We present a new metric for braiding intensity to characterize multi-thread systems (e.g., braided and anastomosing rivers) called the Entropic Braiding Index, eBI. This metric is a generalization of the widely used Braiding Index (BI) which is simply the average count of intercepted channels per cross-section. The co-existence of diverse channels (widely different widths and discharges) within river cross-sections distorts the information conveyed by BI, since its value does not reflect the diversity and natural variability of the system. Moreover, the fact that BI is extremely sensitive to resolution (BI increases at higher resolution as smaller scale channels can be resolved) challenges its applicability. eBI, addresses these main drawbacks of BI. eBI is rooted in the concept of Shannon Entropy, and its value can be intuitively interpreted as the equivalent number of equally important (in terms of discharge) channels per cross-section. Thus, if the channels observed in a multi-thread system are all carrying the same amount of discharge, eBI has the same value of BI. On the other hand, if a very dominant channel in terms of discharge co-exists with much smaller channels, eBI would take a value slightly larger than 1 (note that the actual value would depend on the number of small channels and their relative size with respect to the dominant channel). We present a comparative study of BI and eBI for different multi-thread rivers obtained from numerical simulations and remote-sensing data and for different discharge stages. We also provide evidence of the robustness of eBI in contrast to BI when a given river system is studied under different resolutions. Finally, we explore the potential of eBI as a metric to characterize different types of multi-thread systems and their stability.
NASA’s 2021 STV Incubation Study Report lists vertical (horizontal, geolocation) accuracy as an associated SATM product parameter for all (most) identified Science and Application Knowledge Gaps. The presented generalized Polynomial Chaos Expansion (gPCE) based method has wide ranging applicability to improve positioning, geolocation uncertainty estimates for all STV disciplines, but is presented for the bathymetric lidar use case, due to added complexity introduced by wave structure, roughness, and entry angle. Most LiDARs, though precise, are vulnerable to position, pointing errors as deviations from the expected principal axis lead to projection errors on target. While fidelity of location/pointing solutions can be high, determination of uncertainty remains relatively basic. Currently, the standard approach is the calculation of the Total Propagated Uncertainty (TPU), which is often plagued by simplifying approximations and ignored covariances. Additionally, uncertainty sources are often exclusively modeled as Gaussian, inaccurately capturing some variable distributions. Prominently, wave behavior is better described by Gamma distributions (which are supported under gPCE). This research addresses specific knowledge gaps in bathy-LiDAR measurement uncertainty through a more complete description of total aggregated uncertainties, from system level to geolocation, by applying a gPCE uncertainty quantification approach. gPCE intrinsically accounts for covariance between variables to determine the uncertainty in a measurement, without manually constructing a covariance matrix, through a surrogate model of system response. Determining point-wise positioning uncertainty using gPCE is less computationally expensive than Monte Carlo methods and more tractable for most dimensionalities of interest (roughly from 3 to 20+). The method also does not rely on simplifying assumptions used in typical TPU methods. Additionally, a key attribute of this approach is that global sensitivity analysis (GSA), after obtaining gPCE coefficients, is trivial and nearly costless to compute. Furthermore, GSA of system configurations/uncertainty is a powerful tool to design and develop LiDAR systems with the measurement requirements integrated into the design solution.
