Evaluation of a Simple Hydraulic Resistance Model Using Flow Measurements Collected in Vegetated Waterways

A simple idealized model to describe the hydraulic resistance caused by vegetation is compared to results from flow experiments conducted in natural waterways. Two field case studies are considered: fixed-point flow measurements in a Green River (case 1) and vessel-borne flow measurements along a cross-section with floodplains in the river Rhine (case 2). Analysis of the two cases shows that the simple flow model is consistent with measured flow velocities and the present vegetation characteristics, and may be used to predict a realistic Manning resistance coefficient. From flow measurements in the river floodplain (case 2) an estimate was made of the equivalent height of the drag dominated vegetation layer, as based on measured flow characteristics. The resulting height corresponds well with the observed height of vegetation in the floodplain. The expected depth-dependency of the associated Manning resistance coefficient for could not be detected due to lack of data for relatively shallow flows. Furthermore, it was shown that topographical variations in the floodplain may have an important impact on the flow field, which should not be mistaken as roughness effects.

A Stochastic Model Approach for Optimisation of Lowland River Restoration Works

Over the course of centuries, river systems have been heavily trained for the purpose of safe discharge of water, sediment and ice, and improves navigation. Traditionally, dikes are used to be reinforced and heightened to protect countries from ever higher flood levels. Other types of solutions than technical engineering solutions, such as measures to increase the flood conveyance capacity（e.g., lowering of groynes and floodplains, setting back dikes） become more popular. These solutions may however increase the river bed dynamics and thus impact negatively navigation, maintenance dredging and flood safety. A variety of numerical models are available to predict the impact of river restoration works on river processes. Often little attention is paid to the assessment of uncertainties. In this paper, we show how we can make uncertainty explicit using a stochastic approach. This approach helps identifying uncertainty sources and assessing their contribution to the overall uncertainty in river processes. The approach gives engineers a better understanding of system behaviour and enables them to intervene with the river system, so as to avoid undesired situations. We illustrate the merits of this stochastic approach for optimising lowland river restoration works in the Rhine in the Netherlands.

A prototype web-based analysis platform for drought monitoring and early warning

It has long been recognized that an effective drought monitoring and early warning system,which provides functions for real-time condition monitoring and prediction,risk assessment,information dissemination and response recommendation,is very important for the preparedness for and mitigation of drought impacts.In this article,we review the currently existing drought monitor and early warning systems,discuss applicable remote sensing datasets and drought indicators and present the development of a web-based quasi-real-time Global Drought Monitoring&Analysis Platform(Web-GDMAP).The Web-GDMAP is built upon a series of indicators derived from multi-source satellite remote sensing data and various other sources of data.From a technical perspective,the Web-GDMAP system includes a series of components from data storage,model implementation and distribution,to client-side visualization and user intuitive interaction.From a theoretical perspective,the Web-GDMAP system integrates multi-indicators on different aspects of drought,including anomalies in precipitation,anomalies in land surface thermal and vegetation conditions,water deficit of soil and plants,etc.Several case studies on applying the developed Web-GDMAP in the Asian region are demonstrated.Further improvements and perspectives are discussed.