High-frequency monitoring of hydrological and biogeochemical fluxes in forested catchments of southern Chile     

Cristián Frêne  Juan J. Armesto  Freddy Véliz  Fernando D. Alfaro  Kathleen C. Weathers 《水文研究》2021,35(5):e14175

The variability of rainfall-dependent streamflow at catchment scale modulates many ecosystem processes in wet temperate forests. Runoff in small mountain catchments is characterized by a quick response to rainfall pulses which affects biogeochemical fluxes to all downstream systems. In wet-temperate climates, water erosion is the most important natural factor driving downstream soil and nutrient losses from upland ecosystems. Most hydrochemical studies have focused on water flux measurements at hourly scales, along with weekly or monthly samples for water chemistry. Here, we assessed how water and element flows from broad-leaved, evergreen forested catchments in southwestern South America, are influenced by different successional stages, quantifying runoff, sediment transport and nutrient fluxes during hourly rainfall events of different intensities. Hydrograph comparisons among different successional stages indicated that forested catchments differed in their responses to high intensity rainfall, with greater runoff in areas covered by secondary forests (SF), compared to old-growth forest cover (OG) and dense scrub vegetation (CH). Further, throughfall water was greatly nutrient enriched for all forest types. Suspended sediment loads varied between successional stages. SF catchments exported 455 kg of sediments per ha, followed by OG with 91 kg/ha and CH with 14 kg/ha, corresponding to 11 rainfall events measured from December 2013 to April 2014. Total nitrogen (TN) and phosphorus (TP) concentrations in stream water also varied with rainfall intensity. In seven rainfall events sampled during the study period, CH catchments exported less nutrients (46 kg/ha TN and 7 kg/ha TP) than SF catchments (718 kg/ha TN and 107 kg/ha TP), while OG catchments exported intermediate sediment loads (201 kg/ha TN and 23 kg/ha TP). Further, we found significant effects of successional stage attributes (vegetation structure and soil physical properties) and catchment morphometry on runoff and sediment concentrations, and greater nutrients retention in OG and CH catchments. We conclude that in these southern hemisphere, broad-leaved evergreen temperate forests, hydrological processes are driven by multiple interacting phenomena, including climate, vegetation, soils, topography, and disturbance history.  相似文献   

Travel times for snowmelt-dominated headwater catchments: Influences of wetlands and forest harvesting,and linkages to stream water quality     

Jason A. Leach  James M. Buttle  Kara L. Webster  Paul W. Hazlett  Dean S. Jeffries 《水文研究》2020,34(10):2154-2175

The time it takes water to travel through a catchment, from when it enters as rain and snow to when it leaves as streamflow, may influence stream water quality and catchment sensitivity to environmental change. Most studies that estimate travel times do so for only a few, often rain-dominated, catchments in a region and use relatively short data records (<10 years). A better understanding of how catchment travel times vary across a landscape may help diagnose inter-catchment differences in water quality and response to environmental change. We used comprehensive and long-term observations from the Turkey Lakes Watershed Study in central Ontario to estimate water travel times for 12 snowmelt-dominated headwater catchments, three of which were impacted by forest harvesting. Chloride, a commonly used water tracer, was measured in streams, rain, snowfall and as dry atmospheric deposition over a 31 year period. These data were used with a lumped convolution integral approach to estimate mean water travel times. We explored relationships between travel times and catchment characteristics such as catchment area, slope angle, flowpath length, runoff ratio and wetland coverage, as well as the impact of harvesting. Travel time estimates were then used to compare differences in stream water quality between catchments. Our results show that mean travel times can be variable for small geographic areas and are related to catchment characteristics, in particular flowpath length and wetland cover. In addition, forest harvesting appeared to decrease mean travel times. Estimated mean travel times had complex relationships with water quality patterns. Results suggest that biogeochemical processes, particularly those present in wetlands, may have a greater influence on water quality than catchment travel times.  相似文献   

