Effects of juniper removal and rainfall variation on tree transpiration in a semi‐arid karst: evidence of complex water storage dynamics

Brush removal is widely practiced as a tool for increasing groundwater recharge, but its efficacy depends greatly on the way in which the removed species interact with the hydrological system relative to the vegetation replacing it. We examined the effects of Ashe juniper removal in the recharge zone of the Edwards Aquifer, Texas, USA, a karst aquifer. The study was conducted in an Ashe juniper (Juniperus ashei)–live oak (Quercus fusiformis) woodland on a hill slope composed of rocky, shallow soils over fractured limestone bedrock. Ashe juniper is a native species that has been encroaching grasslands and savannas over the past century. In September 2008, a plot was cleared of 90% of its juniper trees. Tree transpiration, predawn water potentials and vegetation cover across the cleared plot and an adjacent reference site were measured from May 2009 to December 2011. Stand‐level tree transpiration from May 2009 to March 2010 was diminished by a severe summer drought in 2009, from which trees were slow to recover. Subsequently, tree transpiration was 5–10× higher in the woodland compared to the clearing. For all of 2011, also a drought year, tree transpiration in the woodland exceeded precipitation inputs, indicating a high capacity for water storage at the study site. However, site differences for oak trees were generally larger than for juniper trees. While juniper removal accounted for a 431 mm year^?1 difference in tree transpiration between sites, vegetation cover in the clearing increased from 42% to 90% over two years, suggesting that understory growth was increasingly compensating for the loss of juniper transpiration. We conclude that the removal of a relatively shallow‐rooted tree, when replaced with herbaceous vegetation and low shrubs, has little effect on deep recharge. By contrast, successive years of precipitation extremes may be more effective increasing recharge by lowering the water transport capacity of trees in the aftermath of severe drought. Copyright © 2016 John Wiley & Sons, Ltd.     

On the controls of preferential flow in soils of different hillslope position and lithological origin

Soils derived from different lithologies and their controls on preferential flow remain underexplored in forested landscapes. In the same lithology, the propensity for preferential flow occurrence at different hillslope positions also remains largely elusive. By utilizing a soil moisture response time method, we compared preferential flow occurrence between a shale site (Shale Hills, silt loam soils) and a sandstone site (Garner Run, sandy loam soils) at four hillslope positions: ridge-top, North- and South-facing mid-slopes and toe slope, for over 2 years. The catchments are neighbouring and covered by temperate forest. For the four hillslope positions, Shale Hills had higher preferential flow frequencies compared to Garner Run. Between these two catchments, the South-facing mid-slope sites showed the highest contrasts in preferential flow frequency (33.5% of events at Shale Hills vs. 8.8% at Garner Run) while the ridge-top sites showed the lowest contrasts (18.7 vs. 13.2%). Additionally, over the unfrozen period, for seven out of eight monitoring sites, drier antecedent conditions tended to be more favourable for preferential flows to occur, with significant (p < .01) relationships at two sites. Except for the South-facing mid-slope sites, both Shale Hills and Garner Run had two preferential flow pathways. The characteristic preferential flow pathways at Shale Hills were the B_w and C horizons, and for Garner Run, preferential flow moved from the E/AE horizon to the B_w horizon. This study shows that shale-derived soils tended to have higher preferential flow occurrence than sandstone soils, but hillslope positions exhibit different levels of contrasts. More effort should be paid to study the impact of lithology on preferential flows in the context of land surface modelling and biogeochemical reactions to improve ecosystem services of headwater catchments.     

Spatial interpolation using conditional generative adversarial neural networks

ABSTRACT

Spatial interpolation is a traditional geostatistical operation that aims at predicting the attribute values of unobserved locations given a sample of data defined on point supports. However, the continuity and heterogeneity underlying spatial data are too complex to be approximated by classic statistical models. Deep learning models, especially the idea of conditional generative adversarial networks (CGANs), provide us with a perspective for formalizing spatial interpolation as a conditional generative task. In this article, we design a novel deep learning architecture named conditional encoder-decoder generative adversarial neural networks (CEDGANs) for spatial interpolation, therein combining the encoder-decoder structure with adversarial learning to capture deep representations of sampled spatial data and their interactions with local structural patterns. A case study on elevations in China demonstrates the ability of our model to achieve outstanding interpolation results compared to benchmark methods. Further experiments uncover the learned spatial knowledge in the model’s hidden layers and test the potential to generalize our adversarial interpolation idea across domains. This work is an endeavor to investigate deep spatial knowledge using artificial intelligence. The proposed model can benefit practical scenarios and enlighten future research in various geographical applications related to spatial prediction.     

P wave amplitude measurements at the Kaapvaal network: do they help in resolving deep earth structure?

