Long-term variations of rainfall interception in different growth stages of Chinese fir plantations

Abstract

The dynamic properties of rainfall interception were investigated at three growth stages in Chinese fir plantations. The results showed that the annual interception ratio was significantly higher in mature stands than in young stands. For a storm event, interception rainfall amount increased with increasing rainfall, but interception ratio decreased. In contrast to dry season conditions, the interception amount was high in the wet seasons, while the interception ratio was low. The rates of change in interception ratio were extremely rapid in small rainfall events. There was little stemflow in Chinese fir forests due to the pyramid-shaped crowns and thick rough bark of the trees. The power model was suitable to describe the interception process for an individual rainfall event for stands of any age. Our results indicate that the interception process varied for stands of different ages in Chinese fir plantations due to contrasting canopy structures.     

古尔班通古特沙漠灌木冠幅预测模型

古尔班通古特沙漠是中国第二大沙漠,也是中国固定和半固定沙丘主要分布区,固沙灌木种较多。冠幅不仅是反映固沙灌木可视化的重要参数,也是反映沙漠植被生长情况的重要变量。以3种沙丘（固定沙丘、半固定沙丘和流动沙丘）上主要固沙灌木为研究对象,利用12种基础模型、BP(Backpropagation Neural Network)神经网络和支持向量机（Support Vector Machine,SVM）机器学习算法建立了基于固沙灌木株高和冠长率的冠幅预测模型,同时将两种机器学习算法拟合结果与基础模型进行比较,最终选出了适合研究区的冠幅预测模型。结果表明：（1）不同沙丘类型和不同灌木种类的最优冠幅预测模型不同,且固定沙丘和半固定沙丘模型优于流动沙丘。3种沙丘类型最优拟合为M2(Quadratic Model)模型;（2）白梭梭（Haloxylon persicum）在半固定沙丘和流动沙丘上拟合的最优模型分别为M2、M7(Gompertz),沙拐枣（Calligonum mongolicum）最优模型为M2,蛇麻黄（Ephedra distachya）和油蒿（Artemisia ordosica）在...     

植被分布对小流域产流影响的数值实验

基于二维运动波模型,建立了一个适用于小流域场次降雨产汇流过程的动力学模型。通过对典型小流域内不同区域(坡顶、坡中及坡底区域及距离流域出口的远近)种植植被时产流过程的数值模拟,分析了小流域内植被分布对产流过程的影响。结果表明:植被分布及其特性对小流域场次降雨产流有较明显的影响;下游区域种植植被的减水效果和延滞洪峰作用优于上游区域,陡坡区域减水效果优于缓坡区域,且郁闭度越大,这种差别越明显;在该研究条件下,下游区的减水效果可达到上游区的3倍;30%郁闭度条件下减水效果可达10%和20%郁闭度条件下的3倍和1.4倍。     

Hydro-climatic variability and forest fires in Mexico’s northern temperate forests

Global warming is likely modifying the hydrological cycle of forested watersheds. This report set as objectives to: a) assess the hydrological variables interception loss, I, potential and actual evapo-transpiration, E, Et, runoff, Q, and soil moisture content, θ; b) evaluate whether these variables are presenting consistent trends or oscillations that can be associated to global warming or climate variability; and c) relate θ to the number of wildfires and the burned area in Durango, Mexico. A mass balance approach estimated daily variables of the water cycle using sub-models for I and Et to calculate Q and θ for a time series from 1945 to 2007. Regression and auto-regressive and moving averaging (ARIMA) techniques evaluated the statistical significance of trends. The cumulative standardized z value magnified and ARIMA models projected statistically similar monthly and annual time series data of all variables of the water cycle. Regression analysis and ARIMA models showed monthly and annual P, I, E, and Et, Q, and θ do not follow consistent up or downward linear tendencies over time with statistical significance; they rather follow oscillations that could be adequately predicted by ARIMA models (r² ≥ 0.70). There was a consistent statistical association (p ≤ 0.05) of θ with the number of wildfires and the area burned regardless of the different spatial scales used in evaluating these variables. The analysis shows seasonal variability is increasing over time as magnifying pulses of dryness and wetness, which may be the response of the hydrological cycle to climate change. Further research must center on using longer time series data, testing seasonal variability with additional statistical analysis, and incorporating new variables in the analysis.     

