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Assessing the effects of land cover and future climate conditions on the provision of hydrological services in a medium‐sized watershed of Portugal 
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下载免费PDF全文 Claudia Carvalho‐Santos João Pedro Nunes António T. Monteiro Lars Hein João Pradinho Honrado 《水文研究》2016,30(5):720-738
The separated and combined effects of land‐cover scenarios and future climate on the provision of hydrological services were evaluated in Vez watershed, northern Portugal. Soil and Water Assessment Tool was calibrated against daily discharge, sediments and nitrates, with good agreements between model predictions and field observations. Four hypothetical land‐cover scenarios were applied under current climate conditions (eucalyptus/pine, oak, agriculture/vine and low vegetation). A statistical downscaling of four General Circulation Models, bias‐corrected with ground observations, was carried out for 2021–2040 and 2041–2060, using representative concentration pathway 4.5 scenario. Also, the combined effects of future climate conditions were evaluated under eucalyptus/pine and agriculture/vine scenario. Results for land cover revealed that eucalyptus/pine scenario reduced by 7% the annual water quantity and up to 17% in the summer period. Although climate change has only a modest effect on the reduction of the total annual discharge (?7%), the effect on the water levels during summer was more pronounced, between ?15% and ?38%. This study shows that climate change can affect the provision of hydrological services by reducing dry season flows and by increasing flood risks during the wet months. Regarding the combined effects, future climate may reduce the low flows, which can be aggravated with eucalyptus/pine scenario. In turn, peak flows and soil erosion can be offset. Future climate may increase soil erosion and nitrate concentration, which can be aggravated with agriculture scenario. Results moreover emphasize the need to consider both climate and land‐cover impacts in adaptation and land management options at the watershed scale. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
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Roots are responsible for the uptake of water and nutrients by plants and have the plasticity to dynamically respond to different environmental conditions. However, most land surface models currently prescribe rooting profiles as a function only of vegetation type, with no consideration of the surroundings. In this study, a dynamic rooting scheme, which describes root growth as a compromise between water and nitrogen availability, was incorporated into CLM4.5 with carbon–nitrogen(CN) interactions(CLM4.5-CN) to investigate the effects of a dynamic root distribution on eco-hydrological modeling. Two paired numerical simulations were conducted for the Tapajos National Forest km83(BRSa3) site and the Amazon, one using CLM4.5-CN without the dynamic rooting scheme and the other including the proposed scheme. Simulations for the BRSa3 site showed that inclusion of the dynamic rooting scheme increased the amplitudes and peak values of diurnal gross primary production(GPP) and latent heat flux(LE) for the dry season, and improved the carbon(C) and water cycle modeling by reducing the RMSE of GPP by 0.4 g C m~(-2)d~(-1), net ecosystem exchange by 1.96 g C m~(-2)d~(-1), LE by 5.0 W m~(-2), and soil moisture by 0.03 m~3m~(-3), at the seasonal scale, compared with eddy flux measurements, while having little impact during the wet season. For the Amazon, regional analysis also revealed that vegetation responses(including GPP and LE) to seasonal drought and the severe drought of 2005 were better captured with the dynamic rooting scheme incorporated. 相似文献
