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银川平原地表蒸发量的估算及其在生态水文地质中的应用
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摘要
银川平原作为宁夏乃至西北地区珍贵的人工生态绿洲,其规模和稳定性取决于区域水资源量。近年来,由于黄河断流,宁夏黄河引水量逐渐减少。水资源的不合理利用加剧了银川平原生态环境的恶化,造成主要环境因素组合不协调,自然生态系统功能偏低,环境容量较小,生态平衡脆弱。地表蒸散发作为区域水量平衡和能量平衡的主要成分,不仅在水循环和能量循环过程中具有极其重要的作用,也是生态过程与水文过程的重要纽带。通过对银川平原地表蒸散发在时空演化及其影响因素方面的研究,加深对绿洲内部水循环过程的认识,可以为银川平原水资源合理开发利用、水土资源合理配置及生态环境保护等提供决策支持。
     利用获取到的晴空无云的MODIS数据及遥感定量反演模型SEBS(Surface Energy Balance System)估算了银川平原的地表蒸发量,推算了未获取到卫星遥感图像的日蒸发量,并对其推算误差进行了定量评估,结果表明:(1)银川平原2004年的蒸发量约为38.16×108 m3。(2)银川平原地表蒸发量在7月上旬至8月中旬达到最大值,约为3 mm/d;11月中旬至12月以及1月份,地表蒸发量最小,不足0.5 mm/d。
     通过地表蒸发量、土地覆盖类型、地下水位埋深及NDVI进行空间叠加与GIS复合分析,合理地揭示了银川平原地表蒸发量的空间分布特征及其与地下水位埋深及植被覆盖之间的关系,在此基础上获得了不同植被覆盖条件下的潜水蒸发极限埋深:(1)银川平原中的不同土地覆盖类型,其地表蒸发量之间具有明显的差异性,蒸发量由大到小依次是:水体、耕地、密集灌丛、草地、城市和建设用地、稀疏灌丛、裸地。(2)在枯水期,银川平原地表蒸发量的空间分布主要受地下水位埋深的影响;水位埋深小于1.6 m的地区由于土壤次生盐渍化的发育,地表蒸发量较小;地下水位埋深在1.6– 2.2 m时,蒸发量达到最大值,之后随埋深的增大而减小,并在埋深达到4 m时趋向一稳定值,因此银川平原枯水期裸土的潜水蒸发极限埋深约为4 m。(3)在丰水期,银川平原地表蒸发量的空间分布主要受植被覆盖及地下水位埋深的影响;地表蒸发量随地下水位埋深的增大而减小,在埋深达到6 m时趋向一稳定值,因此银川平原丰水期存在植被覆盖时的潜水蒸发极限埋深约为6 m。(4)随着地下水位埋深的增大,地表植被覆盖度逐渐降低,其植被蒸腾量也逐渐减小;而裸土的覆盖度则随地下水位埋深的增加而逐渐增大,裸土蒸发量也随之增大。(5)在地表蒸发量随地下水位埋深和NDVI变化的等值线图中,随着NDVI的增大,地表蒸发量的等值线向地下水位埋深增大的方向倾斜;在NDVI小于0.2的裸土区,潜水蒸发的极限埋深约为3 m;随着NDVI的增大,潜水蒸发的极限埋深也随之增加,最大可以达到6 m左右。
     对SEBS估算出的地表蒸发量在生态水文地质中的应用进行了探索:(1)银川平原的生态需水量等于年陆面蒸散量,即为38.16×108 m3。(2)建立了地下水位埋深的定量反演模型,对银川平原的地下水位埋深进行了遥感估算,其误差分布主要集中在地下水位埋深大于潜水蒸发极限埋深的地区,如贺兰山洪积倾斜平原、银川市的地下水位降落漏斗区等。(3)根据潜水蒸发极限埋深及潜水蒸发系数估算了银川平原2004年的潜水蒸发量为14.2×108 m3,并对植被覆盖条件下的阿维里扬诺夫潜水蒸发公式的参数化进行了探讨。
Yinchuan Plain is in the north of Ningxia Hui Autonomous Region. As a rare oasis of artificial ecosystem, its stability depends on the quantity of regional water resource. In recent years, for the reason of the Yellow River zero flow, the volume of the Yellow River water available for Ningxia has decreased year by year. Irrational utilization of water resource aggravate the deterioration of ecological environment in the Yinchuan Plain, resulting in that major environmental factors lack of coordination, the function of natural ecosystem is weakened, the capacity of the environment is small, and the ecological balance is fragile. As a major component of regional water and energy balances, land surface evapotranspiration is extremely important not only in the processes of water and energy cycle, but also it is an important link between ecological and hydrological processes. Through the research of the temporal and spatial evolution of the land surface evapotranspiration and their impact factors in the Yinchuan Plain, we could understand the process of water cycle in the oasis thoroughly, and the results will provide decision support for rational development and utilization of water resource, allocation of land and water resources as well as protection of ecological environment.
