Variable Infiltration-Capacity Model Sensitivity, Parameter Uncertainty, and Data Augmentation for the Diyala River Basin in Iraq
Publication: Journal of Hydrologic Engineering
Volume 25, Issue 9
Abstract
To construct a valid model, hydrologists face challenges in determining sensitivity to the forcing data and uncertainty in model parameters. These require basin data and forcing data from different sources, which may be incommensurate. The study reported here calibrated the Variable Infiltration-Capacity (VIC) platform to quantify model result sensitivity to model parameters and uncertainty in those parameters. The modeled basin was the Diyala River in Iraq, above the Derbendikhan Dam. The study produced the first complete set of daily forcing data for the basin using different sources. Besides ground observations from the Iraqi Ministry of Water Resources, two additional data sources were tested: Tropical Rainfall Measurement Mission (TRMM) and Global Implemented Data (GIDAL). Several methods were implemented to adjust the data, and model sensitivity and parameter uncertainty were examined by Generalized Likelihood Uncertainty Estimation (GLUE) and Differential Evolution Adaptive Metropolis (DREAM). Neither of these techniques had been applied before in Iraq. The VIC model was then calibrated manually using Kling–Gupta efficiency (KGE). The analyses indicate that neither TRMM nor GIDAL data are adequate for gridded precipitation analysis in the study basin. TRMM tends to underestimate and GIDAL tends to overestimate actual data. Multiplicative random cascade and Schaake Shuffle were used to determine daily precipitation data. A set of correction equations was developed to adjust GIDAL temperature and wind speed. Results for the GLUE and DREAM analyses imply that the depth of the second soil layer is the parameter that causes the most sensitivity in the model. The VIC model outputs were calibrated on a daily timescale with a KGE average of 0.743.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Some or all data, models, or code used during the study were provided by a third party. Direct requests for these materials may be made to the provider as indicated in the Acknowledgments. The data implemented in this study can be shared and conjugated with approval from the MoWR.
Acknowledgments
This study was funded by the Iraq Higher Committee for Education Development (HCED). The authors are grateful to the Iraqi Ministry of Water Resources for assistance. Data and models can be downloaded online (TRMM: https://pmm.nasa.gov/data-access/downloads/trmm; VIC, RVIC, GIDAL, and NND: https://uw-hydro.github.io/code/). The authors are also thankful to the editors and reviewers who offered insightful comments leading to the improvement of this paper. The authors are also grateful to Colorado State University for providing its laboratories and supercomputer to run the model(s) and perform the analyses.
References
Abbas, N., S. Wasimi, and N. Al-Ansari. 2016. “Impacts of climate change on water resources in Diyala River Basin, Iraq.” J. Civ. Eng. Archit. 10 (9): 1059–1074.
Abbaspour, K. C., and E. Rouholahnejad. 2015. “A continental-scale hydrology and water quality model for Europe: Calibration and uncertainty of a high-resolution large-scale SWAT model.” J. Hydrol. 524 (May): 733–752. https://doi.org/10.1016/j.jhydrol.2015.03.027.
Adam, J. C., E. A. Clark, D. P. Lettenmaier, and E. F. Wood. 2006. “Correction of global precipitation products for orographic effects.” J. Clim. 19 (1): 15–38. https://doi.org/10.1175/JCLI3604.1.
Adam, J. C., and D. P. Lettenmaier. 2003. “Adjustment of global gridded precipitation for systematic bias.” J. Geophys. Res. Atmos. 108 (D9). https://doi.org/10.1029/2001JD001489.
Adhikary, S. K., N. Muttil, and A. G. Yilmaz. 2017. “Cokriging for enhanced spatial interpolation of rainfall in two Australian catchments.” Hydrol. Processes 31 (12): 2143–2161. https://doi.org/10.1002/hyp.11163.
