Hydraulic, hydrologic and water resources engineers have been concerned for a long time about failure phenomena. One of the major concerns is the definition of a failure event E, of its probability of occurrence PtE), and of the complementary notion of reliability. However, as the stochastic aspects of hydraulics and water resources engineering were developed, words such as "failure," "reliability," and "risk" took on different meanings for different specialists. For example, "risk" is defined in a Bayesian framework as the expected loss resulting from a precisely defined failure event, while according to the practice of stochastic hydraulics it is the probability of occurrence of a failure event. The need to standardize the various concepts and operational definitions generated numerous exciting discussions between the co-editors of this book during 1983-84 when L. Duckstein, under sponsorship of the Alexander von Humboldt Foundation (FRG), was working with E. Plate at the Institute of Hydrology and Water Resources of the University of Karlsruhe. After consulting with the Scientific Affairs Division of NATO, an organizing committee was formed. This comittee - J. Bernier (France), M. Benedini (Italy), S. Sorooshian (U. S. A. ), and co-directors L. Duckstein (U. S. A. ) and E. J. Plate (F. R. G. ) -- brought into being this NATO Advanced Study Institute (ASI). Precisely stated, the purpose of this ASI was to present a tutorial overview of existing work in the broad area of reliability while also pointing out topics for further development."

The purpose of this paper is to present a methodology for estimating space-time stochastic properties of local climatic factors reflecting global climate change. Specifically, daily precipitation amount and daily mean temperature are considered and illustrated with application to the state of Nebraska, U. S. A. Furthermore, a drought index with and without global climate change is examined. The magnitude and consequences of regional response to anticipated climatic changes are uncertain (Houghton et al., 1990). Typical questions to be answered are: can time series of hydrological events or 10cal climatic variables such as daily temperature be conditioned in scenarios of future climate change and if so, how can this be utilized ? Can extreme historical drought events be reproduced by a stochastic hydroc1imatological model ? Can such a model be used with General Circu1ation Model (GCM) outputs to evaluate the regional/local effects of climate change scenarios? The approach presented in this paper is an extension of the usual analysis of regional hydrometeorological impacts of climate change: we propose to examine time series of GCM produced daily atmospheric circulation patterns (CP), thought to be relatively accurate GCM output to estimate local climatic factors. The paper is organized as follows. First, daily CPs are classified and analyzed statistically, first for historical and then for GCM produced data. Next, the height of the 500 hPa pressure field is introduced as an additional physically relevant variable influencing local climatic factors within each CP type."

Ambitious as the enterprise was, and as demanding as the planning effort promised to be, we set out to organize the IX International Conference on Multiple criteria Decision Making (MCDM) which took place in Fairfax, Virginia, on August 5-8, 1990. We knew it was ambitious because the number of participants expected to attend the conference would approach 160, larger than that of earlier conferences, and because it would include a sizable contingent of 39 participants from the soviet union and Eastern Europe, possibly the largest yet. In many ways, it may be appropriate to say, this international conference presented a microcosm of peoples and new ideas that reflected the extraordinary events that were to take place in Europe and other parts of the world during that summer of 1990. with the theme: "Multiple criteria Decision Making and support at the Interface of Industry, Business and Government" we wanted to focus on new analytical methodologies and management tools, quantitative and qualitative evaluation of decision techniques, the design of experiments to test existing and proposed methods, and the experience gained in the application of these MCDM methods and tools to real-world problems during the last 10-15 years. Many analytical, behavioral, and technological advances are to be made, we feel, at the interface of MCDM Theory, the Behavioral Sciences, operations Research, Systems Engineering, Decision Theory, Mathematical Sciences, and Information Technology. viii The current proliferation of computer-based decision tools offers new challenges and opportunities.

The purpose of this paper is to present a methodology for estimating space-time stochastic properties of local climatic factors reflecting global climate change. Specifically, daily precipitation amount and daily mean temperature are considered and illustrated with application to the state of Nebraska, U. S. A. Furthermore, a drought index with and without global climate change is examined. The magnitude and consequences of regional response to anticipated climatic changes are uncertain (Houghton et al., 1990). Typical questions to be answered are: can time series of hydrological events or 10cal climatic variables such as daily temperature be conditioned in scenarios of future climate change and if so, how can this be utilized ? Can extreme historical drought events be reproduced by a stochastic hydroc1imatological model ? Can such a model be used with General Circu1ation Model (GCM) outputs to evaluate the regional/local effects of climate change scenarios? The approach presented in this paper is an extension of the usual analysis of regional hydrometeorological impacts of climate change: we propose to examine time series of GCM produced daily atmospheric circulation patterns (CP), thought to be relatively accurate GCM output to estimate local climatic factors. The paper is organized as follows. First, daily CPs are classified and analyzed statistically, first for historical and then for GCM produced data. Next, the height of the 500 hPa pressure field is introduced as an additional physically relevant variable influencing local climatic factors within each CP type."