Hillslope‐scale probabilistic characterization of soil moisture dynamics and average water balance

Probabilistic water balance modelling provides a useful framework for investigating the interactions between soil, vegetation, and the atmosphere. It has been used to estimate temporal soil moisture dynamics and ecohydrological responses at a point. This study combines a nonlinear rainfall–runoff theory with probabilistic water balance model to represent varied source area runoff as a function of rainfall depth and a runoff coefficient at hillslope scale. Analytical solutions of the soil‐moisture probability density function and average water balance model are then developed. Based on a sensitivity analysis of soil moisture dynamics, we show that when varied source area runoff is incorporated, mean soil moisture is always lower and total runoff higher, compared with the original probabilistic water balance model. The increased runoff from the inclusion of varied source area runoff is mainly because of a reduction in leakage when the index of dryness is less than one and evapotranspiration when the index of dryness is greater than one. Inclusion of varied source area runoff in the model means that the actual evapotranspiration is limited by less available water (i.e. water limit), which is stricter than Budyko’s and Milly’s water limit. Application of the model to a catchment located in Western Australia showed that the method can predict annual value of actual evapotranspiration and streamflow accurately. Copyright © 2012 John Wiley & Sons, Ltd.     

Assessing the spatial and temporal variation of the rainwater harvesting potential (1971–2010) on the Chinese Loess Plateau using the VIC model

Rainwater harvesting could increase the resilience of ecosystems on the Loess Plateau and thus ensure the sustainability of livelihoods that depend on them. As such, it is a key component of strategies for adapting to global climate change. In this study, we used a new method to quantify the rainwater harvesting potential (RWHP) across the whole Loess Plateau and to characterize its spatial and temporal variation over the last four decades on the basis of the variable infiltration capacity model. It was found that that the mean RWHP of the study region was 731.10 × 10⁸ m³, and the average water layer thickness was 114.34 mm. There is considerable scope for rainwater harvesting across the Loess Plateau as a whole, to the extent that it could potentially provide enough water to implement the ‘Grain for Green’ Project. The annual average RWHP decreased slightly from 1971 to 2010, and Hurst exponent analysis indicated that this trend will exhibit long‐term persistence. The annual RWHP was highest in the southeast of the Loess Plateau and lowest in the northwest. Areas with high RWHP values tended to be clustered around the middle reach of the Yellow River. For most areas, there was no significant change between 1971 and 2010. Those areas for which there was a significant decrease in RWHP were primarily located around the upper–middle reaches of the Weihe River, the upper reach of Jinghe River, the eastern Guanzhong Plain, the Qinhe River watershed and the area around Dongsheng. Quantitative assessments of RWHP are likely to be useful for guiding the development and use of innovative rainwater harvesting technologies around the world and could help to relieve the problems caused by water shortages on the Loess Plateau while simultaneously eliminate the major cause of soil erosion. Copyright © 2012 John Wiley & Sons, Ltd.     

微地震监测数据时频域去噪方法

原始微地震监测数据的信噪比相对较低,监测数据品质决定了微地震有效信号的定位精度,提高监测数据信噪比是微地震处理的关键环节。改进S变换对窗函数进行能量归一化处理,解决了常规S变换时频谱中频率定位不准的问题,具有更高的时频分辨率精度。利用改进S变换的良好二维时频域聚焦特性,设计时变的二维时频域滤波器,将时频域去噪方法引入到微地震监测数据的去噪处理中。利用改进S变换对微地震监测数据进行时频分析,能够更加准确地分析不同信号分量的振幅能量以及频率随时间的变化情况,实现微地震有效信号分量与噪声干扰分量的有效分离。通过合成模拟信号和实际井中微地震监测数据的试处理和对比分析,验证了该方法的可行性和有效性。     

区域综合节水效果的遥感评价方法 研究与应用

区域节水效果的常规评价方法都是利用单项指标评价单一行业的或者单方面的节水效果,不能反映区域综合节水效果.本文从耗水控制水平和地下水可持续利用的角度出发,提出了以目标蒸散量(ET)和地下水位理论变幅为评价基准,利用遥感技术监测区域实际蒸散量和地下水位实际变幅,采用基准比较法评价区域节水综合效果的方法;并以北京市大兴区为例...     

边坡稳定可靠度分析的广义可行方向法

在广义随机空间中直接建立验算点的迭代公式,可以方便地解决含相关随机变量的结构可靠度计算问题。在广义随机空间中推导了一种收敛性较好的验算点迭代公式,并应用于边坡稳定的可靠度分析。针对卡基娃混凝土面板堆石坝地震工况坝坡稳定的可靠度分析表明:(1)由于安全系数法采用的输入参数为确定值,故不能考虑参数随机波动的影响。可靠度分析能够反映参数随机性的影响,这对于深入评估工程安全与抗风险能力是有益的。(2)通过引入条件概率方法考虑地震和坝坡失稳同时发生的概率得到的结构可靠指标将提高,而提高的幅度与地震发生概率的大小有关。(3)堆石非线性强度指标具有正相关性,考虑强度指标的相关性将提高边坡稳定的可靠度。     

基于结构模型的磁性基底反演

常规磁性基底反演方法往往忽略基底磁性变化采用常磁化强度模型,这里分析了其中的局限性,提出了先构建相关搜索重磁三维定量反演技术的变磁化强度模型,然后通过Parker界面反演算法进行基底反演.其中,对反演磁化强度所需磁异常分离采用了小波变换方法,并分析了该方法的关键技术和措施.通过利用该方法对某工区进行了实际资料处理后,得到较好效果.     

