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Byline: Jong-Suk Kim (1), Shaleen Jain (1,2) Abstract: Changes in the seasonality of streamflow in the western United States have important implications for water resources management and the wellbeing of coupled human-natural systems. An assessment of changes in the timing and magnitude of streamflow resolved at fine time scales (days to weeks and seasons) is highly relevant to adaptive management strategies that are responsive to changing hydrologic baselines. In this paper, we present a regional analysis of the changes in streamflow seasonality through a broad classification of streams and quantification of increases and decreases in flow, based on a quantile regression methodology. This analysis affords a useful research product to examine the diversity of trends across seasons for individual streams. The trend analysis methodology can identify windows of change, thus revealing vulnerabilities within decision calendars and species lifecycles, an important consideration for adaptation and mitigation efforts. Author Affiliation: (1) Department of Civil & Environmental Engineering, University of Maine, Orono, ME, 04469, USA (2) Climate Change Institute, University of Maine, Orono, ME, 04469, USA Article History: Registration Date: 16/07/2010 Received Date: 29/12/2009 Accepted Date: 10/07/2010 Online Date: 31/07/2010 Article note: Supported by NSF Grant: AGS0732309 & NOAA Grant: GC04-053. Electronic supplementary material The online version of this article (doi: 10.1007/s10584-010-9933-3) contains supplementary material, which is available to authorized users.

In the eastern United States, the empirical probability distribution of extreme daily precipitation comprises heavy rainfall events stemming from North Atlantic tropical cyclones (TCs). At many locations, these events influence estimates of extreme value statistics (e.g., 100‐year event), thus have important bearing on the sizing of flood protection infrastructure and, in general, flood risk management and preparedness. Consequently, a characterization of location specific and regional patterns in precipitation extremes and changes therein has salience for both scientific and engineering concerns. To this end, analysis of seasonal and annual maximum daily precipitation at 667 long‐term stations across the eastern United States was pursued to ascertain recent changes in the extreme events over the 1950–2011 period. Three key results from this study illuminate less understood facets of recent changes in precipitation extremes: (a) an overall increase in the fraction of seasonal and annual maximum precipitation events linked to TCs, (b) a dramatic increase in the correlation between Accumulated Cyclone Energy Index and the leading principal component of extreme precipitation, and (c) changes in the spatial patterns of regions with highest TC‐related risk for heavy precipitation. [ABSTRACT FROM AUTHOR]

• Drought has wide implications for humans and environment. • Water quality vulnerability to severe drought was assessed. • Probabilistic Water Quality Risk index identifies hotspot areas vulnerable to drought. • The proposed approach can translate drought information to watershed risk for water quality. Projected changes in the global climate indicate warmer temperatures and a highly variable hydrologic cycle, portending significant societal effects, particularly those stemming from drought. Whereas the extent of drought-related effects ranges from humans to environmental systems, the impacts on water quality, in particular, require careful investigation. Such investigation should include the interlinkages across climate and stream quality variables and how risk translates for various watersheds, given their particularities with respect to land use, watershed characteristics, and infrastructure. To this end, this study investigated drought assessment and the water quality vulnerability to severe drought, with the goal of informing planning and mitigation as a means to enhance drought resilience. This study was conducted in the Nakdong River basin in South Korea, which is vulnerable to water quality degradation during severe drought. We propose a method to evaluate spatial-temporal droughts based on the water quality risk and to monitor environmental droughts using the probability of exceeding the target water quality to facilitate a resilient proactive response. The results of this study can be used to provide scientific drought monitoring information for assessing real-time water quality monitoring from meteorological drought information. In addition, we expect to categorize vulnerable drought areas and to suggest essential management measures and tailored countermeasures at a local scale. [ABSTRACT FROM AUTHOR]

