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TRMM ve GPM Uydu Verilerinden Belirlenen Yağış Haritalarının Su Bütçesi Hesaplamalarında Kullanılma Olanakları

Year 2018, 1. Uluslararası Tarımsal Yapılar ve Sulama Kongresi Özel Sayısı, 109 - 118, 31.12.2018

Abstract

Yağış önemli ölçüde konumsal ve zamansal
değişkenliğe sahip bir parametredir. Çoğunlukla yağış ölçüm istasyonlarının bir
havzadaki dağılımı hidrolojik su bütçesi çalışmalarında önemli bir eksiklik
oluşturmaktadır. Son yıllarda yağışın alansal dağılımının belirlenmesinde enterpolasyon
yöntemlerinin ve uzaktan algılama tekniklerinin kullanımı giderek artmaktadır. Ancak
enterpolasyon yöntemlerinin bir havzada kullanılması için yeterli sayıda
yağışölçer verisine ihtiyaç duyulmaktadır. Bu nedenle ölçüm verisinin olmadığı
veya az olduğu büyük ölçekli havzalarda uydu verilerine dayalı uzaktan algılama
teknolojisi oldukça yararlı sonuçlar elde edilebilmektedir. Bu çalışmanın
amacı, tropikal yağış ölçüm misyonu (TRMM) ve birleştirilmiş küresel yağış
ölçümü (GPM-IMERG) uydu verilerinden yağışın alansal dağılımının belirlenmesi
ve bu verilerin hidrolojik çalışmalarda kullanım olanaklarının
değerlendirilmesidir. Bu çalışma Kızılırmak havzasında yürütülmüştür. Bu amaçla
Kızılırmak havzasında 2013 (1 Ekim 2012 – 30 Eylül 2013) ve 2015 su yılları (1
Ekim 2014 – 30 Eylül 2015) için TRMM ve GPM uydu ürünleri temin edilmiş ve yağış
haritalandırılmıştır. Çalışma sonucunda, Kızılırmak havzası gibi büyük ölçekli
havzalarda TRMM ve GPM yağış uydu ürünlerinin çözünürleri ölçüsünde, havza su
bütçesi çalışmalarında kullanılabileceği sonucuna varılmıştır. Çalışma
kapsamında gelecekte yapılacak olan doğrulama ve kalibrasyon çalışmalarıyla,
TRMM ve GPM uydu verilerinin yağışölçer verileriyle doğrulanarak
kullanılabileceği değerlendirilmiştir.

