Broadband seismometers, though designed to record ground motion generated by earthquakes, are also sensitive to a wide range of other processes occurring at the interface between the solid Earth, oceans, and atmosphere, often considered noise. In the sub-seismic band (1–24 hours), they can detect tidal signals but are limited by self-noise for weaker Earth and atmospheric processes. By applying a coherence-based network stacking technique to large seismic arrays, we identify weak, periodic gravity signals at these frequencies. Using three years of collocated vertical seismic and pressure data from USArray, we demonstrate the atmospheric origin of these oscillations. Coherence and transfer function analysis reveal strong links between pressure and seismic acceleration at atmospheric tide periods. The transfer function shows frequency dependence consistent with superconducting gravimeter observations, and its consistently negative phase indicates that pressure increases correspond to decreases in gravitational acceleration. This confirms Newtonian attraction from atmospheric mass changes as the dominant mechanism. Our results show that network stacks of broadband seismometers can detect atmospheric gravity variations as small as 10–100 nanogals, demonstrating their value for gravimetry and for observing atmospheric dynamics. This approach also provides a framework to estimate atmospheric noise in the sub-seismic range, improving the detection of solid Earth signals once such contamination is removed.
<p>Future hydrological projections exhibit significant discrepancies among models, undermining confidence in the predicted magnitude and timing of hydrological extremes. Here we show that observation-constrained changes in global mean terrestrial water storage (TWS), excluding Greenland and Antarctica, could be approximately 83 mm lower than raw projections from the Inter-Sectoral Impact Model Intercomparison Project phase 3b (ISIMIP3b) by the end of this century under both the low (SSP1-2.6) and high (SSP3-7.0) future forcing scenarios. Notably, the 95th percentile upper bounds are substantially reduced from 2 to <span class="inline-formula">−</span>96 mm under the low-emissions scenario and from 8 to <span class="inline-formula">−</span>105 mm under the high-emissions scenario, revealing a notable overestimation of global freshwater availability in the raw model projections. Global models are intricate process representations, making it challenging to isolate causes of their differences with observations. However, by leveraging the emergent constraint (EC) methodology and inter-model spread to empirically adjust biases against observations, we derive more tightly constrained estimates of future TWS changes than those obtained from conventional, unconstrained approaches. The EC-corrected estimates are substantially lower than the raw ISIMIP3b projections, implying that current water resource planning may underestimate the severity of future water shortages, particularly if global water demand remains stable or continues to rise. Our findings pinpoint the urgent need to reduce model uncertainties and enhance the reliability of future hydrological projections to better inform water resource management and climate adaptation strategies.</p>
Mushfiqur Rahman, Sung Joon Maeng, Ismail Guvenc
et al.
Radio Dynamic Zones (RDZs) are geographically defined areas specifically allocated for testing new wireless technologies. It is essential to safeguard the regular spectrum users outside the zones from the interference caused by the deployed equipment within this zone. Previous works have utilized sparse reference signal received power (RSRP) measurements collected by unmanned aerial vehicles (UAVs) to construct a dense 3D radio map through ordinary Kriging. In this work, we illustrate that matrix completion can outperform ordinary Kriging. We partitioned a 2D area of interest into small square grids where each grid corresponds to a single entry of a matrix. The matrix completion algorithm learns the global structure of the radio environment map by leveraging the low-rank property of propagation maps. Additionally, we illustrate that the simple Kriging and trans-Gaussian Kriging yield better results when the density of known measurements is lower. Earlier works of RSRP prediction involved a training dataset at a single altitude. In this work, we also show that performance can be improved by utilizing a combined dataset from multiple altitudes.
Classical hydrodynamics rests on the point-particle idealization, leading to parabolic transport equations, infinite signal speeds, and the inability to capture finite time relaxation, anisotropic transport, or non Fourier thermal phenomena. This work introduces Extended Structural Dynamics (ESD), a kinetic framework in which constituents are described as spatially extended objects possessing orientation, angular momentum, and internal deformation modes. Starting from an extended Boltzmann equation, a Chapman Enskog expansion with BGK closure yields two hyperbolic parabolic transport laws: a dynamical spin equation coupling orientational relaxation to fluid vorticity, and a heat flux relaxation equation with structural thermal conductivity. These equations predict finite propagation speeds for momentum and heat, intrinsic shock regularization, anisotropic transport, and thermal waves. The spin equation provides a kinetic derivation of micropolar fluid theory, while the heat flux equation supplies a microscopic foundation for Cattaneo Vernotte behavior. Quantitative estimates indicate structural contributions can dominate classical transport coefficients. The BGK closure preserves the qualitative geometric structure of extended phase space and captures correct scaling; the connection between the orientational relaxation time and Lyapunov instability is established independently. The resulting scaling laws follow from rotational-translational coupling. Predictions include Mpemba crossover time for colloidal ellipsoids and shock width for asymmetric molecules, both testable with existing techniques.
