Cheng Yao, Zhi-jia Li, Ke Zhang, Ying-chun Huang, Jing-feng Wang, Satish Bastola. 2022: Evaluating performance dependency of a geomorphologic instantaneous unit hydrograph-based hydrological model on DEM resolution. Water Science and Engineering, 15(3): 179-188. doi: 10.1016/j.wse.2022.04.002
Citation: Cheng Yao, Zhi-jia Li, Ke Zhang, Ying-chun Huang, Jing-feng Wang, Satish Bastola. 2022: Evaluating performance dependency of a geomorphologic instantaneous unit hydrograph-based hydrological model on DEM resolution. Water Science and Engineering, 15(3): 179-188. doi: 10.1016/j.wse.2022.04.002

Evaluating performance dependency of a geomorphologic instantaneous unit hydrograph-based hydrological model on DEM resolution

doi: 10.1016/j.wse.2022.04.002
Funds:

This work was supported by the National Natural Science Foundation of China (Grants No. 51979070 and 52079035), the National Key Research and Development Program of China (Grant No. 2018YFC1508103), the Natural Science Foundation of Jiangsu Province (Grant No. BK20180022), and the Six Talent Peaks Project in Jiangsu Province (Grant No. NY-004).

  • Received Date: 2021-10-20
  • Accepted Date: 2022-03-24
  • Rev Recd Date: 2022-03-24
  • Available Online: 2022-08-24
  • The digital elevation model (DEM) is a type of model that has been widely used in terrain analysis and hydrological modeling. DEM resolution influences the hydrological and geomorphologic features of delineated catchments and consequently affects hydrological simulations. This study investigated the impacts of DEM resolution on the performance of the XAJ-GIUH hydrological model, a model coupling the widely used Xinanjiang (XAJ) hydrological model with the geomorphologic instantaneous unit hydrograph (GIUH), in flood simulations in small and medium-sized catchments. To test the model performance, the model parameters were calibrated at a fine DEM resolution (30 m) and then directly transferred to the simulation runs using coarser DEMs. Afterwards, model recalibration was conducted at coarser DEM resolutions. In the simulation runs with the model parameters calibrated at the 30-m resolution, the DEM resolution slightly affected the overall shape of the simulated flood hydrographs but presented a greater impact on the simulated peak discharges in the two study catchments. The XAJ-GIUH model consistently underestimated the peak discharges when the DEM resolution became coarser. The qualified ratio of peak simulations decreased by 35% when the DEM resolution changed from 30 m to 600 m. However, model recalibration produced comparable model performances when DEMs with different resolutions were used. This study showed that the impact of DEM resolution on model performance can be mitigated by model recalibration to some extent, if the DEM resolution is not too coarse.

     

  • [1]
    Beven, K., 2012. Rainfall-Runoff Modelling: The Primer, Second Edition. Wiley-Blackwell, Chichester
    [2]
    Beven, K., 2019. How to make advances in hydrological modelling. Hydrology Research 50(6), 1481-1494. https://doi.org/10.2166/nh.2019.134
    [3]
    Bhadra, A., Panigrahy, N., Singh, R., Raghuwanshi, N.S., Mal, B.C., Tripathi, M.P., 2008. Development of a geomorphological instantaneous unit hydrograph model for scantily gauged watersheds. Environmental Modelling & Software 23(8), 1013-1025. https://doi.org/10.1016/j.envsoft.2007.08.008
    [4]
    Blair, G.S., Beven, K., Lamb, R., Bassett, R., Cauwenberghs, K., Hankin, B., Dean, G., Hunter, N., Edwards, L., Nundloll, V., Samreen, F., Simm, W., Towe, R., 2019. Models of everywhere revisited: A technological perspective. Environmental Modelling & Software 122, 104521. https://doi.org/10.1016/j.envsoft.2019.104521