     We estimated the land surface evapotranspiration of the Yinchuan Plain with MODIS remotely sensed data in the clear sky days and quantitative inversion model– SEBS (Surface Energy Balance System), calculated the evapotranspiration in the date of no available satellite remote sensing images, and the error was evaluated quantitatively, the results show that: (1) The land surface evapotranspiration of the Yinchuan Plain was about 38.16×108 m3 in 2004. (2) The evapotranspiration of the Yinchuan Plain measure up to maximum from early July to mid-August with about 3 mm/d. From mid-November to December and January, the evapotranspiration measure up to minimum, less than 0.5 mm/d.
     By means of spatial overlay and GIS multi-factor analysis of land surface evapotranspiration, land cover types, groundwater depth and NDVI, we arrive at a reasonable characteristic of the spatial distribution of evapotranspiration in the Yinchuan plain and its relationship with groundwater depth and vegetation cover, as well as the limit depth of phreatic water evaporation on different vegetation cover conditions, the results are as follows: (1) The land surface evapotranspiration has a significant difference between different land cover types in the Yinchuan Plain, and its descending order are: water, croplands, closed shrublands, grasslands, urban and built-up, open shrublands, barren or sparsely vegetated. (2) In the dry season, the spatial distribution of evapotranspiration in the Yinchuan Plain is mainly affected by groundwater depth. In areas of groundwater depth being less than 1.6 m, the evapotranspiration is very small as a result of the soil salinization. The evapotranspiration measures up to maximum when groundwater depth is 1.6 - 2.2 m, and then decreases with the increase of groundwater depth until being 4 m, so the limit depth of phreatic water evaporation of bare soil is about 4 m. (3) In the wet season, the spatial distribution of evapotranspiration in the Yinchuan Plain is mainly affected by vegetation cover and groundwater depth. The evapotranspiration decreases with the increase of groundwater depth until being 6 m, so the limit depth of phreatic water evaporation in the Yinchuan Plain covered by vegetation is about 6 m. (4) The land surface vegetation coverage decreases with the increase of groundwater depth, and the amount of vegetation transpiration is gradually reduced. But the evaporation of bare soil increases as a result of the coverage of bare soil increases with groundwater depth gradually. (5) In the contour map of evapotranspiration changes along with groundwater depth and NDVI, the contour of evapotranspiration decline to the deeper groundwater depth with the increase of NDVI. For the bare soil with NDVI less than 0.2, the limit depth of phreatic water evaporation is about 3 m. The limit depth of phreatic water evaporation increases with the increase of NDVI, and the largest of about 6 m can be achieved.
     We explored the application of the land surface evapotranspiration estimated by SEBS in eco-hydrogeology: (1) The ecological water requirement is equivalent to land surface evapotranspiration in the Yinchuan Plain, which is about 38.16×108 m3. (2) We established a quantitative inversion model for groundwater depth and estimated the groundwater depth in the Yinchuan Plain, and the error mainly distribute where the groundwater depth is deeper than the limit depth of phreatic water evaporation, such as Helan Mountain alluvial piedmont plain and the groundwater depression cone in the Yinchuan city. (3) The phreatic water evaporation of the Yinchuan Plain was about 14.2×108 m3 in 2004 which was estimated based on the limit depth of phreatic water evaporation as well as the phreatic water evaporation coefficient.
