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  • 1
    Online Resource
    Online Resource
    Stockholm University Press ; 2012
    In:  Tellus B: Chemical and Physical Meteorology Vol. 64, No. 1 ( 2012-01-01), p. 19005-
    In: Tellus B: Chemical and Physical Meteorology, Stockholm University Press, Vol. 64, No. 1 ( 2012-01-01), p. 19005-
    Type of Medium: Online Resource
    ISSN: 1600-0889 , 0280-6509
    RVK:
    RVK:
    Language: Unknown
    Publisher: Stockholm University Press
    Publication Date: 2012
    detail.hit.zdb_id: 2026992-4
    detail.hit.zdb_id: 246061-0
    SSG: 16,13
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  • 2
    Online Resource
    Online Resource
    Wiley ; 2011
    In:  Hydrological Processes Vol. 25, No. 5 ( 2011-02-28), p. 727-739
    In: Hydrological Processes, Wiley, Vol. 25, No. 5 ( 2011-02-28), p. 727-739
    Abstract: In most studies, trend detection is performed under the assumption of a monotonic trend. However, natural processes and, in particular, hydro‐climatic variables may not conform to this assumption. This study performs a simultaneous evaluation of gradual and abrupt changes in Canadian low streamflows using a modified Mann–Kendall (MK) trend test and a Bayesian multiple change‐point detection model. Statistical analysis, using the whole record of observation (under a monotonic trend assumption), shows that winter and summer low flows are dominated by upward and downward trends, respectively. Overall, about 20% of low flows are characterized by significant trends, where ∼80% of detected significant trends are upward (downward) for winter (summer) season. Change‐point analysis shows that over 50% of low‐flow time series experienced at least one abrupt change in mean or in direction of trend, of which ∼50% occurred in 1980s with a mode in 1987. Analysis of segmented time series based on a common change‐point date indicates a reduced number of significant trends, which is attributed to first, the change in nonstationarity behaviour of low flows leading to less trend‐type changes in the last few decades; and second, the false detection of trends when the sample data are characterized by shifts in mean. Depending on whether the monotonic trend assumption holds, the on‐site and regional interpretation of results may vary (e.g. winter low flow) or even lead to contradictory conclusions (e.g. summer low flow). Trend analysis of last two decades of streamflows shows that (1) winter low flows are increasing in eastern Canada and southern British Columbia, whereas they are decreasing in western Canada; (2) summer low flows are increasing in central Canada, southern British Columbia and Newfoundland, whereas they are decreasing in Yukon and northern British Columbia and also in eastern Ontario and Quebec. Copyright © 2010 John Wiley & Sons, Ltd.
    Type of Medium: Online Resource
    ISSN: 0885-6087 , 1099-1085
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2011
    detail.hit.zdb_id: 1479953-4
    SSG: 14
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  • 3
    Online Resource
    Online Resource
    American Geophysical Union (AGU) ; 2004
    In:  Water Resources Research Vol. 40, No. 1 ( 2004-01)
    In: Water Resources Research, American Geophysical Union (AGU), Vol. 40, No. 1 ( 2004-01)
    Type of Medium: Online Resource
    ISSN: 0043-1397
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2004
    detail.hit.zdb_id: 2029553-4
    detail.hit.zdb_id: 5564-5
    SSG: 13
    SSG: 14
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  • 4
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2017
    In:  Scientific Reports Vol. 7, No. 1 ( 2017-06-07)
    In: Scientific Reports, Springer Science and Business Media LLC, Vol. 7, No. 1 ( 2017-06-07)
    Abstract: Surface Temperature (ST) over India has increased by ~0.055 K/decade during 1860–2005 and follows the global warming trend. Here, the natural and external forcings (e.g., natural and anthropogenic) responsible for ST variability are studied from Coupled Model Inter-comparison phase 5 (CMIP5) models during the 20 th century and projections during the 21 st century along with seasonal variability. Greenhouse Gases (GHG) and Land Use (LU) are the major factors that gave rise to warming during the 20 th century. Anthropogenic Aerosols (AA) have slowed down the warming rate. The CMIP5 projection over India shows a sharp increase in ST under Representative Concentration Pathways (RCP) 8.5 where it reaches a maximum of 5 K by the end of the 21 st century. Under RCP2.6 emission scenarios, ST increases up to the year 2050 and decreases afterwards. The seasonal variability of ST during the 21 st century shows significant increase during summer. Analysis of rare heat and cold events for 2080–2099 relative to a base period of 1986–2006 under RCP8.5 scenarios reveals that both are likely to increase substantially. However, by controlling the regional AA and LU change in India, a reduction in further warming over India region might be achieved.
