Evaluation of Satellite Rainfall Estimates and Gridded Gauge Products over the Upper Blue Nile Region

2011 ◽  
pp. 109-127 ◽  
Author(s):  
Tufa Dinku ◽  
Stephen Connor ◽  
Pietro Ceccato
Keyword(s):  
Blue Nile ◽  
Satellite Rainfall ◽  
Rainfall Estimates

scholarly journals Accuracy of satellite rainfall estimates in the Blue Nile Basin: Lowland plain versus highland mountain

2014 ◽  
Vol 50 (11) ◽  
pp. 8775-8790 ◽  
Author(s):  
Mekonnen Gebremichael ◽  
Menberu M. Bitew ◽  
Feyera A. Hirpa ◽  
Gebrehiwot N. Tesfay
Keyword(s):  
Nile Basin ◽  
Blue Nile ◽  
Blue Nile Basin ◽  
Satellite Rainfall ◽  
Rainfall Estimates

Evaluation of satellite rainfall estimates over the Lake Tana basin at the source region of the Blue Nile River

2018 ◽  
Vol 212 ◽  
pp. 43-53 ◽  
Author(s):  
Ayele Almaw Fenta ◽  
Hiroshi Yasuda ◽  
Katsuyuki Shimizu ◽  
Yasuomi Ibaraki ◽  
Nigussie Haregeweyn ◽  
...  
Keyword(s):  
Source Region ◽  
Nile River ◽  
Lake Tana ◽  
Blue Nile ◽  
Satellite Rainfall ◽  
Rainfall Estimates ◽  
Lake Tana Basin

scholarly journals Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia

2017 ◽  
Author(s):  
Getachew Tesfaye Ayehu ◽  
Tsegaye Tadesse ◽  
Berhan Gessesse ◽  
Tufa Dinku
Keyword(s):  
Validation Study ◽  
Rain Gauge ◽  
Nile Basin ◽  
Spatial And Temporal Patterns ◽  
Blue Nile ◽  
Rainfall Occurrence ◽  
Blue Nile Basin ◽  
Satellite Rainfall ◽  
Rainfall Estimates ◽  
Upper Blue Nile Basin

Abstract. Accurate measurement of rainfall is vital to analyze the spatial and temporal patterns of precipitation at various scales. However, the conventional rain gauge observations in many parts of the world such as Ethiopia are sparse and unevenly distributed. An alternative to traditional rain gauge observations could be satellite-based rainfall estimates. Satellite rainfall estimates could be used as a sole product (e.g. in areas with no (poor) ground observations) or through integrating with rain gauge measurements. In this study, the newly available Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data has been evaluated in comparison to rain gauge data for the period of 2000 to 2015 across the Upper Blue Nile basin in Ethiopia. Besides, the Tropical Applications of Meteorology using SATellite and ground-based observations (TAMSAT) version 2 and 3 (TAMSAT 2 and TAMSAT 3) and the African Rainfall Climatology (ARC 2) products have been used as a benchmark and compared with CHIRPS. The TAMSAT 2 rainfall estimate was used in this study mainly to assess the improvements made with the recent version of a TAMSAT product (TAMSAT 3). From the overall analysis at dekadal and monthly temporal scale, CHIRPS exhibited higher skills and the best bias value in comparison to ARC 2 but overestimates the frequency of rainfall occurrence particularly during the dry months. On the other hand, TAMSAT 3 has shown very comparable performance with that of CHIRPS product, particularly with regards to bias. The ARC 2 product was found to have the weakest performance underestimating rainfall amounts by about 24 %. The skill of CHIRPS is less affected by variation in elevation in comparison to TAMSAT 3 and ARC 2 products. While ARC 2 was found to be affected by elevation with the average biases of 1.53, 0.86 and 0.77 at lower ( 2000 m a.s.l), respectively. Comparing the overall performance of the three products, CHIRPS exhibited the best performance followed closely by TAMSAT 3. This validation study also shows that the TAMSAT 3 has overcome the main weaknesses of TAMSAT 2, which is underestimation of high rainfall amounts by up to 31 % in this study. Overall, the finding of this validation study shows the potentials of CHIRPS product to be used for various operational applications such as rainfall pattern and variability study in the Upper Blue Nile basin in Ethiopia.

