排序方式: 共有22条查询结果,搜索用时 15 毫秒
21.
Water quality is the outcome of numerous landscape factors in the catchment. In addition to land use, soil deposits, bedrock and topography are central in different catchment processes and thus important in predicting water quality. In this study, we explored the influence of geomorphological factors at the catchment scale on water quality in 32 boreal rivers in Finland. Water quality was studied through total phosphorus, total nitrogen, pH and water colour, whereas geomorphological factors covered variables from topography, bedrock and surficial ground material (Quaternary soil deposits). Spearman's rank correlation test was used to study the correlations between variables. The relationship between water quality and geomorphology was analysed using novel multivariate methods by fitting of geomorphological vectors and smooth surfaces onto a non‐metric multidimensional scaling (NMDS) scattergram. Hierarchical partitioning (HP) was used to assess the relative importance of geomorphological variables on water quality. Quaternary soil deposits, especially the covers of clay‐silt and till soils, were important factors in relation to phosphorus and nitrogen based on both NMDS and HP analyses. For example, clay‐silt cover explained over 40% of the variation in these nutrients according to HP. The variation in river water pH was best explained by the covers of sand and open bedrock terrain as well as by catchment topography. Geomorphological variables differed in their effect and relative significance, and thus several geomorphological attributes need to be considered when examining variation in water quality. In conclusion, these results demonstrate that geomorphological factors can be used to predict physical–chemical water quality in a cost‐efficient manner in boreal rivers. NMDS was successfully applied in water quality analyses at the catchment scale. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
22.
Large biases and inconsistent climate change signals in ENSEMBLES regional projections 总被引:1,自引:1,他引:0
Marco Turco Antonella Sanna Sixto Herrera Maria-Carmen Llasat José Manuel Gutiérrez 《Climatic change》2013,120(4):859-869
In this paper we analyze some caveats found in the state-of-the-art ENSEMBLES regional projections dataset focusing on precipitation over Spain, and highlight the need of a task-oriented validation of the GCM-driven control runs. In particular, we compare the performance of the GCM-driven control runs (20C3M scenario) with the ERA40-driven ones (“perfect” boundary conditions) in a common period (1961–2000). Large deviations between the results indicate a large uncertainty/bias for the particular RCM-GCM combinations and, hence, a small confidence for the corresponding transient simulations due to the potential nonlinear amplification of biases. Specifically, we found large biases for some RCM-GCM combinations attributable to RCM in-house problems with the particular GCM coupling. These biases are shown to distort the corresponding climate change signal, or “delta”, in the last decades of the 21st century, considering the A1B scenario. Moreover, we analyze how to best combine the available RCMs to obtain more reliable projections. 相似文献