基于TVDI的玛曲土壤湿度时空变化及其影响因素
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摘要
玛曲位于青藏高原东缘,是黄河重要的水源涵养区,也是生态脆弱地区,研究土壤湿度动态变化及其影响因素,对青藏高原区水资源、生态安全保障具有重要的现实意义。利用温度植被干旱指数法(TVDI)反演玛曲2000—2015年土壤湿度,分析土壤湿度空间分布和时间变化特征,并采用多元线性回归模型探讨了影响土壤湿度的关键要素。研究表明:1) 2000—2015年玛曲地区土壤湿度整体呈现下降趋势,呈旱化的现象,土壤湿度的空间分异特征和季节变化规律显著。其中:土壤湿度空间分布格局为从西北向东南逐渐减少,总体干湿等级以正常为主(0. 5 [Background] Maqu is a significant water conservation area of the Yellow River and an ecologically fragile area,which is located on the eastern edge of the Qinghai-Tibet Plateau. Studying the dynamic changes of soil moisture and its influencing factors have important practical significance for water resources and ecological security in the Qinghai-Tibet Plateau. [Methods] In this study, the temperature vegetation drought index(TVDI) method was used to invert the soil moisture of Maqu county from 2000 to 2015,then the spatial distribution and temporal variation characteristics of soil moisture were analyzed,and finally the correlation analysis and multiple linear regression models were applied to explore the key factors affecting soil moisture. [Results] 1) The soil moisture in the Maqu area from2000 to 2015 showed a downward trend as a whole,with signs of drought,and the spatial differentiation characteristics and seasonal variation of soil moisture were significant. Among them, the spatial distribution pattern of soil moisture gradually decreased from northwest to southeast,and the overall dry and wet grade was dominated by normal(0. 5 < TVDI≤0. 6). On the seasonal scale,the surface soil moisture in the spring gradually decreased with the passage of time,tending to become dry. In summer,the soil moisture in the surface layer was large and stable,which was directly related to the recharge of summer precipitation. Due to the decrease of winter precipitation,the overall soil moisture in winter was the lowest and continued to decline,and further led to the reduction of spring ice and snow melt water. 2)The spatial pattern and change of soil moisture were formed by a combination of several influencing factors. Among them, net primary productivity, annual precipitation, elevation, slope and GDP demonstrated significant positive effects on soil moisture, while annual average temperature and population presented significant negative effects on soil moisture. [Conclusions] Therefore, it is necessary to control the population growth,increase vegetation coverage,actively respond to climate changes to reduce the adverse effects of temperature on soil moisture and so on,so that the soil moisture of the surface of Maqu is maintained in a fine condition,providing a certain guarantee for the runoff of the Yellow River. These research results will provide important reference information for water resources and ecological environment research in the Yellow River source area.
引文
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[15]张志达.基于3S的玛曲湿地动态监测研究[D].兰州:兰州大学,2012:10.ZHANG Zhida. Dynamic monitoring of Maqu wetland based on 3S technology[D]. Lanzhou:Lanzhou University,2012:10.
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[17]胡悦.基于多源数据的宁夏中部干旱带干旱信息时空变化特征研究[D].银川:宁夏大学,2017:10.HU Yue. Temporal and spatial variation characteristics of drought information in the arid region of central Ningxia based on multi-source data[D]. Yinchuan:Ningxia University,2017:10.
[18]郭瑞宁,郭青霞,冯雨豪,等.基于TVDI的土壤湿度时空分布及影响因子分析[J].灌溉排水学报,2018,37(4):52.GUO Ruining,GUO Qingxia,FENG Yuhao,et al. Analysis of the factors affecting the spatiotemporal soil moisture distribution based on the temperature-vegetation drought index[J]. Journal of Irrigation and Drainage,2018,37(4):52.
[19] BHUMIKA U,JORG D,CHRISTOS V,et al. Evaluation of SWAT simulated soil moisture at catchment scale by field measurements and Landsat derived indices[J].Agricultural Water Management,2017,193:55.
[20] TAGESSON T,HORION S,NIRTO H,et al. Disaggregation of SMOS soil moisture over West Africa using the temperature and vegetation dryness index based on SEVIRI land surface parameters[J]. Remote Sensing of Environment,2018,206:424.
[21]陈金雷,文军,刘蓉,等.黄河源区土壤温湿变化及相关气候要素分析[C].第33届中国气象学会年会,西安,2016:12.CHEN Jinlei,WEN Jun,LIU Rong,et al. The analysis of soil temperature and moisture variation and associated climate factors in the source region of the Yellow River[C]. The 33rd Annual Meeting of the Chinese Meteorological Society,Xi'an,2016:12.
