MOSART-WM: The Model for Scale Adaptive River Transport - Water Management
Origin: MOSART-WM was initially developed with funding from DOE and PNNL Laboratory Directed Research and Development (LDRD); mosartwmpy is a Python implementation developed specifically for IM3
The Model for Scale Adaptive River Transport, (MOSART) uses a physically based approach for river routing across local, regional, and global scales (H.-Y. Li et al., 2013, H.-Y. Li et al., 2015). Surface and subsurface runoff simulated by land surface schemes-hydrology models inform MOSART, which routes the runoff within and across grid cells. MOSART divides each grid cell into three categories of hydrologic units: (1) hillslopes that contribute surface runoff into tributaries, (2) tributaries, fed by both surface and sub-surface runoff and that discharge into the main channel, and (3) the main channel that connects the local grid cell with the upstream/downstream grid cells through the river network. More detailed descriptions of MOSART and its input hydrography data and channel geometry parameters can be found in Li et al. (2013). Based on the MOSART framework, a suite of capabilities were developed or are under development to represent river-related processes.
MOSART-WM is a water management scheme (Voisin et al., 2013a, Voisin et al. 2017) that regulates the river streamflow through the representation of dam operations and water extractions and return flow for irrigation and non-irrigation purposes from both surface water and groundwater systems and allows to track sectoral water stress (Voisin et al., 2013b, Hejazi et al. 2015). Recent enhancements include sub-monthly reservoir operations derived from local observations, which make MOSART-WM the only large-scale hydrological model with data-driven rather than generic reservoir regulation.
MOSART-WM-heat (H.-Y. Li et al., 2015, Yigsaw et al. 2020) simulates the heat transport along the regulated river channel including a reservoir stratification scheme.
MOSART-WM-hydropower (Zhou et al. 2018) simulates the process-based hydropower at powered reservoirs (over 1300 in the Western U.S.). MOSART-WM has also been extended to provide monthly hydropower generation constraints and thermo-electric power plant capacity derating to power system models (Voisin et al. 2016, Voisin et al. 2018, OConnell et al. 2019, Voisin et al. 2020).
MOSART-WM-ABM enhances the model with a farmer cropping adaptation module. An agent-based model (ABM) approach is adopted with a representative farmer implemented for each model grid cell. The farmer agent crop selection and irrigation decisions are based on a Positive Mathematical Programming (PMP) approach, a method for calibrating agricultural production functions to observed data. Farmer decisions are based on water availability provided by MOSART-WM, which simulates surface water availability for irrigation (Yoon et al. in progress).
mosartwmpy is the Python implementation of MOSART-WM, with a focus on ease-of-use and extensibility. Ongoing development within IM3 will be targeting this version, with data-driven reservoir regulation to be released as the first enhancement, followed closely by the irrigation demand response ABM.
MOSART-WM is a water management scheme (Voisin et al., 2013a, Voisin et al. 2017) that regulates the river streamflow through the representation of dam operations and water extractions and return flow for irrigation and non-irrigation purposes from both surface water and groundwater systems and allows to track sectoral water stress (Voisin et al., 2013b, Hejazi et al. 2015). Recent enhancements include sub-monthly reservoir operations derived from local observations, which make MOSART-WM the only large-scale hydrological model with data-driven rather than generic reservoir regulation.
MOSART-WM-heat (H.-Y. Li et al., 2015, Yigsaw et al. 2020) simulates the heat transport along the regulated river channel including a reservoir stratification scheme.
MOSART-WM-hydropower (Zhou et al. 2018) simulates the process-based hydropower at powered reservoirs (over 1300 in the Western U.S.). MOSART-WM has also been extended to provide monthly hydropower generation constraints and thermo-electric power plant capacity derating to power system models (Voisin et al. 2016, Voisin et al. 2018, OConnell et al. 2019, Voisin et al. 2020).
MOSART-WM-ABM enhances the model with a farmer cropping adaptation module. An agent-based model (ABM) approach is adopted with a representative farmer implemented for each model grid cell. The farmer agent crop selection and irrigation decisions are based on a Positive Mathematical Programming (PMP) approach, a method for calibrating agricultural production functions to observed data. Farmer decisions are based on water availability provided by MOSART-WM, which simulates surface water availability for irrigation (Yoon et al. in progress).
mosartwmpy is the Python implementation of MOSART-WM, with a focus on ease-of-use and extensibility. Ongoing development within IM3 will be targeting this version, with data-driven reservoir regulation to be released as the first enhancement, followed closely by the irrigation demand response ABM.
The mosartwmpy CONUS domain with streams colored by water volume flux.
Credit: The mosartwmpy development team.
IM3 Model Team
IM3 Papers
Voisin N, MI Hejazi, LR Leung, L Liu, M Huang, H-Y Li, and T Tesfa
Water Resources Research 53(5)
Voisin N, M Kitner-Meyer, R Skaggs, T Nguyen, D Wu, J Dirks, Y Xie, and MI Hejazi
Zhou T, N Voisin, G Leng, M Huang, and I Kraucunas
Zhou T, N Voisin, and T Fu
2019
Sensitivity of western U.S. power system dynamics to droughts compounded with fuel price variability
O'Connell M, N Voisin, J Macknick, and T Fu
Voisin N, A Dyreson, T Fu, M O'Connell, SWD Turner, T Zhou, and J Macknick
Thurber, T, CR Vernon, N Sun, SWD Turner, J Yoon, and N Voisin