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1.
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   
2.
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   
3.
刘敏  姜会明  姜天龙 《地理科学》2020,40(12):2037-2045
按照粮食的产销情况,将全国划分为3类粮食功能区域,利用固定效应模型和门槛效应模型分析了农机投入对农业绿色全要素生产率(GTFP)的影响及门槛效应的区域差异。结果表明:农机投入对农业GTFP的影响程度存在区域异质性,农机投入对粮食主销区农业GTFP提升的促进作用最大,粮食产销平衡区次之,粮食主产区最小;农机投入对农业GTFP的影响路径亦存在区域差异,粮食主产区和产销平衡区的农机投入通过促进农业技术效率和农业技术进步进而推动农业GTFP提升,粮食主销区的农机投入通过促进农业技术进步推动农业GTFP提升;农机投入对粮食主产区农业GTFP的影响存在双门槛效应,对粮食主销区和产销平衡区农业GTFP的影响存在单门槛效应。  相似文献   
4.
基于甘肃河西走廊15个国家基准基本站点提供的1966年1月1日~2018年12月31日春季(3~5月)逐日最低气温值数据,利用线性回归分析方法、Spline空间插值法和Mann-Kendall趋势和突变检验法,探讨了河西走廊地区1966—2018年春季(3~5月)寒潮频次变化及其影响因子。研究表明:(1) 1966—2018年河西走廊地区春季(3~5月)单站寒潮频次总体呈现下降趋势〔–0.098次·(10 a)–1〕,其中1980—2010年寒潮频次呈显著下降趋势,2010年之后下降趋势变缓,未通过显著性检验;区域寒潮53 a来频次总体呈缓慢下降趋势〔–0.015次·(10 a)–1〕。(2) 近53 a河西走廊地区春季三个月中,单站寒潮总量4月>3月>5月,其中4月、5月寒潮频次下降不明显,3月频次下降显著。(3) 空间上,大致以北大河和黑河干流为界,两河中间区域春季寒潮频次低,而北大河以北和黑河干流以东区域则是寒潮高值区,走廊外围地区寒潮频次较高,且大多呈显著下降趋势,寒潮频次与气温距平存在明显负相关关系,内部地区变化趋势不明显。(4) 河西地区春季寒潮频次受气候变暖、地形和大气环流的影响,寒潮频次变化趋势存在地区差异。研究可提高对甘肃河西走廊寒潮演化过程的认知,为河西走廊气候变化的进一步研究奠定基础。  相似文献   
5.
创新型企业作为塑造创新地理格局的重要力量,其区位选择的外部特征及内在机理亟须予以系统化研究。基于对安徽省创新型企业的细分行业与空间建库,采用核密度估计和地理探测器等方法,对细分行业下的创新型企业空间集聚特征及影响因素进行研究。结果表明:(1)安徽省创新型企业类型以先进制造和自动化为主,并以生物与新医药、新材料、电子信息为辅;(2)创新型企业空间集聚的不均衡特征显著,呈现出“一核一带多节点”的集聚分布特征,且合肥、芜湖是两个重要集聚区;不同细分行业视角下创新型企业的空间分布形态各异,可归纳为点-轴式、极核式、双核式及多核分散式等4种空间组织形态。(3)创新型因子对于创新型企业的空间集聚最为重要,但传统型和政策型因子的重要性仍不容忽视。其中,产业基础、人力资本、创新投入是最核心的因素,但各行业创新型企业的影响因素作用力则表现出一定的异质性。  相似文献   
6.
及时掌握水稻的时空分布信息,对调整和优化农业生产结构至关重要。论文利用综合考虑植被物候和地表水变化的水稻自动制图方法,结合海拔、地表水体因素开展2001—2017年东北地区水稻分布的时空演变研究。通过889个地面调研点位对水稻分类结果验证,总体精度达90.66%,Kappa系数为0.8128。研究表明:① 21世纪初,东北地区水稻种植面积呈先略减后持续增加的趋势,2017年水稻种植面积达2001年的2.13倍。其中,水稻扩张面积的60%分布在三江平原,30%分布在松嫩平原,下辽河平原仅占不足5%。水稻扩张的海拔优势区间在200 m范围内,随着海拔的上升水稻扩张与地表水关系越来越密切。② 三江平原内,水稻扩张幅度在海拔30~70 m范围内逐渐增加,使优势区间从相对高度70 m缩减至40 m内,也使得分布优势逐渐趋向于距地表水体较远的区域。而松嫩平原和下辽河平原水稻种植分布的海拔优势区间始终分别保持在相对高度100 m、40 m内。③ 三江平原水稻的集中分布和急剧扩张,使水稻分布优势逐渐趋向于距地表水体远的区域,这将对地下水带来更大的压力;而松嫩平原水稻分布受地表水体影响较大,分布优势随着距地表水体距离的增加而减小。研究可为农业部门评估水资源承载力、保障农业可持续发展提供数据支撑及理论参考。  相似文献   
7.