Human-mediated climate change over the past century has made significant impacts on global ecosystems and biodiversity including accelerating redistribution of the geographic ranges of species. In mountainous regions, the transition zone from continuous closed-canopy subalpine forests to treeless alpine tundra areas at higher elevations is commonly referred to as ‘Alpine Treeline Ecotone’ (ATE). Globally, warming climate is expected to drive the ATE upslope, which could lead to negative impacts on local biodiversity and modify ecosystem function. However, existing studies rely primarily on field-based data which are difficult and time consuming to collect. In this research, we define three critical characteristics of the ATE including 1) an abrupt spatial shift in vegetative activity as elevation varies, 2) reduction in vegetative activity as elevation increases, and 3) vegetative activity is at an intermediate level. Using the geospatial tools provided by Google Earth Engine, we construct an index (ATEI) to identify areas with the three ATE features based on the image gradients of vegetative activity and elevation datasets. Based on the ATEI and Google Earth imagery in 115 Landsat pixels, we establish a Logistic regression model to estimate the probability of whether or not a sampled pixel is located within the ATE. The prediction accuracy is approximately 80%. Furthermore, the ATEI-estimated ATE elevation is strongly correlated (r = 0.96) with a set of field-based data at 20 sampling sites from across the region. Based on the average annual ATEIs from 2009 to 2011, we estimate the average ATE elevation for each mountain range in the western U.S. The result varies from 1,183 m to 3,584 m. The detection metric developed in this study facilitates monitoring the geographic location and potential shifts of ATEs as well as the general impact of climate change in mountainous regions during recent decades. We also expect this approach to be useful in monitoring other ecosystem boundaries.
Spanning a period of more than 15 years, the Landsat Legacy Project Team researched, complied and published, in late 2017, Landsat's Enduring Legacy that describes the myriad of factors that surround the nearly half-century of monitoring the Earth's surface with Landsat. Born of technologies that evolved from the World War II, Landsat not only pioneered global land monitoring but, in the process, drove innovation in digital imaging technologies and encouraged development of global imagery archives. Access to this imagery led to early breakthroughs in natural resources assessments, particularly for agriculture, forestry, and geology. The technical and political aspects of the remote sensing revolution led by Landsat were not simple or straightforward. Early conflicts between civilian and defense satellite remote sensing users gave way to disagreements over whether the Landsat system should be a public service or a private enterprise. Only the combined engagement of civilian and defense organizations ultimately saved this pioneer satellite land monitoring program from termination. With the emergence of 21st century Earth system science research, coupled with greatly enhanced data computing, storage and transfer capabilities, the full value of the Landsat concept and its continuous, calibrated nearly half-century global archive has been recognized and embraced. The attempts to privatize Landsat had dramatic negative impacts on the collection, availability, and use of the data. These impacts should inform deliberations on the future of the Landsat program moving toward a Sustained Land Imaging program following Landsat 9. Discussion of Landsat's future continues, but its heritage will not be forgotten.
Along sandy coasts, the seaward expansion of dunes starts with the development of embryonic dunes. Vegetation is crucial for their initiation and the subsequent increase in dune height and volume when sediment supply is sufficient. During severe storms, the plants’ tolerance to and recovery from hydrodynamic disturbances, such as exposure to saline water during high water levels and their (partial) removal during storms, is vital to the long-term (months to years) resilience of the dune building process. Accordingly, areas with high embryo dune abundance have been correlated to wider beaches, attributed both to increased wind-driven sediment supply and increased wave attenuation during storms. Recent observations have shown that alongshore variations in subtidal sandbar morphology may also lead to variations in wave attenuation and foredune erosion, following a series of extreme storms. With our research we aim to determine whether subtidal bar characteristics play a role in long-term (months to years) embryo dune development. We first analysed a data set of 112 annual bathymetric profiles (spaced 250 m alongshore) and topographic (airborne Lidar) measurements in addition to observations of embryo dune presence derived from aerial photographs, spanning 50 km along the Dutch coast from 2010 to 2016. Embryo dune area extraction was done by supervised classification of vegetation pixels on the beach. Using a linear regression model, we found that profiles with a more seaward vegetation extent significantly correlated to shallower subtidal bars, in particular during stormy years. Second, to study the timing and alongshore variability of individual erosion events in more detail, we analysed 10 years (2005-2015) of half-hourly images of a 4-km stretch of the same coast, near Egmond aan Zee, in addition to the annual data. These images provide unique observations of the entire bar-beach-dune system, allowing for the concurrent analysis of bar morphology, embryo dune areas and, crucially, embryo dune exposure to saline water and wave action during storm events. At the conference, we will further explain the observed spatial and temporal (storm-driven) variability in embryo dune development.
