水文实验研究进展

阐述了水文实验的概念与内涵，归纳了水文实验的研究方法及其特点，系统地回顾了国内外流域水文实验的发展历程，梳理了应用实验方法进行植被截留与阻滞作用、降水径流关系、非饱和带水分运移以及气候变化和人类活动影响下的水文过程研究的进展，分析了当前水文实验发展的不足，提出未来水文实验的发展方向:传统的实验流域着重于地表水研究，没有深入水文循环系统的内部，应将水文实验的研究范围从地表扩展为关键带部分，并加强跨流域的补给、径流与排泄关系研究；多学科交叉的综合观测实验与协同研究是水文实验的发展趋势；当前水文实验的系统性与规范性仍显不足，应重视水文实验站网建设，加强水文实验的规范性，以促进实验数据交换和研究成果对比。

Advances in hydrological experiment

Hydrological experiment plays an important role in hydrology research. In order to promote the development of hydrological experiment and its application in hydrology research, it is necessary to carry out a periodic comb on the relevant work and look forward the future holds. In this paper, the concept and connotation of hydrological experiment are expounded, and some common methods as well as the development of hydrological experiment both at home and abroad are reviewed systematically. Meanwhile, recent research progresses about hydrological effects of vegetation, rainfall-runoff relationship, water movement in unsaturated zone, and impacts of climate change and human activities on hydrologic cycle based on hydrological experiment are summarized. Based on all above, the existing insufficiencies in current hydrological experiment are analyzed and possible future directions of development are pointed out. Firstly, the traditional experiments mainly focused on the surface hydrology rather than explore the interior of the hydrological cycle. It is suggested that the researchers should not only focus on the surface hydrology, but also extend the experimental basin to the critical zone, and pay more attentions on the study of inter-basin supply, runoff and drainage. Secondly, interdisciplinary observations and experiments will become a foreseeable trend of the future hydrological experiments. Thirdly, the operational specifications and standards of current hydrological experiment are not sufficient, and more attentions should be paid to the construction of hydrological experiment station network and the specifications of hydrological experiments, which will make it possible for data sharing and comparison analysis.