Update and spatial extension of strategic forest inventories using time series remote sensing and modeling     

《International Journal of Applied Earth Observation and Geoinformation》2020

Up-to-date forest inventory information relating the characteristics of managed and natural forests is fundamental to sustainable forest management and required to inform conservation of biodiversity and assess climate change impacts and mitigation opportunities. Strategic forest inventories are difficult to compile over large areas and are often quickly outdated or spatially incomplete as a function of their long production cycle. As a consequence, automated approaches supported by remotely sensed data are increasingly sought to provide exhaustive spatial coverage for a set of core attributes in a timely fashion. The objective of this study was to demonstrate the integration of current remotely-sensed data products and pre-existing jurisdictional inventory data to map four forest attributes of interest (stand age, dominant species, site index, and stem density) for a 55 Mha study region in British Columbia, Canada. First, via image segmentation, spectrally homogenous objects were derived from Landsat surface-reflectance pixel composites. Second, a suite of Landsat-based predictors (e.g., spectral indices, disturbance history, and forest structure) and ancillary variables (e.g., geographic, topographic, and climatic) were derived for these units and used to develop predictive models of target attributes. For the often difficult classification of dominant species, two modelling approaches were compared: (a) a global Random Forests model calibrated with training samples collected over the entire study area, and (b) an ensemble of local models, each calibrated with spatially constrained local samples. Accuracy assessment based upon independent validation samples revealed that the ensemble of local models was more accurate and efficient for species classification, achieving an overall accuracy of 72% for the species which dominate 80% of the forested areas in the province. Results indicated that site index had the highest agreement between predicted and reference (R² = 0.74, %RMSE = 23.1%), followed by stand age (R² = 0.62, %RMSE = 35.6%), and stem density (R² = 0.33, %RMSE = 65.2%). Inventory attributes mapped at the image-derived unit level captured much finer details than traditional polygon-based inventory, yet can be readily reassembled into these larger units for strategic forest planning purposes. Based upon this work, we conclude that in a multi-source forest monitoring program, spatially localized and detailed characterizations enabled by time series of Landsat observations in conjunction with ancillary data can be used to support strategic inventory activities over large areas.  相似文献   

BDS卫星钟差半参数平差模型异常数据探测与处理     

李文涛  颜雄  夏磊  任青阳  陈洁  潘雄 《测绘学报》2020,49(1):55-64

针对北斗卫星钟差数据中出现钟跳、粗差等异常数据频次较高的问题,将半参数平差模型引入BDS的钟差数据的处理过程中。首先,在考虑系统误差的同时,改进了常用的钟差模型;其次,综合考虑异常数据和系统误差,利用补偿最小二乘原理和极值求解方法,详细推导了分离异常数据前后参数和非参数估计值与相应观测值改正数的关系表达式,实现了异常数据的定值、参数求解和系统误差分离。在此基础上,引入Cook距离,给出了利用参数分量和非参数分量的Cook距离及混合Cook距离,去判断异常值的位置,并给出了一些参数的选取方法及相应的处理措施,实现了卫星钟差异常数据的定位和定值以及部分系统误差的分离。最后,采用武汉大学GNSS中心提供的采样间隔为5 min的北斗卫星精密钟差数据,将本文方法与常用方法进行了试验对比。试验结果表明,本文方法能够有效地识别并处理卫星钟差数据中的异常值,有效克服了基于经验阈值钟差异常数据探测方法的不足,且该方法对于量级较小的异常钟差数据也有很好的探测效果,一定程度丰富了现有的BDS钟差数据质量控制方法。  相似文献   

