海流兔河流域地下水对植被指数分布的影响研究
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摘要
海流兔河流域属于我国西北地区典型的半干旱流域，由于降水量稀少，蒸发强烈，当地植被演替受到水资源、特别是地下水资源时空分布格局的控制，其变迁演替和地下水埋深之间具有很强的相关性。浅层地下水与植被分布特征之间的耦合关系，是生态水文地质学的重要研究内容。这一关系的确立，可以为缓和西北地区开发利用地下水与保护生态环境之间的矛盾提供一定的科学依据。本文借助于遥感信息，以归一化植被指数（Normalized Difference Vegetation Index, NDVI）作为研究区植被生态的标志，对其与地下水埋深之间的关系进行了定量研究，明确了海流兔河流域植被指数对地下水埋深的依赖方式和依赖程度。
为获得全面的地下水位埋深数据，针对全区观测资料较少的难题，提出了一种设计、优化地下水位统测网的方法。首先通过密网格数值模拟获得参考地下水位等值线图，根据设计的若干水位统测方案在模拟结果中进行水位采样，演示统测行为，用Kriging插值法生成地下水位等值线图评价插值误差，从中优选出精度高且投入少的方案作为实施方案。这种优化的水位统测方法与历史资料相结合，获得了研究区地下水埋深的大样本数据。
综合利用TM NDVI和SPOT VEGETATION遥感数据，对研究区NDVI均值的年际、年内季节性变化及影响因素进行了分析。研究区NDVI平均值年际变化不强，且与前一年降水量有较强的正相关关系。 NDVI的季节性变化与干燥度和温度分别呈较强的负相关和正相关。
对海流兔河流域NDVI和地下水埋深的空间分布特征进行了统计分析，结果表明两者均呈偏态分布，且偏斜系数均为正值，右侧有拖尾现象。不同地下水埋深区间的NDVI频率分布特征与Gamma分布具有较好的一致性。
深入探讨了NDVI均值随地下水埋深的变化，证明NDVI平均值与地下水埋深成相关关系，可以近似用负指数函数描述。各种NDVI统计特征值随地下水埋深的变化均指示埋深10m为一个拐点。当地下水埋深超过这一范围时，植被的覆盖度和多样性均显著降低，不再与地下水紧密相关。在此基础上，基于NDVI值进一步对研究区植被类型进行了划分，研究了当地下水埋深小于10m时，不同类型植被NDVI与地下水埋深空间分布的相关性。随着地下水埋深的增加，灌丛植被NDVI值呈现明显的线性下降趋势，两者相关系数达0.85以上；草地植被由于根系较浅（一般为0.5m），基本依赖于大气降水，与地下水埋深关系不大。由于受到人工灌溉的影响，农田地区的植被与地下水埋深的相关性分析比较复杂，旱柳和小叶杨是乔木的主要物种，由于它们的根系均具有较强的穿透性，因而可以吸收埋深较深的地下水（7-8m）。
为验证上述NDVI与地下水埋深关系在实际景观上的表现，特选择3条样带——分别位于上、中、下游并贯穿流域两侧分水岭，对地形、NDVI、地下水位联合剖面进行分析。剖面上的植被景观变化可以用前述研究成果解释。在地下水埋深较浅地区，NDVI值明显上升；当地下水位埋深增加时，NDVI值下降；下游河谷两岸由于深切地貌地下水埋深均较大，NDVI值很低，但是部分地区由于种植有人工作物，受到人工灌溉的影响，NDVI值出现正异常。
海流兔河流域NDVI与地下水埋深之间的量化关系与前人在额济纳绿洲和银川平原的研究结果有所不同。在额济纳绿洲和银川平原存在某个最有利于植被的埋深，但在海流兔河流域没有这种优势埋深。其原因可能与气象、土壤、水文地质等条件有关。
植被分布会影响陆面蒸散，反过来又会影响地下水。因此，植被、地下水与陆面蒸散之间是耦合关系。本文对此进行了初步的模拟研究。把NDVI与地下水埋深、NDVI与蒸散强度的关系近似描述为线性函数，利用Processing Modflow模拟地下水，并对Recharge和Evapotranspiration模块进行特殊处理，初步建立了海流兔河流域地下水-植被-蒸散的耦合模型，对NDVI的概率平均分布状态进行了反演。
全文对海流兔河流域NDVI分布与地下水埋深的关系进行了定量描述，尝试建立了地下水-植被-蒸散的耦合模型，丰富了生态水文地质学的研究内容和定量研究方法，对于生态水文学的拓展具有一定的理论意义。
Hailiutu River Catchment is a typical semi-arid region in northwest China. Due to the lowprecipitation and high evaporation, the local vegetation is controlled by spatial and temporaldistribution of water resources, especially the groundwater resources. The relationshipbetween shallow groundwater and vegetation becomes an important problem of EcologicalHydrogeology. The solution can be a scientific basis to ease the conflict between the utilizationof groundwater and environment protection. With the application of remote sensing technology,this article used Normalized Difference Vegetation Index (NDVI) as a symbol of vegetation,studied the quantitative relationship between NDVI and depth to groundwater table (DWT),defined the dependent pattern and level of vegetation index to groundwater in Hailiutu RiverCatchment.
