Saddle catchment Distributed Hydrology Soil Vegetation Model Simulation (DHSVM) precipitation and transpiration variable outputs (precipitation, total, potential and actual evapotranspiration), 2 meter, 2000-2019.

The Saddle Catchment of the Niwot Ridge LTER is a densely observed, high elevation site that is ideal for hydrological model simulation and calibration. The files produced are the result of a calibration of the Distributed Hydrology Soil Vegetation model (DHSVM) using observationally based states and forcings. Input state files of vegetation, soil properties, shading, and elevation were generated using ground and satellite observations, which, in the case of coarse-resolution or point scale observations, were then interpolated to match the high resolution of the model (2-meter grid cells). Temporally continuous meteorological forcings at the hourly time-step were used to force the model to produce an hourly simulation of the surface and subsurface hydrology within the Saddle catchment. DHSVM was calibrated to effectively reproduce the annual cycle (r^2) and total volume (percent bias) of observed runoff using observations of streamflow at the outflow pour point of the Saddle Catchment from 2001-2019. Calibrated parameters include the lateral conductivity of soil types, exponential decrease of soil conductivity, snow roughness, the snow melting temperature threshold, and the vertical conductivity of the soils. The resulting simulation generated spatially distributed time series of the snow water equivalent, snow melt, precipitation, total evapotranspiration, potential evapotranspiration, and a time-series of the total runoff generated at the outflow pour-point of the Saddle catchment. This data package contains the spatially distributed time series of precipitation, total evapotranspiration and actual evapotranspiration Outputs of snow water equivalent, snow melt, and runoff, as well as the model configuration file, as well as model inputs are archived separately on the Environmental Data Initiative.尼沃特岭长期生态研究站（Niwot Ridge LTER）的鞍部集水区是一处观测密集的高海拔站点，非常适合开展水文模型模拟与参数率定工作。本次生成的数据集文件，是基于观测得到的模型状态与强迫数据，对分布式水文土壤植被模型（Distributed Hydrology Soil Vegetation Model, DHSVM）进行参数率定后的结果。植被、土壤属性、遮蔽情况以及高程的输入状态文件，均通过地面与卫星观测数据生成；对于低分辨率或单点观测数据，则通过插值处理使其匹配模型的2米网格单元高分辨率。本研究采用逐小时时间步长的连续气象强迫数据驱动模型，对鞍部集水区的地表与地下水文过程进行逐小时模拟。研究基于2001-2019年鞍部集水区出口断面的径流观测数据，对DHSVM进行参数率定，使其能够有效复现观测径流的年循环特征（决定系数r²）与总径流量（百分比偏差）。本次率定的参数包括不同土壤类型的侧向导水率、土壤导水率的指数衰减系数、积雪粗糙度、融雪温度阈值以及土壤垂直导水率。模拟结果生成了积雪水当量、融雪量、降水量、总蒸散发量、潜在蒸散发量的空间分布时间序列，以及鞍部集水区出口断面的总径流量时间序列。本数据包包含降水量、总蒸散发量与实际蒸散发量的空间分布时间序列，积雪水当量、融雪量与径流量的模拟输出结果，以及模型配置文件；模型输入数据则单独归档于环境数据倡议（Environmental Data Initiative）平台。