Strategic assessment of the magnitude and impacts of sand mining in Poyang Lake, China

Planning for the extraction of aggregates is typically dealt with at a case to case basis, without assessing environmental impacts strategically. In this study we assess the impact of sand mining in Poyang Lake, where dredging began in 2001 after sand mining in the Yangtze River had been banned. In April 2008 concern over the impact on the biodiversity led to a ban on sand mining in Poyang Lake until further plans could be developed. Planning will require consideration of both sand extraction in relation to available sediment resources and also environmental impacts within the context of future demand for sand in the lower Yangtze Valley. We used pairs of near-infrared (NIR) Aster satellite imagery to estimate the number of vessels leaving the lake. Based on this we calculated a rate of sand extraction of 236 million m3 year-1 in 2005–2006. This corresponds to 9% of the total Chinese demand for sand. It qualifies Poyang Lake as probably the largest sand mining operation in the world. It also indicates that sand extraction currently dominates the sediment balance of the lower Yangtze River. A positive relation between demand for sand and GDP, revealed by historic data from the USA, suggests that the current per capita demand for sand in China might increase in the near future from 2 to 4 m3 year-1. We review various environmental impacts and question whether it will be possible to preserve the rich biodiversity of the lake, while continuing at the same time satisfying the increasing Chinese demand for sand. Finally we review alternative options for sand mining, in order to relieve the pressure from the Poyang Lake ecosyste

Variational assimilation of remotely sensed flood extents using a 2-D flood model

A variational data assimilation (4D-Var) method is proposed to directly assimilate flood extents into a 2-D dynamic flood model to explore a novel way of utilizing the rich source of remotely sensed data available from satellite imagery for better analyzing or predicting flood routing processes. For this purpose, a new cost function is specially defined to effectively fuse the hydraulic information that is implicitly indicated in flood extents. The potential of using remotely sensed flood extents for improving the analysis of flood routing processes is demonstrated by applying the present new data assimilation approach to both idealized and realistic numerical experiments

Multi-satellite data of land surface temperature, lakes area, and water level for hydrological model calibration and validation in the Yangtze river Basin

This study shows the feasibility of the combined use of multi-satellite data and an energy-water balance model for improving the estimates of water fluxes over time and distributed in space in the Yangtze River basin. In particular, a new methodology is used to constrain an internal model variable of the distributed hydrological model based on the satellite land surface temperature. The hydrological FEST-EWB model (flash flood event-based spatially distributed rainfall-runofftransformation-energy water balance model) with its energy-water balance scheme allows to continuously compute in time and distributed in space soil moisture and evapotranspiration (ET) fluxes thanks to a double link with satellite-derived data as input parameters (e.g., LAI) and as variables for model states' updates as the land surface temperature (LST). This LST was used to calibrate the model soil parameters instead of using only dedicated ground measurements. The effects of the calibration procedure were evaluated at four available river cross-sections along the Yangtze River, considering also the presence of the Three Gorges Dam. Flow duration curves were also considered to understand the volume storages' changes. The Poyang and Dongting Lakes dynamics were simulated from FEST-EWB and compared against satellite water extended from MERIS and ASAR data and water levels from LEGOS altimetry data (Topex/Poseidon). The FEST-EWB model was run at 0.009° spatial resolution and three hours of temporal resolutions for the period between 2003 and 2006. Absolute errors on LST estimates of 3 °C were obtained while discharge data were simulated with errors of 10%. Errors on the water area extent of 7% and on the water level of 3% were obtained for the two lakes

Strategic assessment of the magnitude and impacts of sand mining in Poyang Lake, China

Planning for the extraction of aggregates is typically dealt with at a case to case basis, without assessing environmental impacts strategically. In this study we assess the impact of sand mining in Poyang Lake, where dredging began in 2001 after sand mining in the Yangtze River had been banned. In April 2008 concern over the impact on the biodiversity led to a ban on sand mining in Poyang Lake until further plans could be developed. Planning will require consideration of both sand extraction in relation to available sediment resources and also environmental impacts within the context of future demand for sand in the lower Yangtze Valley. We used pairs of near-infrared (NIR) Aster satellite imagery to estimate the number of vessels leaving the lake. Based on this we calculated a rate of sand extraction of 236 million m3 year-1 in 2005–2006. This corresponds to 9% of the total Chinese demand for sand. It qualifies Poyang Lake as probably the largest sand mining operation in the world. It also indicates that sand extraction currently dominates the sediment balance of the lower Yangtze River. A positive relation between demand for sand and GDP, revealed by historic data from the USA, suggests that the current per capita demand for sand in China might increase in the near future from 2 to 4 m3 year-1. We review various environmental impacts and question whether it will be possible to preserve the rich biodiversity of the lake, while continuing at the same time satisfying the increasing Chinese demand for sand. Finally we review alternative options for sand mining, in order to relieve the pressure from the Poyang Lake ecosyste