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The objective of this study is to quantitatively evaluate Tropical Rainfall Measuring Mission (TRMM) data with rain gauge data and further to use this TRMM data to drive a Distributed Time-Variant Gain Model (DTVGM) to perform hydrological simulations in the semi-humid Weihe River catchment in China. Before the simulations, a comparison with a 10-year (2001-2010) daily rain gauge data set reveals that, at daily time step, TRMM rainfall data are better at capturing rain occurrence and mean values than rainfall extremes. On a monthly time scale, good linear relationships between TRMM and rain gauge rainfall data are found, with determination coefficients R2 varying between 0.78 and 0.89 for the individual stations. Subsequent simulation results of seven years (2001-2007) of data on daily hydrological processes confirm that the DTVGM when calibrated by rain gauge data performs better than when calibrated by TRMM data, but the performance of the simulation driven by TRMM data is better than that driven by gauge data on a monthly time scale. The results thus suggest that TRMM rainfall data are more suitable for monthly streamflow simulation in the study area, and that, when the effects of recalibration and the results for water balance components are also taken into account, the TRMM 3B42-V7 product has the potential to perform well in similar basins.  相似文献   
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ABSTRACT

High-resolution data on the spatial pattern of water use are a prerequisite for appropriate and sustainable water management. Based on one well-validated hydrological model, the Distributed Time Variant Gains Model (DTVGM), this paper obtains reliable high-resolution spatial patterns of irrigation, industrial and domestic water use in continental China. During the validation periods, ranges of correlation coefficient (R) and Nash-Sutcliffe efficiency (NSE) coefficient are 0.67–0.96 and 0.51–0.84, respectively, between the observed and simulated streamflow of six hydrological stations, indicating model applicability to simulate the distribution of water use. The simulated water use quantities have relative errors (RE) less than 5% compared with the observed. In addition, the changes in streamflow discharge were also correctly simulated by our model, such as the Zhangjiafen station in the Hai River basin with a dramatic decrease in streamflow, and the Makou station in the Pearl River basin with no significant changes. These changes are combined results of basin available water resources and water use. The obtained high-resolution spatial pattern of water use could decrease uncertainty of hydrological simulation and guide water management efficiently.
Editor M.C. Acreman; Associate editor X. Fang  相似文献   
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高强度人类活动影响下永定河北京段水质水量模拟   总被引:1,自引:0,他引:1       下载免费PDF全文
自然条件下的河流水质模型在高强度人类活动影响的城市河流应用中存在局限性,构建耦合人类活动影响的水质模型是识别城市河流水质变化的关键。针对永定河北京段自然水循环与再生水、循环管线回水及外调水等人类活动相互作用的特点,构建了基于分布式时变增益水文模型与一维稳态的水质过程耦合的模型,分析了不同调水情景下永定河北京段水质变化过程。应用表明该模型在永定河北京段具有良好的适用性,不仅能描述过去天然条件、现状条件下水质过程,同时能应用于未来规划情景下的水质预测,同时表明外调水工程对永定河北京段的水量水质有显著的改善作用。  相似文献   
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