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Landscape heterogeneity and hydrological processes: a review of landscape-based hydrological models

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Abstract

Introduction

Landscapes and water are closely linked. Water shapes landscapes, and landscape heterogeneity in turn determines water storage, partitioning, and movement. Understanding hydrological processes from an ecological perspective is an exciting and fast-growing field of research.

Objectives

The motivation of this paper is to review advances in the interaction between landscape heterogeneity and hydrological processes, and propose a framework for synthesizing and moving forward.

Methods

Landscape heterogeneity, mainly topography and land cover, has been widely incorporated into existing hydrological models, but not in a systematic way. Topography, as one of the most important landscape traits, has been extensively used in hydrological models, but mostly to drive water flow downhill. Land cover heterogeneity, represented mostly by vegetation, is usually linked with evaporation and transpiration rather than runoff generation. Moreover, the proportion of different land cover types is usually the only index involved in hydrological models, leaving the influence of vegetation patterns and structure on hydrologic connectivity still largely unexplored. Additionally, moving from “what heterogeneity exists” to “why-type” questions probably offers us new insights into the nexus of landscape and water.

Conclusions

We believe that the principles of self-organization and co-evolution of landscape features shed light on the possibility to infer subsurface heterogeneity from a few observable landscapes, allowing us to simplify complexity to a few quantifiable metrics, and utilizing these metrics in models with sufficient heterogeneity but limited complexity. Landscape-based models can also be beneficial to improve our ability of prediction in ungauged basins and prediction in a changing environment (Panta Rhei, everything flows).

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References

  • Abbott MB, Bathurst JC, Cunge JA, O'Connell PE, Rasmussen J (1986) An introduction tothe european hydrological system — systeme hydrologique europeen, “she”, 1: history and philosophyof a physically-based, distributed modelling system. J Hydrol 87(1):45–59

    Article  Google Scholar 

  • Aber JD (1999) Hydrological and biogeochemical processes in complex landscapes: what is the role of temporal and spatial ecosystem dynamics? In: Tenhunen JD, Kabat B (eds) Integrating hydrology ecosystem dynamics, and biogeochemistry in complex landscapes. Wiley, Chichester, pp 335–355

    Google Scholar 

  • Aguilar C, Herrero J, Polo MJ (2010) Topographic effects on solar radiation distribution in mountainous watersheds and their influence on reference evapotranspiration estimates at watershed scale. Hydrol Earth Syst Sci 14:2479–2494. https://doi.org/10.5194/hess-14-2479-2010

    Article  Google Scholar 

  • Allan JD (2004) Landscapes and riverscapes: the influence of land use on stream ecosystems. Annu Rev Ecol Evol Syst 35:257–284. https://doi.org/10.1146/annurev.ecolsys.35.120202.110122

    Article  Google Scholar 

  • Allen, T. F. H. (2001). A summary of the principles of hierarchy theory. http://www.isss.org/hierarchy.htm

  • Ambroise B (2004) Variable “active”versus “contributing”areas or periods: a necessary distinction. Hydrol Process 18:1149–1155

    Article  Google Scholar 

  • Bak P (2013) How nature works: the science of self-organized criticality. Springer Science & Business Media, Berlin

    Google Scholar 

  • Baldocchi DD (2003) Assessing the eddy covariance technique for evaluating carbon dioxide exchange rates of ecosystems: past, present and future. Glob Chang Biol 9:479–492. https://doi.org/10.1046/j.1365-2486.2003.00629.x

    Article  Google Scholar 

  • Band LE, Peterson DL, Running SW, Coughlan J, Lammers R, Dungan J, Nemani R (1991) Forest ecosystem processes at the watershed scale: basis for distributed simulation. Ecol Modell 56:171–196

    Article  Google Scholar 

  • Barry RG (1992) Mountain weather and climate. Psychology Press, Hove

    Book  Google Scholar 

  • Bastiaanssen WGM, Pelgrum H, Wang J, Ma Y, Moreno JF, Roerink GJ, van der Val T (1998) A remote sensing surface energy balance algorithm for land (SEBAL). Part 2: validation. J Hydrol 212(1–4):213–229

    Article  Google Scholar 

  • Bastiaanssen WGM, Cheema MJM, Immerzeel WW, Miltenburg IJ, Pelgrum H (2012) Surface energy balance and actual evapotranspiration of the transboundary Indus Basin estimated from satellite measurements and the ETLook model. Water Resour Res 48:1–16. https://doi.org/10.1029/2011WR010482

    Article  Google Scholar 

  • Bengtsson L (2010) The global atmospheric water cycle. Environ Res Lett 5:25202

    Article  Google Scholar 

  • Bergström S, Lindström G (2015) Interpretation of runoff processes in hydrological modelling—experience from the HBV approach. Hydrol Process 29:3535–3545

    Article  Google Scholar 

  • Berne A, Uijlenhoet R, Troch PA (2005) Similarity analysis of subsurface flow response of hillslopes with complex geometry. Water Resour Res. https://doi.org/10.1029/2004WR003629

    Article  Google Scholar 

  • Beven K (2002) Towards an alternative blueprint for a physically based digitally simulated hydrologic response modelling system. Hydrol Process 16:189–206. https://doi.org/10.1002/hyp.343

    Article  Google Scholar 

  • Beven KJ (2011) Rainfall-runoff modelling: the primer. Wiley, New York

    Google Scholar 

  • Beven K, Germann PF (1982) Macropores and water flows in soils. Water Resour Res 18:1311–1325. https://doi.org/10.1029/WR018i005p01311

    Article  Google Scholar 

  • Beven K, Germann P (2013) Macropores and water flow in soils revisited. Water Resour Res 49:3071–3092. https://doi.org/10.1002/wrcr.20156

    Article  Google Scholar 

  • Beven KJ, Kirkby MJ (1979) A physically based, variable contributing area model of basin hydrology/Un modèle à base physique de zone d’appel variable de l’hydrologie du bassin versant. Hydrol Sci Bull 24:43–69. https://doi.org/10.1080/02626667909491834