    [5]
    Chao, L.J., Zhang, K., Li, Z.J., Wang, J.F., Yao, C., Li, Q.L., 2019. Applicability assessment of the CASCade Two Dimensional SEDiment (CASC2D-SED) distributed hydrological model for flood forecasting across four typical medium and small watersheds in China. Journal of Flood Risk Management 12, e12518. https://doi.org/10.1111/jfr3.12518
    [6]
    Chao, L.J., Zhang, K., Yang, Z.L., Wang, J., Liu, P., Liang, J., Li, Z.J., Gu, Z., 2021. Improving flood simulation capability of the WRF-Hydro-RAPID model using a multi-source precipitation merging method. Journal of Hydrology 592, 125814. https://doi.org/10.1016/j.jhydrol.2020.125814
    [7]
    Chaubey, I., Cotter, A.S., Costello, T.A., Soerens, T.S., 2005. Effect of DEM data resolution on SWAT output uncertainty. Hydrological Processes 19(3), 621-628. https://doi.org/10.1002/hyp.5607
    [8]
    Chavan, S.R., Srinivas, V.V., 2015. Effect of DEM source on equivalent Horton-Strahler ratio based GIUH for catchments in two Indian river basins. Journal of Hydrology 528, 463-489. https://doi.org/10.1016/j.jhydrol.2015.06.049
    [9]
    Chen, Y.B., Shi, P., Ji, X.M., Qu, S.M., Zhao, L.L., Dong, F.C., 2019. New method to calculate the dynamic factor-flow velocity in geomorphologic instantaneous unit hydrograph. Scientific Reports 9, 14201. https://doi.org/10.1038/S41598-019-50723-X
    [10]
    Clark, M.P., Bierkens, M.F.P., Samaniego, L., Woods, R.A., Uijlenhoet, R., Bennett, K.E., Pauwels, V.R.N., Cai, X., Wood, A.W., Peters-Lidard, C.D., 2017. The evolution of process-based hydrologic models: Historical challenges and the collective quest for physical realism. Hydrology and Earth System Sciences 21(7), 3427-3440. https://doi.org/10.5194/hess-21-3427-2017
    [11]
    DaRos, D., Borga, M., 1997. Use of digital elevation model data for the derivation of the geomorphological instantaneous unit hydrograph. Hydrological Processes 11(1), 13-33. https://doi.org/10.1002/(SICI)1099-1085(199701)11:1<13::AID-HYP400>3.0.CO;2-M
    [12]
    Dixon, B., Earls, J., 2009. Resample or not?! Effects of resolution of DEMs in watershed modeling. Hydrological Processes 23(12), 1714-1724. https://doi.org/10.1002/hyp.7306
    [13]
    Duan, Q., Sorooshian, S., Gupta, V., 1992. Effective and efficient global optimization for conceptual rainfall-runoff models. Water Resources Research 28(4), 1015-1031. https://doi.org/10.1029/91WR02985
    [14]
    Gong, J.F., Yao, C., Li, Z.J., Chen, Y.F., Huang, Y.C., Tong, B.X., 2021. Improving the food forecasting capability of the Xinanjiang model for small- and medium-sized ungauged catchments in South China. Natural Hazards 106, 2077-2109. https://doi.org/10.1007/s11069-021-04531-0
    [15]
    Grimaldi, S., Petroselli, A., Nardi, F., 2012. A parsimonious geomorphological unit hydrograph for rainfall-runoff modelling in small ungauged basins. Hydrological Science Journal 57(1), 73-83. https://doi.org/10.1080/02626667.2011.636045
    [16]
    Gupta, V., Waymire, E., Wang, C., 1980. A representation of an instantaneous unit hydrograph from geomorphology. Water Resources Research 16(5), 855-862. https://doi.org/10.1029/WR016i005p00855
    [17]
    Habtezion, N., Tahmasebi Nasab, M., Chu, X., 2016. How does DEM resolution affect microtopographic characteristics, hydrologic connectivity, and modelling of hydrologic processes? Hydrological Processes 30(25), 4870-4892. https://doi.org/10.1002/hyp.10967
