Integration of HEC-HMS Model with the Satellite-based High Spatiotemporal Resolution Dataset for Applying in Flood Simulation

Document Type : Original Article

Authors

1 Water engineering department, IKIU university, Qazvin, Iran

2 water engineering department, IKIU university, Qazvin, Iran

3 Researcher, Research Institute for Geo-Hydrological Protection IRPI, Rome, Italy.

Abstract

Flood simulation using the hydrological model requires an appropriate rainfall dataset and unfortunately, in most parts of the Iran country the spatiotemporal resolution and density of ground gauges aren’t suitable. Hence, using remotely sensed high spatiotemporal resolution datasets can be useful for filling this gap. The main objective of this research is the assessment of PERSIANN-CCs hourly rainfall dataset for simulation of flood hydrograph using HEC-HMS event-based model at the Asalem river basin (ARB), Iran. Furthermore, to better evaluation of this model, three different spatial scenarios (including lumped, Thiessen and link-lumped) at 1, 3 and 6 hour time steps are used. Findings showed that using of link-lumped scenario at 3 and 6-hour time steps for simulation of flood hydrograph leads to the best results.
For example, in this case, the average values of Nash-Sutcliffe efficiency (NSE) and Correlation Coefficient (CC) values for all events are about 0.58 and 0.78 (for Δt= 3 hr) and 0.56 and 0.74 (for Δt= 6 hr), respectively. Moreover, if the main purpose of modeling is the accurate estimation of peak flow, using the second spatial scenario leads to minimum error (with the relative error ranging between 0.2 and 7.6 %) at 1 and 3 hr time steps, while the third spatial scenario(link-lumped) hasn’t the required potential for simulation of peak flow. Also, combing the first spatial scenario and PERSIANN- CCs dataset is the best case for estimation of time to peak (Tp) which is very important in flood warning systems. Findings of this study indicate that in the lack of ground observations, the high spatiotemporal resolution rainfall datasets such as PERSIANN-CCs can be used for flood simulation.

Keywords


Azizian, A and Ramezani, H. 2019. Assessing the Accuracy of European Center for Medium Range Weather Forecasts (ECMWF) Reanalysis Datasets for Estimation of Daily and Monthly Precipitation. Iranian Journal of Soil and Water Research. 50 (40): 777-791.
Ahmadi, M., Dadashi, A.A. and Deyrmajai, A. 2019. Runoff Estimation Using the IHACRES Model Based on CHIRPS Satellite Data and CMIP5 Models (Case Study: Gorganroud Basin- Aq Qala Area). Iranian Journal of Soil and Water Research (under publishing).
Alijanian, M., Rakhshandehroo, G.R., Mishra, A.K. and Dehghani, M. 2017. Evaluation of satellite rainfall climatology using CMORPH, PERSIANN-CDR, PERSIANN, TRMM, MSWEP over Iran. International Journal of Climatology 37(14): 4896–4914.
Azizian, A and Ramezani, H. 2019. Assessing the Accuracy of European Center for Medium Range Weather Forecasts (ECMWF) Reanalysis Datasets for Estimation of Daily and Monthly Precipitation. Iranian Journal of Soil and Water Research. 50 (40): 777-791.
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.
Foglia, L. Hill, M.C. Mehl, S.W. and Burlando, P. 2009. Sensitivity analysis, calibration, and testing of a distributed hydrological model using error‐based weighting and one objective function. Water Resources Research, 45(6).
Hong, Y. Hsu, K.L. Sorooshian, S. and Gao, X. 2004. Precipitation estimation from remotely sensed information using artificial neural network cloud classification system. Journal of Applied Meteorology, 43(12): 1834–1853.
Hong, Y. Ren, LL. Gourley, JJ. Huffman, GJ. Chen, X. Wang, W. and Khan, S. 2012. Assessment of evolving TRMM based multi-satellite real-time precipitation estimation methods and their impacts on hydrologic prediction in a high latitude basin. Journal of Geophys Research. 117, D09108.
Hosseini-Moghari, S.M., Araghinejad, S. and Ebrahimi, K. 2018. Spatio-temporal evaluation of global gridded precipitation datasets across Iran. Hydrological Sciences Journal. Taylor & Francis 63(11): 1669–1688.
Huffman, G.J. and Bolvin, D.T. 2013. TRMM and other data precipitation data set documentation. NASA. Greenbelt USA 28.
Jamli, J.B, 2015. Validation of satellite-based PERSIANN rainfall estimates using surface-based APHRODITE data over Iran. Journal of Earth Sci., 4: 150–160.
Joyce, R.J., Janowiak, J.E., Arkin, P.A. and Xie, 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(2): 487-503.
Katiraie-Boroujerdy, P.S., Nasrollahi, N., Hsu, K. and Sorooshian, S. .2013. Evaluation of satellite-based precipitation estimation over Iran. Journal of Arid Environments. Elsevier Ltd 97(3): 205–219.
Koohi, S., Azizian, A. and Brocca, L. 2019. Calibration of VIC-3L Hydrological Model using Satellite-Based Surface Soil Moisture Datasets. Iran-Water Resources Research, 15(4): 55-67.
Li, J., Yuan, D., Liu, J., Jiang, Y., Chen, Y., Hsu, K.L. and Sorooshian, S. 2019. Predicting floods in a large karst river basin by coupling PERSIANN-CCS QPEs with a physically based distributed hydrological model. Journal of Hydrology and Earth System Sciences. 23 (3): 1505-1532.
Li, Z. Yang, D. and Hong, Y. 2013. Multi-scale evaluation of high-resolution multi-sensor blended global precipitation products over the Yangtze River. Journal of Hydrology, 500, pp.157-169.
Moazami, S. Golian, S. Hong, Y. Sheng, C. and Kavianpour, M.R. 2016. Comprehensive evaluation of four high-resolution satellite precipitation products under diverse climate conditions in Iran. Hydrological Sciences Journal, 61(2): 420-440.
Moriasi, D.N., Arnold, J.G., Van liew, M.W., Bingener, R.L., Harmel, R.D., and Veith, T.L. (2007). Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE. 50: 3. 885-900.
Parisooj, P., Goharnejad, H. and Moazami, S. 2018. Rainfall-Runoff Hydrologic Simulation Using Adjusted Satellite Rainfall Algorithms, a Case Study: Voshmgir Dam Basin. Golestan. Iran-Water Resources Research, 14(3): 140-159.
Prakash, SC. Mahesh, R. Gairola, M. Pal, PK. 2010. Estimation of Indian summer monsoon rainfall using Kalpana-1 VHRR data and its validation using rain gauge and GPCP data. Journal of Meteorology and Atmospheric Physics. 110(1-2), 45.
Qi, W et al. 2016. Evaluation of global fine-resolution precipitation products and their uncertainty quantification in ensemble discharge simulations. Hydrology and Earth System Sciences, 20: 903–920.
Rahmati, A. and Masahbavani, A.R. 2019. Evaluation of the global rainfall datasets for use in physical models, Case study: Karoon Basin. Iran- Water Resources Research, 15 (1): 178-192.
Shayeghi, A., Azizian, A. and Brocca, L. 2020. The Reliability of Reanalysis and Remotely Sensed Precipitation Products for Hydrological Simulation over the SRB, Iran. Hydrological Sciences Journal. 65 (2): 296-310.
USACE .2017. HEC-HMS user’s manual, Davis, CA. USA.
Yong, B. et al. 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 Resources Research, 46, W07542.