Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution Observatory: Toward Prediction of Coupled Hydrological, Biogeochemical, and Ecological Change

Understanding the process interactions and feedbacks among water, porous geological media, microbes, and vascular plants is crucial for improving predictions of the response of Earth’s critical zone to future climatic conditions. However, the integrated coevolution of landscapes under change is notoriously difficult to investigate. Laboratory studies are limited in spatial and temporal scale, while field studies lack observational density and control. To bridge the gap between controlled laboratory and uncontrollable field studies, the University of Arizona built a macrocosm experiment of unprecedented scale: the Landscape Evolution Observatory (LEO). LEO comprises three replicated, heavily instrumented, hillslope-scale model landscapes within the environmentally controlled Biosphere 2 facility. The model landscapes were designed to initially be simple and purely abiotic, enabling scientists to observe each step in the landscapes’ evolution as they undergo physical, chemical, and biological changes over many years. This chapter describes the model systems and associated research facilities and illustrates how LEO allows for tracking of multiscale matter and energy fluxes at a level of detail impossible in field experiments. Initial sensor, sampler, and soil coring data are already providing insights into the tight linkages between water flow, weathering, and microbial community development. These interacting processes are anticipated to drive the model systems to increasingly complex states and will be impacted by the introduction of vascular plants and changes in climatic regimes over the years to come. By intensively monitoring the evolutionary trajectory, integrating data with mathematical models, and fostering community-wide collaborations, we envision that emergent landscape structures and functions can be linked, and significant progress can be made toward predicting the coupled hydro-biogeochemical and ecological responses to global change

Reconstruction of the intersection on the regional road R2- 444 in the settlement of Ozeljan

Diplomska naloga obravnava študijo rekonstrukcije križišča in nevarnega priključka na regionalni cesti v naselju Ozeljan. Na podlagi štetja prometa, analize prometnih nesreč in pregledu obstoječih značilnosti križišča, je bila izvedena kapacitetna analiza in analiza prometne varnosti obstoječega križišča. Predstavljene so tri variantne rešitve obstoječega križišča in priključka, katere so varnostno in kapacitetno analizirane ter med seboj primerjane. Na podlagi primerjave je predlagana najustreznejša varianta in sicer na nivoju idejne zasnove. Predlagana projektna rešitev z izvedbo krožišča je sestavljena v skladu s trenutno veljavnimi smernicami, tehničnimi specifikacijami za javne ceste in krožišča.The diploma thesis deals with the study of the reconstruction of the intersection and the dangerous connection on the regional roads in the settlement of Ozeljan. Based on the traffic count, the traffic accidents were analyzed in the review of the existing characteristics of the intersection, a powerful analysis and traffic safety analysis of the existing intersection were performed. Three variants of the solution of the existing intersection and the connection are presented, which are analyzed in terms of safety and performance. Based on the comparison, the most appropriate version is proposed, namely at the level of conceptual design. The proposed project solution with the implementation of the roundabout is based on the currently valid guidelines, technical specifications for public roads and roundabouts

Evaluation of the Performance of Three Satellite Precipitation Products over Africa

We present an evaluation of daily estimates from three near real-time quasi-global Satellite Precipitation Products-Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and Climate Prediction Center (CPC) Morphing Technique (CMORPH)-over the African continent, using the Global Precipitation Climatology Project one Degree Day (GPCP-1dd) as a reference dataset for years 2001 to 2013. Different types of errors are characterized for each season as a function of spatial classifications (latitudinal bands, climatic zones and topography) and in relationship with the main rain-producing mechanisms in the continent: the Intertropical Convergence Zone (ITCZ) and the East African Monsoon. A bias correction of the satellite estimates is applied using a probability density function (pdf) matching approach, with a bias analysis as a function of rain intensity, season and latitude. The effects of bias correction on different error terms are analyzed, showing an almost elimination of the mean and variance terms in most of the cases. While raw estimates of TMPA show higher efficiency, all products have similar efficiencies after bias correction. PERSIANN consistently shows the smallest median errors when it correctly detects precipitation events. The areas with smallest relative errors and other performance measures follow the position of the ITCZ oscillating seasonally over the equator, illustrating the close relationship between satellite estimates and rainfall regime.Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT); GeoAguas Consultores (Chile); NASA SERVIR Program [11-SERVIR11-0058]; International Center for Integrated Water Resources Management (ICIWaRM) a Category II UNESCO CenterThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Quantifying the role of climate and landscape characteristics on hydrologic partitioning and vegetation response

