论文标题
通过标准化指数和区域气候模型对气候变化对地下水干旱的影响
Impacts of climate change on groundwater droughts by means of standardized indices and regional climate models
论文作者
论文摘要
本文研究了利用区域预测和标准化指数的气候变化对地下水干旱的影响：标准化降水指数（SPI），标准降水蒸发指数（SPEI）和标准化的地下水指数（SGI）。采用了使用监测井中收集的历史降水，温度数据和水位的方法，首先研究了每个孔的气象和地下水指数之间的可能相关性。然后，如果存在相关性，则使用线性回归分析来建模SGIS和SPI之间的关系以及SGIS和SPEI。在不同的气候场景（RCP 4.5和RCP 8.5）下，使用SPI和SPEI预测从SPI和SPEI投影中推断出未来的SGI（RCP 4.5和RCP 8.5）。该方法已应用于意大利托斯卡纳（意大利）收集的数据，该数据的历史系列每日气候变量（自1934年以来）和涵盖2005 - 2020年期间的16口井的每日记录。对地下水的影响是在简短（2006-2035），媒介（2036-2065）和长期（2066-2095）中计算出来的。分析表明，在历史时期，对于大多数监测井，SGIS和SPIS或SPEI之间存在良好的相关性。在全球变暖的情况下，温度对蒸散现象的影响不容忽视，因此SGI-SPEI的关系似乎更适合预测地下水干旱。根据这些关系，几乎所有井中对地下水水平的负面影响估计了所需数据类型及其简单性，该方法可以应用于感兴趣的不同领域，以在气候变化场景下快速估算地下水可用性。
This paper investigates the impacts of climate change on groundwater droughts making use of regional projections and standardized indices: the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Groundwater Index (SGI). The method adopted, using historical precipitation and temperature data and water levels collected in monitoring wells, first investigates the possible correlations between meteorological and groundwater indices at each well. Then, if there is a correlation, a linear regression analysis is used to model the relationships between SGIs and SPIs, and SGIs and SPEIs. The same relationships are used to infer future SGIs from SPI and SPEI projections obtained by means of an ensemble of Regional Climate Models (RCMs), under different climate scenarios (RCP 4.5 and RCP 8.5). This methodology has been applied to data collected in Tuscany (Italy), where historical series of daily climate variables (since 1934) and daily records for 16 wells, covering the period 2005-2020, are available. The impacts on groundwater have been computed in the short (2006-2035), medium (2036-2065) and long term (2066-2095). The analysis indicates that, in the historical period and for most of the monitoring wells, there is a good correlation between SGIs and SPIs or SPEIs. In a global warming scenario, the influence of temperature on evapotranspiration phenomena cannot be overlooked so the SGI-SPEI relationships seem more suitable to forecast groundwater droughts. According to these relationships, negative effects on groundwater levels in almost all wells are estimated for the futureDue to the type of data required and its simplicity, this methodology can be applied to different areas of interest for a quick estimate of groundwater availability under climate change scenarios.
