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In recent years, there has been growing recognition of the importance of riparian buffers between agricultural fields and waterbodies. Riparian buffers play an important role in mitigating the impacts of land use activities on water quality and aquatic ecosystems. However, evaluating the effectiveness of riparian buffer systems on a watershed scale is complex, and watershed models have limited capabilities for simulating riparian buffer processes. Thus, the overall objective of this paper is to develop an understanding of riparian buffer processes towards water quality modelling/monitoring and nonpoint source pollution assessment. The paper provides a thorough review of relevant literature on the performance of vegetative buffers on sediment reduction. It was found that although sediment trapping capacities are site-and vegetation-specific, and many factors influence the sediment trapping efficiency, the width of a buffer is important in filtering agricultural runoff and wider buffers tended to trap more sediment. Sediment trapping efficiency is also affected by slope, but the overall relationship is not consistent among studies. Overall, sediment trapping efficiency did not vary by vegetation type and grass buffers and forest buffers have roughly the same sediment trapping efficiency. This analysis can be used as the basis for planning future studies on watershed scale simulation of riparian buffer systems, design of effective riparian buffers for nonpoint source pollution control or water quality restoration and design of riparian buffer monitoring programs in watersheds. Published in

The Soil Conservation Service (SCS) curve number (CN) estimates of direct runoff from rainfall for semiarid catchments can be inaccurate. Investigation of the Walnut Gulch Experimental Watershed (WGEW) (Southeastern Arizona) and its ten nested catchments determined that the inaccuracy is due to the original SCS ratio (λ) of 0.2 between initial abstraction and maximum potential retention. Sensitivity analyses indicate that runoff estimation can be very sensitive to the initial abstraction ratio, especially for relatively low rainfall amount and for watersheds covered by deep, coarse, and porous soil, conditions that dominate many semiarid watersheds worldwide. Changing the ratio of initial abstraction to the maximum potential retention to optimal values ranging from 0.01 to 0.53 for different Walnut Gulch catchments improved runoff estimates. The greater the channel area and the finer the soil, the smaller the initial abstraction ratio is. The variation of the initial abstraction ratio for the WGEW is due to the variation of maximum potential retention and initial abstraction, which are channel area and soil‐dependent parameters. The greater the channel area, the higher the maximum potential retention S is, and the coarser the soil, the larger the initial abstraction Ia is. In addition, the effect of initial abstraction ratio on runoff estimation increases with decreasing CN. Thus, impacts of initial abstraction ratio on runoff estimation should be considered, especially for semiarid watersheds where the CN is usually low. Copyright © 2012 John Wiley & Sons, Ltd.

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