Boreal forest heights are closely associated with the global carbon and energy budget. Existing investigations of boreal forests were mainly carried out at plot scales, which cannot be guaranteed on an annual and regional-scale basis given their sampling schemes. The launch of the Advanced Topographic Laser Altimeter System (ATLAS) onboard the NASA’s Ice, Cloud and Land Elevation Satellite (ICESat-2) enables the measurement of forest vertical structure at a global scale. However, with a photon-counting system, ICESat-2 receives substantially reduced signals over vegetated regions (low albedo), making its applications in forest height mapping challenging. This study made the first attempt to develop a 30-m canopy height model (CHM) for a mountainous forested site (located at the north of Fairbanks, Alaska) by coupling the ICESat-2 observed canopy heights, Hcanopy (response), with Landsat-8 (L8), Sentinel-1 (S1) and Sentinel-2 (S2) data using a random forest regressor. Here, Hcanopy corresponds to the 95th percentile (RH95) of all identified canopy photons within a 100-m segment. Before CHM development, low-quality ICESat-2 tracks were filtered out by comparing with the reference airborne lidar considering factors such as slope, canopy cover, signal-to-noise ratio, and canopy height uncertainty. Results suggest that: 1) ICESat-2 Hcanopy has the highest correlation with airborne lidar RH95 under strong beams; 2) the errors of ICESat-2 tracks become larger under lower signal-to-noise ratios (<5), steeper terrain (slope >20˚), greater canopy height uncertainty (>0.3) and sparser canopy cover condition (<20%); 3) by adopting the aforementioned criteria in filtering the ICESat-2 tracks, the Pearson’s correlation coefficient (R) between ICESat-2 Hcanopy and airborne lidar RH95 has been significantly improved to >0.8 under any beam strength; 4) based on previous results, we find that incorporating features derived from L8, S1 and S2 produces the most desirable CHM (R=0.85), and S2 overall shows a better capability than L8 in predicting regional-scale canopy heights; 5) among all input features, normalized difference vegetation index (NDVI) calculated based on the first red edge band (703.9nm) of S2 is the leading feature on CHM development, whereas land cover appears the least important.
In online education, student-to-student interaction can be an important component to encouraging independent thinking and achieving learning objectives. The course development team for “Minerals and Human Health” will share experiences in designing and implementing a virtual laboratory and collaborative projects for this online course. The first of its kind to be offered fully online, “Minerals and Human Health” encompasses the study of interactions between people and earth’s mineral resources, and how these interactions are influenced by a variety of natural, human health-related, economic, cultural and political factors. The virtual laboratory takes students on a virtual field trip to abandoned gold mines in the Mojave Desert, where students are able to observe images of samples provided from an electron microscope that the development team extracted for analysis. Using advanced recording techniques, stabilized body cameras, aerial drone footage, macro videography and wireless microphones, the team created a simulated field geologist experience, including footage of having narrowly escaped a massive desert dust storm. The virtual laboratory continues with a sequence of interactive videos where students are introduced to surveying and extraction from the field, lab equipment, and methods for analyzing and identifying mineral particles in dust samples. After learning principle concepts, students prepare an home-project called “The Air we Breathe”. In this collaborative project, students interact with each other via online discussion forums and video conferencing in order to collect dust particles for lab analysis. Students deliver the samples for study under optical and electron microscopes to the instructor, who distributes the results back to the students. Students then present their interpretation of the findings. Students are astonished to discover the air that they breathe every day includes hazards such as PM0.5-0.2 that are classified as carcinogenic materials. Initial student feedback has been collected throughout this newly developed course to identify areas that were most impactful and that could be improved for future iterations. Join us as we share our lessons learned while creating this extraordinary online learning experience.