References

  • Anonymous, 2016d https://asterweb.jpl.nasa.gov/gdem.asp
  • Anonymous, 2018a. https://www.nasa.gov/mission_pages/GPM/overview/index.html
  • Anonymous, 2018b. http://www.suyonetimi.gov.tr/Files/Havzakormaeylemplanraporlari/K%C4 %B1z%C4%B1l%C4%B1rmak_Havzas%C4%B1.pdf
  • Anonymous, 2018c. https://gdex.cr.usgs.gov/gdex/
  • Anonymous, 2018e. https://disc.gsfc.nasa.gov/datasets/TRMM_3B43_7/summary
  • Anonymous, 2018f. https://disc.gsfc.nasa.gov/datasets/GPM_3IMERGM_V05/summary
  • Anonymous, 2018g. http://mirador.gsfc.nasa.gov
  • Anonymous, 2018h. http://pmm.nasa.gov/GPM
  • Apan, M., 2009. Hidroloji Ders Kitabı. Ondokuz Mayıs Üniversitesi, Ziraat Fakültesi, No:52.
  • Casimiro, W. S. L., Labat, D., Guyot, J. L., Ronchail, J., ve Ordonez, J. J. 2009. TRMM rainfall data estimation over the Peruvian Amazon-Andes basin and its assimilation into a monthly water balance model. In New Approaches to Hydrological Prediction in Datasparse Regions, Proceedings of Symposium HS (Vol. 2).Collischonn, B., Collischonn, W., Tucci, C. E. M., 2008. Daily hydrological modeling in the Amazon basin using TRMM rainfall estimates. Journal of Hydrology 360: 207– 216.
  • Gourley, J.J., Vieux, B.E., 2006. A method for identifying sources of model uncertainty in rainfall-runoff simulations. Journal of Hydrology 327 (1–2), 68–80.Guo, H., Chen, S., Bao, A., Behrangi, A., Hong, Y., Ndayisaba, F. 2016. Early assessment of Integrated Multi-satellite Retrievals for Global Precipitation Measurement over China. Atmospheric Research 176–177 (2016) 121–133.
  • Güreşci, N. G., Seyrek, K. ve Sargın, A. H. 2012. Coğrafi Bilgi Sistemleri ile Hidroloji Uygulamaları, Devlet Su İşleri Genel Müdürlüğü, Teknoloji Dairesi Başkanlığı, CBS Şube Müdürlüğü.
  • He, X., Vejen, F., Stisen, S., Sonnenborg, T.O., Jensen, K.H., 2011. An operational weather radar-based quantitative precipitation estimation and its application in catchment water resources modeling. Vadose Zone Journal 10 (1), 8–24.
  • Hong, Y., Hsu, K.L., Sorooshian, S., Gao, X.G., 2004. Precipitation estimation from remotely sensed imagery using an Artificial Neural Network Cloud Classification System. J. Appl. Meteorol. 43, 1834–1852.
  • Hu, Q., Yang, D., Li, Z., Mishra, A. K., Wang, Y., ve Yang, H. 2014. Multi-scale evaluation of six high-resolution satellite monthly rainfall estimates over a humid region in China with dense rain gauges. International Journal of Remote Sensing, 35(4), 1272-1294.
  • Hu, Q., Yang, D., Wang, Y., Yang, H., 2013. Accuracy and spatio-temporal variation of high resolution satellite rainfall estimate over the Ganjiang River Basin. Sci. China Technol. Sci. 56, 853–865.
  • Huffman, G. J., Bolvin, D. T., Braithwaite, D., Hsu, K., Joyce, R., Xie, P., ve Yoo, S. H. 2017. NASA Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG). Algorithm Theoretical Basis Document (ATBD), NASA/GSFC, Greenbelt, MD, USA https://pmm.nasa.gov/sites/default/files/document_files/IMERG_ATBD_V5.1b.pdf
  • Huffman, G. J., Bolvin, D. T., Nelkin, E. J., Wolff, D. B., Adler, R. F., Gu, G., ... ve Stocker, E. F. 2007. The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor Precipitation Estimates at Fine Scales. Journal of Hydrometeorology, 8(1): 38-55.
  • Jiang, S., Ren, L., Yong, B., Yang, X., Shı, L., 2010. Evaluation of high-resolution satellite precipitation products with surface rain gauge observations from Laohahe Basin in northern China. Water Science and Engineering, 3(4): 405-417.
  • Joyce, R.J., Janowiak, J.E., Arkin, P.A., Xie, P.P., 2004. CMORPH: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution. Journal of Hydrometeorology, 5(3): 487-503.
  • Kubota, T., Shige, S., Hashizume, H., Ushio, T., Aonashi, K., Kachi, M., ve Okamoto, K. I. 2007. Global precipitation map using satellite-bornemicrowave radiometers by the GSMaP project: production and validation. IEEE Trans. Geosci. Remote Sens. 45, 2259–2275.
