Combined impacts of uncertainty in precipitation and air temperature on simulated mountain system recharge from an integrated hydrologic model
Combined impacts of uncertainty in precipitation and air temperature on simulated mountain system recharge from an integrated hydrologic model
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DOI：
10.5194/hess-26-1145-2022
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发表时间：
2022-02
影响因子：
6.3
通讯作者：
A. Schreiner‐McGraw;H. Ajami
中科院分区：
文献类型：
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作者：
A. Schreiner‐McGraw;H. Ajami
抽象。山区是世界上的水塔，它产生径流和地下水补给，这一功能在半干旱地区尤为重要。山区系统的补给率很难量化，水文模型提供了一种方法来估计大规模的补给。这些补给估计容易受到各种来源的不确定性，包括模型结构和参数。气象强迫数据集的质量，特别是在山区，是一个很大的不确定性来源，往往被忽视的地下水调查。在这方面的贡献，我们量化的不确定性在降水和空气温度强迫数据集上的模拟地下水补给在山区流域的卡威河在加州，美国。我们利用集成的地表水-地下水模型ParFlow.CLM和水文研究中常用的几个网格数据集，缩小的NLDAS-2，PRISM，Daymet，Gridmet和TopoWx。模拟结果表明，在所有强迫数据集中，山前补给是山区流域水收支的重要组成部分，占年降水量的9%-72%，占邻近中央谷含水层的总山区系统补给的90%左右。在网格化的气温或降水数据集的不确定性，单独评估时，在模拟的水收支的不确定性的类似范围的结果。模拟补给对降水变化（弹性）和气温变化（敏感性）的变化大于1%的降水变化或1 ℃的气温变化的补给变化。融雪总量是造成高水分收支敏感性的主要因素，融雪量受降水和气温强迫的共同影响。在空气温度和降水补给的不确定性的综合效果是添加剂和结果的不确定性水平大致等于个人的不确定性取决于水文气候条件的流域的总和。山地系统补给途径包括山地块体补给、山地含水层补给和山前补给，对气温变化的敏感性低于降水变化。与其他补给途径相比，山前和山块补给对降水变化更敏感。模拟水收支的不确定性程度反映了在山区开发高质量气象强迫数据集的重要性。
Abstract. Mountainous regions act as the water towers of the world by producing streamflow and groundwater recharge, a function that is particularly important in semiarid regions. Quantifying rates of mountain system recharge is difficult, and hydrologic models offer a method to estimate recharge over large scales. These recharge estimates are prone to uncertainty from various sources including model structure and parameters. The quality of meteorological forcing datasets, particularly in mountainous regions, is a large source of uncertainty that is often neglected in groundwater investigations. In this contribution, we quantify the impact of uncertainty in both precipitation and air temperature forcing datasets on the simulated groundwater recharge in the mountainous watershed of the Kaweah River in California, USA. We make use of the integrated surface water–groundwater model, ParFlow.CLM, and several gridded datasets commonly used in hydrologic studies, downscaled NLDAS-2, PRISM, Daymet, Gridmet, and TopoWx. Simulations indicate that, across all forcing datasets, mountain front recharge is an important component of the water budget in the mountainous watershed, accounting for 9 %–72 % of the annual precipitation and ∼90 % of the total mountain system recharge to the adjacent Central Valley aquifer. The uncertainty in gridded air temperature or precipitation datasets, when assessed individually, results in similar ranges of uncertainty in the simulated water budget. Variations in simulated recharge to changes in precipitation (elasticities) and air temperature (sensitivities) are larger than 1 % change in recharge per 1 % change in precipitation or 1 ∘C change in temperature. The total volume of snowmelt is the primary factor creating the high water budget sensitivity, and snowmelt volume is influenced by both precipitation and air temperature forcings. The combined effect of uncertainty in air temperature and precipitation on recharge is additive and results in uncertainty levels roughly equal to the sum of the individual uncertainties depending on the hydroclimatic condition of the watershed. Mountain system recharge pathways including mountain block recharge, mountain aquifer recharge, and mountain front recharge are less sensitive to changes in air temperature than changes in precipitation. Mountain front and mountain block recharge are more sensitive to changes in precipitation than other recharge pathways. The magnitude of uncertainty in the simulated water budget reflects the importance of developing high-quality meteorological forcing datasets in mountainous regions.