Measurements of the amplitudes of seismic body waves at teleseismic distances have rarely resolved significant features mainly because of the large scatter of the data. However, amplitudes are easy to measure and may provide additional constraints on structure to supplement times and waveforms. A new approach to analysing body wave amplitudes at a regional network of similar instruments seeks to minimize scatter by first deriving amplitude station corrections analogous to station corrections for times. After correction for station effects, amplitudes from several events can be combined to give regional amplitude–distance curves without using information on event magnitudes. However, the earthquakes providing the observations must lie in a restricted range of azimuths from the stations of the network and provide considerable overlap in the range of distances between adjacent events, with no gaps in distance coverage. The advantages of the method are explored using P wave amplitudes from two sets of earthquakes in the Indonesian and South American regions recorded by the Kaapvaal network deployed across southern Africa. In the first example, high amplitudes near 88° distance suggest the presence of a small discontinuity at the top of D″ that causes constructive interference between the closely separated arrivals of a small triplication in the travel times. The second example, supplemented by calculations using synthetic data, shows how long-wavelength regional variations in amplitudes can be resolved to assist the interpretation of times and waveforms. However, the limited range of distances in the observations and lateral heterogeneities at any depths can result in bias or tilt of the amplitude–distance relationships. Constraining the depths of the structure causing the long-wavelength variations is a subject for future research.     

On the suitability of 1 s geophone for ambient noise measurements in the 0.1–20Hz frequency range: experimental outcomes

Following the ongoing debate about suitability of short-period sensor for seismic noise measurements at frequencies lower than 1 Hz, in this study we compare recordings from two different seismometers (Güralp CMG-3ESPC and Mark L4C-3D) installed side by side in the GeoForschungsZentrum laboratory. The comparison carried out in terms of Power Spectral Density and coherency analysis shows an excellent agreement between the short-period and the broad-band recordings in the frequency band 0.2–20 Hz. Therefore, this result highlights that with a calibrated short-period sensor one can obtain the same results that would be obtained by using a broad-band seismometer in the band of engineering interest.     

Estimation of the Amount of Suspended Sediment in the Tigris River using Artificial Neural Networks

The amount of sediment should be taken into consideration in the planning of water structures for efficient use of limited water resources. It is important to estimate the amount of sediment for the successful operation of these structures in their future performances. Such estimations can be achieved by Artificial Neural Network (ANNs) with low error percentages as seen in many other disciplines. These networks also enable the modeling of nonlinear relationships between the parameters affecting the event. The purpose of this research is to establish models for sediment amounts in the Tigris River at the Diyarbakir measurement station in Turkey. Rainfall, temperature and discharge are taken as independent variables in the models, whereas sediment is taken as the dependent variable. Fourteen different models are generated using ANNs and Regression Analysis (RA). The results are compared with each other and with the observed data. The relative error and determination coefficient are used as comparison criteria. It is concluded that due to their nonlinear modeling capability, ANNs give better results than RA.     

基于特征面向对象的地理网络模型研究

地理网络建模强调的是对逻辑网络中的节点和联线的网络拓扑和语义操作过程。而传统GIS矢量数据表达所采用的平面图原子级弧段-节点数据模型强调的是几何信息的表达。对此,作者讨论了如何将基于特征的GIS概念建模方法引入地理网络表达中,克服平面图数据模型的不足之处,发展基于特征的地理网络数据模型,并着重阐述了逻辑网络模型的特点和应用特征。在地理网络的表达方法中,作者分析了面向对象方法和数据库技术相结合的途径,比较了传统关系模型和面向对象模型在地理网络表达中的差异,以及面向对象方法在地理网络路径系统表达和动态分段及其网络连通性规则表达中的优势所在。     

基于模糊神经网络的煤与瓦斯突出区域预测研究

煤与瓦斯突出影响因素间复杂的非线性关系,难以用经典的数学理论建立精确的预测模型。本文用自适应模糊神经网络技术建立煤与瓦斯突出预测系统,以模糊数学作为表达与处理不精确数据、模糊信息条件的手段,以自适应BP神经网络作为解决问题的途径。结果表明:方法可行,预测精度高,能够满足要求,进一步充实了煤与瓦斯突出区域预测理论      

地图学网站的设计与实现

随着计算机与互联网技术的发展与应用,古老的地图正在发挥着越来越重要的作用。为了普及地图学知识,增加人们对地图的了解与应用,适应网络化教育发展的需要,我们建立了专业性的“地图学网站”。本文介绍了该地图学网站的主要内容、功能设计与实现方法,对地图学网站及网络地图的设计与实现进行了初步的探索。     

圆弧破坏边坡反演设计的ANN方法与ANFIS方法的比较研究

圆弧破坏边坡反演设计方法,是根据边坡的岩土力学参数及边坡高度,在确保安全系数满足要求的前提下,对圆弧破坏边坡的边坡角进行设计的一种新方法。建立圆弧破坏边坡反演设计方法的关键,就是要对大量稳定圆弧破坏边坡实例加以集成,以建立从{ , c, , H, F}到 的映射。文中收集了大量稳定圆弧破坏边坡实例,采用ANN和ANFIS对其进行了集成,分别建立了圆弧破坏边坡反演设计的ANN方法和ANFIS方法,进而又采用圆弧破坏边坡实例对两者的反演结果进行了比较。结果表明,ANFIS更适合于用来建立圆弧破坏边坡反演设计方法。