Abstract：
In most arid and semi-arid environments, groundwater is one of the precious resources threatened by water table decline and desiccation, thus it must be constantly monitored. Identifying the causes influencing the variations of the subsurface water level, such as meteorological drought, is one approach for monitoring these fluctuations. In the present study, the effect of two meteorological drought indices SPI and SPEI on the fluctuations of the underground water level was evaluated, as was their relationship with the drought index of the subsurface water level (SWI) using multivariate linear regression and M5 decision tree regression. After calculating climatic and hydrological drought indices in a 6-month time window for a long-term statistical period (1989-2018), the semi-deep aquifers of Golestan province, which is located in northern Iran, were considered as a research location for this purpose. The results demonstrated that the effect of meteorological drought does not immediately manifest in the changes of the subsurface water table and the hydrological drought index. By adding the meteorological drought index with a 6-month lag step, the average air temperature, and the total rainfall from the previous 6 months as new variables, the correlation with the SWI index increases, so that in the best-case scenario, the M5 decision tree model provides the best result in predicting the SWI index. The second half of the year yielded a coefficient of determination of 0.92 and an error value of RMSE = 0.27 for the SPEI index. Among the meteorological drought indices, the SPEI index, which is based on precipitation and evapotranspiration, created a stronger link with the SWI index, which highlights the significance of potential evapotranspiration. It is a warning that, as a result of global warming, subsurface water tables in this region may fall in the future.
摘要：
在大多数干旱和半干旱环境中，地下水是受地下水位下降和干燥威胁的宝贵资源之一，因此必须不断监测。确定影响地下水位变化的原因，比如气象干旱，是监测这些波动的一种方法。在本研究中,评价了两个气象干旱指数SPI和SPEI对地下水位波动的影响,使用多元线性回归和M5决策树回归，以及它们与地下水水位干旱指数（SWI）的关系。在长期统计期（1989-2018年）的6个月时间窗口内计算气候和水文干旱指数后，Golestan省的半深含水层,位于伊朗北部，被认为是为此目的的研究地点。结果表明，气象干旱的影响并不能立即体现在地下水位和水文干旱指数的变化中。通过添加滞后6个月的气象干旱指数，平均气温,以及前6个月的总降雨量作为新的变量，与SWI指数的相关性增加，所以在最好的情况下，M5决策树模型在预测SWI指数方面提供了最好的结果。下半年，SPEI指数的确定系数为0.92，误差值为RMSE=0.27。在气象干旱指数中，SPEI指数，这是基于降水和蒸散，与SWI指数建立了更强的联系，这突出了潜在蒸散的重要性。这是一个警告，由于全球变暖，未来该地区的地下水位可能会下降。
