Hydrological Alteration Index as an Indicator of the Calibration Complexity of Water Quantity and Quality Modeling in the Context of Global Change

[EN] Modeling is a useful way to understand human and climate change impacts on the water resources of agricultural watersheds. Calibration and validation methodologies are crucial in forecasting assessments. This study explores the best calibration methodology depending on the level of hydrological alteration due to human-derived stressors. The Soil and Water Assessment Tool (SWAT) model is used to evaluate hydrology in South-West Europe in a context of intensive agriculture and water scarcity. The Index of Hydrological Alteration (IHA) is calculated using discharge observation data. A comparison of two SWAT calibration methodologies are done; a conventional calibration (CC) based on recorded in-stream water quality and quantity and an additional calibration (AC) adding crop managements practices. Even if the water quality and quantity trends are similar between CC and AC, water balance, irrigation and crop yields are different. In the context of rainfall decrease, water yield decreases in both CC and AC, while crop productions present opposite trends (+33% in CC and ¿31% in AC). Hydrological performance between CC and AC is correlated to IHA: When the level of IHA is under 80%, AC methodology is necessary. The combination of both calibrations appears essential to better constrain the model and to forecast the impact of climate change or anthropogenic influences on water resources.This project was supported by the Université Toulouse III Paul Sabatier and by the Ministry of Higher Education and Research. This study was performed as part of the EU Interreg SUDOE IVB program (AGUAMOD SOE1/P5/F0026 project, http://www.aguamod-sudoe.eu) and also supported by ERDF. We want to thank all the partners of this program that shared data and helped with their expertise on irrigation, dam and crop yield management and streamflow calibration: l Agence de l eau Adour-Garonne, la Compagnie d Aménagement des Coteaux de Gascogne, el Universidad Politecnica de Valencia, la Banque Hydro, l Electricité De France (EDF) (the project REGARD-RTRA/STAE), le Syndicat Mixte d Etude et d Aménagement de la Garonne, l Institute National de la Statistique et des Etudes Economiques, el Instituto Nacional de Estatística de Portugal y de España, el Consejo Superior de Investigaciones Científicas, El Ministerio para la Transición Ecológica and el Ministerio de Agricultura, Pesca y Alimentación of Spain.Cakir, R.; Raimonet, M.; Sauvage, S.; Paredes Arquiola, J.; Grusson, Y.; Roset, L.; Meaurio, M.... (2020). Hydrological Alteration Index as an Indicator of the Calibration Complexity of Water Quantity and Quality Modeling in the Context of Global Change. Water. 12(1):1-33. https://doi.org/10.3390/w12010115133121Eliasson, J. (2014). The rising pressure of global water shortages. Nature, 517(7532), 6-6. doi:10.1038/517006aMekonnen, M. M., & Hoekstra, A. Y. (2016). Four billion people facing severe water scarcity. Science Advances, 2(2), e1500323. doi:10.1126/sciadv.1500323Vörösmarty, C. J., McIntyre, P. B., Gessner, M. O., Dudgeon, D., Prusevich, A., Green, P., … Davies, P. M. (2010). Global threats to human water security and river biodiversity. Nature, 467(7315), 555-561. doi:10.1038/nature09440Raimonet, M., Thieu, V., Silvestre, M., Oudin, L., Rabouille, C., Vautard, R., & Garnier, J. (2018). Landward Perspective of Coastal Eutrophication Potential Under Future Climate Change: The Seine River Case (France). Frontiers in Marine Science, 