Hi, I'm an error. x

David William Hyndman

Michigan State University | Professor and Chair

Subject Areas: Hydrogeology, Hydrogeophysics

 Recent Activity

ABSTRACT:

Preferred citation:
Xu, T., Deines, J., Kendall, A., Basso, B., and Hyndman, DW. 2019. Addressing Challenges for Mapping Irrigated Fields in Subhumid Temperate Regions by Integrating Remote Sensing and Hydroclimatic Data. Remote Sensing.

We developed annual, 30-m resolution maps of irrigated corn and soybeans for southwestern Michigan from 2001 to 2016 using a machine learning method (random forest). Please see Xu et al. 2019 for full details. The rasters are in UINT 8 format, with 0 indicates rainfed, 1 indicates irrigated, and 3 indicates masked (not row crops according to NLCD before 2007 and not corn or soybeans according to CDL since 2007).

Show More

ABSTRACT:

Preferred citation:
Hyndman, DW, T Xu, JM Deines, G Cao, R Nagelkirk, A Vina, W McConnell, B Basso, A Kendall, S Li, L Luo, F Lupi, D Ma, JA Winkler, W Yang, C Zheng, and J Liu. 2017. Quantifying changes in water use and groundwater availability in a megacity using novel integrated systems modeling. Geophysical Research Letters, 44. DOI: 10.1002/2017GL074429

We developed a new systems modeling framework to quantify the influence of changes in land use, crop growth, and urbanization on groundwater storage for Beijing, China. This framework was then used to understand and quantify causes of observed decreases in groundwater storage from 1993 to 2006, revealing that the expansion of Beijing'’s urban areas at the expense of croplands has enhanced recharge while reducing water lost to evapotranspiration, partially ameliorating groundwater declines. Please see Hyndman et al. 2017 for full details.

This repository contains assembled model input data not easily acquired through cited sources, model-subcomponent output such as annual land use rasters, and the MODFLOW groundwater model files which integrates these subcomponents.

Groundwater Model and Data
The MODFLOW groundwater model files and associated data can be found in the "Groundwater Model Files" folder. This includes well observation data, input recharge data, as well as data stored within the groundwater model such as pumping data and aquifer top and bottom. See the readme.txt within the folder and Hyndman et al. 2017 for additional detail.

Annual Land Use Rasters
The "Annual land use rasters" folder contains annually modeled land use. The key for land use codes is in LandUse_codeKey.csv. For methods, see Hyndman et al. 2017.

Contact: David Hyndman, hyndman@msu.edu

Show More

 Contact

Mobile 5172823665
Mobile 5172823665
Email (Log in to send email)
Resources
All 0
Collection 0
Composite Resource 0
Generic 0
Geographic Feature 0
Geographic Raster 0
HIS Referenced Time Series 0
Model Instance 0
Model Program 0
MODFLOW Model Instance Resource 0
Multidimensional (NetCDF) 0
Script Resource 0
SWAT Model Instance 0
Time Series 0
Web App 0
Composite Resource Composite Resource
Quantifying changes in water use and groundwater availability in Beijing: Supporting data for Hyndman et al. 2017
Created: Aug. 18, 2017, 5:54 a.m.
Authors: David Hyndman · Tianfang Xu · Jillian Deines · Guoliang Cao · Ryan Nagelkirk · Andres Vina · William McConnell · Bruno Basso · Shuxin Li · Lifeng Luo · Anthony Kendall · Frank Lupi · Doncheng Ma · Julie Winkler · Wu Yang · Chunmiao Zheng · Jianguo Liu

ABSTRACT:

Preferred citation:
Hyndman, DW, T Xu, JM Deines, G Cao, R Nagelkirk, A Vina, W McConnell, B Basso, A Kendall, S Li, L Luo, F Lupi, D Ma, JA Winkler, W Yang, C Zheng, and J Liu. 2017. Quantifying changes in water use and groundwater availability in a megacity using novel integrated systems modeling. Geophysical Research Letters, 44. DOI: 10.1002/2017GL074429

We developed a new systems modeling framework to quantify the influence of changes in land use, crop growth, and urbanization on groundwater storage for Beijing, China. This framework was then used to understand and quantify causes of observed decreases in groundwater storage from 1993 to 2006, revealing that the expansion of Beijing'’s urban areas at the expense of croplands has enhanced recharge while reducing water lost to evapotranspiration, partially ameliorating groundwater declines. Please see Hyndman et al. 2017 for full details.

This repository contains assembled model input data not easily acquired through cited sources, model-subcomponent output such as annual land use rasters, and the MODFLOW groundwater model files which integrates these subcomponents.

Groundwater Model and Data
The MODFLOW groundwater model files and associated data can be found in the "Groundwater Model Files" folder. This includes well observation data, input recharge data, as well as data stored within the groundwater model such as pumping data and aquifer top and bottom. See the readme.txt within the folder and Hyndman et al. 2017 for additional detail.

Annual Land Use Rasters
The "Annual land use rasters" folder contains annually modeled land use. The key for land use codes is in LandUse_codeKey.csv. For methods, see Hyndman et al. 2017.

Contact: David Hyndman, hyndman@msu.edu

Show More
Composite Resource Composite Resource

ABSTRACT:

Preferred citation:
Xu, T., Deines, J., Kendall, A., Basso, B., and Hyndman, DW. 2019. Addressing Challenges for Mapping Irrigated Fields in Subhumid Temperate Regions by Integrating Remote Sensing and Hydroclimatic Data. Remote Sensing.

We developed annual, 30-m resolution maps of irrigated corn and soybeans for southwestern Michigan from 2001 to 2016 using a machine learning method (random forest). Please see Xu et al. 2019 for full details. The rasters are in UINT 8 format, with 0 indicates rainfed, 1 indicates irrigated, and 3 indicates masked (not row crops according to NLCD before 2007 and not corn or soybeans according to CDL since 2007).

Show More