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It is difficult for remolded loess to reproduce the infiltration law of water in natural loess, resulting in inaccurate parameters of the Van-Genuchten model (VG model) obtained by inversion, which subsequently affects the changes in the moisture field during slope stability numerical simulations. To address this gap, a large-scale undisturbed loess soil column with a diameter of 60 cm and a height of 100 cm was artificially excavated for a water infiltration test under ponding conditions. Based on the test results, the VG model parameters were inverted by the Hydrus-1D software. The simulation accuracy was evaluated using the root mean square error (RMSE) and the Nash-Sutcliffe efficiency coefficient (NSE). Based on the inverted VG model parameters, the single-factor perturbation method was employed to calculate different VG model parameters under a disturbance amplitude of ± 20%. The numerical simulations were carried out to investigate the wetting front arrival times at different depths under varying disturbance parameters. Finally, the sensitivity of soil water characteristic parameters was analyzed. The results indicated that the measured water contents in the column closely matched the simulated values, with minimal errors, as evidenced by the RMSE ranging from 0.010 to 0.019. Except for the NSE values at 10 cm and 20 cm depths, which were below 0.900, all other depths exhibited NSE values greater than 0.900, indicating satisfactory simulation performance. The influence of soil water characteristic parameters on simulation results was θs > ks > n > α > θr. The disturbances in θs and α were negatively correlated, while disturbances in ks, n, and θr were positively correlated. Parameter disturbances less influenced the infiltration laws of water in shallow soils. However, as soil column depth increased, sensitivity to parameter changes gradually increased, leading to a greater impact on simulation results. The research findings provide technical support for evaluating and preventing water-induced landslide hazards.

Mangroves buffer inland ecosystems from hurricane winds and storm surge. However, their ability to withstand harsh cyclone conditions depends on plant resilience traits and geomorphology. Using airborne lidar and satellite imagery collected before and after Hurricane Irma, we estimated that 62% of mangroves in southwest Florida suffered canopy damage, with largest impacts in tall forests (>10 m). Mangroves on well-drained sites (83%) resprouted new leaves within one year after the storm. By contrast, in poorly-drained inland sites, we detected one of the largest mangrove diebacks on record (10,760 ha), triggered by Irma. We found evidence that the combination of low elevation (median = 9.4 cm asl), storm surge water levels (>1.4 m above the ground surface), and hydrologic isolation drove coastal forest vulnerability and were independent of tree height or wind exposure. Our results indicated that storm surge and ponding caused dieback, not wind. Tidal restoration and hydrologic management in these vulnerable, low-lying coastal areas can reduce mangrove mortality and improve resilience to future cyclones.

Quantitative results from regional climate models (RCMs) run over ice sheets are frequently used to make projections of surface melt, ice-shelf stability, and subsequently sea-level rise. However, modelled relevant mass fluxes need to be evaluated first before using future output data for projections. This study makes the case for a two-step framework when evaluating RCMs. Firstly, the reliability of the RCM when forced with reanalysis data must be assessed through comparison with historical observations. Secondly, the accuracy of using a non-observationally constrained Earth System Model as forcing must be assessed through comparison with the reanalysis forced run during the same historical period. Simulating surface melt in Antarctica with the RCM RACMO2.3p2 is given as an example. Applying this two-step procedure we show that RACMO2.3p2 respectively forced with ERA5 and CESM2 is robust for modelling contemporary and future surface melt in Antarctica. Building on this conclusion, we briefly discuss an application, i.e. three future SSP realizations of melt-over-accumulation across the Antarctic ice sheet until 2100 are presented, providing insights into the future sensitivity to meltwater ponding of major Antarctic ice shelves.

European rivers are disconnected by more than one million man-made barriers that physically limit aquatic species migration and contribute to modification of freshwater habitats. Here, a Conceptual Habitat Alteration Model for Ponding is developed to aid in evaluating the effects of impoundments on fish habitats. Fish communities present in rivers with low human impact and their broad environmental settings enable classification of European rivers into 15 macrohabitat types. These classifications, together with the estimated fish sensitivity to alteration of their habitat are used for assessing the impacts of six main barrier types (dams, weirs, sluices, culverts, fords, and ramps). Our results indicate that over 200,000 km or 10% of previously free-flowing river habitat has been altered due to impoundments. Although they appear less frequently, dams, weirs and sluices cause much more habitat alteration than the other types. Their impact is regionally diverse, which is a function of barrier height, type and density, as well as biogeographical location. This work allows us to foresee what potential environmental gain or loss can be expected with planned barrier management actions in rivers, and to prioritize management actions. European rivers have over a million barriers hindering aquatic species migration and altering freshwater habitats. This study quantifies the spatial extent of upstream fish habitat alteration caused by physical blockage and shows that impoundments have altered 10% or 200,000 km of free-flowing river habitat in Europe.