  • Kurtzman, D., Navon, S., Morin, E., 2009. Improving interpolation of Daily precipitation for hydrologic modelling: spatial patterns of preferred interpolators. Hydrological Processes 23, 3281–3291.
  • Li, D., Christakos, G., Ding, X., Wu, J., 2018. Adequacy of TRMM satellite rainfall data in driving the SWAT modeling of Tiaoxi catchment (Taihu lake basin, China), Journal of Hydrology 556: 1139–1152.
  • Li, X., Zhang, Q., Xu, C., 2012. Suitability of the TRMM satellite rainfalls in driving a distributed hydrological model for water balance computations in Xinjiang catchment, Poyang lake basin. Journal of Hydrology 426–427: 28–38.
  • Li, Z., Yang, D.W., Hong, Y., 2013. Multi-scale evaluation of high-resolution multi-sensor blended global precipitation products over the Yangtze River. J. Hydrol. 500, 157–169.
  • Okamoto, K., Ushio, T., Iguchi, T., Takahashi, N., Iwanami, K., 2005. The global satellite mapping of precipitation (GSMaP) project. Geoscience and Remote Sensing Symposium, 2005. IGARSS '05. Proceedings 2005 IEEE International, pp. 3414–3416.
  • Peleg, N., Ben-Asher, M., ve Morin, E. 2013. Radar subpixel-scale rainfall variability and uncertainty: lessons learned from observations of a dense rain-gauge network. Hydrology and Earth System Sciences, 17(6), 2195.
  • Sorooshian, S., Hsu, K. L., Gao, X., Gupta, H. V., Imam, B., ve Braithwaite, D. 2000. Evaluation of PERSIANN system satellite-based estimates of tropical rainfall. Bull. Am. Meteorol. Soc. 81 (9), 2035–2046.
  • Taesombat, W., and Sriwongsitanon, N. (2009). Areal rainfall estimation using spatial interpolation techniques. Science Asia, 35(3), 268-275.
  • Tan, M. L. Duan, Z., 2017. Assessment of GPM and TRMM Precipitation Products over Singapore. Remote Sens. 9(7), 720.
  • Tang, G., Behrangi, A., Long, D., Li, C., ve Hong, Y. 2018. Accounting for spatiotemporal errors of gauges: A critical step to evaluate gridded precipitation products. Journal of Hydrology, 559, 294-306.
  • Tang, G., Zeng, Z., Long, D., Guo, X., Yong, B., Zhang, W., ve Hong, Y. 2016. Statistical and hydrological comparisons between TRMM and GPM level-3 products over a midlatitude basin: Is day-1 IMERG a good successor for TMPA 3B42V7?. Journal of Hydrometeorology, 17(1), 121-137.
  • Tian, Y., Peters-Lidard, C.D., 2010. A global map of uncertainties in satellite-based precipitation measurements. Geophys. Res. Lett. 37(24).
  • Ward, A. D., Elliot, W. J. E. 1995. Environmental Hydrology. Boca Raton. New York.
  • Wilk, J., Kniveton, D., Andersson, L., Layberry, R., Todd, M.C., Hughes, D., Ringrose, S., Vanderpost, C., 2006. Estimating rainfall and water balance over the Okavango River Basin for hydrological applications. J. Hydrol. 331, 18–29.
  • Yang, N., Zhang, K., Hong, Y., Zhao, Q., Huang, Q., Xu, Y., Xue,X., Chen,S., 2017. Evaluation of the TRMM multisatellite precipitation analysis and its applicability in supporting reservoir operation and water resources management in Hanjiang basin, China. Journal of Hydrology 549: 313–325.
  • Yılmaz, M. U., Özgür, E., Yeğen, E. B. 2015. Coğrafi Bilgi Sistemleri Yardımıyla Havza Karakteristiklerinin Belirlenmesi. VII. Uluslar arası Katılımlı Atmosfer Bilimleri Sempozyumu, 28-30.
  • Yong, B., Chen, B., Gourley, J.J., Ren, L., Hong, Y., Chen, X., Wang, W., Chen, S., Gong, L., 2014. Intercomparison of the Version-6 and Version-7 TMPA precipitation products over high and low latitudes basins with independent gauge networks: is the newer version better in both real-time and post-real-time analysis for water resources and hydrologic ext. J. Hydrol. 508, 77–87.
  • Yong, B., Ren, L. L., Hong, Y., Wang, J. H., Gourley, J. J., Jiang, S. H., ... ve Wang, W. 2010. Hydrologic evaluation of Multisatellite Precipitation Analysis standard precipitation products in basins beyond its inclined latitude band: a case study in Laohahe basin, China. Water Resour. Res. 46 (7).

