湿地植物固体碳源养分释放动态及其对人工湿地水体脱氮效率的影响

污水低碳氮比(C/N)是影响人工湿地氮去除效果限制因素,传统的碳源添加及利用存在成本较高、补充困难的局限性.本研究契合“就地取材,原位处理”的废物利用原则,选择人工湿地常见的水生植物和农业废弃物(玉米芯、稻草)作为对照,对比了挺水植物(香蒲、美人蕉)、浮叶植物(莲)、沉水植物(菹草)、湿生植物(南荻、短尖苔草)的释碳能力,初步确定了以香蒲、美人蕉、南荻为代表的植物具有较好的释放碳能力,在中国湿地中分布广泛,且均对水体二次污染较小.以南荻、美人蕉、玉米芯作为碳源添加的模拟人工湿地实验验证表明,在低碳氮比的模拟表流人工湿地投入植物碳源,能有效提高系统的脱氮效率,对照组、南荻组、美人蕉组和玉米芯组的出水总氮浓度分别为(5.24±0.07)、(4.50±0.10)、(3.75±0.17)和(2.97±0.18) mg/L,对应的去除率分别为58%、64%、70%和76%,确定南荻和美人蕉植物残体以及改性材料均残体和改性材料适合作为人工湿地中原位利用的外加碳源.本研究探索了通过湿地植物配置解决人工湿地水体低C/N比的问题,为提高湿地脱氮效果提供了有意义的新途径.     

地质约束条件下的地质体智能综合方法研究

地质体综合是地质图编制工作的重中之重,因其处理涉及内容多、 业务逻辑复杂、 重复工作量大,是影响编图工作推进的主要因素.为了能够实现地质体的高效综合,文章提出了一种以地质约束条件(专家知识)为核心、 以制图综合为空间图形合并手段的新型地质体智能综合方法,设计并实现了围绕地质专家知识(如地质年代、 地层名称等)规则映射开...     

智能位置服务工作机理及发展趋势研究

人工智能、大数据挖掘、云计算等技术拓展了位置服务的服务方式和应用领域,并将服务的层次升华至智能化水平。首先,本文阐述了智能位置服务的研究现状,对比一般位置服务,梳理了智能位置服务的内涵与特点;其次,研究了智能位置服务的工作机理,建立基于定位技术、地理信息系统、位置模型构建与管理、活动任务建模、物联网技术、大数据挖掘、机器学习和增强现实8种关键技术的体系结构、运行模式和服务方式;最后,探讨了智能位置服务的发展瓶颈与未来趋势,为进一步智能位置服务的关键技术攻关提供参考和借鉴。     

Hyperparameter optimization of neural network-driven spatial models accelerated using cyber-enabled high-performance computing

Artificial neural networks (ANNs) have been extensively used for the spatially explicit modeling of complex geographic phenomena. However, because of the complexity of the computational process, there has been an inadequate investigation on the parameter configuration of neural networks. Most studies in the literature from GIScience rely on a trial-and-error approach to select the parameter setting for ANN-driven spatial models. Hyperparameter optimization provides support for selecting the optimal architectures of ANNs. Thus, in this study, we develop an automated hyperparameter selection approach to identify optimal neural networks for spatial modeling. Further, the use of hyperparameter optimization is challenging because hyperparameter space is often large and the associated computational demand is heavy. Therefore, we utilize high-performance computing to accelerate the model selection process. Furthermore, we involve spatial statistics approaches to improve the efficiency of hyperparameter optimization. The spatial model used in our case study is a land price evaluation model in Mecklenburg County, North Carolina, USA. Our results demonstrate that the automated selection approach improves the model-level performance compared with linear regression, and the high-performance computing and spatial statistics approaches are of great help for accelerating and enhancing the selection of optimal neural networks for spatial modeling.     

Layered berthing method and experiment of unmanned surface vehicle based on multiple constraints analysis

Considering the dynamic changes of unmanned surface vehicle (USV) in berthing tasks, the planning and control modes are divided into two phases: the remote phase and the terminal phase. According to the main influencing factors of the two phases, an improved artificial potential field method is proposed to complete autonomous berthing trajectory planning based on the analysis of environment constraint, berth point constraint and USV’s dynamics constraint. Combining with the dynamic characteristics and control objectives at different phases of berthing and analyzing the fuzzy rule regulation strategy of USV’s heading and speed control, an improved adaptive fuzzy PID control method is proposed to solve the control problem of USV, which is influenced by weak maneuver, large disturbance, limited water area and strong shore effect. Finally, the comparative test of berthing simulation verifies the superiority of the proposed control method. The autonomous berthing field experiment is completed based on the "Dolphin-I" small USV. It verifies the validity and feasibility of the proposed autonomous berthing method.     

