Articles | Volume 15, issue 18
https://doi.org/10.5194/gmd-15-7099-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-7099-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
20 Sep 2022
Development and technical paper |
| 20 Sep 2022
| 20 Sep 2022
Coupling a large-scale hydrological model (CWatM v1.1) with a high-resolution groundwater flow model (MODFLOW 6) to assess the impact of irrigation at regional scale
Water Security Research Group, Biodiversity and Natural Resources
Program, International Institute for Applied Systems Analysis (IIASA),
Laxenburg, Austria
Mikhail Smilovic
Water Security Research Group, Biodiversity and Natural Resources
Program, International Institute for Applied Systems Analysis (IIASA),
Laxenburg, Austria
Peter Burek
Water Security Research Group, Biodiversity and Natural Resources
Program, International Institute for Applied Systems Analysis (IIASA),
Laxenburg, Austria
Jens de Bruijn
Water Security Research Group, Biodiversity and Natural Resources
Program, International Institute for Applied Systems Analysis (IIASA),
Laxenburg, Austria
Institute for Environmental Studies, VU University, De Boelelaan
1087, 1081HV, Amsterdam, the Netherlands
Peter Greve
Water Security Research Group, Biodiversity and Natural Resources
Program, International Institute for Applied Systems Analysis (IIASA),
Laxenburg, Austria
Taher Kahil
Water Security Research Group, Biodiversity and Natural Resources
Program, International Institute for Applied Systems Analysis (IIASA),
Laxenburg, Austria
Yoshihide Wada
Water Security Research Group, Biodiversity and Natural Resources
Program, International Institute for Applied Systems Analysis (IIASA),
Laxenburg, Austria
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Cited articles
Bakker, M., Post, V., Langevin, C. D., Hughes, J. D., White, J. T., Starn,
J. J., and Fienen, M. N.: Scripting MODFLOW Model Development Using Python
and FloPy, Groundwater, 54, 733–739, https://doi.org/10.1111/gwat.12413, 2016.
Benedict, I., van Heerwaarden, C. C., Weerts, A. H., and Hazeleger, W.: The benefits of spatial resolution increase in global simulations of the hydrological cycle evaluated for the Rhine and Mississippi basins, Hydrol. Earth Syst. Sci., 23, 1779–1800, https://doi.org/10.5194/hess-23-1779-2019, 2019.
Beven, K. J. and Kirkby, M. J.: A physically based, variable contributing
area model of basin hydrology, Hydrol. Sci. Bull., 24, 43–69,
https://doi.org/10.1080/02626667909491834, 1979.
Bierkens, M. F. P.: Global hydrology 2015: State, trends, and directions,
Water Resour. Res., 51, 4923–4947,
https://doi.org/10.1002/2015WR017173, 2015.
Bundesministerium für Land- und Forstwirtschaft, Regionen und Wasserwirtschaft: Messstellen und Archivdaten der Hydrographie Österreichs, https://ehyd.gv.at/, last access: 3 January 2021.
Burek, P., Satoh, Y., Kahil, T., Tang, T., Greve, P., Smilovic, M., Guillaumot, L., Zhao, F., and Wada, Y.: Development of the Community Water Model (CWatM v1.04) – a high-resolution hydrological model for global and regional assessment of integrated water resources management, Geosci. Model Dev., 13, 3267–3298, https://doi.org/10.5194/gmd-13-3267-2020, 2020.
Cao, G., Scanlon, B. R., Han, D., and Zheng, C.: Impacts of thickening
unsaturated zone on groundwater recharge in the North China Plain, J.
Hydrol., 537, 260–270, https://doi.org/10.1016/j.jhydrol.2016.03.049, 2016.
Comprehensive digital field model (DGM) of the state of Burgenland: Produced from Airborne Laserscan data, https://www.data.gv.at/katalog/dataset/b5de6975-417b-4320-afdb-eb2a9e2a1dbf, last access: 29 January 2021, 2019.
Condon, L. E. and Maxwell, R. M.: Simulating the sensitivity of
evapotranspiration and streamflow to large-scale groundwater depletion, Sci.
Adv., 5, eaav4574, https://doi.org/10.1126/sciadv.aav4574, 2019.
