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Implications of GRACE Satellite Gravity Measurements for Diverse Hydrological Applications.

机译:GRACE卫星重力测量对不同水文应用的意义。

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摘要

Soil moisture plays a major role in the hydrologic water balance and is the basis for most hydrological models. It influences the partitioning of energy and moisture inputs at the land surface. Because of its importance, it has been used as a key variable for many hydrological studies such as flood forecasting, drought studies and the determination of groundwater recharge. Therefore, spatially distributed soil moisture with reasonable temporal resolution is considered a valuable source of information for hydrological model parameterization and validation. Unfortunately, soil moisture is difficult to measure and remains essentially unmeasured over spatial and temporal scales needed for a number of hydrological model applications.;The domain of the first case study was the Mackenzie River Basin wherein the GRACE total water storage estimates were successfully inter-compared and validated with the atmospheric based water balance. These were then used to assess the WAT-CLASS hydrological model estimates of total water storage. The outcome of this inter-comparison revealed the potential application of the GRACE-based approach for the closure of the hydrological water balance of the Mackenzie River Basin as well as a dependable source of data for the calibration of traditional hydrological models.;The Mackenzie River Basin result led to a second case study where the GRACE-based total water storage was validated using storage estimated from the atmospheric-based water balance P--E computations in conjunction with the measured streamflow records for the Saskatchewan River Basin at its Grand Rapids outlet in Manitoba. The fallout from this comparison was then applied to the characterization of the Prairie-wide 2002/2003 drought enabling the development of a new drought index now known as the Total Storage Deficit Index (TSDI). This study demonstrated the potential application of the GRACE-based technique as a tool for drought characterization in the Canadian Prairies.;Finally, the hydroinformatic approach based on the artificial neural network (ANN) enabled the downscaling of the groundwater component from the total water storage estimate from the remote sensing satellite, GRACE. This was subsequently explored as an alternate source of calibration and validation for a hydrological modeling application over the Assiniboine Delta Aquifer in Manitoba. Interestingly, a high correlation exists between the simulated groundwater storage from the coupled hydrological model, CLM-PF and the downscaled groundwater time series storage from the remote sensing satellite GRACE over this 4,000 km2 deltaic basin in Canada.;In 2002, the Gravity Recovery And Climate Experiment (GRACE) satellite platform was launched to measure, among other things, the gravitational field of the earth. Over its life span, these orbiting satellites have produced time series of mass changes of the earth-atmosphere system. The subsequent outcome of this, after integration over a number of years, is a time series of highly refined images of the earth's mass distribution. In addition to quantifying the static distribution of mass, the month-to-month variation in the earth's gravitational field are indicative of the integrated value of the subsurface total water storage for specific catchments. Utilization of these natural changes in the earth's gravitational field entails the transformation of the derived GRACE geopotential spherical harmonic coefficients into spatially varying time series estimates of total water storage. These remotely sensed basin total water storage estimates can be routinely validated against independent estimates of total water storage from an atmospheric-based water balance approach or from well calibrated macroscale hydrologic models. The hydrological relevance and implications of remotely estimated GRACE total water storage over poorly gauged, wetland-dominated watershed as well as over a deltaic region underlain by a thick sand aquifer in Western Canada are the focus of this thesis.
机译:土壤水分在水文水分平衡中起主要作用,并且是大多数水文模型的基础。它会影响陆地表面能量和水分输入的分配。由于它的重要性,它已被用作许多水文研究的关键变量,例如洪水预报,干旱研究和地下水补给的确定。因此,具有合理时间分辨率的空间分布的土壤水分被认为是水文模型参数化和验证的有价值的信息来源。不幸的是,土壤水分很难测量,并且在许多水文模型应用所需的时空范围内基本上无法测量。;第一个案例研究的领域是Mackenzie流域,其中GRACE的总储水量估计值在成功之间与基于大气的水平衡进行比较和验证。然后将这些用于评估总蓄水量的WAT-CLASS水文模型估计。这种相互比较的结果表明,基于GRACE的方法在关闭Mackenzie流域水文水量平衡方面的潜在应用,以及为传统水文模型校准提供可靠数据的来源。流域的结果导致了第二个案例研究,其中使用基于大气的水平衡P--E计算估计的储水量,结合大萨皮斯急流出口萨斯喀彻温河流域的实测流量记录,对基于GRACE的总储水量进行了验证。在曼尼托巴。然后,将这种比较的结果应用于全草原2002/2003年干旱的特征分析,从而可以开发出一种新的干旱指数,现在称为总存储赤字指数(TSDI)。这项研究证明了基于GRACE的技术作为加拿大大草原干旱特征分析工具的潜在应用。最后,基于人工神经网络(ANN)的水信息学方法使总蓄水量中的地下水成分得以缩减来自遥感卫星GRACE的估算。随后,将其作为曼尼托巴省Assiniboine三角洲含水层上水文建模应用的替代校准和验证来源。有趣的是,耦合水文模型CLM-PF的模拟地下水储量与遥感卫星GRACE在加拿大这个4000 km2三角洲盆地中按比例缩小的地下水时间序列存储之间存在高度相关性; 2002年,重力恢复和启动了气候实验(GRACE)卫星平台,以测量地球的引力场。这些轨道卫星在其生命周期内产生了地球-大气系统质量变化的时间序列。经过多年的整合,此后的结果是一系列时间精确的地球质量分布图像。除了量化质量的静态分布之外,地球重力场的逐月变化还表示特定集水区地下总蓄水量的积分值。利用地球重力场中的这些自然变化,需要将得出的GRACE势能球谐系数转换为总储水量的空间变化时间序列估计值。这些遥感流域的总储水量估算值可以通过基于大气的水平衡方法或经过很好校准的宏观水文模型,根据总储水量的独立估算值进行常规验证。本文的重点是在稀疏的,以湿地为主的流域以及加拿大西部厚厚的含水层所覆盖的三角洲地区,通过远距离估算的GRACE总蓄水量的水文相关性和意义。

著录项

  • 作者

    Yirdaw-Zeleke, Sitotaw.;

  • 作者单位

    University of Manitoba (Canada).;

  • 授予单位 University of Manitoba (Canada).;
  • 学科 Hydrology.;Engineering Civil.;Engineering Environmental.;Remote Sensing.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 198 p.
  • 总页数 198
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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