广西降水非均匀性多尺度特征与综合评价

doi:10.11867/j.issn.1001-8166.2019.11.1152

地球科学进展 ›› 2019, Vol. 34 ›› Issue (11): 1152 -1164. doi: 10.11867/j.issn.1001-8166.2019.11.1152

广西降水非均匀性多尺度特征与综合评价

谢鑫昌 ¹(

),杨云川 ^1, ^2, ³(

),田忆 ¹,廖丽萍 ^1, ^2, ³,韦钧培 ¹,周津羽 ¹,陈立华 ^1, ^2, ³

1. 广西大学土木建筑工程学院，广西南宁 530004
2. 广西大学工程防灾与结构安全教育部重点实验室，广西南宁 530004
3. 广西防灾减灾与工程安全重点实验室，广西南宁 530004

收稿日期:2019-09-05 修回日期:2019-10-25 出版日期:2019-11-10
通讯作者: 杨云川 E-mail:xiexinchanggxdx@163.com;yyc_sciences@163.com
基金资助:
国家自然科学基金项目“基于AquaCrop模型的甘蔗干旱机制模拟及旱灾风险评估方法研究”(51609041);广西自然科学基金项目“广西甘蔗的骤发性干旱响应机理与三维度量及前兆信号诊断研究”(2019GXNSFAA185015)

Multi-scale Characteristics and Comprehensive Evaluation of Precipitation Heterogeneity in Guangxi

Xinchang Xie ¹( ),Yunchuan Yang ^1, ^2, ³( ),Yi Tian ¹,Liping Liao ^1, ^2, ³,Junpei Wei ¹,Jinyu Zhou ¹,Lihua Chen ^1, ^2, ³

1. College of Civil Engineering and Architecture, Guangxi University, Nanning 530004, China
2. Key Laboratory of Disaster Prevention and Structural Safety of Ministry of Education, Guangxi University, Nanning 530004, China
3. Key Laboratory of Disaster Prevention and Engineering Safety, Guangxi, Nanning 530004, China

Received:2019-09-05 Revised:2019-10-25 Online:2019-11-10 Published:2019-12-31
Contact: Yunchuan Yang E-mail:xiexinchanggxdx@163.com;yyc_sciences@163.com
About author:Xie Xinchang (1995-), male, Lingshan County, Guangxi Province, Master student. Research areas include agricultural water resources. E-mail: xiexinchanggxdx@163.com
Supported by:
the National Natural Science Foundation of China ”Study on simulation of sugarcane drought mechanism based on AquaCrop model and drought risk assessment method”(51609041);The Natural Science Foundation of Guangxi Province ”Study on response mechanism, three-dimensional measurement and precursory signal diagnosis of sugarcane in Guangxi”(2019GXNSFAA185015)

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针对广西降水时空分配不均、旱涝灾害频发的现象，开展降水非均匀性多尺度特征和综合评价，可为区域应对旱涝灾害及水资源智慧管理提供科学支撑。基于1961—2017年广西87个格点的逐日降水资料，采用降水集中度（PCD）、降水集中期（PCP）指数构建日、候、旬、月、季多时间尺度的降水非均匀性等级评价体系，借助R/S分析和地理空间分析方法讨论了广西时空演变和气候分区特征。研究表明：日、候、旬尺度的PCD和PCP时空变化特征相对一致，较月、季尺度更能表达广西降水的非均匀性特征；广西降水的PCD历时变化在东北地区主要呈现递增趋势，而在西南地区主要呈递减趋势，其未来一段时期的变化趋势与历时演变相同；广西降水的PCD空间分布存在显著的空间自相关性和分层异质性，主要表现在PCD的均值、变异系数和发生频率上；广西降水的综合非均匀性总体呈现东北部地区高度分散、南部地区高度集中、西北和中部地区则为轻度集中或分散的分布格局。月以内的时间尺度是表达广西降水非均匀性的最佳尺度，若要考虑侯、旬尺度更加稳定和日尺度更加精细的优势，则采用候尺度进行逐日滑动计算分析将是最佳方式。