[22]陈东东,廖捷,陈功,等.四川盆地土壤湿度时空分布及影响因子分析[J].高原山地气象研究,2016,36(4):36.CHEN Dongdong,LIAO Jie,CHEN Gong,et al. Spatial and temporal distribution of soil moisture and its influence factor analysis in Sichuan Basin[J]. Plateau and Mountain Meteorology Research,2016,36(4):36.
[23]王娟,张优,张杰,等.基于TVDI的山地平原过渡带土壤水分反演:以绵竹市为例[J].水土保持研究,2018,25(2):151.WANG Juan,ZHANG You,ZHANG Jie,et al. Soil moisture inversion in the transitional zone of mountainous plain based on TVDI:A case study of Mianzhu City[J]. Research of Soil and Water Conservation,2018,25(2):151.
[24]陈少丹,张利平,闪丽洁,等.长江中下游流域土壤湿度遥感反演研究及其影响因素分析[J].应用基础与工程科学学报,2017,25(4):657.CHEN Shaodan,ZHANG Liping,SHAN Lijie,et al.Research on remote sensing inversion of soil moisture and analysis of influencing factors in the middle and lower Yangtze River Basin[J]. Journal of Basic Science and Engineering,2017,25(4):657.
[2]杨秀海,卓嘎,罗布.基于MODIS数据的西北地区旱情监测[J].草业科学,2011,28(8):1420.YANG Xiuhai,ZHUO Ga,LUO Bu. Drought monitoring in Northwest China based on MODIS data[J]. Pratacultural Science,2011,28(8):1420.
[3]杨玲,杨艳昭.基于TVDI的西辽河流域土壤湿度时空格局及其影响因素[J].干旱区资源与环境,2016,30(2):76.YANG Ling,YANG Yanzhao. The spatial and temporal pattern of soil moisture in the west Liaohe River Basin based on TVDI method and its influencing factors[J].Journal of Arid Land Resources and Environment,2016,30(2):76.
[4]温国涛,白建军,孙嵩松.基于时间序列遥感数据的陕西省2004—2014年干旱变化特征分析[J].干旱地区农业研究,2018,36(1):221.WEN Guotao,BAI Jianjun,SUN Songsong. Variation of drought in Shaanxi from 2004 to 2014 based on remotely sensed data[J]. Agricultural Research in the Arid Areas,2018,36(1):221.
[5]刘晓婧.基于TM数据的延河流域土壤水分反演研究[D].陕西杨凌:西北农林科技大学,2010:2.LIU Xiaojing. Retrieving the soil moisture based on TM data in Yan River Basin[D]. Yangling,Shaanxi:Northwest A&F University,2010:2.
[6]李彩瑛,阎建忠,刘林山,等.基于TVDI的羌塘高原夏季土壤湿度变化分析[J].地理研究,2017,36(11):2101.LI Caiying,YAN Jianzhong,LIU Linshan,et al. Analysis of soil moisture variation in summer of Qiangtang Plateau based on TVDI[J]. Geographical Research,2017,36(11):2101.
[7]张晶言,白建军,于茜.基于TVDI模型的关中地区春旱时空动态监测[J].兰州大学学报(自然科学版),2017,53(6):799.ZHANG Jingyan,BAI Jianjun,YU Qian. Spatial-temporal dynamic monitoring of spring drought based on TVDI model in the Guanzhong area[J]. Journal of Lanzhou University(Natural Sciences),2017,53(6):799.
[8] PRICE J C. Using spatial context in satellite data to infer regional scale evapotranspiration[C]. IEEE Transactions on Geoscience and Remote Sensing,1990,28:940.
[9] Goetz S J. Multi-sensor analysis of NDVI,surface temperature and biophysical variables at a mixed grassland site[J]. International Journal of Remote Sensing,1997,18(1):71.
[10] SANDHOLT I,RASMUSSEN K,ANDERSEN J. A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status[J]. Remote Sensing of Environment,2002,79:213.
[11]陈斌,张学霞,华开,等.温度植被干旱指数(TVDI)在草原干旱监测中的应用研究[J].干旱区地理,2013,36(5):930.CHEN Bin,ZHANG Xuexia,HUA Kai,et al. Application study of temperature vegetation drought index(TVDI)in grassland drought monitoring[J]. Arid Land Geography,2013,36(5):930.
