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  • 1
    Language: English
    In: Journal of Hydrology, 2007, Vol.335(1), pp.109-123
    Description: The prediction of extreme hydrological events in mesoscale catchments has been a main concern in hydrology because of their considerable societal impacts and because of the compelling evidence that anthropogenic activities significantly modify their occurrence likelihood. In this paper, nonlinear generalized models were used to predict extreme runoff characteristics like the specific volume, the frequency of high-flows, and the total drought duration. Explanatory variables included many physiographic, land cover, and climatic characteristics such as mean slope, aspect, elevation, type of geological formations, shares of a given land cover type, and many composed indicators relating antecedent precipitation index and atmospheric circulation patterns. All time-dependent variables were estimated semiannually for each subcatchment. The proposed method was tested in 46 subcatchments belonging to the Upper Neckar River basin covering an area of approximately 4000 km during the period from 1961 to 1993. The results of this study indicated that macro circulation patters derived from either subjective or operational classifications combined with other explanatory variables can be effectively used to predict seasonal extreme runoff characteristics at the mesoscale. Moreover, the results indicated that most runoff characteristics exhibited a distributional element other than normal and that the selection of nonlinear generalized models was an appropriate choice to deal with the heteroscedasticity of model errors.
    Keywords: Statistical Downscaling ; Hydrological Extremes ; Land Use/Cover Change ; Generalized Models ; Heteroscedasticity ; Geography
    ISSN: 0022-1694
    E-ISSN: 1879-2707
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  • 2
    Language: English
    In: Ecological Modelling, 2006, Vol.196(1), pp.45-61
    Description: The analysis of climatic and anthropogenic effects on mesoscale river basins has become one of the main concerns for hydrologists, environmentalists, and planners during the last decade. Many attempts at dealing with this issue have been proposed in the literature. In most studies, however, the main components of the system have been isolated in order to reduce the complexity of the system and its intrinsic uncertainty. In this paper, an attempt to couple two realms of the water system at a mesoscale catchment, namely, the hydrological behaviour of a catchment and the state of the land cover at a given point in time, is presented. Here, instead of using a standard hydrological model, various nonlinear models relating several runoff characteristics with physiographic, land cover, and meteorological factors were linked with a stochastic land use/cover change model. Then, using this integrated model, the magnitude of the effects of the hydrological consequences of land use/cover and climatic changes was assessed in a probabilistic way by a sequential Monte Carlo simulation provided four different scenarios which take into account likely developments of macroclimatic and socioeconomic conditions relevant for a given study area. The proposed methodology was tested in a river basin of approximately 120 km located to the south of Stuttgart, Germany.
    Keywords: Monte Carlo Simulation ; Land Use Change ; Runoff Characteristics ; Climate Change ; Downscaling ; Master Equation ; Environmental Sciences ; Ecology
    ISSN: 0304-3800
    E-ISSN: 1872-7026
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  • 3
    Language: English
    In: Journal of Hydrology, 2005, Vol.303(1), pp.136-151
    Description: Many hydrologic studies report that runoff characteristics such as means or extremes of a given basin may be modified due to climatic and/or land use/cover changes and that the magnitude of these changes largely depends on the geographic location and the scale at which the study is carried out. Identifying the main causes of variability at the mesoscale, however, is a challenging task because of the lack of data regarding the spatial distribution of relevant explanatory variables and, if they exist, because of their high uncertainty. This study proposes a general method to find a robust non-linear model by solving a constrained multiobjective optimization problem whose solution space is composed of all feasible combinations of given explanatory variables. As a result, a model that simultaneously fulfills several criteria such as parsimony, robustness, significance, and overall performance is expected. Furthermore, it does not require assumptions regarding the sampling distributions neither of the parameters nor of the estimators because their -values are estimated by a non-parametric technique. Finally, there is no limitation with respect to the functional form adopted for a given model and its estimator because a generalized reduced gradient algorithm is used for the calibration of its parameters. The proposed method was tested in the upper catchment of the Neckar River (Germany) covering an area of approximately 4000 km . The objective of this study was to detect trends and responses of runoff characteristics in mesoscale catchments due to changes of climatic or land use/cover conditions. In this case, the explained variables are the specific total discharge in summer and winter whereas the explanatory variables comprise several physiographic, land cover and climatic characteristics evaluated for 46 subcatchments during the period 1961–1993. The results of the study indicate a significant gain in performance and robustness of the selected models compared to traditional stepwise methods. The applicability of this method to other disciplines and/or locations is possible.
