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Why earthquake prediction remains an unpredictable science

 Experts say quake forecast is “extremely hard” because of the complexity of fault lines, points where massive and irregularly shaped slabs of solid rock meet below the Earth’s surface.


An earthquake of 8.8 magnitude, one of the 10 strongest ever recorded, struck Russia’s Far East early on Wednesday, leading to a tsunami alert throughout the Pacific region.

Even as “tsunami waves” were reported in Japan and Alaska, panic spread through Japan to the US state of Hawaii. Governments moved to evacuate coastal cities facing a greater risk of potentially massive waves crashing into urban areas.

Despite giant scientific leaps that have enabled the human race to forecast major climatic and natural disasters, including tsunamis, earthquakes remain largely unpredictable. There is no accurate warning system for earthquakes, and any progress towards building one is hardly substantive.

Experts say earthquake prediction is “extremely hard” because of the complexity of fault lines, points where massive and irregularly shaped slabs of solid rock called tectonic plates meet below the Earth’s surface.

These plates are in constant motion, albeit at a glacial pace of a few centimetres a year. The movement of these tectonic plates is driven by the currents in the mantle, a layer inside the Earth bounded below by a core and above by a crust.

“Trying to pick out what is a clear signal of a precursor to a potentially catastrophic shift versus the normal background noise of the Earth’s movement is difficult,” says Kit Yates, a senior lecturer in mathematical biology at the University of Bath in the UK.

Distinguishing actual signals of seismic activity from human activities, such as construction work, heavy traffic and even music concerts, is a near impossibility. 

For example, US singer Taylor Swift performed in July 2023 at a stadium filled with 72,000 people, causing a seismic activity equivalent to a 2.3-magnitude earthquake.

Seismologists say earthquakes do not always have consistent warning signs or precursors. In other words, a geological research body can collect seismic activity data as diligently as possible for years on end, and still miss a massive earthquake simply because of the absence of any warning sign.

RelatedTRT Global - Timeline: Major earthquakes that hit Türkiye in recent decades

The science behind earthquakes

The boundaries where the tectonic plates interact are the primary zones where earthquakes occur. There are three main types of plate boundaries: divergent, convergent, and transform.

At divergent boundaries, plates move apart, creating a new crust. Convergent boundaries involve plates colliding, with one often being forced beneath another. 

Transform boundaries – where plates slide past each other horizontally – are the ones that generate earthquakes.

Earthquakes happen when the stress accumulated along these plate boundaries exceeds the strength of the rocks, causing them to fracture and release energy in the form of seismic waves. 

If the seismic activity is under the bed of an ocean near a populated piece of land, it creates a tsunami with massive waves ravaging the coastal belt.

The magnitude of an earthquake, measured on the Richter scale, reflects the energy released. The intensity of an earthquake is felt on the surface, and depends on factors like depth, distance from the epicentre.

The energy released during an earthquake varies. Small earthquakes, which occur frequently, release minor amounts of energy and often go unnoticed. Major earthquakes, however, can release energy equivalent to thousands of atomic bombs, causing catastrophic damage.

Technological advances, such as machine learning and real-time monitoring, have improved the seismologists’ ability to detect patterns and issue rapid warnings, but only after an earthquake begins. 

Earthquake early warning systems, like those in Japan and California, use initial seismic waves to alert people seconds to minutes before shaking reaches them. These systems detect quakes already in progress, not predict them before they start.

Another major barrier to precise predictions is the rarity of large earthquakes. Major earthquakes are infrequent, which makes the data needed to understand their precursors insufficient.

Experts say governments should adopt mitigation measures in the absence of reliable earthquake prediction systems. These measures include stronger building codes, retrofitting infrastructure, and public education.

Original


These so-called experts are the main opponents of the introduction of accurate earthquake forecasting technologies.