关键词: 降水集中度, 降水集中期, 降水非均匀性, 多尺度特征, 等级评价体系

Aiming at the uneven spatial and temporal distribution of precipitation and frequent occurrence of drought and waterlogging disasters in Guangxi, the multi-scale characteristics and comprehensive evaluation of precipitation heterogeneity can provide scientific support for regional response to drought and waterlogging disasters and intelligent management of water resources. Based on the daily precipitation data of 87 grid points from 1961 to 2017 in Guangxi, the Precipitation Concentration Degree (PCD) and Precipitation Concentration Period (PCP) index were used to build day, pentad, ten days, month, season precipitation heterogeneity of multiple time scale level evaluation system. By using R/S analysis and geographical spatial analysis methods, the space-time evolution characteristics and climate division in Guangxi were discussed. The study showed that the spatial and temporal variation characteristics of PCD and PCP at the diurnal, synoptic and monthly scales were relatively consistent, and the heterogeneity of precipitation in Guangxi could be better expressed than that at the monthly and seasonal scales. The diachronic change of PCD in precipitation in Guangxi shows an increasing trend in northeast China and a decreasing trend in southwest China, and the trend of its future period is the same as the diachronic evolution. The spatial distribution of PCD in Guangxi has significant spatial autocorrelation and stratification heterogeneity, which are mainly reflected in the mean value, coefficient of variation and frequency of PCD. The comprehensive heterogeneity of precipitation in Guangxi is highly dispersed in the northeast, highly concentrated in the south, and slightly concentrated or dispersed in the northwest and central regions. The time-scale within a month is the best scale to express the non-uniformity of precipitation in Guangxi. If the advantages of more stable climatic and ten-day scales and more fine daily scales are taken into account, the use of climatic scale for daily sliding calculation and analysis will be the best way.

Key words: Precipitation concentration degree, Precipitation concentration period, Precipitation heterogeneity, Multi-scale characteristics, Level evaluation system.

中图分类号:

P426.6

图1 广西降雨格点空间分布示意图

Fig. 1 Spatial distribution of rainfall grid points in Guangxi

表1 各时间尺度非均匀性评价等级表

Table 1 Precipitation heterogeneity evaluation grades of each time scale

等级	类型	实际频率/%	PCD（日）	PCD（候）	PCD（旬）	PCD（月）	PCD（季）
1	高度集中	5	PCD $>$ 0.623	PCD $>$ 0.617	PCD $>$ 0.612	PCD $>$ 0.573	PCD $>$ 0.490
2	中度集中	10	0.575 $<$ PCD≤0.623	0.568 $<$ PCD≤0.617	0.561 $<$ PCD≤0.612	0.524 $<$ PCD≤0.573	0.438 $<$ PCD≤0.490
3	轻度集中	15	0.526 $<$ PCD≤0.575	0.519 $<$ PCD≤0.568	0.511 $<$ PCD≤0.561	0.472 $<$ PCD≤0.524	0.390 $<$ PCD≤0.438
4	正常	40	0.407≤PCD≤0.526	0.399≤PCD≤0.519	0.390≤PCD≤0.511	0.346≤PCD≤0.472	0.280≤PCD≤0.390
5	轻度分散	15	0.342≤PCD $<$ 0.407	0.334≤PCD $<$ 0.399	0.325≤PCD $<$ 0.390	0.279≤PCD $<$ 0.346	0.223≤PCD $<$ 0.280
6	中度分散	10	0.274≤PCD $<$ 0.342	0.265≤PCD $<$ 0.334	0.254≤PCD $<$ 0.325	0.209≤PCD $<$ 0.279	0.153≤PCD $<$ 0.223
7	高度分散	5	PCD $<$ 0.274	PCD $<$ 0.265	PCD $<$ 0.254	PCD $<$ 0.209	PCD $<$ 0.153

表1 各时间尺度非均匀性评价等级表

Table 1 Precipitation heterogeneity evaluation grades of each time scale

等级	类型	实际频率/%	PCD（日）	PCD（候）	PCD（旬）	PCD（月）	PCD（季）
1	高度集中	5	PCD $>$ 0.623	PCD $>$ 0.617	PCD $>$ 0.612	PCD $>$ 0.573	PCD $>$ 0.490
2	中度集中	10	0.575 $<$ PCD≤0.623	0.568 $<$ PCD≤0.617	0.561 $<$ PCD≤0.612	0.524 $<$ PCD≤0.573	0.438 $<$ PCD≤0.490
3	轻度集中	15	0.526 $<$ PCD≤0.575	0.519 $<$ PCD≤0.568	0.511 $<$ PCD≤0.561	0.472 $<$ PCD≤0.524	0.390 $<$ PCD≤0.438
4	正常	40	0.407≤PCD≤0.526	0.399≤PCD≤0.519	0.390≤PCD≤0.511	0.346≤PCD≤0.472	0.280≤PCD≤0.390
5	轻度分散	15	0.342≤PCD $<$ 0.407	0.334≤PCD $<$ 0.399	0.325≤PCD $<$ 0.390	0.279≤PCD $<$ 0.346	0.223≤PCD $<$ 0.280
6	中度分散	10	0.274≤PCD $<$ 0.342	0.265≤PCD $<$ 0.334	0.254≤PCD $<$ 0.325	0.209≤PCD $<$ 0.279	0.153≤PCD $<$ 0.223
7	高度分散	5	PCD $<$ 0.274	PCD $<$ 0.265	PCD $<$ 0.254	PCD $<$ 0.209	PCD $<$ 0.153

