Developing a Stochastic Hydrological Model for Informing Lake Water Level Drawdown Management
This data release consists of four datasets which were used for evaluating winter drawdown (WD) lakes to follow the Massachusetts general WD guidelines. The first dataset ("Water level observations.csv") provides water level monitoring data of 21 (18 WD and 3 non-WD) recreational lakes in Massachusetts from 2014 to 2018. The water levels were measured by paired nonvented pressure transducers (HOBO U20L-01) and processed by ContDataQC package to remove potential inaccurate observations. For better comparison between lakes, the water level was relativized to each lake's normal pool level. This dataset was used for understanding the hydrology of WD and non-WD lakes and validating the hydrological model that we developed for WD lakes. Details of the hydrological model were described in the software release (https://doi.org/10.5066/P9C8BVY2). The second dataset ("Water level simulations.csv") is the hydrological model simulated daily water level (relative to each lake's normal pool level) time series of the WD lakes from the first dataset (15 lakes, 2014-2018). To validate the applicability of the model on simulating water levels in WD lakes, the actual drawdown rules were set in the model to recreate the historical water levels and compare with the in-situ observations in the first dataset. The third dataset ("Guideline_Eval_Dec1drawdown.csv") contains the probability of each WD lake reaching the drawdown level by Dec 1 which is required by the guidelines when selecting different drawdown magnitudes (1-6ft) by Dec 1 in 2015. 2016 and 2017. The fourth dataset (“Guidleine_Eval_Apr1refill.csv”) consists of the latest refill starting dates of each lake with different designed drawdown magnitude (1-6 ft) to ensure over 95% possibility for each WD lake to be fully refilled by Apr 1 in 2016, 2017, 2018.
|Developing a Stochastic Hydrological Model for Informing Lake Water Level Drawdown Management
|Xinchen He, Jason Carmignani, Konstantinos Andreadis, Allison Roy, Abhishek Kumar, Caitlyn Butler
|USGS Digital Object Identifier Catalog
|National Climate Adaptation Science Center