For collecting the DWT data comprehensively, this article proposed a method to designand optimize groundwater level monitoring networks. This method is also appropriate forother ungauged area. Firstly, the referential water table distribution was generated through arough numerical simulation with dense meshes. Secondly, the groundwater level was sampledfrom the modeling results at the nodes on an initially designed network, as a monitoring test.Then, a new contour of groundwater level was obtained with the monitoring test using Krigingmethod and the interpolation error was calculated through comparison with the referentialwater table distribution. With consideration of both the precision and investment, an optimalscheme among the alternative observation networks was chosen. Combined with the previousdata, this optimal method collected the accurate samples of DWT in Hailiutu River Catchment.
Combined TM NDVI with SPOT VEGETATION data, interannual and seasonalvariations of average NDVI, with the influencing factors were analyzed. The results showedthat interannual variation of NDVI was not strong and may have positive correlation withprecipitation of the last year. The seasonal variation of NDVI was negatively correlated withdrought index and positively correlated with temperature.
After the statistical analysis of NDVI and DWT spatial distribution, it indicated that bothof them showed the skewed pattern of frequency distribution, and the coefficients of skewnesswere positive. The statistical distribution of NDVI for different intervals of DWT was Gammadistribution.
The frequency distribution curves of NDVI with respect to different DWT were obtained.The statistical distributions of NDVI values at different DWT intervals indicated that higher vegetation coverage and more plant diversity exist at places of shallow groundwater. Both themean and the standard deviation of NDVI values decreased with the increase of groundwaterdepth when DWT was less than10m. Beyond that depth, a low level of vegetation coverageand diversity was maintained. Comparisons of different sub-areas within the region withdifferent dominant species showed that the NDVI of shrubs was sensitive to DWT. In contrast,NDVI of herbs was not significantly influenced by DWT. The relationship between NDVI andgroundwater depth in farmlands could not be reliably determined because of disturbance byhuman activities. S. matsudana and Populus simonii Carr are the dominant species in grovesof trees, and they can access deep groundwater (7-8m) with their deeply extending roots.
For confirming the relationship between NDVI and DWT,3DEM-NDVI-DWT profiles,which locating upstream, midstream and downstream of Hailiutu River Catchment andstretching across the whole district from west to east were chosen. The results verified theconclusion above-the response of vegetation distribution on increase of DWT was positivecorrelation, except the area with manual irrigation.
However, the dependency of vegetation on groundwater was significantly different in thearid Ejina area and Yinchuan Plain in China. Both in Ejina area and Yinchuan Plain, a suitableDWT interval could be found for the vegetation growth, but not in Hailiutu River Catchment.These differences may attribute to multiple factors such as climate, soil cover andhydrogeology.
The distribution of vegetation can influence the land surface evapotranspiration(ET), andalso be effective to groundwater. As a result, a coupled model of DWT, NDVI and ET wasbuilt. In this model, the relationship between NDVI and DWT, NDVI and ET were presentedas linear formula respectively. The software of Processing Modflow was used to simulate thegroundwater. The Recharge and Evapotranspiration packages were managed specially basedon the linear formula. The model inverted the distribution of average NDVI frequency.
