Abstract. Observation and quantification of the Earth's surface is undergoing a revolutionary change due to the increased spatial resolution and extent afforded by light detection and ranging (lidar) technology. As a consequence, lidar-derived information has led to fundamental discoveries within the individual disciplines of geomorphology, hydrology, and ecology. These disciplines form the cornerstones of critical zone (CZ) science, where researchers study how interactions among the geosphere, hydrosphere, and biosphere shape and maintain the "zone of life", which extends from the top of unweathered bedrock to the top of the vegetation canopy. Fundamental to CZ science is the development of transdisciplinary theories and tools that transcend disciplines and inform other's work, capture new levels of complexity, and create new intellectual outcomes and spaces. Researchers are just beginning to use lidar data sets to answer synergistic, transdisciplinary questions in CZ science, such as how CZ processes co-evolve over long timescales and interact over shorter timescales to create thresholds, shifts in states and fluxes of water, energy, and carbon. The objective of this review is to elucidate the transformative potential of lidar for CZ science to simultaneously allow for quantification of topographic, vegetative, and hydrological processes. A review of 147 peer-reviewed lidar studies highlights a lack of lidar applications for CZ studies as 38 % of the studies were focused in geomorphology, 18 % in hydrology, 32 % in ecology, and the remaining 12 % had an interdisciplinary focus. A handful of exemplar transdisciplinary studies demon- Published by Copernicus Publications on behalf of the European Geosciences Union. 2882 A. A. Harpold et al.: Laser vision: lidar as a transformative toolstrate lidar data sets that are well-integrated with other observations can lead to fundamental advances in CZ science, such as identification of feedbacks between hydrological and ecological processes over hillslope scales and the synergistic co-evolution of landscape-scale CZ structure due to interactions amongst carbon, energy, and water cycles. We propose that using lidar to its full potential will require numerous advances, including new and more powerful open-source processing tools, exploiting new lidar acquisition technologies, and improved integration with physically based models and complementary in situ and remote-sensing observations. We provide a 5-year vision that advocates for the expanded use of lidar data sets and highlights subsequent potential to advance the state of CZ science.

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Abstract. Laser vision: lidar as a transformative tool to advance critical zone science. Observation and quantification of the Earth surface is undergoing a revolutionary change due to the increased spatial resolution and extent afforded by light detection and ranging (lidar) technology. As a consequence, lidar-derived information has led to fundamental discoveries within the individual disciplines of geomorphology, hydrology, and ecology. These disciplines form the cornerstones of Critical Zone (CZ) science, where researchers study how interactions among the geosphere, hydrosphere, and ecosphere shape and maintain the "zone of life", extending from the groundwater to the vegetation canopy. Lidar holds promise as a transdisciplinary CZ research tool by simultaneously allowing for quantification of topographic, vegetative, and hydrological data. Researchers are just beginning to utilize lidar datasets to answer synergistic questions in CZ science, such as how landforms and soils develop in space and time as a function of the local climate, biota, hydrologic properties, and lithology. This review's objective is to demonstrate the transformative potential of lidar by critically assessing both challenges and opportunities for transdisciplinary lidar applications. A review of 147 peer-reviewed studies utilizing lidar showed that 38 % of the studies were focused in geomorphology, 18 % in hydrology, 32 % in ecology, and the remaining 12 % have an interdisciplinary focus. We find that using lidar to its full potential will require numerous advances across CZ applications, including new and more powerful open-source processing tools, exploiting new lidar acquisition technologies, and improved integration with physically-based models and complementary in situ and remote-sensing observations. We provide a five-year vision to utilize and advocate for the expanded use of lidar datasets to benefit CZ science applications.

We present a statistical model of soil and rock weathering in deep profiles to expand the capacity to assess weathering to heterogeneous bedrock types, which are common at the Earth's surface. We developed the Weathering Trends (WT) model by extending the fractional mass change calculation (tau) of the geochemical mass balance model in two important ways. First, WT log transforms the elemental ratio data, to discern the log‐linear patterns that naturally develop from thermodynamic and kinetic laws of chemistry. Second, WT statistically fits log‐transformed element concentration ratio data – log(cj/ci), the only depth‐varying term in tau – as a function of depth to determine characteristic depths of transitions in weathering processes, along with confidence intervals. With no prior assumptions, WT estimates average parent material composition, average composition of the upper weathered zone and mean fractional mass change of each element over the entire weathering profile. WT displays the mean shape of weathering profiles of log‐transformed geochemical data bounded by calculated confidence intervals. We share the WT model code as an open‐source R package (https://github.com/fisherba/WeatheringTrends). The WT model was designed to interpret two 21 m cores from the Laurels Schist bedrock in the Christina River Basin Critical Zone Observatory in the Pennsylvania Piedmont, where our morphological and elemental data provided inconclusive estimates of bedrock depth. The WT model differentiated between rock variability and weathering to delineate the maximum extent of weathering at 12.3 m (CI 95% [9.2, 21.3]) in Ridge Well 1 and 7.2 m (CI 95% [4.3, 13.0]) in Interfluve Well 2. The water table was 5–8 m below fresh rock at Ridge Well 1, but at the same depth as fresh rock at the lower elevation interfluve. We assess statistical approaches to identify the best immobile element for use in WT and tau calculations. Copyright © 2017 John Wiley & Sons, Ltd.