Dynamic,discontinuous stream networks: hydrologically driven variations in active drainage density,flowing channels and stream order

Despite decades of research on the ecological consequences of stream network expansion, contraction and fragmentation, surprisingly little is known about the hydrological mechanisms that shape these processes. Here, we present field surveys of the active drainage networks of four California headwater streams (4–27 km²) spanning diverse topographic, geologic and climatic settings. We show that these stream networks dynamically expand, contract, disconnect and reconnect across all the sites we studied. Stream networks at all four sites contract and disconnect during seasonal flow recessions, with their total active network length, and thus their active drainage densities, decreasing by factors of two to three across the range of flows captured in our field surveys. The total flowing lengths of the active stream networks are approximate power‐law functions of unit discharge, with scaling exponents averaging 0.27 ± 0.04 (range: 0.18–0.40). The number of points where surface flow originates obey similar power‐law relationships, as do the lengths and origination points of flowing networks that are continuously connected to the outlet, with scaling exponents averaging 0.36–0.48. Even stream order shifts seasonally by up to two Strahler orders in our study catchments. Broadly, similar stream length scaling has been observed in catchments spanning widely varying geologic, topographic and climatic settings and spanning more than two orders of magnitude in size, suggesting that network extension/contraction is a general phenomenon that may have a general explanation. Points of emergence or disappearance of surface flow represent the balance between subsurface transmissivity in the hyporheic zone and the delivery of water from upstream. Thus the dynamics of stream network expansion and contraction, and connection and disconnection, may offer important clues to the spatial structure of the hyporheic zone, and to patterns and processes of runoff generation. Copyright © 2014 John Wiley & Sons, Ltd.     

Interannual variability in glacier contribution to runoff from a high‐elevation Andean catchment: understanding the role of debris cover in glacier hydrology

We present a field‐data rich modelling analysis to reconstruct the climatic forcing, glacier response, and runoff generation from a high‐elevation catchment in central Chile over the period 2000–2015 to provide insights into the differing contributions of debris‐covered and debris‐free glaciers under current and future changing climatic conditions. Model simulations with the physically based glacio‐hydrological model TOPKAPI‐ETH reveal a period of neutral or slightly positive mass balance between 2000 and 2010, followed by a transition to increasingly large annual mass losses, associated with a recent mega drought. Mass losses commence earlier, and are more severe, for a heavily debris‐covered glacier, most likely due to its strong dependence on snow avalanche accumulation, which has declined in recent years. Catchment runoff shows a marked decreasing trend over the study period, but with high interannual variability directly linked to winter snow accumulation, and high contribution from ice melt in dry periods and drought conditions. The study demonstrates the importance of incorporating local‐scale processes such as snow avalanche accumulation and spatially variable debris thickness, in understanding the responses of different glacier types to climate change. We highlight the increased dependency of runoff from high Andean catchments on the diminishing resource of glacier ice during dry years.     

Regional extreme‐dry‐spell frequency analysis using the L‐moments method in the middle reaches of the Yellow River Basin,China

In this research, the regional extreme‐dry‐spell frequency in the middle reaches of the Yellow River Basin (YRB) is studied by the L‐moments method. The research area has been divided into three subregions (regions 1, 2 and 3), which have been identified as homogenous regions. The results of a goodness‐of‐fit test indicate that a generalized normal distribution is the optimal regional model for regions 1 and 2 whereas a generalized Pareto distribution is the optimal regional model for region 3. The return period analysis figures out that the maximum length‐of‐dry‐spell (MxDS) values increase from south to north in the southern part and increase from northeast to southwest in the northern part of the middle reaches of the YRB under different return periods. The increments of quantiles of dry spell under different return levels indicate that drought risk in region 1 is higher than that in regions 2 and 3. The analysis of the occurrence day of MxDS shows that MxDS mostly occurred during winter of 1998 and spring of 1999 in most stations during the considered period. By comparing summer MxDS events, it can be found that mean MxDS values have slightly increased in regions 1 and 2 during the last five decades. The maximum mean MxDS values appeared in the 2000s for regions 1 and 2 and in the 1990s for region 3. The atmospheric circulation shows that the positive anomaly centre in the west of North China, negative anomaly centre in the east of North China and the strong western Pacific subtropical high led to the decrease of precipitation in North China during the summer of 1997. Copyright © 2013 John Wiley & Sons, Ltd.     