Hot plumes rising from Earth's deep mantle are thought to cause uplift, rifting and large igneous province (LIP) emplacement. LIP volcanism in continents often spans tens of Ma and scatters unevenly over broad areas. This has been attributed to lateral flow of hot plume material, but observational evidence on such flow is scarce. New waveform tomography with massive data sets reveals detailed seismic velocity structure beneath the East Africa‐Arabia region, where these processes occur at present. It shows interconnected sub‐lithospheric corridors of hot, partially molten rock, fed by three mantle upwellings beneath Kenya, Afar, and Levant. The spatio‐temporal distribution of the volcanism suggests that we are witnessing an integral plume head, which morphed into a three‐pointed star by ponding and channeling within thin‐lithosphere corridors. Plate reconstructions indicate that it spread south‐to‐north since ∼45 Ma. These results suggest that complex‐shape plume heads can explain the enigmatic, scattered LIP volcanism and are, probably, an inherent feature of plume‐continent interaction. Key Points New seismic waveform tomography images a continuous low‐velocity anomaly beneath East Africa‐Arabia interpreted as an extant plume head The body of partially molten rock is shaped as a 3‐pointed star by the lithosphere‐asthenosphere boundary and underlies all the intraplate volcanic areas Complex star‐shaped plume heads spreading via thin‐lithosphere valleys can explain the dispersed, protracted volcanism in many ancient large igneous provinces

Timely and accurately estimating ponding levels during urban floods is the basis of effective disaster prevention and mitigation. Road surveillance videos record the urban flood process as images, and computer vision technology brings new opportunities for extracting ponding information from image data. This study proposes a computer vision-based method for estimating the spatial-temporal distribution of urban street ponding levels from surveillance videos. First, a dataset of sedan images compiled from three sources was collected to train an object detection algorithm, You Only Look Once vision 3 (YOLOv3). Then, the trained model was adopted to identify the ponding levels whenever and wherever sedans were detected from the videos. Second, outlier detection was employed to detect and delete the outliers of ponding levels in each time step. Finally, the ponding level distribution was estimated by inverse distance weighted from the remaining ponding level points. This method was employed for two pluvial flood events at a street crossing, Dongguan Street, in Dalian, China. The mean average precision (mAP) of the trained YOLOv3 model reached 78%, which confirmed the validity of the model. The ponding levels estimated by our method were validated with the submerged depth of a static reference, and the ponding process had a strong correlation with the rainfall time series. Outlier detection improved the accuracy of ponding level estimation in cross-validation to 88% on average. The results can be used to analyze the progress of urban flood evolution, which contributes to arranging drainage facilities and improving urban flood management.

Ice flow models of the Antarctic ice sheet are commonly used to simulate its future evolution in response to different climate scenarios and assess the mass loss that would contribute to future sea level rise. However, there is currently no consensus on estimates of the future mass balance of the ice sheet, primarily because of differences in the representation of physical processes, forcings employed and initial states of ice sheet models. This study presents results from ice flow model simulations from 13 international groups focusing on the evolution of the Antarctic ice sheet during the period 2015–2100 as part of the Ice Sheet Model Intercomparison for CMIP6 (ISMIP6). They are forced with outputs from a subset of models from the Coupled Model Intercomparison Project Phase 5 (CMIP5), representative of the spread in climate model results. Simulations of the Antarctic ice sheet contribution to sea level rise in response to increased warming during this period varies between -7:8 and 30.0 cm of sea level equivalent (SLE) under Representative Concentration Pathway (RCP) 8.5 scenario forcing. These numbers are relative to a control experiment with constant climate conditions and should therefore be added to the mass loss contribution under climate conditions similar to present-day conditions over the same period. The simulated evolution of the West Antarctic ice sheet varies widely among models, with an overall mass loss, up to 18.0 cm SLE, in response to changes in oceanic conditions. East Antarctica ass change varies between -6.1 and 8.3 cm SLE in the simulations, with a significant increase in surface mass balance outweighing the increased ice discharge under most RCP 8.5 scenario forcings. The inclusion of ice shelf collapse, here assumed to be caused by large amounts of liquid water ponding at the surface of ice shelves, yields an additional simulated mass loss of 28mm compared to simulations without ice shelf collapse. The largest sources of uncertainty come from the climate forcing, the ocean-induced melt rates, the calibration of these melt rates based on oceanic conditions taken outside of ice shelf cavities and the ice sheet dynamic response to these oceanic changes. Results under RCP 2.6 scenario based on two CMIP5 climate models show an additional mass loss of 0 and 3 cm of SLE on average compared to simulations done under present-day conditions for the two CMIP5 forcings used and display limited mass gain in East Antarctica.

