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Using the Soil and Water Assessment Tool to develop a LiDAR-based index of the erosion regulation ecosystem service

机译:利用土壤和水分评估工具开发基于激光的侵蚀调节生态系统服务指数

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Maps of ecosystem services are becoming increasingly useful for reporting on the potential impacts of human activity on the environment. However, interactions in watersheds are complex, and mapping hydrological ecosystem services (HES) requires indicators which accurately measure underlying processes. The main objective of this study was to take advantage of the Soil and Water Assessment Tool (SWAT) and Light detection and ranging (LiDAR) data to map the erosion regulation service for a managed boreal forest watershed. To do so, SWAT and partial least-squares (PLS) regression were used to select explanatory variables for sediment yield. Variables of importance in projection (VIP) with a score > 1 were selected to develop LiDAR-based ecological indicators. Four categories of variables were identified as VIP from the PLS: (i) climate: annual precipitation, (ii) land use: forest, cutovers; (iii) land use patterns: cutover patch cohesion index, and (iv) morphometric: main channel length, channel length and sub-watershed area. The height of the 95th percentile of LiDAR returns (p95) < 5 m provided the most accurate spatial representation of cutovers and the optimal cutover patch cohesion index. Other morphometrics were obtained from a LiDAR-based digital terrain model. Explanatory variables for sediment yield were combined in a sediment erosion control (SEC) index, except for yearly average precipitation because the SEC index is not actually used as a temporal index. As expected, a negative relationship was found between sediment yield and SEC index rankings for the 2006-2015 period (Spearman, rho = -0.6, p < 0.05). Moreover, the overall agreement between SWAT and SEC index classes was 87% for 31 sub-watersheds. The study provides a list of relevant explanatory variables for modelling sediment yield in a boreal forest watershed where timber harvest activities occur. It also demonstrates the use of LiDAR data for deriving an index of the erosion regulation ecosystem service in a proxy-based approach as it had not been demonstrated previously at the watershed level. The validation method applied here fills a gap in ecosystem services mapping that could benefit studies in other watershed contexts.
机译:生态系统服务地图在报告人类活动对环境的潜在影响方面正变得越来越有用。然而,流域内的相互作用是复杂的,绘制水文生态系统服务(HES)图需要能够准确测量潜在过程的指标。本研究的主要目的是利用土壤和水评估工具(SWAT)和光探测和测距(LiDAR)数据,为管理的北方森林流域绘制侵蚀治理服务地图。为此,使用SWAT和偏最小二乘(PLS)回归选择产沙量的解释变量。选择得分>1的重要投影变量(VIP)来开发基于激光雷达的生态指标。从PLS中确定四类变量为VIP:(i)气候:年降水量,(ii)土地利用:森林、砍伐;(iii)土地利用模式:割接斑块凝聚力指数,以及(iv)形态测量:主河道长度、河道长度和次级流域面积。激光雷达回波第95百分位(p95)<5m的高度提供了最准确的切割空间表示和最佳切割斑块内聚指数。其他形态测量数据来自基于激光雷达的数字地形模型。产沙量的解释变量被合并到泥沙侵蚀控制(SEC)指数中,但年平均降水量除外,因为SEC指数实际上没有用作时间指数。正如预期的那样,2006-2015年期间,泥沙产量与SEC指数排名之间存在负相关关系(斯皮尔曼,rho=-0.6,p<0.05)。此外,对于31个次级流域,SWAT和SEC指数等级之间的总体一致性为87%。该研究提供了一系列相关的解释变量,用于模拟发生木材采伐活动的北方森林流域的产沙量。它还演示了如何使用激光雷达数据,以基于代理的方法推导侵蚀调节生态系统服务指数,因为之前在流域层面上没有演示过这种方法。这里采用的验证方法填补了生态系统服务制图的空白,这可能有助于其他流域环境的研究。

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