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### 分布式水文模型软件系统研究综述

1. 1. 中国科学院地理科学与资源研究所,北京 100101
2. 中国科学院大学,北京 100049
3. 美国威斯康星大学麦迪逊分校 地理系,麦迪逊 53706
4. 南京师范大学 地理科学学院,南京 210097
5. 中国科学院遥感与数字地球研究所,北京 100094
• 出版日期:2014-08-25 发布日期:2014-08-25
• 作者简介:

作者简介:江净超(1986-),男,河北邢台人,博士生,主要研究方向为Web GIS和地学智能建模,E-mail:jiangjc@lreis.ac.cn

• 基金资助:
国家水专项课题(2013ZX07103006-005);国家科技支撑计划项目(2013BAC08B03-4);中国科学院地理科学与资源研究所“秉维优秀青年人才计划”项目(2011RC203)

### Review on distributed hydrological modelling software systems

Jingchao JIANG1,2(), A-Xing ZHU1,3(), Chengzhi QIN1, Junzhi LIU4, Lajiao CHEN5, Hui WU1,2

1. 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
2. University of Chinese Academy of Sciences, Beijing 100049, China
4. College of Geographic Science, Nanjing Normal University, Nanjing 210097, China
5. Institute of Remote Sensing and Digital Earth, CAS, Beijing 100094, China
• Online:2014-08-25 Published:2014-08-25

Abstract:

Distributed hydrological modelling software systems are crucial because they provide technical support to the application of distributed hydrological models. Currently, applications of distributed hydrological models have exhibited new characteristics including multi-process synthesis simulation, a wide range of users, and intensive computation. Because of these new characteristics, the existing software systems are facing great challenges with respect to flexibility, usability, and efficiency. This paper reviews existing software systems for distributed hydrological models. Firstly, we analyzed the distributed hydrological modelling applications workflow including model structure determination, parameter extraction, model running, and calibration. The characteristics of existing software systems are discussed: (1) model structure flexibility of the existing software systems is divided into three types: no support of process and algorithm selection, only support of algorithm selection, and support of both process and algorithm selection; (2) parameter extraction methods of the existing software systems are divided into menu/command line and wizard method; (3) computing forms of the existing software systems are divided into parallel computing and serial computing; (4) computing modes of the existing software systems are divided into stand-alone and network mode. Secondly, we summarized the limitations of existing software systems with respect to their flexibility, usability, and efficiency. The limitations include the following: (1) contradiction between model structure flexibility and user knowledge dependence-the more flexible the model structure is, the more knowledge users need to have; (2) the existing methods of parameter extraction are too fussy for non-expert users; (3) the serial and stand-alone softwares usually encounter computing bottleneck as the appliaction scenario is data and/or computing intensive. In the last part of this paper, the emerging trends of distributed hydrological modelling software systems are discussed. These include (1) Modular modelling. The modular development ensures software reuse, but it is not enough when scale or semantic is unmatched, so the ontology knowledge needs to be considered; (2) Intelligent modelling. Using expert knowledge to realize model structure determination and parameter extraction and combining expert knowledge and optimization algorithm to parameter calibration is needed in future work; (3) On-line modelling. The development of cloud computing and network techniques makes on-line modelling practical. In addition, mobile terminals with powerful computing and storage capacity could be potential application platforms. This means that special user interface and data format are needed; (4) Parallel computing. Taking full advantage of new parallel programming standards (CUDA, OpenCL) and exploring the finer granularity parallelizability is an emerging trend. In addition, virtual simulation is another important trend.

• P333.9