5. doi:10.3389/fmars.2018.00136Roudier, P., Andersson, J. C. M., Donnelly, C., Feyen, L., Greuell, W., & Ludwig, F. (2015). Projections of future floods and hydrological droughts in Europe under a +2°C global warming. Climatic Change, 135(2), 341-355. doi:10.1007/s10584-015-1570-4Fu, B., Merritt, W. S., Croke, B. F. W., Weber, T. R., & Jakeman, A. J. (2019). A review of catchment-scale water quality and erosion models and a synthesis of future prospects. Environmental Modelling & Software, 114, 75-97. doi:10.1016/j.envsoft.2018.12.008Abbaspour, K. C., Rouholahnejad, E., Vaghefi, S., Srinivasan, R., Yang, H., & Kløve, B. (2015). A continental-scale hydrology and water quality model for Europe: Calibration and uncertainty of a high-resolution large-scale SWAT model. Journal of Hydrology, 524, 733-752. doi:10.1016/j.jhydrol.2015.03.027Grusson, Y., Anctil, F., Sauvage, S., & Pérez, J. M. S. (2018). Coevolution of Hydrological Cycle Components under Climate Change: The Case of the Garonne River in France. Water, 10(12), 1870. doi:10.3390/w10121870Biancamaria, S., Mballo, M., Le Moigne, P., Sánchez Pérez, J. M., Espitalier-Noël, G., Grusson, Y., … Sauvage, S. (2019). Total water storage variability from GRACE mission and hydrological models for a 50,000 km2 temperate watershed: the Garonne River basin (France). Journal of Hydrology: Regional Studies, 24, 100609. doi:10.1016/j.ejrh.2019.100609Hydrologic and Water Quality Models: Performance Measures and Evaluation Criteria. (2015). Transactions of the ASABE, 58(6), 1763-1785. doi:10.13031/trans.58.10715Holzworth, D. P., Huth, N. I., deVoil, P. G., Zurcher, E. J., Herrmann, N. I., McLean, G., … Keating, B. A. (2014). APSIM – Evolution towards a new generation of agricultural systems simulation. Environmental Modelling & Software, 62, 327-350. doi:10.1016/j.envsoft.2014.07.009Wade, A. J., Durand, P., Beaujouan, V., Wessel, W. W., Raat, K. J., Whitehead, P. G., … Lepisto, A. (2002). A nitrogen model for European catchments: INCA, new model structure and equations. Hydrology and Earth System Sciences, 6(3), 559-582. doi:10.5194/hess-6-559-2002Arnold, J. G., Srinivasan, R., Muttiah, R. S., & Williams, J. R. (1998). LARGE AREA HYDROLOGIC MODELING AND ASSESSMENT PART I: MODEL DEVELOPMENT. Journal of the American Water Resources Association, 34(1), 73-89. doi:10.1111/j.1752-1688.1998.tb05961.xRuelland, D., Billen, G., Brunstein, D., & Garnier, J. (2007). SENEQUE: A multi-scaling GIS interface to the Riverstrahler model of the biogeochemical functioning of river systems. Science of The Total Environment, 375(1-3), 257-273. doi:10.1016/j.scitotenv.2006.12.014Sparrow, A. D., Friedel, M. H., & Smith, D. M. S. (1997). A landscape-scale model of shrub and herbage dynamics in Central Australia, validated by satellite data. Ecological Modelling, 97(3), 197-216. doi:10.1016/s0304-3800(96)01904-7Oeurng, C., Sauvage, S., & Sánchez-Pérez, J.-M. (2011). Assessment of hydrology, sediment and particulate organic carbon yield in a large agricultural catchment using the SWAT model. Journal of Hydrology, 401(3-4), 145-153. doi:10.1016/j.jhydrol.2011.02.017Volk, M., Sauvage, S., Sánchez-Pérez, J.