Impatti, adattamento e vulnerabilita Le cause e le responsabilita dei cambiamenti climatici sono state trattate sul numero di ottobre della rivista Cda. Approfondiamo l’argomento presentando il documento: “Cambiamenti climatici 2007: impatti, adattamento e vulnerabilita” votato ad aprile 2007 dal secondo gruppo di lavoro del Comitato Intergovernativo sui Cambiamenti Climatici (Intergovernmental Panel on Climate Change). Si tratta del secondo di tre documenti che compongono il quarto rapporto sui cambiamenti climatici.

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Climate Change 2007: Impacts, Adaptation and Vulnerability.

A review of drought concepts

The talk with present the key results of the IPCC Working Group III 5th assessment report. Concluding four years of intense scientific collaboration by hundreds of authors from around the world, the report responds to the request of the world's governments for a comprehensive, objective and policy neutral assessment of the current scientific knowledge on mitigating climate change. The report has been extensively reviewed by experts and governments to ensure quality and comprehensiveness.

Climate change 2014 - Mitigation of climate change

Foreword 1. Introduction 2. Runoff, erosion and delivery to the coastal ocean 3. Temporal variations 4. Human impacts Appendices. Global River Database: Appendix A: North and Central America Appendix B: South America Appendix C: Europe Appendix D: Africa Appendix E: Eurasia Appendix F: Asia Appendix G: Oceania References Index.

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River Discharge to the Coastal Ocean: A Global Synthesis

Over the past 15 years, artificial neural networks (ANNs) have been used increasingly for prediction and forecasting in water resources and environmental engineering. However, despite this high level of research activity, methods for developing ANN models are not yet well established. In this paper, the steps in the development of ANN models are outlined and taxonomies of approaches are introduced for each of these steps. In order to obtain a snapshot of current practice, ANN development methods are assessed based on these taxonomies for 210 journal papers that were published from 1999 to 2007 and focus on the prediction of water resource variables in river systems. The results obtained indicate that the vast majority of studies focus on flow prediction, with very few applications to water quality. Methods used for determining model inputs, appropriate data subsets and the best model structure are generally obtained in an ad-hoc fashion and require further attention. Although multilayer perceptrons are still the most popular model architecture, other model architectures are also used extensively. In relation to model calibration, gradient based methods are used almost exclusively. In conclusion, despite a significant amount of research activity on the use of ANNs for prediction and forecasting of water resources variables in river systems, little of this is focused on methodological issues. Consequently, there is still a need for the development of robust ANN model development approaches.

Review: Methods used for the development of neural networks for the prediction of water resource variables in river systems: Current status and future directions

Droughts are destructive climatic extreme events that may cause significant damage both in natural environments and in human lives. Drought forecasting plays an important role in the control and ma...

Nonlinear model for drought forecasting based on a conjunction of wavelet transforms and neural networks

Droughts cause severe damage in terms of both natural environments and human lives, and hydrologists and water resources managers are concerned with estimating the relative frequencies of these events. Univariate parametric methods for frequency analysis may not reveal significant relationships among drought characteristics. Alternatively, nonparametric methods provide local estimates of the univariate and multivariate density function by using weighted moving averages of the data in a small neighborhood around the point of estimation and opposed to parametric methods. A methodology for estimating the return period of droughts using a nonparametric kernel estimator is presented in order to examine the univariate as well as the bivariate behavior of droughts. After evaluating and validating a nonparametric kernel estimator, a drought frequency analysis is conducted to estimate the return periods of droughts for the Conchos River Basin in Mexico. The results show that, for the univariate analysis, the retur...

Nonparametric Approach for Estimating Return Periods of Droughts in Arid Regions

Assessment of drought hazard, vulnerability, and risk: a case study for administrative districts in South Korea.

The temporal and spatial characteristics of droughts are investigated to provide a framework for sustainable water resources management in a semi-arid region Using the Palmer Drought Severity Index (PDSI) as an indicator of drought severity, the characteristics of droughts are examined in the Conchos River Basin in Mexico This basin is important to both the United States and Mexico, because the Conchos River supplies approximately 80 percent of the flows of the Lower Bravo/Grande River above the binational reservoirs of Amistad and Falcon The temporal and spatial characteristics of the PDSI are used to develop a drought intensity—areal extent—frequency curve that can assess the severity of a regional drought in the basin The analysis of the PDSI suggests that the Conchos River Basin had a severe drought in the 1990s, which the basin has not experienced before Based on this analysis, the recent drought that occurred in the 1990s has an associated return period of about 80 to 100 years over th

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Frequency and spatial characteristics of droughts in the Conchos River Basin, Mexico

A drought is usually represented by duration and severity, and may last several months or years. Multidimensional characteristics of a drought make univariate analysis unable to reveal the significant relationship among drought properties. Furthermore, historical records tend to be too short to fully evaluate drought characteristics. A practical method was proposed in this study to estimate the bivariate return period of droughts based on the use of synthetic data to overcome the above considerations. The bivariate return period of droughts is dependent on the drought interarrival time and the joint distribution of drought properties. A nonparametric method was employed in this study to estimate the joint distribution of drought properties. The historical droughts in the Conchos River Basin, Mexico were evaluated based on their return period estimated by the proposed method. The proposed method allowed a better understanding of the joint probabilistic behavior of droughts beyond the limitation of the univ...

Tae-Woong Kim

Papers

Nonlinear model for drought forecasting based on a conjunction of wavelet transforms and neural networks

Nonparametric Approach for Estimating Return Periods of Droughts in Arid Regions

Assessment of drought hazard, vulnerability, and risk: a case study for administrative districts in South Korea.

Frequency and spatial characteristics of droughts in the Conchos River Basin, Mexico

Nonparametric Approach for Bivariate Drought Characterization Using Palmer Drought Index