The planetary boundaries framework defines a safe operating space for humanity based on the intrinsic biophysical processes that regulate the stability of the Earth system. Here, we revise and update the planetary boundary framework, with a focus on the underpinning biophysical science, based on targeted input from expert research communities and on more general scientific advances over the past 5 years. Several of the boundaries now have a two-tier approach, reflecting the importance of cross-scale interactions and the regional-level heterogeneity of the processes that underpin the boundaries. Two core boundaries—climate change and biosphere integrity—have been identified, each of which has the potential on its own to drive the Earth system into a new state should they be substantially and persistently transgressed.

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Planetary boundaries: Guiding human development on a changing planet

Cause, conseguenze e strategie di mitigazione Proponiamo il primo di una serie di articoli in cui affronteremo l’attuale problema dei mutamenti climatici. Presentiamo il documento redatto, votato e pubblicato dall’Ipcc - Comitato intergovernativo sui cambiamenti climatici - che illustra la sintesi delle ricerche svolte su questo tema rilevante.

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Climate Change 2007: The Physical Science Basis.

The Intergovernmental Panel on Climate Change (IPCC) Technical Paper Climate Change and Water draws together and evaluates the information in IPCC Assessment and Special Reports concerning the impacts of climate change on hydrological processes and regimes, and on freshwater resources – their availability, quality, use and management. It takes into account current and projected regional key vulnerabilities, prospects for adaptation, and the relationships between climate change mitigation and water. Its objectives are:

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Climate change and water.

An Introduction to MultiAgent Systems.

Climate change 2014 - Synthesis Report

The research described in this article investigates the utility of Artificial Neural Networks (ANNs) for short term forecasting of streamflow. The work explores the capabilities of ANNs and compares the performance of this tool to conventional approaches used to forecast streamflow. Several issues associated with the use of an ANN are examined including the type of input data and the number, and the size of hidden layer(s) to be included in the network. Perceived strengths of ANNs are the capability for representing complex, non-linear relationships as well as being able to model interaction effects. The application of the ANN approach is to a portion of the Winnipeg River system in Northwest Ontario, Canada. Forecasting was conducted on a catchment area of approximately 20 000 km2. using quarter monthly time intervals. The results were most promising. A very close fit was obtained during the calibration (training) phase and the ANNs developed consistently outperformed a conventional model during the verification (testing) phase for all of the four forecast lead-times. The average improvement in the root mean squared error (RMSE) for the 8 years of test data varied from 5 cms in the four time step ahead forecasts to 12.1 cms in the two time step ahead forecasts.

Short Term Streamflow Forecasting Using Artificial Neural Networks

Short term streamflow forecasting using artificial neural networks

During the past three decades, the application of the systems approach to reservoir management and operations has been established as one of the most important advances made in the field of water resources engineering A primary role of systems analysis is to provide an improved basis for decision making It has been concluded that a gap still exists between research studies and the application of a systems approach in practice The objective of this paper is to provide a short review of the mathematical models used in reservoir management and operations, to present conclusions reached by previous state-of-the-art reviews, and to provide two ideas for closing the gap between theory and practice First, a simple simulation-optimization model for reservoir sizing has been presented as an example of systems approach respond to practical needs of water resources engineers The second example illustrates the benefits of knowledge-based technology with regard to single-multipurpose reservoir analysis

Reservoir Systems Analysis: Closing Gap between Theory and Practice

There exists a strong need to explore simulation techniques that not only represent complex dynamic systems in a realistic way but also allow the involvement of end users in model development to increase their confidence in the modeling process. System dynamics, a feedback-based object-oriented simulation ap- proach, is presented for modeling reservoir operations. The increased speed of model development, the trust developed in the model due to user participation, the possibility of group model development, and the effective communication of model results are main strengths of this approach. The ease of model modification in response to changes in the system and the ability to perform sensitivity analysis make this approach more attractive compared with systems analysis techniques for modeling reservoir operations. The proposed approach is applied to the Shellmouth reservoir on the Assiniboine River in Canada. Operating rules are developed for high flow/ flood years to minimize flooding. Alternative operating rules are explored by changing reservoir storage allo- cation and reservoir outflows. Impacts on the flood management capacity of the reservoir are investigated by simulating a gated spillway in addition to an existing unregulated spillway. Sensitivity analysis is performed on the reservoir levels at the start of the flood season and the outflow from the reservoir. The application of systems analysis techniques for reservoir management and operations has been a major focus of research in water resources engineering during the past four decades. Numerous models have been reported in the literature for siz- ing storage capacity and establishing release policy, both at the project planning stage and for real-time operations. Most of the techniques that have been developed or adapted to res- ervoir operations are described in several textbooks, e.g., Loucks et al. (1981) and Mays and Tung (1992). Wurbs and Tibbets (1985), listing over 700 references, produced a state- of-the-art review and an annotated bibliography of systems analysis techniques applied to reservoir operations. Yeh (1985) provided an excellent review on various approaches to reser- voir optimization and simulation and pointed out that, despite considerable progress, research related to reservoir systems analysis has been very slow in finding its way into practice, particularly at the level of the actual operators. He attributes this partly to the fact that operators usually have not been involved in the formulation and development of computer models; partly to the fact that most applications deal with sim- plified reservoir systems and are difficult to adapt to real sys- tems; and partly to institutional constraints. Also, operators and their managers are not comfortable with the degree of abstraction necessary for efficient application of simulation techniques to very complex systems (Russell and Campbell 1996). This literature review suggests that systems analysis has its own place in the field of reservoir management, and simulation is an essential tool for developing a quantitative basis for res- ervoir management decisions (Simonovic 1992). However, there is a strong need to explore simulation tools that can represent the complex systems in a realistic way and where operators can be involved in model development to increase their confidence in the modeling process. A promising alter- native is the system dynamics (SD) approach for modeling 1

Slobodan P. Simonovic

Papers

Short Term Streamflow Forecasting Using Artificial Neural Networks

Short term streamflow forecasting using artificial neural networks

Reservoir Systems Analysis: Closing Gap between Theory and Practice

System dynamics modeling of reservoir operations for flood management

Global water resources modeling with an integrated model of the social-economic-environmental system