Abstract East Asia, including the Korean Peninsula, is exposed to the typhoon-related risk, especially in the form of flooding. The aim of this study was to determine the hydrologic variability characteristics of the Soyang River Dam—a representative multipurpose dam in the Korean Han River basin—with a particular focus on the quantitative assessment of the sensitivity of daily inflow into the dam basin and the related typhoon-impacts. Although the frequency of typhoons occurring in the western North Pacific Ocean region does not indicate any distinct increases, typhoons passing the domain of the Korean Peninsula change the summer flow of the Soyang River Dam significantly. Analysis results suggest that 22.6% of the summer flow in the Soyang River Dam can be attributed to typhoons. Furthermore, during the periods characterized by the transition from El Niño to La Niña, typhoons exert a large influence on the hydrologic regime. The frequency of typhoon occurrence is highly correlated to the typhoon-induced flow, and the occurrence date of peak flows when typhoons strike was determined to be significantly delayed compared to that of the average years (1974–2015). In addition, low-flow metrics show downward trends, however, there is no distinct correlation with the statistical data of typhoons. The results from this study offer baseline information for mid- and long-term plans that cope with natural disasters or the supply of water resources for humans and natural systems according to the seasonal flow patterns of basins. The links to typhoons signify the critical importance of integrative analyses that consider hydrologic and meteorological phenomena. [ABSTRACT FROM AUTHOR]

Over the past few decades, lake ice phenology in northern temperate lakes has exhibited increased interannual variability. The resulting increase in the incidence of unusually early spring lake ice‐out dates has the potential to affect stability, health, and function of the lake ecosystems. Characterizing the dependency of spring lake ice‐out date to winter and/or spring climate variables offers foreknowledge on the annual lake ice cover season, as the spring ice‐out date is an integrated response to prevailing weather/climate conditions during winter and spring. Here a circular regression framework is presented where ice‐out date regression models, conditioned on a suite of predictor winter and/or spring climate variables (i.e., degree days and snowfall), are developed for 12 Maine lakes to determine the relative import of winter and spring meteorological conditions on year‐to‐year variability of ice‐out dates in Maine lakes. In the circular regression models, ice‐out dates are expressed as points on a unit circle instead of real line, as it preserves the periodicity and order of time‐of‐day variables independent of the choice of reference point. Results show that (a) the magnitude and variance of seasonal spring temperatures explain more than half of the total variability in spring ice‐out date for Maine lakes, (b) the modulating efficacy of spring snowfall on the timing of spring ice‐out dates is the strongest in northern interior Maine lakes, (c) the role of winter degree days in determining the ice‐out dates in Maine lakes is significant across all climate regions, and (d) the effect of winter snowfall on ice‐out dates is significant in coastal Maine lakes. Diagnostics suggest that there are other climatic and nonclimatic variables that produce shifts in the lake ice‐out dates. Key Points: Timing of lake ice‐out critically influences physical and biogeochemical processesWinter and spring weather‐climate processes lend predictability to lake ice‐out datesLinear‐circular statistical framework allows comprehensive modeling and assessment of lake ice‐out [ABSTRACT FROM AUTHOR]

In temperate lakes, the wintertime Accumulated Freezing Degree‐Days (AFDD) modulate the thickness and phenology of winter ice‐cover, which in turn influence lake ecosystem processes and functions across seasons. Empirical studies show that the El Niño‐Southern Oscillation (ENSO)‐winter AFDD relationship for North American regions depends on the location and amplitude of the winter ENSO‐related sea surface temperature (SST) warming/cooling in the tropical Pacific (TP), and consequently changes in the magnitude and frequency of different ENSO patterns engender shifts and transitions in the North American lake ice regimes. For eight lakes located across North America, we found quasi‐linear and non‐linear relationships between winter AFDDs and spring lake ice‐out dates, and in some cases, existence of thresholds above and below which regression slopes are materially different, thus illuminating differential sensitivities. Conditional quantile functions for winter AFDDs that incorporate ENSO indices as covariates were developed to estimate the relative risk of early/late lake ice‐out events for these lakes. For seven of the eight lakes, the canonical Eastern Tropical El Niño pattern increases likelihood of low winter AFDDs (associated with early ice‐out dates in these lakes) by 1.5–2.8 times to that of the climatology (1951–2010 average), while the typical Central Pacific El Niño pattern corresponds to a decrease or no significant change in the occurrence probability of early ice‐out dates in these Lakes. These results demonstrate that the conditional winter AFDD estimated based on a comprehensive characterization of ENSO allow for delineation of distinct local‐to‐regional patterns of elevated risk of early ice out and short lake ice‐cover season for North American region. [ABSTRACT FROM AUTHOR]

