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1.
1960-2007年中国地表潜在蒸散发敏感性的时空变化(英文) 总被引：2，自引：0，他引：2
Potential evapotranspiration (E0), as an estimate of the evaporative demand of the atmosphere, has been widely studied in the fields of irrigation management, crop water demand and predictions in ungauged basins (PUBs). Analysis of the sensitivity of E0 to meteorological factors is a basic research on the impact of climate change on water resources, and also is important to the optimal allocation of agricultural water resources. This paper dealt with sensitivity of E0 over China, which was divided into ten drainage systems, including Songhua River basin, Liaohe River basin, Haihe River basin, Yellow River basin, Yangtze River basin, Pearl River basin, Huaihe River drainage system, Southeast river drainage system, Northwest river drainage system and Southwest river drainage system. In addition, the calculation method of global radiation in Penman-Monteith formula was improved by optimization, and the sensitivities of Penman-Monteith potential evapotranspiration to the daily maximum temperature (STmax), daily minimum temperature (STmin), wind speed (SU2), global radiation (SRs) and vapor pressure (SVP) were calculated and analyzed based on the long-term meteorological data from 653 meteorological stations in China during the period 1960-2007. Results show that: (1) the correlation coefficient between E0 and pan evaporation increased from 0.61 to 0.75. E0 had the decline trends in eight of ten drainage systems in China, which indicates that "pan evaporation paradox" commonly exists in China from 1960 to 2007. (2) Spatially, Tmax was the most sensitive factor in Haihe River basin, Yellow River basin, Huaihe River drainage system, Yangtze River basin, Pearl River basin and Southeast river drainage system, and VP was the most sensitive factor in Songhua River Basin, Liaohe River basin, Northwest river drainage system while Rs was the most sensitive factor in Southwest river drainage system. For the nation-wide average, the most sensitive factor was VP, followed by Tmax, Rs, U2 and Tmin. In addition, the changes in sensitivity coefficients had a certain correlation with elevation. (3) Temporally, the maximum values of STmax and SRs occurred in July, while the maximum values of STmin, SVP and SU2 occurred in January. Moreover, trend analysis indicates that STmax had decline trends, while STmin, SU2, SRs and SVP had increasing trends. 相似文献
2.
本文研究涉及生态水文学中生态需水问题的一般认知。探讨了生态系统动态变化与水流驱动力因素之间的关系，重点探讨水流驱动因素中的关键指标——流速，通过分析流速与生态系统相互作用，从生态水文学动力因素出发估算生态需水；基于生态流速和水力半径，提出考虑河道内生态需水与水力因素关系的生态水力半径法，充分利用水生生物信息（鱼类产卵洄游流速）与河道信息（水位、流速、糙率等）估算河道内生态需水；归纳生态水力半径法在生态需水计算中的初步应用：考虑污染物降解耦合水量水质的生态需水计算、考虑鱼类等生物对流速要求的生态需水计算、考虑河道冲淤平衡的输沙需水量计算等方面。本文提出的生态流速研究既包括生物生长发育适宜的流速，又包括流速大小变化所涉及的许多动力因素，旨在延伸与扩展生态水文学的内涵与应用。 相似文献
3.
In areas with topographic heterogeneity, land use change is spatially variable and influenced by climate, soil properties, and topography. To better understand this variability in the high-sediment region of the Loess Plateau in which soil loss is most severe and sediment diameter is larger than in other regions of the plateau, this study builds some indicators to identify the characteristics of land use change and then analyze the spatial variability as it is affected by climate, soil property, and topography. We build two indicators, a land use change intensity index and a vegetation change index, to characterize the intensity of land use change, and the degree of vegetation restoration, respectively. Based on a subsection mean method, the two indicators are then used to assess the spatial variability of land use change affected by climatic, edaphic, and topographic elements. The results indicate that: 1) Land use changed significantly in the period 1998–2010. The total area experiencing land use change was 42,302 km2, accounting for 22.57%of the study area. High-coverage grassland, other woodland, and forest increased significantly, while low-coverage grassland and farmland decreased in 2010 compared with 1998. 2) Land use change occurred primarily west of the Yellow River, between 35 and 38 degrees north latitude. The four transformation types, including(a) low-coverage grassland to medium-coverage grassland,(b) medium-coverage grassland to high-coverage grassland,(c) farmland to other woodland, and(d) farmland to medium-coverage grassland, were the primary types of land use change, together constituting 60% of the area experiencing land use change. 3) The spatial variability of land use change was significantly affected by properties of dryness/wetness, soil conditions and slope gradient. In general, land use changed dramatically in semi-arid regions, remained relativelystable in arid regions, changed significantly in clay-rich soil, remained relatively stable in clay-poor soil, changed dramatically in steeper slopes, and remained relatively stable in tablelands and low-lying regions. The increase in vegetation coincided with increasing changes in land use for each physical element. These findings allow for an evaluation of the effect of the Grain to Green Program, and are applicable to the design of soil and water conservation projects on the Loess Plateau of China. 相似文献
4.
