Hydrodynamic-phytoplankton model for short-term forecasts of phytoplankton in Lake Taihu, China

Phytoplankton biomass is an important factor for short-term forecasts of algal blooms. Our new hydrodynamic-phytoplankton model is primarily intended for simulating the spatial and temporal distribution of phytoplankton in Lake Taihu within a time frame of 1-5 days. The model combines two modules: a simple phytoplankton kinetics module for growth and loss; and a mass-transport module, which defines phytoplankton transport horizontally with a two dimensional hydrodynamic model. To adapt field data for model input and calibration, we introduce two simplifications: (a) exclusion of some processes related to phytoplankton dynamics like nutrient dynamics, sediment resuspension, mineralization and nitrification, and (b) use of monthly measured data of the nutrient state. Chlorophyll-α concentration, representing phytoplankton biomass, is the only state variable in the model. A sensitivity analysis was carried out to identify the most sensitive parameter set in the phytoplankton kinetics module. The model was calibrated with field data collected in 2008 and validated with additional data obtained in 2009. A comparison of simulated and observed chlorophyll-α concentration for 33 grid cells achieved an accuracy of 78.7%. However, mean percent error and mean absolute percent error were 13.4% and 58.2%, respectively, which implies that further improvement is necessary, e.g. by reducing uncertainty of the model input and by an improved parameter calibration.     

Structural uncertainty assessment in a discharge simulation model

Abstract

A major goal in hydrological modelling is to identify and quantify different sources of uncertainty in the modelling process. This paper analyses the structural uncertainty in a streamflow modelling system by investigating a set of models with increasing model structure complexity. The models are applied to two basins: Kielstau in Germany and XitaoXi in China. The results show that the model structure is an important factor affecting model performance. For the Kielstau basin, influences from drainage and wetland are critical for the local runoff generation, while for the XitaoXi basin accurate distributions of precipitation and evapotranspiration are two of the determining factors for the success of the river flow simulations. The derived model uncertainty bounds exhibit appropriate coverage of observations. Both case studies indicate that simulation uncertainty for the low-flow period contributes more to the overall uncertainty than that for the peak-flow period, although the main hydrological features in these two basins differ greatly.

Citation Zhang, X. Y., Hörmann, G., Gao, J. F. & Fohrer, N. (2011) Structural uncertainty assessment in a discharge simulation model. Hydrol. Sci. J. 56(5), 854–869.     

Development of storage capacity and morphology of the Aswan High Dam Reservoir

ABSTRACT

A digital elevation model (DEM), as well as satellite images, was used to detect the changes in the morphology and storage capacity of the Aswan High Dam Reservoir (AHDR) over the past five decades. Study findings indicate that the total storage capacity of the AHDR estimated by the DEM decreased by 12%. This decrease is mainly in the live and the dead storage capacities. The morphology of the reservoir changed in the southern part and at the entrance of the lacustrine part. A gradual conversion of the entrance to the riverine part was observed. The surface area of the AHDR decreased at low water levels because of sedimentation. The average reduction of the surface area between water levels of 140 and 168 m a.s.l. is about 15%, which is equivalent to almost 10 km³.