[1] There is no consensus on how changes in both temperature and precipitation will affect regional vegetation. We investigated controls on hydrologic partitioning at the catchment scale across many different ecoregions, and compared the resulting estimates of catchment wetting and vaporization (evapotranspiration) to remotely sensed indices of vegetation greenness. The fraction of catchment wetting vaporized by plants, known as the Horton index, is strongly related to the ratio of available energy to available water at the Earth's surface, the aridity index. Here we show that the Horton index is also a function of catchment mean slope and elevation, and is thus related to landscape characteristics that control how much and how long water is retained in a catchment. We compared the power of the components of the water and energy balance, as well as landscape characteristics, to predict Normalized Difference Vegetation Index (NDVI), a surrogate for vegetation productivity, at 312 Model Parameter Estimation Experiment (MOPEX) catchments across the United States. Statistical analysis revealed that the Horton index provides more precision in predicting maximum annual NDVI for all catchments than mean annual precipitation, potential evapotranspiration, or their ratio, the aridity index. Models of vegetation productivity should emphasize plant-available water, rather than just precipitation, by incorporating the interaction of climate and landscape. Major findings related to the Horton index are: (1) it is a catchment signature that is relatively constant from year-to-year; (2) it is related to specific landscape characteristics; (3) it can be used to create catchment typologies; and (4) it is related to overall catchment greenness

Highly sampled measurements in a controlled atmosphere at the Biosphere 2 Landscape Evolution Observatory

Land-atmosphere interactions at different temporal and spatial scales are important for our understanding of the Earth system and its modeling. The Landscape Evolution Observatory (LEO) at Biosphere 2, managed by the University of Arizona, hosts three nearly identical artificial bare-soil hillslopes with dimensions of 11x30 m(2) (1m depth) in a controlled and highly monitored environment within three large greenhouses. These facilities provide a unique opportunity to explore these interactions. The dataset presented here is a subset of the measurements in each LEO's hillslopes, from 1 July 2015 to 30 June 2019 every 15minutes, consisting of temperature, water content and heat flux of the soil (at 5cm depth) for 12 co-located points; temperature, relative humidity and wind speed above ground at 5 locations and 5 different heights ranging from 0.25m to 9-10m; 3D wind at 1 location; the four components of radiation at 2 locations; spatially aggregated precipitation rates, total subsurface discharge, and relative water storage; and the measurements from a weather station outside the greenhouses.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Highly Sampled Measurements in a Controlled Atmosphere at the Biosphere 2 Landscape Evolution Observatory

Land-atmosphere interactions at different temporal and spatial scales are important for our understanding of the Earth system and its modeling. The Landscape Evolution Observatory (LEO) at Biosphere 2 managed by the University of Arizona host three nearly identical artificial bare-soil hillslopes with dimensions of 30m x 11m and 1m average depth in a controlled and highly monitored environment under a large greenhouse. These facilities provide a unique opportunity to explore these interactions. This dataset contains, for each one of the three replicate hillslopes, 15-minute measurements from July 1, 2015 to June 30, 2019 of temperature, water content and heat flux of the soil at a depth of 5cm for 12 co-located points; temperature, relative humidity and wind speed above ground at 5 different locations over each hillslope and 5 different heights ranging from 0.25m to 9-10m; 3D wind components at 1 location; the 4 components of radiation at 2 different locations; precipitation rates; and the measurements of an automatic weather station outside the greenhouse

Coevolution of Nonlinear trends in Vegetation, Soils, and Topography with Elevation and Slope Aspect: A Case Study in the Sky Islands of Southern Arizona

Feedbacks among vegetation dynamics, pedogenesis, and topographic development affect the “critical zone”—the living filter for Earth’s hydrologic, biogeochemical, and rock/sediment cycles. Assessing the importance of such feedbacks, which may be particularly pronounced in water-limited systems, remains a fundamental interdisciplinary challenge. The sky islands of southern Arizona offer an unusually well-defined natural experiment involving such feedbacks because mean annual precipitation varies by a factor of five over distances of approximately 10 km in areas of similar rock type (granite) and tectonic history. Here we compile high-resolution, spatially distributed data for Effective Energy and Mass Transfer (EEMT: the energy available to drive bedrock weathering), above-ground biomass, soil thickness, hillslope-scale topographic relief, and drainage density in two such mountain ranges (Santa Catalina: SCM; Pinaleño: PM). Strong correlations exist among vegetation-soil-topography variables, which vary nonlinearly with elevation, such that warm, dry, low-elevation portions of these ranges are characterized by relatively low above-ground biomass, thin soils, minimal soil organic matter, steep slopes, and high drainage densities; conversely, cooler, wetter, higher elevations have systematically higher biomass, thicker organic-rich soils, gentler slopes, and lower drainage densities. To test if eco-pedo-geomorphic feedbacks drive this pattern, we developed a landscape evolution model that couples pedogenesis and topographic development over geologic time scales, with rates explicitly dependent on vegetation density. The model self-organizes into states similar to those observed in SCM and PM. Our results highlight the potential importance of eco-pedo-geomorphic feedbacks, mediated by soil thickness, in water-limited systems