北京城市空间形态对热岛分布影响研究

在城市尺度上探究城市空间形态布局对城市热岛（UHI）影响研究,对于城市规划中通风环境改善、生态宜居城市建设具有重要意义。以北京为例,利用2009—2018年高密度自动气象站逐小时气温资料和2018年NPP/VIIRS夜光卫星资料,分析了UHI时空分布特征;利用2017年1∶2000基础地理信息和Landsat8卫星资料,开展了北京主城区建筑高度（BH）、建筑密度（BD）、建筑高度标准差（BSD）、容积率（FAR）、迎风截面积指数（FAI）、粗糙度长度（RL）、天空开阔度（SVF）、城市分数维（FD）等8个空间形态参数和植被覆盖度（VC）、不透水盖度（IC）、反照率（AB）等3个陆表参数的提取,并在城市尺度上开展了这些参数与UHI之间空间相关性及对UHI变化影响研究。结果显示：2009—2018年北京主城区年均、四季以及夜晚02时UHI均存在一个较为固定的形态,年均、春、夏、秋、冬、白天14时和夜晚02时UHI分别为1.81 ℃、1.50 ℃、1.43 ℃、2.16 ℃、2.17 ℃、0.48 ℃和2.77 ℃;8个空间形态参数在一年中大部分时段与UHI存在明显空间相关性,这种相关性在冬季强于其他季节,在夜晚02时强于白天14时,排名前三的分别为SVF、FAR和BD。空间形态参数已超越陆表参数成为UHI变化的重要驱动因子,11种参数对UHI变化的单独贡献为13.7%~63.7%,其中夏季、冬季和全年时段贡献最大的空间形态参数分别是BD（43.7%）、SVF（63.7%）和SVF（45.4%）,贡献最大的陆表参数分别是VC（42.6%）、AB（57.1%）和VC（45.3%）;夏季、冬季和全年时段多个参数对UHI变化的综合贡献分别为51.4%、69.1%和55.3%,主导要素分别为BD、SVF和BD。     

基于机器学习的稀疏样本下的土壤有机质估算方法

采用GRNN（Generalized Regression Neural Network）和RF（Random Forest）2种机器学习方法构建土壤有机质预测模型,以提高稀疏样本情况下的土壤有机质估算精度。依据北京市大兴区农用地2007年的土壤有机质采样数据,按MMSD准则（Minimization of the Mean of the Shortest Distances）抽稀为8种不同采样密度的样本（分别为2703、1352、676、339、169、85、43、22个样本）,分别采用GRNN、RF和Ordinary kriging对各采样密度下的未知采样点进行预测,采用交叉检验的方式验证各采样密度下未知样点的预测精度。随着采样点密度的下降,样点间的空间自相关性逐渐减弱,半变异函数的拟和精度变差,预测点结果误差增大,预测的置信度降低。当抽稀到43个和22个采样点时,样点间的空间自相关性接近歼灭,半变异函数的决定系数较低且残差较大。普通克里格受到采样点数量和采样密度、样点的空间结构的影响比较明显,其预测精度随采样点数量的下降而下降。在85个采样点及以下时,其预测值与观测值之间没有显著的相关性。GRNN和RF的预测精度受采样密度的影响不大,其预测精度在一个较小的范围内波动,其预测值围绕观测值在一定阈值空间内震荡波动,具有较好的相关性,在85个及以下的采样密度时,预测精度相对普通克里格有较大的提升。普通克里格法不适合在稀疏样本条件下空间插值计算,尤其是在空间自相关性比较弱的情况下。机器学习模型能充分学习土壤间环境信息、样点空间邻近效应信息,兼顾属性相似性和空间自相关,具有更好的稳定性和适应性,不容易受到采样点数量、构型和采样密度等因素的影响,即使在采样点空间自相关性很弱的情况下也能做出稳定预测精度。     

Probability Distribution of the Hull Motion and Mooring Line Tension of Two Floating Systems

The statistical and distribution characteristics of the responses of a floater and its mooring lines are essential in designing floating/mooring systems.In general,the dynamic responses of offshore structures obey a Gaussian distribution,assuming that the structural system,and sea loads are linear or weakly nonlinear.However,mooring systems and wave loads are considerably nonlinear,and the dynamic responses of hull/mooring systems are non-Gaussian.In this study,the dynamic responses of two types of floaters,semi-submersible and spar platforms,and their mooring lines are computed using coupled dynamic analysis in the time domain.Herein,the statistical characteristics and distributions of the hull motion and mooring line tension are discussed and compared.The statistical distributions of the dynamic responses have strong non-Gaussianity and are unreasonably fitted by a Gaussian distribution for the two floating and mooring systems.Then,the effects of water depth,wave parameters,and low-frequency and wave-frequency components on the non-Gaussianity of the hull motion,and mooring line tension are investigated and discussed.A comparison of the statistical distributions of the responses with various probability density functions,including the Gamma,Gaussian,General Extreme Value,Weibull,and Gaussian Mixture Model(GMM)distributions,shows that the GMM distribution is better than the others for characterizing the statistical distributions of the hull motion,and mooring line tension responses.Furthermore,the GMM distribution has the best accuracy of response prediction.     

