Assessment of the impact of different vegetation patterns on soil erosion processes on semiarid loess slopes

Soil erosion hinders the recovery and development of ecosystems in semiarid regions. Rainstorms, coupled with the absence of vegetation and improper land management, are important causes of soil erosion in such areas. Greater effort should be made to quantify the initial erosion processes and try to find better solutions for soil and water conservation. In this research, 54 rainfall simulations were performed to assess the impacts of vegetation patterns on soil erosion in a semiarid area of the Loess Plateau, China. Three rainfall intensities (15 mm h^‐1, 30 mm h^‐1 and 60 mm h^‐1) and six vegetation patterns (arbors‐shrubs‐grass ‐A‐S‐G‐, arbors‐grass‐shrubs ‐A‐G‐S‐, shrubs‐arbors‐grass ‐S‐A‐G‐, shrubs‐grass‐arbors ‐S‐G‐A‐, grass‐shrubs‐arbors ‐G‐S‐A‐ and grass‐arbors‐shrubs ‐G‐A‐S‐) were examined at different slope positions (summits, backslopes and footslopes) in the plots (33.3%, 33.3%, 33.3%), respectively. Results showed that the response of soil erosion to rainfall intensity differed under different vegetation patterns. On average, increasing rainfall intensity by 2 to 4 times induced increases of 3.1 to 12.5 times in total runoff and 6.9 to 46.4 times in total sediment yield, respectively. Moreover, if total biomass was held constant across the slope, the patterns of A‐G‐S and A‐S‐G (planting arbor at the summit position) had the highest runoff (18.34 L m^‐2 h^‐1) and soil losses (197.98 g m^‐2 h^‐1), while S‐A‐G had the lowest runoff (5.51 L m^‐2 h^‐1) and soil loss (21.77 g m^‐2 h^‐1). As indicated by redundancy analysis (RDA) and Pearson correlation results, a greater volume of vegetation located on the back‐ and footslopes acted as effective buffers to prevent runoff generation and sediment yield. Our findings indicated that adjusting vegetation position along slopes can be a crucial tool to control water erosion and benefit ecosystem restoration on the Loess Plateau and other similar regions of the world. Copyright © 2018 John Wiley & Sons, Ltd.     

The application of GPR and ERI in combination with exposure logging and retrodeformation analysis to characterize sinkholes and reconstruct their impact on fluvial sedimentation

This work illustrates the practicality of investigating sinkholes integrating data gathered by ground penetrating radar (GPR), electrical resistivity imaging (ERI) and trenching or direct logging of the subsidence‐affected sediments in combination with retrodeformation analysis. This mutidisciplinary approach has been tested in a large paleosinkhole developed during the deposition of a Quaternary terrace on salt‐bearing evaporites. The subsidence structure, exposed in an artificial excavation, is located next to Puilatos, a village that was abandoned in the 1970s due to severe subsidence damage. Detailed logging of the exposure revealed that the subsidence structure corresponds to an asymmetric sagging and collapse paleosinkhole with no clear evidence of recent activity. The sedimentological and structural relationships together with the retrodeformation analysis indicate that synsedimentary subsidence controlled channel location, the development of a palustrine environment and local changes in the channel pattern. GPR profiles were acquired using an array of systems with different antenna frequencies, including some recently developed shielded antennas with improved vertical resolution and penetration depth. Although radargrams imaged the faulted sagging structure and provided valuable data on fault throw, they did not satisfactorily image the complex architecture of the fluvial deposit. ERI showed lower resolution but higher penetration depth when compared to GPR, roughly capturing the subsidence structure and yielding information on the thickness of the high‐resistivity alluvium and the nature of the underlying low‐resistivity karstic residue developed on top of the halite‐bearing evaporitic bedrock. Data comparison allows the assessment of the advantages and limitations of these complementary techniques, highly useful for site‐specific sinkhole risk management. Copyright © 2016 John Wiley & Sons, Ltd.     