We present evidence that suggests a new risk scenario for the Valdivia basin in south Chile, located in the area of the magnitude 9.5 1960 earthquake. In 1960, three mass movements, triggered by the earthquake shaking, dammed the upper course of the San Pedro River and threatened Valdivia City until it was opened in a controlled manner by its inhabitants. Published historical accounts indicate that the 1575 earthquake, predecessor of the 1960 event, also triggered a mass movement that dammed the upper course of the river. However, here we reinterpret the published account and present new historical records, which we combined with satellite imagery and field surveys to show that the volume of the landslide in 1575 was smaller than the smallest of those of 1960, yet its outburst flood killed thousands of natives located downstream. Additionally, we characterized different mass movement deposits in the upper course of the San Pedro River, including both ancient and those formed in 1960, and we evaluated the mechanisms that could contribute to their generation at present (e.g. land use). Our results suggest that in the present-day conditions a moderately-sized (Mw ~8) earthquake can be sufficient to cause damming the San Pedro River, which challenges the previous assumption that such phenomena are exclusively related to giant 1960-like earthquakes.
Southern California has seen a resurgence of winegrowing regions in the past few decades, however the future of winegrape climatic suitability in the area has not been exhaustively explored. This study evaluated the future climate suitability for the cultivation of winegrape and potential global warming impacts on southern California’s winegrowing regions through a series of high-resolution surface air temperature and precipitation projections obtained with the WRF-SSIB regional climate model. Results reveal that by mid-21st-century the surface air temperature will increase by approximately 1.2 °C, while average precipitation will decrease by as much as 11% in the southern winegrowing areas under the Intergovernmental Panel on Climate Change high greenhouse-gas emissions scenario. Evaluation of bioclimatic suitability indices indicate increases in heat accumulation for all major winegrowing areas; including an increase of about 10% in growing-degree day, while morning low temperatures in September may experience increases of approximately 11% in the future, thus impacting negatively the ripening stage of grapevines and leading to changes in wine composition and quality. Additionally, the extent of areas classified under the cool to warm climate suitability categories could decrease by nearly 42% in the study area by 2050. Conditions in southern California are already warm and dry for viticulture and continuing heat accumulation increase, along with rainfall reduction, could potentially place additional stress to winegrape crop in the area, including advanced phenological timing and moisture deficit stress that could lead to decreases in yield. The projected decline in viticulture suitability highlights the need for adaptive capacity within this sector to mitigate the impacts of global warming. Possible mitigating strategies include planting hotter climate grape varieties, moving vineyards to regions that are more suitable in the future, and adopting dry-farming techniques.
Soil carbon is intimately related to the living part of the organic matter, as represented by the soil microbial biomass, which mediates the decomposition, mineralization, and immobilization of organic carbon available in soils under different land-use systems. Forest-to-agriculture conversion and land-use change often lead to a loss in microbial biomass carbon (MBC) and shifts in microbial activity, directly influencing the soil carbon dynamics. The main aim of this study was to evaluate the effects of land-use change and geographical distribution on the microbial and environmental patterns related to soil C-dynamics. We evaluated MBC and microbial respiration in soils under five different land-use systems and two contrasting seasons, at a regional scale in Santa Catarina State, Southern Brazil. At the west mesoregion, changes in the MBC were correlated to sampling season in forest and grassland systems. Yet at the plateau mesoregion, we observed a land-use effect, as MBC decreased in no-till and crop-livestock integration systems. At the two mesoregions, forest and grassland had presented the highest values of MBC and microbial activity, as represented by microbial respiration. The grassland sites have presented lower values of the metabolic quotient (qCO2) and higher values of the microbial quotient (qMic). The qCO2 was lower in winter for all land-use systems. The forest sites have shown the highest total and particulate organic carbon values. The chemical-physical characteristics have shown correlations with microbiological variables related to the soil microbial C-dynamics. The land-use intensity, season, and geographic location were the main drivers of changes in microbial C-dynamics.
