A New Approach for Assessing Groundwater Recharge by Combining GRACE and Baseflow With Case Studies in Karst Areas of Southwest China

Abstract

A new approach combining groundwater storage change (GWSC) derived from Gravity Recovery and Climate Experiment (GRACE) satellite data and baseflow was proposed to estimate groundwater recharge at large spatial scales but a short (monthly) time scale. This method was applied in two typical karst basins of southwest China, the Wujiang River basin (WRB, ∼87,900 km 2 , ∼70% karstification) and Xijiang River Basin (XRB, ∼360,000 km 2 , ∼44% karstification). The 2006-2012 monthly baseflow was first separated from in situ streamflow through multivariate regression analysis. Groundwater recharge was estimated using separated baseflow and GWSC estimated from GRACE data and observation-based groundwater-level data. The comparison between GRACE-and observation-based recharge in the larger XRB shows better consistency, while that in the smaller WRB shows larger discrepancies. Considering the associated uncertainty (60-93 mm/yr), the 2006-2012 mean recharge in two basins, ranging 199-225 mm/yr (17%-19% of precipitation) is comparable to bulletin-reported estimates (∼145 mm/yr). Both the degree of karstification and aquifer water table depth influence recharge and discharge processes in karst areas of southwest China. The more karstic WRB exhibits more rapid infiltration (due to more developed permeable epikarst zone) and higher discharge capability (due to more developed underground drainage systems), particularly during dry periods (2009, 2011, and winter). Baseflow exhibits a shorter time lag to recharge and GWSC in the XRB than WRB owing to more quick flow, lower storage with more rapid infiltration, and shorter mean groundwater residence time. Observation-based monthly recharge reflects different rainfall-infiltration-runoff processes under different rainfall intensities, particularly in the WRB. Plain Language SummaryGroundwater recharge is a critical water budget component. This study proposed a new method to estimate groundwater recharge at large spatial scales but on a short time scale. This method combines the groundwater storage changes estimated from gravity satellite data and baseflow (i.e., the main groundwater discharge component) separated from in situ streamflow through multiple regression analysis. We applied this method in two karst basins in southwest China, the Wujiang and Xijiang River Basins. We validated groundwater recharge estimates from gravity satellite data against those only from ground observations. At a larger scale in the Xijiang River Basin, the satellite-and ground-based estimates of groundwater recharge showed better agreement. In the Wujiang River Basin, relatively more rainfall infiltrated into the subsurface to form recharge and more groundwater drained out during dry periods because this basin has a larger proportion of karst areas where the underlying rocks were eroded with large voids and spaces to transfer water. In the Xijiang River Basin, the groundwater storage requires less time to drain out to form baseflow because the flow velocity in this basin is faster. Compared to the gravi...

Global‐Scale Groundwater Recharge Modeling Is Improved by Tuning Against Ground‐Based Estimates for Karst and Non‐Karst Areas

“…(2020). GWR at the scale of drainage basins can be estimated by stream hydrograph separation and by the water budget method (Huang et al., 2023; Levin et al., 2023). Some ground‐based estimation methods include hydrological modeling (e.g., Eilers et al., 2007).…”

“…The first two types of methods were used to determine about 80% of the >5,000 local GWR estimates compiled by Moeck et al (2020). GWR at the scale of drainage basins can be estimated by stream hydrograph separation and by the water budget method (Huang et al, 2023;Levin et al, 2023). Some ground-based estimation methods include hydrological modeling (e.g., Eilers et al, 2007).…”

Impact of Climate Change on the Spatio-Temporal Variation in Groundwater Storage in the Guangdong–Hong Kong–Macao Greater Bay Area

“…There was an increasing trend of GWSA in the GBA over the period 2005-2016. consistency between the trend of calculated GWSA and the observed data indicates the combination of GRACE and CLM5.0 simulation can better reflect variations in GW However, differences occurred in 2009, which were possibly caused by the mismatch tween the calculated GWSA and the groundwater table depth observations. Since the tual area of the GBA is 56,000 km 2 , with strong heterogenic hydrological and geolog conditions, GRACE data with a coarse resolution cannot capture these heterogeneities original spatial resolution of GRACE data is 1° × 1° [64]). There was also a large ga spatial scale between the sites and GRACE data, and the spatial scale mismatch cau part of the difference [65].…”

Using Baseflow Ensembles for Hydrologic Hysteresis Characterization in Humid Basins of Southeastern China

“…Baseflow consists of the confluence of soil intermediate flow formed by infiltration of precipitation to replenish soil reservoirs to saturation and subsurface runoff (Gnann et al., 2019; Singh et al., 2019). Baseflow is the primary supply of water for river runoff when there is no precipitation in the basin or during periods of drought, and it is essential to maintain the health of river ecosystems (Huang et al., 2023; Zhang et al., 2020) (Figure 1). Furthermore, baseflow is a critical metric of groundwater discharge rate that also plays a significant role in hydrologic analysis, groundwater characterization, hydrologic modeling, and water resource management (Cochand et al., 2019; Lyu et al., 2022).…”