地理科学进展 ›› 2020, Vol. 39 ›› Issue (10): 1747-1757.doi: 10.18306/dlkxjz.2020.10.013

• 研究综述 • 上一篇    下一篇

土壤侵蚀研究中降雨过程随机模拟综述

殷水清(), 王文婷   

  1. 地表过程与资源生态国家重点实验室,北京师范大学地理科学学部,北京 100875
  • 收稿日期:2019-09-22 修回日期:2020-05-02 出版日期:2020-10-28 发布日期:2020-10-27
  • 作者简介:殷水清(1980— ),女,湖南省宁乡市人,副教授,博士,主要从事降水随机模拟、气候及其变化对土壤侵蚀的影响评价研究。E-mail: yinshuiqing@bnu.edu.cn
  • 基金资助:
    国家自然科学基金项目(41301281)

A review on the stochastic simulation of rainfall process data for soil erosion assessment

YIN Shuiqing(), WANG Wenting   

  1. State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
  • Received:2019-09-22 Revised:2020-05-02 Online:2020-10-28 Published:2020-10-27
  • Supported by:
    National Natural Science Foundation of China(41301281)

摘要:

土壤侵蚀是中国严峻的环境问题之一。土壤侵蚀模型是诊断和防治土壤侵蚀问题的有力工具。降雨随机模拟模型可以弥补观测资料在时空尺度上的不足,满足土壤侵蚀模型对降雨过程数据的需求。论文总结了降雨过程基本特征、随机模拟的研究进展以及未来的发展方向。主要结论有:① 最小降雨间歇(Minimum Inter-event Time, MIT)为分割次降雨的最小时间间隔,当干期小于该临界值,则合并为1次降雨;否则分割为2次独立的次降雨事件。采用指数方法计算得到中国中东部最小降雨间歇变化于7.6~16.6 h 之间,平均值为10.7 h;当MIT值较小时,次降雨过程参数如次雨量、历时、平均雨强与峰值雨强等对MIT的变化敏感。② 降雨的时程分配特征反映次降雨量在降雨过程中的分配,是降雨过程随机模拟的重要方面。采用Huff雨型分析方法得到中国降雨以峰值出现在前期的降雨为主,峰值出现在前1/2时段的降雨占65.1%;峰值出现在前期的降雨事件,与峰值出现在后期的降雨事件相比,历时较短、雨强较大。③ 美国农业部水蚀预报项目WEPP中自带的天气随机模型CLIGEN能较好地模拟日雨量,整体上低估次降雨历时,高估峰值雨强;且对于不同大小的日雨量等级,次降雨历时和峰值雨强的偏差方向和程度不一致。④ CLIGEN的参数输入需要降雨过程观测资料,难以获取,小时降雨观测资料相对更易获取,基于此,发展了使用小时降雨数据计算CLIGEN中2个与降雨过程相关的参数TimePk和MX.5P的方法。未来需加强随机模型对极值的模拟能力,以及建立多站点、多气象要素相关的天气条件约束型随机模型。

关键词: 降雨, 随机模拟, 天气发生器, 土壤侵蚀, CLIGEN

Abstract:

Soil erosion is one of the most serious environmental problems in China. Soil erosion model is an efficient tool for diagnosing and preventing soil erosion. Stochastic simulation of precipitation can generate synthetic input data for soil erosion models when observation data are absent. This study summarized the main progress of rainfall process stochastic simulation in existing studies. One-minute resolution rainfall data were collected from 18 weather stations distributed in the main water erosion areas to analyze the characteristics of the storm process and calibrate, evaluate, and develop CLImate GENerator (CLIGEN) stochastic models for China. The main results are as follows: 1) Minimum inter-event time (MIT) for separating precipitation events from continuous precipitation recording ranged from 7.6 h to 16.6 h, with an average of 10.7 h. The MIT values calculated from 1-minute data and hourly data were not significantly different. Storm process characteristics such as the amount, duration, average intensity, and peak intensity of precipitation were sensitive to the variation of MIT values when the MIT values were smaller than 6 h, which suggests that the comparison of storm process characteristics for different storms and areas should use the same MIT value. 2) Events with peak intensity occurring in the first half of the duration of an event were dominant, which accounted for more than 65% of the total events and they were characterized by relatively short duration and greater intensity, comparing with events whose peak intensity fell in the second half of the duration of the events. 3) Weather generator CLIGEN in the Water Erosion Prediction Project (WEPP) soil erosion model can satisfactorily simulate the daily precipitation amounts (P), but it underestimated the storm duration (D) and overestimated the maximum 30-minute intensity (I30). The direction and degree of the bias for D and I30 were not consistent for different groups classified by different precipitation amounts. 4) A method was developed to use hourly precipitation data to prepare the TimePk and MX.5P parameters for CLIGEN input files for the generation of storm process data in the absence of high resolution hyetography precipitation data. More efforts are needed to improve the simulation of precipitation extremes and develop multi-site and multi-variable stochastic models conditioned on weather types in the future.

Key words: precipitation, stochastic simulation, weather generator, soil erosion, CLImate GENerator (CLIGEN)