Effects of Forest Composition and Spatial Patterns on Storm Flows of a Small Watershed1

Abstract: The PRMS_Storm model was built as a storm event, distributed hydrological model for studying the hydrological effects of forest composition and spatial distribution on storm‐flow volume and peakflow rates in the Xiangshuixi Watershed in the Three Gorges Reservoir Area, in the Yangtze River Basin in southwestern China. We developed three simulation scenarios based on forest composition and their spatial arrangements across the watershed, including all mixed conifer‐evergreen broadleaf forests (Scenario 1), all mixed evergreen broadleaf forests (Scenario 2), and mixed conifer + evergreen broadleaf + shrub forests (Scenario 3). We examined 11 storm events observed during 2002‐2005. Compared with the existing forest covers, modeling results suggested that the amount of overland flow was reduced by 21, 23, and 22%, and the interflow increased by 16, 88, and 30%, for Scenarios 1, 2, and 3, respectively. During the same time, peakflow rates were reduced by 20.8, 9.6, and 18.9%, respectively. The reduction of peakflow rates was most significant when rainfall intensity exceeded 0.8 mm/min and events with a short duration and effect was minor when rainfall intensity was below 0.5 mm/min. In general, we found that Scenarios 1 and 3 were preferred for reducing storm‐flow volume and peakflow rates due to their higher interception rates, large soil water holding capacity, and higher soil infiltration capacity. The modeled results suggested soil properties are important in affecting the flow processes and thus forest composition and forest spatial distributions will affect storm‐flow volume and peakflow rates at the watershed scale. To maximize flood reduction functions of a watershed, high priority should be given to those forest types (Scenarios 1 and 3) in reforestation practices in the study region. This study suggests both forest composition and spatial pattern are important reforestation designs for flood reduction in the Three Gorges Reservoir Area.     

The Role of Climate and Human Influences in the Dry‐Up of the Jinci Springs,China1

Abstract: One of the largest karst springs in North China, the Jinci Springs, dried up and has remained dry since 1994. We develop a correlation analysis with time‐lag and a regression analysis with time‐lag to study the relation between spring flow and precipitation. This allows us to obtain a better understanding of karst hydrological processes by differentiating the contribution of variation in precipitation from anthropogenic impacts on the dry‐up of Jinci Springs. We divided the karstic hydrological processes into two phases: pre‐1961 and post‐1961. In the first phase (i.e., 1954‐1960) the groundwater recharge was affected by precipitation alone, and in the second phase (i.e., 1961‐1994) the groundwater recharge was influenced by both precipitation and human activities. Using precipitation and groundwater recharge data in the first phase, we set up a groundwater recharge model with time‐lags. By running the time‐lags model, we acquired the groundwater recharge likely to occur under the sole effect of precipitation in the second phase. Using a water‐balance calculation, we conclude that the groundwater recharge exhibited statistical stationarity, and the Jinci Springs dry‐up was the result of anthropogenic activities. At least three specific types of anthropogenic activities contributed to the drying‐up of Jinci Springs: (1) groundwater pumping accounts for 51%, (2) the dewatering from coal mining accounts for 33%, (3) and dam‐building 14%. The drying‐up of Jinci Springs meant that the groundwater drained from the aquifer’s fractures, and subsequently changed the structure of the karst aquifer. Although groundwater exploitation has been reduced, the flow at Jinci Springs has not reoccurred.     

Effect of the Spatial Variability of Land Use,Soil Type,and Precipitation on Streamflows in Small Watersheds1

Abstract: The spatial variability of the data used in models includes the spatial discretization of the system into subsystems, the data resolution, and the spatial distribution of hydrologic features and parameters. In this study, we investigate the effect of the spatial distribution of land use, soil type, and precipitation on the simulated flows at the outlet of “small watersheds” (i.e., watersheds with times of concentration shorter than the model computational time step). The Soil and Water Assessment Tool model was used to estimate runoff and hydrographs. Different representations of the spatial data resulted in comparable model performances and even the use of uniform land use and soil type maps, instead of spatially distributed, was not noticeable. It was found that, although spatially distributed data help understand the characteristics of the watershed and provide valuable information to distributed hydrologic models, when the watershed is small, realistic representations of the spatial data do not necessarily improve the model performance. The results obtained from this study provide insights on the relevance of taking into account the spatial distribution of land use, soil type, and precipitation when modeling small watersheds.     