基于时相变化的晴空条件下Himawari-8 AHI火点检测     

鄢俊洁  瞿建华  冉茂农  张芳芳 《遥感学报》2020,24(5):571-577

Himawari-8静止气象卫星具有高空间分辨率、高观测频次和高时效特点,对于火点检测具有很强优势。对Himawari-8卫星的3.9μm和11.2μm两通道亮温进行了连续时相变化研究,得出两通道的亮温在时间上的变化差值稳定且规律明显。根据两通道的亮温时相特征,考虑白天可见光对3.9μm通道的影响,并结合火点产生时引起的亮温变化特征,提出了适用于晴空条件下改进的火点检测算法。在多处进行了此算法的实验,例如2018-11-27 T 16:40(UTC时)河北张家口市桥东区一化工厂附近发生的严重爆炸起火事件以及2019-02-28澳大利亚西南部发生的火灾事件,均快速有效的检测到了火点。实验表明,改进的火点检测算法能很好的进行火点检测,并能解决晨昏交界、冰雪下垫面、常规火源点、太阳耀光等火点检测的难题。  相似文献   

Sentinel-2卫星落叶松林龄信息反演   总被引：1，自引：0，他引：1  

唐少飞  田庆久  徐凯健  徐念旭  岳继博 《遥感学报》2020,24(12):1511-1524

林龄结构信息能够有效反映区域森林群落不同生长阶段的固碳能力，对于评估森林生态系统的健康状况具有重要意义。本研究以中国温带典型优势树种落叶松林为研究对象，分别选择其芽萌动期、展叶期和落叶期时段的Sentinel-2影像，采用多元线性回归（MLR）、随机森林（RF）、支持向量机回归（SVR）、前馈反向传播神经网络（BP）以及多元自适应回归样条（MARS）等5种方法依次构建落叶松林龄反演模型。通过相关性分析首先确定最佳遥感反演物候期，并在此基础上根据相关性差异筛选出5个最优特征变量用于模型反演，分别为冠层含水量（CWC），归一化水体指数（NDWI），叶面积指数（LAI），光合有效辐射吸收率（FAPAR）和植被覆盖度（FVC）。研究结果表明，展叶期为落叶松林最佳遥感反演物候期。除植被衰减指数（PSRI）以及落叶期的NDVI、RVI外，落叶松林龄与各指标之间均呈负相关关系，其中与冠层含水量（CWC）的相关性最高，pearson相关系数达到-0.74（p<0.01）。此外，不同模型反演结果表明，随机森林模型（RF）为最佳落叶松林龄估测模型，其平均决定系数R²和平均均方根误差RMSE分别为0.89和2.91 a；多元线性回归模型（MLR）的林龄估测结果最差，其平均决定系数R²和平均均方根误差RMSE仅为0.57和5.69 a，非线性模型能更好的解释林龄与建模变量之间的关系。  相似文献   

景电灌区移民对祁连山植被恢复的相对生态价值          下载免费PDF全文

赵建林  康德奎  彭维恩  王建礼  史中兴  陈天顺  董志洋  汪杰  常兆丰 《干旱区地理》2020,43(1):182-189

近些年来，生态系统的服务价值研究已成为生态学以及生态经济学领域中的一个热点问题。祁连山被称为伸进西北干旱区的一座湿岛，在我国“一带一路”建设中占有重要地位。景电灌区兴建以来从祁连山移出了大量农牧民。那么，景电灌区移民对祁连山植被恢复的生态价值如何呢？以景电灌区移民涉及到的祁连山东端景泰、古浪、天祝3县山区为研究区，用价值工程方法对从祁连山区向景电灌区移民退耕退牧还林还草的生态价值做了分析，并与模型因子当量法的计算结果进行了比较。结果表明：祁连山向景电灌区移民退耕退牧还林还草总的生态价值为37.458 1×10⁸元。其中，退耕还林还草的生态价值为37.438 6×0⁸元，退牧后草场植被盖度增加的生态价值为194.79×104元。计算结果为用COSTANZA和谢高地模型因子当量法计算得的祁连山向景电灌区移民退耕退牧还林还草总的生态服务价值40.054 0×0⁸元的93.52%。两种方法计算结果祁连山向景电灌区移民退耕退牧还林还草总的生态价值为景电工程年总成本1.45×0⁸元的25.8~27.6倍。两种计算结果一致表明，景电灌区生态移民对祁连山植被恢复的生态价值十分突出。由此也可以看出，COSTANZA和谢高地模型因子当量法适用于祁连山的生态服务价值分析。  相似文献   