Al-Khafaji, M. S., and R. D. Al-Chalabi. 2019. “Assessment and mitigation of streamflow and sediment yield under climate change conditions in Diyala River Basin, Iraq.” Hydrology 6 (3): 63. https://doi.org/10.3390/hydrology6030063.
Alwan, I. A., I. Karim, and M. Mohamed. 2018. “Sediment predictions in Wadi Al-Naft using soil water assessment tool.” In Vol. 162 of Proc., MATEC Web of Conf. Les Ulis, France: EDP Sciences.
Benke, K. K., K. E. Lowell, and A. J. Hamilton. 2008. “Parameter uncertainty, sensitivity analysis and prediction error in a water-balance hydrological model.” Math. Comput. Modell. 47 (11): 1134–1149. https://doi.org/10.1016/j.mcm.2007.05.017.
Beven, K. 2006. “A manifesto for the equifinality thesis.” J. Hydrol. 320 (1): 18–36. https://doi.org/10.1016/j.jhydrol.2005.07.007.
Beven, K., and A. Binley. 1992. “The future of distributed models: Model calibration and uncertainty prediction.” Hydrol. Processes 6 (3): 279–298. https://doi.org/10.1002/hyp.3360060305.
Beven, K., and A. Binley. 2014. “GLUE: 20 years on.” Hydrol. Processes 28 (24): 5897–5918. https://doi.org/10.1002/hyp.10082.
Beven, K., and J. Freer. 2001. “Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology.” J. Hydrol. 249 (1–4): 11–29. https://doi.org/10.1016/S0022-1694(01)00421-8.
Chen, C., Z. Yu, L. Li, and C. Yang. 2011. “Adaptability evaluation of TRMM satellite rainfall and its application in the Dongjiang River Basin.” Procedia Environ. Sci. 10 (2011): 396–402. https://doi.org/10.1016/j.proenv.2011.09.065.
Choi, Y. S., C. K. Choi, H. S. Kim, K. T. Kim, and S. Kim. 2015. “Multi-site calibration using a grid-based event rainfall–runoff model: A case study of the upstream areas of the Nakdong River basin in Korea.” Hydrol. Processes 29 (9): 2089–2099. https://doi.org/10.1002/hyp.10355.
Clark, M., S. Gangopadhyay, L. Hay, B. Rajagopalan, and R. Wilby. 2004. “The Schaake shuffle: A method for reconstructing space–time variability in forecasted precipitation and temperature fields.” J. Hydrometeorol. 5 (1): 243–262. https://doi.org/10.1175/1525-7541(2004)005%3C0243:TSSAMF%3E2.0.CO;2.
Demaria, E. M., B. Nijssen, and T. Wagener. 2007. “Monte Carlo sensitivity analysis of land surface parameters using the Variable Infiltration Capacity model.” J. Geophys. Res. Atmos. 112 (D11). https://doi.org/10.1029/2006JD007534.
Duan, Z., W. G. M. Bastiaanssen, and J. Liu. 2012. “Monthly and annual validation of TRMM mulitisatellite precipitation analysis (TMPA) products in the Caspian Sea region for the period 1999–2003.” In Proc., 2012 IEEE Int. Geoscience and Remote Sensing Symp. New York: IEEE.
Evin, G., D. Kavetski, M. Thyer, and G. Kuczera. 2013. “Pitfalls and improvements in the joint inference of heteroscedasticity and autocorrelation in hydrological model calibration.” Water Resour. Res. 49 (7): 4518–4524. https://doi.org/10.1002/wrcr.20284.
Evin, G., M. Thyer, D. Kavetski, D. McInerney, and G. Kuczera. 2014. “Comparison of joint versus postprocessor approaches for hydrological uncertainty estimation accounting for error autocorrelation and heteroscedasticity.” Water Resour. Res. 50 (3): 2350–2375. https://doi.org/10.1002/2013WR014185.
