Jung Hahn Chul, Getirana Augusto, Policelli Frederick, McNally Amy, Arsenault Kristi R, Kumar Sujay, Tadesse Tsegaye, Peters-Lidard Christa D
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA.
Science Systems and Applications, Inc., Lanham, MD, USA.
J Hydrol (Amst). 2017 Dec;555:535-546. doi: 10.1016/j.jhydrol.2017.10.040. Epub 2017 Oct 24.
Improved understanding of the water balance in the Blue Nile is of critical importance because of increasingly frequent hydroclimatic extremes under a changing climate. The intercomparison and evaluation of multiple land surface models (LSMs) associated with different meteorological forcing and precipitation datasets can offer a moderate range of water budget variable estimates. In this context, two LSMs, Noah version 3.3 (Noah3.3) and Catchment LSM version Fortuna 2.5 (CLSMF2.5) coupled with the Hydrological Modeling and Analysis Platform (HyMAP) river routing scheme are used to produce hydrological estimates over the region. The two LSMs were forced with different combinations of two reanalysis-based meteorological datasets from the Modern-Era Retrospective analysis for Research and Applications datasets (i.e., MERRA-Land and MERRA-2) and three observation-based precipitation datasets, generating a total of 16 experiments. Modeled evapotranspiration (ET), streamflow, and terrestrial water storage estimates were evaluated against the Atmosphere-Land Exchange Inverse (ALEXI) ET, in-situ streamflow observations, and NASA Gravity Recovery and Climate Experiment (GRACE) products, respectively. Results show that CLSMF2.5 provided better representation of the water budget variables than Noah3.3 in terms of Nash-Sutcliffe coefficient when considering all meteorological forcing datasets and precipitation datasets. The model experiments forced with observation-based products, the Climate Hazards group Infrared Precipitation with Stations (CHIRPS) and the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA), outperform those run with MERRA-Land and MERRA-2 precipitation. The results presented in this paper would suggest that the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System incorporate CLSMF2.5 and HyMAP routing scheme to better represent the water balance in this region.
由于气候变化下极端水文气候事件日益频繁,加深对青尼罗河水文平衡的理解至关重要。对与不同气象强迫和降水数据集相关的多个陆面模型(LSM)进行相互比较和评估,可以提供一系列适度的水平衡变量估计值。在此背景下,使用了两个陆面模型,即诺亚版本3.3(Noah3.3)和集水区陆面模型Fortuna 2.5版本(CLSMF2.5),并结合水文建模与分析平台(HyMAP)的河流路由方案来生成该地区的水文估计值。这两个陆面模型由来自现代时代回顾性分析研究与应用数据集(即MERRA-Land和MERRA-2)的两个基于再分析的气象数据集与三个基于观测的降水数据集的不同组合驱动,共产生了16个实验。分别针对大气-陆地交换反演(ALEXI)蒸散量、原位流量观测以及美国国家航空航天局重力恢复与气候实验(GRACE)产品,对模拟的蒸散量(ET)、流量和陆地储水量估计值进行了评估。结果表明,在考虑所有气象强迫数据集和降水数据集时,就纳什-萨特克利夫系数而言,CLSMF2.5比Noah3.3能更好地体现水平衡变量。由基于观测的产品(气候灾害组站点红外降水数据(CHIRPS)和热带降雨测量任务(TRMM)多卫星降水分析(TMPA))驱动的模型实验,其表现优于使用MERRA-Land和MERRA-2降水数据运行的实验。本文给出的结果表明,饥荒早期预警系统网络(FEWS NET)陆地数据同化系统应纳入CLSMF2.5和HyMAP路由方案,以更好地体现该地区的水平衡。