Condon, L. E., Atchley, A. L., and Maxwell, R. M.: Evapotranspiration
depletes groundwater under warming over the contiguous United States, Nat.
Commun., 11, 873, https://doi.org/10.1038/s41467-020-14688-0, 2020.
Dalin, C., Wada, Y., Kastner, T., and Puma, M. J.: Groundwater depletion
embedded in international food trade, Nature, 543, 700–704,
https://doi.org/10.1038/nature21403, 2017.
Decharme, B., Delire, C., Minvielle, M., Colin, J., Vergnes, J. P., Alias,
A., Saint-Martin, D., Séférian, R., Sénési, S., and
Voldoire, A.: Recent Changes in the ISBA-CTRIP Land Surface System for Use
in the CNRM-CM6 Climate Model and in Global Off-Line Hydrological
Applications, J. Adv. Model. Earth Syst., 11, 1207–1252,
https://doi.org/10.1029/2018MS001545, 2019.
de Graaf, I. E. M., van Beek, R. L. P. H., Gleeson, T., Moosdorf, N.,
Schmitz, O., Sutanudjaja, E. H., and Bierkens, M. F. P.: A global-scale
two-layer transient groundwater model: Development and application to
groundwater depletion, Adv. Water Resour., 102, 53–67,
https://doi.org/10.1016/j.advwatres.2017.01.011, 2017.
de Graaf, I. E. M., Gleeson, T., van Beek, R. L. P. H., Sutanudjaja, E.
H., and Bierkens, M. F. P.: Environmental flow limits to global groundwater
pumping, Nature, 574, 90–94, https://doi.org/10.1038/s41586-019-1594-4,
2019.
Döll, P., Müller Schmied, H., Schuh, C., Portmann, F. T., and
Eicker, A.: Global-scale assessment of groundwater depletion and related
groundwater abstractions: Combining hydrological modeling with information
from well observations and GRACE satellites, Water Resour. Res., 50,
5698–5720, https://doi.org/10.1002/2014WR015595, 2014.
Famiglietti, J. S. and Wood, E. F.: Multiscale modeling of spatially
variable water and energy balance processes, Water Resour. Res., 30,
3061–3078, https://doi.org/10.1029/94WR01498, 1994.
Fan, Y. and Miguez-Macho, G.: Potential groundwater contribution to Amazon evapotranspiration, Hydrol. Earth Syst. Sci., 14, 2039–2056, https://doi.org/10.5194/hess-14-2039-2010, 2010.
Fan, Y., Li, H., and Miguez-Macho, G.: Global patterns of groundwater table
depth, Science, 339, 940–943,
https://doi.org/10.1126/science.1229881, 2013.
Fan, Y., Clark, M., Lawrence, D. M., Swenson, S., Band, L. E., Brantley, S.
L., Brooks, P. D., Dietrich, W. E., Flores, A., Grant, G., Kirchner, J. W.,
Mackay, D. S., McDonnell, J. J., Milly, P. C. D., Sullivan, P. L., Tague,
C., Ajami, H., Chaney, N., Hartmann, A., Hazenberg, P., McNamara, J.,
Pelletier, J., Perket, J., Rouholahnejad-Freund, E., Wagener, T., Zeng, X.,
Beighley, E., Buzan, J., Huang, M., Livneh, B., Mohanty, B. P., Nijssen, B.,
Safeeq, M., Shen, C., van Verseveld, W., Volk, J., and Yamazaki, D.:
Hillslope Hydrology in Global Change Research and Earth System Modeling,
Water Resour. Res., 55, 1737–1772, https://doi.org/10.1029/2018WR023903, 2019.
Fortin, F. A., De Rainville, F. M., Gardner, M. A., Parizeau, M., and
Gagńe, C.: DEAP: Evolutionary algorithms made easy, J. Mach. Learn.
Res., 13, 2171–2175, 2012.
Gleeson, T. and Richter, B.: How much groundwater can we pump and protect
environmental flows through time? Presumptive standards for conjunctive
management of aquifers and rivers, River Res. Appl., 34, 83–92,
https://doi.org/10.1002/rra.3185, 2018.
