River Routing in the INM RAS-MSU Land Surface Model: Numerical Scheme and Parallel Implementation on Hybrid Supercomputers

Victor M. Stepanenko

doi:10.14529/jsfi220103

Authors

Victor M. Stepanenko Lomonosov Moscow State University, Moscow, Russian Federation

DOI:

https://doi.org/10.14529/jsfi220103

Keywords:

land surface model, soil, river network, MPI, OpenMP

Abstract

The land surface model (LSM) is a necessary compartment of any numerical weather forecast system or the Earth system model. This paper presents a new version of the INM RAS-MSU land surface model where the river hydrodynamic and thermodynamic scheme is embedded into the parallel execution framework using MPI and OpenMP. Numerical experiments have been performed for the East European domain with resolution 0.5°× 0.5°. The soil model parallel efficiency at 1–144 MPI cores was 0.52–0.79 and limited by the presence of ocean area, and by imbalance of computational load between soil columns. The acceleration of the river model at MPI level was defined by the size of the largest river basin in the domain. At the OpenMP level, the potential for acceleration of large river basin simulation is shown to be close to number of threads used, based on fractal properties of the river networks. This acceleration was hindered in our numerical experiments by the reduced river orders at the coarse land surface model resolution, so that the optimal speedup for the Volga river basin was 2.5–3 times attained at 4–6 threads. This performance is projected to improve with refinement of the LSM spatial resolution.

References

Bell, V.A., Kay, A.L., Jones, R.G., Moore, R.J.: Development of a high resolution grid-based river flow model for use with regional climate model output. Hydrology and Earth System Sciences 11(1), 532–549 (2007). https://doi.org/10.5194/hess-11-532-2007

Bowring, S.P.K., Lauerwald, R., Guenet, B., et al.: ORCHIDEE MICT-LEAK (r5459), a global model for the production, transport, and transformation of dissolved organic carbon from Arctic permafrost regions – Part 1: Rationale, model description, and simulation protocol. Geoscientific Model Development 12(8), 3503–3521 (2019). https://doi.org/10.5194/gmd-12-3503-2019

Bowring, S.P.K., Lauerwald, R., Guenet, B., et al.: ORCHIDEE MICT-LEAK (r5459), a global model for the production, transport, and transformation of dissolved organic carbon from Arctic permafrost regions – Part 2: Model evaluation over the Lena River basin. Geoscientific Model Development 13(2), 507–520 (2020). https://doi.org/10.5194/gmd-13-507-2020

Brooks, R., Corey, A.: Hydraulic Properties of Porous Media. Tech. rep., Colorado State University, Fort Collins (1964)

Clapp, R., Hornberger, M.: Empirical equations for some soil hydraulic properties. Water Resources Research 14(4), 601–604 (1978)

Conil, S., Douville, H., Tyteca, S.: The relative influence of soil moisture and SST in climate predictability explored within ensembles of AMIP type experiments. Climate Dynamics 28(2), 125–145 (2007). https://doi.org/10.1007/s00382-006-0172-2

Döll, P., Lehner, B.: Validation of a new global 30-min drainage direction map. Journal of Hydrology 258(1-4), 214–231 (2002). https://doi.org/10.1016/S0022-1694(01)00565-0

Downing, J., Cole, J., Duarte, C., et al.: Global abundance and size distribution of streams and rivers. Inland Waters 2(4), 229–236 (2012). https://doi.org/10.5268/IW-2.4.502

Du, C.: Comparison of the performance of 22 models describing soil water retention curves from saturation to oven dryness. Vadose Zone Journal 19(1) (2020). https://doi.org/10.1002/vzj2.20072

Fadeev, R.Y., Ushakov, K.V., Tolstykh, M.A., Ibrayev, R.A.: Design and development of the SLAV-INMIO-CICE coupled model for seasonal prediction and climate research. Russian Journal of Numerical Analysis and Mathematical Modelling 33(6), 333–340 (2018). https://doi.org/10.1515/rnam-2018-0028

Falloon, P., Betts, R., Bunton, C.: New Global River Routing Scheme in the Unified Model. Tech. rep., Hadley Centre (2007)

van Genuchten, M.T.: A Closed-form Equation for Predicting the Hydraulic Conductivity of Unsaturated Soils. Soil Science Society of America Journal 44(5), 892–898 (1980). https://doi.org/10.2136/sssaj1980.03615995004400050002x

Guth, P.L.: Drainage basin morphometry: a global snapshot from the shuttle radar topography mission. Hydrology and Earth System Sciences 15(7), 2091–2099 (2011). https://doi.org/10.5194/hess-15-2091-2011