-M., & Biegerd, K. (2016). Development and applications of the SWAT model to support sustainable river basin management on different scales. Sustainability of Water Quality and Ecology, 8, 1-3. doi:10.1016/j.swaqe.2016.12.001Gassman, P. W., Sadeghi, A. M., & Srinivasan, R. (2014). Applications of the SWAT Model Special Section: Overview and Insights. Journal of Environmental Quality, 43(1), 1-8. doi:10.2134/jeq2013.11.0466Arnold, J. G., Srinivasan, R., Muttiah, R. S., & Allen, P. M. (1999). CONTINENTAL SCALE SIMULATION OF THE HYDROLOGIC BALANCE. Journal of the American Water Resources Association, 35(5), 1037-1051. doi:10.1111/j.1752-1688.1999.tb04192.xZalasiewicz, J., Waters, C., Summerhayes, C., & Williams, M. (2018). The Anthropocene. Geology Today, 34(5), 177-181. doi:10.1111/gto.12244Volk, M., Bosch, D., Nangia, V., & Narasimhan, B. (2016). SWAT: Agricultural water and nonpoint source pollution management at a watershed scale. Agricultural Water Management, 175, 1-3. doi:10.1016/j.agwat.2016.06.013Volk, M. (2015). Modelling ecosystem services: Current approaches, challenges and perspectives. Sustainability of Water Quality and Ecology, 5, 1-2. doi:10.1016/j.swaqe.2015.05.002Grizzetti, B., Pistocchi, A., Liquete, C., Udias, A., Bouraoui, F., & van de Bund, W. (2017). Human pressures and ecological status of European rivers. Scientific Reports, 7(1). doi:10.1038/s41598-017-00324-3Richter, B. D., Baumgartner, J. V., Powell, J., & Braun, D. P. (1996). A Method for Assessing Hydrologic Alteration within Ecosystems. Conservation Biology, 10(4), 1163-1174. doi:10.1046/j.1523-1739.1996.10041163.xEEA Report European Waters—Assessment of Status and Pressures 2018https://www.eea.europa.eu/publications/state-of-waterThe Statistical Office of the European Union Water use by NUTS 2 regions—Eurostathttps://ec.europa.eu/eurostat/web/products-datasets/-/env_watuse_r2Romero, E., Garnier, J., Lassaletta, L., Billen, G., Le Gendre, R., Riou, P., & Cugier, P. (2012). Large-scale patterns of river inputs in southwestern Europe: seasonal and interannual variations and potential eutrophication effects at the coastal zone. Biogeochemistry, 113(1-3), 481-505. doi:10.1007/s10533-012-9778-0Gao, Y., Vogel, R. M., Kroll, C. N., Poff, N. L., & Olden, J. D. (2009). Development of representative indicators of hydrologic alteration. Journal of Hydrology, 374(1-2), 136-147. doi:10.1016/j.jhydrol.2009.06.009Richter, B. D., Mathews, R., Harrison, D. L., & Wigington, R. (2003). ECOLOGICALLY SUSTAINABLE WATER MANAGEMENT: MANAGING RIVER FLOWS FOR ECOLOGICAL INTEGRITY. Ecological Applications, 13(1), 206-224. doi:10.1890/1051-0761(2003)013[0206:eswmmr]2.0.co;2Richter, B. D., Baumgartner, J. V., Braun, D. P., & Powell, J. (1998). A spatial assessment of hydrologic alteration within a river network. Regulated Rivers: Research & Management, 14(4), 329-340. doi:10.1002/(sici)1099-1646(199807/08)14:43.0.co;2-eBioclimatic map of Europe, bioclimates, University of León, E-24071, Spainhttps://www.globalbioclimatics.org/form/maps.htmAQUASTAThttp://www.fao.org/nr/water/aquastat/data/query/results.htmlCunge, J. A. (1969). On The Subject Of A Flood Propagation Computation Method (Musklngum Method). Journal of Hydraulic Research, 7(2), 205-230. doi:10.1080/00221686909500264George H. Hargreaves, & Zohrab A. Samani. (1985). Reference Crop Evapotranspiration from Temperature. Applied Engineering in Agriculture, 1(2), 96-99. doi:10.13031/2013.26773Hargreaves, G. H., & Allen, R. G. (2003). History and Evaluation of Hargreaves Evapotranspiration Equation. Journal of Irrigation and Drainage Engineering, 129(1), 53-63. doi:10.1061/(asce)0733-9437(2003)129:1(53)P. W. Gassman, M. R. Reyes, C. H. Green, & J. G. Arnold. (2007). The Soil and Water Assessment Tool: Historical Development, Applications, and Future Research Directions. Transactions of the ASABE, 50(4), 1211-1250. doi:10.13031/2013.23637Battude, M., Al Bitar, A., Brut, A., Tallec, T., Huc, M., Cros, J., … Demarez, V. (2017). Modeling water needs and total irrigation depths of maize crop in the south west of France using high spatial and temporal resolution satellite imagery. Agricultural Water Management, 189, 123-136. doi:10.1016/j.agwat.2017.04.018Gilmore, E. C., & Rogers, J. S. (1958). Heat Units as a Method of Measuring Maturity in Corn 1. Agronomy Journal, 50(10), 611-615. doi:10.2134/agronj1958.00021962005000100014xClimate and the efficiency of crop production in Britain. (1977). Philosophical Transactions of the Royal Society of London. B, Biological Sciences, 281(980), 277-294. doi:10.1098/rstb.1977.0140Gesch, D., Farr, T., Slater, J., Muller, J.