当前位置: X-MOL 学术Wetlands › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Predictive Mapping of Solute‐rich Wetlands in the Canadian Prairie Pothole Region Through High‐resolution Digital Elevation Model Analyses
Wetlands ( IF 2 ) Pub Date : 2021-03-08 , DOI: 10.1007/s13157-021-01436-3
Jeremy Kiss , Angela Bedard-Haughn

Prairie Pothole Region wetlands are integral in reducing nutrient mobility in prairie watersheds. Wetland soil CaCO3 content likely plays an important role in wetland phosphorus retention capacity. Accurate predictions of the spatial distributions of wetlands with CaCO3-enriched soils would allow for further study on these relationships and prioritized wetland conservation efforts to encourage this ecosystem service. Solute accumulations (including CaCO3) within wetlands are largely determined by the wetland’s topographic position and relationship with groundwater. These characteristics were estimated by predicting spill channel connections between wetlands using LiDAR-derived digital elevation models. Spatial distributions of solute-rich wetlands were predicted with a simple decision tree model that predicts wetlands as either fresh or solute-rich based on approximated hydrologic characteristics (Strahler order and terminal status) determined from the predicted active spill channel networks. The model was trained and tested using measurements of wetland pond water and soil electrical conductivity (i.e., solute-richness) in three study areas within the Saskatchewan Prairie Pothole Region. The model achieved acceptable predictive accuracies based on training and independent validation tests. The proposed methodologies could be incorporated into more complex multivariate models for the purposes of predictive soil mapping or hydrologic studies in the Prairie Pothole Region.



中文翻译:

高分辨率数字高程模型分析预测加拿大大草原坑洼地区溶质丰富的湿地

草原坑洼地湿地是减少大草原流域养分流动性不可或缺的组成部分。湿地土壤CaCO 3含量可能在湿地磷保持能力中起重要作用。富含CaCO 3的土壤对湿地空间分布的准确预测将有助于进一步研究这些关系,并优先开展湿地保护工作,以鼓励这种生态系统服务。溶质堆积物(包括CaCO 3)在很大程度上取决于湿地的地形位置以及与地下水的关系。通过使用LiDAR衍生的数字高程模型预测湿地之间的溢流通道连接来估算这些特征。利用简单的决策树模型来预测富含溶质的湿地的空间分布,该模型基于根据预测的活动溢洪道网络确定的近似水文特征(Strahler阶和末端状态)将湿地预测为新鲜的或富含溶质的湿地。在萨斯喀彻温省草原坑洼地带的三个研究区域中,通过测量湿地池塘水和土壤电导率(即富溶质)对模型进行了训练和测试。该模型基于训练和独立验证测试获得了可接受的预测准确性。

更新日期:2021-03-08
down
wechat
bug