EVALUATION OF CFSR CLIMATE DATA FOR HYDROLOGIC PREDICTION IN DATASCARCE WATERSHEDS: AN APPLICATION IN THE BLUE NILE RIVER BASIN
Paper No. JAWRA-13-0074-P of the Journal of the American Water Resources Association (JAWRA). Received March 22, 2013; accepted January 3, 2014. © 2014 American Water Resources Association. Discussions are open until 6 months from print publication.
Yihun Taddele Dile and Raghavan Srinivasan
Ph.D. Candidate (Dile), Stockholm Resilience Center, Stockholm University, Kraftriket 2B, 106 91, Stockholm, Sweden and Stockholm € Environment Institute, Linnegatan 87D, 104 51 Stockholm, Sweden; and Professor (Srinivasan), Spatial Sciences Laboratory in the Department of Ecosystem Sciences and Management, Texas A&M University, 1500 Research Parkway, College Station, Texas 77845 (E-Mail/Dile: yihun.dile@sei-international.org).
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
ABSTRACT:
Data scarcity has been a huge problem in modeling the water resources of the Upper Blue Nile basin, Ethiopia. Satellite data and different statistical methods have been used to improve the quality of conventional meteorological data. This study assesses the applicability of the National Centers for Environmental Prediction’s Climate Forecast System Reanalysis (CFSR) climate data in modeling the hydrology of the region. The Soil and Water Assessment Tool was set up to compare the performance of CFSR weather with that of conventional weather in simulating observed streamflow at four river gauging stations in the Lake Tana basin — the upper part of the Upper Blue Nile basin. The conventional weather simulation performed satisfactorily (e.g., NSE ≥ 0.5) for three gauging stations, while the CFSR weather simulation performed satisfactorily for two. The simulations with CFSR and conventional weather yielded minor differences in the water balance components in all but one watershed, where the CFSR weather simulation gave much higher average annual rainfall, resulting in higher water balance components. Both weather simulations gave similar annual crop yields in the four administrative zones. Overall the simulation with the conventional weather performed better than the CFSR weather. However, in data-scarce regions such as remote parts of the Upper Blue Nile basin, CFSR weather could be a valuable option for hydrological predictions where conventional gauges are not available.
KEY TERMS:
hydrologic cycle; time series analysis; meteorology; CFSR; SWAT; Ethiopia; Upper Blue Nile basin; Lake Tana basin.
Dile, Yihun Taddele and Raghavan Srinivasan, 2014. Evaluation of CFSR Climate Data for Hydrologic Prediction in Data-Scarce Watersheds: An Application in the Blue Nile River Basin. Journal of the American Water Resources Association (JAWRA) 1-16. DOI: 10.1111/jawr.12182
INTRODUCTION
Several hydrological modeling studies have been carried out in the Upper Blue Nile basin, Ethiopia. Some of these studies (e.g., Liu et al., 2008; Uhlenbrook et al., 2010; Gebrehiwot et al., 2011) have sought to understand the hydrology of the region, while others (e.g., Abdo et al., 2009; Beyene et al., 2009; Elshamy et al., 2009; Kim and Kaluarachchi, 2009; Betrie et al., 2011; Setegn et al., 2011; Taye et al., 2011) have applied hydrological models to assess the implications of environmental and management changes on the water resources in the region. Hydrological modeling has been used to inform the teleconnection between upstream and downstream countries (e.g., Barrett, 1994; Conway and Mike, 1996).
