Formation Mechanism for Upland Low-Relief Surface Landscapes in the Three Gorges Region, China

Extensive areas with low-relief surfaces that are almost flat surfaces high in the mountain ranges constitute the dominant geomorphic feature of the Three Gorges area. However, their origin remains a matter of debate, and has been interpreted previously as the result of fluvial erosion after peneplain uplift. Here, a new formation mechanism for these low-relief surface landscapes has been proposed, based on the analyses of low-relief surface distribution, swath profiles, χ mapping, river capture landform characteristics, and a numerical analytical model. The results showed that the low-relief surfaces in the Three Gorges area could be divided into higher elevation and lower elevation surfaces, distributed mainly in the highlands between the Yangtze River and Qingjiang River. The analyses also showed that the rivers on both sides of the drainage divide have not yet reached equilibrium, with actively migrating drainage divides and river basins in the process of reorganizing. It was concluded that the low-relief surfaces in the Three Gorges area did not share a common uplift history, and neither were they peneplain relicts, but rather that the effect of “area-loss feedback” caused by river capture has promoted the formation of upland low-relief surface landscapes. A future work aims to present the contribution of accurate dating of low-relief surface landscapes.

IMPACT OF THE THREE GORGES WATER CONSERVANCY PROJECT ON RADIOACTIVITY CONCENTRATION LEVELS IN SURROUNDING WATERS

Large-scale water conservancy projects bear much economic and social significance. However, there is a lack of systematic research on how such projects affect radioactivity levels in regional water bodies. For the first time, the present paper uses data for nearly 10 y at different impoundment levels during construction of the dam to analyze changes in water radioactivity concentration levels in China’s Three Gorges region, in order to provide a valuable reference for evaluating the impact of large-scale water conservancy projects on radioactivity concentration levels. Results show that gross α, gross β, U, Th, 226Ra, 40K, 90Sr and 137Cs levels in the water bodies of the Three Gorges region fall within normal limits and annual effective dose for the adults, children and infants are below the WHO recommended reference level of 0.1 mSv per y. The period where the sample was collected and spatial distribution are the main reasons why some radionuclides are not normally distributed. Different water levels during different periods result in large variations in the levels of certain radionuclides, indicating that water levels can have a strong influence on radionuclide levels in reservoir regions. Hence, when evaluating the impact of large-scale water conservancy projects on radioactivity levels, analysis should be carried out on samples collected during different periods in order to make accurate assessments.

Landslide Monitoring by Integrating Multi-Sensor InSAR Time Series Datasets and Corner Reflectors in the Three Gorges Area

<p>Landslide is one of the major geohazards in the Three Gorges area as a result of steep valley-side slopes and environmental conditions, e.g., high precipitation. To monitor and detect the landslides and rock falls at a regional scale as Three Gorges area, the differential Synthetic Aperture Radar Interferometry (D-InSAR) technology could be more effective and efficient than other conventional geological and geodetic measurements that can be performed only at a few sites with proper accessibility and conditions.</p><p>Over the past few decades, InSAR technology and advanced SAR Interferometry techniques such as Persistent Scatterer Interferometry (PSI) and Small Baseline Subsets (SBAS) have been developed to derive ground displacement over large areas with high-resolution measurement points and acceptable accuracy (cm to mm level). Both PSI and SBAS methods are based on a network of coherent pixels, including natural persistent scatterer (NPS) and artificial corner reflector (CR). NPSs can be easily found in urban areas or rocky regions. However, for landslide monitoring, the NPSs are usually difficult to be identified due to the steepness, vegetated and vulnerable moisture content among the high-risk locations. In this work, multiple SAR datasets including C-band Sentinel-1, L-band ALOS-2 and X-band TerraSAR-X (TSX) are exploited for landslide monitoring along the Yangtze River in the Three Gorges area in China.  Both PSI and SBAS methods are utilized. Besides, stable artificial CRs are deployed on selected sites to evaluate their performance in deriving landslide kinematics. Results are presented and discussed for a better assessment of landslide hazards in the Three Gorges region.</p>

Improvement of model evaluation by incorporating prediction and measurement uncertainty

Numerous studies have been conducted to assess uncertainty in hydrological and non-point source pollution predictions, but few studies have considered both prediction and measurement uncertainty in the model evaluation process. In this study, the cumulative distribution function approach (CDFA) and the Monte Carlo approach (MCA) were developed as two new approaches for model evaluation within an uncertainty condition. For the CDFA, a new distance between the cumulative distribution functions of the predicted data and the measured data was established in the model evaluation process, whereas the MCA was proposed to address conditions with dispersed data points. These new approaches were then applied in combination with the Soil and Water Assessment Tool in the Three Gorges Region, China. Based on the results, these two new approaches provided more accurate goodness-of-fit indicators for model evaluation compared to traditional methods. The model performance worsened when the error range became larger, and the choice of probability density functions (PDFs) affected model performance, especially for non-point source (NPS) predictions. The case study showed that if the measured error is small and if the distribution can be specified, the CDFA and MCA could be extended to other model evaluations within an uncertainty framework and even be used to calibrate and validate hydrological and NPS pollution (H/NPS) models.