基于DEM栅格的分布式BTOPMC模型在水文模拟中的应用

应用一个基于DEM栅格的分布式水文模型BTOPMC(Block-wise use of TOPMODEL)模型进行水文模拟研究。该模型结合IGBP全球陆面土壤覆盖与FAO全球数字土壤组成信息,以栅格为计算单元,进行产流计算;汇流采用Muskingum-Cunge法。为了探讨模型的应用范围,将BTOPMC模型与新安江模型应用于湿润流域与半干旱半湿润流域的水文日径流过程模拟,并采用SCE-UA算法进行模型参数优化。结果表明2个模型均能很好地模拟湿润流域日径流过程,在半干旱半湿润流域BTOPMC模型的模拟效果较差,模型的产流机制需要进一步的完善,以扩大模型的应用范围。

湿润亚热带典型白云岩流域的水文水化学动态特征初步研究--以贵州施秉黄洲河流域为例

利用水文水化学自动监测仪,于2018年5月18日至2018年12月3日期间对地处湿润亚热带季风气候条件下的贵州省施秉世界自然遗产地境内的黄洲河白云岩小流域进行了高时间分辨率的连续监测,目的是为了揭示湿润亚热带季风气候区典型白云岩小流域不同时间尺度与不同降雨强度下水文水化学动态特征。研究获得了黄洲河白云岩小流域的降雨量、出口流量、水温、电导率、pH、方解石及白云石饱和指数、CO2分压等连续数据。结果表明:(1)黄洲河流域出口河水的pH、电导率、CO2分压、方解石及白云石饱和指数等指标具有明显的日周期变化规律,即水温、pH、方解石及白云石饱和指数与气温的昼夜周期变化曲线相似,而电导率、CO2分压与气温的日周期变化曲线相反;(2)黄洲河流域出口河水的水化学指标对不同强度的降雨会产生不同变幅与变化方向的响应特征,暴雨会显著干扰河水水化学指标的日周期变化规律,主要表现在随着降雨强度的增大,电导率与CO2分压呈现显著下降;(3)白云岩流域具有明显的化学稳态行为。

Flash flood type identification and simulation based on flash flood behavior indices in China

Flash floods present significant heterogeneity over both space and time due to diverse topographic,geomorphologic,and hydro-meteorological conditions of catchments.Accurate identification and simulation of typical flash flood types are of great significance for the mitigation of flash flood disasters at the national scale.Three flood peak indices and dynamic indices were adopted to characterize the behavioral variability of flash floods.The typical flash flood types and corresponding behavior indices were identified and simulated using statistical analysis(i.e.,principal component analysis,dynamic K-means clustering,and analysis of similarity)and hydrological modelling(i.e.,HEC and XAJ models).There were 177 flash flood events at the hourly scale being selected for case study from eight catchments with various climatic and geographic characteristics.Results showed that all the flash flood events were clustered into three types(named Types 1,2,and 3).Type 1 was characterized by low peak flow intensity,early flood peak occurrence time,and thin flood process with short duration.Type 2 was characterized by low peak flow intensity,late flood peak occurrence time,and flat flood process with long duration.Type 3 was characterized by high peak flow intensity and late flood peak occurrence time.Flash flood types showed high consistency with their influencing factors(e.g.,catchment forest ratio and drainage area,occurrence time and magnitude of maximum storm intensity,and concentration of a storm event).The simulation performances were basically the same for HEC and XAJ models.As for flash flood event simulations,the average relative error varied from 23.25%to 27.98%,from 11.95%to 18.19%,and from 8.30%to18.25%for Types 1,2 and 3,respectively.The average Nash-Sutcliffe efficiency coefficient varied from 0.39 to 0.54,from 0.76 to 0.85,and from 0.86 to 0.91,respectively.As for the six flash flood behavior indices simulations,the average relative rootmean-square error(RMSEr)varied from 0.37 to 0.69,from 0.37 to 0.41,and from 0.18 to 0.25 for Types 1,2,and 3,respectively.The average correlation coefficient(r)varied from 0.52 to 0.68,from 0.78 to 0.85,and from 0.88 to 0.94,respectively.The flood peak indices were the best simulated for Types 2 and 3 with RMSEr varying from 0.18 to 0.28 and r varying from 0.86 to 0.91.The flood dynamic indices were the best simulated for Type 3 with RMSEr varying from 0.19 to 0.21 and r varying from 0.91 to0.97.The study provided detailed flood information supports for flood management at catchment scale,and also provided new insights into flash flood simulations in small and medium-sized catchments from perspective of flood behavioral processes.