This experimental study examines the effects of landfill leachate contamination on soil hydraulic conductivity over a 12-month period, addressing the current lack of long-term experimental data in this field. Laboratory permeability tests were performed on sandy clayey silt samples contaminated with leachate at concentrations ranging from 5% to 25%. Microstructural and mineralogical analyses were conducted using SEM and XRD to identify the mechanisms behind observed changes. The results identify a critical threshold at 15% contamination, where soil behavior transitions from granular to cohesive characteristics. Hydraulic conductivity increases at low contamination levels (5–10%, up to 1.2 × 10<sup>−7</sup> m/s) but decreases significantly at higher levels (4.172 × 10<sup>−8</sup> m/s at 15%, 8.545 × 10<sup>−9</sup> m/s at 20%). These changes are controlled by contamination level rather than exposure time, with values remaining stable throughout the 12-month period. The study provides essential parameters for landfill design and contamination assessment, demonstrating how leachate concentration affects long-term soil hydraulic properties through mineral formation and structural modification.
Rapidly obtaining spatial distribution maps of secondary disasters triggered by strong earthquakes is crucial for understanding the disaster-causing processes in the earthquake hazard chain and formulating effective emergency response measures and post-disaster reconstruction plans. On April 3, 2024, a MW 7.4 earthquake struck offshore east of Hualien, Taiwan, China, which triggered numerous coseismic landslides in bedrock mountain regions and severe soil liquefaction in coastal areas, resulting in significant economic losses. This study utilized post-earthquake emergency data from China's high-resolution optical satellite imagery and applied visual interpretation method to establish a partial database of secondary disasters triggered by the 2024 Hualien earthquake. A total of 5 348 coseismic landslides were identified, which were primarily distributed along the eastern slopes of the Central Mountain Range watersheds. In high mountain valleys, these landslides mainly manifest as localized bedrock collapses or slope debris flows, causing extensive damage to highways and tourism facilities. Their distribution partially overlaps with the landslide concentration zones triggered by the 1999 Chi-Chi earthquake. Additionally, 6 040 soil liquefaction events were interpreted, predominantly in the Hualien Port area and the lowland valleys of the Hualien River and concentrated within the IX-intensity zone. Widespread surface subsidence and sand ejections characterized soil liquefaction. Verified against local field investigation data in Taiwan, rapid imaging through post-earthquake remote sensing data can effectively assess the distribution of coseismic landslides and soil liquefaction within high-intensity zones. This study provides efficient and reliable data for earthquake disaster response. Moreover, the results are critical for seismic disaster mitigation in high mountain valleys and coastal lowlands.
Geophysics. Cosmic physics, Dynamic and structural geology
Brittany N. Hupp, Mohammed S. Hashim, Raquel Bryant
et al.
Scientific ocean drilling (SciOD) has been invaluable in advancing our understanding of Earth history. However, the most recent international SciOD programme ended in 2024, alongside the non-renewal of the riserless drilling vessel, the JOIDES Resolution. The US has not committed to joining a new SciOD programme despite prior efforts focused on important scientific priorities (e.g. climate change, assessing natural hazards). During this critical juncture, we argue that incorporating accessibility, justice, equity, diversity and inclusion (AJEDI) efforts will further develop a cohesive community that is well prepared to tackle questions critical to the US and global community. Herein we provide recommendations to develop a knowledgeable and diverse community of scientists in the changing landscape of US SciOD, as informed by historical participation data and recent efforts by early career scientists. Recommendations focus on accessible training opportunities, enhanced stewardship of archived materials, additional funding for research at all academic levels, inclusion of cultural advisors and social scientists, and a commitment to continuing SciOD education. By pursuing these recommendations, the US SciOD community could become a leader for modelling AJEDI principles and ensuring equitable knowledge transfer that is needed to reimagine and rebuild a new, inclusive SciOD programme.
Simon Ghyselincks, Valeriia Okhmak, Stefano Zampini
et al.