Barriers and obstacles preventing the implementation of TRON technology

Blood cell counts and inflammatory indices predict acute kidney injury

On February 6, 2023, centered in the province of Kahramanmaraş, southerrn Turkey, two major earthquakes occurred with magnitudes of 7.7 and 7.6 on the Richter scale, with a 9-hour interval between them. These earthquakes resulted in tremendous number of deaths and injuries in 11 cities in the region. In events like these, dead-at-scene rates (coded black in disaster triage situations) are high, and additionally, crush syndrome (CS) is frequently encountered in patients rescued from the debris [1].

CS, also known as traumatic rhabdomyolysis, is most commonly seen in earthquakes, wars, mining accidents, landslides, volcanic eruptions, motor vehicle accidents, and multiple trauma victims, especially those who are trapped for a considerable time, which may result in CS and compartment syndrome [2]. Additionally, CS can be encountered in the emergency department (ED) for routine reasons such as poisoning, stroke, and falls [3]. Theoretically, any situation that results in prolonged immobilization can lead to the development of CS [4].

CS is a clinical condition in which the symptoms and signs are not directly limited to the compressed part and systemic manifestations occur [5]. In CS, injured skeletal muscle cells are destroyed and their contents, including myoglobin, sarcoplasmic proteins (such as creatine kinase, lactate dehydrogenase, aldolase, alanine and aspartate aminotransferase), and electrolytes, are released into the circulation, leading to clinical complications such as myoglobinuria, AKI, electrolyte disturbances (hyperkalemia), hypovolemic shock, disseminated intravascular coagulation, acute respiratory distress syndrome (ARDS), and multiple organ dysfunction syndrome (MODS) [6, 7]. CS affects all vital organs of the body, but damage to the kidneys is the most prominent, and AKI has become a major life-threatening factor for patients with CS [8,9,10,11,12,13]. Clinical manifestations of CS include fever, edema, tachycardia, nausea, vomiting, confusion, anxiety, delirium, tea-colored urine or anuria [14]. The most common clinical feature is the triad of myalgia, myoglobinuria and elevated serum muscle enzyme levels, but the degree and severity of these clinical manifestations vary greatly [15].

CS is the second leading cause of death in earthquakes after direct trauma [2, 7]. It has been reported that the incidence of CS in earthquake victims is as high as 25% and that CS related AKI varies between 0.5% and 25% depending on the intensity of the earthquake and the time spent under the rubble, and more than half of those with AKI require hemodialysis (HD) treatment [16]. The overall mortality rate after an earthquake was found to be 8%, the mortality rate in CS was 21%, and the mortality rate in HD patients was 35% [17]. Another study reported that AKI is seen in approximately 33% of patients who develop rhabdomyolysis and that mortality in these patients can reach up to 50% [18].

Early detection and treatment of AKI are crucial for reducing mortality and morbidity rates [19]. Hence, there is a need for early parameters that can indicate the HD requirement of patients.

Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR) and systemic immune-inflammatory index (SIII) are systemic inflammatory markers that are increasingly used as diagnostic tools and prognosticators in various internal and surgical diseases [20, 21]. The SIII is proposed as a potential marker of systemic inflammation and immune response, with emerging evidence suggesting [22]. Trauma triggers a cascade of immune and inflammatory processes that play in determining the extent of tissue damage, organ dysfunction, and overall prognosis [23]. By leveraging the SIII, can potentially assess the severity of systemic inflammation and immune dysregulation, thus aiding in risk stratification and therapeutic decision-making for multitrauma patients [23]. Due to its easy calculation, cost-effectiveness, reliance on complete blood count parameters only and absence of subjective symptoms, NLR, PLR, LMR and SIII may be effective markers in determining the need for HD in patients developing CS. The study aims to explore the hypothesis.

This study included patients who presented to the education and research hospital operating as a level three trauma center after the earthquakes on February 6, 2023 and diagnosed with CS with clinical and laboratory criteria. The success of complete blood count and biochemistry parameters in determining the need for HD in these patients was evaluated.