[12]梁华.基于TVDI的新疆祁漫塔格土壤湿度遥感反演研究[D].北京:中国地质大学,2016:44.LIANG Hua. Remote sensing retrieval study of soil moisture in Qmantage,Xinjiang based on TVDI[D].Beijing:China University Of Geosciences,2016:44.
[13]王行汉,刘超群,丛沛桐.基于增强温度植被指数的农业旱情遥感监测[J].干旱区资源与环境,2018,32(5):165.WANG Xinghan,LIU Chaoqun,CONG Peitong,Agriculture drought monitoring using remote sensing based on enhanced temperature vegetation dryness index[J].Journal of Arid Land Resources and Environment,2018,32(5):165.
[14]褚琳.黄河源玛曲高寒湿地生态退化与修复适宜性评价研究[D].武汉:华中农业大学,2012:67.CHU Lin. The research on degradation and restoration suitability assessment of Yellow River source alpine wetlands in Maqu[D]. Wuhan:Huazhong Agricultural University,2012:67.
[15]张志达.基于3S的玛曲湿地动态监测研究[D].兰州:兰州大学,2012:10.ZHANG Zhida. Dynamic monitoring of Maqu wetland based on 3S technology[D]. Lanzhou:Lanzhou University,2012:10.
[16]宋春桥,游松财,刘高焕,等.基于TVDI的藏北地区土壤湿度空间格局[J].地理科学进展,2011,30(5):569.SONG Chunqiao,YOU Songcai,LIU Gaohuan,et al.The spatial pattern of soil moisture in Northern Tibet based on TVDI method[J]. Progress in Geography,2011,30(5):569.
[17]胡悦.基于多源数据的宁夏中部干旱带干旱信息时空变化特征研究[D].银川:宁夏大学,2017:10.HU Yue. Temporal and spatial variation characteristics of drought information in the arid region of central Ningxia based on multi-source data[D]. Yinchuan:Ningxia University,2017:10.
[18]郭瑞宁,郭青霞,冯雨豪,等.基于TVDI的土壤湿度时空分布及影响因子分析[J].灌溉排水学报,2018,37(4):52.GUO Ruining,GUO Qingxia,FENG Yuhao,et al. Analysis of the factors affecting the spatiotemporal soil moisture distribution based on the temperature-vegetation drought index[J]. Journal of Irrigation and Drainage,2018,37(4):52.
[19] BHUMIKA U,JORG D,CHRISTOS V,et al. Evaluation of SWAT simulated soil moisture at catchment scale by field measurements and Landsat derived indices[J].Agricultural Water Management,2017,193:55.
[20] TAGESSON T,HORION S,NIRTO H,et al. Disaggregation of SMOS soil moisture over West Africa using the temperature and vegetation dryness index based on SEVIRI land surface parameters[J]. Remote Sensing of Environment,2018,206:424.
[21]陈金雷,文军,刘蓉,等.黄河源区土壤温湿变化及相关气候要素分析[C].第33届中国气象学会年会,西安,2016:12.CHEN Jinlei,WEN Jun,LIU Rong,et al. The analysis of soil temperature and moisture variation and associated climate factors in the source region of the Yellow River[C]. The 33rd Annual Meeting of the Chinese Meteorological Society,Xi'an,2016:12.
[22]陈东东,廖捷,陈功,等.四川盆地土壤湿度时空分布及影响因子分析[J].高原山地气象研究,2016,36(4):36.CHEN Dongdong,LIAO Jie,CHEN Gong,et al. Spatial and temporal distribution of soil moisture and its influence factor analysis in Sichuan Basin[J]. Plateau and Mountain Meteorology Research,2016,36(4):36.
[23]王娟,张优,张杰,等.基于TVDI的山地平原过渡带土壤水分反演:以绵竹市为例[J].水土保持研究,2018,25(2):151.WANG Juan,ZHANG You,ZHANG Jie,et al. Soil moisture inversion in the transitional zone of mountainous plain based on TVDI:A case study of Mianzhu City[J]. Research of Soil and Water Conservation,2018,25(2):151.
[24]陈少丹,张利平,闪丽洁,等.长江中下游流域土壤湿度遥感反演研究及其影响因素分析[J].应用基础与工程科学学报,2017,25(4):657.CHEN Shaodan,ZHANG Liping,SHAN Lijie,et al.Research on remote sensing inversion of soil moisture and analysis of influencing factors in the middle and lower Yangtze River Basin[J]. Journal of Basic Science and Engineering,2017,25(4):657.
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