Reconstructing the structural geology and mineral composition of the first few kilometers of the Earth's subsurface from sparse or indirect surface observations remains a long-standing challenge with critical applications in mineral exploration, geohazard assessment, and geotechnical engineering. This inherently ill-posed problem is often addressed by classical geophysical inversion methods, which typically yield a single maximum-likelihood model that fails to capture the full range of plausible geology. The adoption of modern deep learning methods has been limited by the lack of large 3D training datasets. We address this gap with \textit{StructuralGeo}, a geological simulation engine that mimics eons of tectonic, magmatic, and sedimentary processes to generate a virtually limitless supply of realistic synthetic 3D lithological models. Using this dataset, we train both unconditional and conditional generative flow-matching models with a 3D attention U-Net architecture. The resulting foundation model can reconstruct multiple plausible 3D scenarios from surface topography and sparse borehole data, depicting structures such as layers, faults, folds, and dikes. By sampling many reconstructions from the same observations, we introduce a probabilistic framework for estimating the size and extent of subsurface features. While the realism of the output is bounded by the fidelity of the training data to true geology, this combination of simulation and generative AI functions offers a flexible prior for probabilistic modeling, regional fine-tuning, and use as an AI-based regularizer in traditional geophysical inversion workflows.
The optimization-based damage detection and damage state digital twinning capabilities are examined here of a novel conditional-labeled generative adversarial network methodology. The framework outperforms current approaches for fault anomaly detection as no prior information is required for the health state of the system: a topic of high significance for real-world applications. Specifically, current artificial intelligence-based digital twinning approaches suffer from the uncertainty related to obtaining poor predictions when a low number of measurements is available, physics knowledge is missing, or when the damage state is unknown. To this end, an unsupervised framework is examined and validated rigorously on the benchmark structural health monitoring measurements of Z24 Bridge: a post-tensioned concrete highway bridge in Switzerland. In implementing the approach, firstly, different same damage-level measurements are used as inputs, while the model is forced to converge conditionally to two different damage states. Secondly, the process is repeated for a different group of measurements. Finally, the convergence scores are compared to identify which one belongs to a different damage state. The process for both healthy-to-healthy and damage-to-healthy input data creates, simultaneously, measurements for digital twinning purposes at different damage states, capable of pattern recognition and machine learning data generation. Further to this process, a support vector machine classifier and a principal component analysis procedure is developed to assess the generated and real measurements of each damage category, serving as a secondary new dynamics learning indicator in damage scenarios. Importantly, the approach is shown to capture accurately damage over healthy measurements, providing a powerful tool for vibration-based system-level monitoring and scalable infrastructure resilience.
The dynamic structural load identification capabilities of the gated recurrent unit, long short-term memory, and convolutional neural networks are examined herein. The examination is on realistic small dataset training conditions and on a comparative view to the physics-based residual Kalman filter (RKF). The dynamic load identification suffers from the uncertainty related to obtaining poor predictions when in civil engineering applications only a low number of tests are performed or are available, or when the structural model is unidentifiable. In considering the methods, first, a simulated structure is investigated under a shaker excitation at the top floor. Second, a building in California is investigated under seismic base excitation, which results in loading for all degrees of freedom. Finally, the International Association for Structural Control-American Society of Civil Engineers (IASC-ASCE) structural health monitoring benchmark problem is examined for impact and instant loading conditions. Importantly, the methods are shown to outperform each other on different loading scenarios, while the RKF is shown to outperform the networks in physically parametrized identifiable cases.
On January 1, 2024 at 16:10:09 JST, an Mj 7.6 earthquake struck the Noto Peninsula in the southern part of the Sea of Japan. This location has been experiencing an earthquake swarm for more than three years. Here, we provide an overview of this earthquake, focusing on the slip distribution of the mainshock and its relationship with the preceding swarm. We also reexamined the source areas of other large earthquakes that occurred around the Sea of Japan in the past and compared them with the Matsushiro earthquake swarm in central Japan from 1964 to 1968. The difference between the Matsushiro earthquake swarm and the Noto earthquake swarm is the surrounding stress field. The Matsushiro earthquake swarm was a strike-slip stress field, so the cracks in the crust were oriented vertically. This allowed fluids seeped from the depths to rise and flow out to the surface. On the other hand, the Noto area was a reverse fault stress field. Therefore, the cracks in the earth's crust were oriented horizontally. Fluids flowing underground in deep areas could not rise and spread over a wide area in the horizontal plane. This may have caused a large amount of fluid to accumulate underground, triggering a large earthquake. Although our proposed mechanism does not take into account other complex geological conditions into consideration, it may provide a simple way to explain why the Noto swarm is followed by a large earthquake while other swarms are not.