    Article  Google Scholar 

  • Blöschl G, Sivapalan M (1995) Scale issues in hydrological modelling: a review. Hydrol Process 9:251–290. https://doi.org/10.1002/hyp.3360090305

    Article  Google Scholar 

  • Bras RL (2015) Complexity and organization in hydrology: a personal view. Water Resour Res 51:6532–6548. https://doi.org/10.1002/2015WR016958

    Article  Google Scholar 

  • Broxton PD, Troch PA, Lyon SW (2009) On the role of aspect to quantify water transit times in small mountainous catchments. Water Resour Res. https://doi.org/10.1029/2008WR007438

    Article  Google Scholar 

  • Brutsaert W, Sugita M (2008) Is Mongolia’s groundwater increasing or decreasing? The case of the Kherlen River basin/Les eaux souterraines de Mongolie s’accroissent ou décroissent-elles? Cas du bassin versant la Rivière Kherlen. Hydrol Sci J 53:1221–1229. https://doi.org/10.1623/hysj.53.6.1221

    Article  Google Scholar 

  • Budyko MI (1974) Climate and life, translated from Russian by DH Miller. Elsevier, New York

    Google Scholar 

  • Burt TP, Pinay G (2005) Linking hydrology and biogeochemistry in complex landscapes. Prog Phys Geogr 29:297–316

    Article  Google Scholar 

  • Chen X, Chen YD (2004) Human-induced hydrological changes in the river network of the Pearl River Delta, South China. IAHS Publ, Guangzhou, pp 197–205

    Google Scholar 

  • Chorover J, Troch PA, Rasmussen C, Brooks PD, Pelletier JD, Breshars DD, Huxman TE, Kurc SA, Lohse KA, Mclntosh JC, Meixner T, Schaap MG, Litvak ME, Perdrial J, Harpold A, Durcik M (2011) How water, carbon, and energy drive critical zone evolution: the Jemez-Santa Catalina Critical Zone Observatory. Vadose Zone J 10:884–899

    Article  CAS  Google Scholar 

  • Clair JS, Moon S, Holbrook WS, Perron JT, Riebe CS, Martel SJ, Carr B, Harman C, Singha K, deB Richter D, (2015) Geophysical imaging reveals topographic stress control of bedrock weathering. Science 350:534–538

    Article  Google Scholar 

  • Coenders-Gerrits AMJ, Van der Ent RJ, Bogaard TA, Wang-Erlandsson L, Hrachowitz M, Savenije HHG (2014) Uncertainties in transpiration estimates. Nature 506:E1–E2. https://doi.org/10.1038/nature12925

    Article  PubMed  CAS  Google Scholar 

  • Costa-Cabral MC, Burges SJ (1994) Digital elevation model networks (DEMON): a model of flow over hillslopes for computation of contributing and dispersal areas. Water Resour Res 30:1681–1692

    Article  Google Scholar 

  • Covault JA, Craddock WH, Romans BW, Fildani A, Gosai M (2013) Spatial and temporal variations in landscape evolution: historic and longer-term sediment flux through global catchments. J Geol 121:35–56. https://doi.org/10.1086/668680

    Article  Google Scholar 

  • Cox BA (2003) A review of currently available in-stream water-quality models and their applicability for simulating dissolved oxygen in lowland rivers. Sci Total Environ 314:335–377

    Article  PubMed  Google Scholar 

  • Dawson CW, Wilby RL (2001) Hydrological modelling using artificial neural networks. Prog Phys Geogr 25:80–108. https://doi.org/10.1177/030913330102500104

    Article  Google Scholar 

  • de Boer-Euser T, McMillan HK, Hrachowitz M, Winsemius HC, Savenije HH (2016) Influence of soil and climate on root zone storage capacity. Water Resour Res 52:2009–2024. https://doi.org/10.1002/2015WR018115

    Article  Google Scholar 

  • Detty JM, McGuire KJ (2010) Threshold changes in storm runoff generation at a till-mantled headwater catchment. Water Resour Res. https://doi.org/10.1029/2009wr008102

    Article  Google Scholar 

  • Dunne T, Zhang W, Aubry BF (1991) Effects of rainfall, vegetation, and microtopography on infiltration and runoff. Water Resour Res 27:2271–2285

    Article  Google Scholar 

  • EPA SWMM5 (2005) Storm water management model. U.S. Environmental Protection Agency, Washington, DC

    Google Scholar 

  • Euser T, Hrachowitz M, Winsemius HC, Savenije HHG (2015) The effect of forcing and landscape distribution on performance and consistency of model structures. Hydrol Process 29:3727–3743. https://doi.org/10.1002/hyp.10445

    Article  Google Scholar 

  • Fan Y, Miguezmacho G, Jobbágy EG, Jackson RB, Oterocasal C (2017) Hydrologic regulation of plant rooting depth. Proc Natl Acad Sci USA 114(40):201712381

    Article  Google Scholar 

  • Fenicia F, Kavetski D, Savenije HHG (2011) Elements of a flexible approach for conceptual hydrological modeling: 1. Motivation and theoretical development. Water Resour Res. https://doi.org/10.1029/2010wr010174

    Article  Google Scholar 

  • Fenicia F, Savenije HHG, Avdeeva Y (2009) Anomaly in the rainfall-runoff behaviour of the Meuse catchment. Climate, land-use, or land-use management? Hydrol Earth Syst Sci 13(9):1727–1737

    Article  Google Scholar 

  • Ferguson BK (1991) Landscape hydrology, a component of landscape ecology. J Environ Syst 21:193–205

    Article  Google Scholar 

  • Fletcher TD, Andrieu H, Hamel P (2013) Understanding, management and modelling of urban hydrology and its consequences for receiving waters: a state of the art. Adv Water Resour 51:261–279

    Article  Google Scholar 

  • Ford WI, Fox JF, Pollock E (2017) Reducing equifinality using isotopes in a process-based stream nitrogen model highlights the flux of algal nitrogen from agricultural streams. Water Resour Res 53:6539–6561. https://doi.org/10.1002/2017WR020607

