基于海洋机器人的科学观测与实验系统研究现状与展望

海洋机器人具有观测范围大、作业灵活、机动性好、可控性强等突出优点,在海洋科学观测与海洋科学实验中发挥了重要作用,促进了物理海洋和海洋生物地球化学的发展。为阐明海洋机器人在海洋科学观测和实验中的应用情况,以水下滑翔机、自主水下机器人（Autonomous Underwater Vehicle,AUV）和无人帆船3种典型的观测型海洋机器人为例介绍了海洋机器人在海洋科学观测中的应用现状;以原位采样与固定、原位培养与分析海洋机器人为例介绍了海洋机器人在海洋科学实验中的应用现状;最后结合未来海洋科学研究需求,从需求牵引的角度对基于机器人的科学观测与实验系统的发展趋势进行了展望。     

卫星测高技术应用研究回顾与展望

简要介绍了笔者所在单位近十年来密切跟踪世界发展动态,灵活运用高新技术,致力于卫星测高技术应用研究所取得的一些有理论意义和实用价值的成果,这些成果主要包括四个方面：卫星测高径向轨道误差时域和空域特征分析、卫星测高反演海洋重力场、卫星测高反演海底地形以及利用测高重力异常扩展超高阶地球位模型研究成果。最后对这一研究领域未来的发展方向作了展望。     

KSS 31海洋重力仪配套接口子系统开发

介绍一种采用VC 语言开发成功的KSS 31型海洋重力仪导航系统适配的接口应用程序,对如何解决引进新型号设备与现有的系统(设备)集成(连接)问题有一定的借鉴作用。     

青藏高原边缘积雪辐射特征

利用中国陆地生态系统通量观测研究网络的玛曲站观测的一次降雪过程的资料,对青藏高原东部边缘冬季的降雪、积雪过程的辐射特征进行了分析.研究结果表明;积雪期晴天和降雪过程的向上短波辐射的峰值分别约为降雪前晴天的3和2倍.无积雪晴天地表反射率主要分布在0.175～0.36,新雪地表反射率主要分布在0.8～0.9.大气逆辐射变化较小,降雪过程的最大,积雪时的最小.地表长波辐射则为降雪前最大,降雪时最小.积雪覆盖的晴天比无积雪时的净辐射变化幅度减小,且早上由负转正的时间推迟.     

对海洋生态学和生物海洋学的浅析

海洋生态学和生物海洋学的研究内容大多交叉、重叠。为利于学科发展,文章在简述学科的产生与定义的基础上,强调学科之间要加强合作,适当分工。建议:海洋生态学侧重研究生物之间的相互关系和对环境的适应性、生存策略,并积极与经济、社会和文化相关学科交叉、融合;生物海洋学侧重于研究生物在海洋环境中的作用和功能,把推进对海洋的认识放在首位,加强与物理海洋学、化学海洋学的耦合,为海洋在地球四大圈层的相互关系中展现活力。据此,以渔业海洋学、海洋生态灾害和生物对地质的作用为例,阐述海洋生态学和生物海洋学的理解及其相互之间关系。     

Salinisation de l’aquifère libre de la Chaouia côtière (Azemmour-Tnine Chtouka), Maroc

L’aquifère libre de la Chaouia côtière constitue un exemple des aquifères les plus exploités au Maroc. Ce travail est consacré à l’étude des processus de la salinisation des eaux souterraines par l’analyse physico-chimique de 39 puits répartis dans la zone. Deux types de faciès ont été révélés, l’un est chloruré-sodique dans la frange côtière ; l’autre faciès est de type chloruré bicarbonaté-calcique caractérisant les eaux exploitées dans les calcaires marneux du Crétacé. L’influence marine (aérosols et intrusion marine), la dissolution/précipitation de la roche aquifère et l’infiltration des eaux d’irrigation, sont parmi les causes de l’augmentation de la salinité des eaux souterraines, en plus de l’exploitation excessive de l’eau souterraine.     