Beach recovery capabilities after El Niño 2015–2016 at Ensenada Beach,Northern Baja California

This study investigates the recovery capabilities of a single-barred beach in the Pacific Mexican coast before and after the 2015–2016 El Niño winter. Concurrent hydrodynamic and morphological data collected over a 3-year period (August 2014–2017) were analysed to determine the subaerial-subtidal volumetric exchange and cross-shore subtidal sandbar migrations, in relation to the incident wave forcing. The beach presented a seasonal seaward and landward sandbar migration cycle. The sandbar migrated offshore during the energetic waves between November and February, and onshore during the milder wave period in spring, until welding to the subaerial beach around May. The transfer of sediment towards the subaerial section continued over the summer, reaching a complete recovery by September/October. Prior to El Niño, the subaerial beach successfully recovered by the end of summer 2015 through the landward sandbar migration process. The 2015–2016 energetic winter waves caused a subaerial volume loss of ~ 140 m³ m^?1 (from October 2015 to March 2016), more than twice the amount eroded in the other winters, and the sandbar moved further offshore and to deeper depths (3–4 m) than the winter before. In addition, the energetic 2015–2016 winter waves lasted for 2 months longer than in other years, making the 2016 spring shorter. Consequently, during the onshore migration, the sandbar was unable of reaching shallow depths, and a large portion of sand remained in the subtidal beach. The subaerial beach recovered 60 and 65% of the loss in the 2016 and 2017 summers, respectively. It is concluded that the landward migration process of the sandbar during the spring is critical to ensure a full subaerial beach recovery over the mild wave period in summer. The recovery capabilities of the subaerial beach will depend on the cross-shore distance and depth where the sandbar is located, and on the duration of mild wave conditions required for the sandbar to migrate onshore.     

Random forests as a tool to understand the snow depth distribution and its evolution in mountain areas

The small scale distribution of the snowpack in mountain areas is highly heterogeneous, and is mainly controlled by the interactions between the atmosphere and local topography. However, the influence of different terrain features in controlling variations in the snow distribution depends on the characteristics of the study area. As this leads to uncertainties in high spatial resolution snowpack simulations, a deeper understanding of the role of terrain features on the small scale distribution of snow depth is required. This study applied random forest algorithms to investigate the temporal evolution of snow depth in complex alpine terrain using as predictors various topographical variables and in situ snow depth observations at a single location. The high spatial resolution (1 m x 1 m) snow depth distribution database used in training and evaluating the random forests was derived from terrestrial laser scanner (TLS) devices at three study sites, in the French Alps (2 sites) and the Spanish Pyrenees (1 site). The results show the major importance of two topographic variables, the topographic position index and the maximum upwind slope parameter. For these variables the search distances and directions depended on the characteristics of each site and the TLS acquisition date, but are consistent across sites and are tightly related to main wind directions. The weight of the different topographic variables on explaining snow distribution evolves while major snow accumulation events still take place and minor changes are observed after reaching the annual snow accumulation peak. Random forests have demonstrated good performance when predicting snow distribution for the sites included in the training set with R² values ranging from 0.82 to 0.94 and mean absolute errors always below 0.4 m. Oppositely, this algorithm failed when used to predict snow distribution for sites not included in the training set, with mean absolute errors above 0.8 m.     

Supernova remnants, planetary nebulae and the distance to NGC 4214

We present narrow band, continuum subtracted Hα, [S ii], Hβ, [O iii] and [O ii] data taken with the Wide Field Camera 3 on the Hubble Space Telescope in the nearby dwarf starburst galaxy NGC 4214. From these images, we identify seventeen new planetary nebula candidates, and seven supernova remnant candidates. We use the observed emission line luminosity function of the planetary nebulae to establish a new velocity-independent distance to NGC 4214. We conclude that the PNLF technique gives a reddening independent distance to NGC 4214 of 3.19±0.36 Mpc, and that our current best-estimate of the distance to this galaxy ids 2.98±0.13 Mpc.     

