Evaluation of Snow and Streamflows Using Noah-MP and WRF-Hydro Models in Aroostook River Basin, Maine

Snow influences land–atmosphere interactions in snow-dominated areas, and snow melt contributes to basin streamflows. However, estimating snowpack properties such as the snow depth (SD) and snow water equivalent (SWE) from land surface model simulations remains a challenge. This is, in part, due to...

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Main Authors: Engela Sthapit, Tarendra Lakhankar, Mimi Hughes, Reza Khanbilvardi, Robert Cifelli, Kelly Mahoney, William Ryan Currier, Francesca Viterbo, Arezoo Rafieeinasab
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Water
Subjects:
Online Access:https://www.mdpi.com/2073-4441/14/14/2145
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author Engela Sthapit
Tarendra Lakhankar
Mimi Hughes
Reza Khanbilvardi
Robert Cifelli
Kelly Mahoney
William Ryan Currier
Francesca Viterbo
Arezoo Rafieeinasab
author_facet Engela Sthapit
Tarendra Lakhankar
Mimi Hughes
Reza Khanbilvardi
Robert Cifelli
Kelly Mahoney
William Ryan Currier
Francesca Viterbo
Arezoo Rafieeinasab
author_sort Engela Sthapit
collection DOAJ
description Snow influences land–atmosphere interactions in snow-dominated areas, and snow melt contributes to basin streamflows. However, estimating snowpack properties such as the snow depth (SD) and snow water equivalent (SWE) from land surface model simulations remains a challenge. This is, in part, due to uncertainties in the atmospheric forcing variables, which propagate into hydrological model predictions. This study implements the Weather Research and Forecasting (WRF)-Hydro framework with the Noah-Multiparameterization (Noah-MP) land surface model in the NOAA’s National Water Model (NWM) version 2.0 configuration to estimate snow in a single column and subsequently the streamflow across the Aroostook River’s sub-basins in Maine for water years (WY) 2014–2016. This study evaluates how differences between two atmospheric forcing datasets, the North American Land Data Assimilation version 2 (NLDAS-2) and in situ (Station), translate into differences in the simulation of snow. NLDAS-2 was used as the meteorological forcing in the retrospective NWM 2.0 simulations. The results from the single-column study showed that differences in the simulated SWE and SD were linked to differences in the 2 m air temperature (T2m), which influenced the precipitation partitioning of rain and snow, as parameterized in Noah-MP. The negative mean bias of −0.7 K (during the accumulation period) in T2m for NLDAS-2, compared to the Station forcing, was a major factor that contributed to the positive mean bias of +52 mm on average in the peak SWE in the NLDAS-2-forced Noah-MP simulation during the study period. The higher T2m values at the Station led to higher sensible heat fluxes towards the snowpack, which led to a higher amount of net energy at the snow’s surface and melt events during the accumulation season in Station-forced Noah-MP simulations. The results from the retrospective NWM version 2.0′s simulation in the basin showed that the streamflow estimates were closer to the United States Geological Survey gage observations at the two larger sub-basins (NSE = 0.9), which were mostly forested, compared to the two smaller sub-basins (NSE ≥ 0.4), which had more agricultural land-use. This study also showed that the spring snowmelt timing was captured quite well by the timing of the decline in the simulated SWE and SD, providing an early indication of melt in most sub-basins. The simulated fractional snow cover area (fSCA) however provided less information about the changes in snow or onset of snowmelt as it was mostly binary (full snow cover in winter), which differed from the more realistic fSCA values shown by the Moderate Resolution Imaging Spectroradiometer.
