蒋家沟流域坡面侵蚀特征实验研究

受流域内物质成分、气候条件和复杂侵蚀营力的影响,蒋家沟流域坡面侵蚀现象甚为严重。根据流域内坡面物质成分、气候、降雨等方面分析了发生坡面严重侵蚀的原因;并进行了大量的人工降雨侵蚀实验,分析降雨坡面产流产沙过程和特征。实验结果表明径流随降雨时间和降雨量的增加呈跳跃和波动性增加,泥沙含量随降雨时间增加而逐渐减小。     

近50a来青海水文要素变化特征分析

对青海省境内降水、径流、水面蒸发站观测资料的分析,结果显示年降水量在昆仑山、巴颜喀拉山、达板山以北,阿尼玛卿山、日月山以西的地区呈增加的趋势,且以柴达木盆地增幅较大,以东的黄河流域降水略有减少;以南的长江流域变化趋势不明显.年径流量在柴达木盆地南部、昆仑山北麓呈较明显增加的趋势,盆地北部诸河、长江流域、大通河变化趋势不明显,其它地区包括青海湖、黄河及其支流(不含大通河)呈减少的趋势.水面蒸发量除个别站点外,呈明显下降的态势,而且减幅较大,下降的幅度西部地区大于东部地区.与此对应是全省的干旱指数明显变小,湿润程度有所增加.     

Topmodel模型在黑河干流出山径流模拟中的应用

概念性模型应用广泛,它由集总模式逐步发展为分布参数模式。文中介绍了一个基于土壤含水量和地形指数的概念性分布参数模型——Topmodel。该模型以小时为步长,对DEM分辨率的要求为50 m×50 m。为将模型应用到我国内陆河山区中大型流域,将模型的DEM分辨率拓宽到1 500 m×1 500 m,模拟过程也分别以日和月为步长。日径流模拟结果表明,在DEM分辨率较粗的情况下,模型有一个较长时间的土壤含水量调整期,之后模拟效果较好,尤其是枯水径流。月模型模拟效果较好,但模拟效果总体还是受DEM分辨率较粗的影响。     

黄河源区径流年内分配变化规律分析

河川径流的年内分配特征与特定的径流补给条件关系密切。在气候变化以及人类活动的影响下,河川径流的年内分配特征也发生着相应的变化,直接影响水资源的开发利用以及生态系统的健康。本文根据黄河源区主要测站1952～1997年的月天然径流资料,分析了年内分配不均匀系数、集中度和集中期、变化幅度等特性。结果表明:1)黄河源区径流的年内分配特征20世纪90年代和70年代较为接近,而80年代则与60年代较为接近。2)90年代的径流年内分配特征出现了较大的变化,突出表现在汛期径流量的减少;3)玛曲水文站径流年内分配的不均匀性、集中度以及相对变化幅度都略高于唐乃亥,而绝对变化幅度则较小。     

潮白河径流分布规律及人类活动对径流的影响分析

利用潮白河五个水文站1956年以来的径流资料,应用多种数值分析方法,详细分析了潮白河径流的年际、年内分配规律,计算了人类活动对径流的影响。结果表明,潮白河径流的年际变化剧烈,丰水时段历时很短,而枯水时段历时很长。应用累积滤波器和肯德尔秩次相关法,对年径流变化趋势所作的定性和定量的结果表明,潮白河年径流总体呈减少趋势,且减少趋势显著。根据年径流累积曲线和回归分析,人类活动是引起潮白河径流减少的主要因素。     

青藏公路路堤边坡产流产沙规律及影响因素分析

公路建设引起的人为加速侵蚀对生态环境造成很大影响,为摸清道路边坡的侵蚀规律,在青藏公路边坡布设了自然径流观测小区,降雨过后进行采样,获得径流深和侵蚀模数数据。对所得数据整理分析表明:(1)次径流深、次侵蚀模数与降雨量和降雨强度的乘积有很好的线性相关,相关系数分别为0.802和0.554。次径流深与次侵蚀模数之间的相关系数达到0.771;(2)产流产沙随坡长增加有减少的趋势,但其规律还有待进一步研究;(3)随着时间的推移,产流产沙有所下降,小区坡面的干扰得到了恢复,因此,时间是公路边坡水土流失的重要影响因素;(4)公路边坡的年侵蚀模数,包括降雨侵蚀和冻融侵蚀,共计11991.41 t/km²,属于极强度侵蚀。     

生态护坡对边坡岩土体基质吸力的影响研究

对植被蒸腾作用以及阻滞地表径流作用进行了研究,提出生态护坡对边坡岩土体基质吸力的影响主要有3个方面：(1) 植被的蒸腾作用消耗边坡岩土体中的水分,使边坡体基质吸力升高,对边坡稳定有利;(2) 植被阻滞地表径流,增加降雨入渗量,使边坡体含水率增高,基质吸力降低,对边坡稳定不利;(3) 植被的存在究竟使边坡体基质吸力如何变化以及对边坡稳定是否有利,最终决定于降雨量和雨型。在此基础上,更进一步提出在降雨丰沛、暴雨较多的地区进行生态护坡时,应对边坡体采取防排水处理措施。     