Coupling snow accumulation and melt rate modules of monthly water balance models with the Jazim monthly water balance model

Several models for simulation of water balance processes in semi-arid mountainous basins were developed by coupling different modules of existing water balance models (WBM). Snow accumulation and snowmelt rate relationships extracted from the McCabe-Markstrom, Guo, Rao-Al Wagdany and WASMOD-M WBMs, originally developed for basins with humid climate, were coupled with the Jazim WBM, primarily developed for arid basins. Karaj Basin, central Iran, with snowy autumn–winter and dry summer periods, was selected to assess model performance. The model parameters were optimized using a genetic algorithm (GA). All coupled models performed better than the non-modified (original) WBMs in the study basin. The coupled Jazim–McCabe-Markstrom model provided the best performance in simulating low and high monthly flows. It estimated the snowmelt runoff values more accurately than other proposed coupled models because the linear relationships used in the snow module of the McCabe-Markstrom model are more compatible with snow variations in the Karaj Basin.     

基于M-BEMT2.0研究串列海流发电机的水动力性能

海流发电机(MCT)是开发海洋可再生能源的重要装置。在预测海流发电机水动力性能方面,修正叶素动量理论(M-BEMT)方法被验证是一种简单有效的方法。为了进一步提高M-BEMT方法的适用性和准确性,基于M-BEMT方法开发M-BEMT2.0方法包括时均法(TA-BEMT2.0)和瞬态积分法(TI-BEMT2.0),新方法考虑了来流的轴向非均匀性和周向非均匀性。首先使用文献的试验结果验证均匀来流时新方法的适用性。然后使用计算流体力学(CFD)计算结果验证非均匀来流时新方法的适用性。最后结合新方法和CFD方法深入研究两个串列排布海流发电机(MCTA)的水动力性能。基于M-BEMT2.0研究发现,均匀来流时计算结果与试验结果基本吻合,非均匀来流时新方法的计算结果优于M-BEMT的计算结果。对于MCTA,当第一个MCT的叶尖速度比越大,第二个MCT功率比和推力比恢复到90%的距离越短。     

Evaluation of snow water equivalent datasets over the Saint‐Maurice river basin region of southern Québec

A 10‐km gridded snow water equivalent (SWE) dataset is developed over the Saint‐Maurice River basin region in southern Québec from kriging of observed snow survey data for evaluation of SWE products. The gridded SWE dataset covers 1980–2014 and is based on manual gravimetric snow surveys carried out on February 1, March 1, March 15, April 1, and April 15 of each snow season, which captures the annual maximum SWE (SWEM) with a mean interpolation error of ±19%. The dataset is used to evaluate SWEM from a range of sources including satellite retrievals, reanalyses, Canadian regional climate models, and the Canadian Meteorological Centre operational snow depth analysis. We also evaluate a number of solid precipitation datasets to determine their contribution to systematic errors in estimated SWEM. None of the evaluated datasets is able to provide estimates of SWEM that are within operational requirements of ±15% error, and insufficient solid precipitation is determined to be one of the main reasons. The Climate System Forecast Reanalysis is the only dataset where snowfall is sufficiently large to generate SWEM values comparable to observations. Inconsistencies in precipitation are also found to have a strong impact on year‐to‐year variability in SWEM dataset performance and spread. Version 3.6.1 of the Canadian Land Surface Scheme land surface scheme driven with ERA‐Interim output downscaled by Version 5.0.1 of the Canadian Regional Climate Model was the best physically based model at explaining the observed spatial and temporal variability in SWEM (root‐mean‐square error [RMSE] = 33%) and has potential for lower error with adjusted precipitation. Operational snow products relying on the real‐time snow depth observing network performed poorly due to a lack of real‐time data and the strong local scale variability of point snow depth observations. The results underscore the need for more effort to be invested in improving solid precipitation estimates for use in snow hydrology applications.     

A new method for establishing hydrologic fidelity of snow depth measurements based on snowmelt–runoff hydrographs

For snowmelt-driven flood studies, snow water equivalent (SWE) is frequently estimated using snow depth data. Accurate measurements of snow depth are important in providing data for continuous hydrologic simulations of such watersheds. A new hydrologic fidelity metric is proposed in this study to evaluate the potential contribution of particular snow depth datasets to flow characteristics using observed data and hydrologic modeling using the Variable Infiltration Capacity (VIC) model. Data-based hydrologic fidelity of snow depth measurements is defined as a categorical skill score between the snow depth in the watershed and the hydrograph peak or volume at the watershed outlet. Similarly, model-based hydrologic fidelity is defined as a categorical skill score between the model-simulated snow depth and the model-simulated hydrograph peak or volume. The proposed framework is illustrated using the Pecatonica River watershed in the USA, indicating which sites have a higher hydrologic fidelity, which is preferred in hydrologic studies.