A Streamflow Forecasting Framework using Multiple Climate and Hydrological Models1

Abstract: Water resources planning and management efficacy is subject to capturing inherent uncertainties stemming from climatic and hydrological inputs and models. Streamflow forecasts, critical in reservoir operation and water allocation decision making, fundamentally contain uncertainties arising from assumed initial conditions, model structure, and modeled processes. Accounting for these propagating uncertainties remains a formidable challenge. Recent enhancements in climate forecasting skill and hydrological modeling serve as an impetus for further pursuing models and model combinations capable of delivering improved streamflow forecasts. However, little consideration has been given to methodologies that include coupling both multiple climate and multiple hydrological models, increasing the pool of streamflow forecast ensemble members and accounting for cumulative sources of uncertainty. The framework presented here proposes integration and offline coupling of global climate models (GCMs), multiple regional climate models, and numerous water balance models to improve streamflow forecasting through generation of ensemble forecasts. For demonstration purposes, the framework is imposed on the Jaguaribe basin in northeastern Brazil for a hindcast of 1974‐1996 monthly streamflow. The ECHAM 4.5 and the NCEP/MRF9 GCMs and regional models, including dynamical and statistical models, are integrated with the ABCD and Soil Moisture Accounting Procedure water balance models. Precipitation hindcasts from the GCMs are downscaled via the regional models and fed into the water balance models, producing streamflow hindcasts. Multi‐model ensemble combination techniques include pooling, linear regression weighting, and a kernel density estimator to evaluate streamflow hindcasts; the latter technique exhibits superior skill compared with any single coupled model ensemble hindcast.     

赣江源头流域植被变化的水文响应模拟研究

应用2个分布式水文模型（SWAT和Topmodel模型）,对赣江流域的源头--梅江流域20年内的植被变化所造成的生态水文响应做出了模拟研究。根据2个模型不同的特点,设计了不同的模拟方案,使用SWAT模型模拟径流量的变化,Topmodel模型模拟汇流过程的变化。模拟得到的结果是：排除研究时间段内流域气候变化的影响,仅变换流域下垫面的属性,植被的变化对流域水文特征产生了明显影响,在整个梅江流域的范围内,2000年的年径流总量比1987年增加了146%;在其子流域--琴江流域,1995~2000年的7次洪峰峰值径流出现时间比1987年延迟,峰值径流量减少约5%。这说明从上世纪80年代开始在该流域内进行的植树造林和国土整治工作,即江西省“山江湖工程”,对流域的生态健康具有良好的回馈效应。     