    Article  CAS  Google Scholar 

  • Forman RTT, Godron M (1986) Landscape ecology. Wiley, Chichester

    Google Scholar 

  • Freeze RA, Harlan RL (1969) Blueprint for a physically-based, digitally-simulated hydrologic response model. J Hydrol 9:237–258

    Article  Google Scholar 

  • Frissell CA, Liss WJ, Warren CE, Hurley MD (1986) A hierarchical framework for stream habitat classification: viewing streams in a watershed context. Environ Manage 10:199–214. https://doi.org/10.1007/BF01867358

    Article  Google Scholar 

  • Fu BP (1981) On the calculation of the evaporation from land surface. Sci Atmos Sin 5:23–31

    Google Scholar 

  • Fu B, Chen L, Ma K, Zhou H, Wang J (2000) The relationships between land use and soil conditions in the hilly area of the loess plateau in northern Shaanxi, China. CATENA 39:69–78. https://doi.org/10.1016/S0341-8162(99)00084-3

    Article  Google Scholar 

  • Fu B-J, Wu B-F, Lü Y-H, Xu Z-H, Cao J-H, Niu D, Yang G-S, Zhou Y-M (2010) Three Gorges project: efforts and challenges for the environment. Prog Phys Geogr 34:741–754. https://doi.org/10.1177/0309133310370286

    Article  Google Scholar 

  • Gao H, Birkel C, Hrachowitz M, Tetzlaff D, Soulsby C, Savenije HHG (2018) A simple topography-driven and calibration-free runoff generation model. Hydrol Earth Syst Sci Discuss. https://doi.org/10.5194/hess-2018-141-RC1

    Article  Google Scholar 

  • Gao H, Ding Y, Zhao Q, Hrachowitz M, Savenije HHG (2017a) The importance of aspect for modelling the hydrological response in a glacier catchment in Central Asia. Hydrol Process 31(16):2842–2859

    Article  Google Scholar 

  • Gao H, Han T, Liu Y, Zhao Q (2017b) Use of auxiliary data of topography, snow and ice to improve model performance in a glacier-dominated catchment in Central Asia. Hydrol Res 48(5):1418–1437

    Article  Google Scholar 

  • Gao H, He X, Ye B, Pu J (2012) Modeling the runoff and glacier mass balance in a small watershed on the Central Tibetan Plateau, China, from 1955 to 2008. Hydrol Process 26:1593–1603. https://doi.org/10.1002/hyp.8256

    Article  Google Scholar 

  • Gao H, Hrachowitz M, Fenicia F, Gharari S, Savenije HHG (2014a) Testing the realism of a topography-driven model (FLEX-Topo) in the nested catchments of the Upper Heihe, China. Hydrol Earth Syst Sci 18:1895–1915. https://doi.org/10.5194/hess-18-1895-2014

    Article  Google Scholar 

  • Gao H, Hrachowitz M, Schymanski SJ, Fenicia F, Sriwongsitanon N, Savenije HHG (2014b) Climate controls how ecosystems size the root zone storage capacity at catchment scale. Geophys Res Lett 41:7916–7923. https://doi.org/10.1002/2014GL061668

    Article  Google Scholar 

  • Gao H, Hrachowitz M, Sriwongsitanon N, Fenicia F, Gharari S, Savenije HHG (2016) Accounting for the influence of vegetation and landscape improves model transferability in a tropical savannah region. Water Resour Res 52:7999–8022. https://doi.org/10.1002/2016WR019574

    Article  Google Scholar 

  • Gharari S, Hrachowitz M, Fenicia F, Savenije HHG (2011) Hydrological landscape classification: investigating the performance of HAND based landscape classifications in a central European meso-scale catchment. Hydrol Earth Syst Sci 15:3275–3291. https://doi.org/10.5194/hess-15-3275-2011

    Article  Google Scholar 

  • Gharari S, Hrachowitz M, Fenicia F, Gao H, Savenije HHG (2014) Using expert knowledge to increase realism in environmental system models can dramatically reduce the need for calibration. Hydrol Earth Syst Sci 18:4839–4859. https://doi.org/10.5194/hess-18-4839-2014

    Article  Google Scholar 

  • Good SP, Noone D, Bowen G (2015) Hydrologic connectivity constrains partitioning of global terrestrial water fluxes. Science 349:175–177

    Article  PubMed  CAS  Google Scholar 

  • Harman CJ, Lohse KA, Troch PA, Sivapalan M (2014) Spatial patterns of vegetation, soils, and microtopography from terrestrial laser scanning on two semiarid hillslopes of contrasting lithology. J Geophys Res Biogeosci 119:163–180

    Article  Google Scholar 

  • Heistermann M, Müller C, Ronneberger K (2006) Land in sight? Achievements, deficits and potentials of continental to global scale land-use modeling. Agr Ecosyst Environ 114:141–158

    Article  Google Scholar 

  • Hoorn C, Wesselingh FP, ter Steege H, Bermudez MA, Mora A, Sevink J, Sanmartin I, Sanchez-Meseguer A, Anderson CL, Figueiredo JP, Jaramillo C, Riff D, Negri FR, Hooghiemstra H, Lundberg J, Stadler T, Sarkinen T, Antonelli A (2010) Amazonia through time: Andean uplift, climate change, landscape evolution, and biodiversity. Science 330:927–931

    Article  PubMed  CAS  Google Scholar 

  • Hrachowitz M, Savenije HHG, Blöschl G, McDonnell JJ, Sivapalan M, Pomeroy JW, Arheimer B, Blume T, Clark MP, Ehret U, Fenicia F, Freer JE, Gelfan A, Gupta HV, Hughes DA, Hut RW, Montanari A, Pande S, Tetzlaff D, Troch PA, Uhlenbrook S, Wagener T, Winsemius HC, Woods RA, Zehe E, Cudennec C (2013a) A decade of predictions in ungauged basins (PUB)—a review. Hydrol Sci J 58:1198–1255. https://doi.org/10.1080/02626667.2013.803183

