Assessment of runoff,water and sediment quality in the Selenga River basin aided by a web-based geoservice

The Selenga River is the main artery feeding Lake Baikal. It has a catchment of ~450000 km² in the boundary region between Northern Mongolia and Southern Siberia. Climate, land use and dynamic socioeconomic changes go along with rising water abstractions and contaminant loads originating from mining sites and urban wastewater. In the future, these pressures might have negative impacts on the ecosystems of Lake Baikal and the Selenga River Delta, which is an important wetland region in itself and forms the last geobiochemical barrier before the Selenga drains into Lake Baikal. The following study aims to assess current trends in hydrology and water quality in the Selenga-Baikal basin, identify their drivers and to set up models (WaterGAP3 framework and ECOMAG) for the prediction of future changes. Of particular relevance for hydrological and water quality changes in the recent past were climate and land use trends as well as contaminant influx from mining areas and urban settlements. In the near future, additional hydrological modifications due to the construction of dams and abstractions/water diversions from the Selenga’s Mongolian tributaries could lead to additional alterations.     

Lake ice simulation using a 3D unstructured grid model

Ocean Dynamics - We develop a single-class ice and snow model embedded inside a 3D hydrodynamic model on unstructured grids and apply it to lake studies using highly variable mesh resolution. The...     

Undersea Buried Pipeline Reconstruction Based on the Level Set and Inverse Multiquadric Regularization Method

The electric inversion technique reconstructs the subsurface medium distribution from acquired data. On the basis of electric inversion, objects buried under the earth or seabed, such as pipelines and unexploded ordnance, are detected and located in a contactless manner. However, the process of accurately reconstructing the shape of the target object is challenging because electric inversion is a nonlinear and ill-posed problem. In this work, we present an inverse multiquadric (IMQ) regularization method based on the level set function for reconstructing buried pipelines. In the case of locating underwater objects, the unknown inversion area is split into two parts, the background and the pipeline with known conductivity. The geometry of the pipeline is represented based on the level set function for achieving a noiseless inversion image. To obtain a binary image, the IMQ is used as the regularization term, which 'pushes' the level set function away from 0. We also provide an appropriate method to select the bandwidth and regularization pa-rameters for the IMQ regularization term, resulting in reconstructed images with sharp edges. The simulation results and analysis show that the proposed method performs better than classical inversion methods.