Advancing groundwater hydrology in a data-scarce mountainous catchment on the Tibetan plateau: challenges and innovations

Climate warming is altering the water cycle on the Tibetan Plateau (TP). Groundwater is a crucial component for human use within this cycle. However, studying groundwater on the TP faces significant challenges due to data scarcity, complex topography, and intricate geology. This thesis aims to understand the groundwater in the Maqu catchment, a data-scarce area on the TP, and to explore the importance of groundwater modeling in mountainous regions.
In Chapter 2, intensive fieldwork was carried out to obtain a comprehensive dataset, including borehole core lithology, soil thickness, altitude, hydrogeological data (groundwater level and aquifer test data), and hydrogeophysical data (MRS, ERT, and TEM). The hydrogeological surveys reveal that groundwater flows from the west to the east, recharging the Yellow River. The hydraulic conductivity ranges from 0.2 m d-1 to 12.4 m d-1. The MRS soundings results, i.e., water content and hydraulic conductivity, confirmed the presence of an unconfined aquifer in the flat eastern area. Based on TEM results, the depth of the Yellow River deposits was derived at several places in the flat eastern area, ranging from 50 m to 208 m. Most soil thicknesses, except on the valley floor, are within 1.2 m in the western mountainous area of the catchment, and the soil thickness decreases as the slope increases.
In Chapter 3, the hydrogeochemical composition and stable isotopes (δD and δ18O) of surface water and groundwater samples collected in the Maqu catchment were analyzed to characterize the surface water and groundwater, investigate the contributions of different sources, and determine CO2 consumptions. Different techniques were used, including inverse modeling, end-member mixing analysis (EMMA), and a forward mass balance model. The results indicated that all water samples are of the HCO3-Ca type. Both the surface water and groundwater are of meteoric origin and there is close contact between them (except wetlands). Water in the wetlands is substantially evaporated (0-45%). Calcite and illite generally precipitate, whereas chlorite and CO2 generally dissolve along groundwater flow paths in the east. The mean contributions of fresh surface waters, mountain-front groundwaters, and anthropogenic inputs to the surface water samples are 56%, 16%, and 28%, respectively. Carbonate and silicate weathering are the dominant sources of major cations. Moreover, high CO2 consumption rates in both the surface runoff and groundwater make the Maqu catchment an important carbon sink in the Yellow River Basin.
In Chapter 4, a systematic methodology for integrating diverse datasets from various sources to develop a comprehensive conceptual model for the Maqu catchment is proposed. The approach incorporates a wide range of data including hydrogeological and hydrogeophysical data, bedrock depth information, reanalysis datasets, and satellite-derived gravimetry and altimetry data. Within the framework of the Maqu catchment's hydrogeological conceptual model, the driving forces and state variables are presented; a hydrostratigraphic unit and system parameters are determined; the flow system, hydrogeological boundary conditions, preliminary water balance, and water storage are analyzed. Finally, a one-layer numerical model, with a shallow, unconfined layer is recommended. Based on the numerical model by Yu (2022), the time-varying stages of the Yellow River and reanalysis precipitation data are incorporated into the integrated hydrological model STEMMUS-MODFLOW. The proposed method for developing hydrogeological conceptual models is expected to be readily extended to other data-scarce catchments on the Tibetan Plateau.
In Chapter 5, compared to the previous groundwater model, notable enhancements to the hydraulic conductivity, specific yield, and recharge have been made. These improvements are attributed to the inclusion of additional groundwater level data and MRS-estimated hydraulic conductivities during the calibration process.
Simulating only the downstream flat region may result in severe underestimation of groundwater recharge. The groundwater level in upstream mountainous regions exhibits greater sensitivity to recharge compared to the downstream flat regions. This implies that a more accurate representation of recharge dynamics can be achieved through the calibration process using time-series groundwater level data from the upstream mountainous regions. Consequently, the inclusion of upstream mountainous regions is essential in groundwater modeling.
To extend parameters from points to the entire Maqu catchment, both inverse distance weighting (IDW) and Ordinary cokriging (OCK) are implemented. The performances of simulated results using interpolated hydraulic conductivity, specific yield, and recharge derived from IDW and OCK are generally similar. However, each interpolation method exhibits distinct strengths and limitations. IDW produces smooth interpolated results, leading to good simulations of groundwater levels in data-sparse areas. However, it struggles to adequately capture spatial variabilities in parameters. In contrast, OCK, which integrates diverse spatial information, effectively represents parameter spatial variabilities. Consequently, it yields good simulations in data-sufficient areas but exhibits weaker performance in data-sparse areas.
This thesis contributes to the understanding of groundwater in the data-scarce Maqu catchment on the Tibetan Plateau, and highlights the importance of groundwater modeling in mountainous regions. Both relevant observations and numerical modeling tools are required to advance the understanding of the groundwater system at different temporal and spatial scales under current and future climate conditions in future studies.