Gleeson, T., Wada, Y., Bierkens, M. F. P., and van Beek, L. P. H.: Water
balance of global aquifers revealed by groundwater footprint, Nature, 488,
197–200, https://doi.org/10.1038/nature11295, 2012.
Gleeson, T., Moosdorf, N., Hartmann, J., and van Beek, L. P. H.: A glimpse
beneath earth's surface: GLobal HYdrogeology MaPS (GLHYMPS) of permeability
and porosity, Geophys. Res. Lett., 41, 3891–3898,
https://doi.org/10.1002/2014GL059856, 2014.
Gleeson, T., Wagener, T., Döll, P., Zipper, S. C., West, C., Wada, Y., Taylor, R., Scanlon, B., Rosolem, R., Rahman, S., Oshinlaja, N., Maxwell, R., Lo, M.-H., Kim, H., Hill, M., Hartmann, A., Fogg, G., Famiglietti, J. S., Ducharne, A., de Graaf, I., Cuthbert, M., Condon, L., Bresciani, E., and Bierkens, M. F. P.: GMD perspective: The quest to improve the evaluation of groundwater representation in continental- to global-scale models, Geosci. Model Dev., 14, 7545–7571, https://doi.org/10.5194/gmd-14-7545-2021, 2021.
Grafton, R. Q., Williams, J., Perry, C. J., Molle, F., Ringler, C., Steduto,
P., Udall, B., Wheeler, S. A., Wang, Y., Garrick, D., and Allen, R. G.: The
paradox of irrigation efficiency, Science, 361, 748–750,
https://doi.org/10.1126/science.aat9314, 2018.
Groundwater Resource Committe: Report of the ground water resource
estimation commitee, Ministry of Water Resources – Government of India, 113
pp., http://cgwb.gov.in/documents/gec97.pdf (last access: 2 June 2022), 2009.
Guillaumot, L., Smilovic, M., Burek, P., de Bruijn, J., Greve, P., Kahil, T., and Wada, Y.: CWatM-MODFLOW model, Zenodo [code], https://doi.org/10.5281/zenodo.6609072, 2022.
Gupta, H. V., Kling, H., Yilmaz, K. K., and Martinez, G. F.: Decomposition
of the mean squared error and NSE performance criteria: Implications for
improving hydrological modelling, J. Hydrol., 377, 80–91,
https://doi.org/10.1016/j.jhydrol.2009.08.003, 2009.
Hanasaki, N., Yoshikawa, S., Pokhrel, Y., and Kanae, S.: A global hydrological simulation to specify the sources of water used by humans, Hydrol. Earth Syst. Sci., 22, 789–817, https://doi.org/10.5194/hess-22-789-2018, 2018.
Hanasaki, N., Matsuda, H., Fujiwara, M., Hirabayashi, Y., Seto, S., Kanae, S., and Oki, T.: Toward hyper-resolution global hydrological models including human activities: application to Kyushu island, Japan, Hydrol. Earth Syst. Sci., 26, 1953–1975, https://doi.org/10.5194/hess-26-1953-2022, 2022.
Harbaugh, A. W.: MODFLOW 2005, The U. S. Geological Survey Modular GroundWater Model: the GroundWater Flow Process, U.S. Geological Survey Techniques and Methods, 6-A16, https://doi.org/10.3133/tm6A16 (last access: 16 September 2022), 2005.
Hatvani, I. G., Magyar, N., Zessner, M., Kovács J., and Blaschke A. P.: The Water Framework Directive: Can more information be extracted from groundwater data? A case study of Seewinkel, Burgenland, eastern Austria, Hydrogeol. J., 22, 779–794, https://doi.org/10.1007/s10040-013-1093-x, 2014.
Hazenberg, P., Fang, Y., Broxton, P., Gochis, D., Niu, G.-Y., Pelletier, J.
D., Troch, P. A., and X, Z.: A hybrid-3D hillslope hydrological model for
use in Earth system models, Water Resour. Res., 51, 8218–8239,
https://doi.org/10.1002/2014WR016842, 2015.
Houben, T., Pujades, E., Kalbacher, T., Dietrich, P., and Attinger, S.: From dynamic groundwater level measurements to regional aquifer parameters – Assessing the power of spectral analysis, Water Resour. Res., 58, e2021WR031289, https://doi.org/10.1029/2021WR031289, 2022.
