Accuracy of PERSIANN-CDR Precipitation Satellite Database in Simulation Assessment of Runoff in SWAT Model on Maharlu Basin

Document Type : Full length article


1 MSc in Water Resources Engineering, Aburaihan Campus, University of Tehran, Iran

2 Assistant Professor of Water Engineering, Aburaihan Campus, University of Tehran, Iran

3 Assistant Professor of Water Resources Engineering, Tarbiat Modares University, Iran

4 Associate Professor, Department of Meteorology, Natural Resources Faculty, Kurdistan University, Iran


Rainfall is the most important meteorological factor driving the hydrology of river basins. For the development and management of water resources, it is required to have a reliable coverage of rain gauges, rainfall satellite data and weather radars. Well-maintained ground-based rainfall stations give the best rainfall estimation with high accuracy over time for a small area. The spatial sampling error becomes higher in estimating rainfall when using interpolation techniques. This issue becomes particularly critical in data scarce regions with unevenly distributed rain gauge stations. This is recognized as one of the principal sources of uncertainty in hydrological modeling. Currently, with more and more global precipitation datasets developed, a decline is seen in the application of reanalysis products in hydrological modelling. As a hot research field, many studies focus on the application of directly measured precipitation data on flood risk evaluation at basin scales and discuss their potential for hydrological prediction of ungauged/poorly gauged basins. In this study, we used PERSIANN-CDR gridded database precipitation for modeling runoff in SWAT model in Maharlu Lake basin.
Materials and methods
The PERSIANN-CDR was used as a gridded database of precipitation for modeling runoff in SWAT model in Maharlu Lake basin. The PERSIANN-CDR is initially compared with rain gauged data and after that it was used as input to SWAT model. SWAT model was calibrated by rain gauge data during 1983 to 2013. The Warmup period set to 3 years. Three discharge stations were used for calibration. Correlation coefficient of, Nash-Sutcliff, POD, CSI, FAR, RMSE, ME and BIAS had been assessed to determine the accuracy of PERSIANN-CDR. SWAT model uncertainty and sensitivity were calculated in SWAT-CUP by SUFI2 method.  
Results and discussion
Comparing the PERSIANN-CDR in monthly scales, we found that this satellite wheatear database less estimates the variables in all months. The results showed average of correlation coefficient is 0.6 and RMSE showed a high error in rainy seasons. In SWAT model, calibration period was set to 1983 to 2010 with validation from 2011 to 2013. Calibration with gauged data showed satisfactory Nash-Sutcliff and R2 statistical indices about 0.6 for the area. The best result was occurred in Chenar-Sokhte-khosh discharge station, R2 was about 72% in calibration and 81% in validation. Calibration with PERSIANN-CDR database showed that this database is not good enough to be used in this semi-distributed model. In Chenar-Sokhte-khosh discharge station, R2 is calculated about 0.59 and Nash-Sutcliff about 0.21. R-factor and P-factor was presented about 0.5 in all discharge stations. These factors show that uncertainty calculation was occurred in good form. The simulation of annual runoff showed that the average runoff simulated using observation database was 1.68 m3/s, the mean runoff simulated by PERSIANN-CDR is 0.84 m3/s, and mean runoff of discharge stations were 1.77 cubic meters per second. On monthly scale, PERSIANN-CDR estimated less runoff like rainfall over all months. Both databases simulate runoff values relative to those recorded in the autumn months less than actual values. The results of this study, which were conducted using the PERSIANN-CDR satellite product, unlike the other studies with global exploratory bases, displayed that in the simulation with the SWAT model, this base cannot be accurately high in simulation. The error of estimating precipitation has been entered directly into the model and caused an error.
In this study, with the accuracy of precipitation data, PERSIANN-CDR satellite data on rainfall estimation revealed that this database estimated precipitation values less than real values in all months of the year. Runoff simulation using this satellite product expresses the explanatory factor and the efficiency of Nash-Sutcliff about 0.59 and 0.21.
Despites the time series of precipitation values, this satellite database has a high correlation with the actual values observed on rain-fed stations, but as the findings show the estimated rainfall values are always lower than actual recorded values. Based on the findings from this study, the PERSIANN-CDR satellite is not very accurate on the area of the Maharlou Lake Basin, located in eastern Zagros. In the semi-distributed SWAT model, it cannot simulate runoff. Therefore, it is suggested that before applying estimated rainfall data, this satellite database will have its error and bias values compared with the observed data on rain gauge stations and, then, the estimated precipitation values are corrected based on the bias.


