Abstract. Alluvial fans are highly heterogeneous due to complex depositional processes, which make difficult to characterize the spatial distribution of the hydraulic conductivity K. An original methodology is developed to identify the spatial statistical parameters (mean, variance, correlation range) of the hydraulic conductivity in a three-dimensional setting by using geological and geophysical data. The Chaobai River alluvial fan in the Beijing Plain, China, is used as an example to test the proposed approach. Due to the non-stationary property of the K distribution in the alluvial fan, a multi-zone parameterization approach is applied to analyze the conductivity statistical properties of different hydrofacies in the various zones. The composite variance in each zone is computed to describe the evolution of the conductivity along the flow direction. Consistently with the scales of the sedimentary transport energy, the results show that conductivity variances of fine sand, medium-coarse sand, and gravel decrease from the upper (Zone 1) to the lower (Zone 3) portion along the flow direction. In Zone 1, sediments were moved by higher-energy flooding, which induces bad sorting and larger conductivity variances. The composite variance confirms this feature with statistically different facies from Zone 1 to Zone 3. The results of this study provide insights to improve our understanding on conductivity heterogeneity and a method for characterizing the spatial distribution of K in alluvial fans.

Abstract. Land subsidence caused by groundwater over-pumping threatens the sustainable development in Beijing. Hazard assessments of land subsidence can provide early warning information to improve prevention measures. However, uncertainty and fuzziness are the major issues during hazard assessments of land subsidence. We propose a method that integrates fuzzy set theory and weighted Bayesian model (FWBM) to evaluate the hazard probability of land subsidence measured by Interferometric Synthetic Aperture Radar (InSAR) technology. The model is structured as a directed acyclic graph. The hazard probability distribution of each factor triggering land subsidence is determined using Bayes’ theorem. Fuzzification of the factor significance reduces the ambiguity of the relationship between the factors and subsidence. The probability of land subsidence hazard under multiple factors is then calculated with the FWBM. The subsidence time-series obtained by InSAR is used to infer the updated posterior probability. The upper and middle parts of the Chaobai River alluvial fan is taken as a case-study site, which locates the first large-scale Emergency Groundwater Resource Region in Beijing plain. The results show that rates of groundwater level decrease larger than 1 m/y in the confined and unconfined aquifers, compressible layer thicknesses between 160 and 170 m, and Quaternary thicknesses between 400 and 500 m yield maximum hazard probabilities of 0.65, 0.68, 0.32, and 0.35, respectively. The overall hazard probability of land subsidence in the study area decreased from 51.3 % to 28.3 % between 2003 and 2017 due to lower rates of groundwater level decrease. This study provides useful insights for decision-makers to select different approaches for land subsidence prevention.