陕北地区退耕还林还草工程土壤保护效应的时空特征   总被引：1，自引：1，他引：0  

刘文超  刘纪远  匡文慧 《地理学报(英文版)》2020,30(3):401-422

This paper looks at the Green for Grain Project in northern Shaanxi Province.Based on remote sensing monitoring data,this study analyzes the locations of arable land in northern Shaanxi in the years 2000,2010 and 2013 as well as spatio-temporal changes over that period,and then incorporates data on the distribution of terraced fields to improve the input parameters of a RUSLE model and simulate and generate raster data on soil erosion for northern Shaanxi at different stages with a accuracy verification.Finally,combined with the dataset of farmland change,compared and analyzed the characteristics of soil erosion change in the converted farmland to forest(grassland)and the unconverted farmland in northern Shaanxi,so as to determine the project’s impact on soil erosion over time across the region.The results show that between 2000 and 2010,the soil erosion modulus of repurposed farmland in northern Shaanxi decreased 22.7 t/ha,equivalent to 47.08%of the soil erosion modulus of repurposed farmland in 2000.In the same period,the soil erosion modulus of non-repurposed farmland fell 10.99 t/ha,equivalent to 28.6%of the soil erosion modulus of non-repurposed farmland in 2000.The soil erosion modulus for all types of land in northern Shaanxi decreased by an average of 14.51 t/ha between 2000 and 2010,equivalent to 41.87%of the soil erosion modulus for the entire region in 2000.This suggests that the Green for Grain Project effectively reduced the soil erosion modulus,thus helping to protect the soil.In particular,arable land that was turned into forest and grassland reduced erosion most noticeably and contributed most to soil conservation.Nevertheless,in the period 2010 to 2013,which was a period of consolidation of the Green for Grain Project,the soil erosion modulus and change in volume of soil erosion in northern Shaanxi were significantly lower than in the previous decade.  相似文献   

A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing     

Peng Yue  Fan Gao  Boyi Shangguan  Zheren Yan 《International journal of geographical information science》2020,34(11):2243-2274

ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.  相似文献   

黑龙江哈尔滨白渔泡国家湿地公园沼泽、林地和农田土壤物理、化学和生物性质差异     

丁俊男  于少鹏  史传奇 《湿地科学》2020,18(1):77-84

为了揭示黑龙江哈尔滨白渔泡国家湿地公园沼泽、林地和农田土壤物理、化学和生物性质的差异,于2018年7月25日~8月2日,在湿地公园内,在天然芦苇(Phragmites australis)沼泽、林地、旱田和水田中设置采样地,采集不同深度(0~10 cm、10~20 cm和20~30 cm)的土壤样品,测定土壤样品的物理、化学和生物指标。研究结果表明,白渔泡国家湿地公园不同采样地土壤指标存在差异;与天然芦苇沼泽土壤相比,其它采样地土壤的含水量明显偏低,土壤全氮、全磷、碱解氮和有机质含量都明显偏小,水田土壤速效磷含量偏大;天然芦苇沼泽土壤脲酶、硝酸还原酶、纤维素酶、蛋白酶和β-葡萄糖苷酶活性都高于林地和农田土壤,水田0~10 cm和10~20 cm深度土壤的硝酸还原酶活性显著高于旱田和林地;与天然芦苇沼泽土壤相比,旱田土壤小于0.25 mm的小团聚体含量偏大,而其它采样地土壤的各粒级团聚体的比例变化较小,水田土壤团聚体平均重量直径比天然芦苇沼泽和旱田土壤低。  相似文献