The Characteristics of Storm Wave Behavior and Its Effect on Cage Culture Using the ADCIRC+SWAN Model in Houshui Bay,China

The current storm wave hazard assessment tends to rely on a statistical method using wave models and fewer historical data which do not consider the effects of tidal and storm surge.In this paper,the wave-current coupled model ADCIRC+SWAN was used to hindcast storm events in the last 30 years.We simulated storm wave on the basis of a large set of historical storms in the North-West Pacific Basin between 1985 and 2015 in Houshui Bay using the wave-current coupled model ADCIRC+SWAN to obtain the storm wave level maps.The results were used for the statistical analysis of the maximum significant wave heights in Houshui Bay and the behavior of wave associated with storm track.Comparisons made between observations and simulated results during typhoon Rammasun(2014)indicate agreement.In addition,results demonstrate that significant wave height in Houshui Bay is dominated by the storm wind velocity and the storm track.Two groups of synthetic storm tracks were designed to further investigate the worst case of typhoon scenarios.The storm wave analysis method developed for the Houshui Bay is significant in assisting government's decision-making in rational planning of deep sea net-cage culture.The method can be applied to other bays in the Hainan Island as well.     

Effects of a Dry-Mass Conserving Dynamical Core on the Simulation of Tropical Cyclones

The accurate forecasting of tropical cyclones(TCs) is a challenging task. The purpose of this study was to investigate the effects of a dry-mass conserving(DMC) hydrostatic global spectral dynamical core on TC simulation. Experiments were conducted with DMC and total(moist) mass conserving(TMC) dynamical cores. The TC forecast performance was first evaluated considering 20 TCs in the West Pacific region observed during the 2020 typhoon season. The impacts of the DMC dynamical core on forecasts o...     

黑河流域降水统计——动力降尺度问题研究

依据区域气候模式RIEMS2.0输出的3 km高分辨率数据和站点降水记录分析了中国西北黑河流域降水的动力降尺度和统计—动力降尺度问题,检验了多种因子组合下多元线性回归（MLR）和贝叶斯模式平均（BMA）降尺度模型,评估了降尺度降水的均方根误差、相关系数、方差百分率及“负降水”偏差率等方面的统计特征。结果表明,动力降尺度降水相关系数最高,误差也最大,降水方差达到观测值的1.5～2倍;除相关系数外,统计—动力降尺度模型的几个统计特征均最优,纯统计模型次之。检验表明,仅用700 hPa位势高度场、经向风和比湿等构建的统计降尺度模型估计的站点降水相关系数较低,均方根误差也较大。当在统计降尺度模型中引入模式降水因子后站点降水的估计得到明显改善,其中MLR类模型的降水相关系数和方差百分率均明显高于BMA类模型,均方根误差二者相当,但前者“负降水”出现频次明显大于后者,“负降水”偏差主要出现在降水稀少的冬半年及黑河中、下游干旱或极端干旱区,上游出现频率较低,其中MLR类模型“负降水”出现频次明显高于BMA类模型,后者仅出现在黑河中、下游地区。包含模式降水因子的统计—动力降尺度模型能减少“负降水”出现...     

Change detection of linear features in temporally spaced remotely sensed images using edge-based grid analysis

Automatic change detection of land cover features using high-resolution satellite images, is a challenging problem in the field of intelligent remote sensing data interpretation, and is becoming more and more effective for its applications viz. urban planning and monitoring, disaster assessment etc. In the present study, a change in detection approach based on the image morphology that analyses change in the local image grids is proposed. In this approach, edges from both the images are extracted and grid wise comparison is made by probabilistic thresholding and power spectral density analysis for identifying change area. One of the advantages of the proposed methodology is that the temporal images used in the change analysis need not be radiometrically corrected as analysis is based on edge extractions. The grid-based analysis further reduces the error, which might have been introduced by image mis-registration. The proposed methodology is validated by finding the temporal changes in the linear land cover features in parts of Kolkata city, India using three different image data-sets from LISS IV, Cartosat-1 and Google earth having varied spatial resolutions of 5.8 m, 2.5 m and about 1 m, respectively. The overall accuracy in identifying changes is found to be 64.82, 73.86 and 80.93% for LISS IV, Cartosat-1 and Google earth data-set, respectively.