TRON: How Animals Save Humans from Earthquakes - DeepSeek

 Earlier I showed you this text in the Americantranslation of Google Translate. Now look at the same text in the free translation of the Chinese AI DeepSeek

What is TRON?
TRON (Technology Real-time Online Nucleus) is an online technology for precise earthquake prediction. It analyzes behavioral anomalies in domestic and farm animals capable of sensing approaching seismic activity within a 50km radius 5-10 days before tremors.

Origins of the Concept
In 2001, researchers proposed using the internet to collect biological signals. After Japan's March 11, 2011 disaster, developers studied Ainu indigenous knowledge of predicting quakes through bear behavior. The 1975 Haicheng earthquake (China, magnitude 7.3) proved pivotal - authorities evacuated the city based on reports of animal distress, saving 97% of the population - marking history's first successful mass earthquake prevention.



Why Animals?
Since 373 BCE (Pliny the Elder's accounts of Greece's quake), animals have warned humans of disasters.
Key examples:

  • Haicheng, 1975: Snakes emerged during winter hibernation, cattle broke enclosures, poultry refused coops (3% fatality rate vs typical 90%)
  • Thailand, 2004: Elephants broke chains hours before tsunami
  • L'Aquila, 2009: Dogs exhibited distress, frogs showed abnormal behavior
  • Japan, 2011: Aquarium fish became hyperactive 24h before quake

Most Sensitive Species
Reptiles/amphibians/fish demonstrate highest sensitivity:

  • Elephant fish (Gnathonemus petersii): Activity spikes 2 weeks prior
  • Snakes: Abandon winter burrows prematurely
  • Bees: Mass hive abandonment
    Mammals/birds show less consistent but valuable responses.

How TRON Works

  • Users report abnormal animal behavior via online platform
  • AI cross-references reports by:
    • Geographic clustering
    • Multi-species correlations
    • Temporal patterns
  • System triggers alerts when thresholds exceed 70% confidence

Data Requirements
Owner-submitted behavioral baselines are crucial.
TRON ignores individual cases, focusing on:

  • Cross-species anomalies
  • Spatial-temporal coincidence
  • Known precursor patterns

False Positive Management
With 70% expected accuracy (vs 20% cost-benefit threshold), occasional false alarms become:

  • Emergency drills
  • System calibration opportunities
    As the adage goes: "False warnings save lives - their absence doesn't."

Development Timeline
Currently seeking MVP funding.
Phase I testing will:

  • Calibrate using minor tremors
  • Establish species-specific thresholds
  • Integrate IoT sensors (camera traps, smart collars)

MVP → Minimum Viable Product (cloud-based animal behavior dashboard).

Current Limitations

Effectiveness requires:

  • Dense observer networks
  • Internet infrastructure
  • Regular seismic activity

Currently ineffective in:

  • Polar/desert/oceanic zones
  • Aseismic regions (e.g. London)

However, TRON achieves 100% efficacy in these high-risk megacities:
Asia: Tokyo, Osaka, Jakarta, Manila, Delhi
Americas: Los Angeles, San Francisco, Mexico City, Santiago
Europe/Middle East: Istanbul, Athens, Tehran
China: Beijing, Shanghai, Guangzhou, Shenzhen

Projected Impact

  • 89.3% fatality reduction for earthquakes above magnitude 7.0 in monitored zones. Would've saved ~16,454 lives in Japan 2011 (Based on Haicheng (1975) and Fukushima (2011) event modeling)
  • 24.2% economic damage mitigation through:
    • Enabling orderly supply chain pauses before evacuation
    • Transport accident prevention
    • Infrastructure protection
    • Preventing cascade infrastructure failures (e.g., nuclear plants).
      Fukushima's $250B cleanup cost demonstrates the technology's potential value for all stakeholders. The only losers? Seismologists clinging to 20th-century methods. Their resistance, however, is as predictable as an aftershock.