The poor across the world is very vulnerable to floods and drought disasters and have a detrimental effect on the lives and livelihoods of the poor. Weather based index insurance is one of the ways of dealing with these disasters. Protecting against floods and providing risk cover against losses due to floods has been a major area of concern for any government. Risk transfer through insurance is an important component in managing agricultural risks from extreme flood events. The study developed the first of its kind of designing and implementation of an index-based flood insurance (IBFI) product with the advanced use of satellite data and flood models to estimate crop losses due to floods. IBFI insurance product uses two different data elements, the first one is based on the flood model using HEC-HMS and HEC-RAS that uses inputs from NASA GPM bias-corrected satellite rainfall estimates, observed water level and discharge data, river characteristics, and digital elevation model to generate flood depth and flood duration to develop pre-determined thresholds based on the historical flood events between 1991 to 2015 and the second IBFI product uses only satellite data from NASA MODIS Terra and Aqua satellite data and the Copernicus Sentinel-1 SAR data to generate flood depth and flood duration to develop pre-determined thresholds based on the historical flood events and economic losses. More than 7,000 farming households in Bihar (India) and northern Bangladesh have signed up for a pilot IBFI scheme, which went live in 2017. The participating farmers have received insurance compensation for crop losses of over USD 160,000. In addition to the insurance product implementation, the research evaluated the farming willingness to pay, developing business models for scaling; social equity, and economic benefits of derisk disasters. IBFI initiative promotes a closer linkage between risk transfer and risk reduction that could make this more sustainable and robust financial instruments for flood-affected communities and reducing the burden of post-disaster relief funds for the government. In summary, the index insurance using open-access satellite imagery is a win-win opportunity as it brings down the data development cost, lower insurance premium, quick settlement, and greater transparency among various users.
We analyze changes in vegetation greenness across the coastal, Andean, and Amazonian regions of continental Ecuador, 1982-2010. Using Normalized Difference Vegetation Index (NDVI) anomalies derived from the Advanced Very High-Resolution Radiometer (AVHRR) on monthly and annual bases, we identify: i) long-term changes in annual NDVI, ii) seasonal shifts in greenness patterns, and iii) spatial patterns of change in vegetation greenness. Results indicate overall significant greening, or NDVI increase, after the mid-1990s, with distinct seasonal and regional variations. In the Amazon changes occur between September and February, resulting in a prolonged growing season during the later period. Significant increases are witnessed in coastal regions between February and May, but with no change in growing season. Fluctuations in NDVI in the Andes mimic the coast in the western slopes and the Amazon in the eastern slopes but exclude major changes in NDVI. The research investigates the possible effects of precipitation and CO2, and contributes to the understanding of tropical vegetation change in a rapidly changing environment.
Unmanned Aerial Vehicle (UAV) based Structure-from-Motion (SfM) techniques have renovated 3D topographic monitoring of earth surface, offering low-cost, rapid and reliable data acquisition and processing. Multi-temporal models of the river environment can be produced by autonomous operation in order to determine erosion, subsidence, landslide, soil transport and surface deformation in the riverbeds. Herein, the acquisition of repeated topographic surveys helps us to characterize the flow regime and to monitor the sediment dynamics. This study presents the hydromorphological changes of the meandering structures by using UAV-generated point clouds and Digital Surface Models (DSMs) produced by SfM at different times in the Büyük Menderes Basin located in the western part of Turkey. The processing of the data obtained with the flights were made in January and June 2018 at selected three meander locations with the highest visible changes according to the long-term satellite imageries. Especially, riverbank erosion along the river was determined by digitizing the edges and volumetric calculations of the eroded/deposited sediments derived from UAV-based measurements. In addition to the periodic volumetric differences of the meander structures, the differences in volumetric comparison methods for the same meander structures have been evaluated. Ultimately, the sediment profiles were extracted along the river banks at the selected part of the meanders and the amount of deposited sediments were determined to increase in a range between 1.5% and 3.3% of the total sediment. In conclusion, it is estimated that UAVs will be used instead of conventional photogrammetry aircraft in many future projects, considering the data production times and costs in large areas. Further, various digital cameras and sensors can be mounted on UAVs in order for examining the sediment effect on the health and productivity of plants in agricultural areas around the meanders.
