2008—2014年新疆艾比湖流域土壤水分时空分布特征
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摘要
传统的土壤水分模拟研究难以从土壤水分变化的时空双向出发表达其连续演变的过程,存在时空尺度效应问题。借助SWAT模型模拟的长时间序列优势,结合高分辨率卫星影像和遥感技术,力图在时空尺度效应问题上取得突破。并利用长时间序列的模拟结果分析流域土壤水分的空间格局和不同维度时空异质性。结果表明:(1)2008—2014年间艾比湖流域土壤水分主要受气温、降水及人类活动影响,呈波动变化,总体偏低且具有逐年减小趋势。(2)受降水、地形及土地覆被影响,土壤水分分布呈现出由山区向两侧平原减少的特点,且林地>农用地>草地>稀疏植被。(3)近10年间土壤水分低值区由原来的北部山区及平原向东部、东南部平原区及南部山区迁移,东部减少最为明显。(4)流域四季土壤水分变化差异显著。其中,春季主要受融雪影响;夏季、秋季主要受降雨量和气温影响;冬季主要受固态降雪和气温影响;且不同年份、相同季节、相同子流域土壤水分变化趋势表现一致。
It is difficult to express the true soil moisture temporal and spatial variation in traditional methods, because it always reflects a certain spatial resolution or discrete temporal pattern, which is not a continuous process. In this paper, we use SWAT(Soil and Water Assessment Tool)model and multi-source remote sensing data to solve the problems caused by the effects of spatial and temporal scales of soil moisture monitoring. Explore the scientific regional scale and long-time-series soil moisture simulation method, and use the simulation results analysis soil moisture in different time and space in study area. The results showed the following:(1) soil moisture over the entire region was continued decline from 2008—2014. The major factors affecting this trend are temperature, precipitation, and human activities.(2) The distribution of soil moisture is affected by precipitation, temperature, and land cover. The distribution of soil moisture is characterized by decreasing from the mountainous area to the plains, and in the following order: woodland > agricultural land > grassland > sparse vegetation.(3) In the past 10 years, the area with low soil moisture shifted from the northern mountainous plains to the eastern part, southeastern plains, and southern mountains, one of the most obvious change was eastern part.(4) The variation in soil moisture in the four seasons was significant. Soil moisture in spring and autumn were affected by rainfall and temperature, and that in winter was affected by the snow melt and temperature. The sub-basin soil moisture change were consistent in same season in different years.
It is difficult to express the true soil moisture temporal and spatial variation in traditional methods, because it always reflects a certain spatial resolution or discrete temporal pattern, which is not a continuous process. In this paper, we use SWAT(Soil and Water Assessment Tool)model and multi-source remote sensing data to solve the problems caused by the effects of spatial and temporal scales of soil moisture monitoring. Explore the scientific regional scale and long-time-series soil moisture simulation method, and use the simulation results analysis soil moisture in different time and space in study area. The results showed the following:(1) soil moisture over the entire region was continued decline from 2008—2014. The major factors affecting this trend are temperature, precipitation, and human activities.(2) The distribution of soil moisture is affected by precipitation, temperature, and land cover. The distribution of soil moisture is characterized by decreasing from the mountainous area to the plains, and in the following order: woodland > agricultural land > grassland > sparse vegetation.(3) In the past 10 years, the area with low soil moisture shifted from the northern mountainous plains to the eastern part, southeastern plains, and southern mountains, one of the most obvious change was eastern part.(4) The variation in soil moisture in the four seasons was significant. Soil moisture in spring and autumn were affected by rainfall and temperature, and that in winter was affected by the snow melt and temperature. The sub-basin soil moisture change were consistent in same season in different years.
引文
[1] Seneviratne S I, Davin E, Hirschi M, Mueller B, Orlowsky B, Teuling A. Soil moisture-ecosystem-climate interactions in a changing climate//AGU Fall Meeting. AGU, 2011. San Francisco Marriott Marquis.
[2] 杨涛, 宫辉力, 李小娟, 赵文吉, 孟丹. 土壤水分遥感监测研究进展. 生态学报, 2010, 30(22): 6264- 6277.
