Modeling of Mass Balance Variability and Its Impact on Water Discharge from the Urumqi Glacier No. 1 Catchment, Tian Shan, China
Modeling of Mass Balance Variability and Its Impact on Water Discharge from the Urumqi Glacier No. 1 Catchment, Tian Shan, China
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DOI：
10.3390/w12123297
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发表时间：
2020-11
期刊：
影响因子：
3.4
通讯作者：
Kira Thiel;A. Arndt;Puyu Wang;Huilin Li;Zhong-qin Li;C. Schneider
中科院分区：
文献类型：
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作者：
Kira Thiel;A. Arndt;Puyu Wang;Huilin Li;Zhong-qin Li;C. Schneider
乌鲁木齐河发源于天山山脉，在下游地区的供水方面发挥着重要作用。在其源头，乌鲁木齐一号冰川（UG1）是最大的排水量冰川。评估其对该地区不断变化的气候条件的反应对于量化未来的可用水量至关重要。我们在这里将 COSIPY（PYthon 中的耦合积雪和冰表面能量和质量平衡模型）应用于 UG1，实现了一种新的反照率参数化，该参数化在遥感观测到的逐像素基础上集成了特定地点的裸冰反照率值。我们从三方面评估模型性能：基于（1）表面质量平衡（SMB）和（2）排水的长期测量数据进行定量评估，以及（3）将模拟雪线高度与基于延时摄影的模拟雪线高度进行定性比较。将建模的 SMB 与消融桩的年平均数据进行比较表明，包含新反照率参数化的 COSIPY 占测量中观察到的方差的 57.6%。原始反照率参数化的性能仅稍差（57.1%）。模型化 SMB 与冰川学 SMB 之间的冰川范围比较显示出高度一致性。在放电预测方面，COSIPY 很好地再现了放电季节的开始和持续时间。整个流域的估计流量显示出与测量时间序列精确匹配的缺陷，但捕获了年际变化。
Originating in the Tian Shan mountains, Urumqi River plays a key role in terms of water supply to downstream areas. In its headwaters, Urumqi Glacier No. 1 (UG1) is the largest glacier contributing to water discharge. Assessing its response to the changing climatic conditions in the area is of major importance to quantify future water availability. We here apply COSIPY, a COupled Snowpack and Ice surface energy and mass balance model in PYthon, to UG1, implementing a new albedo parameterization which integrates site-specific bare-ice albedo values on a pixel-by-pixel basis observed by remote sensing. We assess model performance threefold: quantitatively based on long-term measurement data of (1) surface mass balance (SMB) and (2) water discharge as well as qualitatively (3) comparing simulated snow line altitudes to such imated on the basis of time-lapse photography. Comparison of the modeled SMB with annually-averaged data from ablation stakes reveals that COSIPY including the new albedo parameterization accounts for 57.6% of the variance observed in the measurements. The original albedo parameterization performs only slightly inferior (57.1%). Glacier-wide comparison between modeled and glaciological SMB shows high agreement. In terms of discharge prediction, COSIPY reproduces onset and duration of the discharge season well. Estimated discharge from the whole catchment shows shortcomings in exactly matching the measured times series, but interannual variability is captured.