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spelling doaj.art-11d5c0e33c7747c5992ac7c008f345fa2023-12-03T12:24:47ZengMDPI AGWater2073-44412022-07-011414214510.3390/w14142145Evaluation of Snow and Streamflows Using Noah-MP and WRF-Hydro Models in Aroostook River Basin, MaineEngela Sthapit0Tarendra Lakhankar1Mimi Hughes2Reza Khanbilvardi3Robert Cifelli4Kelly Mahoney5William Ryan Currier6Francesca Viterbo7Arezoo Rafieeinasab8NOAA Center for Earth System Sciences and Remote Sensing Technologies, The City College of New York, 160 Convent Avenue, New York, NY 10031, USANOAA Center for Earth System Sciences and Remote Sensing Technologies, The City College of New York, 160 Convent Avenue, New York, NY 10031, USANOAA Earth System Research Laboratory, Physical Sciences Laboratory, Boulder, CO 80305, USANOAA Center for Earth System Sciences and Remote Sensing Technologies, The City College of New York, 160 Convent Avenue, New York, NY 10031, USANOAA Earth System Research Laboratory, Physical Sciences Laboratory, Boulder, CO 80305, USANOAA Earth System Research Laboratory, Physical Sciences Laboratory, Boulder, CO 80305, USANOAA Earth System Research Laboratory, Physical Sciences Laboratory, Boulder, CO 80305, USANOAA Earth System Research Laboratory, Physical Sciences Laboratory, Boulder, CO 80305, USANational Center for Atmospheric Research, Research Applications Laboratory, Boulder, CO 80301, USASnow influences land–atmosphere interactions in snow-dominated areas, and snow melt contributes to basin streamflows. However, estimating snowpack properties such as the snow depth (SD) and snow water equivalent (SWE) from land surface model simulations remains a challenge. This is, in part, due to uncertainties in the atmospheric forcing variables, which propagate into hydrological model predictions. This study implements the Weather Research and Forecasting (WRF)-Hydro framework with the Noah-Multiparameterization (Noah-MP) land surface model in the NOAA’s National Water Model (NWM) version 2.0 configuration to estimate snow in a single column and subsequently the streamflow across the Aroostook River’s sub-basins in Maine for water years (WY) 2014–2016. This study evaluates how differences between two atmospheric forcing datasets, the North American Land Data Assimilation version 2 (NLDAS-2) and in situ (Station), translate into differences in the simulation of snow. NLDAS-2 was used as the meteorological forcing in the retrospective NWM 2.0 simulations. The results from the single-column study showed that differences in the simulated SWE and SD were linked to differences in the 2 m air temperature (T2m), which influenced the precipitation partitioning of rain and snow, as parameterized in Noah-MP. The negative mean bias of −0.7 K (during the accumulation period) in T2m for NLDAS-2, compared to the Station forcing, was a major factor that contributed to the positive mean bias of +52 mm on average in the peak SWE in the NLDAS-2-forced Noah-MP simulation during the study period. The higher T2m values at the Station led to higher sensible heat fluxes towards the snowpack, which led to a higher amount of net energy at the snow’s surface and melt events during the accumulation season in Station-forced Noah-MP simulations. The results from the retrospective NWM version 2.0′s simulation in the basin showed that the streamflow estimates were closer to the United States Geological Survey gage observations at the two larger sub-basins (NSE = 0.9), which were mostly forested, compared to the two smaller sub-basins (NSE ≥ 0.4), which had more agricultural land-use. This study also showed that the spring snowmelt timing was captured quite well by the timing of the decline in the simulated SWE and SD, providing an early indication of melt in most sub-basins. The simulated fractional snow cover area (fSCA) however provided less information about the changes in snow or onset of snowmelt as it was mostly binary (full snow cover in winter), which differed from the more realistic fSCA values shown by the Moderate Resolution Imaging Spectroradiometer.https://www.mdpi.com/2073-4441/14/14/2145National Water Modelland surface modelmeteorological forcingsnow water equivalentsnow depthfractional snow cover area
spellingShingle Engela Sthapit
Tarendra Lakhankar
Mimi Hughes
Reza Khanbilvardi
Robert Cifelli
Kelly Mahoney
William Ryan Currier
Francesca Viterbo
Arezoo Rafieeinasab
Evaluation of Snow and Streamflows Using Noah-MP and WRF-Hydro Models in Aroostook River Basin, Maine
Water
National Water Model
land surface model
meteorological forcing
snow water equivalent
snow depth
fractional snow cover area
title Evaluation of Snow and Streamflows Using Noah-MP and WRF-Hydro Models in Aroostook River Basin, Maine
title_full Evaluation of Snow and Streamflows Using Noah-MP and WRF-Hydro Models in Aroostook River Basin, Maine
title_fullStr Evaluation of Snow and Streamflows Using Noah-MP and WRF-Hydro Models in Aroostook River Basin, Maine
title_full_unstemmed Evaluation of Snow and Streamflows Using Noah-MP and WRF-Hydro Models in Aroostook River Basin, Maine
title_short Evaluation of Snow and Streamflows Using Noah-MP and WRF-Hydro Models in Aroostook River Basin, Maine
title_sort evaluation of snow and streamflows using noah mp and wrf hydro models in aroostook river basin maine
topic National Water Model
land surface model
meteorological forcing
snow water equivalent
snow depth
fractional snow cover area
url https://www.mdpi.com/2073-4441/14/14/2145
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