Changes in flood events inferred from centennial length streamflow data records

The final publication is available at Elsevier via https://dx.doi.org/10.1016/j.advwatres.2018.08.017 © 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/This research examines ways that climate change may alter the risk of flooding in cold regions focusing on changes in the flood regimes and changes and shifts in the dominant flood generating processes at 27 natural watersheds across Canada and the northern United States. Changes in flood regimes are examined using data from long term hydrometric reference streamflow gauging stations whose data record spans the past 100 years; stations included are considered to have good quality data and were screened to avoid the influences of regulation, diversions, or land use change. Changes in flood regimes are complex and require different approaches to properly characterize the variety of changes that have occurred and are likely to occur in the future. Peaks over threshold data are used to explore changes to the magnitude, timing, volume and duration of threshold exceedences. Circular statistics are used to explore changes in the nature of the flood regime based on changes in the timing and regularity of flood threshold exceedences. All flood regimes show an increased number of threshold exceeding events. An increased prevalence of rainfall flood responses is observed as flood events occur more often during the rainfall dominated portion of the seasonal cycle resulting in a shift for nival regime stations to a more mixed regime and for mixed regime stations towards a more pluvial regime. The results support viewing hydrologic regime as a continuum from nival to pluvial with several stations shifting towards the pluvial end.Natural Sciences and Engineering Research Council of Canada ["NETGP 451456"

Automatic feature selection and weighting for the formation of homogeneous groups for regional IDF estimation

The final publication is available at Elsevier via https://doi.org/10.1016/j.jhydrol.2019.05.015. © 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/The intensity-duration frequency (IDF) curve has been used as an effective tool to quantify the risk associated with the impact of extreme rainfall on civil infrastructure. However, recent changes in the rainfall climatology caused by climate change and urbanization have made estimates in the stationary environment provided by the traditional regional IDF approach increasingly inaccurate. This inaccuracy is mainly caused by the lack of consideration for the temporal and spatial differences in the selection of similarity indicators (attributes that are used to measure similarity of extreme rainfall patterns among different stations), resulting in ineffective formation of homogeneous groups (group of stations that share similar extreme rainfall patterns) at various regions. To consider the temporal differences of similarity indicators, including meteorological factors, topographic features and urban impact indicators, a three-layer design is proposed based on the three stages in extreme rainfall formation: cloud formation, rainfall generation and change of rainfall intensity over an urban surface. During the process, the impacts from climate change and urbanization on extreme rainfall patterns are considered through the inclusion of potential features that relate to the rainfall mechanism at each layer. The spatial differences of similarity indicators for Homogeneous Group Formation (HGF) at various regions is resolved by using an automatic feature selection and weighting algorithm, specifically the hybrid searching algorithm of Tabu Search, Lagrange Multiplier and Fuzzy C-means clustering, to select the optimal combination of features for HGF based on the uncertainty in the regional estimates of the rainfall quantiles for a specific site. The proposed methodology fills the gap of including the urbanization impacts on the extreme rainfall patterns during HGF process and challenges the traditional assumption that the same set of features can be equally effective in generating the optimal homogeneous group in regions with different geographic and meteorological characteristics.This work was supported by the Natural Science and Engineering Research Council (NSERC) Canadian FloodNet (Grant number: NETGP 451456). The authors are grateful to Dr. Nadav Peleg and two anonymous reviewers whose comments and suggestions contributed to the improvement of the manuscript

Time-varying nonstationary multivariate risk analysis using a dynamic Bayesian copula