[3] Jung M, Reichstein M, Ciais P, Seneviratne S I, Sheffield J, Goulden M L, Bonan G, Cescatti A, Chen J Q, de Jeu R, Dolman A J, Eugster W, Gerten D, Gianelle D, Gobron N, Heinke J, Kimball J, Law B E, Montagnani L, Mu Q Z, Mueller B, Oleson K, Papale D, Richardson A D, Roupsard O, Running S, Tomelleri E, Viovy N, Weber U, Williams C, Wood E, Zaehle S, Zhang K. Recent decline in the global land evapotranspiration trend due to limited moisture supply. Nature, 2010, 467(7318): 951- 954.
[4] Hu Shoulin, Jia Zhikuan, Wan Sumei. Soil moisture consumption and ecological effects in alfalfa grasslands in Longdong area of Loess Plateau[J]. Transactions of the CSAE, 2009,25(8):48- 53.
[5] 曹雷,丁建丽,牛增懿. 基于TVDI的艾比湖地区土壤水分时空变化分析.水土保持研究,2016,23(03):43-47.
[6] 秦璐, 傅德平, 杨军, 何学敏, 张雪妮, 吕光辉. 艾比湖湿地自然保护区典型群落土壤理化性质分析. 干旱区资源与环境, 2011, 25(8): 144- 151.
[7] 张海威, 张飞, 李哲. 不同环境背景下的艾比湖区域土壤水盐差异性特征研究. 干旱区地理, 2017, 40(3): 606- 613.
[8] 张雅莉. 艾比湖流域土壤盐渍化地区生态环境遥感监测研究[D].新疆大学,2017.
[9] 朱小强. 基于多源遥感数据的艾比湖面积动态变化研究[D].新疆大学,2018.
[10] 王中根, 刘昌明, 黄友波. SWAT模型的原理、结构及应用研究. 地理科学进展, 2003, 22(1): 79- 86.
[11] Arnold J G, Allen P M. Estimating hydrologic budgets for three Illinois watersheds. Journal of Hydrology, 1996, 176(1/4): 57- 77.
[12] Fohrer N, M?ller D, Steiner N. An interdisciplinary modelling approach to evaluate the effects of land use change. Physics and Chemistry of the Earth, Parts A/B/C, 2002, 27(9/10): 655- 662.
[13] Grizzetti B, Bouraoui F, Granlund K, Rekolainen S, Bidoglio G. Modelling diffuse emission and retention of nutrients in the Vantaanjoki watershed (Finland) using the SWAT model. Ecological Modelling, 2003, 169(1): 25- 38.
[14] Gosain A K, Rao S, Srinivasan R, Reddy N G. Return‐flow assessment for irrigation command in the Palleru river basin using SWAT model. Hydrological Processes, 2005, 19(3): 673- 682.
[15] 赵堃, 苏保林, 申萌萌, 管毓堂, 周静雯. 一种SWAT模型参数识别的改进方法. 南水北调与水利科技, 2017, 15(4): 49- 53.
[16] 申蒙蒙, 陆忠华, 王彦棡. 水文模拟中并行参数优化算法. 计算机工程与设计, 2017, 38(4): 1002- 1007.
[17] Kiniry J R, Williams J R, Srinivasan R. Soil and water assessment tool user′s manual. Nature Clinical Practice Rheumatology, 2000, 3(3): 119- 119.
[18] Neitsch S L, Arnold J G, Kiniry J R, Williams J R. SWAT 2009理论基础. 龙爱华, 邹松兵, 许宝荣, 陆志翔, 尹振良, 汪党献, 译. 郑州: 黄河水利出版社, 2012.
[19] 孟现勇, 王浩, 刘志辉, 师春香, 刘时银, 陈曦, 龚伟伟. 基于CLDAS强迫CLM3.5模式的新疆区域土壤温度陆面过程模拟及验证. 生态学报, 2017, 37(3): 979- 995.
[20] 刘广明, 杨劲松. 土壤含盐量与土壤电导率及水分含量关系的试验研究. 土壤通报, 2001, 32(S1): 85- 87.
[21] Moriasi D N, Arnold J G, van Liew M W, Bingner R L, Harmel R D, Veith T L. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE, 2007, 50(3): 885- 900.
[22] 毛飞. 基于风云三号卫星数据的土壤水分遥感反演研究[D]. 南京: 南京信息工程大学, 2014.
[2] 杨涛, 宫辉力, 李小娟, 赵文吉, 孟丹. 土壤水分遥感监测研究进展. 生态学报, 2010, 30(22): 6264- 6277.