Estimation of potential pollution from mine tailings in the San Pedro River (1993–2005), Mexico–US border

The San Pedro River (SPR) is located in northern Sonora (Mexico) and southeastern Arizona (USA). SPR is a transboundary river that develops along the Sonora (Mexico) and Arizona (USA) border, and is considered the main source of water for a variety of users (human settlements, agriculture, livestock, and industry). The SPR originates in the historic Cananea mining area, which hosts some of the most important copper mineralizations in Mexico. Acid mine drainage derived from mine tailings is currently reaching a tributary of the SPR near Cananea City, resulting in the contamination of the SPR with heavy metals and sulfates in water and sediments. This study documents the accumulation and distribution of heavy metals in surface water along a segment of the SPR from 1993 to 2005. Total concentrations of Cd, Cu, Fe, Mn, Pb, and Zn in surface waters are above maximum permissible levels in sampling sites near mine tailing deposits. Nevertheless, a significant decrease in the Fe and SO₄ ²⁻ in surface water (SO₄ ²⁻: 7,180–460.39 mg/L; Fe: 1,600–9.51 mg/L) as well as a gradual decrease in the heavy and transition metal content were observed during the period from 1994 to 2005. Approximately 2.3 km downstream of the mine tailings, the heavy metal content of the water drops quickly following an increase in pH values due to the discharging of wastewater into the river. The attenuation of the heavy metal content in surface waters is related to stream sediment precipitation (accompanied by metal coprecipitation and sorption) and water dilution. Determining the heavy metal concentration led to the conclusion that the Cananea mining area and the San Pedro River are ecosystems that are impacted by the mining industry and by untreated wastewater discharges arising from the city of Cananea (Sonora, Mexico).     

Backward snow depth reconstruction at high spatial resolution based on time‐lapse photography

We report a methodology for reconstructing the daily snow depth distribution at high spatial resolution in a small Pyrenean catchment using time‐lapse photographs and snow depletion rates derived from an on‐site measuring meteorological station. The results were compared with the observed snow depth distribution, determined on a number of separate occasions using a terrestrial laser scanner (TLS). The time‐lapse photographs were projected onto a digital elevation model of the study site, and converted into snow presence/absence information. The melt‐out date (MOD; first occurrence of melt out after peak snow accumulation) was obtained from the projected photograph series. Commencing the backward reconstruction for each grid cell at the MOD, the method uses simulated snow depth depletion rates using a temperature index approach, which are extrapolated to the grid cells of the domain to arrive at the snow distribution of the previous day. Two variants of the reconstruction techniques were applied (1) using a spatially constant degree day factor (DDF) for calculating the daily expected snow depth depletion rate, and (2) allowing a spatially distributed DDF calculated from two consecutive TLS acquisitions compared to the snow depth depletion rate observed at the meteorological station. Validation revealed that both methods performed well (average R² = 0.68; standard RMSE = 0.58), with better results obtained from the spatially distributed approach. Nevertheless, the spatially corrected DDF reconstruction, which requires TLS data, suggests that the constant DDF approach is an efficient, and for most applications sufficiently accurate and easily reproducible method. The results highlight the usefulness of time‐lapse photography for not only determining the snow covered area, but also for estimating the spatial distribution of snow depth. Copyright © 2016 John Wiley & Sons, Ltd.     

Shallow frontal deformation related to active continental subduction: structure and recent stresses in the westernmost Betic Cordillera

The westernmost Betic Cordillera front is located along the arcuate alpine belt formed by the interaction of the Eurasian‐African plate boundary and the Alboran continental domain in between. Although classical geological data suggest that the western Cordillera front is inactive, recent GPS data show a westward–north‐westward motion of up to 3.4 mm a^?1 with respect to the foreland. In addition, the increasing thickness of Guadalquivir sedimentary infill towards the Cordillera, and the rectilinear character of the front formed by soft sediments, suggest that the Cordillera is still active. Large ENE–WSW‐oriented open folds detected in the field, seismic reflection profiles and new audiomagnetotellurics data are consistent with active deformation. Fracture analysis in Quaternary deposits evidences recent NW–SE horizontal compression. The GPS motion and maximum stress orientation may be due to north‐westward tectonic collision of the westernmost Betic Cordillera, accommodated at depth by active continental subduction of the Iberian lithosphere.