不同碳源对球孢鱼腥藻生长的影响

本文研究了有机碳源和无机碳源对球胞鱼腥藻生长的影响,结果表明:有机碳源中葡萄糖以0.5—1.0μg/mL、蔗糖以5.0μg/mL促进其生长效果最好;无机碳源中,碳酸钠以10.0—15.0μg/mL、碳酸氢钠以10.0μg/mL效果最好。葡萄糖和蔗糖的浓度高低对球孢鱼腥藻叶绿素a的含量没有明显影响,但前者略高于后者。碳酸钠和碳酸氢钠的浓度在5.0μg/mL时均提高了叶绿素a含量。四种碳源都提高了球孢鱼腥藻的同氮活性,有机碳源中蔗糖优于葡萄塘,无机碳源中碳酸钠优于碳酸氢钠。     

Influence of cohesion on California bearing ratio of clay-gravel mixtures

An understanding of the behavior of cohesive sediment is required to solve various engineering problems such as scour around bridge elements, mitigation of soil erosion, pavement design, river bed degradation,stable channel design. Pavement foundation designers principally use the California bearing ratio(CBR)to describe the subgrade and subbase materials and their strength. Several laboratory experiments were done to study the variation in the CBR of cohesive mixtures comprised of clay-gravel m...     

A new concept to forecast the process of suspended sediment accumulation in the bottom sediment of small reservoirs

The new concept presented for forecasting the rate of accumulation of suspended sediment in reservoir water in the bottom sediment allows reasonable estimates of the siltation process globally, regionally, or locally, to be obtained without the need for costly research. The method draws on three key parameters, i.e., the concentration of suspended sediments (SS), and its organic matter (OM_SS) content, as well as the storage capacity (V_R) (i.e., the water storage in the reservoir). All of these parameters easy to determine, with information on them, in fact, made widely available by most agencies managing reservoirs in different parts of the world. In practice, the proposed method can represent a missing link in the precise determination of a reservoirs rate of siltation (and hence, losses of storage capacity).     

Differences in flood hazard projections in Europe – their causes and consequences for decision making

This paper interprets differences in flood hazard projections over Europe and identifies likely sources of discrepancy. Further, it discusses potential implications of these differences for flood risk reduction and adaptation to climate change. The discrepancy in flood hazard projections raises caution, especially among decision makers in charge of water resources management, flood risk reduction, and climate change adaptation at regional to local scales. Because it is naïve to expect availability of trustworthy quantitative projections of future flood hazard, in order to reduce flood risk one should focus attention on mapping of current and future risks and vulnerability hotspots and improve the situation there. Although an intercomparison of flood hazard projections is done in this paper and differences are identified and interpreted, it does not seems possible to recommend which large-scale studies may be considered most credible in particular areas of Europe.

EDITOR D. Koutsoyiannis

ASSOCIATE EDITOR not assigned     

Are modern metaheuristics successful in calibrating simple conceptual rainfall–runoff models?

In recent years sampling approaches have been used more widely than optimization algorithms to find parameters of conceptual rainfall–runoff models, but the difficulty of calibration of such models remains in dispute. The problem of finding a set of optimal parameters for conceptual rainfall–runoff models is interpreted differently in various studies, ranging from simple to relatively complex and difficult. In many papers, it is claimed that novel calibration approaches, so-called metaheuristics, outperform the older ones when applied to this task, but contradictory opinions are also plentiful. The present study aims at calibration of two simple lumped conceptual hydrological models, HBV and GR4J, by means of a large number of metaheuristic algorithms. The tests are performed on four catchments located in regions with relatively similar climatic conditions, but on different continents. The comparison shows that, although parameters found may somehow differ, the performance criteria achieved with simple lumped models calibrated by various metaheuristics are very similar and differences are insignificant from the hydrological point of view. However, occasionally some algorithms find slightly better solutions than those found by the vast majority of methods. This means that the problem of calibration of simple lumped HBV or GR4J models may be deceptive from the optimization perspective, as the vast majority of algorithms that follow a common evolutionary principle of survival of the fittest lead to sub-optimal solutions.     