基于CMIP6多模式集合的未来中国风功率预估

实现我国2060年“碳中和”目标,需要大力发展包括风能在内的清洁能源,然而气候变化给未来风资源利用带来较大的不确定性。本文利用人工神经网络(Artificial Neural Network,ANN)算法对16个CMIP6气候模式风速数据进行逐一订正,在此基础上预估21世纪30、60年代以及21世纪末这3个不同年代在低(SSP1-2.6)和高(SSP5-8.5)排放情景下中国风功率较当代的变化。结果表明,ANN算法使CMIP6气候模式均方根误差平均降低(39.93％±9.57％),并使多模式集合平均与观测的相关系数从0.56增加到0.83,更好地再现了中国当代风速的空间分布和季节变化。在此基础上,预估的21世纪60年代(2050—2064年)风功率密度在两种情景下分别减少了(1.01±0.94) W·m^-2(2.62％±2.27％)和(1.11±1.45) W·m^-2(1.90％±2.51％)。时间上,春季作为风能密度最大的季节,两种排放情景下风功率分别减少了(1.16±1.14) W·m^-2和(1.43±1.58) W·m^-2。空间上,中国东南部风功率密度在SSP1-2.6情景下降(0.56±0.53) W·m^-2,而SSP5-8.5情景下上升(0.40±0.29) W·m^-2。近期(2025—2039年)全国平均风功率密度在两种情景下分别减少了(0.52±0.83) W·m^-2和(0.54±1.02) W·m^-2,而长期(2085—2099年)风功率密度分别减小了(0.98±1.17) W·m^-2和(1.83±1.17) W·m^-2。利用极度梯度提升(XGB)算法订正CMIP6数据的预估变化量级偏小但趋势一致,表明随着全球变暖幅度的增加,我国风功率降低的趋势将更加显著。     

湖泊碳循环研究中遥感技术的机遇与挑战

湖泊碳循环是全球碳循环过程中的重要环节,随着全球碳循环研究的不断深入,湖泊碳循环对全球碳循环的影响,以及其对全球气候变化的调节作用越来越受到关注.然而,由于湖泊分布的破碎性(大于0.002 km2的湖泊约有1.17×108个,并零星地分布在全球)和多样性(流域生态多样性,湖泊类型多样性,分布的气候带多样性等),使得全面...     

A practical device for evaluating periphyton colonization dynamics in tropical shallow wetlands

Here, we have presented a field device for sampling periphyton in lentic systems, with a tropical lowland wetland in Colombia as the model system. The periphyton sampler (PS) is composed of a central soft iron pole to which rectangular woody boxes and glass slides are attached to lateral iron axes, which can be distributed at different depths. Our PS can be used to evaluate changes in the richness and density of algal communities at different scales as well as in water quality studies.     

自动观测与人工观测数据差异的初步分析

利用2004—2007年内蒙古地区50个地面自动气象站与人工平行观测期间的数据,对自动与人工观测的气温、相对湿度、地表温度进行了差异分析,统计了两种观测之间的对比差值。对各要素观测差异在全区的分布特点进行了分析。结果表明:自动观测与人工观测各气象要素均存在一定的差异,但大部分地区各要素的差异都在自动站误差允许范围之内;造成差异的原因是多方面的,包括仪器本身存在缺陷及观测方法不一致等。     

松嫩沙地天然草地与人工草地土壤动物的对比研究

松嫩沙地天然草地和人工草地土壤动物的对比研究表明,天然草地大型土壤动物的优势类群与人工草地优势类群数相同,但类群有差别。而中小型土壤动物的优势类群是人工草地多。天然草地大型土壤动物和中小型土壤动物的常见类群都多于人工草地,而稀有类群则相反。两种草地类型的土壤动物在土层中的垂直分布存在差异性,但基本上是随着土层加深而递减,天然草地表层的土壤动物类群数均多于人工草地,主要是受土壤营养状况和理化性质的制约。