Changing River Flood Timing in the Northeastern and Upper Midwest United States: Weakening of Seasonality over Time?

Climate change is likely to impact precipitation as well as snow accumulation and melt in the Northeastern and Upper Midwest United States, ultimately affecting the quantity and seasonal distribution of streamflow. The objective of this study is to analyze seasonality of long-term daily annual maximum streamflow (AMF) records and its changes for 158 sites in Northeastern and Upper Midwest Unites States. A comprehensive circular statistical approach comprising a kernel density method was used to assess the seasonality of AMF. Temporal changes were analyzed by separating the AMF records into two 30-year sub-periods (1951–1980 and 1981–2010). Results for temporal change in seasonality showed mixed pattern/trend across the stations. While for majority of stations, the distribution of AMF timing is strongly unimodal (concentrated around spring season) for the period 1951–1980, the seasonal modes have weakened during the period 1981–2010 for several stations along the coastal region with simultaneous emergence of multiple modes indicating changes of seasonality therein. The fresh statistical approach based on non-parametric circular density estimates reduces some of the limitations of previous studies to detect and model event timing distributions with multiple seasons and addresses issues of non-stationarity in the data records of extreme events

Use of WRF-Hydro over the Northeast of the US to Estimate Water Budget Tendencies in Small Watersheds

In the Northeast of the US, climate change will bring a series of impacts on the terrestrial hydrology. Observations indicate that temperature has steadily increased during the last century, including changes in precipitation. This study implements the Weather Research and Forecasting (WRF)-Hydro framework with the Noah-Multiparameterization (Noah-MP) model that is currently used in the National Water Model to estimate the tendencies of the different variables that compounded the water budget in the Northeast of the US from 1980 to 2016. We use North American Land Data Assimilation System-2 (NLDAS-2) climate data as forcing, and we calibrated the model using 192 US Geological Survey (USGS) Geospatial Attributes of Gages for Evaluating Streamflow II (Gages II) reference stations. We study the tendencies determining the Kendall-Theil slope of streamflow using the maximum three-day average, seven-day minimum flow, and the monotonic five-day mean times series. For the water budget, we determine the Kendall-Theil slope for changes in monthly values of precipitation, surface and subsurface runoff, evapotranspiration, transpiration, soil moisture, and snow accumulation. The results indicate that the changes in precipitation are not being distributed evenly in the components of the water budget. Precipitation is decreasing during winter and increasing during the summer, with the direct impacts being a decrease in snow accumulation and an increase in evapotranspiration. The soil tends to be drier, which does not translate to a rise in infiltration since the surface runoff aggregated tendencies are positive, and the underground runoff aggregated tendencies are negative. The effects of climate change on streamflows are buffered by larger areas, indicating that more attention needs to be given to small catchments to adapt to climate change

Fluorescence of thermal control coatings on S0069 and A0114

Many of the thermal control surfaces exposed to the space environment during the 5.8 year LDEF mission experienced changes in fluorescence. All of the thermal control coatings flown on LDEF experiments S0069 and A0114 were characterized for fluorescence under ambient conditions. Some of the black coatings, having protective overcoats, appear bright yellow under ultraviolet exposure. Urethane based coatings exhibited emission spectra shifts toward longer wavelengths in the visible range. Zinc oxide pigment based coatings experienced a quenching of fluorescence, while zinc orthotitanate pigment based and other ceramic type coatings had no measurable fluorescence

Low-Flow (7-Day, 10-Year) Classical Statistical and Improved Machine Learning Estimation Methodologies

