Effect of an environmental flow on vegetation growth and health using ground and remote sensing metrics
Effect of an environmental flow on vegetation growth and health using ground and remote sensing metrics
复制标题
DOI：
10.1002/hyp.13689
复制
发表时间：
2020-02
影响因子：
3.2
通讯作者：
M. Gómez‐Sapiens;C. Jarchow;K. Flessa;P. Shafroth;E. Glenn;P. Nagler
中科院分区：
文献类型：
--
作者：
M. Gómez‐Sapiens;C. Jarchow;K. Flessa;P. Shafroth;E. Glenn;P. Nagler
了解河流环境流量输送的有效性需要监测植被。监测数据通常在多个空间尺度上收集。对于河岸植被，光学遥感方法可以估算河岸走廊尺度上的生长响应，而基于野外的测量可以量化物种组成；但是，在规划资源有限的监测方案时，必须了解这些不同措施在多大程度上是重复或互补的。在这项研究中，我们分析了科罗拉多河三角洲河岸植被的生长对实验脉冲流的响应。我们的目标是比较基于地面的植被结构和组成测量与基于卫星的Landsat辐射变量，如归一化植被指数（NDVI）。我们在2014年春季将1.318亿立方米（mcm）的水作为脉冲流和38.4 mcm作为基流输送到河道后的21个断面进行了比较。到2015年10月，植被覆盖增加了14%，NDVI增加了0.02(15%)，这两个变量在2016年10月都恢复到脉冲前的流量值。观察到的植被结构和组成的变化在第二年之后不再持续。2014年10月和2015年10月植被覆盖度增幅最大的是芦苇（Arundo donax）和芦苇（Phragmites australis）、香蒲（Typha domingensis）和草本植物等对额外水分反应迅速的物种。优势灌木柽柳（Tamarix spp）和箭草（Pluchea sericea）均表现出不同程度的覆盖度增长，原生乔木（水杨科）的覆盖度增长较低（1%）。NDVI与植被覆盖度的密切关系表明，NDVI适合于在河岸走廊尺度上检测变化，但需要与地面数据相补充，以确定不同物种对观测趋势的贡献。
Understanding the effectiveness of environmental flow deliveries along rivers requires monitoring vegetation. Monitoring data are often collected at multiple spatial scales. For riparian vegetation, optical remote sensing methods can estimate growth responses at the riparian corridor scale, and field‐based measures can quantify species composition; however, the extent to which these different measures are duplicative or complementary is important to understand when planning monitoring programmes with limited resources. In this study, we analysed riparian vegetation growth in the delta of the Colorado River in response to an experimental pulse flow. Our goal was to compare ground‐based measurements of vegetation structure and composition with satellite‐based Landsat radiometric variables, such as the normalized difference vegetation index (NDVI). We made this comparison in 21 transects following the delivery of 131.8 million cubic meters (mcm) of water in the stream channel during the spring of 2014 as a pulse flow and 38.4 mcm as base flows. Vegetation cover increased 14% and NDVI increased 0.02 (15%) by October 2015, and both variables returned to pre‐pulse flow values in October 2016. Observed changes in vegetation structure and composition did not persist after the second year. The highest increase in vegetation cover in October 2014 and October 2015 resulted from species that could respond rapidly to additional water such as reeds (Arundo donax and Phragmites australis), cattail (Typha domingensis), and herbaceous plants. Dominant shrubs, saltcedar (Tamarix spp.) and arrowweed (Pluchea sericea), both indicative of nonrestored habitats showed variable increases in cover, and native trees (Salicaceae family) presented low increases (1%). The strong NDVI–vegetation cover relationship indicates that NDVI is appropriate to detect changes at the riparian corridor scale but needs to be complemented with ground data to determine the contributions by different species to the observed trends.