Comparing potential recharge estimates from three Land Surface Models across the Western US.
Comparing potential recharge estimates from three Land Surface Models across the Western US.
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DOI：
10.1016/j.jhydrol.2016.12.028
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发表时间：
2017-02
影响因子：
6.4
通讯作者：
R. Niraula;T. Meixner;H. Ajami;M. Rodell;D. Gochis;C. Castro
中科院分区：
文献类型：
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作者：
R. Niraula;T. Meixner;H. Ajami;M. Rodell;D. Gochis;C. Castro
地下水是美国西部的主要水源。然而，由于补给过程的复杂性和直接观测的挑战，该区域的补给估计有限。陆面模式（LSMs）可能是一个有价值的工具，估计目前的补给和预测的变化，由于未来的气候变化。在这项研究中，模拟三个LSM（诺亚，马赛克和维克）从北美陆地数据同化系统（NLDAS-2）获得的估计潜在的补给在美国西部。对该区域几个含水层的模拟补给与已公布的补给估计进行了比较。整个研究流域的年补给量与降水量的比率变化范围为0.01%至15%的马赛克，3.2%至42%的诺亚，和6.7%至31.8%的维克模拟。Mosaic一直低估了所有流域的补给量。诺亚在较湿润的盆地中捕获了相当好的补给，但在较干燥的盆地中高估了它。维克略微高估了干旱盆地的补给，略微低估了湿润盆地的补给。虽然各模型的年平均补给值各不相同，但这些模型在确定该区域的高补给区和低补给区方面是一致的。模型同意在整个地区的春季主要发生在充电的季节性。总体而言，我们的研究结果强调，LSM有潜力捕捉的空间和时间模式，以及在大尺度上的季节性补给。因此，LSM（特别是维克和诺亚）可用作估计数据有限区域未来再充的工具。
Groundwater is a major source of water in the western US. However, there are limited recharge estimates in this region due to the complexity of recharge processes and the challenge of direct observations. Land surface Models (LSMs) could be a valuable tool for estimating current recharge and projecting changes due to future climate change. In this study, simulations of three LSMs (Noah, Mosaic and VIC) obtained from the North American Land Data Assimilation System (NLDAS-2) are used to estimate potential recharge in the western US. Modeled recharge was compared with published recharge estimates for several aquifers in the region. Annual recharge to precipitation ratios across the study basins varied from 0.01% to 15% for Mosaic, 3.2% to 42% for Noah, and 6.7% to 31.8% for VIC simulations. Mosaic consistently underestimates recharge across all basins. Noah captures recharge reasonably well in wetter basins, but overestimates it in drier basins. VIC slightly overestimates recharge in drier basins and slightly underestimates it for wetter basins. While the average annual recharge values vary among the models, the models were consistent in identifying high and low recharge areas in the region. Models agree in seasonality of recharge occurring dominantly during the spring across the region. Overall, our results highlight that LSMs have the potential to capture the spatial and temporal patterns as well as seasonality of recharge at large scales. Therefore, LSMs (specifically VIC and Noah) can be used as a tool for estimating future recharge in data limited regions.