Inference of effective soil properties from observed vegetal canopy density

There are no author-identified significant results in this report

Areal coverage of storm precipitation

The probability distributions of the spatial distribution of precipitation from storms of different types were studied. The occurrence of wetted rainstorm area within a catchment was modeled as a Poisson arrival process in which each storm is composed of stationary, nonoverlapping, independent random cell clusters whose centers are Poisson-distributed as through fractals. The portion of a catchment covered by a stationary rainstorm was modeled by the common area of two overlapping circles. The first two moments of the distribution of the common area were derived from purely geometrical considerations. The spatial structure of the depth of rainfall from a stationary rainstorm was investigated using point process techniques. Total storm rainfall at the center of each cell is a random variable, and rainfall is distributed around the center specified by a spread function that may incorporate random parameters

Feasibility of using LANDSAT images of vegetation cover to estimate effective hydraulic properties of soils

Research activities conducted from February 1, 1985 to July 31, 1985 and preliminary conclusions regarding research objectives are summarized. The objective is to determine the feasibility of using LANDSAT data to estimate effective hydraulic properties of soils. The general approach is to apply the climatic-climax hypothesis (Ealgeson, 1982) to natural water-limited vegetation systems using canopy cover estimated from LANDSAT data. Natural water-limited systems typically consist of inhomogeneous vegetation canopies interspersed with bare soils. The ground resolution associated with one pixel from LANDSAT MSS (or TM) data is generally greater than the scale of the plant canopy or canopy clusters. Thus a method for resolving percent canopy cover at a subpixel level must be established before the Eagleson hypothesis can be tested. Two formulations are proposed which extend existing methods of analyzing mixed pixels to naturally vegetated landscapes. The first method involves use of the normalized vegetation index. The second approach is a physical model based on radiative transfer principles. Both methods are to be analyzed for their feasibility on selected sites

Extensions and applications of a second-order landsurface parameterization

Extensions and applications of a second order land surface parameterization, proposed by Andreou and Eagleson are developed. Procedures for evaluating the near surface storage depth used in one cell land surface parameterizations are suggested and tested by using the model. Sensitivity analysis to the key soil parameters is performed. A case study involving comparison with an "exact" numerical model and another simplified parameterization, under very dry climatic conditions and for two different soil types, is also incorporated

Spatial analysis of storm depths from an Arizona raingage network

Eight years of summer rainstorm observations are analyzed by a dense network of 93 raingages operated by the U.S. Department of Agriculture, Agricultural Research Service, in the 150 km Walnut Gulch experimental catchment near Tucson, Arizona. Storms are defined by the total depths collected at each raingage during the noon-to-noon period for which there was depth recorded at any of the gages. For each of the resulting 428 storm days, the gage depths are interpolated onto a dense grid and the resulting random field analyzed to obtain moments, isohyetal plots, spatial correlation function, variance function, and the spatial distribution of storm depth

Spatial characteristics of observed precipitation fields: A catalog of summer storms in Arizona, Volume 1

Eight years of summer raingage observations are analyzed for a dense, 93 gage, network operated by the U. S. Department of Agriculture, Agricultural Research Service, in their 150 sq km Walnut Gulch catchment near Tucson, Arizona. Storms are defined by the total depths collected at each raingage during the noon to noon period for which there was depth recorded at any of the gages. For each of the resulting 428 storms, the 93 gage depths are interpolated onto a dense grid and the resulting random field is anlyzed. Presented are: storm depth isohyets at 2 mm contour intervals, first three moments of point storm depth, spatial correlation function, spatial variance function, and the spatial distribution of total rainstorm depth

Developing Intensity-Duration-Frequency (IDF) Curves From Satellite-Based Precipitation: Methodology and Evaluation

Given the continuous advancement in the retrieval of precipitation from satellites, it is important to develop methods that incorporate satellite-based precipitation data sets in the design and planning of infrastructure. This is because in many regions around the world, in situ rainfall observations are sparse and have insufficient record length. A handful of studies examined the use of satellite-based precipitation to develop intensity-duration-frequency (IDF) curves; however, they have mostly focused on small spatial domains and relied on combining satellite-based with ground-based precipitation data sets. In this study, we explore this issue by providing a methodological framework with the potential to be applied in ungauged regions. This framework is based on accounting for the characteristics of satellite-based precipitation products, namely, adjustment of bias and transformation of areal to point rainfall. The latter method is based on previous studies on the reverse transformation (point to areal) commonly used to obtain catchment-scale IDF curves. The paper proceeds by applying this framework to develop IDF curves over the contiguous United States (CONUS); the data set used is Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks – Climate Data Record (PERSIANN-CDR). IDFs are then evaluated against National Oceanic and Atmospheric Administration (NOAA) Atlas 14 to provide a quantitative estimate of their accuracy. Results show that median errors are in the range of (17–22%), (6–12%), and (3–8%) for one-day, two-day and three-day IDFs, respectively, and return periods in the range (2–100) years. Furthermore, a considerable percentage of satellite-based IDFs lie within the confidence interval of NOAA Atlas 14

Open access, open source and cloud computing: a glimpse into the future of GIS

Open access data, open source software and cloud computing are three parallel and mutually reinforcing drivers of change in the field of applied geographical information systems (GIS). While these developments create many new opportunities for GIS users and companies, they are also associated with under-explored risks. This chapter investigates cloud GIS, focusing on the Australian Urban Research Infrastructure Network (AURIN), an online, cloud-based data portal and GIS designed explicitly for Australian urban research and public-sector planning applications. AURIN provides direct access to more than 4000 data sets, over 100 spatial analysis tools and powerful computational resources that are typically available in desktop GIS. The experience of developing, communicating and using AURIN has provided insights into the opportunities unleashed by new models of GIS research. This chapter explores those opportunities, such as greater accessibility, transparency and consistency in decision support for public policy, and risks of cloud GIS and its potential uses for social benefit

A new synaptic player leading to autism risk: Met receptor tyrosine kinase

The validity for assigning disorder risk to an autism spectrum disorder (ASD) candidate gene comes from convergent genetic, clinical, and developmental neurobiology data. Here, we review these lines of evidence from multiple human genetic studies, and non-human primate and mouse experiments that support the conclusion that the MET receptor tyrosine kinase (RTK) functions to influence synapse development in circuits relevant to certain core behavioral domains of ASD. There is association of both common functional alleles and rare copy number variants that impact levels of MET expression in the human cortex. The timing of Met expression is linked to axon terminal outgrowth and synaptogenesis in the developing rodent and primate forebrain, and both in vitro and in vivo studies implicate this RTK in dendritic branching, spine maturation, and excitatory connectivity in the neocortex. This impact can occur in a cell-nonautonomous fashion, emphasizing the unique role that Met plays in specific circuits relevant to ASD