-P., & Cook, S. (2006). New products from the shuttle radar topography mission. Eos, Transactions American Geophysical Union, 87(18), 174. doi:10.1029/2006eo180003Häggmark, L., Ivarsson, K.-I., Gollvik, S., & Olofsson, P.-O. (2000). Mesan, an operational mesoscale analysis system. Tellus A: Dynamic Meteorology and Oceanography, 52(1), 2-20. doi:10.3402/tellusa.v52i1.12250Landelius, T., Dahlgren, P., Gollvik, S., Jansson, A., & Olsson, E. (2016). A high‐resolution regional reanalysis for Europe. Part 2: 2D analysis of surface temperature, precipitation and wind. Quarterly Journal of the Royal Meteorological Society, 142(698), 2132-2142. doi:10.1002/qj.2813Raimonet, M., Oudin, L., Thieu, V., Silvestre, M., Vautard, R., Rabouille, C., & Le Moigne, P. (2017). Evaluation of Gridded Meteorological Datasets for Hydrological Modeling. Journal of Hydrometeorology, 18(11), 3027-3041. doi:10.1175/jhm-d-17-0018.1Quintana-Seguí, P., Le Moigne, P., Durand, Y., Martin, E., Habets, F., Baillon, M., … Morel, S. (2008). Analysis of Near-Surface Atmospheric Variables: Validation of the SAFRAN Analysis over France. Journal of Applied Meteorology and Climatology, 47(1), 92-107. doi:10.1175/2007jamc1636.1Quintana-Seguí, P. (2016). Meteorological Analysis Systems in North-East Spain: Validation of SAFRAN and SPAN. Journal of Environmental Informatics. doi:10.3808/jei.201600335EEA Report UWWTD Data Sourceshttps://www.eea.europa.eu/themes/water/european-waters/water-use-and-environmental-pressures/uwwtd/uwwtd-data-sourcesZessner, M., & Lindtner, S. (2005). Estimations of municipal point source pollution in the context of river basin management. Water Science and Technology, 52(9), 175-182. doi:10.2166/wst.2005.0313Loubier, S., Campardon, M., & Morardet, S. (2013). L’irrigation diminue-t-elle en France ? Premiers enseignements du recensement agricole de 2010. Sciences Eaux & Territoires, Numéro 11(2), 12. doi:10.3917/set.011.0012Hengl, T., de Jesus, J. M., MacMillan, R. A., Batjes, N. H., Heuvelink, G. B. M., Ribeiro, E., … Gonzalez, M. R. (2014). SoilGrids1km — Global Soil Information Based on Automated Mapping. PLoS ONE, 9(8), e105992. doi:10.1371/journal.pone.0105992Abbaspour, K., Vaghefi, S., & Srinivasan, R. (2017). A Guideline for Successful Calibration and Uncertainty Analysis for Soil and Water Assessment: A Review of Papers from the 2016 International SWAT Conference. Water, 10(1), 6. doi:10.3390/w10010006Van Griensven, A., Meixner, T., Grunwald, S., Bishop, T., Diluzio, M., & Srinivasan, R. (2006). A global sensitivity analysis tool for the parameters of multi-variable catchment models. Journal of Hydrology, 324(1-4), 10-23. doi:10.1016/j.jhydrol.2005.09.008J. G. Arnold, D. N. Moriasi, P. W. Gassman, K. C. Abbaspour, M. J. White, R. Srinivasan, … M. K. Jha. (2012). SWAT: Model Use, Calibration, and Validation. Transactions of the ASABE, 55(4), 1491-1508. doi:10.13031/2013.42256Khalid, K., Ali, M. F., Rahman, N. F. A., Mispan, M. R., Haron, S. H., Othman, Z., & Bachok, M. F. (2016). Sensitivity Analysis in Watershed Model Using SUFI-2 Algorithm. Procedia Engineering, 162, 441-447. doi:10.1016/j.proeng.2016.11.086Yang, J., Reichert, P., Abbaspour, K. C., Xia, J., & Yang, H. (2008). Comparing uncertainty analysis techniques for a SWAT application to the Chaohe Basin in China. Journal of Hydrology, 358(1-2), 1-23. doi:10.1016/j.jhydrol.2008.05.012D. N. Moriasi, J. G. Arnold, M. W. Van Liew, R. L. Bingner, R. D. Harmel, & T. L. Veith. (2007). Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations. Transactions of the ASABE, 50(3), 885-900. doi:10.13031/2013.23153Gupta, H. V., Kling, H., Yilmaz, K. K., & Martinez, G. F. (2009). Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling. Journal of Hydrology, 377(1-2), 80-91. doi:10.1016/j.jhydrol.2009.08.003Kling, H., Fuchs, M., & Paulin, M. (2012). Runoff conditions in the upper Danube basin under an ensemble of climate change scenarios. Journal of Hydrology, 424-425, 264-277. doi:10.1016/j.jhydrol.2012.01.011Knoben, W. J. M., Freer, J. E., & Woods, R. A. (2019). Technical note: Inherent benchmark or not? Comparing Nash–Sutcliffe and Kling–Gupta efficiency scores. Hydrology and Earth System Sciences, 23(10), 4323-4331. doi:10.5194/hess-23-4323-2019Runkel, R. L., Crawford, C. G., & Cohn, T. A. (2004). Load estimator (LOADEST): a FORTRAN program for estimating constituent loads in streams and rivers. Techniques and Methods. doi:10.3133/tm4a5Boithias, L., Srinivasan, R., Sauvage, S., Macary, F., & Sánchez-Pérez, J. M. (2014). Daily Nitrate Losses: Implication on Long-Term River Quality in an Intensive Agricultural Catchment of Southwestern France. Journal of Environmental Quality, 43(1), 46-54. doi:10.2134/jeq2011.0367Meaurio, M., Zabaleta, A., Uriarte, J. A., Srinivasan, R., & Antigüedad, I. (2015). Evaluation of SWAT models performance to simulate streamflow spatial origin. The case of a small forested watershed. Journal of Hydrology, 525, 326-334. doi:10.1016/j.jhydrol.2015.03.050Mittelstet, A. R., Storm, D. E., & White, M. J. (2016). Using SWAT to enhance watershed-based plans to meet numeric water quality standards. Sustainability of Water Quality and Ecology, 7, 5-21. doi:10.1016/j.swaqe.2016.01.002Spearman, C. (1904). The Proof and Measurement of Association between Two Things. The American Journal of Psychology, 15(1), 72. doi:10.2307/1412159Taguas, E. V., Gómez, J. A., Denisi, P., & Mateos, L. (2015). Modelling the Rainfall-Runoff Relationships in a Large Olive Orchard Catchment in Southern Spain. Water Resources Management, 29(7), 2361-2375. doi:10.1007/s11269-015-0946-6Vicente, D. J., Rodríguez-Sinobas, L., Garrote, L., & Sánchez, R. (2018). Applying Water Accounting Methods Through Statistical Data and Simulation Models. Advances in Chemical Pollution, Environmental Management and Protection, 115-146. doi:10.1016/bs.apmp.2018.06.001Vautard, R., Gobiet, A., Sobolowski, S., Kjellström, E., Stegehuis, A., Watkiss, P., … Jacob, D. (2014). The European climate under a 2 °C global warming. Environmental Research Letters, 9(3), 034006. doi:10.1088/1748-9326/9/3/034006Wei, X., Sauvage, S., Le, T. P. Q., Ouillon, S., Orange, D., Vinh, V. D., & Sanchez-Perez, J.-M. (2019). A Modeling Approach to Diagnose the Impacts of Global Changes on Discharge and Suspended Sediment Concentration within the Red River Basin. Water, 11(5), 958. doi:10.3390/w11050958Jeuffroy, M.-H., Casadebaig, P., Debaeke, P., Loyce, C., & Meynard, J.