GroMoPo Metadata for Qaidam Basin FEFLOW model

Traditional numerical models usually use extensive observed hydraulic-head data as calibration targets. However, this calibration process is not applicable in remote areas with limited or no monitoring data. This study presents an approach to calibrate a large-scale groundwater flow model using the monthly Gravity Recovery and Climate Experiment (GRACE) satellite data, which have been available globally on a spatial grid of 1A degrees in the geographic coordinate system since 2002. A groundwater storage anomaly isolated from the terrestrial water storage (TWS) anomaly is converted into hydraulic head at the center of the grid, which is then used as observed data to calibrate a numerical model to estimate aquifer hydraulic conductivity. The aquifer system in the remote and hyperarid Qaidam Basin, China, is used as a case study to demonstrate the applicability of this approach. A groundwater model using FEFLOW is constructed for the Qaidam Basin and the GRACE-derived groundwater storage anomaly over the period 2003-2012 is included to calibrate the model, which is done using an automatic estimation method (PEST). The calibrated model is then run to output hydraulic heads at three sites where long-term hydraulic head data are available. The reasonably good fit between the calculated and observed hydraulic heads, together with the very similar groundwater storage anomalies from the numerical model and GRACE data, demonstrate that this approach is generally applicable in regions of groundwater data scarcity.

传统数值模型通常以大量实测水头（hydraulic head）数据作为校准目标。然而该校准流程无法适用于监测数据匮乏甚至无监测数据的偏远地区。本研究提出一种基于月度重力恢复与气候实验（Gravity Recovery and Climate Experiment, GRACE）卫星数据的大规模地下水流模型校准方法，该数据自2002年起以地理坐标系下1度空间网格的形式在全球范围内发布。从陆地水储量（terrestrial water storage, TWS）异常中分离提取得到的地下水储量异常，被转换为网格中心处的水头，随后作为实测数据用于校准数值模型以估算含水层水力传导系数。本研究以中国偏远且极端干旱的柴达木盆地含水层系统为案例，验证该方法的适用性。针对柴达木盆地构建了基于FEFLOW的地下水模型，并采用2003-2012年期间由GRACE反演得到的地下水储量异常对模型进行校准，校准过程使用自动估算方法（PEST）。随后运行校准后的模型，输出三个具备长期水头监测数据的站点的水头值。计算所得水头与实测水头间吻合度良好，同时数值模型模拟的地下水储量异常与GRACE反演结果高度相似，这表明该方法可广泛适用于地下水监测数据匮乏的地区。