Using Opportunities of Precipitation Maps Generated by TRMM and GPM Satellite Products for Water Budget Calculations

Year 2018, 1. Uluslararası Tarımsal Yapılar ve Sulama Kongresi Özel Sayısı, 109 - 118, 31.12.2018

Abstract

Precipitation has significant spatial and temporal variability. Mostly the distribution of precipitation measuring stations in one basin is a major deficiency in water accounting studies. In recent years for determining the spatial distribution of precipitation, using of interpolation methods and remote sensing techniques are increasing. However, a sufficient number of raingauge data is needed to use interpolation methods in a basin. For this reason, in large scale basins with little or no measurement data, remote sensing technology based on satellite data can be very useful. The purpose of this study is to determine the spatial distribution of precipitation from TRMM and GPM satellite data and to evaluate the usage possibilities of these data in hydrological studies. This study was carried out in Kizilirmak Basin. For this purpose, In Kizilirmak Basin, TRMM and GPM satellite products are obtained for 2013 (October 1, 2012 - Sep 30 2013) and 2015 water years (October 1, 2014 - September 30, 2015) and precipitation maps were generated. As a result of this study, it was concluded that TRMM and GPM precipitation satellite products to the extent of resolutions, can be used in watershed water budget studies in large scale basins such as Kızılırmak basin. This study t has been evaluated that future validation and calibration studies, TRMM and GPM satellite data can be used by validating with raingauge data.