    Article  Google Scholar 

  • Hrachowitz M, Savenije H, Bogaard TA, Tetzlaff D, Soulsby C (2013b) What can flux tracking teach us about water age distribution patterns and their temporal dynamics? Hydrol Earth Syst Sci 17:533–564. https://doi.org/10.5194/hess-17-533-2013

    Article  Google Scholar 

  • Huffman GJ, Adler RF, Bolvin DT, Nelkin EJ (2010) The TRMM multi-satellite precipitation analysis (TMPA). Satellite rainfall applications for surface hydrology. Springer, Netherlands

    Google Scholar 

  • Hunsaker CT, Levine DA (1995) Hierarchical approaches to the study of water quality in rivers. Bioscience 45:193–203. https://doi.org/10.2307/1312558

    Article  Google Scholar 

  • Ivanov VY, Vivoni ER, Bras RL, Entekhabi D (2004) Preserving high-resolution surface and rainfall data in operational-scale basin hydrology: a fully-distributed physically-based approach. J Hydrol 298:80–111. https://doi.org/10.1016/j.jhydrol.2004.03.041

    Article  Google Scholar 

  • Jasechko S, Sharp ZD, Gibson JJ, Jean Birks S, Yi Y, Fawcett PJ (2013) Terrestrial water fluxes dominated by transpiration. Nature 496:347–350. https://doi.org/10.1038/nature11983

    Article  PubMed  CAS  Google Scholar 

  • Jencso KG, McGlynn BL, Gooseff MN, Wondzell SM, Bencala KE, Marshall LA (2009) Hydrologic connectivity between landscapes and streams: transferring reach- and plot-scale understanding to the catchment scale. Water Resour Res 45:1–16. https://doi.org/10.1029/2008WR007225

    Article  Google Scholar 

  • Kirchner JW (2006) Getting the right answers for the right reasons: linking measurements, analyses, and models to advance the science of hydrology. Water Resour Res. https://doi.org/10.1029/2005wr004362

    Article  Google Scholar 

  • Kirkby M, Bracken L, Reaney S (2002) The influence of land use, soils and topography on the delivery of hillslope runoff to channels in SE Spain. Earth Surf Process Landforms 27:1459–1473. https://doi.org/10.1002/esp.441

    Article  Google Scholar 

  • Klausmeier CA (1999) Regular and irregular patterns in semiarid vegetation. Science (80-) 284:1826–1828

  • Lane SN, Brookes CJ, Kirkby MJ, Holden J (2004) A network-index-based version of TOPMODEL for use with high-resolution digital topographic data. Hydrol Process 18:191–201. https://doi.org/10.1002/hyp.5208

    Article  Google Scholar 

  • Lane SN, Reaney SM, Heathwaite AL (2009) Representation of landscape hydrological connectivity using a topographically driven surface flow index. Water Resour Res. https://doi.org/10.1029/2008wr007336

    Article  Google Scholar 

  • Li X, Ren L (2007) Effect of temporal resolution of ndvi on potential evapotranspiration estimation and hydrological model performance. Chin Geogra Sci 17(4):357–363

    Article  CAS  Google Scholar 

  • Lian X, Piao S, Huntingford C, Li Y, Zeng Z, Wang X, Ciais P, McVicar TR, Peng S, Ottlé C, Yang H, Yang Y, Zhang Y, Wang T (2018) Partitioning global land evapotranspiration using CMIP5 models constrained by observations. Nat Clim Change 8(7):640–646. https://doi.org/10.1038/s41558-018-0207-9

    Article  Google Scholar 

  • Liang X, Lettenmaier DP, Wood EF, Burges SJ (1994) A simple hydrologically based model of land surface water and energy fluxes for general circulation models. J Geophys Res 99:14415. https://doi.org/10.1029/94JD00483

    Article  Google Scholar 

  • Lin H, Bouma J, Pachepsky Y, Western A, Thompson J, van Genuchten R, Vogel H-J, Lilly A (2006) Hydropedology: synergistic integration of pedology and hydrology. Water Resour Res. https://doi.org/10.1029/2005wr004085

    Article  Google Scholar 

  • Liu X, Liang Xun, Li Xia, Xiaocong Xu, Jinpei Ou, Chen Yimin, Li Shaoying, Wang Shaojian, Pei Fengsong (2017) A future land use simulation model (FLUS) for simulating multiple land use scenarios by coupling human and natural effects. Landsc Urban Plann 168:94–116

    Article  Google Scholar 

  • Long D, Pan Y, Zhou J, Chen Y, Hou X, Hong Y, Scanlon BR, Longuevergne L (2017) Global analysis of spatiotemporal variability in merged total water storage changes using multiple GRACE products and global hydrological models. Remote Sens Environ 192:198–216

    Article  Google Scholar 

  • Lookingbill T, Urban D (2004) An empirical approach towards improved spatial estimates of soil moisture for vegetation analysis. Landsc Ecol 19:417–433

    Article  Google Scholar 

  • Martinez GF, Gupta HV (2011) Hydrologic consistency as a basis for assessing complexity of monthly water balance models for the continental United States. Water Resour Res 47:W12540. https://doi.org/10.1029/2011wr011229

    Article  Google Scholar 

  • McDonnell J (2003) Where does water go when it rains? Moving beyond the variable source area concept of rainfall-runoff response. Hydrol Process 17:1869–1875. https://doi.org/10.1002/hyp.5132

    Article  Google Scholar 

  • McDonnell JJ, Sivapalan M, Vaché K, Dunn S, Grant G, Haggerty R, Hinz C, Hooper R, Kirchner J, Roderick ML, Selker J, Weiler M (2007) Moving beyond heterogeneity and process complexity: a new vision for watershed hydrology. Water Resour Res. https://doi.org/10.1029/2006wr005467

    Article  Google Scholar 

  • McGarigal K, Cushman SA, Ene E (2012) FRAGSTATS v4: spatial pattern analysis program for categorical and continuous maps. University of Massachusetts, Amherst, MA

