FEATURED COLLECTION: FOREST HYDROLOGY IN CHINA
We are pleased to present a Featured Collection of 11 papers organized by Guest Associate Editors Ge Sun, Shirong Liu, Zhiqiang Zhang, and Xiaohua Wei. Papers include:

An overview of the progress and lessons learned from forest hydrological research in China during the past 40 years in the context of worldwide literature on forest-water relations;
Case studies on the semi-arid Loess Plateau in northwest China, a region that suffers severe soil erosion and water shortages and contributes most of the runoff and sediment to the Yellow River basin;
Hydrologic effects of forest vegetation changes in the subalpine region of the Upper Minjiang River, a major tributary of the Yangtze River, in southwestern China;
A case study of forest watershed hydrology in the Yangtze River Basin with a subtropical climate; and
Forest-water relations at a regional to a continental scale by using large-scale computer simulation models.

OTHER PAPERS
Thompson et al. compared the thermal runoff characteristics between asphalt and turfgrass sod surfaces, to identify meteorological variables that influence these thermal characteristics, and to evaluate evaporative heat loss for runoff from asphalt surfaces.

They found existing evaporation equations developed from studies on lakes were not adequate to predict evaporation from runoff on a heated impervious surface.

Jonkman and Penning-Rowsell review past experimental work on human instability in flood flows and report on new experiments by the Flood Hazard Research Centre (FHRC). Those concerned to identify locations where high flood flows could be a threat to human life need to modify their hazard assessments.

Ungtae Kim et al. developed a methodology to project the future precipitation in large river basins under limited data and climate change while preserving the historical temporal and spatial characteristics. They tested it in the upper Blue Nile River Basin of Ethiopia.

Vecchia et al. developed a parametric regression model for assessing the variability and long-term trends in pesticide concentrations in streams. Application to selected herbicides and insecticides in four diverse streams indicated the model is robust with respect to pesticide type, stream location, and the degree of censoring. They found incorrectly modeling the seasonal structure of the concentration data resulted in substantial estimation bias and moderate increases in mean-squared error and decreases in power.