References

  • Anonymous, 2016d https://asterweb.jpl.nasa.gov/gdem.asp
  • Anonymous, 2018a. https://www.nasa.gov/mission_pages/GPM/overview/index.html
  • Anonymous, 2018b. http://www.suyonetimi.gov.tr/Files/Havzakormaeylemplanraporlari/K%C4 %B1z%C4%B1l%C4%B1rmak_Havzas%C4%B1.pdf
  • Anonymous, 2018c. https://gdex.cr.usgs.gov/gdex/
  • Anonymous, 2018e. https://disc.gsfc.nasa.gov/datasets/TRMM_3B43_7/summary
  • Anonymous, 2018f. https://disc.gsfc.nasa.gov/datasets/GPM_3IMERGM_V05/summary
  • Anonymous, 2018g. http://mirador.gsfc.nasa.gov
  • Anonymous, 2018h. http://pmm.nasa.gov/GPM
  • Apan, M., 2009. Hidroloji Ders Kitabı. Ondokuz Mayıs Üniversitesi, Ziraat Fakültesi, No:52.
  • Casimiro, W. S. L., Labat, D., Guyot, J. L., Ronchail, J., ve Ordonez, J. J. 2009. TRMM rainfall data estimation over the Peruvian Amazon-Andes basin and its assimilation into a monthly water balance model. In New Approaches to Hydrological Prediction in Datasparse Regions, Proceedings of Symposium HS (Vol. 2).Collischonn, B., Collischonn, W., Tucci, C. E. M., 2008. Daily hydrological modeling in the Amazon basin using TRMM rainfall estimates. Journal of Hydrology 360: 207– 216.
  • Gourley, J.J., Vieux, B.E., 2006. A method for identifying sources of model uncertainty in rainfall-runoff simulations. Journal of Hydrology 327 (1–2), 68–80.Guo, H., Chen, S., Bao, A., Behrangi, A., Hong, Y., Ndayisaba, F. 2016. Early assessment of Integrated Multi-satellite Retrievals for Global Precipitation Measurement over China. Atmospheric Research 176–177 (2016) 121–133.
  • Güreşci, N. G., Seyrek, K. ve Sargın, A. H. 2012. Coğrafi Bilgi Sistemleri ile Hidroloji Uygulamaları, Devlet Su İşleri Genel Müdürlüğü, Teknoloji Dairesi Başkanlığı, CBS Şube Müdürlüğü.
  • He, X., Vejen, F., Stisen, S., Sonnenborg, T.O., Jensen, K.H., 2011. An operational weather radar-based quantitative precipitation estimation and its application in catchment water resources modeling. Vadose Zone Journal 10 (1), 8–24.
  • Hong, Y., Hsu, K.L., Sorooshian, S., Gao, X.G., 2004. Precipitation estimation from remotely sensed imagery using an Artificial Neural Network Cloud Classification System. J. Appl. Meteorol. 43, 1834–1852.
  • Hu, Q., Yang, D., Li, Z., Mishra, A. K., Wang, Y., ve Yang, H. 2014. Multi-scale evaluation of six high-resolution satellite monthly rainfall estimates over a humid region in China with dense rain gauges. International Journal of Remote Sensing, 35(4), 1272-1294.
  • Hu, Q., Yang, D., Wang, Y., Yang, H., 2013. Accuracy and spatio-temporal variation of high resolution satellite rainfall estimate over the Ganjiang River Basin. Sci. China Technol. Sci. 56, 853–865.
  • Huffman, G. J., Bolvin, D. T., Braithwaite, D., Hsu, K., Joyce, R., Xie, P., ve Yoo, S. H. 2017. NASA Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG). Algorithm Theoretical Basis Document (ATBD), NASA/GSFC, Greenbelt, MD, USA https://pmm.nasa.gov/sites/default/files/document_files/IMERG_ATBD_V5.1b.pdf
  • Huffman, G. J., Bolvin, D. T., Nelkin, E. J., Wolff, D. B., Adler, R. F., Gu, G., ... ve Stocker, E. F. 2007. The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor Precipitation Estimates at Fine Scales. Journal of Hydrometeorology, 8(1): 38-55.
  • Jiang, S., Ren, L., Yong, B., Yang, X., Shı, L., 2010. Evaluation of high-resolution satellite precipitation products with surface rain gauge observations from Laohahe Basin in northern China. Water Science and Engineering, 3(4): 405-417.
  • Joyce, R.J., Janowiak, J.E., Arkin, P.A., Xie, P.P., 2004. CMORPH: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution. Journal of Hydrometeorology, 5(3): 487-503.
  • Kubota, T., Shige, S., Hashizume, H., Ushio, T., Aonashi, K., Kachi, M., ve Okamoto, K. I. 2007. Global precipitation map using satellite-bornemicrowave radiometers by the GSMaP project: production and validation. IEEE Trans. Geosci. Remote Sens. 45, 2259–2275.
  • Kurtzman, D., Navon, S., Morin, E., 2009. Improving interpolation of Daily precipitation for hydrologic modelling: spatial patterns of preferred interpolators. Hydrological Processes 23, 3281–3291.