scholarly journals Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia

2018 ◽  
Vol 11 (4) ◽  
pp. 1921-1936 ◽  
Author(s):  
Getachew Tesfaye Ayehu ◽  
Tsegaye Tadesse ◽  
Berhan Gessesse ◽  
Tufa Dinku
Keyword(s):  
Correlation Coefficients ◽  
Rain Gauge ◽  
Nile Basin ◽  
Spatial And Temporal Patterns ◽  
Blue Nile ◽  
Rainfall Occurrence ◽  
Blue Nile Basin ◽  
Satellite Rainfall ◽  
Rainfall Estimates ◽  
Upper Blue Nile Basin

Abstract. Accurate measurement of rainfall is vital to analyze the spatial and temporal patterns of precipitation at various scales. However, the conventional rain gauge observations in many parts of the world such as Ethiopia are sparse and unevenly distributed. An alternative to traditional rain gauge observations could be satellite-based rainfall estimates. Satellite rainfall estimates could be used as a sole product (e.g., in areas with no (or poor) ground observations) or through integrating with rain gauge measurements. In this study, the potential of a newly available Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) rainfall product has been evaluated in comparison to rain gauge data over the Upper Blue Nile basin in Ethiopia for the period of 2000 to 2015. In addition, the Tropical Applications of Meteorology using SATellite and ground-based observations (TAMSAT 3) and the African Rainfall Climatology (ARC 2) products have been used as a benchmark and compared with CHIRPS. From the overall analysis at dekadal (10 days) and monthly temporal scale, CHIRPS exhibited better performance in comparison to TAMSAT 3 and ARC 2 products. An evaluation based on categorical/volumetric and continuous statistics indicated that CHIRPS has the greatest skills in detecting rainfall events (POD = 0.99, 1.00) and measure of volumetric rainfall (VHI = 1.00, 1.00), the highest correlation coefficients (r= 0.81, 0.88), better bias values (0.96, 0.96), and the lowest RMSE (28.45 mm dekad−1, 59.03 mm month−1) than TAMSAT 3 and ARC 2 products at dekadal and monthly analysis, respectively. CHIRPS overestimates the frequency of rainfall occurrence (up to 31 % at dekadal scale), although the volume of rainfall recorded during those events was very small. Indeed, TAMSAT 3 has shown a comparable performance with that of the CHIRPS product, mainly with regard to bias. The ARC 2 product was found to have the weakest performance underestimating rain gauge observed rainfall by about 24 %. In addition, the skill of CHIRPS is less affected by variation in elevation in comparison to TAMSAT 3 and ARC 2 products. CHIRPS resulted in average biases of 1.11, 0.99, and 1.00 at lower (< 1000 m a.s.l.), medium (1000 to 2000 m a.s.l.), and higher elevation (> 2000 m a.s.l.), respectively. Overall, the finding of this validation study shows the potentials of the CHIRPS product to be used for various operational applications such as rainfall pattern and variability study in the Upper Blue Nile basin in Ethiopia.

scholarly journals Comparing TRMM 3B42, CFSR and ground-based rainfall estimates as input for hydrological models, in data scarce regions: the Upper Blue Nile Basin, Ethiopia

2015 ◽  
Vol 12 (2) ◽  
pp. 2081-2112 ◽  
Author(s):  
A. W. Worqlul ◽  
A. S. Collick ◽  
S. A. Tilahun ◽  
S. Langan ◽  
T. H. M. Rientjes ◽  
...  
Keyword(s):  
Rain Gauge ◽  
Hydrological Models ◽  
Nile Basin ◽  
Blue Nile ◽  
Blue Nile Basin ◽  
Satellite Rainfall ◽  
Trmm 3B42 ◽  
Rainfall Estimates ◽  
Better Than ◽  
Upper Blue Nile Basin