Gao, H., Q. Tang, X. Shi, C. Zhu, T. Bohn, F. Su, J. Sheffield, M. Pan, D. Lettenmaier, and E. F. Wood. 2010. “Water budget record from variable infiltration capacity (VIC) model: Algorithm theoretical basis document for terrestrial water cycle data records.” Accessed September 9, 2018. https://eprints.lancs.ac.uk/id/eprint/89407/1/Gao_et_al_VIC_2014.pdf.
Guo, J., J. Zhou, J. Lu, Q. Zou, H. Zhang, and S. Bi. 2014. “Multi-objective optimization of empirical hydrological model for streamflow prediction.” J. Hydrol. 511 (Apr): 242–253. https://doi.org/10.1016/j.jhydrol.2014.01.047.
Gupta, H. V., H. Kling, K. K. Yilmaz, and G. F. Martinez. 2009. “Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling.” J. Hydrol. 377 (1–2): 80–91. https://doi.org/10.1016/j.jhydrol.2009.08.003.
Gupta, V. K., and E. C. Waymire. 1993. “A statistical analysis of mesoscale rainfall as a random cascade.” J. Appl. Meteorol. 32 (2): 251–267. https://doi.org/10.1175/1520-0450(1993)032%3C0251:ASAOMR%3E2.0.CO;2.
Guse, B., M. Pfannerstill, A. Gafurov, J. Kiesel, C. Lehr, and N. Fohrer. 2019. “Identifying the connective strength between model parameters and performance criteria.” Hydrol. Earth Syst. Sci. 21 (11): 5663–5679. https://doi.org/10.5194/hess-21-5663-2017.
Hamza, N. H. 2012. “Evaluation of water quality of Diyala River for irrigation purposes.” Diyala J. Eng. Sci. 5 (2): 82–98.
He, R., and B. Pang. 2014. “Sensitivity and uncertainty analysis of the Variable infiltration Capacity model in the upstream of Heihe River basin.” Proc. Int. Assoc. Hydrol. Sci. 8 (4): 312–316. https://doi.org/10.2166/wcc.2017.149.
Ishida, T., and S. Kawashima. 1993. “Use of cokriging to estimate surface air temperature from elevation.” Theor. Appl. Climatol. 47 (3): 147–157. https://doi.org/10.1007/BF00867447.
Jin, X., C.-Y. Xu, Q. Zhang, and V. P. Singh. 2010. “Parameter and modeling uncertainty simulated by GLUE and a formal Bayesian method for a conceptual hydrological model.” J. Hydrol. 383 (3–4): 147–155. https://doi.org/10.1016/j.jhydrol.2009.12.028.
Kang, B., and J. A. Ramírez. 2010. “A coupled stochastic space-time intermittent random cascade model for rainfall downscaling.” Water Resour. Res. 46 (10). https://doi.org/10.1029/2008WR007692.
Li, X., and V. Babovic. 2019. “A new scheme for multivariate, multisite weather generator with inter-variable, inter-site dependence and inter-annual variability based on empirical copula approach.” Clim. Dyn. 52 (3–4): 2247–2267. https://doi.org/10.1007/s00382-018-4249-5.
Li, Z. 2014. “A new framework for multi-site weather generator: A two-stage model combining a parametric method with a distribution-free shuffle procedure.” Clim. Dyn. 43 (3–4): 657–669. https://doi.org/10.1007/s00382-013-1979-2.
Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges. 1994. “A simple hydrologically based model of land surface water and energy fluxes for general circulation models.” J. Geophys. Res. Atmos. 99 (D7): 14415–14428. https://doi.org/10.1029/94JD00483.
Liang, X., E. F. Wood, and D. P. Lettenmaier. 1996. “Surface soil moisture parameterization of the VIC-2L model: Evaluation and modification.” Global Planet. Change 13 (1–4): 195–206. https://doi.org/10.1016/0921-8181(95)00046-1.
Liu, H. 2019. “Improved data uncertainty handling in hydrologic modeling and forecasting applications.” Master thesis, Dept. Civil and Environmental Engineering, Univ. of Waterloo.
