Recharge to mountainous carbonated aquifers in SE Spain: Different approaches and new challenges

As in most semiarid regions, the main source of freshwater in SE Spain is its aquifers, and their exploitation has enabled the development of highly profitable irrigated agriculture and tourism industries. The application of sustainable water management plans requires aquifer recharge to be quantified and its spatial pattern evaluated. This paper gives a comprehensive review of various recharge studies in mountainous carbonated aquifers, the most important groundwater reservoirs in SE Spain. Quantification of potential recharge rates and their spatial variability are illustrated using satellite-based modeling and tracer techniques. Actual recharge figures from the application of a lumped model based on water table fluctuations are also presented. Potential recharge relative to actual recharge is around 1 in small aquifers and flat areas and may increase up to 1.3 in heterogeneous mountainous aquifers with deep water levels due to losses of recharge in transit in the vadose zone. The complex interaction between climate, geology, aquifer geometry, topography, soil properties and the degree of karstification prevents the systematization of any particular technique to quantify potential recharge. The use of water table fluctuation methods for actual recharge evaluation requires daily time steps to compute unnoticed small recharge events. Therefore, the monitoring of environmental variables and the use of complementary techniques for comparison are recommended. Despite their importance for the correct assessment of recharge in the region, uncertainty analyses are still scarce, and the natural variability of recharge is unknown in most cases. Effort is required to improve the spatial and temporal characterization of recharge through the integration of interdisciplinary sciences.     

Landslides triggered by the 22 July 2013 Minxian–Zhangxian,China, Mw 5.9 earthquake: Inventory compiling and spatial distribution analysis

On July 22, 2013, an earthquake of Ms. 6.6 occurred at the junction area of Minxian and Zhangxian counties, Gansu Province, China. This earthquake triggered many landslides of various types, dominated by small-scale soil falls, slides, and topples on loess scarps. There were also a few deep-seated landslides, large-scale soil avalanches, and fissure-developing slopes. In this paper, an inventory of landslides triggered by this event is prepared based on field investigations and visual interpretation of high-resolution satellite images. The spatial distribution of the landslides is then analyzed. The inventory indicates that at least 2330 landslides were triggered by the earthquake. A correlation statistics of the landslides with topographic, geologic, and earthquake factors is performed based on the GIS platform. The results show that the largest number of landslides and the highest landslide density are at 2400 m–2600 m of absolute elevation, and 200 m–300 m of relative elevation, respectively. The landslide density does not always increase with slope gradient as previously suggested. The slopes most prone to landslides are in S, SW, W, and NW directions. Concave slopes register higher landslide density and larger number of landslides than convex slopes. The largest number of landslides occurs on topographic position with middle slopes, whereas the highest landslide density corresponds to valleys and lower slopes. The underlying bedrocks consisting of conglomerate and sandstone of Lower Paleogene (E^b) register both the largest number and area of landslides and the highest landslide number and area density values. Correlations of landslide number and landslide density with perpendicular- and along-strike distance from the epicenter show an obvious spatial intensifying character of the co-seismic landslides. The spatial pattern of the co-seismic landslides is strongly controlled by a branch of the Lintan-Dangchang fault, which indicates the effect of seismogenic fault on co-seismic landslides. In addition, the area affected by landslides related to the earthquake is compared to the relationship of “area affected by landslides vs. earthquake magnitude” constructed based on earthquakes worldwide, and it is shown that the area affected by landslides triggered by the Minxian–Zhangxian earthquake is larger than that of almost all other events with similar magnitudes.     

地面滑坡信息图谱的浅析

地学信息图谱作为地学问题的一种研究思路和方法论 ,有助于深化地学现象和过程滑坡研究。从地球信息科学和滑坡学理解的滑坡信息图谱形式上有一定的差别 ,其研究内容也有一些异同。本文从地球信息科学的角度详细阐述了滑坡信息图谱方法的内容及具体应用 ,文中将滑坡信息图谱分解为滑坡征兆、诊断与实施图谱 ,用于辅助解决滑坡研究不同阶段和层次的方法论问题 ,其主要目的是提出并寻找 GIS对滑坡研究应用的途径和方法体系。     