Abstract. Accurate prediction of hydrological models requires accurate spatial and temporal distribution of rainfall observation network. In developing countries rainfall observation station network are sparse and unevenly distributed. Satellite-based products have the potential to overcome these shortcomings. The objective of this study is to compare the advantages and the limitation of commonly used high-resolution satellite rainfall products as input to hydrological models as compared to sparsely populated network of rain gauges. For this comparison we use two semi-distributed hydrological models Hydrologiska Byråns Vattenbalansavdelning (HBV) and Parameter Efficient Distributed (PED) that performed well in Ethiopian highlands in two watersheds: the Gilgel Abay with relatively dense network and Main Beles with relatively scarce rain gauge stations. Both are located in the Upper Blue Nile Basin. The two models are calibrated with the observed discharge from 1994 to 2003 and validated from 2004 to 2006. Satellite rainfall estimates used includes Climate Forecast System Reanalysis (CFSR), Tropical Rainfall Measuring Mission (TRMM) 3B42 version 7 and ground rainfall measurements. The results indicated that both the gauged and the CFSR precipitation estimates were able to reproduce the stream flow well for both models and both watershed. TRMM 3B42 performed poorly with Nash Sutcliffe values less than 0.1. As expected the HBV model performed slightly better than the PED model, because HBV divides the watershed into sub-basins resulting in a greater number of calibration parameters. The simulated discharge for the Gilgel Abay was better than for the less well endowed (rain gauge wise) Main Beles. Finally surprisingly, the ground based gauge performed better for both watersheds (with the exception of extreme events) than TRMM and CFSR satellite rainfall estimates. Undoubtedly in the future, when improved satellite products will become available, this will change.

scholarly journals Evaluation of Satellite Rainfall Estimates for Meteorological Drought Analysis over the Upper Blue Nile Basin, Ethiopia

Geosciences ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 352
Author(s):  
Mintesinot Taye ◽  
Dejene Sahlu ◽  
Benjamin F. Zaitchik ◽  
Mulugeta Neka
Keyword(s):  
Linear Trend ◽  
Standardized Precipitation Index ◽  
Warning System ◽  
Meteorological Drought ◽  
Extreme Drought ◽  
Drought Analysis ◽  
Blue Nile ◽  
The Mean ◽  
Satellite Rainfall ◽  
Rainfall Estimates

The objective of this study was to evaluate the performance of satellite rainfall estimates (Climate Hazards Group Infrared Precipitation with Stations version 2 (CHIRPSv2) and Multi-Source Weighted-Ensemble Precipitation version 2 (MSWEPv2) from 1981 to 2018 for monthly meteorological drought analysis over the Upper Blue Nile (UBN) basin. The reference for the performance evaluation was rainfall measured in situ selected with reference to the elevation zones of the basin: Highland, midland, and lowland. Both the measured and estimated rainfall datasets were aggregated by month at a spatial resolution of 10 km × 10 km with a temporal coverage of 38 years from 1981 to 2018 and evaluated with respect to raw precipitation statistics and the standardized precipitation index (SPI). The values of SPI were validated with reference to documented meteorological drought records of the country. The mean bias, correlation coefficient, probability of bias (PBias, %), mean error (ME, mm), and root mean square error (RMSE, mm) values across the elevation zones for CHIRPSv2 were found to be 1.07, 0.91, 6.75, 7.74, and 122.34, respectively. The corresponding values were 1.19, 0.87, 18.56, 19.54, and 130.26 for MSWEPv2. Based on this result, CHIRPSv2 was employed to analyze the magnitude of drought in the different elevation zones of the UBN. The magnitude (SPI) of monthly meteorological drought over the entire UBN basin from 1981 to 2018 ranged from 0 to −3.74. The strongest negative SPI value (−3.74) was observed in August 1984 in midland areas. The highest magnitude of drought was −3.0 in July 2015 over the highland and −3.03 in June 2015 over the lowland during 2014–2017. The observed drought was characterized by extreme, severe, and moderate levels. The mean frequency of severe/extreme meteorological drought in the 38-year period over the highland, midland, and lowland parts of the UBN ranged from 7% to 11%. The average of severe/extreme drought events in each of the elevation zones of the basin was 9%, that is, drought occurred almost every 10 years for all elevation zones of the basin. Over the 38-year period, severe/extreme drought occurred at the onset and/or offset time of rainy season over all elevation zones of the basin. The UBN is characterized as a drought-prone basin. However, the frequency and magnitude of drought could neither be described as a decreasing nor as an increasing linear trend. Thus, the farming practices in the basin need to be enhanced with an improved early warning system and drought-resistant seed technologies.