Changes in seasonality of extreme storms have important implications for public safety, storm water infrastructure, and, in general, adaptation strategies in a changing climate. While past research on this topic offers some approaches to characterize seasonality, the methods are somewhat limited in their ability to discern the diversity of distributional types for extreme precipitation dates. Herein, we present a comprehensive approach for assessment of temporal changes in the calendar dates for extreme precipitation within a circular statistics framework which entails: (a) three measures to summarize circular random variables (traditional approach), (b) four nonparametric statistical tests, and (c) a new nonparametric circular density method to provide a robust assessment of the nature of probability distribution and changes. Two 30 year blocks (1951-1980 and 1981-2010) of annual maximum daily precipitation from 10 stations across the state of Maine were used for our analysis. Assessment of seasonality based on nonparametric approach indicated nonstationarity; some stations exhibited shifts in significant mode toward Spring season for the recent time period while some other stations exhibited multimodal seasonal pattern for both the time periods. Nonparametric circular density method, used in this study, allows for an adaptive estimation of seasonal density. Despite the limitation of being sensitive to the smoothing parameter, this method can accurately characterize one or more modes of seasonal peaks, as well as pave the way toward assessment of changes in seasonality over time. [ABSTRACT FROM AUTHOR]

The total ionizing dose response of both CMOS transistors and SiGe HBTs implemented without utilizing any radiation hardening by design techniques in Jazz Semiconductor's SBC-18-HXL BiCMOS technology platform is evaluated. The SiGe HBTs remain functional up to the 6 \Mrad(\SiO2) dose levels needed to support multi-Mrad exploration missions such as NASA's Europa mission. The CMOS devices are also functional to this extreme total dose. The nFETs exhibit significantly reduced shallow trench isolation leakage compared with nFETs implemented in prior SiGe BiCMOS processes. Both nFETs and pFETs show negligible transconductance and on-current degradation. We conclude that this SiGe process technology is a potential candidate for implementing reliable and survivable multi-Mrad total ionizing dose-hard electronic systems. [ABSTRACT FROM PUBLISHER]

An improved understanding of hydroclimatic variability is central to efforts that seek to anticipate and adapt water resources management in a variable and changing climate. In Korea's Han River Basin, warm season (June-September) streamflow contributes nearly 74% of the annual water supply. In this study, a 40-year record of simulated daily unimpaired streamflow for the Han River Basin and its 24 sub-watersheds is analysed with a view to identify relationships with atmospheric teleconnection patterns. Tree-based classification methods identify East Atlantic-Western Russia (EA-WR) and East Atlantic (EA) as the two dominant atmospheric circulation patterns that influence seasonal streamflow variability in the Han River Basin. The classification method allows partitioning of predictor space into three sub-regions, wherein conditional streamflow statistics were computed based on the joint phases of EA-WR and EA teleconnection indices. On the basis of conditional hydrologic-teleconnection information, we estimated the 50-year return period high- and low-flow events (fitted to a lognormal distribution), thus allowing a simultaneous assessment of the joint effect of changes in the mean and variability of streamflow. Application of this approach for the 24 sub-watersheds clarified the spatial coherence of teleconnection-related impacts on streamflow. Despite the relatively modest sample size, the approach presented here illustrates the potential for identification of conditional streamflow information based on climatic precursors. This diagnostic study is a critical first step in developing seasonal streamflow estimates conditioned upon large-scale climatic state, particularly for multi-objective reservoir and watershed management. Copyright © 2011 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Warm season (June-September) hydroclimatology is a key determinant of freshwater supplies in the Korean Peninsula. In the Han River Basin, nearly three-fourths of annual discharge occurs during the warm season. Given the increased reliance on water supplies for numerous human and ecosystem functions, an integrated view of water supplies within the context of the regional hydroclimate will aid efforts to achieve water resources sustainability. To that end, this diagnostic study investigates several key aspects of the Han River hydrologic regime: (i) the warm season hydroclimatology; (ii) understanding the relative contribution of typhoon and non-typhoon precipitation events to warm season streamflow; and (iii) relationships with large-scale atmospheric teleconnections patterns and the implied seasonal predictability. Statistical analysis of modelled unimpaired streamflow indicates that the East Atlantic-Western Russia (EA-WR) teleconnection pattern modulates the Han River streamflow during the warm season. Furthermore, a linear modelling approach using the EA-WR and East Atlantic (EA) teleconnection indices offers a useful empirical framework for understanding the systematic shifts in streamflow probability distributions. Based on these results, potential use of this information for multi-objective water resources management, environmental flow prescriptions, proactive use of seasonal forecasts, and some open questions are briefly discussed. Copyright © 2010 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Seasonal variations in streamflow and the associated hydrologic extremes impart significant temporal structure to watershed-scale chemical fluxes. Consequently, a careful characterization of the episodic-to-seasonal and longer-term streamflow variations is a first step toward developing a comprehensive view of the temporal dynamics of watershed processes in a changing climate. Here we analyze a nearly two-decade-long streamflow record for the East Bear subwatershed within the Bear Brook Watershed in Maine (BBWM) (USA) to understand the envelope of streamflow variability by season, with a particular focus on the high flow events that have a disproportionately large impact on the biogeochemical processes and fluxes. Interannual and longer-term variations in a number of derived statistical metrics of hydrologic variability are examined. Our analysis shows substantial interannual and longer-term variability in seasonal flow volumes and peak flows. Furthermore, a long, unimpaired streamflow record for the Narraguagus River (a proximate watershed to the BBWM) is examined with a view to understand the relative coherence in hydrologic variability, as well as quantifying the decadal and longer-term hydrologic variations in this region. We find that the streamflow variability in the two watersheds shows similarity in all seasons. A moving window analysis to assess the changing flood potential over time indicates upward trends in the recent decades. Spring season (March-May) flood estimates show a near-monotonic trend over the 1949-2008 record. Finally, empirical relationships between streamflow and large-scale atmospheric circulation patterns highlight the regional and global climatic drivers of hydrologic extremes in this region, including impacts from remnants of Atlantic hurricanes. [ABSTRACT FROM AUTHOR]