Geophysics. Cosmic physics, Dynamic and structural geology
<p>Oceanic bromoform (CHBr<span class="inline-formula"><sub>3</sub></span>) is an important precursor of atmospheric bromine. Although highly relevant for the future halogen burden and ozone layer in the stratosphere, global CHBr<span class="inline-formula"><sub>3</sub></span> production in the ocean and its emissions are still poorly constrained in observations and are mostly neglected in climate models. Here, we newly implement marine CHBr<span class="inline-formula"><sub>3</sub></span> in the second version of the state-of-the-art Norwegian Earth System Model (NorESM2) with fully coupled interactions of ocean, sea ice, and atmosphere. Our results are validated using oceanic and atmospheric observations from the HalOcAt (Halocarbons in the Ocean and Atmosphere) database. The simulated mean oceanic concentrations (6.61 <span class="inline-formula">±</span> 3.43 pmol L<span class="inline-formula"><sup>−1</sup>)</span> are in good agreement with observations from open-ocean regions (5.02 <span class="inline-formula">±</span> 4.50 pmol L<span class="inline-formula"><sup>−1</sup>)</span>, while the mean atmospheric mixing ratios (0.76 <span class="inline-formula">±</span> 0.39 ppt) are lower than observed but within the range of uncertainty (1.45 <span class="inline-formula">±</span> 1.11 ppt). The NorESM2 ocean emissions of CHBr<span class="inline-formula"><sub>3</sub></span> (214 Gg yr<span class="inline-formula"><sup>−1</sup>)</span> are within the range of or higher than previously published estimates from bottom-up approaches but lower than estimates from top-down approaches. Annual mean fluxes are mostly positive (sea-to-air fluxes); driven by oceanic concentrations, sea surface temperature, and wind speed; and dependent on season and location. During winter, model results imply that some oceanic regions in high latitudes act as sinks of atmospheric CHBr<span class="inline-formula"><sub>3</sub></span> due to their elevated atmospheric mixing ratios. We further demonstrate that key drivers for oceanic and atmospheric CHBr<span class="inline-formula"><sub>3</sub></span> variability are spatially heterogeneous. In the tropical West Pacific, which is a hot spot for oceanic bromine delivery to the stratosphere, wind speed is the main driver for CHBr<span class="inline-formula"><sub>3</sub></span> fluxes on an annual basis. In the North Atlantic, as well as in the Southern Ocean region, atmospheric and oceanic CHBr<span class="inline-formula"><sub>3</sub></span> variabilities interact during most of the seasons except for the winter months, when sea surface temperature is the main driver. Our study provides an improved process-based understanding of the biogeochemical cycling of CHBr<span class="inline-formula"><sub>3</sub></span> and more reliable natural emission estimates, especially on seasonal and spatial scales, compared to previously published model estimates.</p>
Mehran Ebrahimi, Hyunmin Cheong, Pradeep Kumar Jayaraman
et al.
In optimizing real-world structures, due to fabrication or budgetary restraints, the design variables may be restricted to a set of standard engineering choices. Such variables, commonly called categorical variables, are discrete and unordered in essence, precluding the utilization of gradient-based optimizers for the problems containing them. In this paper, incorporating the Gumbel-Softmax (GSM) method, we propose a new gradient-based optimizer for handling such variables in the optimal design of large-scale frame structures. The GSM method provides a means to draw differentiable samples from categorical distributions, thereby enabling sensitivity analysis for the variables generated from such distributions. The sensitivity information can greatly reduce the computational cost of traversing high-dimensional and discrete design spaces in comparison to employing gradient-free optimization methods. In addition, since the developed optimizer is gradient-based, it can naturally handle the simultaneous optimization of categorical and continuous design variables. Through three numerical case studies, different aspects of the proposed optimizer are studied and its advantages over population-based optimizers, specifically a genetic algorithm, are demonstrated.
