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Trend Analysis of Precipitation Data: A Case Study of Blue Nile Basin, Africa

Part of the The Handbook of Environmental Chemistry book series (HEC,volume 56)

Abstract

Implementation of water management policies requires decision support system tools in order to evaluate available water resources and create awareness of possible threats such as floods and droughts. Modelling is one of these decision support tools. However, in developing countries, they do not lack only appropriate tools and personnel to develop and maintain water resources model, but they do not have sufficient data to build, calibrate and validate models. For instance, the rain gauge network is too sparse to produce reliable areal rainfall estimation. Blue Nile Basin is one of the basins that suffer from this problem. Consequently, it can effect on the drainages countries like Sudan and Egypt if it is not managed. In order to develop management, different sources other than ground collected data should be used. Radar technology for topography is not feasible based on the high cost. Another alternative is remote sensed data and its derivatives. This chapter gives an assessment for the availability and quality of remote sensed and global rainfall data as one of the important forcing data which should be used to set up a hydrological model.

Keywords

  • Blue Nile Basin
  • Rainfall
  • Remote sensing
  • Spatial
  • Temporal

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References

  1. Bardossy A, Das T (2006) Influence of rainfall observation network on model calibration and application. Hydrol Earth Syst Sci Discuss 3:3691–3726

    CrossRef  Google Scholar 

  2. Levizzani V, Amorati R, Meneguzzo F (2002) A review of satellite-based rainfall estimation methods. Consiglio Nazionale delle Ricerche, Istituto di Scienze dell’Atmosfera e del Clima, Bologna, Italy

    Google Scholar 

  3. Kawanishi T, Kuroiwa H, Kojima M, Oikawa K, Kozu T (2000) TRMM precipitation radar. Adv Space Res 25(5):969–972

    CrossRef  Google Scholar 

  4. Saavedra O, Yoshimura C, Negm A, Nadaoka K, Kanae S, Tri Phong V, Phu L, Toan Q, Ragab O, Suif Z, Hak D, El-Adawy A, Masria A, El-Tarabily A (2015) A platform for integrated water resources management for mega deltas under climate change. JSPS Mega Delta Project, IWTC

    Google Scholar 

  5. IPCC (Intergovernmental Panel on Climate Change) 2008: Climate change 2008: Synthesis Report. Contribution of working Group I, II and III to the Fourth Assessment Report

    Google Scholar 

  6. Conway D, Hulme M (1996) The impact of climate variability and climate change in the Nile Basin on future water resources in Egypt. Water Resour Dev 12(3):277–296

    CrossRef  Google Scholar 

  7. Pfafstetter O 1989 Classification of hydrographic basins Coding methodology

    Google Scholar 

  8. Arnold JG, Neitsch SL, Kiniry JR, Williams JR, King KW (2002) Soil and water assessment tool, theoretical documentation, Grassland, soil and water research laboratory—Agricultural Research Service. US, Texas

    Google Scholar 

  9. Ragab O (2014) Flood forecasting in Blue Nile basin using a process-based hydrological model. Int J Environ ISSN 2091–2854

    Google Scholar 

  10. Engman ET, Chouhan N (1995) Status of microwave soil moisture measurements with remote sensing. Remote Sens Environ 51:189–198

    CrossRef  Google Scholar 

  11. Hong Y, Alder RF, Hossain F, Curtis S, Huffman GJ (2007) Estimate gridded and time variant runoff curve numbers using satelliteremote sensing and geospatial data. Water Resour Res 43:285–294

    CrossRef  Google Scholar 

  12. Barrett EC, Martin DW (1981) The use of satellite data in rainfall monitoring. Academic Press, London, 340 pp

    Google Scholar 

  13. Kubota T et al. (2007) Global precipitation map using satelliteborne microwave radiometers by the GSMAP project: production and validation. IEEE Trans Geosci Remote Sens 45:2259–2275

    CrossRef  Google Scholar 

  14. Lakshmi V (2004) The role of satellite remote sensing in the prediction of ungauged basins. Hydrol Process 18:1029–1034

    CrossRef  Google Scholar 

  15. Easton ZM, Walter MT, Fuka DR, White ED, Steenhuis TS (2010) A simple concept for calibrating runoff thresholds in quasi-distributed variable source area watershed models. Process submitted, Hydrol

    Google Scholar 

  16. Huffman GJ, Adler RF, Bolvin DT, Gu G, Nelkin EJ, Bowman KP, Hong Y, Stocker EF, Wolff DB (2007) The TRMM multi-satellite precipitation analysis: Quasi-Global, Multi-Year, Combined-Sensor precipitation estimates at fine scale. J Hydrometeor 8(1):38–55

    CrossRef  Google Scholar 

  17. Ushio T, Kubota T, Shinge S, Okamoto K, Aonashi K, Inoue T, Takahashi N, Iguchi T, Kachi M, Oki R, Morimoto T, Kawasaki Z (2009) A kalman filter approach to the global satellite mapping of precipitation (GSMAP) from combined passive microwave and infrared data. J Meteor Soc Japan 87A:137–151

    CrossRef  Google Scholar 

  18. Ragab O, Ushio T (2012) Evaluation of GSMaP precipitation Estimates Over Blue Nile Basin, GPM and TRMM International Conference, at Tokyo, Japan

    Google Scholar 

  19. Ragab O (2011) Saavedra O. Simulation of Blue Nile River using a distributed hydrological model and Global Data Sets, ICWEE

    Google Scholar 

  20. Ragab O, Saavedra O, Hirabayashi Y (2013) Future variation in IVER discharge in the Atbara basin under climate change scenarios. Ann J Hydr Eng 57

    Google Scholar 

  21. Yatagai A, Arakawa O, Kamiguchi K, et al. (2009) A 44-year daily gridded precipitation dataset for Asia based on a dense network of rain ganges. SOLA 5:137–140. doi:10.2151/Sola.2009-035

    CrossRef  Google Scholar 

  22. Gregory JM (2002) Stouffer, Raper, Stott: an observationally based estimate of the climate sensitivity. J Climate 15(22):3117–3121

    CrossRef  Google Scholar 

  23. Barrett EC (1981) Satellite monitoring of extreme rainfall events in Satellite remote sensing. Applications to rural disasters Prof. joint ESA/FAO/WHO training Course, Rome, 1980, (European Space Agency, Paris, ESA – SP – 1035), pp 97–103

    Google Scholar 

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Correspondence to Osama Ragab .

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Ragab, O., Negm, A. (2016). Trend Analysis of Precipitation Data: A Case Study of Blue Nile Basin, Africa. In: Negm, A. (eds) The Nile River. The Handbook of Environmental Chemistry, vol 56. Springer, Cham. https://doi.org/10.1007/698_2016_114

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