Allowing near-surface geophysics students to learn ground penetrating radar (GPR) data processing through hands-on exercises poses a challenge because of the high cost of professional GPR software. Free processing and visualization packages are scarce and often either require other commercial software such as Matab, which many students may not have on their own computers, or they are limited to specific operating systems. To allow students to process GPR data on their own computers, for example data collected as part of a class-based research project or online available data, the processing software needs to be (1) free, (2) platform independent, (3) easy to install and use, and should record the steps the students take to obtain their results in order to facilitate reproducibility and grading. GPRPy (https://github.com/NSGeophysics/GPRPy) is an open-source ground penetrating radar data processing and visualization software that has a graphical user interface and which is also scriptable. It is python-based, making it platform independent and independent of commercial programming environments. The graphical user interface allows for writing out humanly readable python scripts that can be run from the command line to automatize the data processing and visualization. GPRPy is hosted on the collaborative software development website GitHub, allowing educators and researchers to create and adapt their own versions to their needs.
Physical habitat losses for Pacific salmonids in California’s Central Valley motivate stream restoration. Considerable river morphodynamics affect the sustainability of habitat enhancing interventions. In addition, the presence of large dams in many river catchments causes low sediment supply. This study revises existing stream restoration techniques for their ecologically efficient and physically stable embedding in a 36-km testbed river. Ecological efficiency is evaluated in terms of a commonly used hydraulic habitat suitability index. Physical stability results from 2D hydrodynamic modelling of bed shear stress during steady flows of different flood frequencies. We differentiate between terraforming, stabilizing and maintaining stream restoration techniques, which constitute three feature layers. The first layer, terraforming, includes artificial terrain modifications such as grading or backwater creation to generate new habitat. These features require stabilization, which is provided by the second feature layer. The stabilization (layer two) is achieved by bioengineering such as placement of streamwood, angular boulders and vegetation plantings. The third feature layer has the purpose to maintain newly created habitat, e.g., through artificial gravel injections. We illustrate the application of the three-layer-approach at one major restoration site of the lower Yuba River using a self-written Python package. Ecohydraulic 2D modeling was applied to designs with incremental layer additions to evaluate newly created spawning habitat and feature sustainability. This procedure represents a pertinent way for stream restoration planning, which avoids non-sustainable habitat enhancement features and implements ecologically as well as physically sustainable features only.
Various teaching methods including classroom lectures, physical experiments, and field excursions are useful for students to learn and understand the basic concepts of geography and earth sciences. However, due to constraints in the current curriculum of geographic education in Japanese schools, physical experiments and field excursions are rarely conducted, and classroom lectures tend to focus on memorizing some technical terms. This environment is not ideal for teaching processes and mechanisms of geographic phenomena. High-frequency, high-definition topographic data obtained using a TLS (Terrestrial Laser Scanner) and SfM-MVS photogrammetry with a UAS (Unmanned Aerial System) have become popular in geoscience. Those surveying approaches allow us to directly monitor rapidly changing landforms, while we can also use the obtained data to visualize geographic phenomena by various methods and materials including 3D print models, 3D virtual models, pictures, videos, and virtual/mixed reality. Here we explore the use of high-frequency, high-definition topographic data for educating geographic thinking. We arranged and conducted experimental teaching classes for elementary school students. First, we showed two 3D print models of the same sea cliff for years 2015 and 2017 constructed form high-definition topographic data. When students touched the two models, they were able to feel topographic changes due to erosion and sedimentation effectively. Furthermore, after exploring the 3D print models, many students were able to imagine how the sea cliff would change in the future. Next, we showed two images of fluvial deposits along a river segment in the area where the students live for July 2017 and September 2017. Then, they were able to imagine the transportation force of river flow. They also understood that the river flows typically in quiet but becomes powerful at high flow to move more sediment, and it might cause a disaster. Such visualized and touchable learning materials derived from high-frequency, high-definition topographic data enable students to enhance their geographic imagination of landforms, which are familiar to them but unexpectedly changing, at appropriate spatial and time scales.
