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How far can be SAR considered a tool for mountain hydrology?

机译:SAR可以算作多远的山区水文学工具?

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摘要

Accurate information about soil moisture content (SMC) in mountain catchments is of great importance in hydrological applications, agriculture and climate change impact analysis. In the last two decades microwave remote sensing sensors such as Synthetic Aperture Radar (SAR) have been deeply exploited for surface SMC estimation. However, obtaining reliable predictions of fine-scale spatial and temporal patterns of SMC in mountain areas is still challenging due to the extreme variability in topography, soil and vegetation properties. In this contribution we analyze the spatial and temporal dynamic of surface SMC of alpine meadows and pastures with different techniques: (Ⅰ) a network of fixed stations; (Ⅱ) field campaigns with mobile ground sensors; (Ⅲ) SMC retrieval from RADARSAT2 SAR images; (Ⅳ) simulations using the GEOtop 2.0 hydrological model. The strength and the weaknesses of the different estimation techniques are evaluated and the physical controls of the observed SMC patterns are analyzed. Results show that SAR SMC estimation corresponds well to the spatial ground surveys, but shows different patterns with respect to the model, especially for irrigated meadows. In fact, SAR patterns reflect vegetation, soil type and topography. Model output is in agreement with fixed stations observations, but it shows less spatial variability compared to SAR. Differences are likely due to the difficulties to know with sufficient spatial detail model parameters and irrigation amount. Therefore, results suggest that SAR products have a good ability to reproduce small-scale SMC patterns in mountain regions, thus complementing the ability of the hydrological model to predict temporal variations of SMC.
机译:有关山区流域土壤水分含量(SMC)的准确信息在水文应用,农业和气候变化影响分析中非常重要。在过去的二十年中,诸如合成孔径雷达(SAR)之类的微波遥感传感器已被广泛用于表面SMC估计。然而,由于地形,土壤和植被特性的极大变化,在山区获得可靠的SMC时空分布的精细预测仍然具有挑战性。在这项贡献中,我们用不同的技术分析了高山草甸和牧场表面SMC的时空动态:(Ⅰ)固定站网络; (二)带有移动地面传感器的野战活动; (Ⅲ)从RADARSAT2 SAR图像中提取SMC; (四)使用GEOtop 2.0水文模型进行模拟。评估了不同估计技术的优缺点,并分析了所观察到的SMC模式的物理控制。结果表明,SAR SMC估计与空间地面调查非常吻合,但相对于模型显示出不同的模式,尤其是对于灌溉草地。实际上,SAR模式反映了植被,土壤类型和地形。模型输出与固定站的观测结果一致,但是与SAR相比,它显示出较小的空间变异性。可能由于难以掌握足够的空间细节模型参数和灌溉量而导致差异。因此,结果表明,SAR产品具有在山区再现小型SMC模式的良好能力,从而补充了水文模型预测SMC时间变化的能力。

著录项

  • 来源
    《SAR image analysis, modeling, and techniques XIII》|2013年|88910G.1-88910G.13|共13页
  • 会议地点 Dresden(DE)
  • 作者单位

    Institute for Alpine Environment, EURAC, Viale Druso 1, 39100 Bolzano, Italy;

    Institute for Applied Remote Sensing, EURAC, Viale Druso 1, 39100 Bolzano, Italy;

    Institute for Alpine Environment, EURAC, Viale Druso 1, 39100 Bolzano, Italy,Institute of Ecology, University of Innsbruck, Sternwarterstrasse 17, Innsbruck, Austria;

    Institute for Alpine Environment, EURAC, Viale Druso 1, 39100 Bolzano, Italy,Institute of Ecology, University of Innsbruck, Sternwarterstrasse 17, Innsbruck, Austria;

    Institute for Applied Remote Sensing, EURAC, Viale Druso 1, 39100 Bolzano, Italy;

    Institute for Alpine Environment, EURAC, Viale Druso 1, 39100 Bolzano, Italy,Institute of Ecology, University of Innsbruck, Sternwarterstrasse 17, Innsbruck, Austria;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Soil moisture; RADARSAT2; SAR; hydrology; models;

    机译:土壤湿度;雷达卫星2; SAR;水文学楷模;

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