Lohmann, D., E. Raschke, B. Nijssen, and D. P. Lettenmaier. 1998. “Regional scale hydrology. I: Formulation of the VIC-2L model coupled to a routing model.” Hydrol. Sci. J. 43 (1): 131–141. https://doi.org/10.1080/02626669809492107.
Lohmann, D. A. G., R. A. Nolte-Holube, and E. Raschke. 1996. “A large-scale horizontal routing model to be coupled to land surface parametrization schemes.” Tellus A48 (5): 708–721. https://doi.org/10.3402/tellusa.v48i5.12200.
Luo, W., M. C. Taylor, and S. R. Parker. 2008. “A comparison of spatial interpolation methods to estimate continuous wind speed surfaces using irregularly distributed data from England and Wales.” Int. J. Climatol. 28 (7): 947–959. https://doi.org/10.1002/joc.1583.
Maggioni, V., P. C. Meyers, and M. D. Robinson. 2016. “A review of merged high-resolution satellite precipitation product accuracy during the tropical rainfall measuring mission (TRMM) era.” J. Hydrometeorol. 17 (4): 1101–1117. https://doi.org/10.1175/JHM-D-15-0190.1.
Medhioub, E., M. Bouaziz, H. Achour, and S. Bouaziz. 2019. “Monthly assessment of TRMM 3B43 rainfall data with high-density gauge stations over Tunisia.” Arabian J. Geosci. 12 (2): 15. https://doi.org/10.1007/s12517-018-4155-5.
Mehta, A., and K. Markert. 2018. “Introduction to using the VIC model with NASA earth observations.” Accessed November 17, 2018. https://arset.gsfc.nasa.gov/sites/default/files/water/18-VIC/s1.pdf.
Moazami, S., S. Golian, Y. Hong, C. Sheng, and M. R. Kavianpour. 2016. “Comprehensive evaluation of four high-resolution satellite precipitation products under diverse climate conditions in Iran.” Hydrol. Sci. J. 61 (2): 420–440. https://doi.org/10.1080/02626667.2014.987675.
Molnar, P., and P. Burlando. 2005. “Preservation of rainfall properties in stochastic disaggregation by a simple random cascade model.” Atmos. Res. 77 (1): 137–151. https://doi.org/10.1016/j.atmosres.2004.10.024.
Montanari, A., et al. 2013. “‘Panta Rhei—Everything flows’: Change in hydrology and society—The IAHS scientific decade 2013–2022.” Hydrol. Sci. J. 58 (6): 1256–1275. https://doi.org/10.1080/02626667.2013.809088.
NASA (National Aeronautics and Space Administration). 2013. “Variable infiltration capacity (VIC) model manual: Step by step manual for setting up, running, calibrating, and validating of VIC model over GBM Basin.” Accessed January 10, 2017. http://128.95.45.89/Manual_VIC_V_1.1.pdf.
Nash, J. E., and J. V. Sutcliffe. 1970. “River flow forecasting through conceptual models. I: A discussion of principles.” J. Hydrol. 10 (3): 282–290. https://doi.org/10.1016/0022-1694(70)90255-6.
Nastos, P. T., J. Kapsomenakis, and K. C. Douvis. 2013. “Analysis of precipitation extremes based on satellite and high-resolution gridded data set over Mediterranean basin.” Atmos. Res. 131 (Sep): 46–59. https://doi.org/10.1016/j.atmosres.2013.04.009.
Nijssen, B., G. M. O’Donnell, D. P. Lettenmaier, D. Lohmann, and E. F. Wood. 2001a. “Predicting the discharge of global rivers.” J. Clim. 14 (15): 3307–3323. https://doi.org/10.1175/1520-0442(2001)014%3C3307:PTDOGR%3E2.0.CO;2.
