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识别加利福尼亚州中谷南部地表水供应对气候变化的影响。

Identifying climate change impacts on surface water supply in the southern Central Valley, California.

机构信息

Department of Land, Air and Water Resource, University of California-Davis, 1 Shields Ave, Davis, CA 95616, USA.

Department of Civil and Environmental Engineering, University of California-Davis, 1 Shields Ave, Davis, CA 95616, USA.

出版信息

Sci Total Environ. 2021 Mar 10;759:143429. doi: 10.1016/j.scitotenv.2020.143429. Epub 2020 Nov 1.

Abstract

Mountain regions in arid and semi-arid climates, such as California, are considered particularly sensitive to climate change because global warming is expected to alter snowpack storage and related surface water supply. It is therefore important to accurately capture snowmelt processes in watershed models for climate change impact assessment. In this study we use the Soil and Water Assessment Tool (SWAT) to estimate projected changes in snowpack and streamflow in four alpine tributaries to the agriculturally important but less studied southern Central Valley, California. Watershed responses are evaluated for four CMIP5 climate models (HadGEM_ES, CNRM-CM5, CanESM2 and MIROC5) and two emission scenarios (RCP 4.5 and RCP 8.5) for 2020-2099. SWAT models are calibrated following a dual-objective, lumped calibration approach with an automatic calibration against observed streamflow (stage 1) and a manual calibration against reconstructed Parallel Energy Balance (ParBal) snow water equivalent (SWE) data (stage 2). Results indicate that under a warming climate, peak streamflow is expected to increase 0.5-4 times in magnitude in the coming decades and to arrive 2-4 months earlier in the year because of earlier snowmelt. In the foreseeable future, snow cover will reduce gradually in the lower elevations and diminish at higher rates at higher elevation towards the end of the 21st century. Surface water supply is predicted to increase in the southern Central Valley under the evaluated scenarios but increased temporal variability (wetter wet seasons and drier dry seasons) will create new challenges for managing supply. The study further highlights that the use of remote sensing based, reconstructed SWE data could fill the current gap of limited in-situ SWE observations to improve the snow calibration of SWAT to better predict climate change impacts in semi-arid, snow-dominated watersheds.

摘要

干旱和半干旱气候条件下的山区,如加利福尼亚,被认为对气候变化特别敏感,因为预计全球变暖将改变积雪储存和相关的地表水供应。因此,在气候变化影响评估中,准确捕捉流域模型中的融雪过程非常重要。在这项研究中,我们使用土壤和水评估工具(SWAT)来估计加利福尼亚南部中央谷地农业重要但研究较少的四个高山支流的积雪和径流量的预计变化。对于四个 CMIP5 气候模型(HadGEM_ES、CNRM-CM5、CanESM2 和 MIROC5)和两个排放情景(RCP 4.5 和 RCP 8.5),评估了流域的响应情况,时间范围为 2020 年至 2099 年。SWAT 模型采用双目标、集中式校准方法进行校准,该方法自动根据观测到的流量进行校准(第 1 阶段),并根据重建的平行能量平衡(ParBal)积雪水当量(SWE)数据进行手动校准(第 2 阶段)。结果表明,在气候变暖的情况下,未来几十年,峰值径流量预计将增加 0.5 到 4 倍,并且由于融雪提前,流量将提前 2 到 4 个月到达。在可预见的未来,低海拔地区的积雪将逐渐减少,而高海拔地区的积雪将以更高的速率减少,到 21 世纪末。在评估的情景下,南加州中央谷地的地表水资源预计会增加,但增加的时间变异性(湿润的雨季和干燥的旱季)将为管理供应带来新的挑战。该研究进一步强调,使用基于遥感的重建 SWE 数据可以填补目前现场 SWE 观测有限的空白,从而改善 SWAT 的积雪校准,以更好地预测半干旱、以雪为主的流域的气候变化影响。

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