Main Subjects

حاجی‏حسینی، ح.؛ حاجی‏حسینی، م.؛ نجفی، ع؛ مرید، س. و دلاور، م. (1393). ارزیابی تغییرات متغیرهای هواشناسی در بالادست حوضة هیرمند طی سدة گذشته با استفاده از داده‏های اقلیمی CRU و مدل SWAT، مجلة تحقیقات منابع آب، ۱۰(3): 38-52.
دارند، م. و زند کریمی، س. (1395). ارزیابی دقت داده‏های بارش مرکز اقلیم‏شناسی بارش جهانی بر روی ایران، مجلة ژئوفیزیک ایران، 10(۳): 95-113.
عینی، م.ر.؛ جوادی، س. و دلاور، م. (1397). ارزیابی عملکرد داده‏های بازتحلیل‏شدة پایگاه‏های اقلیمی جهانی CRU و NCEP CFSR  در شبیه‏سازی‏ هیدرولوژیکی مدلSWAT ، مطالعة موردی: حوضة آبریز مهارلو، مجلة تحقیقات منابع آب ایران، 14(۱):32-44.
عینی، م.ر.؛ جوادی، س.؛ دلاور، م. و دارند، م. (1397). ارزیابی داده‏های بارش پایگاه ملی اسفزاری در برآورد رواناب و پایش خشک‏سالی منطقه‏ای، مجلة اکوهیدرولوژی، 5(۱): 99-110.
غضنفری مقدم، م.؛ علیزاده، ا.؛ موسوی باسگی، م.؛ فرید حسینی، ع. و بنایان اول، م. (1390). مقایسة مدل PERSIANN با روش‏های درون‏یابی به منظور کاربرد در تخمین مقادیر بارندگی روزانه، نشریة آب و خاک، 1: ۲۰۷ـ215.
کتیرایی بروجردی، پ.‏س. (1392). مقایسة داده‏های بارش ماهانة ماهواره‏ای و زمینی در شبکه‏ای با تفکیک زیاد روی ایران، مجلة ژئوفیزیک ایران، 4: ۱۴۹ـ 160.
مسعودیان، ا.؛ کیخسروی کیانی، م.‏ص. و رعیت‏پیشه، ف. (1393). معرفی و مقایسة پایگاه دادة اسفزاری با پایگاه‏های دادة GPCC ،GPCP ، و CMAP، تحقیقات جغرافیایی، 29(۱): 73ـ 87.
Auerbach, D.A.; Easton, Z.M.; Walter, M.T.; Flecker, A.S. and Fuka, D.R (2016). Evaluating weather observations and the climate forecast system reanalysis as inputs for hydrologic modelling in the tropics, Hydrol. Process, 30: 3466-3477.
Casse, C.; Gosset, M.; Peugeot, C.; Pedinotti, V.; Boone, A.; Tanimoun, B.A. and Decharme, B. (2015). Potential of satellite rainfall products to predict Niger Riverflood events in Niamey, Atmos. Res., 163: 162-176.
Darand, M.; Amanollahi, J. and Zandkarimi, S. (2017). Evaluation of the performance of TRMM Multi-satellite Precipitation, Analysis (TMPA) estimation over Iran, Atmospheric Research, 190: 121-127.
Darand, M.; Zerafati, O.; Kefayatmotlagh, R. and Samandar, R. (2015). Comparison between global and regional precipitation data bases with base station Asfazari precipitation Iran, Geographical Research, 3: 30-47.
Darand, M. and Zand Karimi, S. (2016). Evaluation of the accuracy of the Global Precipitation Climatology Center (GPCC) data over Iran, Journal of Iran Geophysical, 103: 95-113.
Dile, Y.T. and Srinivasan, R. (2014). Evaluation of CFSR climate data for hydrologic prediction in data-scarce watersheds: An application in the Blue Nile River Basin, J. Am. Water Resour. Assoc., 50: 1226-1241.
Eini, M.R., Javadi, S. and Delavar, M. (2018). Evaluating the performance of CRU and NCEP CFSR global reanalysis climate datasets, in hydrological simulation by SWAT model, Case Study: Maharlu basin, Iran-Water Resources Research 14(1), 32-44 DOI: 10.13140/RG.2.2.24445.41444.
Eini, M.R., Javadi, S., Delavar, M., and Darand, M. (2018). Assessment of Asfezari national database precipitation data in runoff evaluating and monitoring regional drought, Iranian Journal of EcoHydrology, (5)1, 95-110,