scholarly journals Effect of Bias Correction of Satellite-Rainfall Estimates on Runoff Simulations at the Source of the Upper Blue Nile

2014 ◽  
Vol 6 (7) ◽  
pp. 6688-6708 ◽  
Author(s):  
Emad Habib ◽  
Alemseged Haile ◽  
Nazmus Sazib ◽  
Yu Zhang ◽  
Tom Rientjes
Keyword(s):  
Bias Correction ◽  
Blue Nile ◽  
Satellite Rainfall ◽  
Rainfall Estimates

scholarly journals A susceptibility-based rainfall threshold approach for landslide occurrence

2019 ◽  
Vol 19 (4) ◽  
pp. 775-789 ◽  
Author(s):  
Elise Monsieurs ◽  
Olivier Dewitte ◽  
Alain Demoulin
Keyword(s):  
Landslide Susceptibility ◽  
Rainfall Threshold ◽  
Exceedance Probability ◽  
Equal Weight ◽  
Antecedent Rainfall ◽  
Rainfall Thresholds ◽  
Landslide Occurrence ◽  
Continental Scale ◽  
Satellite Rainfall ◽  
Rainfall Estimates

Abstract. Rainfall threshold determination is a pressing issue in the landslide scientific community. While major improvements have been made towards more reproducible techniques for the identification of triggering conditions for landsliding, the now well-established rainfall intensity or event-duration thresholds for landsliding suffer from several limitations. Here, we propose a new approach of the frequentist method for threshold definition based on satellite-derived antecedent rainfall estimates directly coupled with landslide susceptibility data. Adopting a bootstrap statistical technique for the identification of threshold uncertainties at different exceedance probability levels, it results in thresholds expressed as AR = (α±Δα)⋅S(β±Δβ), where AR is antecedent rainfall (mm), S is landslide susceptibility, α and β are scaling parameters, and Δα and Δβ are their uncertainties. The main improvements of this approach consist in (1) using spatially continuous satellite rainfall data, (2) giving equal weight to rainfall characteristics and ground susceptibility factors in the definition of spatially varying rainfall thresholds, (3) proposing an exponential antecedent rainfall function that involves past daily rainfall in the exponent to account for the different lasting effect of large versus small rainfall, (4) quantitatively exploiting the lower parts of the cloud of data points, most meaningful for threshold estimation, and (5) merging the uncertainty on landslide date with the fit uncertainty in a single error estimation. We apply our approach in the western branch of the East African Rift based on landslides that occurred between 2001 and 2018, satellite rainfall estimates from the Tropical Rainfall Measurement Mission Multi-satellite Precipitation Analysis (TMPA 3B42 RT), and the continental-scale map of landslide susceptibility of Broeckx et al. (2018) and provide the first regional rainfall thresholds for landsliding in tropical Africa.

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