引文
Bastiaanssen W.G.M., Kabat P., Menenti M. A new simulation model of bare soil evaporation in deserts. EVADES, ICW Note 1938. Wgeningen, the Netherlands: The Winand Staring Centre, 1989
    Bastiaanssen W.G.M., Menenti M. Surface reflectance and surface temperature in relation with soil type and regional energy fluxes [A]. In: Bouwman A.F. eds. Soils and the greenhouse effect [C]. Chichester, UK: John Wiley & Sons, 1989
    Bastiaanssen W.G.M., Menenti M. Mapping groundwater losses in the western desert of Egypt with satellite measurement of surface reflectance and surface temperature [A]. In: Hooghaet J.C. eds. Water management and remote sensing [C]. The Hague, the Netherlands: TNO-Proc and Inform, 1990
    Bastiaanssen W.G.M., Menenti M., Feddes R.A., et al. A remote sensing surface energy balance algorithm for land (SEBAL): 1. Formulation [J]. Journal of Hydrology, 1998, 212-213: 198-212
    Bastiaanssen W.G.M., Pelgrum H., Wang J., et al. A remote sensing surface energy balance algorithm for land (SEBAL): 2.Validation [J]. Journal of Hydrology, 1998, 212-213: 213-229
    Bastiaanssen W.G.M.. SEBAL-based sensible and latent heat fluxes in the irrigated Gediz Basin, Turkey [J]. Journal of Hydrology, 2000, 229: 87-100
    Bastiaanssen W.G.M., Ahmad M.D., Chemin Y. Satellite surveillance of evaporative depletion across the Indus Basin [J]. Water Resources Research, 2002, 38(12): 1273
    Beljaars A.C.M., Holtslag A.A.M. Flux parameterization over land surfaces for atmospheric models [J]. J. Appl. Meteorol., 1991, 30: 327-341
    Brown K.W., Rosenberg N.J. A resistance model to predict evapotranspiration and its application to a sugarbeet field [J]. Agronomy Journal, 1973, 65: 341-347
    Brutsaert W. Evaporation into the Atmosphere: Theory, History and Applications [M]. New York: Springer, 1982
    Brutsaert W. Aspects of bulk atmospheric boundary layer similarity under free-convective conditions [J]. Review of Geophysics, 1999, 37: 439-451
    Burman R., Pochop L.O. Evaporation, evapotranspiration and climate data [M]. The Netherlands: Elsevier Science BV, 1994
    Campbell G.S., Norman J.M. An introduction to environmental biophysics [M]. New York: Springer, 1998
    Choudhury B.J., Monteith J.L. A four layer model for the heat budget of homogeneous land surfaces [J]. Q. J. R. Meteorol. Soc., 1988, 114: 373-398
    Gao Yanchun, Long Di, Li Zhao-Liang. Estimation of daily actual evapotranspiration from remotely sensed data under complex terrain over the upper Chao river basin in North China [J]. International Journal of Remote Sensing, 2008, 29(11): 3295-3315
    Griend A, A Van De, Gurney R J. Satellite remote sensing and energy balance modeling for water balance assessment (semi-) arid regions [A]. In: Simmersed I. Estimation of natural ground water recharge [C]. Dordrecht, the Netherlands: D Reidel Publishing company, 1988
    Gutman G, Ignatov V. The derivation of the green vegetation fraction from NOAA/AVHRR datafor use in numerical weather prediction models [J]. Remote Sensing, 1998, 19(8): 1533-1543
    Hatfield JL, Perrier A, Jackson RD. Estimation of evapotranspiration at one time-of-day using remotely sensed surface temperatures [J]. Agricultural Water Management, 1983, 7(1-3): 341-350