Ages of Valles Marineris (Mars) landslides and implications for canyon history

The chronology of landslides of Valles Marineris, the equatorial trough system of Mars, has been investigated by a crater population study. Valles Marineris landslides have widespread debris aprons which offer a remarkable opportunity to study the crater population with high resolution images from Mars Orbiter Camera (MOC) and from Mars Odyssey Thermal Emission Imaging System (THEMIS). Sixty-six ages were determined within Valles Marineris including 56 landslide ages and 10 ages of the canyon floor. Results reveal that landslides of Valles Marineris system of canyons occurred during a widespread period of time between 3.5 Gy and 50 My. In some locations, the canyon floor has an apparent age of 3.5 Gy suggesting that at least locally within Valles Marineris no major refreshing processes have occurred for 3.5 Gy. The temporal repetitivity of landslides implies that the triggering mechanisms of the landslides are reproducible in time. Landslides have the same features whatever their age. The dynamic of these landslides is probably the same either with intervention of water up to recently (the last 100 My) or without water since 3.5 Gy.     

Population amount risk assessment of extreme precipitation-induced landslides based on integrated machine learning model and scenario simulation

In this study, the future landslide population amount risk (LPAR) is assessed based on integrated machine learning models (MLMs) and scenario simulation techniques in Shuicheng County, China. Firstly, multiple MLMs were selected and hyperparameters were optimized, and the generated 11 models were cross-integrated to select the best model to calculate landslide susceptibility; by calculating precipitation for different extreme precipitation recurrence periods and combining the susceptibility results to assess the landslide hazard. Using the town as the basic unit, the exposure and vulnerability of the future landslide population under different Shared Socioeconomic Pathways (SSPs) scenarios in each town were assessed, and then combined with the hazard to estimate the LPAR in 2050. The results showed that the integrated model with the optimized random forest model as the combination strategy had the best comprehensive performance in susceptibility assessment. The distribution of hazard classes is similar to susceptibility, and with an increase in precipitation, the low-hazard area and high-hazard decrease and shift to medium-hazard and very high-hazard classes. The high-risk areas for future landslide populations in Shuicheng County are mainly concentrated in the three southwestern towns with high vulnerability, whereas the northern towns of Baohua and Qinglin are at the lowest risk class. The LPAR increased with the intensity of extreme precipitation. The LPAR differs significantly among the SSPs scenarios, with the lowest in the “fossil-fueled development (SSP5)” scenario and the highest in the “regional rivalry (SSP3)” scenario. In summary, the landslide susceptibility model based on integrated machine learning proposed in this study has a high predictive capability. The results of future LPAR assessment can provide theoretical guidance for relevant departments to cope with future socioeconomic development challenges and make corresponding disaster prevention and mitigation plans to prevent landslide risks from a developmental perspective.     

Diversification of landslide areas as a means for reducing noise in dendrogeomorphic dating

The result of tree-ring-based reconstruction of past landslide events is often the development of a single total chronology. This approach can be very effective for small homogeneous landslides. However, compiling chronological data from heterogeneous (often independent) zones of large complex landslide areas into one chronology can induce over- or underestimation of some events, resulting in lowered reliability of the reconstruction. The solution for elimination of this effect can lie in the diversification of complex landslide areas into homogeneous zones with separate analyses. The aim of this study was to quantify the effect of this separation on detected slope movement events and to define parameters whose investigation could distinguish events (sliding) from noise (creeping).For this purpose, 412 tree-ring series from 206 disturbed common spruce (Picea abies (L.) Karst.) occupying complex landslide areas were dendrogeomorphically analysed. The landslide area was divided into five homogeneous zones using geomorphic mapping, LiDAR-based DEM and geophysical sounding (ERT). Five events (verified in individual zones) were detected in the total chronology. Two extra events in the total chronology (28.6%) were considered noise. Moreover, two zonal events were detected but not recorded in the total chronology. This indicates that the noise in the total chronology of the complex landslide area could reach more than a quarter of dated events. Next, true slide events and noise (caused by creep) were differentiated in the structure of growth disturbances (reaction wood vs. abrupt growth suppression) and their proportion in event reconstruction, spatial patterns of trees containing slope movement signals, and the character of triggers. Thus, for better filtering of noise from signals in tree-ring-based chronologies of landslides, not only observations of dendrogeomorphic index values but also the morphology of landslides and characteristics of dated processes must be considered.     