    Google Scholar 

  • McGlynn BL, McDonnell JJ (2003) Quantifying the relative contributions of riparian and hillslope zones to catchment runoff. Water Resour Res. https://doi.org/10.1029/2003wr002091

    Article  Google Scholar 

  • Melsen LA, Teuling AJ, van Berkum SW, Torfs PJJF, Uijlenhoet R (2014) Catchments as simple dynamical systems: a case study on methods and data requirements for parameter identification. Water Resour Res 50:5577–5596. https://doi.org/10.1002/2013wr014720.received

    Article  Google Scholar 

  • Milly PCD (1994) Climate, soil water storage, and the average annual water balance. Water Resour Res 30:2143–2156. https://doi.org/10.1029/94WR00586

    Article  Google Scholar 

  • Mitchell VG, Duncan HP, Inman M, Rahilly M, Stewart J, Vieritz A, Holt P, Grant A, Fletcher TD, Coleman JR, Maheepala S, Sharma A, Deletic A, Breen P (2007) Integrated urban water modelling—past, present and future. Rainwater 2007, Sydney, NSW. In: Proceedings of the thirteenth international conference on rain water catchment systems.

  • Molenat J, Gascuel-Odoux C, Ruiz L, Gruau G (2008) Role of water table dynamics on stream nitrate export and concentration in agricultural headwater catchment (France). J Hydrol 348:363–378

    Article  Google Scholar 

  • Montanarella L, Panagos P (2015) Policy relevance of critical zone science. Land Use Policy 49:86–91. https://doi.org/10.1016/j.landusepol.2015.07.019

    Article  Google Scholar 

  • Montanari A, Young G, Savenije HHG, Hughes D, Wagener T, Ren LL, Koutsoyiannis D, Cudennec C, Toth E, Grimaldi S, Blöschl G, Sivapalan M, Beven K, Gupta H, Hipsey M, Schaefli B, Arheimer B, Boegh E, Schymanski SJ, Di Baldassarre G, Yu B, Hubert P, Huang Y, Schumann A, Post DA, Srinivasan V, Harman C, Thompson S, Rogger M, Viglione A, McMillan H, Charachlis G, Pang Z, Belyaev V (2013) “Panta Rhei—everything flows”: change in hydrology and society—the IAHS scientific decade 2013–2022. Hydrol Sci J 58:1256–1275

    Article  Google Scholar 

  • Mücher CA, Klijn JA, Wascher DM, Schaminée JHJ (2010) A new european landscape classification (LANMAP): a transparent, flexible and user-oriented methodology to distinguish landscapes. Ecol Indic 10:87–103. https://doi.org/10.1016/j.ecolind.2009.03.018

    Article  Google Scholar 

  • Mutzner R, Bertuzzo E, Tarolli P, Weijs SV, Nicotina L, Ceola S, Tomasic N, Rodriguez-Iturbe I, Parlange MB, Rinaldo A (2013) Geomorphic signatures on Brutsaert base flow recession analysis. Water Resour Res 49:5462–5472. https://doi.org/10.1002/wrcr.20417

    Article  Google Scholar 

  • Nijzink R, Hutton C, Pechlivanidis I, Capell R, Arheimer B, Freer J, Han D, Wagener T, McGuire K, Savenije H, Hrachowitz M (2016) The evolution of root-zone moisture capacities after deforestation: a step towards hydrological predictions under change? Hydrol Earth Syst Sci 20:4775–4799. https://doi.org/10.5194/hess-20-4775-2016

    Article  Google Scholar 

  • Peano A, Cassatella C (2011) Landscape assessment landscape assessment and monitoring landscape monitoring. In: Peano A, Cassatella C (eds) Landscape indicators. Springer, New York, pp 1–14

    Google Scholar 

  • Pelletier JD, Barron-Gafford GA, Breshears DD, Brooks PD, Chorover J, Durcik M, Harman CJ, Huxman TE, Lohse KA, Lybrand R, Meixner T, McIntosh JC, Papuga SA, Rasmussen C, Schaap M, Swetnam TL, Troch PA (2013) Coevolution of nonlinear trends in vegetation, soils, and topography with elevation and slope aspect: a case study in the sky islands of southern Arizona. J Geophys Res Earth Surf 118:741–758. https://doi.org/10.1002/jgrf.20046

    Article  Google Scholar 

  • Perrin C, Michel C, Andréassian V (2001) Does a large number of parameters enhance model performance? Comparative assessment of common catchment model structures on 429 catchments. J Hydrol 242:275–301. https://doi.org/10.1016/S0022-1694(00)00393-0

    Article  Google Scholar 

  • Pickett STA, Cadenasso ML (1995) Landscape ecology: spatial heterogeneity in ecological systems. Science 269:331

    Article  PubMed  CAS  Google Scholar 

  • Pijanowski BC, Robinson KD (2011) Rates and patterns of land use change in the Upper Great Lakes States, USA: a framework for spatial temporal analysis. Landsc Urban Plan 102:102–116. https://doi.org/10.1016/j.landurbplan.2011.03.014

    Article  Google Scholar 

  • Preston StephenD, Alexander RichardB, Wolock DavidM (2011) SPARROW modeling to understand water-quality conditions in major regions of the United States: a featured collection introduction. J Am Water Resour Assoc (JAWRA) 47(5):887–890. https://doi.org/10.1111/j.1752-1688.2011.00585.x

    Article  CAS  Google Scholar 

  • Qiu Y, Fu B, Wang J, Chen L (2001) Spatial variability of soil moisture content and its relation to environmental indices in a semi-arid gully catchment of the Loess Plateau, China. J Arid Environ 49:723–750. https://doi.org/10.1006/jare.2001.0828

    Article  Google Scholar 

  • Qiu J, Turner MG (2015) Importance of landscape heterogeneity in sustaining hydrologic ecosystem services in an agricultural watershed. Ecosphere 6:1–19

    Article  CAS  Google Scholar 

  • Reaney SM, Bracken LJ, Kirkby MJ (2007) Use of the connectivity of runoff model (CRUM) to investigate the influence of storm characteristics on runoff generation and connectivity in semi-arid areas. Hydrol Process 21:894–906. https://doi.org/10.1002/hyp.6281

