Potential for hydrologic characterization of deep mountain snowpack via passive microwave remote sensing in the Kern River basin, Sierra Nevada, USA

被引:42
作者
Li, Dongyue [1 ,2 ]
Durand, Michael [1 ,2 ]
Margulis, Steven A. [3 ]
机构
[1] Ohio State Univ, Sch Earth Sci, Columbus, OH 43210 USA
[2] Ohio State Univ, Byrd Polar Res Ctr, Columbus, OH 43210 USA
[3] Univ Calif Los Angeles, Dept Civil & Environm Engn, Los Angeles, CA USA
基金
美国国家科学基金会;
关键词
Remote sensing of snow; Passive microwave radiometry; WATER EQUIVALENT; AMSR-E; BRIGHTNESS TEMPERATURES; SPATIAL-DISTRIBUTION; UNITED-STATES; GRAIN-SIZE; DEPTH; SSM/I; RETRIEVAL; COLORADO;
D O I
10.1016/j.rse.2012.06.027
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Snow plays a critical role in hydrology and water resources, but snow properties in mountainous areas vary dramatically in space, making characterization difficult: in situ measurements represent a single point of spatially-variable snow properties. Spaceborne passive microwave (PM) remote sensing has spatially continuous coverage, but coarse spatial resolution. PM spatial footprints are nominally elliptical, with the spatial orientation changing relative to a given basin on the ground from one satellite pass to the next. The widely used Equal-Area Scalable Earth Grid (EASE-Grid) resamples the raw PM observations to a 25 km x 25 km grid; this is far coarser than The Advanced Microwave Scanning Radiometer for EOS (AMSR-E) 37 GHz Level 2A (L2A) footprints with an area of 87.9 km(2). This paper presents methods for processing the L2A data in order to illustrate that PM measurements contain information about snow accumulation and ablation cycles in mountainous regions. Methods are presented 1) to calculate the average T-b over a hydrologic basin for monitoring SWE accumulation amount, and 2) to interpolate T-b to a point for monitoring SWE ablation timing. Across the six-year study period, the range of the T-b was 50 K. while the range of the air temperature was only 30 K, indicating significant surface emissivity variations. The minimum T-b of each water year (WY), which starts from October 1 of a calendar year and ends at September 30 of the next, showed a strong inverse relationship to SWE measured in situ; the correlation coefficient between T-b and an in situ basin average SWE was -0.94. The L2A data is three times more sensitive to than the EASE-Grid data to in situ SWE. The diurnal amplitude variability (DAV, or difference between daytime and nighttime T-b) was used to identify the day of melt onset and compared with in situ estimates of onset derived from daily SWE measurements. L2A data corresponded well with the in situ onset dates with a correlation coefficient of 0.94 and an RMSE of 5.04 days. When using EASE-Grid data, the RMSE in onset date was 11.7 days. In addition, T-b DAV was found to be correlated with T-air DAV during winter, with an average correlation coefficient of 0.72. Future work will explore methods to extract this information in order to improve estimates of snow accumulation and ablation patterns. (c) 2012 Elsevier Inc. All rights reserved.
引用
收藏
页码:34 / 48
页数:15
相关论文
共 72 条
  • [1] Evaluating the utility of the ANSA blended snow cover product in the mountains of eastern Turkey
    Akyurek, Zuhal
    Hall, Dorothy K.
    Riggs, George A.
    Sensoy, Aynur
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2010, 31 (14) : 3727 - 3744
  • [2] Armstrong R. L., 1993, ANN GLACIOL, V17, P171
  • [3] AN EARTH-GRIDDED SSM/I DATA SET FOR CRYOSPHERIC STUDIES AND GLOBAL CHANGE MONITORING
    ARMSTRONG, RL
    BRODZIK, MJ
    [J]. SATELLITE MONITORING OF THE EARTH'S SURFACE AND ATMOSPHERE, 1995, 16 (10): : 155 - 163
  • [4] Mountain hydrology of the western United States
    Bales, Roger C.
    Molotch, Noah P.
    Painter, Thomas H.
    Dettinger, Michael D.
    Rice, Robert
    Dozier, Jeff
    [J]. WATER RESOURCES RESEARCH, 2006, 42 (08)
  • [5] Combining binary decision tree and geostatistical methods to estimate snow distribution in a mountain watershed
    Balk, B
    Elder, K
    [J]. WATER RESOURCES RESEARCH, 2000, 36 (01) : 13 - 26
  • [6] Barrett T. P., 2005, NATURE, V438, P303
  • [7] A satellite snow depth multi-year average derived from SSM/I for the high latitude regions
    Biancamaria, Sylvain
    Mognard, Nelly M.
    Boone, Aaron
    Grippa, Manuela
    Josberger, Edward G.
    [J]. REMOTE SENSING OF ENVIRONMENT, 2008, 112 (05) : 2557 - 2568
  • [8] Satellite-based high latitude snow volume trend, variability and contribution to sea level over 1989/2006
    Biancamaria, Sylvain
    Cazenave, Anny
    Mognard, Nelly M.
    Llovel, William
    Frappart, Frederic
    [J]. GLOBAL AND PLANETARY CHANGE, 2011, 75 (3-4) : 99 - 107
  • [9] The influence of stratigraphy on microwave radiation from natural snow cover
    Boyarskii, DA
    Tikhonov, VV
    [J]. JOURNAL OF ELECTROMAGNETIC WAVES AND APPLICATIONS, 2000, 14 (09) : 1265 - 1285
  • [10] Chang A.T. C., 1976, J GLACIOL, V16, P23, DOI [10.1017/S0022143000031415, DOI 10.1017/S0022143000031415]