Uncertainty pattern in landslide susceptibility prediction modelling: Effects of different landslide boundaries and spatial shape expressions

In some studies on landslide susceptibility mapping (LSM), landslide boundary and spatial shape characteristics have been expressed in the form of points or circles in the landslide inventory instead of the accurate polygon form. Different expressions of landslide boundaries and spatial shapes may lead to substantial differences in the distribution of predicted landslide susceptibility indexes (LSIs); moreover, the presence of irregular landslide boundaries and spatial shapes introduces uncertainties into the LSM. To address this issue by accurately drawing polygonal boundaries based on LSM, the uncertainty patterns of LSM modelling under two different landslide boundaries and spatial shapes, such as landslide points and circles, are compared. Within the research area of Ruijin City in China, a total of 370 landslides with accurate boundary information are obtained, and 10 environmental factors, such as slope and lithology, are selected. Then, correlation analyses between the landslide boundary shapes and selected environmental factors are performed via the frequency ratio (FR) method. Next, a support vector machine (SVM) and random forest (RF) based on landslide points, circles and accurate landslide polygons are constructed as point-, circle- and polygon-based SVM and RF models, respectively, to address LSM. Finally, the prediction capabilities of the above models are compared by computing their statistical accuracy using receiver operating characteristic analysis, and the uncertainties of the predicted LSIs under the above models are discussed. The results show that using polygonal surfaces with a higher reliability and accuracy to express the landslide boundary and spatial shape can provide a markedly improved LSM accuracy, compared to those based on the points and circles. Moreover, a higher degree of uncertainty of LSM modelling is present in the expression of points because there are too few grid units acting as model input variables. Additionally, the expression of the landslide boundary as circles introduces errors in measurement and is not as accurate as the polygonal boundary in most LSM modelling cases. In addition, the results under different conditions show that the polygon-based models have a higher LSM accuracy, with lower mean values and larger standard deviations compared with the point- and circle-based models. Finally, the overall LSM accuracy of the RF is superior to that of the SVM, and similar patterns of landslide boundary and spatial shape affecting the LSM modelling are reflected in the SVM and RF models.     

Wave–current interaction in a river and wave dominant estuary: A seasonal contrast

The dynamic feature of the Modaomen Estuary (ME) in the Pearl River Delta in southern China has been the subject of extensive research. In previous studies, wave–current interaction (WCI) was often neglected due to its complexity. This study uses a coupled hydrodynamic module TELEMAC-2D and wave propagation module TOMAWAC in the TELEMAC-Mascaret modeling system to quantify the effects of WCI on the hydrodynamics in the ME. The coupled wave and current modeling system was well validated against the field measurements at selected locations. The model results show that WCI varies with the seasonal change in runoff in the ME. The effect of waves on the currents is insignificant during the wet season with a current change of no more than 0.07 m/s; but, in contrast, the currents have a noticeable effect on waves. However, during the dry season, the interactions of waves and currents on each other are found to be equally significant. When wave model and current model are coupled, the velocity could increase up to a maximum of 0.30 m/s and decrease up to a maximum of 0.17 m/s. WCI is greatly affected by the propagation directions of wave and current in both seasons. Generally, wave height decreases and current increases for a following wave and current; wave height increases and current decreases for an opposing wave and current. The effects of waves on currents change with the tide. Changes are larger during neap tide than during spring tide, and stronger during ebb tide than during flood tide.     

A GPU parallel computing strategy for the material point method

The material point method (MPM), which is a combination of the finite element and meshfree methods, suffers from significant computational workload due to the fine mesh that is required in spite of its advantages in simulating large deformations. This paper presents a parallel computing strategy for the MPM on the graphics processing unit (GPU) to boost the method’s computational efficiency. The interaction between a structural element and soil is investigated to validate the applicability of the parallelisation strategy. Two techniques are developed to parallelise the interpolation from soil particles to nodes to avoid a data race; the technique that is based on workload parallelisation across threads over the nodes has a higher computational efficiency. Benchmark problems of surface footing penetration and a submarine landslide are analysed to quantify the speedup of GPU parallel computing over sequential simulations on the central processing unit. The maximum speedup with the GPU used is ∼30 for single-precision calculations and decreases to ∼20 for double-precision calculations.