表2 各时间尺度 PCD均值、 STD、 CV统计表

Table 2 statistical tables of PCD mean value, STD and CV of each time scale

时间尺度		最大值	最小值	均值	极差值
日	STD	0.1192	0.0721	0.0965	0.0471
	年均PCD	0.5557	0.3288	0.4589	0.2269
	CV	0.2871	0.1302	0.2145	0.1569
候	STD	0.1199	0.0730	0.0973	0.0469
	年均PCD	0.5488	0.3221	0.4519	0.2267
	CV	0.2918	0.1338	0.2200	0.1580
旬	STD	0.1200	0.0732	0.0978	0.0468
	年均PCD	0.5434	0.3130	0.4442	0.2304
	CV	0.2978	0.1350	0.2253	0.1628
月	STD	0.1215	0.0805	0.1013	0.0410
	年均PCD	0.5000	0.2781	0.4024	0.2219
	CV	0.3329	0.1611	0.2576	0.1718
季	STD	0.1389	0.0845	0.1047	0.0544
	年均PCD	0.3849	0.2923	0.3267	0.0926
	CV	0.3810	0.2435	0.3209	0.1375

表2 各时间尺度 PCD均值、 STD、 CV统计表

Table 2 statistical tables of PCD mean value, STD and CV of each time scale

时间尺度		最大值	最小值	均值	极差值
日	STD	0.1192	0.0721	0.0965	0.0471
	年均PCD	0.5557	0.3288	0.4589	0.2269
	CV	0.2871	0.1302	0.2145	0.1569
候	STD	0.1199	0.0730	0.0973	0.0469
	年均PCD	0.5488	0.3221	0.4519	0.2267
	CV	0.2918	0.1338	0.2200	0.1580
旬	STD	0.1200	0.0732	0.0978	0.0468
	年均PCD	0.5434	0.3130	0.4442	0.2304
	CV	0.2978	0.1350	0.2253	0.1628
月	STD	0.1215	0.0805	0.1013	0.0410
	年均PCD	0.5000	0.2781	0.4024	0.2219
	CV	0.3329	0.1611	0.2576	0.1718
季	STD	0.1389	0.0845	0.1047	0.0544
	年均PCD	0.3849	0.2923	0.3267	0.0926
	CV	0.3810	0.2435	0.3209	0.1375

图2 不同PCP时间尺度效应变化图

Fig.2 Time scale effect changes of different PCP

图3 日、月、候尺度PCD时间趋势空间分布图

Fig. 3 Temporal and spatial distribution of daily, monthly and pentad scale PCD

图4 日、候、月尺度PCD平均等级空间分异图
（a）日尺度PCD平均等级空间分异图；（b）候尺度PCD平均等级空间分异图；（c）月尺度PCD平均等级空间分异图

Fig. 4 Spatial differentiation of average grades of daily, pentad and monthly PCD
(a) Spatial differentiation map of average grade of daily scale PCD;(b) Spatial differentiation map of average grade of pentad scale PCD;(c) Spatial differentiation map of average grade of monthly scale PCD

表3 日、候、月尺度 q统计量数值表

Table 3 q statistical values of daily, pentad and monthly scales

时间尺度	q统计量	显著性
日	0.703150	显著
候	0.709575	显著
月	0.680029	显著

表3 日、候、月尺度 q统计量数值表

Table 3 q statistical values of daily, pentad and monthly scales

时间尺度	q统计量	显著性
日	0.703150	显著
候	0.709575	显著
月	0.680029	显著

表4 日、候、月尺度 Moran’s I数值表

Table 4 Moran's I values of daily, pentad and monthly scales

时间尺度	Moran's I	z得分	显著性
日	0.715481	8.349583	显著
候	0.761723	8.881113	显著
月	0.757252	8.823312	显著

表4 日、候、月尺度 Moran’s I数值表

Table 4 Moran's I values of daily, pentad and monthly scales

时间尺度	Moran's I	z得分	显著性
日	0.715481	8.349583	显著
候	0.761723	8.881113	显著
月	0.757252	8.823312	显著

图5 日、候、月尺度PCD局部Lisa聚类图
（a）日尺度；（b）候尺度；（c）月尺度

Fig.5 Partial Lisa clustering diagram of daily, pentad and monthly PCD scales
(a) Daily scale;(b) Pentad scale;(c) Monthly scale

图6 PCD空间非均匀性变化（日尺度）

Fig.6 Spatial heterogeneity variation of PCD (daily scale)

图7 1961—2017年广西区域综合评价图
（a）日尺度；（b）候尺度；（c）月尺度

Fig 7 Guangxi regional comprehensive evaluation map 1961-2017
(a) Daily scale;(b) Pentad scale;(c) Monthly scale

图8 1961—2017年不同时间尺度区域等级变化图
（a）日尺度；（b）候尺度；（c）月尺度

Fig. 8 Grading changes of different time scales from 1961 to 2017
(a) Daily scale；(b) Pentad scale;(c) Monthly scale

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