[3] Jung M, Reichstein M, Ciais P, Seneviratne S I, Sheffield J, Goulden M L, Bonan G, Cescatti A, Chen J Q, de Jeu R, Dolman A J, Eugster W, Gerten D, Gianelle D, Gobron N, Heinke J, Kimball J, Law B E, Montagnani L, Mu Q Z, Mueller B, Oleson K, Papale D, Richardson A D, Roupsard O, Running S, Tomelleri E, Viovy N, Weber U, Williams C, Wood E, Zaehle S, Zhang K. Recent decline in the global land evapotranspiration trend due to limited moisture supply. Nature, 2010, 467(7318): 951- 954.
[4] Hu Shoulin, Jia Zhikuan, Wan Sumei. Soil moisture consumption and ecological effects in alfalfa grasslands in Longdong area of Loess Plateau[J]. Transactions of the CSAE, 2009,25(8):48- 53.
[5] 曹雷,丁建丽,牛增懿. 基于TVDI的艾比湖地区土壤水分时空变化分析.水土保持研究,2016,23(03):43-47.
[6] 秦璐, 傅德平, 杨军, 何学敏, 张雪妮, 吕光辉. 艾比湖湿地自然保护区典型群落土壤理化性质分析. 干旱区资源与环境, 2011, 25(8): 144- 151.
[7] 张海威, 张飞, 李哲. 不同环境背景下的艾比湖区域土壤水盐差异性特征研究. 干旱区地理, 2017, 40(3): 606- 613.
[8] 张雅莉. 艾比湖流域土壤盐渍化地区生态环境遥感监测研究[D].新疆大学,2017.
[9] 朱小强. 基于多源遥感数据的艾比湖面积动态变化研究[D].新疆大学,2018.
[10] 王中根, 刘昌明, 黄友波. SWAT模型的原理、结构及应用研究. 地理科学进展, 2003, 22(1): 79- 86.
[11] Arnold J G, Allen P M. Estimating hydrologic budgets for three Illinois watersheds. Journal of Hydrology, 1996, 176(1/4): 57- 77.
[12] Fohrer N, M?ller D, Steiner N. An interdisciplinary modelling approach to evaluate the effects of land use change. Physics and Chemistry of the Earth, Parts A/B/C, 2002, 27(9/10): 655- 662.
[13] Grizzetti B, Bouraoui F, Granlund K, Rekolainen S, Bidoglio G. Modelling diffuse emission and retention of nutrients in the Vantaanjoki watershed (Finland) using the SWAT model. Ecological Modelling, 2003, 169(1): 25- 38.
[14] Gosain A K, Rao S, Srinivasan R, Reddy N G. Return‐flow assessment for irrigation command in the Palleru river basin using SWAT model. Hydrological Processes, 2005, 19(3): 673- 682.
[15] 赵堃, 苏保林, 申萌萌, 管毓堂, 周静雯. 一种SWAT模型参数识别的改进方法. 南水北调与水利科技, 2017, 15(4): 49- 53.
[16] 申蒙蒙, 陆忠华, 王彦棡. 水文模拟中并行参数优化算法. 计算机工程与设计, 2017, 38(4): 1002- 1007.
[17] Kiniry J R, Williams J R, Srinivasan R. Soil and water assessment tool user′s manual. Nature Clinical Practice Rheumatology, 2000, 3(3): 119- 119.
[18] Neitsch S L, Arnold J G, Kiniry J R, Williams J R. SWAT 2009理论基础. 龙爱华, 邹松兵, 许宝荣, 陆志翔, 尹振良, 汪党献, 译. 郑州: 黄河水利出版社, 2012.
[19] 孟现勇, 王浩, 刘志辉, 师春香, 刘时银, 陈曦, 龚伟伟. 基于CLDAS强迫CLM3.5模式的新疆区域土壤温度陆面过程模拟及验证. 生态学报, 2017, 37(3): 979- 995.
[20] 刘广明, 杨劲松. 土壤含盐量与土壤电导率及水分含量关系的试验研究. 土壤通报, 2001, 32(S1): 85- 87.
[21] Moriasi D N, Arnold J G, van Liew M W, Bingner R L, Harmel R D, Veith T L. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE, 2007, 50(3): 885- 900.
[22] 毛飞. 基于风云三号卫星数据的土壤水分遥感反演研究[D]. 南京: 南京信息工程大学, 2014.