This article made a quantitative description of the relationship between NDVI and DWTin Hailiutu River Catchment, built a coupled model of DWT-NDVI-ET. We concluded that thisresearch may significantly improve the contents and methodology of Ecological Hydrogeology,and will provide theoretical significance to the development of Ecohydrology.
为获得全面的地下水位埋深数据，针对全区观测资料较少的难题，提出了一种设计、优化地下水位统测网的方法。首先通过密网格数值模拟获得参考地下水位等值线图，根据设计的若干水位统测方案在模拟结果中进行水位采样，演示统测行为，用Kriging插值法生成地下水位等值线图评价插值误差，从中优选出精度高且投入少的方案作为实施方案。这种优化的水位统测方法与历史资料相结合，获得了研究区地下水埋深的大样本数据。
综合利用TM NDVI和SPOT VEGETATION遥感数据，对研究区NDVI均值的年际、年内季节性变化及影响因素进行了分析。研究区NDVI平均值年际变化不强，且与前一年降水量有较强的正相关关系。 NDVI的季节性变化与干燥度和温度分别呈较强的负相关和正相关。
对海流兔河流域NDVI和地下水埋深的空间分布特征进行了统计分析，结果表明两者均呈偏态分布，且偏斜系数均为正值，右侧有拖尾现象。不同地下水埋深区间的NDVI频率分布特征与Gamma分布具有较好的一致性。
深入探讨了NDVI均值随地下水埋深的变化，证明NDVI平均值与地下水埋深成相关关系，可以近似用负指数函数描述。各种NDVI统计特征值随地下水埋深的变化均指示埋深10m为一个拐点。当地下水埋深超过这一范围时，植被的覆盖度和多样性均显著降低，不再与地下水紧密相关。在此基础上，基于NDVI值进一步对研究区植被类型进行了划分，研究了当地下水埋深小于10m时，不同类型植被NDVI与地下水埋深空间分布的相关性。随着地下水埋深的增加，灌丛植被NDVI值呈现明显的线性下降趋势，两者相关系数达0.85以上；草地植被由于根系较浅（一般为0.5m），基本依赖于大气降水，与地下水埋深关系不大。由于受到人工灌溉的影响，农田地区的植被与地下水埋深的相关性分析比较复杂，旱柳和小叶杨是乔木的主要物种，由于它们的根系均具有较强的穿透性，因而可以吸收埋深较深的地下水（7-8m）。
为验证上述NDVI与地下水埋深关系在实际景观上的表现，特选择3条样带——分别位于上、中、下游并贯穿流域两侧分水岭，对地形、NDVI、地下水位联合剖面进行分析。剖面上的植被景观变化可以用前述研究成果解释。在地下水埋深较浅地区，NDVI值明显上升；当地下水位埋深增加时，NDVI值下降；下游河谷两岸由于深切地貌地下水埋深均较大，NDVI值很低，但是部分地区由于种植有人工作物，受到人工灌溉的影响，NDVI值出现正异常。
海流兔河流域NDVI与地下水埋深之间的量化关系与前人在额济纳绿洲和银川平原的研究结果有所不同。在额济纳绿洲和银川平原存在某个最有利于植被的埋深，但在海流兔河流域没有这种优势埋深。其原因可能与气象、土壤、水文地质等条件有关。
植被分布会影响陆面蒸散，反过来又会影响地下水。因此，植被、地下水与陆面蒸散之间是耦合关系。本文对此进行了初步的模拟研究。把NDVI与地下水埋深、NDVI与蒸散强度的关系近似描述为线性函数，利用Processing Modflow模拟地下水，并对Recharge和Evapotranspiration模块进行特殊处理，初步建立了海流兔河流域地下水-植被-蒸散的耦合模型，对NDVI的概率平均分布状态进行了反演。
全文对海流兔河流域NDVI分布与地下水埋深的关系进行了定量描述，尝试建立了地下水-植被-蒸散的耦合模型，丰富了生态水文地质学的研究内容和定量研究方法，对于生态水文学的拓展具有一定的理论意义。
Hailiutu River Catchment is a typical semi-arid region in northwest China. Due to the lowprecipitation and high evaporation, the local vegetation is controlled by spatial and temporaldistribution of water resources, especially the groundwater resources. The relationshipbetween shallow groundwater and vegetation becomes an important problem of EcologicalHydrogeology. The solution can be a scientific basis to ease the conflict between the utilizationof groundwater and environment protection. With the application of remote sensing technology,this article used Normalized Difference Vegetation Index (NDVI) as a symbol of vegetation,studied the quantitative relationship between NDVI and depth to groundwater table (DWT),defined the dependent pattern and level of vegetation index to groundwater in Hailiutu RiverCatchment.