    Article  Google Scholar 

  • Refsgaard JC, Storm B, Refsgaard A (1995) Recent developments of the systeme hydrologique Europeen (SHE) towards the MIKE SHE. IAHS Publ Proc Reports-Intern Assoc Hydrol Sci 231:427

    Google Scholar 

  • Reggiani P, Sivapalan M, Hassanizadeh SM (2000) Conservation equations governing hillslope responses: exploring the physical basis of water balance. Water Resour Res 36:1845. https://doi.org/10.1029/2000WR900066

    Article  Google Scholar 

  • Rempe DM, Dietrich WE (2014) A bottom-up control on fresh-bedrock topography under landscapes. Proc Natl Acad Sci 111:6576–6581. https://doi.org/10.1073/pnas.1404763111

    Article  PubMed  CAS  Google Scholar 

  • Ren Z, Gao H, Elser JJ (2017) Longitudinal variation of microbial communities in benthic biofilms and association with hydrological and physicochemical conditions in glacier-fed streams. Freshw Sci 36:479–490. https://doi.org/10.1086/693133

    Article  Google Scholar 

  • Reynolds JF, Wu J (1999) Do landscape structural and functional units exist. In: Tenhunen JD, Kabat P (eds) Integrating hydrology ecosystem dynamics, and biogeochemistry in complex landscapes. Wiley, Chichester, pp 273–296

    Google Scholar 

  • Rietkerk M, Van de Koppel J (2008) Regular pattern formation in real ecosystems. Trends Ecol Evol 23:169–175

    Article  PubMed  Google Scholar 

  • Rigon R, Bancheri M, Formetta G, de Lavenne A (2016) The geomorphological unit hydrograph from a historical-critical perspective. Earth Surf Process Landforms 41:27–37. https://doi.org/10.1002/esp.3855

    Article  Google Scholar 

  • Rodríguez-Iturbe I, Porporato A (2007) Ecohydrology of water-controlled ecosystems: soil moisture and plant dynamics. Cambridge University Press, Cambridge

    Google Scholar 

  • Rodríguez-Iturbe I, Rinaldo A (2001) Fractal river basins: chance and self-organization. Cambridge University Press, Cambridge

    Google Scholar 

  • Rodríguez-Iturbe I, Valdés JB (1979) The geomorphologic structure of hydrologic response. Water Resour Res 15:1409–1420. https://doi.org/10.1029/WR015i006p01409

    Article  Google Scholar 

  • Sabo JL, Sinha T, Bowling LC, Schoups GHW, Wallender WW, Campana ME, Cherkauer KA, Fuller PL, Graf WL, Hopmans JW, Kominoski JS, Taylor C, Trimble SW, Webb RH, Wohl EE (2010) Reclaiming freshwater sustainability in the Cadillac Desert. Proc Natl Acad Sci 107:21263–21269. https://doi.org/10.1073/pnas.1009734108

    Article  PubMed  Google Scholar 

  • Samaniego L, Kumar R, Attinger S (2010) Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale. Water Resour Res. https://doi.org/10.1029/2008wr007327

    Article  Google Scholar 

  • Samaniego L, Kumar R, Thober S, Rakovec O, Zink M, Wanders N, Eisner S, Schmied HM, Sutanudjaja EH, Warrach-Sagi K, Attinger S (2017) Toward seamless hydrologic predictions across spatial scales. Hydrol Earth Syst Sci 21:4323–4346. https://doi.org/10.5194/hess-21-4323-2017

    Article  Google Scholar 

  • Sanderson J (1999) Landscape ecology: a top down approach. CRC Press, Boca Raton

    Google Scholar 

  • Savenije HHG (2004) The importance of interception and why we should delete the term evapotranspiration from our vocabulary. Hydrol Process 18:1507–1511. https://doi.org/10.1002/hyp.5563

    Article  Google Scholar 

  • Savenije HHG (2009) HESS opinions “the art of hydrology”. Hydrol Earth Syst Sci 13:157–161. https://doi.org/10.5194/hess-13-157-2009

    Article  Google Scholar 

  • Savenije HHG (2010) HESS opinions “topography driven conceptual modelling (FLEX-Topo)”. Hydrol Earth Syst Sci 14:2681–2692. https://doi.org/10.5194/hess-14-2681-2010

    Article  Google Scholar 

  • Saxton K, Rawls W (2006) Soil water characteristic estimates by texture and organic matter for hydrologic solutions. Soil Sci Soc Am J 70:1569–1578. https://doi.org/10.2136/sssaj2005.0117

    Article  CAS  Google Scholar 

  • Schröder B (2006) Pattern, process, and function in landscape ecology and catchment hydrology? How can quantitative landscape ecology support predictions in ungauged basins? Hydrol Earth Syst Sci Discuss 10:967–979

    Article  Google Scholar 

  • Schymanski SJ, Sivapalan M, Roderick ML, Hutley LB, Beringer J (2009) An optimality-based model of the dynamic feedbacks between natural vegetation and the water balance. Water Resour Res 45:1–18. https://doi.org/10.1029/2008WR006841

    Article  Google Scholar 

  • Seibert J (2003) Groundwater dynamics along a hillslope: a test of the steady state hypothesis. Water Resour Res 39:1–9. https://doi.org/10.1029/2002WR001404

    Article  Google Scholar 

  • Seibert J, McDonnell JJ (2002) On the dialog between experimentalist and modeler in catchment hydrology: use of soft data for multicriteria model calibration. Water Resour Res 38(23):1–14. https://doi.org/10.1029/2001WR000978

    Article  Google Scholar 

  • Seneviratne SI, Corti T, Davin EL, Hirschi M, Jaeger EB, Lehner I, Orlowsky B, Teuling AJ (2010) Investigating soil moisture-climate interactions in a changing climate: a review. Earth Sci Rev 99:125–161. https://doi.org/10.1016/j.earscirev.2010.02.004