Spatial surface patterns of hummocks, hollows, ridges, and pools (microtopography) are common features of many northern peatlands and are particularly distinct within the vast peatlands of the Hudson Bay Lowland (HBL), Canada. Hypotheses and models describe how small-scale feedbacks among vegetation, hydrology, and nutrients cause spatial differences in peat accumulation that enable microforms and surface patterns to develop over time. Empirical tests of the predictions from theoretical models of these proposed feedback mechanisms are limited, particularly in large peatland complexes such as the HBL. We investigate feedbacks controlling peatland structure and function in an ombrogenous bog and a minerogenous fen in the HBL. Our sites represent surface patterns found in many northern peatlands, specifically spatially irregular hummocks and hollows, and parallel ridges and pools that are perpendicular to slope. We found the occurrence of different spatial patterns depends on position within a peat landform, with these differences attributed to the ecohydrological setting. In turn, the ecohydrological setting, with different water table depths, nutrient availability, and species composition, influences the strength and direction of feedback mechanisms at the microform scale. Our data support the prediction of a positive feedback between plant productivity and acrotelm thickness for peat accumulation and hummock growth and that this may be enhanced by water ponding on slopes to form ridge–pool tracks. We did not find evidence to support the proposed feedback among evapotranspiration-driven transport of water and nutrients for the development of hummocks. Our results suggest a combination of mechanisms operating at various temporal and spatial scales is associated with the development of surface patterns in northern peatlands.

Antarctic ice sheet (AIS) mass loss is predominantly driven by increased solid ice discharge, but its variability is governed by surface processes. Snowfall fluctuations control the surface mass balance (SMB) of the grounded AIS, while meltwater ponding can trigger ice shelf collapse potentially accelerating discharge. Surface processes are essential to quantify AIS mass change, but remain poorly represented in climate models typically running at 25-100 km resolution. Here we present SMB and surface melt products statistically downscaled to 2 km resolution for the contemporary climate (1979-2021) and low, moderate and high-end warming scenarios until 2100. We show that statistical downscaling modestly enhances contemporary SMB (3%), which is sufficient to reconcile modelled and satellite mass change. Furthermore, melt strongly increases (46%), notably near the grounding line, in better agreement with in-situ and satellite records. The melt increase persists by 2100 in all warming scenarios, revealing higher surface melt rates than previously estimated. High-resolution 2-km Antarctic maps reveal higher snowfall and surface melt than low-resolution products, reconciling satellite-observed ice sheet mass change. Projected higher surface melt near grounding lines threatens future ice shelf stability.

Accurate prediction of urban floods is regarded as one of the critical means to prevent urban floods and reduce the losses caused by floods. In this study, a refined prediction and early warning method system for urban flood and waterlogging processes based on deep learning methods is proposed. The spatial autocorrelation of rain and ponding points is analyzed by Moran's I (a common used statistic for spatial autocorrelation). For each ponding point, the relationship model between the rainfall process and ponding process is constructed based on different deep learning methods, and the results are analyzed and verified by mean absolute error (MAE), root mean square error (RMSE), Nash efficiency coefficient (NSE) and correlation coefficient (CC). The results show that the gradient boosting decision tree algorithm has the highest accuracy and efficiency (with a 0.001 m RMSE of the predicted and measured ponding depth) for ponding process prediction and is regarded as the most suitable method for ponding process prediction. Finally, the real‐time prediction and early warning of urban floods and waterlogging processes driven by rainfall forecast data are realized, and the results are verified by the measured data. The research results can provide theoretical support for urban flood prevention and control.