Stochastic Interpolation of Precipitation Data From Multiple Sensors

Introduction: This report summarizes the work conducted under Grant No. ECE-8419189, Stochastic Interpolation of Precipitation Data from Multiple Sensors, which was awarded to Utah State University in September, 1985, and completed February 29, 1988. it also covers work under a supplemental award made in February, 1986. The final report is organized into four sections. The following section presents the objective of the research and a brief problem statment. Section 3 contains a summary of second-year work including the project team, work plan, work completed, and publications. In Section4, project conclusions are summarized. A summary of on-going future work is given in Section 5, together with our plans for publication of research results from this project. Copies of preliminary draft manuscripts and completed technical reports which have been prepared as a result of second-year activities are contained in the Appendices. A cummulative summary of project publications is presented in Appendix A

Prolonged maternal separation induces undernutrition and systemic inflammation with disrupted hippocampal development in mice

Objective: Prolonged maternal separation (PMS) in the first 2 wk of life has been associated with poor growth with lasting effects in brain structure and function. This study aimed to investigate whether PMS-induced undernutrition could cause systemic inflammation and changes in nutrition-related hormonal levels, affecting hippocampal structure and neurotransmission in C57BL/6J suckling mice. Methods: This study assessed mouse growth parameters coupled with insulin-like growth factor-1 (IGF-1) serum levels. In addition, leptin, adiponectin, and corticosterone serum levels were measured following PMS. Hippocampal stereology and the amino acid levels were also assessed. Furthermore, we measured myelin basic protein and synapthophysin (SYN) expression in the overall brain tissue and hippocampal SYN immunolabeling. For behavioral tests, we analyzed the ontogeny of selected neonatal reflexes. PMS was induced by separating half the pups in each litter from their lactating dams for defined periods each day (4 h on day 1, 8 h on day 2, and 12 h thereafter). A total of 67 suckling pups were used in this study. Results: PMS induced significant slowdown in weight gain and growth impairment. Significant reductions in serum leptin and IGF-1 levels were found following PMS. Total CA3 area and volume were reduced, specifically affecting the pyramidal layer in PMS mice. CA1 pyramidal layer area was also reduced. Overall hippocampal SYN immunolabeling was lower, especially in CA3 field and dentate gyrus. Furthermore, PMS reduced hippocampal aspartate, glutamate, and gammaaminobutyric acid levels, as compared with unseparated controls. Conclusion: These findings suggest that PMS causes significant growth deficits and alterations in hippocampal morphology and neurotransmission.This work was supported in part by National Institutes of Health (NIH) research grant 5R01HD053131, funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and the NIH Office of Dietary Supplements, and Brazilian grants from CNPq and CAPES (Grant # RO1 HD053131). The authors would like to thank Dr. Patricia Foley for veterinarian technical support and Dr. Jose Paulo Andrade for the excellent comments and suggestions to improve this manuscript. N.S. contributed with the stereological studies. I.L.F. and R.B.O. contributed with the behavioral studies. I.L.F., R.B.O., and R.L.G. contributed with the study design, study analysis, and manuscript preparation. G.A.M. and P.B.F. contributed with neurochemical brain analyses. J.I.A.L. and G.M.A. contributed with hormonal and CRP serum analyses. D.G.C., K.M.C., and R.S.R. contributed with animal experimentation and data collection

Comparing Approaches to Deal with Non-Gaussianity of Rainfall Data in Kriging-Based Radar-Gauge Rainfall Merging

Merging radar and rain gauge rainfall data is a technique used to improve the quality of spatial rainfall estimates and in particular the use of Kriging with External Drift (KED) is a very effective radar-rain gauge rainfall merging technique. However, kriging interpolations assume Gaussianity of the process. Rainfall has a strongly skewed, positive, probability distribution, characterized by a discontinuity due to intermittency. In KED rainfall residuals are used, implicitly calculated as the difference between rain gauge data and a linear function of the radar estimates. Rainfall residuals are non-Gaussian as well. The aim of this work is to evaluate the impact of applying KED to non-Gaussian rainfall residuals, and to assess the best techniques to improve Gaussianity. We compare Box-Cox transformations with λ parameters equal to 0.5, 0.25, and 0.1, Box-Cox with time-variant optimization of λ, normal score transformation, and a singularity analysis technique. The results suggest that Box-Cox with λ = 0.1 and the singularity analysis is not suitable for KED. Normal score transformation and Box-Cox with optimized λ, or λ = 0.25 produce satisfactory results in terms of Gaussianity of the residuals, probability distribution of the merged rainfall products, and rainfall estimate quality, when validated through cross-validation. However, it is observed that Box-Cox transformations are strongly dependent on the temporal and spatial variability of rainfall and on the units used for the rainfall intensity. Overall, applying transformations results in a quantitative improvement of the rainfall estimates only if the correct transformations for the specific data set are used.ISSN:0043-1397ISSN:1944-797

WRRCSR No.06:30:91(II) Simulation of Solute Transport in Heterogeneous Soils - Volume II: Numerical Experiments

Spatial variability of saturated hydraulic conductivity is examined to assess the effect of uncertainty in leaching of pesticides from heterogeneous soils. Saturated hydraulic conductivity, an important soil parameter that controls the transport of pesticides in soils, is assumed to be composed of a homogeneous mean value and a perturbation caused by the spatial variability of soil properties producing a stochastic process in the mean flow direction. The spatial heterogeneity of porous soils is characterized by the variance and the correlation scale of the saturated hydraulic conductivity in the transport domain. In the first part of the study, numerical experiments are used to investigate the development of scale-dependent macrodispersivity in the unsaturated heterogeneous soils. In the second part of the study, the significance of the variance on the spatial and temporal distribution of tracer spreading is demonstrated for Hawaii Oxic soils. The significance of variance regarding the spatial and temporal distribution of tracer concentrations is demonstrated using solute breakthrough curves at various depths in the soil profile. Macrodispersivity values in heterogeneous soils are proportional to the variance at smaller travel distances and converge to the same value at larger travel distances. For greater correlational distances, a faster breakthrough of solutes at various depths was observed.U.S. Geological Survey Grant/Contract No. B-10