Hughes, J. D., Langevin, C. D., and Banta, E. R.: Documentation for the MODFLOW 6 framework, U.S. Geological Survey Techniques and Methods, book 6, chap. A57, 42 pp., https://doi.org/10.3133/tm6A57, 2017.
Huscroft, J., Gleeson, T., Hartmann, J., and Börker, J.: Compiling and
Mapping Global Permeability of the Unconsolidated and Consolidated Earth:
GLobal HYdrogeology MaPS 2.0 (GLHYMPS 2.0), Geophys. Res. Lett., 45,
1897–1904, https://doi.org/10.1002/2017GL075860, 2018.
Jing, M., Heße, F., Kumar, R., Wang, W., Fischer, T., Walther, M., Zink, M., Zech, A., Samaniego, L., Kolditz, O., and Attinger, S.: Improved regional-scale groundwater representation by the coupling of the mesoscale Hydrologic Model (mHM v5.7) to the groundwater model OpenGeoSys (OGS), Geosci. Model Dev., 11, 1989–2007, https://doi.org/10.5194/gmd-11-1989-2018, 2018.
Karner, K., Mitter, H., and Schmid, E.: The economic value of stochastic
climate information for agricultural adaptation in a semi-arid region in
Austria, J. Environ. Manage., 249, 109431,
https://doi.org/10.1016/j.jenvman.2019.109431, 2019.
Karutz, R., Omann, I., Gorelick, S. M., Klassert, C. J. A., Zozmann, H.,
Zhu, Y., Kabisch, S., Kindler, A., Figueroa, A. J., Wang, A., and
Küblböck, K.: Capturing Stakeholders' Challenges of the
Food–Water–Energy Nexus – A Participatory Approach for Pune and the Bhima
Basin, India, Sustain., 14, 5323, https://doi.org/10.3390/su14095323, 2022.
Keune, J., Gasper, F., Goergen, K., Hense, A., Shrestha, P., Sulis, M., and
Kollet, S.: Studying the influence of groundwater representations on land
surface-atmosphere feedbacks during the European heat wave in 2003, J.
Geophys. Res., 121, 13301–13325, https://doi.org/10.1002/2016JD025426,
2016.
Keune, J., Sulis, M., Kollet, S., Siebert, S., and Wada, Y.: Human Water Use
Impacts on the Strength of the Continental Sink for Atmospheric Water,
Geophys. Res. Lett., 45, 4068–4076, https://doi.org/10.1029/2018GL077621,
2018.
Koirala, S., Jung, M., Reichstein, M., de Graaf, I. E. M., Camps-Valls, G.,
Ichii, K., Papale, D., Ráduly, B., Schwalm, C. R., Tramontana, G., and
Carvalhais, N.: Global distribution of groundwater-vegetation spatial
covariation, Geophys. Res. Lett., 44, 4134–4142,
https://doi.org/10.1002/2017GL072885, 2017.
Koirala, S., Kim, H., Hirabayashi, Y., Kanae, S., and Oki, T.: Sensitivity
of Global Hydrological Simulations to Groundwater Capillary Flux
Parameterizations, Water Resour. Res., 55, 402–425,
https://doi.org/10.1029/2018WR023434, 2019.
Kollet, S. J. and Maxwell, R. M.: Capturing the influence of groundwater
dynamics on land surface processes using an integrated, distributed
watershed model, Water Resour. Res., 44, W02402,
https://doi.org/10.1029/2007WR006004, 2008.
Krakauer, N. Y., Li, H., and Fan, Y.: Groundwater flow across spatial
scales: Importance for climate modeling, Environ. Res. Lett., 9, 034003,
https://doi.org/10.1088/1748-9326/9/3/034003, 2014.
Le Coz, M., Favreau, G., and Ousmane, S. D.: Modeling Increased Groundwater
Recharge due to Change from Rainfed to Irrigated Cropping in a Semiarid
Region, Vadose Zo. J., 12, vzj2012.0148,
https://doi.org/10.2136/vzj2012.0148, 2013.
