This article examines the effects of watershed urbanization on stream flood behavior in the Los Angeles metropolitan region. Stream gauge data, spatially distributed rainfall data, land use/land cover, and census population data were used to quantify change in flood behavior and urbanization in multiple watersheds. Increase in flood discharge started at the very early stage of the urbanization when the population density was relatively low but the rate of increase of flood discharge varied across watersheds depending on the distribution of the imperviousness surface and flood mitigation practices. This spatial variability in rainfall-runoff indices and the increasing flood risk across the metropolitan region has posed a challenge to the conventional flood emergency management, which usually responds to flood damages rather than being concerned with the broader issues of land use, land cover, and planning. This study pointed out that alternative land use planning and flood management practices could be mitigating the urban flood implemented hazard.

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The purpose of this paper is to evaluate the "fitness for use" of the highresolution National Hydrography Dataset (NHD) for regional watershed assessments. The Nature Conservancy's GIS tools were combined with various data sources and techniques to identify and fix four types of problems in the high resolution NHD-dangling streams, attribute errors, flow divergences, and duplicate streams. This effort generated a single-line natural flow network with correct arcnode topology, no dangling streams (with the exception of streams terminating in low relief basins), and few, if any, attribute designation problems. The revised NHD network improved on the original representation of the stream network and accompanying sub-watersheds in several ways.

This paper focuses on the attribute weight issue and advocates use of modifiable attribute weights in terrain-based environmental analysis and classification. A question was asked: 'How much will the result of a terrain-based environmental analysis be affected if the weights of used terrain attributes are changed?' The literature on landform classification and the fuzzy k-means method was reviewed in particular to help clarify the background and importance of this weight assignment issue. As an example, the effects of modifying attribute weights were evaluated for fuzzy k-means landform classification in a case study area. A total of 102 classifications were compared with each other and with a soil map, and comparison methods were specifically designed to evaluate the differences between these classifications. The results show that fuzzy k-means landform classification is sensitive to weight adjustments of adopted terrain attributes. The sensitivity is particularly high when the attribute weights started to be tuned away from the standard (i.e. uniform) weight of one. Better matching between landform classification and a soil map may be produced when attribute weights are tuned. In all, we advocate the widespread adoption of an exploratory attitude in assigning attribute weights for environmental analysis and classification. Copyright