Gait abnormality detection is critical for the early discovery and progressive tracking of musculoskeletal and neurological disorders, such as Parkinson's and Cerebral Palsy. Especially, analyzing the foot-floor contacts during walking provides important insights into gait patterns, such as contact area, contact force, and contact time, enabling gait abnormality detection through these measurements. Existing studies use various sensing devices to capture such information, including cameras, wearables, and force plates. However, the former two lack force-related information, making it difficult to identify the causes of gait health issues, while the latter has limited coverage of the walking path. In this study, we leverage footstep-induced structural vibrations to infer foot-floor contact profiles and detect gait abnormalities. The main challenge lies in modeling the complex force transfer mechanism between the foot and the floor surfaces, leading to difficulty in reconstructing the force and contact profile during foot-floor interaction using structural vibrations. To overcome the challenge, we first characterize the floor vibration for each contact type (e.g., heel, midfoot, and toe contact) to understand how contact forces and areas affect the induced floor vibration. Then, we leverage the time-frequency response spectrum resulting from those contacts to develop features that are representative of each contact type. Finally, gait abnormalities are detected by comparing the predicted foot-floor contact force and motion with the healthy gait. To evaluate our approach, we conducted a real-world walking experiment with 8 subjects. Our approach achieves 91.6% and 96.7% accuracy in predicting contact type and time, respectively, leading to 91.9% accuracy in detecting various types of gait abnormalities, including asymmetry, dragging, and midfoot/toe contacts.
Nearly 30 years after the discovery of the first exoplanet around a main sequence star, thousands of planets have now been confirmed. These discoveries have completely revolutionized our understanding of planetary systems, revealing types of planets that do not exist in our solar system but are common in extrasolar systems, and a wide range of system architectures. Our solar system is clearly not the default for planetary systems. The community is now moving beyond basic characterization of exoplanets (mass, radius, and orbits) towards a deeper characterization of their atmospheres and even surfaces. With improved observational capabilities there is potential to now probe the geology of rocky exoplanets; this raises the possibility of an analogous revolution in our understanding of rocky planet evolution. However, characterizing the geology or geological processes occurring on rocky exoplanets is a major challenge, even with next generation telescopes. This chapter reviews what we may be able to accomplish with these efforts in the near-term and long-term. In the near-term, the James Webb Space Telescope (JWST) is revealing which rocky planets lose versus retain their atmospheres. This chapter discusses the implications of such discoveries, including how even planets with no or minimal atmospheres can still provide constraints on surface geology and long-term geological evolution. Longer-term possibilities are then reviewed, including whether the hypothesis of climate stabilization by the carbonate-silicate cycle can be tested by next generation telescopes. New modeling strategies sweeping through ranges of possibly evolutionary scenarios will be needed to use the current and future observations to constrain rocky exoplanet geology and evolution.
<p>Groundwater is a vital resource for the development of
urban areas, where the problem focuses on the quantity and on the quality of
this freshwater resource. Barcelona is a good example as because currently
groundwater is used for irrigation of parks and gardens and street cleaning
due to its poor quality as drinking water source. Among the pollutants found
in groundwater, of special interest are contaminants of emerging concern
(CEC), as they pose a high risk to the aquatic environment and human health.
The behaviour, spatial distribution and processes that control them in the
aquatic environment are still uncertain and most of them are unregulated. In
this paper we study the inputs and processes controlling the hydrochemistry
of Barcelona urban groundwater with special emphasis on the CEC. We selected
29 CEC that were detected at high concentrations of up to 1 <span class="inline-formula">µ</span>g L<span class="inline-formula"><sup>−1</sup></span> (e.g.
gemfibrozil, benzotriazole, among others). Towards the higher zones we
identify groundwater with relative low mineralization more proximate to the
natural recharge composition, while towards the urban area the anthropic
inputs are evident (e.g. nitrate concentrations range from 50 to 200 mg L<span class="inline-formula"><sup>−1</sup></span>).
Near the Besòs river there is a clear contribution from this superficial
water highly polluted, mostly from wastewater treatment plant (WWTP)
discharges, and reducing conditions. The main contributor of CEC pollution
in groundwater was the river-aquifer interaction (Besòs river), while
towards the urban area it might come from sewage seepage and probably a
minor input from urban runoff. The redox state of these waters seems to
control the fate and occurrence of several of these CEC. The limitations of
this study are restricted to a single sampling campaign, therefore these
results should be corroborated with other sampling campaigns, including the
seasonal variations, which would allow establishing more robust conclusions.</p>
Ковалев Дмитрий Петрович, Ковалев Петр Дмитриевич, Зарочинцев Виталий Сергеевич
et al.