To control soil erosion and restore the degraded environment in the Loess Plateau, a large number of measures related to soil and water conservation have been employed that have profoundly affected catchment properties. This study constructed three indicators to characterize changes to the catchment slope, proposed both a method for a regression analysis of adjacent images and a sequence model, and applied multisource remotely sensed images and GIS spatial clustering analysis technologies to extract thematic information and comprehensively analyze the catchment change characteristics. The results indicate that the catchment slope properties changed significantly. At catchment scale, the average values of ARC, DVC and ART were 6.43%, 25.57% and 4.30%, respectively. There were six clustering types of catchment slope property changes. The maximum and minimum of the average similarities of the clustering types were 0.992 and 0.935. Each slope control measures had a distinct effect on catchment slope; the dominating factor of each clustering type was identified as: Type 1: D-VC, Type 2: D-VCLU, Type 3: D-LUVC, Type 4: D-TAVC, Type 5: D-TAC and Type 6: D-MFC. Type 5 and Type 1 covered the largest areas, respectively occupying 37.28% and 31.01%. Catchment slope property changes also had distinct types that depended on their geomorphological conditions. These findings provide a useful basis from which to further study catchment slope hydrological and soil erosion processes. 相似文献
5.
为了克服实际工作中常规预测模型的弊端,本文提出了水文序列解析- 集成预测模型(Prediction Model based on Segregation and Aggregation of Hydrological Time Series, PMSAHTS),通过分离水文序列中的趋势信号和周 期信号得到消除了人类活动影响的序列纯随机信号,然后通过随机因子预测预报方法(如BP 神经网络)使用这些 随机信号进行训练和仿真预测,将预测结果与趋势、周期预测结果重新集成,得到水文序列的预测值。将该模型应 用到和田子项目区进行年内月平均蒸发量的预测,结果表明,PMSAHTS 模型达到了水文情报预报规范的合格要 求,可以用于实际预测。 相似文献
6.
河湖水系连通的关键科学问题与研究方向 总被引：2，自引：1，他引：1
水资源时空分布不均,与经济社会格局不匹配,严重制约了中国的可持续发展。中国水情复杂,河湖水系正面临洪涝频繁、供水不足、河湖萎缩、水生态退化、水环境污染等诸多问题。面向国家发展新战略要求和现代化目标,有效解决复杂水问题,是新形势下生态文明建设和水资源可持续利用的重大需求。积极推进河湖水系连通,着力提高水资源统筹配置能力、河湖健康保障能力和水旱灾害抵御能力,是科学治水兴水的重大战略;开展深入的理论与技术研究是科学推进河湖水系连通的当务之急,也是治水兴水保障生态文明建设、支撑国家现代化进程的重大需求,具有重大意义。在分析全国河湖水系面临问题的基础上,讨论了河湖水系连通研究的必要性和迫切性,分析提出了河湖水系连通的三个关键科学问题及其研究框架,并对河湖水系连通的重要研究方向进行了探讨。 相似文献
7.