Modern bedrock streams and rivers emerged in the Midwestern United States in response to glacial outwash floods ~19,000 years ago and continued to adjust to new drainage patterns over the landscape formed by Wisconsin glaciation events. The Illinois River and corresponding tributaries form a fascinating landscape with canyons carved 50-200 m deep into the St. Peter Sandstone. These geomorphic features are preserved and open to visitors as Starved Rock State Park in Central Illinois. Free access to the state parks and close proximity to the large Chicago metropolitan area result in frequent visitation to this natural attraction. Recently, the rates of natural stream incision appear to be overprinted by direct human influences on the landscape. The St. Peter Sandstone is a weakly cemented, extremely friable quartz arenite, making it susceptible to human disturbance and rapid natural erosion. This study explores how quickly present day changes occur along bedrock surfaces using photogrammetric Structure-from-Motion (SfM). Repeat photographic data were collected once per month from two sites within the park where canyon walls contained human carvings that served as reference features to align photos and monitor change. Photos were merged in Agisoft PhotoScan Pro to construct 3D point clouds and imported into CloudCompare to measure changes to rock surfaces between monthly visits. The photogrammetric SfM analysis detected measurable change on a centimeter to millimeter scale. Changes along footpaths were observed when visitor traffic was high. During winter months when visitor traffic decreased, rainfall and snowmelt runoff primarily caused mobilization and removal of loose sediments covering bedrock surfaces. Bedrock thin sections from each site were studied to assess the influence of cement on erosion rates. Lower cement concentrations were observed at the outcrop site with the greatest measured surface change. Changes detected with SfM analyses demonstrate that human interactions can influence erosion processes in a short time. While both natural and human caused changes occurred on bedrock surfaces, precipitation created greater measurable differences.
Forest management can enhance forest resiliency against natural disturbances such as fire, drought, or disease. Mechanical thinning, followed by a prescribed burn, is a useful technique to achieve a desired forest structure, usually maximizing large tree basal area or decreasing fuel loads, meant to protect against wildfire or reduce water stress in the western US. Changing forest structure can alter ecosystem function by reducing competition and exposing soil, modifying microclimates and creating suitable conditions for shrubs and grasses to encroach. Typically, forest treatments are expected to make the remaining trees more productive through competitive release, and an open canopy helps the understory to thrive. This enhanced plant water use often contradicts the expected result of increased streamflow following thinning. In mountainous terrain, water yield is further complicated by hillslope-scale processes of subsurface lateral flow and groundwater recharge. This research seeks to understand how management-derived forest structure influences hillslope-scale forest regrowth and water yield. We apply a spatially-distributed ecohydrologic model (RHESSys) to an experimental hillslope in the Sierra Nevada, CA. We incorporate multi-temporal Lidar observations and U.S. Forest Service Forest Inventory & Analysis (FIA) survey data to estimate post-thinning regrowth in treated plots in the watershed, which is used to verify RHESSys accuracy of vegetation regrowth. Then, we run long-term virtual thinning experiments to understand how the combination of thinning and prescribed burns in upslope and riparian sites separately and concurrently influences regrowth and water fluxes in these sites. We expect that an intermediate forest density will yield the most co-benefits in terms of carbon sequestration and water yield. However, these patterns will likely be modified along a hillslope, such that riparian forest stands will be less sensitive to the competitive release that thinning provides, whereas dense upslope forests will be highly sensitive to treatment since they are more water-limited. Water yield is likely to be confounded by multiple factors, including topography, whether a burn follows thinning to remove understory fluxes, and interactions between upslope thinning and processes of lateral flow and groundwater recharge when increased riparian water use compensates for additional upslope subsidies.