Simultaneous Heat and Water (SHAW) input and outputs for four parameterizations of upland deciduous boreal forest at Bonanza Creek, Alaska 2003-2015

This dataset provides inputs and outputs for the Simultaneous Heat and Water (SHAW) model implemented at the upland birch site (labeled UP1A) at the Bonanza Creek Long Term Ecological Research (BNZ LTER) site. The purpose of this study was to parameterize SHAW for upland boreal deciduous forest. Input climate data includes air temperature, precipitation, wind speed, relative humidity, and downward solar radiation, and was derived from previously published data from the BNZ LTER. Model parameters describing plant structural and water use characteristics were obtained from vegetation surveys at the BNZ LTER and from relevant scientific literature. Soil texture model parameters were also obtained from data published through the BNZ LTER. A Generalized Likelihood Uncertainty Estimation (GLUE) approach was used to assess soil hydraulic parameters. Four sets of soil hydraulic parameters are identified. These sets respectively minimize the root mean squared error of volumetric water content at 50 centimeter (cm) (expanded data), root mean squared error of soil temperature at 1 meter (m) (T1_RMSE) model performance dependence on interannual variability (Case 3), and two sets that minimize the dependence of volumetric water content RMSE on temperature (CSMP_warm) and precipitation (CSMP_wet). The first set of parameter inputs and outputs are uploaded as individual files; inputs and outputs for the other cases are provided as compressed directories with model inputs and outputs for their respective parameters. These data are published in support of the manuscript: Marshall, A.M.; Link, T.E., Flerchinger, G.N., Nicolsky, D.J., Lucash, M.S. (2021). Ecohydrological modeling in a deciduous boreal forest: Model evaluation for application in non-stationary climates. Manuscript submitted to Hydrological Processes.本数据集为博纳泽溪长期生态研究（Bonanza Creek Long Term Ecological Research, BNZ LTER）站点内高地桦木样地（标记为UP1A）所部署的水热耦合（Simultaneous Heat and Water, SHAW）模型提供输入与输出数据。本研究旨在为寒带高地落叶阔叶林率定SHAW模型的参数。输入的气候数据涵盖气温、降水量、风速、相对湿度与下行太阳辐射，数据取自BNZ LTER已公开发表的研究成果。描述植物结构与水分利用特性的模型参数，取自BNZ LTER的植被调查数据及相关学术文献；土壤质地模型参数同样来自BNZ LTER发布的公开数据集。研究采用广义似然不确定性估计（Generalized Likelihood Uncertainty Estimation, GLUE）方法对土壤水力参数开展评估，最终确定四组土壤水力参数方案：第一组最小化50厘米深度体积含水量的均方根误差（root mean squared error, RMSE，拓展数据集），第二组最小化1米深度土壤温度的均方根误差（T1_RMSE），第三组考察模型性能对年际变率的依赖性（案例3），剩余两组分别最小化体积含水量RMSE对温度（CSMP_warm）与降水量（CSMP_wet）的依赖性。第一组参数对应的模型输入与输出数据以独立文件形式上传；其余案例的输入与输出数据则以压缩目录形式提供，包含对应参数集的模型输入与输出内容。本数据集的发布旨在支撑以下学术论文：Marshall, A.M.; Link, T.E., Flerchinger, G.N., Nicolsky, D.J., Lucash, M.S. (2021). 寒带落叶阔叶林生态水文建模：非平稳气候下的应用模型评估。该论文已投稿至《水文过程（Hydrological Processes）》期刊。