    Article  CAS  Google Scholar 

  • Seneviratne SI, Wilhelm M, Stanelle T, van den Hurk B, Hagemann S, Berg A, Cheruy F, Higgins ME, Meier A, Brovkin V, Claussen M, Ducharne A, Dufresne J-L, Findell KL, Ghattas J, Lawrence DM, Malysheve S, Rummukainen M, Smith B (2013) Impact of soil moisture-climate feedbacks on CMIP5 projections: first results from the GLACE-CMIP5 experiment. Geophys Res Lett 40:5212–5217

    Article  Google Scholar 

  • Sivapalan M, Blöschl G, Zhang L, Vertessy R (2003a) Downward approach to hydrological prediction. Hydrol Process 17:2101–2111. https://doi.org/10.1002/hyp.1425

    Article  Google Scholar 

  • Sivapalan M, Kalma J (1995) Scale problems in hydrology: contributions of the Robertson Workshop. Hydrol Process 9:243–250. https://doi.org/10.1002/hyp.3360090304

    Article  Google Scholar 

  • Sivapalan M, Takeuchi K, Franks SW, Gupta VK, Karambiri H, Lakshmi V, Liang X, McDonnell JJ, Mendiondo EM, O’Connell PE, Oki T, Pomeroy JW, Schertzer D, Uhlenbrook S, Zehe E (2003) IAHS decade on predictions in ungauged basins (PUB), 2003–2012: shaping an exciting future for the hydrological sciences. Hydrol Sci J 48:857–880. https://doi.org/10.1623/hysj.48.6.857.51421

    Article  Google Scholar 

  • Smith T, Marshall L, McGlynn B, Jencso K (2013) Using field data to inform and evaluate a new model of catchment hydrologic connectivity. Water Resour Res 49:6834–6846

    Article  Google Scholar 

  • Sriwongsitanon N, Gao H, Savenije HHG, Maekan E, Saengsawang S, Thianpopirug S (2016) Comparing the normalized difference infrared index (NDII) with root zone storage in a lumped conceptual model. Hydrol Earth Syst Sci 20:3361–3377. https://doi.org/10.5194/hess-20-3361-2016

    Article  Google Scholar 

  • Tague CL, Band LE (2004) RHESSys: regional hydro-ecologic simulation system—an object-oriented approach to spatially distributed modeling of carbon, water, and nutrient cycling. Earth Interact 8:1–42

    Article  Google Scholar 

  • Tague C, Grant GE (2004) A geological framework for interpreting the low-flow regimes of Cascade streams. Water Resour Res, Willamette River Basin, Oregon. https://doi.org/10.1029/2003wr002629

    Book  Google Scholar 

  • Tang Q, Gao H, Lu H, Lettenmaier DP (2009) Remote sensing: hydrology. Prog Phys Geogr 33:490–509. https://doi.org/10.1177/0309133309346650

    Article  Google Scholar 

  • Trenberth KE, Fasullo JT, Kiehl J (2009) Earth’s global energy budget. Bull Am Meteorol Soc 90:311–323. https://doi.org/10.1175/2008BAMS2634.1

    Article  Google Scholar 

  • Troch PA, Berne A, Bogaart P, Harman C, Hilberts AGJ, Lyon SW, Paniconi C, Pauwels VRN, Rupp DE, Selker JS, Teuling AJ, Uijlenhoet R, Verhoest NEC (2013a) The importance of hydraulic groundwater theory in catchment hydrology: the legacy of Wilfried Brutsaert and Jean-Yves Parlange. Water Resour Res 49:5099–5116. https://doi.org/10.1002/wrcr.20407

    Article  Google Scholar 

  • Troch PA, Carrillo G, Sivapalan M, Wagener T, Sawicz K (2013b) Climate-vegetation-soil interactions and long-term hydrologic partitioning: signatures of catchment co-evolution. Hydrol Earth Syst Sci 17:2209–2217. https://doi.org/10.5194/hess-17-2209-2013

    Article  Google Scholar 

  • Troch PA, Lahmers T, Meira A, Mukherjee R, Pedersen JW, Roy T, Valdes-Pineda R (2015) Catchment coevolution: a useful framework for improving predictions of hydrological change? Water Resour Res 51:4903–4922

    Article  Google Scholar 

  • Turner MG, Gardner RH (2015) Landscape ecology in theory and practice: pattern and process. Springer, New York, USA, p 482

    Google Scholar 

  • Uhlenbrook S (2006) Catchment hydrology—a science in which all processes are preferential. Hydrol Process 20:3581–3585. https://doi.org/10.1002/hyp.6564

    Article  Google Scholar 

  • Van de Koppel J, Gascoigne JC, Theraulaz G, Rietkerk M, Mooij WM, Herman PMJ (2008) Experimental evidence for spatial self-organization and its emergent effects in mussel bed ecosystems. Science 322:739–742

    Article  PubMed  Google Scholar 

  • Van Nieuwenhuyse BHJ, Antoine M, Wyseure G, Govers G (2011) Pattern-process relationships in surface hydrology: hydrological connectivity expressed in landscape metrics. Hydrol Process 25:3760–3773

    Article  Google Scholar 

  • Vidon PGF, Hill AR (2004) Landscape controls on the hydrology of stream riparian zones. J Hydrol 292:210–228. https://doi.org/10.1016/j.jhydrol.2004.01.005

    Article  Google Scholar 

  • Viville D, Ladouche B, Bariac T (2006) Isotope hydrological study of mean transit time in the granitic Strengbach catchment (Vosges massif, France): application of the FlowPC model with modified input function. Hydrol Process 20:1737–1751

    Article  CAS  Google Scholar 

  • Vivoni ER, Ivanov VY, Bras RL, Entekhabi D (2005) On the effects of triangulated terrain resolution on distributed hydrologic model response. Hydrol Process 19:2101–2122

    Article  Google Scholar 

  • Wagener T, McIntyre N, Lees MJ, Wheater HS, Gupta HV (2003) Towards reduced uncertainty in conceptual rainfall-runoff modelling: dynamic identifiability analysis. Hydrol Process 17:455–476