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Pattern recognition in road networks can be used for different applications, including spatiotemporal data mining, automated map generalization, data matching of different levels of detail, and other important research topics. Grid patterns are a common pattern type. This paper proposes and implements a method for grid pattern recognition based on the idea of mesh classification through a supervised learning process. To train the classifier, training datasets are selected from worldwide city samples with different cultural, historical, and geographical environments. Meshes are subsequently labeled as composing or noncomposing grids by participants in an experiment, and the mesh measures are defined while accounting for the mesh’s individual characteristics and spatial context. The classifier is generated using the C4.5 algorithm. The accuracy of the classifier is evaluated using Kappa statistics and the overall rate of correctness. The average Kappa value is approximately 0.74, which corresponds to a total accuracy of 87.5%. Additionally, the rationality of the classifier is evaluated in an interpretation step. Two other existing grid pattern recognition methods were also tested on the datasets, and comparison results indicate that our approach is effective in identifying grid patterns in road networks. 相似文献
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基于C4.5决策树算法的道路结冰预报模型构建及应用 总被引：2，自引：0，他引：2
道路结冰是气象上规定的主要灾害性天气之一,准确认识道路结冰发生规律并科学有效地预报是防灾减灾的关键问题。以影响道路结冰的日积雪深度、日最低气温、日降水量等气象要素为主要因子,将是否结冰抽象成二元分类问题,借助数据挖掘中C4.5决策树算法进行分类分析,得到便于预报员使用的预报道路结冰规则集。在实验部分,选取2004—2013年连云港和嘉定为例,用前8 a的连云港(嘉定)地区道路结冰数据样本进行分类规则的学习,从而得到适合连云港(嘉定)地区的4(3)条预报道路结冰规则集,然后用剩下2 a的数据进行检验,准确率高达96.82%(94.87%)。实验表明采用C4.5决策树算法构建的道路结冰预报模型不仅预报准确率高、易解释、方便预报员直接使用,而且预报规则与道路结冰现象的天气过程及理论一致。 相似文献
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基于MODIS数据的决策树分类方法研究与应用 总被引：23，自引：0，他引：23
介绍了目前国际上流行的两种决策树算法———CART算法与C4·5算法,并引入了两种机器学习领域里的分类新技术———boosting和bagging技术,为探究这些决策树分类算法与新技术在遥感影像分类方面的潜力,以中国华北地区MODIS250m分辨率影像进行了土地覆盖决策树分类试验与分析。研究结果表明决策树在满足充分训练样本的条件下,相对于传统方法如最大似然法(MLC)能明显提高分类精度,而在样本量不足下决策树分类表现差于MLC;并发现在单一决策树生成中,分类回归树CART算法表现较C4·5算法具有分类精度和树结构优势,分类精度的提高取决于树结构的合理构建与剪枝处理;另外在决策树CART中引入boosting技术,能明显提高那些较难识别类别的分类准确率18·5%到25·6%。 相似文献
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区域尺度土地覆盖变化是自然变化和人类活动共同驱动的结果,同时又对区域气候环境产生反馈。利用欧洲中值数值预报中心（ECMWF） ERA-Interim再分析资料,驱动RegCM4.5区域气候模式,进行了两个时间段（1980-2014、2005-2014）的数值模拟试验。以1：250 000土地利用图为基础,结合植被图、土壤图制作具有高精度、极强现势性的土地覆盖资料,区域模式中陆面过程模式采用BATS,模拟了现实的土地覆盖改变对气候要素的影响,分析了黄土高原地区土地覆盖变化对气候的反馈作用。结果表明：（1） RegCM4.5不但能够较好描述黄土高原气温、降水的时间空间分布特征,也能够模拟土地覆盖变化对黄土高原局地气候变化的反馈。（2）不同土地覆盖变化特征对气候反馈作用不同,荒漠化会引起局部地区气温升高和降水减少,并通过正反馈机制,致使自然植被生长发育受阻;水域旱化会导致夏季气温升高和降水增加,从而加剧干旱洪涝灾害风险;草地覆盖增加会导致春夏季降水量与气温的降低,秋冬季降水量与气温升高。（3）土地覆盖变化对气温与降水的影响在夏季较强。该研究可促进对黄土高原生态治理环境效应的理解,也能深化对土地利用-气候变化之间互馈作用的过程认识,并为区域生态建设对策选择提供参考。 相似文献
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基于长江流域142个气象站1986—2005年月降水和气温数据,评估由MPI-ESM-LR模式驱动的CCLM区域气候模式对长江流域气温和降水的模拟能力,并采用EDCDF法对气温和降水预估数据进行偏差校正。结果表明：该区域气候模式能较好地模拟出长江流域平均气温的季节变化和空间分布特征,但模拟值无论在季节还是年际尺度上均高于观测值。对降水而言,该模式不能较好地模拟出降水的季节分布特征,导致春季、冬季及年模拟值高于观测值,而夏季和秋季模拟值低于观测值。总体而言,该模式对气温的模拟效果相对较好。偏差校正后的预估结果表明：在RCP4.5情景下,长江流域未来（2016—2035年）平均气温相对于基准期（1986—2005年）将升高0.66℃,年降水量将减少2.2%。 相似文献
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Characteristics of great geomagnetic storms during solar cycle 23 were statistically investigated. Firstly, we focused on the uniqueness of solar cycle 23 by analyzing both the great storm number and sunspot number from 1957 to 2008. It was found that the relationship between the sunspot number and great storm number weakened as the activity of the storms strengthened. There was no obvious relationship between the annual sunspot number and great storm number with Dstxi≤-300 nT. Secondly, we studied the relationship between the peak Dst and peak Bz in detail. It was found that the condition Bz≤-10 nT is not necessary for storms with Dst≤-100 nT, but seems necessary for storms with Dst≤-150 nT. The duration for Bz≤-10 nT has no direct relationship with the giant storm. The correlation coefficient between the Dst peak and Bz peak for the 89 storms studied is 0.81. After removing the effect of solar wind dynamic pressure on the Dst peak, we obtained a better correlation coefficient of 0.86. We also found the difference between the Dst peak and the corrected Dst peak was proportional to the Dst peak. 相似文献
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基于CMIP5的逐日最高温度模拟资料、GGI情景数据库逐年代人口数据,在RCP4.5情景下,以对应栅格高温日数与人口数量的乘积作为人口对高温的暴露度指标,通过多模式集合平均预估未来中国人口对不同强度高温的暴露度变化。结果表明：相比于基准时段（1981-2010年）,中国人口对高温和强危害性高温的暴露度从2021-2040年开始明显增加,至2081-2100年暴露度分别增加了5.7倍和17.5倍;除了中国西部部分地区外,全国大部地区人群均受高温的影响,在21世纪中后期中东部大部人口对高温的暴露度超过10.0×106人?d;相比基准时段,随着年代的增长,中国人口对强危害性高温的暴露度在范围和强度上均有明显增加;2081-2100年,人口对高温和强危害性高温的暴露度增幅减缓。从气象地理区域上看,未来各时段人口对高温、强危害性高温的暴露度均有一定程度增加,但增加明显的区域主要集中在华北、黄淮、江南和江淮地区,华南地区对强危害性高温的暴露度增幅较小。高温日数变化对全国人口对高温暴露度的变化所产生的作用最明显。多模式集合的预估结果可以为防控未来高温风险提供重要的参考价值。 相似文献