These modeling efforts have ranged from simple conceptual models (e.g., Kim and Kaluarachchi, 2008; Liu et al., 2008; Conway, 2009; Uhlenbrook et al., 2010) to complex, physically based distributed hydrological models (e.g., Mishra and Hata, 2006; Setegn et al., 2010; White et al., 2011). However, these modeling efforts have not always gone smoothly. One of the main challenges they have faced has been the limited availability of hydrometeorological data (Kim and Kaluarachchi, 2008; Kim et al., 2008; Collick et al., 2009; Mekonnen et al., 2009; Melesse et al., 2010). Improved data collection and management is needed to increase the reliability of hydrological modeling efforts in the Upper Blue Nile basin
Many studies have explored ways to improve the quality of hydro-climatic data in the Upper Blue Nile basin. Some (e.g., Barrett, 1994; Tsintikidis et al., 1999; Ymeti, 2007) have applied satellite data as inputs to hydrological models. Others have employed various statistical methods to fill data gaps (e.g., Betrie et al., 2011; Tesemma et al., 2009; Uhlenbrook et al., 2010) or to generate finer-resolution inputs from coarser datasets (e.g., Engida and Esteves, 2011). Tsintikidis et al. (1999) applied daily average aerial precipitation from METEOSAT satellite data to study the sensitivity of the Blue Nile region’s hydrologic response to the type of precipitation data (i.e., rain gauge-based vs. satellite-based estimates). Similarly, Barrett (1994) utilized METEOSAT satellite inputs to predict the inflows into the Aswan High Dam and to forecast flow hydrographs at selected gauging locations above the dam. Ymeti (2007) estimated rainfall from geostationary METEOSTAT Second Generation (infrared channel) and orbiting Tropical Rainfall Measurement Mission (TRMM; microwave channel) satellite data and assessed the performance of two conceptual rainfall-runoff models. Tesemma et al. (2009) and Uhlenbrook et al. (2010) used regression and spatial interpolation to fill data gaps. Most of the studies that have applied the Soil and Water Assessment Tool (SWAT) (e.g., Betrie et al., 2011) have used a daily weather generator (WXGEN) (Neitsch et al., 2012) to generate climatic data or to fill gaps in measured records. While these are some of the various efforts exerted to improve hydro-climatic data quality in the Upper Blue Nile basin, global reanalysis data sources are becoming very promising options in representing observed weather data (cf., Zhang et al., 2012).
Global reanalysis weather data have been used for various hydrological applications all over the world and yielded sound results (Lavers et al., 2012; Najafi et al., 2012; Fuka et al., 2013; Quadro et al., 2013; Smith and Kummerow, 2013; Wei et al., 2013). For example, Smith and Kummerow (2013) analyzed the surface and atmospheric water budgets of the Upper Colorado River basin using reanalysis, in situ, and satellite-derived datasets. The reanalysis data they used included National Aeronautics and Space Administration Modern-Era Retrospective Analysis for Research Applications (MERRA), the European Centre for Medium-Range Weather Forecasts (ECMWF) interim Reanalysis (ERA-Interim), and the National Centers for Environmental Prediction’s Climate Forecast System Reanalysis (CFSR). They found that all datasets captured the seasonal cycle for each water budget component. Likewise, Najafi et al. (2012) generated reasonable volumetric estimates of the streamflow of the snow-dominated East River basin, a tributary of the Gunnison River in the Colorado River basin, with the Sacramento Soil Moisture Accounting (SAC-SMA) model using CFSR data. Fuka et al. (2013) used CFSR precipitation and temperature data in modeling five small watersheds representing different hydroclimates (four in the United States and one in Ethiopia) in SWAT. Their findings suggest that utilizing CFSR precipitation and temperature data for watershed models can predict the streamflow as good as or better than simulations using traditionally observed weather data. Lavers et al. (2012) used five atmospheric reanalysis products — CFSR, ERA-Interim, 20th Century Reanalysis (20CR), MERRA, and NCEP-NCAR (National Center for Atmospheric Research) — to detect atmospheric rivers (narrow plumes of enhanced moisture transport in the lower troposphere) and their links to British winter floods and large-scale climatic circulation. Their study provided valuable evidence of generally good agreement on atmospheric river occurrences between the products. Quadro et al. (2013) evaluated the hydrological cycle over South America using CFSR, MERRA, and the NCEP Reanalysis II (NCEP-2). They observed general agreement in precipitation patterns among the three products and the observed precipitation over much of South America. They reported that the CFSR precipitation showed the smallest biases. Wei et al. (2013) used the CFSR dataset to study the water budgets of three tropical cyclones that passed through the Taiwan Strait. They assessed the quality of CFSR for tropical cyclone studies by comparing CFSR precipitation data with TRMM precipitation data. They concluded that the CFSR data were reliable for studying tropical cyclones in this area. The applicability of global reanalysis climate data for hydrological model predictions in the Upper Blue Nile basin has not so far been adequately investigated. The present study, focusing on a relatively data-rich part of the basin, assesses the applicability of CFSR data for hydrological predictions
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