A time-varying risk analysis is proposed for an adaptive design framework in nonstationary conditions arising from climate change. A Bayesian, dynamic conditional copula is developed for modeling the time-varying dependence structure between mixed continuous and discrete multiattributes of multidimensional hydrometeorological phenomena. Joint Bayesian inference is carried out to fit the marginals and copula in an illustrative example using an adaptive, Gibbs Markov Chain Monte Carlo (MCMC) sampler. Posterior mean estimates and credible intervals are provided for the model parameters and the Deviance Information Criterion (DIC) is used to select the model that best captures different forms of nonstationarity over time. This study also introduces a fully Bayesian, time-varying joint return period for multivariate time-dependent risk analysis in nonstationary environments.We thank the associate editor and three anonymous reviewers whose suggestions helped improve the paper. We acknowledge the CMIP5 climate coupled modelling groups, for producing and making their model outputs available, the U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison (PCMDI), which provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. The CMIP5 model outputs used in the present study are available from http://cmip-pcmdi.llnl.gov/cmip5/data_portal.html. We also thank the Iran Meteorological Organization (IRIMO) for providing rainfall data recorded at the Tehran synoptic station. Funding support was provided by the Natural Sciences and Engineering Research Council (NSERC) of Canada

Reference hydrologic networks II: using reference hydrologic networks to assess climate-driven changes in streamflow

Reference hydrologic networks (RHNs) can play an important role in monitoring for changes in the hydrological regime related to climate variation and change. Currently, the literature concerning hydrological response to climate variations is complex and confounded by the combinations of many methods of analysis, wide variations in hydrology, and the inclusion of data series that include changes in land use, storage regulation and water use in addition to those of climate. Three case studies that illustrate a variety of approaches to the analysis of data from RHNs are presented and used, together with a summary of studies from the literature, to develop approaches for the investigation of changes in the hydrological regime at a continental or global scale, particularly for international comparison. We present recommendations for an analysis framework and the next steps to advance such an initiative. There is a particular focus on the desirability of establishing standardized procedures and methodologies for both the creation of new national RHNs and the systematic analysis of data derived from a collection of RHNs

A nationwide regional flood frequency analysis at ungauged sites using ROI/GLS with copulas and super regions

The final publication is available at Elsevier via https://dx.doi.org/10.1016/j.jhydrol.2018.10.011 © 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/Region of influence is a common approach to estimate runoff information at ungauged locations. To estimate flood quantiles from annual maximum discharges, the Generalized Least Squares (GLS) framework has been recommended to account for unequal sampling variance and intersite correlation, which requires a proper evaluation of the sampling covariance structure. Since some jurisdictions do not have clear guidelines to perform this evaluation, a general procedure using copulas and a nonparametric intersite correlation model is investigated to estimate sampling covariance structure in situations where no common at-site distribution is imposed or when some paired sites do not have common periods of record. The investigated methodology is applied on 771 sites in Canada. The Normal copula is verified to be an adequate model that better fit paired observations than other types of extreme copulas. A sensitivity analysis is carried out to evaluate the impact of either ignoring, or considering a simpler form of, intersite correlation. Additionally, super regions are defined based on drainage area and mean annual precipitation to improve the calibration of pooling groups across large territories and a wide range of climate conditions. Performance criteria based on cross-validation revealed that using super regions and a combination of geographic distance and similarity between catchment descriptors improves the calibration of the pooling groups by providing more accurate estimates.Natural Sciences and Engineering Research Council of Canada [NETGP 451456 – 13

Reference hydrologic networks I: the status and potential future directions of national reference hydrologic networks for detecting trends

Identifying climate-driven trends in river flows on a global basis is hampered by a lack of long, quality time series data for rivers with relatively undisturbed regimes. This is a global problem compounded by the lack of support for essential long-term monitoring. Experience demonstrates that, with clear strategic objectives, and the support of sponsoring organizations, reference hydrologic networks can constitute an exceptionally valuable data source to effectively identify, quantify and interpret hydrological change—the speed and magnitude of which is expected to a be a primary driver of water management and flood alleviation strategies through the future—and for additional applications. Reference hydrologic networks have been developed in many countries in the past few decades. These collections of streamflow gauging stations, that are maintained and operated with the intention of observing how the hydrology of watersheds responds to variations in climate, are described. The status of networks under development is summarized. We suggest a plan of actions to make more effective use of this collection of networks

Climate-driven variability in the occurrence of major floods across North America and Europe

