Characterization of sudden and sustained base flow jump hydrologic behaviour in the humid seasonal tropics of the Panama Canal Watershed     

Yanyan Cheng  Fred L. Ogden  Jianting Zhu 《水文研究》2020,34(3):569-582

Base flows are important for tropical regions with pronounced dry seasons, which are facing increasing water demands. Base flow generation, however, is one of the most challenging hydrological processes to characterize in the tropics. In many years during the May–December wet season in the Panama Canal Watershed (PCW), base flows in rivers abruptly increase. This increase persists until the start of the December–April dry season. Understanding this unusual base flow jump (BFJ) behaviour is critical to improve water provisioning in the seasonal tropics, especially during droughts and extended dry seasons. This study developed an integrated approach combining piecewise regression on cumulative average base flow and sensitivity analysis to calculate the timing and magnitude of BFJ. Rainfall, forest cover, mean land surface slope, catchment area, and estimated subsurface storage were tested as predictors for the occurrence and magnitude of the BFJs in seven subcatchments of the PCW. Sensitivity analysis on correlated predictors allowed ranking of predictor contributions due to isolated and cross-correlation effects. Correlations between observed BFJs and BFJs predicted by watershed and rainfall-related predictors were 0.92 and 0.65 for BFJ timing and magnitude, respectively. Forest cover was the second most significant predictor after cumulative rainfall for jump magnitude, owing to larger subsurface storage and groundwater recharge in forests than pastures. Catchments in the mountainous eastern PCW always generated larger jumps due to their higher rainfall and greater forest cover than the western PCW catchments. The cross-correlations between predictors contributed to more than 50% of the jump variances. The results demonstrate the importance of rainfall gradient and catchment characteristics in affecting the sudden and sustained BFJs, which can help inform land management decisions intended to enhance water supplies in the tropics. This study underscores the need for more research to further understand the hydrological processes involved in the BFJ phenomenon, including better BFJ models and field characterizations, to help improve tropical ecosystem services under a changing environment.  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   

Integrating spectral and non-spectral data to improve urban settlement mapping in a large Latin-American city     

Feilin Lai 《地理信息系统科学与遥感》2020,57(6):830-844

ABSTRACT

Information on urban settlements is crucial for sustainability planning and management. While remote sensing has been used to derive such information, its applicability can be compromised due to the complexity in the urban environment. In this study, we developed a remote sensing method to map land cover types in a large Latin-American city, which is well known for its mushrooming unplanned and informal settlements. After carefully considering the landscape complexity there, we designed a data fusion method combining multispectral imagery and non-spectral data for urban and land mapping. Specifically, we acquired a cloud-free Landsat-8 image and two non-spectral datasets, i.e., digital elevation models and road networks. Then, we implemented a set of experiments with different inputs to evaluate their merits in thematic mapping through a supervised protocol. We found that the map generated with the multispectral data alone had an overall accuracy of 73.3% but combining multispectral imagery and non-spectral data yielded a land cover map with 90.7% overall accuracy. Interestingly, the thermal infrared information helped substantially improve both the overall and categorical accuracies, particularly for the two urban classes. The two types of non-spectral data were critical in resolving several spectrally confused categories, thus considerably increasing the mapping accuracy. However, the panchromatic band with higher spatial resolution and its derived textural measurement only generated a marginal accuracy improvement. The novelties of our work are with the successful separation between the two major types of urban settlements in a complex environment using a carefully designed data fusion approach and the insight into the relative merits of the thermal infrared information and non-spectral data in helping resolve the issue of class ambiguity. These findings should be valuable in deriving accurate urban settlement information which can further advance the research on socio-ecological dynamics and urban sustainability.  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   