Nijssen, B., R. Schnur, and D. P. Lettenmaier. 2001b. “Global retrospective estimation of soil moisture using the variable infiltration capacity land surface model, 1980–93.” J. Clim. 14 (8): 1790–1808. https://doi.org/10.1175/1520-0442(2001)014%3C1790:GREOSM%3E2.0.CO;2.
Over, T. M., and V. K. Gupta. 1994. “Statistical analysis of mesoscale rainfall: Dependence of a random cascade generator on large-scale forcing.” J. Appl. Meteorol. 33 (12): 1526–1542. https://doi.org/10.1175/1520-0450(1994)033%3C1526:SAOMRD%3E2.0.CO;2.
Over, T. M., and V. K. Gupta. 1996. “A space-time theory of mesoscale rainfall using random cascades.” J. Geophys. Res. Atmos. 101 (D21): 26319–26331. https://doi.org/10.1029/96JD02033.
Pagliero, L., F. Bouraoui, J. Diels, P. Willems, and N. McIntyre. 2019. “Investigating regionalization techniques for large-scale hydrological modelling.” J. Hydrol. 570 (Mar): 220–235. https://doi.org/10.1016/j.jhydrol.2018.12.071.
Pang, B., R. He, and L. Zhang. 2014. “Parameter estimation and uncertainty analysis of the variable infiltration capacity model in the Xitiaoxi catchment.” In Proc., 6th Int. Conf. of Flood Management. São Paulo, Brazil: Brazilian Water Resource Association.
Patnaik, S., V. C. Sharma, and B. Biswal. 2019. “Evaluation of an instantaneous dryness index-based calibration-free continuous hydrological model in India.” Hydrol. Res. 50 (3): 915–924. https://doi.org/10.2166/nh.2019.081.
Peel, M. C., B. L. Finlayson, and T. A. McMahon. 2007. “Updated world map of the Köppen-Geiger climate classification.” Hydrol. Earth Syst. Sci. Discuss. 4 (2): 439–473. https://doi.org/10.5194/hessd-4-439-2007.
Pidwirny, M. 2006. “Climate classification and climatic regions of the world.” In Fundamentals of physical geography. 2nd ed. Okanagan, Canada: Cengage Learning.
Pradhan, A., and J. Indu. 2019. “Uncertainty in calibration of variable infiltration capacity model.” In Hydrology in a changing world, 89–108. Cham, Switzerland: Springer.
Quan, Z., J. Teng, W. Sun, T. Cheng, and J. Zhang. 2015. “Evaluation of the HYMOD model for rainfall–runoff simulation using the GLUE method.” Proc. Int. Assoc. Hydrol. Sci. 368 (2015): 180–185. https://doi.org/10.5194/piahs-368-180-2015.
Schoups, G., and J. A. Vrugt. 2010. “A formal likelihood function for parameter and predictive inference of hydrologic models with correlated, heteroscedastic, and non-Gaussian errors.” Water Resour. Res. 46 (10). https://doi.org/10.1029/2009WR008933.
Shafii, M., B. Tolson, and L. S. Matott. 2015. “Addressing subjective decision-making inherent in GLUE-based multi-criteria rainfall–runoff model calibration.” J. Hydrol. 523 (Apr): 693–705. https://doi.org/10.1016/j.jhydrol.2015.01.051.
Song, W., W. Ye, and Y. Li. 2019. “The study of the variation law of TRMM rainfall measurement precision on time scale.” In Vol. 252 of Proc., IOP Conf. Series: Earth and Environmental Science. Bristol, UK: IOP Publishing.
Sood, A., and V. Smakhtin. 2015. “Global hydrological models: A review.” Hydrol. Sci. J. 60 (4): 549–565. https://doi.org/10.1080/02626667.2014.950580.
Steinschneider, S., S. Wi, and C. Brown. 2015. “The integrated effects of climate and hydrologic uncertainty on future flood risk assessments.” Hydrol. Processes 29 (12): 2823–2839. https://doi.org/10.1002/hyp.10409.