Water resource managers require accurate estimates of the 7-day, 10-year low flow (7Q10) of streams for many reasons, including protecting aquatic species, designing wastewater treatment plants, and calculating municipal water availability. StreamStats, a publicly available web application developed by the United States Geologic Survey that is commonly used by resource managers for estimating the 7Q10 in states where it is available, utilizes state-by-state, locally calibrated regression equations for estimation. This paper expands StreamStats’ methodology and improves 7Q10 estimation by developing a more regionally applicable and generalized methodology for 7Q10 estimation. In addition to classical methodologies, namely multiple linear regression (MLR) and multiple linear regression in log space (LTLR), three promising machine learning algorithms, random forest (RF) decision trees, neural networks (NN), and generalized additive models (GAM), are tested to determine if more advanced statistical methods offer improved estimation. For illustrative purposes, this methodology is applied to and verified for the full range of unimpaired, gaged basins in both the northeast and mid-Atlantic hydrologic regions of the United States (with basin sizes ranging from 2–1419 mi2) using leave-one-out cross-validation (LOOCV). Pearson’s correlation coefficient (R2), root mean square error (RMSE), Kling–Gupta Efficiency (KGE), and Nash–Sutcliffe Efficiency (NSE) are used to evaluate the performance of each method. Results suggest that each method provides varying results based on basin size, with RF displaying the smallest average RMSE (5.85) across all ranges of basin sizes

The Effects of Climate Change on Seasonal Snowpack and the Hydrology of the Northeastern and Upper Midwest United States

Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC §108) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form, such as on a website or in a searchable database, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. All AMS journals and monograph publications are registered with the Copyright Clearance Center (http://www.copyright.com). Questions about permission to use materials for which AMS holds the copyright can also be directed to the AMS Permissions Officer at [email protected]. Additional details are provided in the AMS Copyright Policy statement, available on the AMS website (http://www.ametsoc.org/CopyrightInformation).The potential effects of climate change on the snowpack of the northeastern and upper Midwest United States are assessed using statistically downscaled climate projections from an ensemble of 10 climate models and a macroscale hydrological model. Climate simulations for the region indicate warmer-than-normal temperatures and wetter conditions for the snow season (November–April) during the twenty-first century. However, despite projected increases in seasonal precipitation, statistically significant negative trends in snow water equivalent (SWE) are found for the region. Snow cover is likely to migrate northward in the future as a result of warmer-than-present air temperatures, with higher loss rates in northern latitudes and at high elevation. Decreases in future (2041–95) snow cover in early spring will likely affect the timing of maximum spring peak streamflow, with earlier peaks predicted in more than 80% of the 124 basins studied

Planning for the Impacts of Climate Change on Municipal Water Supplies

Four approaches for incorporating climate change into evaluating system performance are presented in this paper. These approaches range from simple modification of historic streamflow records to incorporation of the results of global circulation models

Transport behavior of holes in boron delta-doped diamond structures

Boron delta-doped diamond structures have been synthesized using microwave plasma chemical vapor deposition and fabricated into FET and gated Hall bar devices for assessment of the electrical characteristics. A detailed study of variable temperature Hall, conductivity, and field-effect mobility measurements was completed. This was supported by Schr€dinger-Poisson and relaxation time o calculations based upon application of Fermi’s golden rule. A two carrier-type model was developed with an activation energy of $0.2 eV between the delta layer lowest subband with mobility$1 cm2/Vs and the bulk valence band with high mobility. This new understanding of the transport of holes in such boron delta-doped structures has shown that although Hall mobility as high as 900 cm2/Vs was measured at room temperature, this dramatically overstates the actual useful performance of the device

Groupoids, Loop Spaces and Quantization of 2-Plectic Manifolds

We describe the quantization of 2-plectic manifolds as they arise in the context of the quantum geometry of M-branes and non-geometric flux compactifications of closed string theory. We review the groupoid approach to quantizing Poisson manifolds in detail, and then extend it to the loop spaces of 2-plectic manifolds, which are naturally symplectic manifolds. In particular, we discuss the groupoid quantization of the loop spaces of R^3, T^3 and S^3, and derive some interesting implications which match physical expectations from string theory and M-theory.Comment: 71 pages, v2: references adde

On Universal Halos and the Radial Orbit Instability

The radial orbit instability drives dark matter halos toward a universal structure. This conclusion, first noted by Huss, Jain, and Steinmetz, is explored in detail through a series of numerical experiments involving the collapse of an isolated halo into the non-linear regime. The role played by the radial orbit instability in generating the density profile, shape, and orbit structure is carefully analyzed and, in all cases, the instability leads to universality independent of initial conditions. New insights into the underlying physics of the radial orbit instability are presented.Comment: 31 pages, 11 figures, submitted to the Astrophysical Journa