淮北平原降水量和参考作物蒸散量时空演变规律研究
|
摘要
【目的】研究淮北平原降水量和参考作物蒸散量的时空演变规律。【方法】基于5个气象站1955—2015年的气象数据,采用M-K检验法、Kendall秩次相关检验法、R/S分析法、M-K突变检验法、Yamamoto法、滑动t检验法,并结合Arc GIS,分析了降水量和参考作物蒸散量的时空演变规律。【结果】淮北平原年降水量整体呈不显著的上升趋势,未来仍将保持这种微弱的上升趋势;参考作物蒸散量整体呈显著的下降趋势,未来仍将维持这种明显的下降趋势。降水量变化较大的年份为1966、1998、1999、2000、2007、2013年,参考作物蒸散量变化较大的年份为1998年和2004年。经检验,这些年份均没有达到气候突变的要求。1955—2015年,降水量高值中心出现在蚌埠和阜阳的概率各占50%,低值中心出现在砀山的概率为83%;参考作物蒸散量高值中心出现在亳州的概率为33%,低值中心出现在蚌埠的概率为67%。因此,淮北平原各地的灌溉任务可据此作一定的调整,亳州和砀山地区的灌溉应加强,蚌埠和阜阳的灌溉可适当减少。【结论】1955—2015年,降水量和参考作物蒸散量都没有发生突变,但相对而言,参考作物蒸散量的波动较大。未来一段时间内降水量将增加,参考作物蒸散量将减少,淮北平原未来出现涝渍的概率加大,因此,未来的排涝任务可能会加重。
【Objective】This paper is to calculate the spatiotemporal variation of precipitation and evapotranspiration in Huaibei Plain over the past six decades.【Method】The spatiotemporal change in the reference crop evapotranspiration was calculated based on the meteorological data measured from five weather stations in the region from 1955 to 2015, using ArcGIS, the M-K test and the R/S analysis method, the Kendall rank correlation and the M-K mutation test method, as well as the Yamamoto method and the sliding t-test method.【Result】From 1955 to2015, the precipitation in this region increased steadily, accompanied by a declined reference evapotranspiration.The wettest years were 1966, 1998, 1999, 2000, 2007 and 2013, and the reference evapotranspiration endured dramatic changes in 1998 and 2004 although the climate in these two years was comparable with in other years.Analysis of all data from 1955 to 2015 revealed that the probability of Bengbu and Fuyang being the wettest region was 50%, while Dangshan becoming the driest area was 83%. For evapotranspiration, the probability it peaked in Bozhou was 33% and troughed in Bengbu was 67%. These results suggested that irrigation schedule in the Huaibei Plain should be adjusted in that more irrigations should be considered for Bozhou and Dangshan and less for Bengbu and Fuyang.【Conclusion】There were no dramatic change in precipitation and evapotranspiration from 1955 to 2015, although evapotranspiration fluctuated noticeably. It is predicted that the precipitation in this region will continue to increase and the evapotranspiration will decrease in the coming years, rendering the region vulnerable to waterlogging or even flooding. Therefore, improving drainage should be the priority for this region to maintain its agricultural production.
【Objective】This paper is to calculate the spatiotemporal variation of precipitation and evapotranspiration in Huaibei Plain over the past six decades.【Method】The spatiotemporal change in the reference crop evapotranspiration was calculated based on the meteorological data measured from five weather stations in the region from 1955 to 2015, using ArcGIS, the M-K test and the R/S analysis method, the Kendall rank correlation and the M-K mutation test method, as well as the Yamamoto method and the sliding t-test method.【Result】From 1955 to2015, the precipitation in this region increased steadily, accompanied by a declined reference evapotranspiration.The wettest years were 1966, 1998, 1999, 2000, 2007 and 2013, and the reference evapotranspiration endured dramatic changes in 1998 and 2004 although the climate in these two years was comparable with in other years.Analysis of all data from 1955 to 2015 revealed that the probability of Bengbu and Fuyang being the wettest region was 50%, while Dangshan becoming the driest area was 83%. For evapotranspiration, the probability it peaked in Bozhou was 33% and troughed in Bengbu was 67%. These results suggested that irrigation schedule in the Huaibei Plain should be adjusted in that more irrigations should be considered for Bozhou and Dangshan and less for Bengbu and Fuyang.【Conclusion】There were no dramatic change in precipitation and evapotranspiration from 1955 to 2015, although evapotranspiration fluctuated noticeably. It is predicted that the precipitation in this region will continue to increase and the evapotranspiration will decrease in the coming years, rendering the region vulnerable to waterlogging or even flooding. Therefore, improving drainage should be the priority for this region to maintain its agricultural production.
引文
[1]袁再健,沈彦俊,褚英敏,等.海河流域近40年来降水和气温变化趋势及其空间分布特征[J].水土保持研究,2009,16(3):24-26.
[2]姬宏,王振龙,李瑞.淮北平原地下水资源演变情势研究[J].水文,2009,29(1):59-62.
[3]钟瑞森,吴彬.开都河径流年内分配特征研究[J].灌溉排水学报,2011,30(2):123-126.
[4]牛建龙,柳维扬,王家强,等.塔里木河干流流域气候变化特征及其突变分析[J].灌溉排水学报,2017,36(2):106-112.
[5]DAO Nguyen Khoi,HOANG Thi Trang.Analysis of changes in precipitation and extremes events in Ho Chi Minh city Vietnam[J].Procedia Engineering,2016,142:229-235.