    [18]
    Hrachowitz, M., Savenije, H.H.G., Bloschl, G., McDonnell, J.J., Sivapalan, M., Pomeroy, J.W., Arheimer, B., Blume, T., Clark, M.P., Ehret, U., et al., 2013. A decade of Predictions in Ungauged Basins (PUB): A review. Hydrological Sciences Journal 58(6), 1198-1255. https://doi.org/10.1080/02626667.2013.803183
    [19]
    Khaing, Z.M., Zhang, K., Sawano, H., Shrestha, B.B., Sayama, T., Nakamura, K., 2019. Flood hazard mapping and assessment in data-scarce Nyaungdon area, Myanmar. PLoS One 14(11), e0224558. https://doi.org/10.1371/journal.pone.0224558
    [20]
    López-Vicente, M., Álvarez, S., 2018. Influence of DEM resolution on modelling hydrological connectivity in a complex agricultural catchment with woody crops. Earth Surface Processes and Landforms 43(7), 1403-1415. https://doi.org/10.1002/esp.4321
    [21]
    Maidment, D., Olivera, F., Calver, A., Eatherall, A., Fraczek, W., 1996. Unit hydrograph derived from a spatially distributed velocity field. Hydrological Processes 10, 831-844. https://doi.org/10.1002/(SICI)1099-1085(199606)10:6<831::AID-HYP374>3.0.CO;2-N
    [22]
    Moglen, G.E., Hartman, G.L., 2001. Resolution effects on hydrologic modeling parameters and peak discharge. Journal of Hydrologic Engineering 6(6), 490-497. https://doi.org/10.1061/(Asce)1084-0699(2001)6:6(490)
    [23]
    Mu, D.R., Luo, P.P., Lyu, J., Zhou, M.M., Huo, A.D., Duan, W.L., Nover, D., He, B., Zhao, X.L., 2021. Impact of temporal rainfall patterns on flash floods in Hue City, Vietnam. Journal of Flood Risk Management 14(1), e12668. https://doi.org/10.1111/jfr3.12668
    [24]
    Munoth, P., Goyal, R., 2019. Effects of DEM source, spatial resolution and drainage area threshold values on hydrological modeling. Water Resources Management 33(6), 3303-3319. https://doi.org/10.1007/s11269-019-02303-x
    [25]
    Reddy, A.S., Reddy, M.J., 2015. Evaluating the influence of spatial resolutions of DEM on watershed runoff and sediment yield using SWAT. Journal of Earth System Science 124(7), 1517-1529. https://doi.org/10.1007/s12040-015-0617-2
    [26]
    Rodriguez-Iturbe, I., Valdes, J., 1979. The geomorphological structure of hydrologic response. Water Resources Research 15(6), 1409-1420. https://doi.org/10.1029/WR015i006p01409
    [27]
    Rui, X.F., Yu, M., Liu, F.G., Gong, X.L., 2008. Calculation of watershed flow concentration based on the grid drop concept. Water Science and Engineering 1(1), 1-9. https://doi.org/10.1016/S1674-2370(15)30013-2
    [28]
    Sahoo, R., Jain, V., 2018. Sensitivity of drainage morphometry based hydrological response (GIUH) of a river basin to the spatial resolution of DEM data. Computers & Geosciences 111, 78-86. https://doi.org/10.1016/j.cageo.2017.10.001
    [29]
    Valeo, C., Moin, S.M.A., 2000. Grid-resolution effects on a model for integrating urban and rural areas. Hydrological Processes 14(14), 2505-2525. https://doi.org/10.1002/1099-1085(20001015)14:14<2505::AID-HYP111>3.0.CO;2-3
    [30]
    Vieux, B.E., 2001. Distributed Hydrologic Modeling Using GIS. Kluwer Academic Publishers, Dordrecht
    [31]
    Vivoni, E.R., Ivanov, V.Y., Bras, R.L., Entekhabi, D., 2005. On the effects of triangulated terrain resolution on distributed hydrologic model response. Hydrological Processes 19(11), 2101-2122. https://doi.org/10.1002/hyp.5671
    [32]
    Wei, X.D., Wang, N., Luo, P.P., Yang, J., Zhang, J., Lin, K.L., 2021. Spatiotemporal assessment of land marketization and its driving forces for sustainable urban-rural development in Shaanxi Province in China. Sustainability 13(14), 7755. https://doi.org/10.3390/su13147755
