ABSTRACT:

This archive includes data used in Zhang et al.'s paper "Streamflow prediction in poorly gauged watersheds in the United States through data-driven sparse sensing", which has been published in Water Resources Research (WRR) (https://doi.org/10.1029/2022WR034092). The archive contains 1) raw data (daily-scale CAMELS streamflow data and watershed attributes) and 2) MATLAB scripts used to perform data-driven sparse sensing and generate sample figures. The streamflow data used in this study was retrieved from the Catchment Attributes and Meteorology for Large-sample Studies (CAMELS) dataset (https://ral.ucar.edu/solutions/products/camels). The MATLAB code used for data-driven sparse sensing was retrieved from the Github repository by Krithika Manohar (https://github.com/kmanohar/SSPOR_pub) and customized for this study.

ABSTRACT:

This archive includes data used in Zhang et al.'s WRR paper "Streamflow prediction in poorly gauged watersheds in the United States through data-driven sparse sensing", which is under review currently. The archive contains 1) raw data (daily-scale CAMELS streamflow data and watershed attributes) and 2) MATLAB scripts used to perform data-driven sparse sensing and generate sample figures. The streamflow data used in this study was retrieved from the Catchment Attributes and Meteorology for Large-sample Studies (CAMELS) dataset (https://ral.ucar.edu/solutions/products/camels). The MATLAB code used for data-driven sparse sensing was retrieved from the Github repository by Krithika Manohar (https://github.com/kmanohar/SSPOR_pub) and customized for this study.

ABSTRACT:

This archive includes data used in Zhang et al.'s Water Resources Research (WRR) paper "The role of inflow and infiltration (I/I) in urban water balances and streamflow regimes: A hydrograph analysis along the sewershed-watershed continuum", which is under review currently. There are three directories that contain 1) hourly-scale precipitation data at one rain gauge in Milwaukee, WI, 2) hourly-scale sanitary sewer flow data in 17 sewersheds in Milwaukee, WI, and 3) daily-scale streamflow data in 18 watersheds near Milwaukee, WI. The sanitary sewer flow data was retrieved from Metropolitan Milwaukee Sewer District (MMSD). The streamflow data was retrieved from the USGS National Water Information System (https://waterdata.usgs.gov/nwis).

ABSTRACT:

This archive includes data used in Zhang et al.'s GRL paper "Reconstruction of sparse stream flow and concentration time-series through compressed sensing", which has been published and is available at https://doi.org/10.1029/2022GL101177. There are two directories that contain 1) daily-scale streamflow and water quality data in multiple gages during 2015-2021, and 2) 15-min-scale stream flow and water quality data in one gage during 2015-2021. The variables include streamflow, temperature, specific conductance, turbidity, dissolved oxygen, nitrate concentration, and phosphorous concentration. The number of gages for different variables varies in the daily-scale data. All the data was retrieved from the USGS National Water Information System (https://waterdata.usgs.gov/nwis).