Hydrologists have traditionally assumed that the annual maximum flood process at a location is independent and identically distributed. While nonstationarities in the flood process due to land use changes have long been recognized, it is only recently becoming clear that structured interannual, interdecadal, and longer time variations in planetary climate impart the temporal structure to the flood frequency process at flood control system design and operation timescales. The influence of anthropogenic climate change on the nature of floods is also an issue of societal concern. Here we focus on (1) a diagnosis of variations in the frequency of floods that are synchronous with low-frequency climate state and (2) an exploration of limiting flood probability distributions implied by a long simulation of a model of the El Niño/Southern Oscillation. Implications for flood risk analysis are discussed. [ABSTRACT FROM AUTHOR]

• The flow variability within summer season has increased significantly. • Minimum flow trends reveal broad patterns toward increases at the selected quantiles. • Base Flow Index trends show decreases across the majority of the rivers. • Weak to strong linear and nonlinear relationships are found between the indices. Summer flow regime is an important determinant of the health and integrity of riverine ecosystems. In particular, summertime low flows and the range of variability impact the extent and connectivity of habitat, production in and composition of ecosystems, as well as water quality. Four streamflow-based metrics are used in the analysis and assessment of summertime hydrologic variability and trends: Lane Index, UK Institute of Hydrology Index, Base Flow Index, and 7-day Minimum Flow Index. In this study, historical streamflow records at 33 locations in New England (USA) were analyzed to understand the nature of trends as well as the extent of changes, individually and collectively, for the four indices. The main contribution of this paper is to develop a comprehensive characterization of the regional flow regime and trends therein. Two complementary statistical analyses applied in this study are: (a) quantile regression-based estimates of the spatial and temporal patterns of changes in flow indices variability over the past six decades and (b) interrelationship between flow indices based on non-parametric probability density estimation approach. The multi-index regional analysis revealed that flow variability (based on the Lane Index) within the summer season has increased significantly, with 25 out of the 33 streamgages showing increases, of which 12 are highly significant. Similar trends are mirrored in the UK Institute of Hydrology Index based analysis. Base Flow Index trends show decreases across 30 of the 33 streamgages at the median level, and 19 are highly significant. Trends are most pronounced at the upper quartile level, with 21 highly significant. Regional analysis of 7-day Minimum Flow Index reveal broad patterns towards increases at the three selected quantile levels (τ = 0.25 , 0.5 , 0.75) with 29, 22, and 19 streamgages showing increases, of which 13, 10, and 6 are highly significant respectively. There is also diversity in trends across quantiles, wherein 17 locations show increases at all quantile levels, while 22 stations showed increases at the median level. The analysis of interrelationships between the four indices revealed inverse variations between Lane Index and 7-day Minimum Flow, and also a diversity of relationships ranging from weakly to strongly nonlinear. As such, our analysis underscores the importance of the use of multiple indices to fully assess variability and change of relevance to management and policy concerns, such as Maine's water allocation rulemaking. [ABSTRACT FROM AUTHOR]