PTrees: A point-based approach to forest tree extraction from lidar data

This paper introduces PTrees, a multi-scale dynamic point cloud segmentation dedicated to forest tree extraction from lidar point clouds. The method process the point data using the raw elevation values (Z) and compute height (H = Z − ground elevation) during post-processing using an innovative procedure allowing to preserve the geometry of crown points. Multiple segmentations are done at different scales. Segmentation criteria are then applied to dynamically select the best set of apices from the tree segments extracted at the various scales. The selected set of apices is then used to generate a final segmentation. PTrees has been tested in 3 different forest types, allowing to detect 82% of the trees with under 10% of false detection rate. Future development will integrate crown profile estimation during the segmentation process in order to both maximize the detection of suppressed trees and minimize false detections.     

硫铁矿地下深井巷堵水工程设计

本文工程设计阐述了在动水条件下,封堵水平巷道的“三段式”组合灌浆方法,以及定向钻进在地下深井巷堵水工程中的应用。     

江西泰和县森林生态系统水源涵养功能评估

森林生态系统综合水源涵养能力是林冠层、枯落物层和土壤层蓄水能力的总和。本文根据江西泰和县 2003 年森林资源二类调查,结合文献收集,从3 个作用层评估了泰和县森林生态系统的水源涵养量及其空间分布格局,比较了不同森林类型、林龄、海拔、坡度下的林冠降雨截留能力,枯落物最大持水量和土壤蓄水能力。结果表明,林冠层平均截留率为16.31%,枯落物层持水率为2.14%,土壤层蓄水率为81.55%,3 个层次总截留和蓄水量为1.41 亿m³。各种森林类型水源涵养量由大到小依次为：杉木林>马尾松林>湿地松林>阔叶林>毛竹林>灌木林> 混交林>经济林。幼林龄、中林龄、近熟林、成熟林和过熟林水源涵养贡献率分别为17.58%、65.39%、14.18%、 2.48%和0.37%,涵养水源能力随林龄的增加而增加。空间上,泰和县森林生态系统的综合水源涵养力表现出从东西两侧向中部递减的分布。不同立地条件下林分的合理经营与管理对于整个森林生态系统水源涵养功能的发挥具有重要的作用。     

腾格里沙漠人工固沙植被区生物土壤结皮对降水的拦截作用

在沙坡头人工植被区对人工模拟降水及天然降水后生物土壤结皮层含水率进行了动态定位监测,并分析了生物土壤结皮拦截降水的作用.结果表明:①生物土壤结皮的发育改变了原来沙丘剖面的水分分配格局,10%～40%的年降水量被拦截到结皮层;②随固沙年限的增加,生物土壤结皮的进一步发育和演变,其对降水的拦截能力也进一步提高;③生物土壤结皮对降水的拦截有明显的季节变化,7～10月份平均拦截雨量比4～6月份平均高出12%.     

Rainfall interception of typical ecosystems in the Heihe River Basin: Based on high temporal resolution soil moisture data

Journal of Geographical Sciences - Rainfall interception is of great significance to the fully utilization of rainfall in water limited areas. Until now, studies on rainfall partitioning process of...     

基于无人机影像的无瓣海桑单木提取与地上生物量估算

无瓣海桑(Sonneratia apetala)是中国红树林恢复种植最早引进的优质红树树种,其生产力在红树林群落中处于较高水平,具有显著的高生物量和能量积累。然而,由于红树林群落冠层密集、结构复杂,精确描绘无瓣海桑的单木树冠存在极大挑战性。传统的卫星遥感侧重于区域或更大尺度监测需求,而新兴的低空无人机遥感在更精细尺度的红树林生态监测中具有显著优势。以广东省珠海市淇澳岛红树林自然保护区为研究区,利用消费级无人机影像生成的冠层高度模型(Canopy Height Model, CHM)和种子区域生长(Seed Region Growing, SRG)算法进行无瓣海桑单木树冠提取,并建立基于地面调查数据获取的树高和胸径两者之间的回归关系,以优化无瓣海桑地上生物量异速生长方程,进而实现研究区单木尺度的无瓣海桑地上生物量估算。结果表明：基于无人机影像可以有效提取无瓣海桑单木树冠,其提取精度达到67%;验证了树高和胸径之间较高的相关性,提出了基于树高的无瓣海桑地上生物量异速生长方程;研究区无瓣海桑平均地上生物量的范围为2.99～247.24 t/hm²,平均值为92.14 t...