充分掌握大尺度流域降雨侵蚀力的时空变化特征对流域水土保持、防洪减灾和生态环境保护至关重要。基于长江中下游的119个气象站点57a逐日降雨资料,通过Xie模型计算各站降雨侵蚀力,使用旋转经验正交函数(REOF)法对降雨侵蚀力进行区域划分...充分掌握大尺度流域降雨侵蚀力的时空变化特征对流域水土保持、防洪减灾和生态环境保护至关重要。基于长江中下游的119个气象站点57a逐日降雨资料,通过Xie模型计算各站降雨侵蚀力,使用旋转经验正交函数(REOF)法对降雨侵蚀力进行区域划分;结合Mann-Kendal检验、重标极差(R/S)法和相关性分析方法分析长江中下游降雨侵蚀力的时空变化特征,并揭示其与植被覆盖度之间的关系。结果表明:(1)长江中下游降雨侵蚀力整体呈上升趋势,年均降雨侵蚀力为5643MJ mm hm^(-2)h^(-1)。(2)不同季节降雨侵蚀力空间分布存在差异。冷季降雨侵蚀力空间分布不均,高值区主要集中在流域的西部和东北部,而暖季降雨侵蚀力则表现为以江西省为中心沿西北方向递减的空间分布格局,最大值和最小值出现在鄱阳湖环湖区(III区)和长江干流武汉以下段及太湖水系(IV区)。(3)长江中下游相邻地理分区间降雨侵蚀力变化速率差异较大,降雨侵蚀力区域性差异显著。其中III区、湘江及赣江流域(I区)和IV区年均降雨侵蚀力呈显著增长趋势(P<0.05)且未来将保持该趋势,为水土保持重点关注区域。(4)研究所发现的长江中下游水土保持重点关注区域的降雨侵蚀力与植被覆盖度存在负相关。但值得注意的是I区在冷季呈现正相关,而且其中的湘江上游流域出现显著正相关。研究表明降雨侵蚀力是影响地表侵蚀过程的关键因素,侵蚀性降水会影响植被覆盖情况,进而影响地表的侵蚀过程。因此在重点关注高降雨侵蚀力地区的同时还需加强植被保护工作。研究结果可为长江中下游区域水土保持及生态环境保护工作提供科学依据。展开更多
卫星降水产品具有覆盖范围广、更适用于无资料区域的优势,但分辨率较低、精度不足,为获取高时空分辨率、高精度的降水数据,需对卫星产品进行降尺度,并与地面观测数据融合,以提高数据质量。以澜沧江流域为例,在综合考虑地形、地理和植被...卫星降水产品具有覆盖范围广、更适用于无资料区域的优势,但分辨率较低、精度不足,为获取高时空分辨率、高精度的降水数据,需对卫星产品进行降尺度,并与地面观测数据融合,以提高数据质量。以澜沧江流域为例,在综合考虑地形、地理和植被等要素的基础上,建立地理加权回归(geographic weighted regression,GWR)模型对热带降雨测量卫星(tropical rainfall measurement mission,TRMM)和基于人工神经网络的遥感降水估计-气候数据记录(precipitation estimation from remotely sensed information using artificial neural networks-climate data record,PERSIANN-CDR)产品进行空间降尺度,再采用集合卡尔曼滤波算法,将地面气象站点经反距离加权插值法(inverse distance weighted,IDW)插值后的数据作为融合算法观测值,对降尺度后的TRMM、PERSIANN-CDR数据进行融合,以进一步提高降水数据精度。结果表明:1)相比TRMM卫星降水产品,PERSIANN-CDR降水产品对澜沧江流域降水的捕捉能力更弱,但降尺度后两者卫星产品数据精度都有较显著的提升;且两类产品在旱季(11月至次年4月)的精度评估效果相较于雨季(5月至10月)更为明显,表明GWR方法能显著提升这两类卫星降水产品对旱季降水的监测效果。2)对比其他学者的研究表明,对降尺度后的产品进一步使用集合卡尔曼滤波算法,最终得到的融合结果极好,并改善了卫星产品高估降水的现象。综上所述,该研究所使用的降尺度与融合方法,能够显著提升数据空间分辨率与精度,最终得到与地面观测降水数据相关性极高的高空间分辨率卫星产品结果。展开更多
Urban growth is a key indicator of economic development.At the same time,haphazard urban growth creates serious socioeconomic,environmental and urban land management problems.In this context,understanding the process ...Urban growth is a key indicator of economic development.At the same time,haphazard urban growth creates serious socioeconomic,environmental and urban land management problems.In this context,understanding the process of urban landscape change is important for guiding the sustainable growth of urban areas.This study analyzes the urban land changes during 1990–2018 in two metropolitan cities of Gandaki basin:Pokhara and Bharatpur.Landsat satellite images were analyzed using supervised classification methods.The results revealed that the built-up area has increased significantly by 300%in Pokhara and by nearly 500%in the Bharatpur during the past 28 years.Population growth,migration from surrounding areas due to urban facilities and the easy lifestyle in cities were found to be major determinants of urban growth within the study area.In addition,the changing urban definition and expansion of municipal boundaries are key factors for rapid urban growth.Both cities are likely to grow in the future as they are both located in areas that encompass the high levels of commercial activity and modern service facilities.The haphazard urban growth should be minimized through planning and policies for sustainable urban development.展开更多
