Despite recent advances in authoring systems and tools, creating multimedia presentations remains a labor-intensive process. This paper describes a system for automatically constructing structured multimedia documents from live presentations. The automatically produced documents contain synchronized and edited audio, video, images, and text. Two essential problems, synchronization of captured data and automatic editing, are identified and solved.

Abstract. Global hydroclimatic conditions have been substantially altered over the past century by anthropogenic influences that arise from the warming global climate and from local/regional anthropogenic disturbances. Traditionally, studies have used coupling of multiple models to understand how land-surface water fluxes vary due to changes in global climatic patterns and local land-use changes. We argue that because the basis of the Budyko framework relies on the supply and demand concept, the framework could be effectively adapted and extended to quantify the role of drivers – both changing climate and local human disturbances – in altering the land-surface response across the globe. We review the Budyko framework, along with these potential extensions, with the intent of furthering the applicability of the framework to emerging hydrologic questions. Challenges in extending the Budyko framework over various spatio-temporal scales and the use of global datasets to evaluate the water balance at these various scales are also discussed.

Weather regime based stochastic weather generators (WR‐SWGs) have recently been proposed as a tool to better understand multi‐sector vulnerability to deeply uncertain climate change. WR‐SWGs can distinguish and simulate different types of climate change that have varying degrees of uncertainty in future projections, including thermodynamic changes (e.g., rising temperatures, Clausius‐Clapeyron scaling of extreme precipitation) and dynamic changes (e.g., shifting circulation and storm tracks). These models require the accurate identification of WRs that are representative of both historical and plausible future patterns of atmospheric circulation, while preserving the complex space–time variability of weather processes. This study proposes a novel framework to identify such WRs based on WR‐SWG performance over a broad geographic area and applies this framework to a case study in California. We test two components of WR‐SWG design, including the method used for WR identification (Hidden Markov Models (HMMs) vs. K‐means clustering) and the number of WRs. For different combinations of these components, we assess performance of a multi‐site WR‐SWG using 14 metrics across 13 major California river basins during the cold season. Results show that performance is best using a small number of WRs (4–5) identified using an HMM. We then juxtapose the number of WRs selected based on WR‐SWG performance against the number of regimes identified using metastability analysis of atmospheric fields. Results show strong agreement in the number of regimes between the two approaches, suggesting that the use of metastable regimes could inform WR‐SWG design. We conclude with a discussion of the potential to expand this framework for additional WR‐SWG design parameters and spatial scales.

Reliable operation of physical infrastructures such as reservoirs, dikes, nuclear power plants positioned along a river network depends on monitoring riverine conditions and infrastructure interdependency with the river network, especially during hydrologic extremes. Developing this cascading interdependency between the riverine conditions and infrastructures for a large watershed is challenging, as conventional tools (e.g., watershed delineation) do not provide the relative topographic information on infrastructures along the river network. Here, we present a generic geo-processing tool that systematically combines three geospatial layers: topographic information from the National Hydrographic Dataset (NHDPlusV2), streamgages from the USGS National Water Information System, and reservoirs from the National Inventory of Dams, to develop the interdependency between reservoirs and streamgages along the river network for upper and lower Colorado River Basin (CRB) resulting in River and Infrastructure Connectivity Network (RICON) that shows the said interdependency as a concise edge list for the CRB. Another contribution of this study is an algorithm for developing the cascading interdependency between infrastructure and riverine networks to support their management and operation.

This paper presents a new approach for constructing libraries for building processing-intensive multimedia software. Such software is currently constructed either by using high-level libraries or by writing it "from scratch" using C. We have found that the first approach produces inefficient code, while the second approach is time-consuming and produces complex code that is difficult to maintain or reuse. We therefore designed and implemented Da11 a set of reusable, high-performance primitives and abstractions that are at an intermediate level of abstraction between C and conventional libraries. By decomposing common multimedia data types and operations into thin abstractions and primitives, programs written using Dali achieve performance competitive with hand-tuned C code, but are shorter and more reusable. Furthermore, Dali programs can employ optimizations that are difficult to exploit in C (because the code is so verbose) and impossible using conventional libraries (because the abstractions are too thick). We discuss the design of Dali, show several example programs written using Dali, and show that programs written in Dali achieve performance competitive to hand-tuned C programs.