Long, D., Yang, W., Scanlon, B. R., Zhao, J., Liu, D., Burek, P., Pan, Y.,
You, L., and Wada, Y.: South-to-North Water Diversion stabilizing Beijing's
groundwater levels, Nat. Commun., 11, 3665,
https://doi.org/10.1038/s41467-020-17428-6, 2020.
Loritz, R., Hassler, S. K., Jackisch, C., Allroggen, N., van Schaik, L., Wienhöfer, J., and Zehe, E.: Picturing and modeling catchments by representative hillslopes, Hydrol. Earth Syst. Sci., 21, 1225–1249, https://doi.org/10.5194/hess-21-1225-2017, 2017.
Magyar, N., Hatvani, I. G., Arato, M., Trasy, B., Blaschke, A. P., and
Kovacs, J.: A New Approach in Determining the Decadal Common Trends in the
Groundwater Table of the Watershed of Lake Neusiedlersee, Water, 13, 290,
https://doi.org/10.3390/w13030290, 2021.
Martínez-de la Torre, A. and Miguez-Macho, G.: Groundwater influence on soil moisture memory and land–atmosphere fluxes in the Iberian Peninsula, Hydrol. Earth Syst. Sci., 23, 4909–4932, https://doi.org/10.5194/hess-23-4909-2019, 2019.
Maxwell, R. M., Condon, L. E., and Kollet, S. J.: A high-resolution simulation of groundwater and surface water over most of the continental US with the integrated hydrologic model ParFlow v3, Geosci. Model Dev., 8, 923–937, https://doi.org/10.5194/gmd-8-923-2015, 2015.
Meixner, T., Manning, A. H., Stonestrom, D. A., Allen, D. M., Ajami, H.,
Blasch, K. W., Brookfield, A. E., Castro, C. L., Clark, J. F., Gochis, D.
J., Flint, A. L., Neff, K. L., Niraula, R., Rodell, M., Scanlon, B. R.,
Singha, K., and Walvoord, M. A.: Implications of projected climate change
for groundwater recharge in the western United States, J. Hydrol., 534,
124–138, https://doi.org/10.1016/j.jhydrol.2015.12.027, 2016.
Meredith, E. and Blais, N.: Quantifying irrigation recharge sources using
groundwater modeling, Agric. Water Manag., 214, 9–16,
https://doi.org/10.1016/j.agwat.2018.12.032, 2019.
Messager, M. L., Lehner, B., Grill, G., Nedeva, I., and Schmitt, O.:
Estimating the volume and age of water stored in global lakes using a
geo-statistical approach, Nat. Commun., 7, 13603,
https://doi.org/10.1038/ncomms13603, 2016.
Miguez-Macho, G. and Fan, Y.: The role of groundwater in the Amazon water
cycle: 2. Influence on seasonal soil moisture and evapotranspiration, J.
Geophys. Res., 117, D15114, https://doi.org/10.1029/2012JD017540, 2012.
Mitter, H. and Schmid, E.: Informing groundwater policies in semi-arid
agricultural production regions under stochastic climate scenario impacts,
Ecol. Econ., 180, 106908, https://doi.org/10.1016/j.ecolecon.2020.106908,
2021.
Ochoa, C. G., Fernald, A. G., Guldan, S. J., Tidwell, V. C., and Shukla, M.
K.: Shallow Aquifer Recharge from Irrigation in a Semiarid Agricultural
Valley in New Mexico, J. Hydrol. Eng., 18, 1219–1230,
https://doi.org/10.1061/(asce)he.1943-5584.0000718, 2013.
Reinecke, R., Foglia, L., Mehl, S., Trautmann, T., Cáceres, D., and Döll, P.: Challenges in developing a global gradient-based groundwater model (G3M v1.0) for the integration into a global hydrological model, Geosci. Model Dev., 12, 2401–2418, https://doi.org/10.5194/gmd-12-2401-2019, 2019a.
Reinecke, R., Foglia, L., Mehl, S., Herman, J. D., Wachholz, A., Trautmann, T., and Döll, P.: Spatially distributed sensitivity of simulated global groundwater heads and flows to hydraulic conductivity, groundwater recharge, and surface water body parameterization, Hydrol. Earth Syst. Sci., 23, 4561–4582, https://doi.org/10.5194/hess-23-4561-2019, 2019b.