    Keywords: Runoff ; Multiobjective Optimization ; Cross-Validation ; Permutation Test ; Mallows' Cp' Statistic ; Geography
    ISSN: 0022-1694
    E-ISSN: 1879-2707
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  • 4
    Language: English
    In: Journal of Hydrology, 2010, Vol.392(1), pp.54-69
    Description: Water resources management in mesoscale river basins requires, among other things, reliable predictions on extreme runoff characteristics such as magnitude and frequency of floods and droughts. Hydrologic models are increasingly used for these prediction purposes. Outputs of these models, however, are sensitive to various factors like the spatial representation of hydrologic processes, the parameterization method, and the type of estimator used for calibration. This study aimed to investigate the possible effects of these factors on extreme runoff characteristics derived from simulated streamflow. For this purpose, lumped and distributed versions of the conceptual mesoscale hydrologic model (mHM) were implemented in 22 German basins ranging in size from 58 to 4000 km . The distributed mHM version was, in turn, parameterized with hydrological response units (HRU) and multiscale parameter regionalization (MPR) methods. Free parameters of both model versions were calibrated with three objective functions emphasizing high flows, low flows, and a combination of both. Six extreme runoff characteristics were derived from daily streamflow simulations for winter and summer. Results indicated that the model performance evaluated with both daily streamflow and seasonal runoff characteristics was sensitive to the type of estimator, the spatial discretization, and the parameterization method employed. The lumped version exhibited the highest sensitivity to previous factors and the least performance, whereas the opposite behavior was noticed for the distributed version parameterized with the MPR technique. Furthermore, the efficiency of the model parameterized with MPR were higher than that obtained with the HRU parameterization, in particular, when the model was evaluated in locations not used for calibration.
    Keywords: High and Low Flow ; Parameterization ; Calibration ; Mpr ; Hru ; Hydrologic Model ; Mhm ; Geography
    ISSN: 0022-1694
    E-ISSN: 1879-2707
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  • 5
    Language: English
    In: Journal of Chemical Health & Safety, July 2012, Vol.19(4), pp.52-52
    Keywords: Medicine
    ISSN: 1871-5532
    E-ISSN: 1878-0504
    Source: ScienceDirect Journals (Elsevier)
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  • 6
    Language: English
    In: Climatic Change, 2017, Vol.141(3), p.451(15)
    Description: To access, purchase, authenticate, or subscribe to the full-text of this article, please visit this link: http://dx.doi.org/10.1007/s10584-016-1886-8 Byline: Vimal Mishra (1), Rohini Kumar (2), Harsh L. Shah (1), Luis Samaniego (2), S. Eisner (3), Tao Yang (4) Abstract: Partitioning of precipitation (P) into actual evapotranspiration (ET) and runoff affects a proxy for water availability (P-ET) on land surface. ET accounts for more than 60% of global precipitation and affects both water and energy cycles. We study the changes in precipitation, air temperature, ET, and P-ET in seven large basins under the RCP 2.6 and 8.5 scenarios for the projected future climate. While a majority of studied basins is projected to experience a warmer and wetter climate, uncertainty in precipitation projections remains large in comparison to the temperature projections. Due to high uncertainty in ET, uncertainties in fraction of precipitation that is evaporated (ET/P) and a proxy for available water (P-ET) are also large under the projected future climate. Our assessment showed that under the RCP 8.5 scenario, global climate models are major contributors to uncertainties in ET (P-ET) simulations in the four (six) basins, while uncertainty due to hydrological models is prevailing or comparable in the other three (one) basins. The simulated ET is projected to increase under the warmer and wetter future climates in all the basins and periods under both RCPs. Regarding P-ET, it is projected to increase in five out of seven basins in the End term (2071--2099) under the RCP 8.5 scenario. Precipitation elasticity and temperature sensitivity estimated for ET were found to be positive in all the basins under the RCP 8.5 scenario. In contrast, the temperature sensitivity estimated for (P-ET) was found to be negative for all the basins under the RCP 8.5 scenario, indicating the role of increased energy availability and limited soil moisture. Our results highlight the need for improvements in climate and hydrological models with better representation of soil, vegetation, and cold season processes to reduce uncertainties in the projected ET and P-ET. Author Affiliation: (1) Civil Engineering, Indian Institute of Technology (IIT) Gandhinagar, Gujarat, India (2) UFZ-Helmholtz Centre for Environmental Research, Leipzig, Germany (3) Center for Environmental Systems Research (CESR), Kassel, Germany (4) State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Center for Global Change and Water Cycle, Hohai University, Nanjing, China Article History: Registration Date: 22/12/2016 Received Date: 25/01/2016 Accepted Date: 21/12/2016 Online Date: 03/01/2017 Article note: This article is part of a Special Issue on "Hydrological Model Intercomparison for Climate Impact Assessment" edited by Valentina Krysanova and Fred Hattermann. Electronic supplementary material The online version of this article (doi: 10.1007/s10584-016-1886-8) contains supplementary material, which is available to authorized users.