Sun, R., and H. Yuan. 2013. “Hydrological ensemble simulation in Huaihe catchment based on VIC model.” In Proc., AGU Fall Meeting Abstracts. Washington, DC: American Geophysical Union.
Sun, W., H. Ishidaira, and S. Bastola. 2012. “Calibration of hydrological models in ungauged basins based on satellite radar altimetry observations of river water level.” Hydrol. Processes 26 (23): 3524–3537. https://doi.org/10.1002/hyp.8429.
Surfleet, C. G., D. Tullos, H. Chang, and I.-W. Jung. 2012. “Selection of hydrologic modeling approaches for climate change assessment: A comparison of model scale and structures.” J. Hydrol. 464 (Sep): 233–248. https://doi.org/10.1016/j.jhydrol.2012.07.012.
Tarek, M. H., A. Hassan, J. Bhattacharjee, S. H. Choudhury, and A. B. M. Badruzzaman. 2017. “Assessment of TRMM data for precipitation measurement in Bangladesh.” Meteorol. Appl. 24 (3): 349–359. https://doi.org/10.1002/met.1633.
Tofiq, F. A., and A. Guven. 2014. “Prediction of design flood discharge by statistical downscaling and general circulation models.” J. Hydrol. 517 (Sep): 1145–1153. https://doi.org/10.1016/j.jhydrol.2014.06.028.
Vrac, M., and P. Friederichs. 2015. “Multivariate—Intervariable, spatial, and temporal—Bias correction.” J. Clim. 28 (1): 218–237. https://doi.org/10.1175/JCLI-D-14-00059.1.
Vrugt, J. A. 2016. “Markov chain Monte Carlo simulation using the DREAM software package: Theory, concepts, and MATLAB implementation.” Environ. Modell. Software 75 (Jan): 273–316. https://doi.org/10.1016/j.envsoft.2015.08.013.
Vrugt, J. A., and W. Bouten. 2002. “Validity of first-order approximations to describe parameter uncertainty in soil hydrologic models.” Soil Sci. Soc. Am. J. 66 (6): 1740–1751. https://doi.org/10.2136/sssaj2002.1740.
Vrugt, J. A., C. J. F. Ter Braak, C. G. H. Diks, B. A. Robinson, J. M. Hyman, and D. Higdon. 2009a. “Accelerating Markov chain Monte Carlo simulation by differential evolution with self-adaptive randomized subspace sampling.” Int. J. Nonlinear Sci. Numer. Simul. 10 (3): 273–290. https://doi.org/10.1515/IJNSNS.2009.10.3.273.
Vrugt, J. A., C. J. F. Ter Braak, H. V. Gupta, and B. A. Robinson. 2009b. “Equifinality of formal (DREAM) and informal (GLUE) Bayesian approaches in hydrologic modeling?” Stochastic Environ. Res. Risk Assess. 23 (7): 1011–1026. https://doi.org/10.1007/s00477-008-0274-y.
Xue, X., K. Zhang, Y. Hong, J. J. Gourley, W. Kellogg, R. A. McPherson, Z. Wan, and B. N. Austin. 2015. “New multisite cascading calibration approach for hydrological models: Case study in the Red River Basin using the VIC model.” J. Hydrol. Eng. 21 (2): 05015019. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001282.
Yen, H., X. Wang, D. G. Fontane, R. D. Harmel, and M. Arabi. 2014. “A framework for propagation of uncertainty contributed by parameterization, input data, model structure, and calibration/validation data in watershed modeling.” Environ. Modell. Software 54 (Apr): 211–221. https://doi.org/10.1016/j.envsoft.2014.01.004.
Information & Authors
Information
Published In
Journal of Hydrologic Engineering
Volume 25 • Issue 9 • September 2020
Copyright
©2020 American Society of Civil Engineers.
History
Received: Oct 31, 2019
Accepted: Apr 10, 2020
Published online: Jun 27, 2020
Published in print: Sep 1, 2020
Discussion open until: Nov 27, 2020
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.