    [33]
    Wilby, R.L., 2019. A global hydrology research agenda fit for the 2030s. Hydrology Research 50(6), 1464-1480. https://doi.org/10.2166/nh.2019.100
    [34]
    Xu, C., 2021. Issues influencing accuracy of hydrological modeling in a changing environment. Water Science and Engineering 14(2), 167-170. https://doi.org/10.1016/j.wse.2021.06.005
    [35]
    Yang, P., Ames, D.P., Fonseca, A., Anderson, D., Shrestha, R., Glenn, N.F., Cao, Y., 2014. What is the effect of LiDAR-derived DEM resolution on large-scale watershed model results? Environmental Modelling & Software 58, 48-57. https://doi.org/10.1016/j.envsoft.2014.04.005
    [36]
    Yao, C., Li, Z.J., Bao, H.J., Yu, Z.B., 2009. Application of a developed grid-Xinanjiang model to chinese watersheds for flood forecasting purpose. Journal of Hydrologic Engineering 14(9), 923-934. https://doi.org/10.1061/(Asce)He.1943-5584.0000067
    [37]
    Yao, C., Li, Z.J., Yu, Z.B., Zhang, K., 2012. A priori parameter estimates for a distributed, grid-based Xinanjiang model using geographically based information. Journal of Hydrology 468-469, 47-62. https://doi.org/10.1016/j.jhydrol.2012.08.025
    [38]
    Yao, C., Zhang, K., Yu, Z.B., Li, Z.J., Li, Q.L., 2014. Improving the flood prediction capability of the Xinanjiang model in ungauged nested catchments by coupling it with the geomorphologic instantaneous unit hydrograph. Journal of Hydrology 517, 1035-1048. https://doi.org/10.1016/j.jhydrol.2014.06.037
    [39]
    Yao, C., Ye, J.Y., He, Z.X., Bastola, S., Zhang, K., Li, Z.J., 2019. Evaluation of flood prediction capability of the distributed grid-Xinanjiang model driven by weather research and forecasting precipitation. Journal of Flood Risk Management 12, e12544. https://doi.org/10.1111/jfr3.12544
    [40]
    Zha, X.B., Luo, P.P., Zhu, W., Wang, S.T., Lyu, J.Q., Zhou, M.M., Huo, A.D., Wang, Z.H., 2021. A bibliometric analysis of the research on sponge city: Current situation and future development direction. Ecohydrology 14(7), e2328. https://doi.org/10.1002/eco.2328
    [41]
    Zhang, K., Xue, X.W., Hong, Y., Gourley, J.J., Lu, N., Wan, Z.M., Hong, Z., Wooten, R., 2016. iCRESTRIGRS: A coupled modeling system for cascading flood-landslide disaster forecasting. Hydrology and Earth System Sciences 20(12), 5035-5048. https://doi.org/10.5194/hess-20-5035-2016
    [42]
    Zhang, K., Niu, J., Li, X., Chao, L., 2021. Comparison of artificial intelligence flood forecasting models in China's semi-arid and semi-humid regions. Water Resources Protection 37(1), 28-35 (in Chinese). https://doi.org/10.3880/j.issn.1004-6933.2021.01.005
    [43]
    Zhao, R., 1992. The Xinanjiang model applied in China. Journal of Hydrology 135, 371-381. https://doi.org/10.1016/0022-1694(92)90096-E
    [44]
    Zhao, R., Liu, X., 1995. The Xinanjiang model. In: Singh, V., ed., Computer Models of Watershed Hydrology. Water Resources Publications, Colorado, pp. 215-232
    [45]
    Zheng, X., Tarboton, D.G., Maidment, D.R., Liu, Y.Y., Passalacqua, P., 2018. River channel geometry and rating curve estimation using height above the nearest drainage. Journal of the American Water Resources Association 54(4), 785-806. https://doi.org/10.1111/1752-1688.12661
    [46]
    Zhu, Y.H., Luo, P.P., Zhang, S., Sun, B., 2020. Spatiotemporal analysis of hydrological variations and their impacts on vegetation in semiarid areas from multiple satellite data. Remote Sensing 12(24), 4177. https://doi.org/10.3390/Rs12244177
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