Huang, B., Mehta, V.M.: Influences of freshwater from major rivers on global ocean circulation and temperatures in the MIT ocean general circulation model. Advances in Atmospheric Sciences 27(3), 455–468 (2010). https://doi.org/10.1007/s00376-009-9022-6

Lucas-Picher, P., Arora, V.K., Caya, D., Laprise, R.: Implementation of a large-scale variable velocity river flow routing algorithm in the Canadian Regional Climate Model (CRCM). Atmosphere-Ocean 41(2), 139–153 (2003). https://doi.org/10.3137/ao.410203

Lykossov, V., Palagin, E.: Dynamics of coupled heat and moisture transport in the soilatmosphere system. Russian Meteorology and Hydrology 8, 48–56 (1978), (in Russian)

Malakhova, V., Golubeva, E.: The role of the Siberian rivers in increasing dissolved methane in the East Siberian shelf. Bull. Nov. Comp. Center, Num. Model. in Atmosph. 13, 43–56 (2014)

Medvedev, A.I., Stepanenko, V.M.: The influence of external parameters on river runoff in the INM RAS – MSU land surface model. IOP Conference Series: Earth and Environmental Science 611, 012023 (2020). https://doi.org/10.1088/1755-1315/611/1/012023

Miralles, D.G., Teuling, A.J., van Heerwaarden, C.C., Vilà-Guerau de Arellano, J.: Megaheatwave temperatures due to combined soil desiccation and atmospheric heat accumulation. Nature Geoscience 7(5), 345–349 (2014). https://doi.org/10.1038/ngeo2141

Mualem, Y.: A new model for predicting the hydraulic conductivity of unsaturated porous media. Water Resources Research 12(3), 513–522 (1976). https://doi.org/10.1029/WR012i003p00513

Raymond, P.A., Hartmann, J., Lauerwald, R., et al.: Global carbon dioxide emissions from inland waters. Nature 503(7476), 355–359 (2013). https://doi.org/10.1038/nature12760

Sheng, M., Lei, H., Jiao, Y., Yang, D.: Evaluation of the Runoff and River Routing Schemes in the Community Land Model of the Yellow River Basin. Journal of Advances in Modeling Earth Systems 9(8), 2993–3018 (2017). https://doi.org/10.1002/2017MS001026

Solomon, A., Heuzé, C., Rabe, B., et al.: Freshwater in the Arctic Ocean 2010–2019. Ocean Science 17(4), 1081–1102 (2021). https://doi.org/10.5194/os-17-1081-2021

Stepanenko, V., Medvedev, A., Korpushenkov, I., et al.: A River Routing Scheme for an Earth System Model. Numerical Methods and Programming 20, 396–410 (2019). https://doi.org/10.26089/NumMet.v20r435, (in Russian)

Tarboton, D.G., Bras, R.L., Rodriguez-Iturbe, I.: The fractal nature of river networks. Water Resources Research 24(8), 1317–1322 (1988). https://doi.org/10.1029/WR024i008p01317

Voevodin, V.V., Antonov, A.S., Nikitenko, D.A., et al.: Supercomputer Lomonosov-2: Large Scale, Deep Monitoring and Fine Analytics for the User Community. Supercomputing Frontiers and Innovations 6(2), 4–11 (2019). https://doi.org/10.14529/jsfi190201

Volodin, E.M., Gritsun, A.S.: Simulation of Possible Future Climate Changes in the 21st Century in the INM-CM5 Climate Model. Izvestiya, Atmospheric and Oceanic Physics 56(3), 218–228 (2020). https://doi.org/10.1134/S0001433820030123

Volodina, E., Bengtsson, L., Lykosov, V.N.: Parameterization of heat and moisture transfer in a snow cover for modelling of seasonal variations of land hydrological cycle. Russian Journal of Meteorology and Hydrology (5), 5–14 (2000)

Vorobyev, S.N., Karlsson, J., Kolesnichenko, Y.Y., et al.: Fluvial carbon dioxide emission from the Lena River basin during the spring flood. Biogeosciences 18(17), 4919–4936 (2021). https://doi.org/10.5194/bg-18-4919-2021

Vreman, A.W.: The adjoint filter operator in large-eddy simulation of turbulent flow. Physics of Fluids 16(6), 2012–2022 (2004). https://doi.org/10.1063/1.1710479

Ye, A., Duan, Q., Zhan, C., et al.: Improving kinematic wave routing scheme in Community Land Model. Hydrology Research 44(5), 886–903 (2013). https://doi.org/10.2166/nh.2012.145

Zhang, H., Liu, J., Li, H., et al.: The Impacts of Soil Moisture Initialization on the Forecasts of Weather Research and Forecasting Model: A Case Study in Xinjiang, China. Water 12(7), 1892 (2020). https://doi.org/10.3390/w12071892