    Article  Google Scholar 

  • Wang S, Fu B, Piao S, Lü Y, Ciais P, Feng X, Wang Y (2016) Reduced sediment transport in the Yellow River due to anthropogenic changes. Nat Geosci 9:38

    Article  CAS  Google Scholar 

  • Wang D, Hejazi M (2011) Quantifying the relative contribution of the climate and direct human impacts on mean annual streamflow in the contiguous United States. Water Resour Res. https://doi.org/10.1029/2010WR010283

    Article  Google Scholar 

  • Wang Q, Li S, Jia P, Qi C, Ding F (2013) A review of surface water quality models. Sci World J. https://doi.org/10.1155/2013/231768

    Article  Google Scholar 

  • Wang P, Yu J, Pozdniakov SP, Grinevsky SO, Liu C (2014) Shallow groundwater dynamics and its driving forces in extremely arid areas: a case study of the lower Heihe River in northwestern China. Hydrol Process 28:1539–1553. https://doi.org/10.1002/hyp.9682

    Article  Google Scholar 

  • Wang-Erlandsson L, Bastiaanssen WGM, Gao H, Jägermeyr J, Senay GB, van Dijk AIJM, Guerschman JP, Keys PW, Gordon LJ, Savenije HHG (2016) Global root zone storage capacity from satellite-based evaporation. Hydrol Earth Syst Sci 20:1459–1481

    Article  Google Scholar 

  • Wierda A, Fresco LFM, Grootjans AP, van Diggelen R (1997) Numerical assessment of plant species as indicators of the groundwater regime. J Veg Sci 8:707–716

    Article  Google Scholar 

  • Wigmosta MS, Vail LW, Lettenmaier DP (1994) A distributed hydrology-vegetation model for complex terrain. Water Resour Res 30:1665–1679. https://doi.org/10.1029/94WR00436

    Article  Google Scholar 

  • Wiley MJ, Hyndman DW, Pijanowski BC, Kendall AD, Riseng C, Rutherford ES, Cheng ST, Carlson ML, Tyler JA, Stevenson RJ, Steen PJ, Richards PL, Seelback PW, Koche JM, Rediske RR (2010) A multi-modeling approach to evaluating climate and land use change impacts in a Great Lakes River Basin. Hydrobiologia 657:243–262. https://doi.org/10.1007/s10750-010-0239-2

    Article  Google Scholar 

  • Winsemius HC, Savenije HHG, Bastiaanssen WBG (2008) Constraining model parameters on remotely sensed evaporation: justification for distribution in ungauged basins? Hydrol Earth Syst Sci 5(4):1403–1413

    Article  Google Scholar 

  • Winter TC (2001) The concept of hydrologic landscapes. J Am Water Resour Assoc 37:335–349. https://doi.org/10.1111/j.1752-1688.2001.tb00973.x

    Article  Google Scholar 

  • Wu J (2013) Key concepts and research topics in landscape ecology revisited: 30 years after the Allerton Park workshop. Landsc Ecol 28:1–11

    Article  CAS  Google Scholar 

  • Wu J, David JL (2002) A spatially explicit hierarchical approach to modeling complex ecological systems: theory and applications. Ecol Modell 153:7–26

    Article  Google Scholar 

  • Wu J, Hobbs RJ (2007) Key topics in landscape ecology. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Xu YD, Fu BJ, He CS (2013) Assessing the hydrological effect of the check dams in the Loess Plateau, China, by model simulations. Hydrol Earth Syst Sci 17:2185–2193. https://doi.org/10.5194/hess-17-2185-2013

    Article  Google Scholar 

  • Yang D, Shao W, Yeh PJ-F, Yang H, Kanae S, Oki T (2009) Impact of vegetation coverage on regional water balance in the nonhumid regions of China. Water Resour Res 45:W00A14. https://doi.org/10.1029/2008wr006948

    Article  Google Scholar 

  • Yu D, Coulthard TJ (2015) Evaluating the importance of catchment hydrological parameters for urban surface water flood modelling using a simple hydro-inundation model. J Hydrol 524:385–400. https://doi.org/10.1016/j.jhydrol.2015.02.040

    Article  Google Scholar 

  • Zehe E, Flühler H (2001) Preferential transport of isoproturon at a plot scale and a field scale tile-drained site. J Hydrol 247:100–115

    Article  CAS  Google Scholar 

  • Zehe E, Maurer T, Ihringer J, Plate E (2001) Modeling water flow and mass transport in a loess catchment. Phys Chem Earth Part B Hydrol Ocean Atmos 26:487–507. https://doi.org/10.1016/S1464-1909(01)00041-7

    Article  Google Scholar 

  • Zhang L, Dawes WR, Walker GR (2001) Response of mean annual evapotranspiration to vegetation changes at catchment scale. Water Resour Res 37:701–708. https://doi.org/10.1029/2000WR900325

    Article  Google Scholar 

  • Zhang GP, Savenije HHG (2005) Rainfall-runoff modelling in a catchment with a complex groundwater flow system: application of the representative elementary watershed (REW) approach. Hydrol Earth Syst Sci Discuss 2:639–690. https://doi.org/10.5194/hessd-2-639-2005

    Article  Google Scholar 

  • Zhao R-J (1992) The Xinanjiang model applied in China. J Hydrol 135:371–381. https://doi.org/10.1016/0022-1694(92)90096-E

    Article  Google Scholar 

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Acknowledgements

This study was supported by the National Key R&D Program of China (2017YFE0100700), the Key Program of National Natural Science Foundation of China (No. 41730646), and the Key Laboratory for Mountain Hazards and Earth Surface Process, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences (KLMHESP-17-02). We are grateful for constructive comments from Prof. Hubert H. G. Savenije in Delft University of Technology. We also thank the two anonymous referees, whose valuable review helped improve and clarify this manuscript.

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Gao, H., Sabo, J.L., Chen, X. et al. Landscape heterogeneity and hydrological processes: a review of landscape-based hydrological models. Landscape Ecol 33, 1461–1480 (2018). https://doi.org/10.1007/s10980-018-0690-4

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