Рассматриваются результаты изучения длинноволновых движений с периодами более 20 ч на шельфе юго-западного побережья о. Сахалин с использованием полученных в натурных экспериментах временных серий колебаний уровня моря с дискретностью 1 с и продолжительностью от 4 до 6 мес. Спектральный анализ временных серий колебаний уровня моря для диапазона периодов от 8 до 200 ч выявил наличие длинноволновых процессов с периодами от 26.1 до 46.7 ч, которые значительно превышают инерционный период 16.48 ч. Численное моделирование шельфовых волн для экспоненциально выпуклых профилей морского дна, проведенное с использованием дисперсионного соотношения В.Т. Бухвальда и Дж.К. Адамса для волн континентального шельфа, показало, что обнаруженные волновые процессы с периодами от 31.2 ч до 46.7 ч являются шельфовыми волнами. Их амплитуды увеличиваются во время штормов; показана возможность передачи энергии от атмосферных возмущений шельфовым волнам, которые вносят вклад в формирование уровня моря, что подтверждает ранее сделанное предположение. Путем расчета разности фаз шельфовых волн на расстоянии 12.4 км между Невельском и Горнозаводском, наблюдаемых и определенных по теоретической модели, установлено, что вторая мода шельфовой волны с частотой 0.152 цикл/ч близка к теоретической. Регистрируемая в Ильинском и Горнозаводске волна с периодом 26.1 ч при расстоянии между пунктами 173.6 км не может быть шельфовой, а является волной Кельвина. Это подтверждено рассчитанной дисперсионной диаграммой, согласно которой длина волны около 689 км хорошо соответствует разности фаз для расстояния Ильинский–Горнозаводск. Установлено, что шельфовые волны, одним из механизмов генерации которых является напряжение ветра вдоль берега, имеют разные амплитуды в летнее и зимнее время, что обусловлено сезонным направлением вдольберегового ветра. В летний период направления распространения шельфовых волн и ветра противоположны, что ослабляет шельфовые волны.
Stuart D. C. Walsh, Laura Easton, Changlong Wang
et al.
Australia has ambitions to become a major global hydrogen producer by 2030. The establishment of Australia’s and the world’s hydrogen economy, however, will depend upon the availability of affordable and reliable hydrogen storage. Geological hydrogen storage is a practical solution for large scale storage requirements ensuring hydrogen supply can always meet demand, and excess renewable electricity can be stored for later use, improving electricity network reliability. Hosting thick, underground halite (salt) deposits and an abundance of onshore depleted gas fields, Australia is well placed to take advantage of geological hydrogen storage options to support its ambition of building a global hydrogen hub export industry. Using the Bluecap modelling software, we identify regions in Australia that are potentially profitable for large scale hydrogen production and storage. We use the results of this work to suggest high-potential regions for hydrogen development, supporting policymaker and investor decisions on the locations of new infrastructure and hydrogen projects in Australia.
Accurate measurements and predictions of near-surface soil drying and evaporation following heavy rainfall events are often needed for research in agriculture and hydrology. However, such measurements and predictions at mine waste pile and tailing settings are limited. The prediction of evaporation at mine waste piles is essential for many problems in geotechnical engineering, including the design of soil cover systems for the long-term closure of hazardous waste sites, and thus mitigates, for example, the generation of acid mine drainage (AMD) and metal leaching. AMD is one of mining’s most serious threats to the environment. This study investigated the short-term (8 days) and medium-term (27 days) drying rates and evaporative fluxes at the surface and near-surface of the Deilmann South waste-rock (DSWR) pile at the Key Lake uranium mine, northern Saskatchewan, using the gravimetric (GV) method and SoilCover (SC) model, respectively, during and following heavy rainfall events for the environment. The SC simulation results showed that during the weather-controlled stage (Stage I) of the first 5-day period of rainfall events, while the surface was wet, the potential evaporation (PE) was equal to the actual evaporation (AE) (i.e., AE/PE = 1). As the surface became drier on Day 6, the cumulative PE began to separate from the cumulative AE and the surface’s drying rate rapidly diverged from those at the deeper depths. This occurrence signaled the onset of the soil profile property-controlled stage (Stage II). As the drying continued, the surface became desiccated and the slow-rate drying stage (Stage III) was established from Day 7 onward. The SC-simulated AE results were compared to those measured using the eddy covariance (EC) method for the same test period at the DSWR pile in a different study. The comparison showed that the two methods yielded similar AE results, with 18% relative errors. The results of this study provided the opportunity to validate the SC model using actual data gathered under field conditions and to ascertain its ability to accurately predict the PE and AE at the surfaces of mine waste piles.