Data & Code

Code

• SWMM-LID-GW: a modified Storm Water Model (SWMM) that enables considering groundwater table depth in the simulation of low-impact development (LID) (Zhang et al., 2018, JH).

• Data-driven sparse sensing

  • Code for Zhang et al. (2023, WRR) that enables 1) identifying the optimal timings for streamflow measurements and 2) predicting streamflow time-series with temporally-sparse measurements.

  • Code for Ding & Zhang (2025, Arxiv) that enables 1) identifying the optimal sensor locations in storm sewer networks and 2) predicting water levels with spatially-sparse measurements.

DATA

• Stream flow and concentration data in Midwest 2015-2021 (collected from USGS, 2022) 

• Stream flow data across the CONUS 1981-2010 (collected from CAMELS dataset, 2022)

• Sanitary sewer flow in Milwaukee 2014-2019 (collected from MMSD, 2020)