Fuka, D.R.; Walter, M.T.; MacAlister, C.; Degaetano, A.T.; Steenhuis, T.S. and Easton, Z.M. (2014). Using the climate forecast system reanalysis as weather input data for watershed models, Hydrol. Process, 28: 5613-5623.
Ghazanfari, M.M.; Alizadeh, A.; Mosavi, B.M.; Farid, H.A. and Banaian, A.M. (2010). Comparing PERSIANN with interpolation methods in order to application estimation daily rainfall, Soil and Water Journal, 1: 207-215.
HajiHosseini, H.; HajiHosseini, M.R.; Morid, S. and Delavar, M. (2013). Assessment of changes in hydro-meteorological variables upstream of Helmand Basin during the last century using CRU data and SWAT model, Iran-Water Resources Research, 17: 38-52.
Katiraie-Boroujerdy, S.P. (2012). Comparing satellite and ground base monthly data rainfall in high spatial over Iran, Iran Geophysics Journal, 1: 149:160.
Katiraie-Boroujerdy, S.P.; Nasrollahi, N.; Hsu, KL. and Sorooshian, S. (2016). Quantifyin the reliability of four global datasets for drought monitoring over a semiarid region: Theor, Appl. Climatol., 123: 387-398.
Masoudian, A.; Keykhosravi, M. and Rayat Pisheh, F. (2015). Intruduction and evaluation Asafzari database with GPCC, GPCP, CMAP, Geographical Research, 19: 73-88.
Mei, Y.W.; Anagnostou, E.N.; Nikolopoulos, E.I. and Borga, M. (2014). Error analysis of satellite precipitation products in mountainous basins, J. Hydrometeorol, 15: 1778-1793.
Miao, C.; Ashouri, H.; Hsu, K-L.; Sorooshian, S. and Duan, Q. (2015). Evaluation of the PERSIANN-CDR daily rainfall estimates in capturing the behavior of extreme precipitation events over China, Journal of Hydrometeorology, 16: 1387-1396.
Monteiro, J.A.F.; Strauch, M.; Srinivasan, R.; Abbaspour, K. and Gücker, B. (2016). Accuracy of grid precipitation data for Brazil: Application in river discharge modelling of the Tocantins catchment, Hydrol. Process., 30: 1419-1430.
Neitsch, S.L.; Arnold, J.G.; Kiniry, J.R.; Srinivasan, R. and Williams, J.R. (2011). Soil and Water Assessment Tool, User Manual, Version 2012, Grassland, Soil and Water Research Laboratory, Temple, Tex, USA.
Nikolopoulos, E.I.; Anagnostou, E.N. and Borga, M. (2013). Using high-resolution satellite rain-fall products to simulate a major flash flood event in northern Italy, J. Hydrometeorol., 14: 171-185.
Nkiaka, E.; Nawaz, N. and Lovett, JC. (2017). Evaluating global reanalysis datasets as input for hydrological modelling in the sudano-sahel region, Hydrology, 4(1): 13.
Qian Z., Weidong Xuan; Li, Liu and Yue-Ping, Xu (2016). Evaluation and hydrological application of precipitation estimates derived from PERSIANN-CDR, TRMM 3B42V7, and NCEP-CFSR over humid regions in China, Hydrol. Process, 42: 1832-1861.
Thiemig, V.; Rojas, R.; Zambranobigiarini, M. and Roo, A.D. (2013). Hydrological evaluation of satellite-based rainfall estimates over the Volta and Baro-Akobo basin, J. Hydrol, 499: 324-338.
Volume 50, Issue 3
October 2018
Pages 563-576
  • Receive Date: 30 July 2017
  • Revise Date: 02 June 2018
  • Accept Date: 01 July 2018
  • First Publish Date: 23 September 2018