  • Li, D., Christakos, G., Ding, X., Wu, J., 2018. Adequacy of TRMM satellite rainfall data in driving the SWAT modeling of Tiaoxi catchment (Taihu lake basin, China), Journal of Hydrology 556: 1139–1152.
  • Li, X., Zhang, Q., Xu, C., 2012. Suitability of the TRMM satellite rainfalls in driving a distributed hydrological model for water balance computations in Xinjiang catchment, Poyang lake basin. Journal of Hydrology 426–427: 28–38.
  • Li, Z., Yang, D.W., Hong, Y., 2013. Multi-scale evaluation of high-resolution multi-sensor blended global precipitation products over the Yangtze River. J. Hydrol. 500, 157–169.
  • Okamoto, K., Ushio, T., Iguchi, T., Takahashi, N., Iwanami, K., 2005. The global satellite mapping of precipitation (GSMaP) project. Geoscience and Remote Sensing Symposium, 2005. IGARSS '05. Proceedings 2005 IEEE International, pp. 3414–3416.
  • Peleg, N., Ben-Asher, M., ve Morin, E. 2013. Radar subpixel-scale rainfall variability and uncertainty: lessons learned from observations of a dense rain-gauge network. Hydrology and Earth System Sciences, 17(6), 2195.
  • Sorooshian, S., Hsu, K. L., Gao, X., Gupta, H. V., Imam, B., ve Braithwaite, D. 2000. Evaluation of PERSIANN system satellite-based estimates of tropical rainfall. Bull. Am. Meteorol. Soc. 81 (9), 2035–2046.
  • Taesombat, W., and Sriwongsitanon, N. (2009). Areal rainfall estimation using spatial interpolation techniques. Science Asia, 35(3), 268-275.
  • Tan, M. L. Duan, Z., 2017. Assessment of GPM and TRMM Precipitation Products over Singapore. Remote Sens. 9(7), 720.
  • Tang, G., Behrangi, A., Long, D., Li, C., ve Hong, Y. 2018. Accounting for spatiotemporal errors of gauges: A critical step to evaluate gridded precipitation products. Journal of Hydrology, 559, 294-306.
  • Tang, G., Zeng, Z., Long, D., Guo, X., Yong, B., Zhang, W., ve Hong, Y. 2016. Statistical and hydrological comparisons between TRMM and GPM level-3 products over a midlatitude basin: Is day-1 IMERG a good successor for TMPA 3B42V7?. Journal of Hydrometeorology, 17(1), 121-137.
  • Tian, Y., Peters-Lidard, C.D., 2010. A global map of uncertainties in satellite-based precipitation measurements. Geophys. Res. Lett. 37(24).
  • Ward, A. D., Elliot, W. J. E. 1995. Environmental Hydrology. Boca Raton. New York.
  • Wilk, J., Kniveton, D., Andersson, L., Layberry, R., Todd, M.C., Hughes, D., Ringrose, S., Vanderpost, C., 2006. Estimating rainfall and water balance over the Okavango River Basin for hydrological applications. J. Hydrol. 331, 18–29.
  • Yang, N., Zhang, K., Hong, Y., Zhao, Q., Huang, Q., Xu, Y., Xue,X., Chen,S., 2017. Evaluation of the TRMM multisatellite precipitation analysis and its applicability in supporting reservoir operation and water resources management in Hanjiang basin, China. Journal of Hydrology 549: 313–325.
  • Yılmaz, M. U., Özgür, E., Yeğen, E. B. 2015. Coğrafi Bilgi Sistemleri Yardımıyla Havza Karakteristiklerinin Belirlenmesi. VII. Uluslar arası Katılımlı Atmosfer Bilimleri Sempozyumu, 28-30.
  • Yong, B., Chen, B., Gourley, J.J., Ren, L., Hong, Y., Chen, X., Wang, W., Chen, S., Gong, L., 2014. Intercomparison of the Version-6 and Version-7 TMPA precipitation products over high and low latitudes basins with independent gauge networks: is the newer version better in both real-time and post-real-time analysis for water resources and hydrologic ext. J. Hydrol. 508, 77–87.
  • Yong, B., Ren, L. L., Hong, Y., Wang, J. H., Gourley, J. J., Jiang, S. H., ... ve Wang, W. 2010. Hydrologic evaluation of Multisatellite Precipitation Analysis standard precipitation products in basins beyond its inclined latitude band: a case study in Laohahe basin, China. Water Resour. Res. 46 (7).
There are 39 citations in total.

Details

Primary Language Turkish
Subjects Agricultural Engineering
Journal Section Research
Authors

Sakine Çetin

Eyüp Selim Köksal This is me

Emre Tunca

Publication Date December 31, 2018
Submission Date August 3, 2018
Acceptance Date November 20, 2018
Published in Issue Year 2018 1. Uluslararası Tarımsal Yapılar ve Sulama Kongresi Özel Sayısı

Cite

APA Çetin, S., Köksal, E. S., & Tunca, E. (2018). TRMM ve GPM Uydu Verilerinden Belirlenen Yağış Haritalarının Su Bütçesi Hesaplamalarında Kullanılma Olanakları. Ziraat Fakültesi Dergisi109-118.