    H?gstr?m U. Non-dimensional wind and temperature profiles in the atmospheric surface layer: a re-evaluation [J]. Boundary-Layer Meteorol., 1988, 42: 55-78
    Jackson RD, Reginato RJ, Idso SB. Wheat canopy temperature: A practical tool for evaluating water requirements [J]. Water Resources Research, 1977, 13(3): 651-656
    Kader B.A., Yaglom A.M. Mean fields and fluctuation moments in unstably stratified turbulent boundary layers [J]. J. Fluid Mech., 1990, 212: 637-662
    Kustas W.P., Daughtry C.S.T. Estimation of the soil heat flux/net radiation ratio from spectral data [J]. Agric. For. Meteorol., 1989, 49: 205-223
    Liang Shunlin. Narrowband to broadband conversions of land surface albedo I: Algorithms [J]. Remote Sensing of Environment, 2000, 76(2): 213-238
    Massman W.J. Molecular diffusivities of Hg vapor in air, O2 and N2 near STP and the kinematic viscosity and the thermal diffusivity of air near STP [J]. Atmos. Environ., 1999, 33: 453-457
    Menenti M. Physical aspects and determination of evaporation in deserts applying remote sensing techniques [R]. Report 10 (Special Issue), Institute for Land and Water Management Research (ICW), the Netherlands, 1984
    Menenti M., Lorkeers A., Vissers M. An application of thematic mapper data in Tunisia: estimation of daily amplitude in near-surface soil temperature and discrimination on hypersaline soils [J]. ITC Jounal, 1986, l: 35-42
    Menenti M., Bastiaanssen W.G.M., Eick D. van. Determination of surface hemispherical reflectance with Thematic Mapper data [J]. Remote Sensing of Environment, 1989, 28: 327-337
    Menenti M., Bastiaanssen W.G.M., Eick D. van, et al. Linear relationships between surface reflectance and temperature and their application to map actual evaporation of groundwater [J]. Advances in Space Research, 1989, 9 (1): 165-176
    Menenti M., Choudhury B.J. Parametrization of land surface evapotranspiration using a location-dependent potential evapotranspiration and surface temperature range [A]. In: H. J. Bolle (Eds.). Exchange Processes at the Land Surface for a Range of Space and Time Scales [C]. Oxfordshire: IAHS Publ. 1993, (212): 561-568
    Monteith J.L. Principles of environmental physics [M]. London: Edward Arnold Press, 1973 Roerink G.J., Su Z., Menenti M. S-SEBI: A simple remote sensing algorithm to estimate the surface energy balance [A]. Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere [C], 2000, 25(2): 147-157
    Rosenberg N.J., Blad B.L., Verma S.B. Microclimate– the biological environment of plants (2nd Ed.) [M]. New York: John Wiley & Sons, 1983
    Seguin B, Itier B. Using midday surface temperature to estimate daily evaporation from satellite thermal IR data [J]. International Journal of Remote Sensing, 1983, 4(2): 371-383
    Su Z., Pelgrum H., Menenti M. Aggregation effects of surface heterogeneity in land surface processes [J]. Hydrological Earth System Science, 1999, 3(4): 549-563
    Su Z., Jacobs C. Advanced Earth Observation - Land Surface Climate [R]. Report USP-2, 01-02, Publications of the National Remote Sensing Board (BCRS), the Netherlands, 2001: 184
