For sustainable water resource management,it is important to determine the relationship between streamfl ow and other variables that infl uence availability of water resources.However,many catchments do not have suffi cient data to allow for a more detailed study of these relationships.We faced a similar challenge in the Chengcun Basin(limited historical data: from 1986–1999); and therefore we used a new approach to overcome this.We found that,using nonparametric trend methods in conjunction with the climate elasticity analyses and the 2D visualization of hydrologic data,it is possible to assess the relationships between streamfl ow and other hydro-climatic variables.In the past,streamfl ow trends in the basin were more correlated with precipitation than with potential evapotranspiration(PET).In addition,there is a gradual shift in the hydrological regime of the catchment,which may affect the occurrence of available water resources and activities that depend on them.In addition,based on our climate sensitivity analyses,the streamfl ow is dependent and more sensitive to variations in precipitation than to PET(δQ=0.79δP+0.42δE; precipitation elasticity,ε P=1.32; PET elasticity,ε E=-2.10).Therefore pending more detailed studies,the use of our approach will provide a rapid means to assess the variation of water resources(streamfl ow)in a watershed.In the future,we hope to carry out related research in other watersheds and also perform a more detailed studies to improve upon the results of this study.
Streamflow in the Kuye River basin has been sharply reduced by the effects of climate change and human activities.Since 1997,the intensification of coal mining has resulted in substantial reductions to streamflow alongside an ever-increasing demand for water.In this study,we present a derived statistical method,incorporating the Mann-Kendall and Pettitt method(MK-P) and the Soil and Water Assessment Tool(SWAT),and apply it to estimating the streamflow reductions caused by underground mining for coal in the Kuye River basin.The results show that underground mining is an important cause of the streamflow reductions observed since1997,being responsible for reductions of 21.15 mm/yr(~56%of the total) during 1997-2009.The results of the SWAT simulation were assessed by several performance criteria:Nash-Suttcliffe Efficiency(Nse),correlation coefficient(R^2),relative error(RE),P-factor and Pv-factor.The close match between the simulations and observed data supports the reasonability of our findings.We suggest that engineering strategies be adopted to limit streamflow loss into goafs via fractured zones in the coalfield.
Intense human activities have greatly changed the flood generation conditions in most areas of the world, and have destroyed the consistency in the annual flood peak and volume series. For design flood estimation, coaxial correlation diagram and conceptual hydrological model are two frequently used tools to adjust and reconstruct the flood series under human disturbance. This study took a typical mountain catchment of the Haihe River Basin as an example to investigate the effects of human activities on flood regime and to compare and assess the two adjustment methods. The main purpose is to construct a conceptual hydrological model which can incorporate the effects of human activities. The results show that the coaxial correlation diagram is simple and widely-used, but can only adjust the time series of total flood volumes. Therefore, it is only applicable under certain conditions(e.g. There is a strong link between the flood peaks and volumes and the link is not significantly affected by human activities). The conceptual model is a powerful tool to adjust the time series of both flood peak flows and flood volumes over different durations provided that it is closely related to the catchment hydrological characteristics, specifically accounting for the effects of human activities, and incorporating expert knowledge when estimating or calibrating parameters. It is suggested that the two methods should be used together to cross check each other.