For collecting the DWT data comprehensively, this article proposed a method to designand optimize groundwater level monitoring networks. This method is also appropriate forother ungauged area. Firstly, the referential water table distribution was generated through arough numerical simulation with dense meshes. Secondly, the groundwater level was sampledfrom the modeling results at the nodes on an initially designed network, as a monitoring test.Then, a new contour of groundwater level was obtained with the monitoring test using Krigingmethod and the interpolation error was calculated through comparison with the referentialwater table distribution. With consideration of both the precision and investment, an optimalscheme among the alternative observation networks was chosen. Combined with the previousdata, this optimal method collected the accurate samples of DWT in Hailiutu River Catchment.
Combined TM NDVI with SPOT VEGETATION data, interannual and seasonalvariations of average NDVI, with the influencing factors were analyzed. The results showedthat interannual variation of NDVI was not strong and may have positive correlation withprecipitation of the last year. The seasonal variation of NDVI was negatively correlated withdrought index and positively correlated with temperature.
After the statistical analysis of NDVI and DWT spatial distribution, it indicated that bothof them showed the skewed pattern of frequency distribution, and the coefficients of skewnesswere positive. The statistical distribution of NDVI for different intervals of DWT was Gammadistribution.
The frequency distribution curves of NDVI with respect to different DWT were obtained.The statistical distributions of NDVI values at different DWT intervals indicated that higher vegetation coverage and more plant diversity exist at places of shallow groundwater. Both themean and the standard deviation of NDVI values decreased with the increase of groundwaterdepth when DWT was less than10m. Beyond that depth, a low level of vegetation coverageand diversity was maintained. Comparisons of different sub-areas within the region withdifferent dominant species showed that the NDVI of shrubs was sensitive to DWT. In contrast,NDVI of herbs was not significantly influenced by DWT. The relationship between NDVI andgroundwater depth in farmlands could not be reliably determined because of disturbance byhuman activities. S. matsudana and Populus simonii Carr are the dominant species in grovesof trees, and they can access deep groundwater (7-8m) with their deeply extending roots.
For confirming the relationship between NDVI and DWT,3DEM-NDVI-DWT profiles,which locating upstream, midstream and downstream of Hailiutu River Catchment andstretching across the whole district from west to east were chosen. The results verified theconclusion above-the response of vegetation distribution on increase of DWT was positivecorrelation, except the area with manual irrigation.
However, the dependency of vegetation on groundwater was significantly different in thearid Ejina area and Yinchuan Plain in China. Both in Ejina area and Yinchuan Plain, a suitableDWT interval could be found for the vegetation growth, but not in Hailiutu River Catchment.These differences may attribute to multiple factors such as climate, soil cover andhydrogeology.
The distribution of vegetation can influence the land surface evapotranspiration(ET), andalso be effective to groundwater. As a result, a coupled model of DWT, NDVI and ET wasbuilt. In this model, the relationship between NDVI and DWT, NDVI and ET were presentedas linear formula respectively. The software of Processing Modflow was used to simulate thegroundwater. The Recharge and Evapotranspiration packages were managed specially basedon the linear formula. The model inverted the distribution of average NDVI frequency.
This article made a quantitative description of the relationship between NDVI and DWTin Hailiutu River Catchment, built a coupled model of DWT-NDVI-ET. We concluded that thisresearch may significantly improve the contents and methodology of Ecological Hydrogeology,and will provide theoretical significance to the development of Ecohydrology.
引文
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