    Su Z. The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes [J]. Hydrology and Earth System Sciences, 2002, 6(1): 85-99
    Su Z., Jacobs C. ENVISAT: Actual Evaporation. BCRS Report 2001: USP - 2 Report 2001 01 - 02 [R]. Beleidscommissie Remote Sensing (BCRS), 2003
    Tasumi M., Allen R.G., Trezza R., et al. Use of SEBAL to assess the band width of crop coefficient curves in Idaho [J]. ASCE Journal of Irrigation and Drainage Engineering, 2005, 131(1): 94-109
    Van den Hurk B.J.J.M., Holtslag A.A.M. On the bulk parameterization of surface fluxes for various conditions and parameter ranges [J]. Boundary-Layer Meteorol., 1995, 82: 199-234
    阿布都瓦斯提?吾拉木,秦其明.地下水遥感监测研究进展[J].农业工程学报,2004,20(1):184– 188
    陈镜明.现用遥感蒸散模式中的一个重要缺点及改进[J].科学通报,1988,39(6):454– 457
    陈云浩,李晓兵,李京,等.陆面日蒸发散量计算的两层阻抗遥感模型[J].武汉大学学报(信息科学版),2005,30(12):1075– 1079
    陈乾,陈添宇.用NOAA卫星气象资料计算复杂地形下的流域蒸散[J].地理学报,1993,48(1):61– 69
    崔亚莉,徐映雪,邵景力,等.应用遥感方法研究黄河三角洲地表蒸发及其与下垫面关系[J].地学前缘,2005,12(特刊):159– 165
    崔树彬.关于生态环境需水量若干问题的探讨[J].中国水利,2001,(8):71– 74
    高彦春,龙笛.遥感蒸散发模型研究进展[J].遥感学报,2008,12(3):515– 528
    郭铌.植被指数及其研究进展[J].干旱气象,2003,21(4):71– 75
    郭晓寅,程国栋.遥感技术应用于地表面蒸散发的研究进展[J].地球科学进展,2004,19(1):107– 114
    何玲,莫兴国,汪志农.基于MODIS遥感数据计算无定河流域日蒸散[J].农业工程学报,2007,23(5):144– 149
    何延波,Su Z.,Jia L.,等.遥感数据支持下不同地表覆盖的区域蒸散[J].应用生态学报,2007,18(2):288– 296
    金晓媚,万力,梁继运.水均衡法验证蒸散量计算的可靠性——以张掖盆地为例[J].现代地质,2008,22(2):299– 303
    雷志栋,杨诗秀,谢森传.土壤水动力学[M].北京:清华大学出版社,1988
    李云玲.基于水资源合理配置的黑河下游生态恢复研究:[博士学位论文].南京:河海大学,2005
    李强坤,胡亚伟,丁宪宝,等.西北干旱地区绿洲生态需水及其量化方法研究[J].资源环境与工程,2007,21(5):558– 561
    刘玉洁,杨忠东. MODIS遥感信息处理原理与算法[M].北京:科学出版社,2001
    蔺文静,董华,王贵玲,等.河北平原区域蒸发蒸腾量遥感估算[J].国土资源遥感,2008,(1):86– 90
    卢娜.基于遥感的鄂尔多斯盆地蒸发量计算及植被指数分析:[硕士学位论文].北京:中国地质大学(北京),2006
    卢娜,万力.基于RS的鄂尔多斯北部盆地地表蒸发量的计算[J].地质通报,2008,27(8):1165– 1167
    马耀明,王介民,Menenti M.,等.卫星遥感结合地面观测估算非均匀地表区域能量通量[J].气象学报,1999,57(2):180– 189
    潘卫华,徐涵秋,李文,等.卫星遥感在东南沿海区域蒸散(发)量计算上的反演[J].中国农业气象,2007,28(2):154– 158
    尚松浩,毛晓敏,雷志栋,等.计算潜水蒸发系数的反Logistic公式[J].灌溉排水,1999,18(2):18– 21
    孙丹峰.土地利用/覆被遥感分析[M].北京:中国大地出版社,2006
    苏中波,张廷,马耀明,等.青藏高原地区能量水分循环:地表能量平衡和湍流热通量[J].地球科学进展,2006,21(12):1224– 1236
    田庆久,闵祥军.植被指数研究进展[J].地球科学进展,1998,13(4):327– 333
    田国良,郑柯,李付琴,等.用NOAA / AVHRR数字图像和地面气象站资料估算麦田的蒸
    散和土壤水分[A].黄河流域典型地区遥感动态研究[C].北京:科学出版社,1990
    汤国安,刘学军,闾国年.数字高程模型及地学分析的原理与方法[M].北京:科学出版社,2005
    王正兴,刘闯,陈文波,等. MODIS增强型植被指数EVI与NDVI初步比较[J].武汉大学学报,2006,31(5):407– 410
    王芳,梁瑞驹,杨小柳,等.中国西北地区生态需水研究(1)一一干早半干旱地区生态需水理论分析[J].自然资源学报,2002,17(1):1– 8
    王根绪,程国栋.干旱内陆流域生态需水量及其估算——以黑河流域为例[J].中国沙漠,2002,22(2):129– 134
    吴炳方,熊隽,闫娜娜,等.基于遥感的区域蒸散量监测方法—ETWatch [J].水科学进展,2008,19(5):671– 678
    谢贤群.遥感瞬时作物表面温度估算农田全日蒸散总量[J].环境遥感,1991,6(4):253– 259
    杨志峰,崔保山,刘静玲,等.生态环境需水量理论、方法与实践[M].北京:科学出版社,2003
    詹志明,冯兆东,秦其明.陇西黄土高原陆面蒸散的遥感研究[J].地理与地理信息科学,2004,20(1):16– 19
    张长春,王晓燕,邵景力.利用NOAA数据估算黄河三角洲区域蒸散量[J].资源科学,2005,27(1):86– 91
    张长春,王光谦,魏加华,等.联合TM和NOAA数据研究黄河三角洲地表蒸发(散)量[J].清华大学学报(自然科学版),2005,45(9):1184– 1188
    张仁华,孙晓敏,朱治林,等.以微分热惯量为基础的地表蒸发全遥感信息模型及在甘肃沙坡头地区的验正[J].中国科学(D辑),2002,32(12):1041– 1050
    张会平,杨农,刘少峰,等.数字高程模型(DEM)在构造地貌研究中的应用新进展[J].地质通报,2006,25(6):660– 669
    张鑫,蔡焕杰.区域生态环境需水量与水资源合理配置[M].杨凌:西北农林科技大学出版社,2007
    朱学愚,钱孝星.地下水水文学[M].北京:中国环境科学出版社,2005

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