Nepal's quake-driven landslide hazards Large earthquakes can trigger dangerous landslides across a wide geographic region. The 2015 M w 7.8 Gorhka earthquake near Kathmandu, Nepal, was no exception. Kargal et al. used remote observations to compile a massive catalog of triggered debris flows. The satellite-based observations came from a rapid response team assisting the disaster relief effort. Schwanghart et al. show that Kathmandu escaped the historically catastrophic landslides associated with earthquakes in 1100, 1255, and 1344 C.E. near Nepal's second largest city, Pokhara. These two studies underscore the importance of determining slope stability in mountainous, earthquake-prone regions. Science , this issue p. 10.1126/science.aac8353 ; see also p. 147

Abstract. Measurements of the isotopic composition of separate and potentially interacting pools of soil water provide a powerful means to precisely resolve plant water sources and quantify water residence time and connectivity among soil water regions during recharge events. Here we present an approach for quantifying the time-dependent isotopic mixing of water recovered at separate suction pressures or tensions in soil over an entire moisture release curve. We wetted oven-dried, homogenized sandy loam soil first with isotopically “light” water (δ2H =-130 ‰; δ18O =-17.6 ‰) to represent antecedent moisture held at high matric tension. We then brought the soil to near saturation with “heavy” water (δ2H =-44 ‰; δ18O =-7.8 ‰) that represented new input water. Soil water samples were subsequently sequentially extracted at three tensions (“low-tension” centrifugation ≈0.016 MPa; “mid-tension” centrifugation ≈1.14 MPa; and “high-tension” cryogenic vacuum distillation at an estimated tension greater than 100 MPa) after variable equilibration periods of 0 h, 8 h, 1 d, 3 d, and 7 d. We assessed the differences in the isotopic composition of extracted water over the 7 d equilibration period with a MANOVA and a model quantifying the time-dependent isotopic mixing of water towards equilibrium via self-diffusion. The simplified and homogenous soil structure and nearly saturated moisture conditions used in our experiment likely facilitated rapid isotope mixing and equilibration among antecedent and new input water. Despite this, the isotope composition of waters extracted at mid compared with high tension remained significantly different for up to 1 d, and waters extracted at low compared with high tension remained significantly different for longer than 3 d. Complete mixing (assuming no fractionation) for the pool of water extracted at high tension occurred after approximately 4.33 d. Our combination approach involving the extraction of water over different domains of the moisture release curve will be useful for assessing how soil texture and other physical and chemical properties influence isotope exchange and mixing times for studies aiming to properly characterize and interpret the isotopic composition of extracted soil and plant waters, especially under variably unsaturated conditions.

As geophysical data allow for the monitoring of hydrological processes at relatively fine spatial resolutions, these data can help identify otherwise poorly constrained hydraulic parameters within hydrologic models. For example, Binley et al. ( 2002) constrained the saturated hydraulic conductivity value of one layer in a three-layer subsurface flow model by calculating the first and second spatial moments of the change in water content from petrophysically transformed resistivity and radar data. Many studies have since extended the usefulness of geophysical data to, for example, calibrate hydrologic models of salt water intrusion (e.g.,

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The belowground architecture of the Critical Zone consists of soil and rock in various stages of weathering and wetness that acts as a medium for biological growth, mediates chemical reactions, and controls partitioning of hydrological fluxes. Hydrogeophysical imaging provides unique insights into geometries and properties of the earth materials that are present in the Critical Zone and beyond the reach of direct observation besides sparse wellbores. Improved understanding of Critical Zone architecture can be achieved by leveraging geophysical measurements of the subsurface. Creating categorical models of the Critical Zone is valuable for driving hydrological models and comparing belowground architectures between different sites to interpret weathering processes. The Critical Zone architecture is revealed through a novel comparison of hillslopes by applying facies classification in the elastic-electric domain driven by surface-based hydrogeophysical measurements. Three pairs of hillslopes grouped according to common geologic substrates – granite, volcanic extrusive, and glacially altered, are classified by five different hydro-facies classes to reveal relative wetness and weathering states. The hydro-facies classifications are robust to the choice of initial mean values used in the classification and non-contemporaneous timing of geophysical data acquisition. These results will lead to improved interdisciplinary models of Critical Zone processes at various scales, and to an increased ability to predict hydrologic timing and partitioning. Beyond the hillslope scale, this enhanced capability to compare Critical Zone architecture can also be exploited at the catchment scale with implications for improved understanding of the link between rock weathering, hydrochemical fluxes, and landscape morphology.