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.     

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。     

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。     

复杂城市环境下边坡预裂爆破应用与效果检验

城市名胜风景区内某建筑工程基坑开挖遇山体石方,需进行岩石边坡爆破施工。为了降低爆破振动危害和保护边坡开挖轮廓面的预期效果,采用了预裂爆破技术。经过合理设计,提出了预裂爆破方案,并按照方案精心施工,同时对周边重点建（构）筑物的爆破振速进行监测。结果表明：各监测点振动速度远小于安全允许范围,宏观爆破效果良好,为后期开挖爆破提供了良好的开挖条件,该预裂爆破技术对类似工程具有一定指导意义和参照价值。     

工程岩体物理场

摘 要　 从岩体的空隙度、强度、变形和渗透性等几个方面说明了岩体的性质受应力状态的 影响情况。这种影响是空间位置的函数‚具有随机场的特点。据此‚提出了工程岩体物理场 的概念。针对岩体性质所具有的这种 “场” 的特点‚认为目前岩体工程中的一些工作方法‚ 如原位试验点的布置、试验数据的统计等‚应相应地作某些改进。 关键词     

冲击回转在复杂条件下钻进若干问题分析及处理措施

气动冲击回转钻进主要应用于难用或忌用液体作为循环介质的地区。而“引松入长”工程中的爆破孔施工是在水量极丰富、气温极低、地层极复杂条件下进行,本文对其出现的问题进行了分析,并提出了合理的解决措施     

裂隙,岩溶含水层疏排水钻孔的爆炸洗孔试验研究

在裂隙,岩溶裂隙含水层水文地质条件研究基础上,根据炸药在水中原理,介绍了控制炸药爆炸能量和孔内爆炸方法,达到对岩体的爆炸致裂以及对原储导水裂隙的冲刷作用,提高了地下工程中钻孔或水源井的疏排效率,同时又保护站孔孔壁不被破坏。