[6]王振龙.淮北平原区水文实验研究[M].合肥:中国科技大学出版社,2011.
[7]单鱼洋,张新民,陈丽娟.彭曼公式在参考作物需水量中的应用[J].安徽农业科学,2008,36(10):4 196-4 197.
[8]邹璐,陈涛涛,孔凡丹,等.辽宁省参考作物腾发量的敏感性分析[J].灌溉排水学报,2014,33(1):50-54.
[9]MALAMOS N,BAROUCHAS P E,TSIROGIANNIS I L,et al.Estimation of monthly FAO Penman-Monteith evapotranspiration in GIS environment,through a geometry independent algorithm[J].Agriculture and Agricultural Science Procedia,2015,4:290-299.
[10]章诞武,丛振涛,倪广恒.基于中国气象资料的趋势检验方法对比分析[J].水科学进展,2013,24(4):490-496.
[11]牛凯杰,梁川,赵璐,等.西南地区干旱时空变化特征[J].灌溉排水学报,2014,33(3):1-6.
[12]金保明,高兰兰,颜望栋.基于Kendall与R/S法的年最大洪峰流量变化特性分析[J].水力发电,2016,42(11):20-23.
[13]奚圆圆,黄晓荣,李晶晶,等.四川盆地降水量变化特征分析[J].灌溉排水学报,2017,36(1):95-101.
[14]王孝礼,胡宝清,夏军.水文时序趋势与变异点的R/S分析法[J].武汉大学学报(工学版),2002,35(2):10-12.
[15]于延胜,陈兴伟.R/S和Mann-Kendall法综合分析水文时间序列未来的趋势特征[J].水资源与水工程学报,2008,19(3):41-44.
[16]黄济琛,陆宝宏,徐玲玲,等.变化条件下常德市降水气温特征分析[J].水文,2016,36(5):85-91.
[17]符淙斌,王强.气候突变的定义和检测方法[J].大气科学,1992,16(4):482-493.
[18]贾悦,崔宁博,魏新平,等.基于反距离权重法的长江流域参考作物蒸散量算法适用性评价[J].农业工程学报,2016,32(6):130-138.
[19]胡巍巍,王式成,王根绪,等.安徽淮北平原地下水动态变化研究[J].自然资源学报,2009,24(11):1 893-1 901.
[20]钱筱暄.淮北平原水文循环要素时空演变规律研究[D].扬州:扬州大学,2011.
[2]姬宏,王振龙,李瑞.淮北平原地下水资源演变情势研究[J].水文,2009,29(1):59-62.
[3]钟瑞森,吴彬.开都河径流年内分配特征研究[J].灌溉排水学报,2011,30(2):123-126.
[4]牛建龙,柳维扬,王家强,等.塔里木河干流流域气候变化特征及其突变分析[J].灌溉排水学报,2017,36(2):106-112.
[5]DAO Nguyen Khoi,HOANG Thi Trang.Analysis of changes in precipitation and extremes events in Ho Chi Minh city Vietnam[J].Procedia Engineering,2016,142:229-235.
[6]王振龙.淮北平原区水文实验研究[M].合肥:中国科技大学出版社,2011.
[7]单鱼洋,张新民,陈丽娟.彭曼公式在参考作物需水量中的应用[J].安徽农业科学,2008,36(10):4 196-4 197.
[8]邹璐,陈涛涛,孔凡丹,等.辽宁省参考作物腾发量的敏感性分析[J].灌溉排水学报,2014,33(1):50-54.
[9]MALAMOS N,BAROUCHAS P E,TSIROGIANNIS I L,et al.Estimation of monthly FAO Penman-Monteith evapotranspiration in GIS environment,through a geometry independent algorithm[J].Agriculture and Agricultural Science Procedia,2015,4:290-299.
[10]章诞武,丛振涛,倪广恒.基于中国气象资料的趋势检验方法对比分析[J].水科学进展,2013,24(4):490-496.
[11]牛凯杰,梁川,赵璐,等.西南地区干旱时空变化特征[J].灌溉排水学报,2014,33(3):1-6.
[12]金保明,高兰兰,颜望栋.基于Kendall与R/S法的年最大洪峰流量变化特性分析[J].水力发电,2016,42(11):20-23.
[13]奚圆圆,黄晓荣,李晶晶,等.四川盆地降水量变化特征分析[J].灌溉排水学报,2017,36(1):95-101.
[14]王孝礼,胡宝清,夏军.水文时序趋势与变异点的R/S分析法[J].武汉大学学报(工学版),2002,35(2):10-12.
[15]于延胜,陈兴伟.R/S和Mann-Kendall法综合分析水文时间序列未来的趋势特征[J].水资源与水工程学报,2008,19(3):41-44.
[16]黄济琛,陆宝宏,徐玲玲,等.变化条件下常德市降水气温特征分析[J].水文,2016,36(5):85-91.
[17]符淙斌,王强.气候突变的定义和检测方法[J].大气科学,1992,16(4):482-493.
[18]贾悦,崔宁博,魏新平,等.基于反距离权重法的长江流域参考作物蒸散量算法适用性评价[J].农业工程学报,2016,32(6):130-138.
[19]胡巍巍,王式成,王根绪,等.安徽淮北平原地下水动态变化研究[J].自然资源学报,2009,24(11):1 893-1 901.
[20]钱筱暄.淮北平原水文循环要素时空演变规律研究[D].扬州:扬州大学,2011.