine its application to other climate models and explore whether the approach could be useful in broader machine learning applications. The work was supported by Schmidt Sciences through the MIT Grand Challenges initiative and was part of the Bringing Computation to the Climate Challenge project.

Global climate finance reached an unprecedented annual average of $1.9 trillion in 2023–2024, increasing by 32 per cent compared with the previous two-year period. However, despite the growth in investment, developing countries continue to face significant barriers in accessing the resources needed to adapt to climate change, according to assessments by the United Nations Framework Convention on Climate Change (UNFCCC) and the Organisation for Economic Co-operation and Development (OECD).

The findings come as countries meet for the 31st United Nations Climate Change Conference (COP31) in Antalya, Türkiye, from November 9 to 20. The conference takes place during the transition from the previous $100 billion annual climate-finance commitment to a new target of $300 billion by 2035.

Developed countries exceed $100 billion target, but questions remain

Developed countries had pledged to mobilise $100 billion annually by 2020 to support climate action in developing countries. The commitment was subsequently extended through 2025. According to the OECD’s 2026 assessment, developed countries provided and mobilised $132.8 billion in 2023 and $136.7 billion in 2024, exceeding the target for the third consecutive year.

However, the reported totals do not necessarily represent grants or money directly disbursed to developing countries. They include different forms of public finance, multilateral development bank contributions and private finance mobilised through public interventions.

Differences in accounting methods have also complicated assessments of whether countries are meeting their commitments. The UNFCCC’s 2026 assessment highlights variations in how countries report loans, grants, commitments and disbursements, making comparisons between datasets difficult.

Total global climate finance reached an annual average of USD 1.9 trillion in 2023–2024.

The earlier target is now being replaced by the New Collective Quantified Goal (NCQG), adopted at COP29 in 2024. It calls for developed countries to take the lead in mobilising at least $300 billion annually for developing countries by 2035. The wider ambition is to scale up climate finance from all sources to at least $1.3 trillion annually by the same year.

Adaptation remains dependent on public finance

The expansion of climate finance has not translated into comparable support for adaptation. Investments in mitigation, including renewable energy and low-emission transport, have attracted substantial private capital. Adaptation projects such as flood protection, resilient agriculture, water management and coastal infrastructure, however, often generate fewer direct commercial returns.

The OECD reported that developed countries’ adaptation finance reached $33.6 billion in 2023 and $34.7 billion in 2024. Public finance accounted for more than 90 per cent of the tracked adaptation finance in both years, highlighting the continued dependence of adaptation initiatives on government and multilateral funding.

The broader financing gap is considerably larger. The United Nations Environment Programme’s Adaptation Gap Report 2026 estimates that developing countries will require approximately $305 billion annually by 2035 to meet their adaptation needs. This is substantially higher than the current international public adaptation finance flows.

LDCs and island nations receive a limited share

The financing imbalance is particularly significant for Least Developed Countries (LDCs) and Small Island Developing States (SIDS), which face high exposure to extreme weather, rising sea levels and other climate-related risks.

According to the OECD, LDCs received an annual average of $24.5 billion in climate finance in 2023–2024. SIDS received $3.8 billion in each of those years. The figures underline the limited scale of financial support reaching countries with substantial adaptation requirements.

A report published by the United Nations Capital Development Fund ahead of COP31 found that LDCs, which are home to almost 20 per cent of the global population, received only 1.9 per cent of global climate finance in 2024.

The terms on which finance is provided are also important. The UNFCCC’s assessment found that loans accounted for 91 per cent of multilateral development bank climate finance in its 2023–2024 channel-level breakdown. While loans can support large infrastructure projects, debt-based finance may place additional pressure on countries already facing economic constraints.

COP31 must move from targets to delivery

The latest figures reveal a gap between the scale of global climate investment and the resources reaching countries most vulnerable to climate impacts. Although the new $300 billion target represents an increase in the international climate-finance commitment, its effectiveness will depend on how much funding is accessible, predictable and directed towards adaptation.

For developing countries, particularly LDCs and SIDS, increasing the grant component, improving transparency in financial reporting and expanding concessional funding will be essential.

COP31 offers an opportunity to address these concerns as countries begin implementing the new climate-finance framework. The challenge is no longer only to mobilise larger sums, but to ensure that finance reaches communities facing the greatest climate risks.