Reinecke, R., Wachholz, A., Mehl, S., Foglia, L., Niemann, C., and Döll,
P.: Importance of Spatial Resolution in Global Groundwater Modeling, Groundwater, 58,
363–376, https://doi.org/10.1111/gwat.12996, 2020.
Roark, M. and Healy, D. F.: Quantification of deep percolation from two flood-irrigated alfalfa fields, Roswell basin, New Mexico, US Geological Survey Water-Resources Investigations Report 98-4096, https://doi.org/10.3133/wri984096, 1998.
Rouholahnejad Freund, E. and Kirchner, J. W.: A Budyko framework for estimating how spatial heterogeneity and lateral moisture redistribution affect average evapotranspiration rates as seen from the atmosphere, Hydrol. Earth Syst. Sci., 21, 217–233, https://doi.org/10.5194/hess-21-217-2017, 2017.
Russcher, M. J., Hofer, J., and Hughes, J. D.: xmipy–Python bindings for
the eXtended Model Interface version 1.0.0 (1.0.0), Zenodo [code],
https://doi.org/10.5281/zenodo.4740983, 2020.
Sadki, M., Munier, S., Boone, A., and Ricci, S.: Implementation and sensitivity analysis of a Dam-Reservoir OPeration model (DROP v1.0) over Spain, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2022-108, in review, 2022.
Scanlon, B. R., Reedy, R. C., Stonestrom, D. A., Prudic, D. E., and Dennehy,
K. F.: Impact of land use and land cover change on groundwater recharge and
quality in the southwestern US, Glob. Chang. Biol., 11, 1577–1593,
https://doi.org/10.1111/j.1365-2486.2005.01026.x, 2005.
Schaller, M. F. and Fan, Y.: River basins as groundwater exporters and
importers: Implications for water cycle and climate modeling, J. Geophys.
Res. Atmos., 114, D04103, https://doi.org/10.1029/2008JD010636, 2009.
Scheidegger, J. M., Jackson, C. R., Muddu, S., Tomer, S. K., and Filgueira,
R.: Integration of 2D lateral groundwater flow into the variable
infiltration capacity (VIC) model and effects on simulated fluxes for
different grid resolutions and aquifer diffusivities, Water, 13, 663,
https://doi.org/10.3390/w13050663, 2021.
Shangguan, W., Hengl, T., de Jesus, J. M., Yuan, H., and Dai, Y.: Mapping
the global depth to bedrock for land surface modeling, J. Adv. Model. Earth
Syst., 8, 1248–1269, https://doi.org/10.1002/2016MS000689, 2016.
Shrestha, P., Sulis, M., Simmer, C., and Kollet, S.: Effects of horizontal
grid resolution on evapotranspiration partitioning using TerrSysMP, J.
Hydrol., 557, 910–915, https://doi.org/10.1016/j.jhydrol.2018.01.024, 2018.
Siebert, S., Burke, J., Faures, J. M., Frenken, K., Hoogeveen, J., Döll, P., and Portmann, F. T.: Groundwater use for irrigation – a global inventory, Hydrol. Earth Syst. Sci., 14, 1863–1880, https://doi.org/10.5194/hess-14-1863-2010, 2010.
Smilovic, M., Burek, P., Guillaumot, L., Kahil, T., Wada, Y., Lee, J. Y., and Gorelick, S. M.: Hyper-resolution hydrological modeling of a managed watershed: The application of CWatM at 30 arc-seconds resolution in the Upper Bhima basin, AGU Fall Meeting 2019, December 2019, abstract H11O-1729, 2019AGUFM.H11O1729S, 2019.
Soltani, M., Bjerre, E., Koch, J., and Stisen, S.: Integrating remote
sensing data in optimization of a national water resources model to improve
the spatial pattern performance of evapotranspiration, J. Hydrol., 603,
127026, https://doi.org/10.1016/j.jhydrol.2021.127026, 2021.
Surinaidu, L., Bacon, C. G. D., and Pavelic, P.: Agricultural groundwater management in the Upper Bhima Basin, India: current status and future scenarios, Hydrol. Earth Syst. Sci., 17, 507–517, https://doi.org/10.5194/hess-17-507-2013, 2013.