Hydrological system analysis and modelling of the Kara River basin (West Africa) using a lumped metric conceptual model

This paper discusses the analysis and modelling of the hydrological system of the basin of the Kara River, a transboundary river in Togo and Benin, as a necessary step towards sustainable water resources management. The methodological approach integrates the use of discharge parameters, flow duration curves and the lumped conceptual model IHACRES. A Sobol sensitivity analysis is performed and the model is calibrated by applying the shuffled complex evolution algorithm. Results show that discharge generation in three nested catchments of the basin is affected by landscape physical characteristics. The IHACRES model adequately simulates the rainfall–runoff dynamics in the basin with a mean modified Nash-Sutcliffe efficiency measure of 0.6. Modelling results indicate that parameters controlling rainfall transformation to effective rainfall are more sensitive than those routing the streamflow. This study provides insights into understanding the catchment’s hydrological system. Nevertheless, further investigations are required to better understand detailed runoff generation processes.

EDITOR M.C. Acreman; ASSOCIATE EDITOR N Verhoest     

Comparison of two rainfall–runoff models: effects of conceptualization on water budget components

Rainfall–runoff models with different conceptual structures for the hydrological processes can be calibrated to effectively reproduce the hydrographs of the total runoff, while resulting in water budget components that are essentially different. This finding poses an open question on the reliability of rainfall–runoff models in reproducing hydrological components other than those used for calibration. In an effort to address this question, we use data from the Glafkos catchment in western Greece to calibrate and compare the ENNS model, a research-oriented lumped model developed for the river Enns in Austria developed for the river Enns in Austria, with the operational MIKE SHE model. Model performance is assessed in the light of the conceptual/structural differences of the modelled hydrological processes, using indices calculated independently for each year, rather than for the whole calibration period, since the former are stricter. We show that even small differences in the representation of hydrological processes may impact considerably on the water budget components that are not measured (i.e. not used for model calibration). From all water budget components, direct runoff exhibits the highest sensitivity to structural differences and related model parameters.

EDITOR M.C. Acreman

ASSOCIATE EDITOR S. Huang     

Evaluation of nonlinear models for precipitation forecasting

Prediction of factors affecting water resources systems is important for their design and operation. In hydrology, wavelet analysis (WA) is known as a new method for time series analysis. In this study, WA was combined with an artificial neural network (ANN) for prediction of precipitation at Varayeneh station, western Iran. The results obtained were compared with the adaptive neural fuzzy inference system (ANFIS) and ANN. Moreover, data on relative humidity and temperature were employed in addition to rainfall data to examine their influence on precipitation forecasting. Overall, this study concluded that the hybrid WANN model outperformed the other models in the estimation of maxima and minima, and is the best at forecasting precipitation. Furthermore, training and transfer functions are recommended for similar studies of precipitation forecasting.     

Macroinvertebrate community structure and feeding interactions along a pollution gradient in Gilgel Gibe watershed,Ethiopia: Implications for biomonitoring

Feeding interactions among functional feeding groups (FFGs) of macroinvertebrates are robust indicators of aquatic ecosystem interactions. They provide information regarding organic matter processing, habitat condition and trophic dynamics. In tropical rivers with pronounced wet and dry seasons, macroinvertebrate based ecological monitoring tools are explicitly focused on metrics and indices, while ignoring interactions of FFGs. Therefore, the objective of this study was to investigate the functional feeding type metrics, diversity indices and feeding interactions among FFGs of macroinvertebrates along the water pollution gradient in Gilgel Gibe watershed, Ethiopia. Water quality parameters and macroinvertebrate community attributes were assessed for samples collected from upstream sites (15 sites), urban-impacted stretches (12 sites) and wetland-affected river zones (7 sites) of the watershed during the rainy (July) and dry (February) seasons. To understand the effect of pollution on the feeding interactions, stable carbon and nitrogen isotopes were analyzed. Macroinvertebrate-based diversity indices and functional feeding type metric showed deterioration of ecological integrity at the urban-impacted sites and substantial recovery in the wetland-affected downstream sites. Omnivorous feeding behavior of macroinvertebrates was noted for the upstream sites, whereas clear trophic guilds of FFGs were suggested for the wetland-affected river zones by the stable isotope results. The results of pollution gradient analysis and feeding interactions among FFGs revealed that the urban-impacted sites showed weaker interactions when compared to upstream and wetland influenced sites. This affirms the potential importance of feeding interactions among FFGs of macroinvertebrates in water quality monitoring.