6 research outputs found

    Track D Social Science, Human Rights and Political Science

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    Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138414/1/jia218442.pd

    Pier and Contraction Scour Prediction in Cohesive Soils at Selected Bridges in Illinois

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    This report presents the results of testing the Scour Rate In Cohesive Soils-Erosion Function Apparatus (SRICOS-EFA) method for estimating scour depth of cohesive soils at 15 bridges in Illinois. The SRICOS-EFA method for complex pier and contraction scour in cohesive soils has two primary components. The first component includes the calculation of the maximum contraction and pier scour (Zmax). The second component is an integrated approach that considers a time factor, soil properties, and continued interaction between the contraction and pier scour (SRICOS runs). The SRICOS-EFA results were compared to scour prediction results for non-cohesive soils based on Hydraulic Engineering Circular No. 18 (HEC-18). On average, the HEC-18 method predicted higher scour depths than the SRICOS-EFA method. A reduction factor was determined for each HEC-18 result to make it match the maximum of three types of SRICOS run results. The unconfined compressive strength (Qu) for the soil was then matched with the reduction factor and the results were ranked in order of increasing Qu. Reduction factors were then grouped by Qu and applied to each bridge site and soil. These results, and comparison with the SRICOS Zmax calculation, show that less than half of the reduction-factor method values were the lowest estimate of scour; whereas, the Zmax method values were the lowest estimate for over half. A tiered approach to predicting pier and contraction scour was developed. There are four levels to this approach numbered in order of complexity, with the fourth level being a full SRICOS-EFA analysis. Levels 1 and 2 involve the reduction factors and Zmax calculation, and can be completed without EFA data. Level 3 requires some surrogate EFA data. Levels 3 and 4 require streamflow for input into SRICOS. Estimation techniques for both EFA surrogate data and streamflow data were developed.Illinois Department of Transportation ICT-R27-19not peer reviewe

    An analysis of the soil moisture feedback on convective and stratiform precipitation

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    Land-atmosphere interactions in midlatitude continental regions are particularly active during the warm season. It is still unclear whether and under what circumstances these interactions may involve positive or negative feedbacks between soil moisture conditions and rainfall occurrence. Assessing such feedbacks is crucially important to a better understanding of the role of land surface conditions on the regional dynamics of the water cycle. This work investigates the relationship between soil moisture and subsequent precipitation at the daily time scale in a midlatitude continental region. Sounding data from 16 locations across the midwestern United States are used to calculate two indices of atmospheric instability—namely, the convective available potential energy (CAPE) and the convective inhibition (CIN). These indices are used to classify rainfall as convective or stratiform. Correlation analyses and uniformity tests are then carried out separately for these two rainfall categories, to assess the dependence of rainfall occurrence on antecedent soil moisture conditions, using simulated soil moisture values. The analysis suggests that most of the positive correlation observed between soil moisture and subsequent precipitation is due to the autocorrelation of long stratiform events. The authors found both areas with positive and areas with negative feedback on convective precipitation. This behavior is likely due to the contrasting effects of soil moisture conditions on convective phenomena through changes in surface temperature and the supply of water vapor to the overlying air column. No significant correlation is found between daily rainfall intensity and antecedent simulated soil moisture conditions either for convective or stratiform rainfal

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