Sutanudjaja, E. H., van Beek, L. P. H., de Jong, S. M., van Geer, F. C., and Bierkens, M. F. P.: Large-scale groundwater modeling using global datasets: a test case for the Rhine-Meuse basin, Hydrol. Earth Syst. Sci., 15, 2913–2935, https://doi.org/10.5194/hess-15-2913-2011, 2011.
Sutanudjaja, E. H., Van Beek, L. P. H., De Jong, S. M., Van Geer, F. C., and
Bierkens, M. F. P.: Calibrating a large extent high resolution coupled
groundwater land surface model using soil moisture and discharge data, Water
Resour. Res., 50, 687–705, https://doi.org/10.1002/2013WR013807, 2014.
Sutanudjaja, E. H., van Beek, R., Wanders, N., Wada, Y., Bosmans, J. H. C., Drost, N., van der Ent, R. J., de Graaf, I. E. M., Hoch, J. M., de Jong, K., Karssenberg, D., López López, P., Peßenteiner, S., Schmitz, O., Straatsma, M. W., Vannametee, E., Wisser, D., and Bierkens, M. F. P.: PCR-GLOBWB 2: a 5 arcmin global hydrological and water resources model, Geosci. Model Dev., 11, 2429–2453, https://doi.org/10.5194/gmd-11-2429-2018, 2018.
Swenson, S. C., Clark, M., Fan, Y., Lawrence, D. M., and Perket, J.:
Representing Intra-Hillslope Lateral Subsurface Flow in the Community Land
Model, J. Adv. Model. Earth Syst., 11, 4044–4065, https://doi.org/10.1029/2019MS001833,
2019.
Szilagyi, J., Zlotnik, V. A., and Jozsa, J.: Net recharge vs. depth to
groundwater relationship in the platte river Valley of Nebraska, United
States, Groundwater, 51, 945–951, https://doi.org/10.1111/gwat.12007, 2013.
Taylor, R. G., Scanlon, B., Döll, P., Rodell, M., van Beek, R., Wada,
Y., Longuevergne, L., Leblanc, M., Famiglietti, J. S., Edmunds, M., Konikow,
L., Green, T. R., Chen, J., Taniguchi, M., Bierkens, M. F. P., MacDonald,
A., Fan, Y., Maxwell, R. M., Yechieli, Y., Gurdak, J. J., Allen, D. M.,
Shamsudduha, M., Hiscock, K., Yeh, P. J.-F., Holman, I., and Treidel, H.:
Ground water and climate change, Nat. Clim. Chang., 3, 322–329, https://doi.org/10.1038/nclimate1744, 2012.
Trichakis, I., Burek, P., de Roo, A., and Pistocchi, A.: Towards a
Pan-European Integrated Groundwater and Surface Water Model: Development and
Applications, Environ. Process., 4, 81–93,
https://doi.org/10.1007/s40710-017-0216-0, 2017.
Troch, P. a, Paniconi, C., and Emiel van Loon, E.: Hillslope-storage
Boussinesq model for subsurface flow and variable source areas along complex
hillslopes: 1. Formulation and characteristic response, Water Resour. Res.,
39, 1316, https://doi.org/10.1029/2002wr001728, 2003.
Turner, S. W. D., Hejazi, M., Yonkofski, C., Kim, S. H., and Kyle, P.:
Influence of Groundwater Extraction Costs and Resource Depletion Limits on
Simulated Global Nonrenewable Water Withdrawals Over the Twenty-First
Century, Earth's Future, 7, 123–135, https://doi.org/10.1029/2018EF001105,
2019.
Verbeke, T., Tootchi, A., Jost, A., Ghattas, J., Cheruy, F., and
Ducharne, A.: Subgrid-scale parametrization of groundwater-soil
moisture interactions in the ORCHIDEE land surface model:
first results at global scale, Geophysical Research Abstracts, Vol. 21, EGU2019-16650, EGU General Assembly 2019, https://meetingorganizer.copernicus.org/EGU2019/EGU2019-16650.pdf (last access: 2 June 2022), 2019.