Concern over the potential impact of anthropogenic climate change on flooding has led to a proliferation of studies examining past flood trends. Many studies have analysed annual-maximum flow trends but few have quantified changes in major (25–100 year return period) floods, i.e. those that have the greatest societal impacts. Existing major-flood studies used a limited number of very large catchments affected to varying degrees by alterations such as reservoirs and urbanisation. In the current study, trends in major-flood occurrence from 1961 to 2010 and from 1931 to 2010 were assessed using a very large dataset (>1200 gauges) of diverse catchments from North America and Europe; only minimally altered catchments were used, to focus on climate-driven changes rather than changes due to catchment alterations. Trend testing of major floods was based on counting the number of exceedances of a given flood threshold within a group of gauges. Evidence for significant trends varied between groups of gauges that were defined by catchment size, location, climate, flood threshold and period of record, indicating that generalizations about flood trends across large domains or a diversity of catchment types are ungrounded. Overall, the number of significant trends in major-flood occurrence across North America and Europe was approximately the number expected due to chance alone. Changes over time in the occurrence of major floods were dominated by multidecadal variability rather than by long-term trends. There were more than three times as many significant relationships between major-flood occurrence and the Atlantic Multidecadal Oscillation than significant long-term trends

Climate driven trends in historical extreme low streamflows on four continents

Understanding temporal trends in low streamflows is important for water management and ecosystems. This work focuses on trends in the occurrence rate of extreme low-flow events (5- to 100-year return periods) for pooled groups of stations. We use data from 1,184 minimally altered catchments in Europe, North and South America, and Australia to discern historical climate-driven trends in extreme low flows (1976–2015 and 1946–2015). The understanding of low streamflows is complicated by different hydrological regimes in cold, transitional, and warm regions. We use a novel classification to define low-flow regimes using air temperature and monthly low-flow frequency. Trends in the annual occurrence rate of extreme low-flow events (proportion of pooled stations each year) were assessed for each regime. Most regimes on multiple continents did not have significant (p < 0.05) trends in the occurrence rate of extreme low streamflows from 1976 to 2015; however, occurrence rates for the cold-season low-flow regime in North America were found to be significantly decreasing for low return-period events. In contrast, there were statistically significant increases for this period in warm regions of NA which were associated with the variation in the Pacific Decadal Oscillation. Significant decreases in extreme low-flow occurrence rates were dominant from 1946 to 2015 in Europe and NA for both cold- and warm-season low-flow regimes; there were also some non-significant trends. The difference in the results between the shorter (40-year) and longer (70-year) records and between low-flow regimes highlights the complexities of low-flow response to changing climatic conditions

Genome-Wide Association Studies of Cognitive and Motor Progression in Parkinson's Disease.

BACKGROUND: There are currently no treatments that stop or slow the progression of Parkinson's disease (PD). Case-control genome-wide association studies have identified variants associated with disease risk, but not progression. The objective of the current study was to identify genetic variants associated with PD progression. METHODS: We analyzed 3 large longitudinal cohorts: Tracking Parkinson's, Oxford Discovery, and the Parkinson's Progression Markers Initiative. We included clinical data for 3364 patients with 12,144 observations (mean follow-up 4.2 years). We used a new method in PD, following a similar approach in Huntington's disease, in which we combined multiple assessments using a principal components analysis to derive scores for composite, motor, and cognitive progression. These scores were analyzed in linear regression in genome-wide association studies. We also performed a targeted analysis of the 90 PD risk loci from the latest case-control meta-analysis. RESULTS: There was no overlap between variants associated with PD risk, from case-control studies, and PD age at onset versus PD progression. The APOE ε4 tagging variant, rs429358, was significantly associated with composite and cognitive progression in PD. Conditional analysis revealed several independent signals in the APOE locus for cognitive progression. No single variants were associated with motor progression. However, in gene-based analysis, ATP8B2, a phospholipid transporter related to vesicle formation, was nominally associated with motor progression (P = 5.3 × 10-6 ). CONCLUSIONS: We provide early evidence that this new method in PD improves measurement of symptom progression. We show that the APOE ε4 allele drives progressive cognitive impairment in PD. Replication of this method and results in independent cohorts are needed. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.Funding sources: Parkinson’s U