低空遥感无人机影像反演河道流量 总被引：5，自引：1，他引：4
河道流量在维持水圈系统稳定性、估算国家水能资源可开发量等方面具有重要作用。卫星遥感受其分辨率限制很难准确反演中小河流流量,近地面遥感流量计算方法及传统水文测流方法技术复杂、设备昂贵、测算效率低,限制了其在无资料区、灾害突发事件非接触式应急监测等方面的广泛应用。为此,在充分吸收国内外遥感反演河道流量方法优点的基础上,基于低空遥感无人机（UAV）影像,提出了一种适用于各类尺度河流的高效、非接触、简易快速反演河道流量的方法。该方法提供了有、无地面实测大断面两类情况下流量反演途径,通过无人机影像生成点云和表面高程（DSM）,基于点云和DSM获取水面宽、糙率、水面比降以及水上大断面信息,采用水力学方法计算河道流量。并根据地面336组野外站点实测数据验证了方法的精度,进一步分析了无地面实测大断面情况下的流量计算误差。结果表明,反演流量在高值区略高于实测流量,可以满足灾害应急监测流量精度需求（R 2= 0.997,RMSE = 4.55 m 3/s）;无地面实测大断面资料而进行概化时,流量计算误差随水位升高、河宽增大而减小,最大累积误差为最大过水流量的8.28%,误差主要来自于水位低、河宽小、流量小的过水断面底部。考虑到研究区大断面多样性受限,而人类活动影响下的河底断面复杂多样,未来尚需进一步研究提高近河底处大断面概化精度,以提高无地面实测大断面情况下的流量反演精度。本文利用无人机遥感影像反演河道流量的思路可为灾害应急监测提供快速流量监测的新途径,也可为无资料地区遥感水文测站的建立提供重要参考依据。 相似文献
8.
小型消费级无人机地形数据精度验证 总被引：5，自引：0，他引：5
低空遥感是近几年快速发展、应用非常广泛的新兴技术。小型消费级无人机集成可见光传感器,具有快速、灵活、高性价比等优势,受到广泛关注。然而目前有关该类无人机综合测量精度的研究不足,影响其进一步的推广应用。为此,本文开展了针对大疆(Phantom 3 professional)小型消费级无人机地形测量数据精度验证工作,设定6种航高(50 m、60 m、70 m、80 m、90 m和100 m)获取研究区的立体像对,生成影像点云(point cloud)、数字表面模型(DSM)以及数字正射影像图(DOM)等结果。在测量精度验证中,首先,在标准实验场均匀布设地面控制点(GCP),利用差分GPS测出GCP的高精度3维坐标;然后,通过GCP对立体像对进行绝对定位;最后,利用误差统计方法分析上述结果的测量精度。验证表明,在50—100m航高时,无人机影像结果的分辨率为2.22—4.23 cm,水平方向平均误差为±0.51 cm,垂直方向平均误差为±4.39 cm,相对均方根误差(RMSE)水平方向为±2.79 cm,垂直方向为±9.98 cm。研究结果表明,小型消费级无人机在飞控系统下的测量精度可达厘米级,这不仅为野外地理和生态调查工作者提供一种低成本、快速、灵活与精确获取地形信息的新型测量手段,同时还对使用此类无人机做航测应用及飞行参数设置提供一定参考。 相似文献
9.
本文研究涉及生态水文学中生态需水问题的一般认知。探讨了生态系统动态变化与水流驱动力因素之间的关系，重点探讨水流驱动因素中的关键指标—流速，通过分析流速与生态系统相互作用，从生态水文学动力因素出发估算生态需水；基于生态流速和水力半径，提出考虑河道内生态需水与水力因素关系的生态水力半径法，充分利用水生生物信息（鱼类产卵洄游流速）与河道信息（水位、流速、糙率等）估算河道内生态需水；归纳生态水力半径法在生态需水计算中的初步应用:考虑污染物降解耦合水量水质的生态需水计算、考虑鱼类等生物对流速要求的生态需水计算、考虑河道冲淤平衡的输沙需水量计算等方面。本文提出的生态流速研究既包括生物生长发育适宜的流速，又包括流速大小变化所涉及的许多动力因素，旨在延伸与扩展生态水文学的内涵与应用。 相似文献
10.
基于19822010年无定河流域的遥感影像、气象和土地利用数据,利用Priestley-Taylor公式计算出潜在蒸散发,进而得到干旱指数,将各气象因子与干旱指数差值进行叠加、逐象元相关分析,得到了无定河流域19822010年干旱指数的时空变化,并分析了气候和土地利用变化对干旱指数变化的影响。结果显示:（1）1982年、2010年干旱指数分别为2.01和2.13,总体趋势是趋干旱的;（2）干旱指数2.0以下的区域迅速减少,2.15以上的区域明显扩张;（3）干旱指数均呈现增加趋势,显著增加的区域集中于无定河流域中游和下游地区;（4）干旱指数变化同气温、水汽压、净辐射的变化成正相关,同降水量变化成负相关;（5）各种土地利用类型的干旱指数均呈现增长趋势,但是增长的幅度有所不同:林地>耕地>草地>建筑用地>水域>未利用地。（6）土地利用对干旱指数平均值的影响非常微弱,干旱指数的变化主要是由于气候变化导致的。 相似文献