对取自渤海湾的307个表层沉积物进行了元素测试和粒度分析。渤海湾表层沉积物的常微量元素呈现4种组合:富集于粗粒沉积区的SiO_2、Na_2O亲碎屑元素组合;富集于细粒沉积区的以Al_2O_3和重金属元素为代表的亲黏土元素组合;与缺氧环境有关的MnO、V、TOC元素组合和与河流输入有关的陆源CaO、TiO_2元素组合。粒度粗细主导了渤海湾元素含量分布的整体格局;海域河流物源供应不同较大影响了渤海湾南部(富Na_2O、CaO和SiO_2)和北部(富Ba和P_2O_5)在元素含量上的差异;高流速潮流对海底的冲刷再分配导致曹妃甸南侧Sr、Ca元素的条带状富集异常;有机质在细粒沉积区的富集导致缺氧环境的形成和K_2O、Mn、V、自生黄铁矿的海洋自生化学沉积;人类活动导致以Pb为代表的重金属污染在河流入海口、港口及沿岸海域的元素分布异常;曹妃甸沙坝内侧的泻湖(海洋钙质生物沉积)与沙坝外侧水下岸坡(陆源碎屑沉积)的截然不同的物源,导致了独特地貌沉积环境下元素分布的局部差异。  相似文献   
8.
章奇  居琪  李健欣  曹驰程  江和龙  张晖 《湖泊科学》2020,32(4):1041-1049
为探究富营养化湖泊中自生源可溶有机质(DOM)在泥水界面的吸附行为,以马来眼子菜(Potamogeton malaianus)和铜绿微囊藻(Microcystis aeruginosa)释放的DOM为代表,考察针铁矿对草、藻源DOM中不同组分的吸附特征.三维荧光平行因子分析表明类富里酸组分C1和类胡敏酸组分C4的含量很低,而类蛋白物质(类酪氨酸组分C2和类色氨酸组分C3)分别占草、藻源DOM荧光组成的70%和93%. 2种DOM均可被针铁矿吸附,吸附过程符合伪一级动力学.通过等温线拟合发现针铁矿吸附藻源DOM的非线性更强,饱和吸附量(23.77 mg/g)高于草源DOM(19.10 mg/g).特别地,类蛋白组分呈现非线性吸附,而类腐殖物质的吸附近似线性,且针铁矿对于DOM各荧光组分的吸附量顺序为:C3C2 C4 C1,此非均质吸附特征与DOM组分的初始含量、分子大小、芳香性及有效吸附位点有关.红外光谱证实氨基、羧基和羟基是吸附过程中的重要官能团.因此,草、藻源DOM显著改变了针铁矿表面的有机物质组成,影响湖泊沉积物的生物地球化学行为.  相似文献   
9.
采用Mann-Kendall、Theil指数、空间马尔科夫链等方法,对1994-2014年中国十大重点产业创新产出时空演化进行分析,并对创新发展空间分异成因进行了探讨。研究表明:① 研究期内,中国重点产业创新产出分为两个时段,成果呈指数型增长;② 创新产出差异先增后减,东、中、西、东北板块间差异小于板块内部,创新产出发展呈现出传染扩散与等级扩散的双重特征;③ 邻域环境影响创新发展,创新产出水平发生类型转移的单元集中在东、中部地区,且活跃度不断提升;④ 经济社会与政策条件、高等教育基础条件对重点产业创新发展有明显的正向驱动作用,而工业化程度影响微弱,未来加强对高等教育基础与智力资本的投入可进一步增强重点产业创新发展竞争力。  相似文献   
10.
Simulating land use/cover change (LUCC) and determining its transition rules have been a focus of research for several decades. Previous studies used ordinary logistic regression (OLR) to determine transition rules in cellular automata (CA) modeling of LUCC, which often neglected the spatially non-stationary relationships between driving factors and land use/cover categories. We use an integrated geographically weighted logistic regression (GWLR) CA-Markov method to simulate LUCC from 2001–2011 over 29 towns in the Connecticut River Basin. Results are compared with those obtained from the OLR-CA-Markov method, and the sensitivity of LUCC simulated by the GWLR-CA-Markov method to the spatial non-stationarity-based suitability map is investigated. Analysis of residuals indicates better goodness of fit in model calibration for geographically weighted regression (GWR) than OLR. Coefficients of driving factors indicate that GWLR outperforms OLR in depicting the local suitability of land use/cover categories. Kappa statistics of the simulated maps indicate high agreement with observed land use/cover for both OLR-CA-Markov and GWLR-CA-Markov methods. Similarity in simulation accuracy between the methods suggests that the sensitivity of simulated LUCC to suitability inputs is low with respect to spatial non-stationarity. Therefore, this study provides critical insight on the role of spatial non-stationarity throughout the process of LUCC simulation.  相似文献   
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