    Keywords: Water Cycle – Research ; Watersheds – Research
    ISSN: 0165-0009
    E-ISSN: 15731480
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  • 7
    Language: English
    In: Journal of Hydrology: Regional Studies, December 2017, Vol.9, pp.110-110
    Keywords: Geography
    ISSN: 2214-5818
    E-ISSN: 2214-5818
    Source: ScienceDirect Journals (Elsevier)
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  • 8
    In: Journal of Geophysical Research: Atmospheres, 27 January 2014, Vol.119(2), pp.594-613
    Description: Extreme hydrometeorological events often cause severe socioeconomic damage. For water resources assessments and policy recommendations, future extreme hydrometeorological events must be correctly estimated. For this purpose, projections from Regional Climate Models (RCMs) are increasingly used to provide estimates of meteorological variables such as temperature and precipitation. The main objective of this study is to investigate whether a full ensemble or a subset of RCMs reproduces the spatiotemporal variability of observed extremes better than single models. The implications for policy recommendations and impact assessments are then discussed. In particular, the key conditions under which a subset of RCMs could be used for impact assessments are examined. Temperature and precipitation fields of 13 ENSEMBLES RCMs are compared against observations from Germany between 1961 and 2000. Eleven indices characterizing extreme meteorological events were selected for this comparison. The ability of the individual RCMs is estimated based on an overall score and a rejection rate. The former quantifies the biases of these indices. The latter estimates the mean statistical significance quantified by the Wilcoxon rank‐sum test. The performance of all possible combinations of RCMs is investigated. Computationally feasible algorithms for finding the best‐performing subensemble are also presented and evaluated. One of the proposed algorithms is able to find subensembles with the lowest rejection rate, which are useful for either policy recommendations or impact assessments. These subsets of RCMs showed smaller and less significant bias than single RCMs or the full ensemble over several regions. Evaluating extreme temperature and precipitation indices for RCM simulations Studying the effect of ensemble averaging employing different selection methods Ensemble ranking by quantifying an overall rejection rate
    Keywords: Rcm ; Ensemble ; Rejection Rate ; Extremes ; Significance Test ; Stepwise Selection
    ISSN: 2169-897X
    E-ISSN: 2169-8996
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  • 9
    In: Revista de Investigaciones Veterinarias del Perú, 03/20/2013, Vol.12(2)
    Description: La cuenca lechera del sur es la más importante del país debido a su aporte a la producción láctea nacional, por sus proyecciones y por sus posibilidades de desarrollo. Debemos señalar que más del 90% de la producción de la cuenca del sur es producida por Arequipa, siendo la irrigación de Majes (Caylloma) la que produce más del 40% de ella. Esto es importante mencionarlo, porque la información que se va a proporcionar se sitúa principalmente en la irrigación de Majes y se plantea como un componente esencial de la situación sanitaria de las enfermedades de control oficial, y de otras enfermedades importantes, así como de problemas de infertilidad y mastitis.
    Keywords: Veterinary Medicine;
    ISSN: 1682-3419
    E-ISSN: 1609-9117
    Source: CrossRef
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  • 10
    Language: English
    In: Liver International, 2016, Vol.36(7), p.952(2)
    Description: Byline: Luis Ibanez-Samaniego, Rafael Banares ***** No abstract is available for this article. ***** Article Note: See Article on Page 1043
    Keywords: Liver Diseases ; Poisoning
    ISSN: 1478-3223
    ISSN: 14783231
    E-ISSN: 14783231
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