农业水权交易大数据技术应用研究

李 楠; 张 雨; 张振华; 边晓南; 高 清

引用本文:	李楠,张雨,张振华,等.农业水权交易大数据技术应用研究[J].灌溉排水学报,2022,41(S2):99-104.
	LI Nan,ZHANG Yu,ZHANG Zhenhua,et al.农业水权交易大数据技术应用研究[J].灌溉排水学报,2022,41(S2):99-104.

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农业水权交易大数据技术应用研究
李楠，张雨，张振华，边晓南，高清
德州市水利局，山东德州 253014

摘要:

实行农业水权交易是促进农业水资源优化配置的有效方法之一，然而农业用水的资源数据具有多源性、时效性、不确定性的特点，为了实现水权交易的智能高效管理，需要利用大数据技术对相关数据进行高度融合和利用。本研究通过数据采集、数据存储、数据分析、数据应用等4方面技术，建立农业水权交易大数据技术框架。以德州市农业水权交易为例，基于大数据技术设计了农业水权交易平台，其功能和技术实现了对数据利用的全面性、时效性和准确性，以大数据技术提出了农业水权交易管理新模式。本研究深度挖掘了水权交易的交易信息和交易潜力，为农业水权交易的发展提供可视化技术支持和决策信息，深化了农业水权交易的应用，提升了农业水资源优化配置技术。

关键词: 水权交易；大数据技术；农业水权；交易平台

DOI：10.13522/j.cnki.ggps.2022583

分类号:

基金项目:

Research on the Application of Big Data Technology in Agricultural Water Rights Trading

LI Nan, ZHANG Yu, ZHANG Zhenhua, BIAN Xiaonan, GAO Qing

Dezhou Water Conservancy Bureau of Shandong, Dezhou 253014, China

Abstract:

【Objective】The implementation of agricultural water rights trading is one of the effective methods to promote the optimal allocation of agricultural water resources. However, the data of agricultural water resources has multi-source, timeliness and uncertainty. To realize the intelligent and efficient management of water rights trading, it is necessary to highly integrate and utilize relevant data with big data technology. 【Method】 This paper establishes the big data technology framework of agricultural water rights trading through the big data technology of data collection, data storage, data analysis and data application. 【Result】Taking Dezhou agricultural water rights trading as an example, a platform of agricultural water rights trading is designed based on big data technology. Its functions and technologies realize the comprehensiveness, timeliness and accuracy of data utilization. A new management mode for agricultural water rights trading is proposed based on big data technology. 【Conclusion】The research deeply explored the trading information and trading potential of water rights trading, that provided visual technical support and decision-making information for the development of agricultural water rights trading. It deepened the application of agricultural water rights trading, and improved the optimal allocation of agricultural water resources.

Key words: water rights trading; big data technology; agricultural water rights; trading platform