Vergnes, J. P., Decharme, B., and Habets, F.: Introduction of groundwater
capillary rises using subgrid spatial variability of topography into the
ISBA land surface model, J. Geophys. Res., 119, 11065–11086,
https://doi.org/10.1002/2014JD021573, 2014.
Vergnes, J.-P., Roux, N., Habets, F., Ackerer, P., Amraoui, N., Besson, F., Caballero, Y., Courtois, Q., de Dreuzy, J.-R., Etchevers, P., Gallois, N., Leroux, D. J., Longuevergne, L., Le Moigne, P., Morel, T., Munier, S., Regimbeau, F., Thiéry, D., and Viennot, P.: The AquiFR hydrometeorological modelling platform as a tool for improving groundwater resource monitoring over France: evaluation over a 60-year period, Hydrol. Earth Syst. Sci., 24, 633–654, https://doi.org/10.5194/hess-24-633-2020, 2020.
Wada, Y., Wisser, D., and Bierkens, M. F. P.: Global modeling of withdrawal, allocation and consumptive use of surface water and groundwater resources, Earth Syst. Dynam., 5, 15–40, https://doi.org/10.5194/esd-5-15-2014, 2014.
Wada, Y., Bierkens, M. F. P., de Roo, A., Dirmeyer, P. A., Famiglietti, J. S., Hanasaki, N., Konar, M., Liu, J., Müller Schmied, H., Oki, T., Pokhrel, Y., Sivapalan, M., Troy, T. J., van Dijk, A. I. J. M., van Emmerik, T., Van Huijgevoort, M. H. J., Van Lanen, H. A. J., Vörösmarty, C. J., Wanders, N., and Wheater, H.: Human–water interface in hydrological modelling: current status and future directions, Hydrol. Earth Syst. Sci., 21, 4169–4193, https://doi.org/10.5194/hess-21-4169-2017, 2017.
Wang, F., Ducharne, A., Cheruy, F., Lo, M. H., and Grandpeix, J. Y.: Impact
of a shallow groundwater table on the global water cycle in the IPSL
land–atmosphere coupled model, Clim. Dynam., 50, 3505–3522,
https://doi.org/10.1007/s00382-017-3820-9, 2018.
Willis, T. M. and Black, A. S.: Irrigation increases groundwater recharge in
the Macquarie Valley, Aust. J. Soil Res., 34, 837–847,
https://doi.org/10.1071/SR9960837, 1996.
Wood, E. F., Roundy, J. K., Troy, T. J., Beek, L. P. H. Van, Bierkens, M. F.
P., Blyth, E., Roo, A. De, Döll, P., Ek, M., Famiglietti, J., Gochis,
D., Giesen, N. Van De, Houser, P., Jaffé, P. R., Kollet, S., Lehner, B.,
Lettenmaier, D. P., Lidard, C. P., Sivapalan, M., Sheffield, J., Wade, A.,
and Whitehead, P.: Hyperresolution global land surface modeling: Meeting a
grand challenge for monitoring Earth's terrestrial water, Water Resour.
Res., 47, W05301, https://doi.org/10.1029/2010WR010090, 2011.
Wösten, J. H. M. and van Genuchten, M. T.: Using Texture and Other Soil
Properties to Predict the Unsaturated Soil Hydraulic Functions, Soil Sci.
Soc. Am. J., 52, 1762–1770,
https://doi.org/10.2136/sssaj1988.03615995005200060045x, 1988.
Yamazaki, D., Ikeshima, D., Sosa, J., Bates, P. D., Allen, G. H., and
Pavelsky, T. M.: MERIT Hydro: A High-Resolution Global Hydrography Map Based
on Latest Topography Dataset, Water Resour. Res., 55, 5053–5073,
https://doi.org/10.1029/2019WR024873, 2019.
Short summary
We develop and test the first large-scale hydrological model at regional scale with a very high spatial resolution that includes a water management and groundwater flow model. This study infers the impact of surface and groundwater-based irrigation on groundwater recharge and on evapotranspiration in both irrigated and non-irrigated areas. We argue that water table recorded in boreholes can be used as validation data if water management is well implemented and spatial resolution is ≤ 100 m.
We develop and test the first large-scale hydrological model at regional scale with a very high...