文摘充分掌握大尺度流域降雨侵蚀力的时空变化特征对流域水土保持、防洪减灾和生态环境保护至关重要。基于长江中下游的119个气象站点57a逐日降雨资料,通过Xie模型计算各站降雨侵蚀力,使用旋转经验正交函数(REOF)法对降雨侵蚀力进行区域划分;结合Mann-Kendal检验、重标极差(R/S)法和相关性分析方法分析长江中下游降雨侵蚀力的时空变化特征,并揭示其与植被覆盖度之间的关系。结果表明:(1)长江中下游降雨侵蚀力整体呈上升趋势,年均降雨侵蚀力为5643MJ mm hm^(-2)h^(-1)。(2)不同季节降雨侵蚀力空间分布存在差异。冷季降雨侵蚀力空间分布不均,高值区主要集中在流域的西部和东北部,而暖季降雨侵蚀力则表现为以江西省为中心沿西北方向递减的空间分布格局,最大值和最小值出现在鄱阳湖环湖区(III区)和长江干流武汉以下段及太湖水系(IV区)。(3)长江中下游相邻地理分区间降雨侵蚀力变化速率差异较大,降雨侵蚀力区域性差异显著。其中III区、湘江及赣江流域(I区)和IV区年均降雨侵蚀力呈显著增长趋势(P<0.05)且未来将保持该趋势,为水土保持重点关注区域。(4)研究所发现的长江中下游水土保持重点关注区域的降雨侵蚀力与植被覆盖度存在负相关。但值得注意的是I区在冷季呈现正相关,而且其中的湘江上游流域出现显著正相关。研究表明降雨侵蚀力是影响地表侵蚀过程的关键因素,侵蚀性降水会影响植被覆盖情况,进而影响地表的侵蚀过程。因此在重点关注高降雨侵蚀力地区的同时还需加强植被保护工作。研究结果可为长江中下游区域水土保持及生态环境保护工作提供科学依据。
文摘卫星降水产品具有覆盖范围广、更适用于无资料区域的优势,但分辨率较低、精度不足,为获取高时空分辨率、高精度的降水数据,需对卫星产品进行降尺度,并与地面观测数据融合,以提高数据质量。以澜沧江流域为例,在综合考虑地形、地理和植被等要素的基础上,建立地理加权回归(geographic weighted regression,GWR)模型对热带降雨测量卫星(tropical rainfall measurement mission,TRMM)和基于人工神经网络的遥感降水估计-气候数据记录(precipitation estimation from remotely sensed information using artificial neural networks-climate data record,PERSIANN-CDR)产品进行空间降尺度,再采用集合卡尔曼滤波算法,将地面气象站点经反距离加权插值法(inverse distance weighted,IDW)插值后的数据作为融合算法观测值,对降尺度后的TRMM、PERSIANN-CDR数据进行融合,以进一步提高降水数据精度。结果表明:1)相比TRMM卫星降水产品,PERSIANN-CDR降水产品对澜沧江流域降水的捕捉能力更弱,但降尺度后两者卫星产品数据精度都有较显著的提升;且两类产品在旱季(11月至次年4月)的精度评估效果相较于雨季(5月至10月)更为明显,表明GWR方法能显著提升这两类卫星降水产品对旱季降水的监测效果。2)对比其他学者的研究表明,对降尺度后的产品进一步使用集合卡尔曼滤波算法,最终得到的融合结果极好,并改善了卫星产品高估降水的现象。综上所述,该研究所使用的降尺度与融合方法,能够显著提升数据空间分辨率与精度,最终得到与地面观测降水数据相关性极高的高空间分辨率卫星产品结果。
基金The National Natural Science Foundation of China(41761144081)The Second Tibetan Plateau Scientific Expedition and Research(2019QZKK2203)+1 种基金The International Partnership Program of Chinese Academy of Sciences(131C11KYSB20160061)The Chinese Academy of Sciences-The World Academy of Sciences(CAS-TWAS)President’s Fellowship Program for Ph D Study
文摘Urban growth is a key indicator of economic development.At the same time,haphazard urban growth creates serious socioeconomic,environmental and urban land management problems.In this context,understanding the process of urban landscape change is important for guiding the sustainable growth of urban areas.This study analyzes the urban land changes during 1990–2018 in two metropolitan cities of Gandaki basin:Pokhara and Bharatpur.Landsat satellite images were analyzed using supervised classification methods.The results revealed that the built-up area has increased significantly by 300%in Pokhara and by nearly 500%in the Bharatpur during the past 28 years.Population growth,migration from surrounding areas due to urban facilities and the easy lifestyle in cities were found to be major determinants of urban growth within the study area.In addition,the changing urban definition and expansion of municipal boundaries are key factors for rapid urban growth.Both cities are likely to grow in the future as they are both located in areas that encompass the high levels of commercial activity and modern service facilities.The haphazard urban growth should be minimized through planning and policies for sustainable urban development.