地方政府土地出让干预对区域工业碳排放影响的对比分析——以中国8大经济区为例     

王博  吴天航  冯淑怡 《地理科学进展》2020,39(9):1436-1446

探讨不同区域地方政府干预对碳排放的影响差异,对于中国推进碳减排战略、协调区域经济社会发展具有重要意义。鉴于此,论文基于地方政府土地出让的视阈,以中国8大经济区为研究对象,有机耦合STIRPAT模型与CKC模型,构建形成STIRPAT拓展模型,并使用2007—2016年中国28个省(市、自治区)的工业面板数据,对比考察8大经济区政府土地出让干预对区域碳排放的影响差异。结果表明:不同经济区的地方政府土地出让干预对区域碳排放的影响存在显著差异。其中,同为CKC“倒N”型的北部沿海、南部沿海、长江中游经济区,其政府土地出让干预对区域碳排放的影响呈现出北部沿海经济区为负、南部沿海经济区为正、长江中游经济区无显著影响的差异效果;同为CKC“倒U”型的东北、西南和西北经济区,其政府土地出让干预对区域碳排放的影响,东北和西南经济区都显著为负,西北经济区未表现出显著影响;同为CKC“U”型的东部沿海和黄河中游经济区,其政府土地出让干预对碳排放也呈现出前者为负、后者为正的相反影响。研究结果可为制定碳减排差别化政策、协调区域可持续发展提供参考。  相似文献   

土地利用视角下城市交通事故驱动机理的研究进展     

王成  谢波 《地理科学进展》2020,39(9):1597-1606

城镇化与机动交通的快速发展,引发了城市土地利用与交通系统的重塑,导致城市交通安全问题日益严峻。为了优化土地利用布局并改善交通安全,需要从土地利用视角开展交通事故的驱动机理研究。国内外该方面研究形成了以交通流量和交通速度为主要中介因素联系土地利用与交通事故的经典理论框架,却忽略了源于土地利用并深刻影响交通安全的交通需求因素,导致缺乏“土地利用—交通需求—交通事故”完整路径链的研究。论文通过综述该领域文献,在归纳总结城市交通事故影响因素的基础上,揭示土地利用视角下交通事故的驱动机理并探讨未来研究方向。研究指出,土地利用的多维属性特征对交通事故具有重要影响,土地利用与交通系统的动态匹配关系及其对出行行为的影响是揭示交通事故驱动机理的关键突破口,对于构建交通安全导向的城市土地利用模式具有重要的理论与实践意义。  相似文献   

China’s rural revitalization and development: Theory,technology and management     

Liu  Yansui  Zang  Yuzhu  Yang  Yuanyuan 《地理学报(英文版)》2020,30(12):1923-1942

Journal of Geographical Sciences - The urban-rural transformation from dichotomy to integration is a gradual process. Like rural areas in many countries, Chinese rural society is experiencing a...  相似文献   

An overview of clustering methods for geo-referenced time series: from one-way clustering to co- and tri-clustering     

Xiaojing Wu  Raul Zurita-Milla  Changqing Song 《International journal of geographical information science》2020,34(9):1822-1848

  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   

基于金矿规格单元数据的机器学习方法在成矿建模分析中的应用     

张野  李明超  韩帅  任秋兵  朱月琴 《大地构造与成矿学》2020,(2):183-191

现代金矿勘察主要是通过综合地球化学和地质测量等数字化方法对深部矿床进行研究,所需要的人力物力成本较高。而通过分析积累的金矿规格单元数据,可以建立金矿成矿情况与相关成矿元素含量之间的非线性关系,从已有的勘查数据中寻找金矿成矿的一般规律。本文基于与金矿相关的成矿元素含量数据,分别采用逻辑斯蒂回归、随机森林和决策树方法对原始数据和重采样数据进行训练,综合运用召回率、精确率和准确率对模型进行评价。通过对比发现,在训练和测试原始数据过程中,由于每组之间数据量的巨大差距,导致成矿数据被淹没;而在训练重采样数据过程中,随机森林在召回率和准确率方面均有较好的表现,分别达到了90.63%和70.78%;并最终分析了随机森林模型中不同分类边界对于金矿成矿情况预测结果的影响。利用不同的测量指标对模型进行评价分析,使模型更适用于金矿成矿预测,可有效地提高金矿勘察的效率。  相似文献