3维干旱变量联合概率分布研究

研究多变量干旱特性联合分布的推求方法。选择干旱历时、干旱烈度和烈度峰值为水文干旱特性变量。单变量的边际分布参数分别采用矩法、概率权重法、极大似然法和遗传算法进行计算和优化。应用检验、Kolmogorov-Smirnov等6种检验法进行单变量分布的拟合度检验。采用Pearson’s古典相关系数,Spearman秩相关系数,Kendall’s,Chi-Plots和K-Plots进行变量间的相依性度量。选择4种常用的3维Archimedean Copula函数进行干旱特性变量联合分布拟合。根据RMSE、AIC和BIC准则选择最优copula。在此基础上,采用基于Rosenblatt变换的Bootstrap法进行3维copula的拟合度检验。模型应用于渭河流域北洛河状头站径流序列,结果表明:Gumbel-Hougaard copula拟合效果最好,可以描述洛河状头站3维干旱变量的联合分布。     

可变模糊理论与模糊粗糙集在地下水污染评估中的应用

传统的地下水污染评估方法需检测多项地下水化学变量,成本较高且无法考虑水质指标区间量值的影响。为此,笔者利用可变模糊理论对地下水污染进行综合评估,在此基础上通过模糊粗糙集理论挖掘关键变量,并利用生成的最小决策规则库对样品点的污染综合指数进行预测。将该方法应用于洛阳盆地,对其有效性进行验证,计算结果表明:As、Hg、Se、I、NH3-N对研究区地下水污染分类起控制作用。通过与实测的13种化学变量所计算的地下水污染综合指数相比,测试数据中7组样品的相对误差为0.104 0～0.172 5;剩余15组样品的相对误差为0.001 5～0.093 7,基本满足地下水污染评估的要求。可变模糊集与模糊粗糙集理论能够通过较少的化学变量对污染综合指数进行预测,从而降低地下水污染评估成本,为后续的地下水污染控制与修复提供可靠的数据来源。     

TLS-bridged co-prediction of tree-level multifarious stem structure variables from worldview-2 panchromatic imagery: a case study of the boreal forest

ABSTRACT

In forest ecosystem studies, tree stem structure variables (SSVs) proved to be an essential kind of parameters, and now simultaneously deriving SSVs of as many kinds as possible at large scales is preferred for enhancing the frontier studies on marcoecosystem ecology and global carbon cycle. For this newly emerging task, satellite imagery such as WorldView-2 panchromatic images (WPIs) is used as a potential solution for co-prediction of tree-level multifarious SSVs, with static terrestrial laser scanning (TLS) assumed as a ‘bridge’. The specific operation is to pursue the allometric relationships between TLS-derived SSVs and WPI-derived feature parameters, and regression analyses with one or multiple explanatory variables are applied to deduce the prediction models (termed as Model1s and Model2s). In the case of Picea abies, Pinus sylvestris, Populus tremul and Quercus robur in a boreal forest, tests showed that Model1s and Model2s for different tree species can be derived (e.g. the maximum R²?=?0.574 for Q. robur). Overall, this study basically validated the algorithm proposed for co-prediction of multifarious SSVs, and the contribution is equivalent to developing a viable solution for SSV-estimation upscaling, which is useful for large-scale investigations of forest understory, macroecosystem ecology, global vegetation dynamics and global carbon cycle.     

Determining the susceptibility of Eucalyptus nitens forests to Coryphodema tristis (cossid moth) occurrence in Mpumalanga,South Africa

The cossid moth, Coryphodema tristis was first noted on Eucalyptus nitens trees in Mpumalanga province, South Africa during July 2004. Currently, the moth poses a major threat to commercial forestry in the country. In this study, selected climatic and topographical variables were used to model the susceptibility of E. nitens forests to cossid moth occurrence, thereby providing insight into the variables that may influence the occurrence and spread of the moth. A zigzag sampling technique was used to survey 5316 ha of E. nitens forests for the presence or absence of the moth. The random forest classification algorithm was then used to model the relationship between the climatic and topographical variables and the occurrence of the cossid moth. Results indicate that four variables that included elevation, maximum temperature for September, maximum temperature for April and the median rainfall for April best explained the presence or absence of C. tristis with an overall accuracy of 82% and a kappa value of 0.63. Partial dependence plots indicated that the areas that have a maximum temperature greater than 23°C in September and 22°C in April are likely to be infested by the cossid moth. The results from this study provide a robust and accurate spatial framework to assist forest managers in focussing their existing monitoring and control efforts to specific E. nitens forested areas that are highly susceptible to C. tristis infestations.