极端干旱区咸水灌溉人工防护林土壤可溶性碳的垂直分布及其影响因素

可溶性碳（DC）是土壤中最活跃的碳组分,植被恢复与重建加速了干旱荒漠区的碳循环过程.研究咸水灌溉下沙漠人工防护林地土壤剖面DC的分布,可为干旱荒漠区人工林的管理和开发利用提供理论支撑和决策依据.本研究选取塔克拉玛干沙漠公路沿线5个不同矿化度咸水滴灌林地作为研究样地,流沙地为对照（CK）,分析并讨论了0~1 m剖面土壤可溶性有机碳（SDOC）和可溶性无机碳（SDIC）的垂直分布特征及其与各因子间的相关关系.结果表明,CK与2.82 g·L^-1矿化度滴灌处理SDOC、SDIC呈"I"型分布,其分布满足线性函数关系,其他各样地SDOC和SDIC均呈"Γ"型分布,分布满足幂函数关系;所有处理表层SDOC、SDIC波动能力及贡献度均高于下层土壤,且SDOC波动及贡献度均大于SDIC,2.82 g·L^-1之外的各林地SDOC平均含量是SDIC的2~4倍;2.82 g·L^-1样地SDOC平均含量低于CK,其他各样地SDOC是CK的3~5倍,各样地SDIC含量较CK增加了15.0%~57.9%;矿化度高于2.82 g·L^-1的样地0~5 cm土层SDOC含量随灌溉水矿化度的增加而增加,各样地SDIC含量随矿化度的升高呈先增加后下降低趋势,4.82 g·L^-1样地达到最大.SDOC和SDIC与灌溉水矿化度、EC、SOC、SIC及土壤含水量均呈正相关关系,其中与土壤含水量表现出弱正相关,SDOC和SDIC与土层深度呈负相关关系;SDOC和SDIC与pH分别呈微弱的负相关和微弱的正相关.总之,灌溉水矿化度对SDOC和SDIC的垂直分布具有重要影响,同时与土壤含水量、土层深度、EC、SOC和SIC等因素紧密相关,这对极端干旱区人工林建设及管护具有重要意义.     

北江流域水文特征变异研究

水文特征变异研究是水文学研究中的重点之一。水文特征变异不仅包括时间、空间上的概念,还包括属性上的概念。研究水文序列在属性、时间及空间上的变异,才能够全面地反映水文序列的变异情况。论文探讨了水文特征变异的内涵,提出水文特征变异是研究对象或现象在属性、时间和空间上的变异量度。以北江流域径流量及降雨量资料为基础,全面分析了属性范畴下及时空范畴下北江流域水文序列的变异情况。结果表明:1992-2006年的径流量序列和1973-2006年的径流量序列相对于1956-1972年的径流量序列都发生了变异;从重心移动方向来看,北江流域在1959、1967、1975和1983年移动方向发生了转折,从重心移动的距离来看,降雨重心离多年平均较远的年份分别是1967、1975、1983和2000年。     

荒漠草原区油气管道建设对地表植被格局的影响

以油气管道经过的乌鲁木齐荒漠草原地区为研究对象,选择施工前、施工期以及恢复期3个不同施工阶段的遥感影像数据,解译地表植被类型,采用象元二分法提取植被覆盖度,通过比较时间上植被覆盖格局和土地利用格局的变化,分析油气管道建设对生态系统影响的范围和特点.研究发现:不同建设时期管道两边荒漠草原区土地利用类型差异较大,草地面积持续降低,共计减少32.53%,灌木林地面积增加到24.61%,建设用地面积在建设期增加,植被恢复期降低.研究区复杂程度提高,原有生态结构发生改变;建设期管道施工作业带及两侧10m范围内植被覆盖度显著低于其他区域,而管道两侧50~100以及100~200m范围内的植被覆盖度无明显差异,但与200~300m范围相比差异显著.管道建设主要影响范围为管道上方施工作业带以及两侧10m的范围内,间接影响范围为施工作业带两侧200m内;恢复期人为措施对研究区植被覆盖度的主要影响范围为施工作业带;管道建设改变了荒漠草原生态系统的组成结构,是管道周边土地利用类型和荒漠草地系统变化的主要推动力;人为恢复措施无法使受影响区域的植被恢复到建设前的水平.     

古尔班通古特沙漠边缘生态环境建设策略

沙漠古已有之,近期由于开发的需要,人为造成的沙漠扩张明显超过历史时期,沙漠化与人类干扰的加剧有直接关系。在荒漠区的开发及其生态环境建设过程中,应深入了解荒漠区的环境现状,充分利用该区的自然环境条件,改造沙漠,实施保护、利用与建设相结合的方针,以荒漠植被自然侵移规律为依据,依靠自然降水,以最大限度人工发展可供饲用的灌林,实现荒漠生态环境建设的目的     

我国干热沙漠环境特点对电工电子产品的影响

本文介绍我国干热沙漠的环境特点,分析其对电工电子产品的主要影响和危害,并介绍克服影响应采取的措施。