# Assessing Groundwater Level with a Unified Seasonal Outlook and Hydrological Modeling Projection
## 1 Introduction  
Groundwater is the second-largest accessible source of freshwater after frozen water [1]. Almost half of the world's population has access to groundwater for drinking purposes, which is considered a cleaner and more reliable water source than other sources [2]. Wet seasons may produce ahigh groundwater table, whereas dry seasons may result in groundwater depletion and degradation in water quality [3]. Groundwater management should be taken in advance to preserve water resources before the groundwater reaches a deficient level [2]. [PERSON] et al. [3] used seasonal rainfall forecasts and a lumped groundwater model in simulations to predict the groundwater level at 21 locations in the United Kingdom (UK) up to 3 months into the future. [PERSON] et al. [4] described the development of Hydrological Outlook UK (HOUK), a seasonal hydrological forecasting service providing streamflow and groundwater level forecasts for the next 3 months. [PERSON] et al. [5] presented the Global Flood Awareness System (GloFAS), coupling seasonal meteorological forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) with a hydrological model to provide openly available probabilistic estimates of river flow for a global river network up to 4 months ahead. The existing works used the seasonal outlook forecast to assess the water resource problems using some hydrological or statistical models. Here, this study tried to utilize seasonal forecasting by incorporating a physical model to evaluate the variation in the groundwater level. In Taiwan, [PERSON] et al. [6] pointed out that, although there has been no significant change in annual rainfall over the last 40 years, the ratio of typhoon precipitation to total precipitation has increased from 15% in the 1970s to 30% in the 2000s. According to the statistics, approximately 60% of the rainfall makes its way into the sea via Taiwan's short and fast-flowing rivers. The annual consumption of surface water accounts for a mere 12.1% of total rainfall, and it is mainly extracted from reservoirs and rivers, with only 5.6% coming from groundwater [7]. Increasing the use of surface water and accurately assessing the amount of groundwater, as supportive water supply sources, can improve the effectiveness of water use management during dry periods. Moreover, groundwater management standards, such as the allowable extraction rate given the different groundwater levels, need to be identified to enhance sustainable management. Rainfall estimation, as a function of analyzing the possibilities of rainfall in seasonal forecasts, is critical for the effective management of water resources. However, a stand-alone use of seasonal weather forecasts to assess groundwater resources with hydrological simulations might produce unreliable results [8; 9; 10]. A relatively good temporal resolution, with at least daily intervals, is an essential requirement for hydrological modeling at the watershed scale [10; 11]. Weather generating models have been extensively applied to generate synthetic daily weather sequences as inputs to drive hydrological models [12]. [PERSON] and [PERSON] [13] used a weather generating model to predict future precipitation and temperature using general circulation models (GCMs). A generalized watershed loading functions (GWLF) model was proposed and applied to evaluate the effects of global warming on streamflow in New York watersheds [13; 14; 15]. [PERSON] et al. [16] incorporated the climate change scenarios from the Intergovernmental Panel on Climate Change (IPCC) into the GWLF hydrological model to provide an integrated system. The Taiwan Water Resources Assessment Program to Climate Change (TaiWAP) proposed a dynamic decision support model to assess the vulnerability of water resources in Taiwan [17]. According to the above studies, parameter-based watershed models were widely employed to discuss surface and subsurface interactions in early studies.