-M. (2013). Agronomic model uses to predict cultivar performance in various environments and cropping systems. A review. Agronomy for Sustainable Development, 34(1), 121-137. doi:10.1007/s13593-013-0170-9Uribe, N., Corzo, G., Quintero, M., van Griensven, A., & Solomatine, D. (2018). Impact of conservation tillage on nitrogen and phosphorus runoff losses in a potato crop system in Fuquene watershed, Colombia. Agricultural Water Management, 209, 62-72. doi:10.1016/j.agwat.2018.07.006Estrela, T., Pérez-Martin, M. A., & Vargas, E. (2012). Impacts of climate change on water resources in Spain. Hydrological Sciences Journal, 57(6), 1154-1167. doi:10.1080/02626667.2012.702213Robles-Morua, A., Halvorsen, K. E., Mayer, A. S., & Vivoni, E. R. (2014). Exploring the application of participatory modeling approaches in the Sonora River Basin, Mexico. Environmental Modelling & Software, 52, 273-282. doi:10.1016/j.envsoft.2013.10.006Starkl, M., Brunner, N., López, E., & Martínez-Ruiz, J. L. (2013). A planning-oriented sustainability assessment framework for peri-urban water management in developing countries. Water Research, 47(20), 7175-7183. doi:10.1016/j.watres.2013.10.037Kim, J., Lim, K. J., & Park, Y. S. (2018). Evaluation of Regression Models of LOADEST and Eight-Parameter Model for Nitrogen Load Estimations. Water, Air, & Soil Pollution, 229(6). doi:10.1007/s11270-018-3844-8Cerro, I., Antigüedad, I., Srinavasan, R., Sauvage, S., Volk, M., & Sanchez-Perez, J. M. (2014). Simulating Land Management Options to Reduce Nitrate Pollution in an Agricultural Watershed Dominated by an Alluvial Aquifer. Journal of Environmental Quality, 43(1), 67-74. doi:10.2134/jeq2011.0393Jégo, G., Martínez, M., Antigüedad, I., Launay, M., Sanchez-Pérez, J. M., & Justes, E. (2008). Evaluation of the impact of various agricultural practices on nitrate leaching under the root zone of potato and sugar beet using the STICS soil–crop model. Science of The Total Environment, 394(2-3), 207-221. doi:10.1016/j.scitotenv.2008.01.021Olesen, J. E., Carter, T. R., Díaz-Ambrona, C. H., Fronzek, S., Heidmann, T., Hickler, T., … Sykes, M. T. (2007). Uncertainties in projected impacts of climate change on European agriculture and terrestrial ecosystems based on scenarios from regional climate models. Climatic Change, 81(S1), 123-143. doi:10.1007/s10584-006-9216-1Stahl, K., Hisdal, H., Hannaford, J., Tallaksen, L. M., van Lanen, H. A. J., Sauquet, E., … Jódar, J. (2010). Streamflow trends in Europe: evidence from a dataset of near-natural catchments. Hydrology and Earth System Sciences, 14(12), 2367-2382. doi:10.5194/hess-14-2367-2010Jeppesen, E., Kronvang, B., Olesen, J. E., Audet, J., Søndergaard, M., Hoffmann, C. C., … Özkan, K. (2010). Climate change effects on nitrogen loading from cultivated catchments in Europe: implications for nitrogen retention, ecological state of lakes and adaptation. Hydrobiologia, 663(1), 1-21. doi:10.1007/s10750-010-0547-6Peraza-Castro, M., Ruiz-Romera, E., Meaurio, M., Sauvage, S., & Sánchez-Pérez, J. M. (2018). Modelling the impact of climate and land cover change on hydrology and water quality in a forest watershed in the Basque Country (Northern Spain). Ecological Engineering, 122, 315-326. doi:10.1016/j.ecoleng.2018.07.016Pesce, M., Critto, A., Torresan, S., Giubilato, E., Santini, M., Zirino, A., … Marcomini, A. (2018). Modelling climate change impacts on nutrients and primary production in coastal waters. Science of The Total Environment, 628-629, 919-937. doi:10.1016/j.scitotenv.2018.02.131Sinnathamby, S., Douglas-Mankin, K. R., & Craige, C. (2017). Field-scale calibration of crop-yield parameters in the Soil and Water Assessment Tool (SWAT). Agricultural Water Management, 180, 61-69. doi:10.1016/j.agwat.2016.10.024Gudmundsson, L., Tallaksen, L. M., Stahl, K., Clark, D. B., Dumont, E., Hagemann, S., … Koirala, S. (2012). Comparing Large-Scale Hydrological Model Simulations to Observed Runoff Percentiles in E