    Type of Medium: Online Resource
    ISSN: 2045-2322
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2017
    detail.hit.zdb_id: 2615211-3
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  • 5
    Online Resource
    Online Resource
    Informa UK Limited ; 2004
    In:  Hydrological Sciences Journal Vol. 49, No. 3 ( 2004-06)
    In: Hydrological Sciences Journal, Informa UK Limited, Vol. 49, No. 3 ( 2004-06)
    Type of Medium: Online Resource
    ISSN: 0262-6667 , 2150-3435
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2004
    detail.hit.zdb_id: 2180448-5
    SSG: 14
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  • 6
    In: Water Resources Research, American Geophysical Union (AGU), Vol. 45, No. 8 ( 2009-08)
    Type of Medium: Online Resource
    ISSN: 0043-1397
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2009
    detail.hit.zdb_id: 2029553-4
    detail.hit.zdb_id: 5564-5
    SSG: 13
    SSG: 14
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  • 7
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2012
    In:  Water Resources Management Vol. 26, No. 14 ( 2012-11), p. 4259-4280
    In: Water Resources Management, Springer Science and Business Media LLC, Vol. 26, No. 14 ( 2012-11), p. 4259-4280
    Type of Medium: Online Resource
    ISSN: 0920-4741 , 1573-1650
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2012
    detail.hit.zdb_id: 2016360-5
    SSG: 14
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  • 8
    Online Resource
    Online Resource
    Wiley ; 2020
    In:  International Journal of Climatology Vol. 40, No. 4 ( 2020-03-30), p. 2373-2392
    In: International Journal of Climatology, Wiley, Vol. 40, No. 4 ( 2020-03-30), p. 2373-2392
    Abstract: The development of nonstationary frequency analysis models is gaining popularity in the field of hydro‐climatology. Such models account for nonstationarities related to climate change and climate variability but at the price of added complexity. It has been debated if such models are worth developing considering the increase in uncertainty inherent to more complex models. However, the uncertainty associated to nonstationary models is rarely studied. The objective of this article is to compare the uncertainties in stationary and nonstationary models based on objective criteria. The study is based on observed rainfall data in the United Arab Emirates (UAE) where strong nonstationarities were observed. In this study, a nonstationary frequency analysis introducing covariates into the distribution parameters was carried out for total and maximum annual rainfalls observed in the UAE. The generalized extreme value (GEV) distribution was used to model annual maximum rainfalls and the gamma (G) distribution was used to model total annual rainfalls. A number of nonstationary models, using time and climate indices as covariates, were developed and compared to classical stationary frequency analysis models. Two climate oscillation patterns having strong impacts on precipitation in the UAE were selected: the Oceanic Niño Index and the Northern Oscillation Index. Results indicate that the inclusion of a climate oscillation index generally improves the fit of the models to the observed data and the inclusion of two covariates generally provides the overall best fits. Uncertainties of estimated quantiles were assessed with confidence intervals (CIs) computed with the parametric bootstrap method. Results show that for the small sample sizes in this study, the width of the CIs can be very large for extreme nonexceedance probabilities and for the most extreme values of the climate index covariates. The weaknesses of nonstationary models revealed by the bootstrap uncertainties are discussed and words of caution are formulated.
    Type of Medium: Online Resource
    ISSN: 0899-8418 , 1097-0088
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2020
    detail.hit.zdb_id: 1491204-1
    SSG: 14
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  • 9
    Online Resource
    Online Resource
    Wiley ; 2019
    In:  International Journal of Climatology Vol. 39, No. 4 ( 2019-03-30), p. 2306-2323
    In: International Journal of Climatology, Wiley, Vol. 39, No. 4 ( 2019-03-30), p. 2306-2323
    Abstract: Rainfall intensity‐duration‐frequency (IDF) curves are commonly used for the design of water resources infrastructure. Numerous studies reported non‐stationarity in meteorological time series. Neglecting to incorporate non‐stationarities in hydrological models may lead to inaccurate results. The present work focuses on the development of a general methodology that copes with non‐stationarities that may exist in rainfall, by making the parameters of the IDF relationship dependent on the covariates of time and climate oscillations. In the recent literature, non‐stationary models are generally fit on data series of specific durations. In the approach proposed here, a single model with a separate functional relation with the return period and the rainfall duration is instead defined. This model has the advantage of being simpler and extending the effective sample size. Its parameters are estimated with the maximum composite likelihood method. Two sites in Ontario, Canada and one site in California, USA, exhibiting non‐stationary behaviours are used as case studies to illustrate the proposed method. For these case studies, the time and the climate indices Atlantic Multi‐decadal Oscillation (AMO) and Western Hemisphere Warm Pool (WHWP) for the stations in Canada, and the time and the climate indices Southern Oscillation Index (SOI) and Pacific Decadal Oscillation (PDO) for the stations in United States are used as covariates. The Gumbel and the generalized extreme value distributions are used as the time‐dependent functions in the numerator of the general IDF relationship. Results show that the non‐stationary framework for IDF modelling provides a better fit to the data than its stationary counterpart according to the Akaike information criterion. Results indicate also that the proposed generalized approach is more robust than the common approach especially for stations with short rainfall records (e.g., R 2 of 0.98 compared to 0.69 for duration of 30 min and a sample size of 27 years).
    Type of Medium: Online Resource
    ISSN: 0899-8418 , 1097-0088
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2019
    detail.hit.zdb_id: 1491204-1
    SSG: 14
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  • 10
    Online Resource
    Online Resource
    Wiley ; 2014
    In:  Hydrological Processes Vol. 28, No. 13 ( 2014-06-30), p. 4057-4066
    In: Hydrological Processes, Wiley, Vol. 28, No. 13 ( 2014-06-30), p. 4057-4066
    Abstract: The ordinary least square method (OLS) has been the most frequently used least square method in hydrological data analysis. Its computational algorithm is simple, and the error analysis is also simple and clear. However, the primary assumption of the OLS method, which states that the dependent variable is the only error‐contaminated variable and all other variables are error free, is often violated in hydrological data analyses. Recently, a matrix algorithm using the singular value decomposition for the total least square (TLS) method has been developed and used in data analyses as errors‐in‐variables model where several variables could be contaminated with observational errors. In our study, the algorithm of the TLS is introduced in the evaluation of rating curves between the flow discharge and the water level. Then, the TLS algorithm is applied to real data set for rating curves. The evaluated TLS rating curves are compared with the OLS rating curves, and the result indicates that the TLS rating curve and the OLS rating curve are in good agreement. The TLS and OLS rating curves are discussed about their algorithms and error terms in the study. Copyright © 2013 John Wiley & Sons, Ltd.
    Type of Medium: Online Resource
    ISSN: 0885-6087 , 1099-1085
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2014
    detail.hit.zdb_id: 1479953-4
    SSG: 14
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