Multiple criteria rainfall–runoff model calibration using a parallel genetic algorithm in a cluster of computers / Calage multi-critères en modélisation pluie–débit par un algorithme génétique parallèle mis en œuvre par une grappe d'ordinateurs

Abstract

Genetic algorithms are among of the global optimization schemes that have gained popularity as a means to calibrate rainfall–runoff models. However, a conceptual rainfall–runoff model usually includes 10 or more parameters and these are interdependent, which makes the optimization procedure very time-consuming. This may result in the premature termination of the optimization process which will prejudice the quality of the results. Therefore, the speed of optimization procedure is crucial in order to improve the calibration quality and efficiency. A hybrid method that combines a parallel genetic algorithm with a fuzzy optimal model in a cluster of computers is proposed. The method uses the fuzzy optimal model to evaluate multiple alternatives with multiple criteria where chromosomes are the alternatives, whilst the criteria are flood performance measures. In order to easily distinguish the performance of different alternatives and to address the problem of non-uniqueness of optimum, two fuzzy ratios are defined. The new approach has been tested and compared with results obtained by using a two-stage calibration procedure. The current single procedure produces similar results, but is simpler and automatic. Comparison of results between the serial and parallel genetic algorithms showed that the current methodology can significantly reduce the overall optimization time and simultaneously improve the solution quality.     

Using integrated modelling to understand seasonal vegetation dynamics and its relationship to runoff generation

Vegetation dynamics and hydrological processes are major components of terrestrial ecosystems, and they interact strongly with each other. Studies of hydrological responses to vegetation dynamics are usually conducted on a long-term scale, whereas the hydrological responses within a single year have rarely been studied. In the present study, Poyang Lake runoff (PYL-R) model, a new hydrological model coupled with leaf area index (LAI) remote sensing products, was established and applied to simulate the runoff process in the Poyang Lake Watershed. The simulation results obtained in three sub-watersheds of the Poyang Lake Watershed (Ganjiang Watershed, Xinjiang Watershed, and Fuhe Watershed) agreed well with the observations (Nash efficiency coefficient values and R values exceeded 0.6 and 0.9, respectively). The PYL-R experiment (PYL-R-E) model was designed as a contrast model without considering the impact of LAI. The simulated monthly runoff results obtained using the PYL-R and PYL-R-E models were compared, and the within-year changes in the differences between the two results were analysed to evaluate and quantify the impact of vegetation dynamic on runoff. From January to July, when LAI values increased by around 2.6 m² m⁻², monthly runoff depth differences between PYL-R and PYL-R-E results increased by 35.25, 27.98, and 29.14 mm in the Ganjiang, Xinjiang, and Fuhe watersheds, respectively. Dense vegetation caused high interception and evapotranspiration during summer, which largely reduced runoff. By contrast, during winter, the effect of vegetation was weaker on runoff process whereas the impacts of other factors (e.g., precipitation) were higher. The sensitivity of monthly runoff to vegetation dynamics varied greatly throughout the whole year. In particular, during August and September, the LAI-caused runoff changes were very high, accounting for 28–42% of monthly runoff in the sub-watersheds. Our findings clarify the effects of changes in vegetation on hydrological processes over short time scales, thereby providing insights into the effects of scale on eco-hydrological processes.     

Estimating source regions for snowmelt runoff in a Rocky Mountain basin: tests of a data‐based conceptual modeling approach

In many mountain basins, river discharge measurements are located far away from runoff source areas. This study tests whether a basic snowmelt runoff conceptual model can be used to estimate relative contributions of different elevation zones to basin‐scale discharge in the Cache la Poudre, a snowmelt‐dominated Rocky Mountain river. Model tests evaluate scenarios that vary model configuration, input variables, and parameter values to determine how these factors affect discharge simulation and the distribution of runoff generation with elevation. Results show that the model simulates basin discharge well (NSCE and R >0.90) when input precipitation and temperature are distributed with different lapse rates, with a rain‐snow threshold parameter between 0 and 3.3 °C, and with a melt rate parameter between 2 and 4 mm °C^?1 d^?1 because these variables and parameters can have compensating interactions with each other and with the runoff coefficient parameter. Only the hydrograph recession parameter can be uniquely defined with this model structure. These non‐unique model scenarios with different configurations, input variables, and parameter values all indicate that the majority of basin discharge comes from elevations above 2900 m, or less than 25% of the basin total area, with a steep increase in runoff generation above 2600 m. However, the simulations produce unrealistically low runoff ratios for elevations above 3000 m, highlighting the need for additional measurements of snow and discharge at under‐sampled elevations to evaluate the accuracy of simulated snow and runoff patterns. Copyright © 2013 John Wiley & Sons, Ltd.