Browsing by Author "Voisin, Nathalie"

Now showing 1 - 2 of 2

Effects of spatially distributed sectoral water management on the redistribution of water resources in an integrated water model
(2017-06) Voisin, Nathalie; Hejazi, Mohamad; Leung, L. Ruby; Liu, Lu; Huang, Maoyi; Li, HongYi; Tesfa, Teklu
Realistic representations of sectoral water withdrawals and consumptive demands and their allocation to surface and groundwater sources are important for improving modeling of the integrated water cycle. To inform future model development, we enhance the representation of water management in a regional Earth system (ES) model with a spatially distributed allocation of sectoral water demands simulated by a regional integrated assessment (IA) model to surface and groundwater systems. The integrated modeling framework (IA-ES) is evaluated by analyzing the simulated regulated flow and sectoral supply deficit in major hydrologic regions of the conterminous U.S, which differ from ES studies looking at water storage variations. Decreases in historical supply deficit are used as metrics to evaluate IA-ES model improvement in representating the complex sectoral human activities for assessing future adaptation and mitigation strategies. We also assess the spatial changes in both regulated flow and unmet demands, for irrigation and nonirrigation sectors, resulting from the individual and combined additions of groundwater and return flow modules. Results show that groundwater use has a pronounced regional and sectoral effect by reducing water supply deficit. The effects of sectoral return flow exhibit a clear east-west contrast in the hydrologic patterns, so the return flow component combined with the IA sectoral demands is a major driver for spatial redistribution of water resources and water deficits in the US. Our analysis highlights the need for spatially distributed sectoral representation of water management to capture the regional differences in interbasin redistribution of water resources and deficits.
A New Global Storage-Area-Depth Data Set for Modeling Reservoirs in Land Surface and Earth System Models
(2018-12) Yigzaw, Wondmagegn; Li, Hong-Yi; Demissie, Yonas; Hejazi, Mohamad I.; Leung, L. Ruby; Voisin, Nathalie; Payn, Robert A.
Reservoir storage‐area‐depth relationships are the most important factors controlling thermal stratification in reservoirs and, more broadly, the water, energy, and biogeochemical dynamics in the reservoirs and subsequently their impacts on downstream rivers. However, most land surface or Earth system models do not account for the gradual changes of reservoir surface area and storage with the changing depth, inhibiting a consistent and accurate representation of mass, energy, and biogeochemical balances in reservoirs. Here we present a physically coherent parameterization of reservoir storage‐area‐depth data set at the global scale. For each reservoir, the storage‐area‐depth relationships were derived from an optimal geometric shape selected iteratively from five possible regular geometric shapes that minimize the error of total storage and surface area estimation. We applied this algorithm to over 6,800 reservoirs included in the Global Reservoir and Dam database. The relative error between the estimated and observed total storage is no more than 5% and 50% for 66% and 99% of all Global Reservoir and Dam reservoirs, respectively. More importantly, the storage‐depth profiles derived from the approximated reservoir geometry compared well with remote sensing based estimation at 40 major reservoirs from previous studies and ground‐truth measurements for 34 reservoirs in the United States and China. The new global reservoir storage‐area‐depth data set is critical for advancing future modeling and understanding of reservoir processes and subsequent effects on the terrestrial hydrological, ecological, and biogeochemical cycles at the regional and global scales.