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Landscape Ecology

, Volume 33, Issue 9, pp 1461–1480 | Cite as

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

  • Hongkai Gao
  • John L. Sabo
  • Xiaohong ChenEmail author
  • Zhiyong Liu
  • Zongji Yang
  • Ze Ren
  • Min LiuEmail author
Review Article

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).

Keywords

Catchment hydrology Landscape ecology Landscape-based hydrological modelling Ecohydrology Landscape patterns 

Notes

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.

References

  1. 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):45–59CrossRefGoogle Scholar
  2. 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 335–355Google Scholar
  3. 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 CrossRefGoogle Scholar
  4. 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 CrossRefGoogle Scholar
  5. Allen, T. F. H. (2001). A summary of the principles of hierarchy theory. http://www.isss.org/hierarchy.htm
  6. Ambroise B (2004) Variable “active”versus “contributing”areas or periods: a necessary distinction. Hydrol Process 18:1149–1155CrossRefGoogle Scholar
  7. Bak P (2013) How nature works: the science of self-organized criticality. Springer Science & Business Media, BerlinGoogle Scholar
  8. 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 CrossRefGoogle Scholar
  9. 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 56:171–196CrossRefGoogle Scholar
  10. Barry RG (1992) Mountain weather and climate. Psychology Press, HoveCrossRefGoogle Scholar
  11. 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):213–229CrossRefGoogle Scholar
  12. 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 CrossRefGoogle Scholar
  13. Bengtsson L (2010) The global atmospheric water cycle. Environ Res Lett 5:25202CrossRefGoogle Scholar
  14. Bergström S, Lindström G (2015) Interpretation of runoff processes in hydrological modelling—experience from the HBV approach. Hydrol Process 29:3535–3545CrossRefGoogle Scholar
  15. 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 CrossRefGoogle Scholar
  16. 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 CrossRefGoogle Scholar
  17. Beven KJ (2011) Rainfall-runoff modelling: the primer. Wiley, New YorkGoogle Scholar
  18. Beven K, Germann PF (1982) Macropores and water flows in soils. Water Resour Res 18:1311–1325.  https://doi.org/10.1029/WR018i005p01311 CrossRefGoogle Scholar
  19. 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 CrossRefGoogle Scholar
  20. 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 CrossRefGoogle Scholar
  21. Blöschl G, Sivapalan M (1995) Scale issues in hydrological modelling: a review. Hydrol Process 9:251–290.  https://doi.org/10.1002/hyp.3360090305 CrossRefGoogle Scholar
  22. Bras RL (2015) Complexity and organization in hydrology: a personal view. Water Resour Res 51:6532–6548.  https://doi.org/10.1002/2015WR016958 CrossRefGoogle Scholar
  23. 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 CrossRefGoogle Scholar
  24. 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 CrossRefGoogle Scholar
  25. Budyko MI (1974) Climate and life, translated from Russian by DH Miller. Elsevier, New YorkGoogle Scholar
  26. Burt TP, Pinay G (2005) Linking hydrology and biogeochemistry in complex landscapes. Prog Phys Geogr 29:297–316CrossRefGoogle Scholar
  27. Chen X, Chen YD (2004) Human-induced hydrological changes in the river network of the Pearl River Delta, South China. IAHS Publ, Guangzhou, pp 197–205Google Scholar
  28. 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 10:884–899CrossRefGoogle Scholar
  29. 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 350:534–538CrossRefGoogle Scholar
  30. 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 PubMedCrossRefGoogle Scholar
  31. 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 30:1681–1692CrossRefGoogle Scholar
  32. 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 CrossRefGoogle Scholar
  33. 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 314:335–377PubMedCrossRefGoogle Scholar
  34. Dawson CW, Wilby RL (2001) Hydrological modelling using artificial neural networks. Prog Phys Geogr 25:80–108.  https://doi.org/10.1177/030913330102500104 CrossRefGoogle Scholar
  35. 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 CrossRefGoogle Scholar
  36. 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 CrossRefGoogle Scholar
  37. Dunne T, Zhang W, Aubry BF (1991) Effects of rainfall, vegetation, and microtopography on infiltration and runoff. Water Resour Res 27:2271–2285CrossRefGoogle Scholar
  38. EPA SWMM5 (2005) Storm water management model. U.S. Environmental Protection Agency, Washington, DCGoogle Scholar
  39. 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 CrossRefGoogle Scholar
  40. Fan Y, Miguezmacho G, Jobbágy EG, Jackson RB, Oterocasal C (2017) Hydrologic regulation of plant rooting depth. Proc Natl Acad Sci USA 114(40):201712381CrossRefGoogle Scholar
  41. 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 CrossRefGoogle Scholar
  42. 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):1727–1737CrossRefGoogle Scholar
  43. Ferguson BK (1991) Landscape hydrology, a component of landscape ecology. J Environ Syst 21:193–205CrossRefGoogle Scholar
  44. 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 51:261–279CrossRefGoogle Scholar
  45. 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 CrossRefGoogle Scholar
  46. Forman RTT, Godron M (1986) Landscape ecology. Wiley, ChichesterGoogle Scholar
  47. Freeze RA, Harlan RL (1969) Blueprint for a physically-based, digitally-simulated hydrologic response model. J Hydrol 9:237–258CrossRefGoogle Scholar
  48. 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 CrossRefGoogle Scholar
  49. Fu BP (1981) On the calculation of the evaporation from land surface. Sci Atmos Sin 5:23–31Google Scholar
  50. 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 CrossRefGoogle Scholar
  51. 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 CrossRefGoogle Scholar
  52. 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 CrossRefGoogle Scholar
  53. 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):2842–2859CrossRefGoogle Scholar
  54. 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):1418–1437CrossRefGoogle Scholar
  55. 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 CrossRefGoogle Scholar
  56. 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 CrossRefGoogle Scholar
  57. 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 CrossRefGoogle Scholar
  58. 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 CrossRefGoogle Scholar
  59. 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 CrossRefGoogle Scholar
  60. 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 CrossRefGoogle Scholar
  61. Good SP, Noone D, Bowen G (2015) Hydrologic connectivity constrains partitioning of global terrestrial water fluxes. Science 349:175–177PubMedCrossRefGoogle Scholar
  62. 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 119:163–180CrossRefGoogle Scholar
  63. 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 114:141–158CrossRefGoogle Scholar
  64. 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 330:927–931PubMedCrossRefGoogle Scholar
  65. 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 CrossRefGoogle Scholar
  66. 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 CrossRefGoogle Scholar
  67. Huffman GJ, Adler RF, Bolvin DT, Nelkin EJ (2010) The TRMM multi-satellite precipitation analysis (TMPA). Satellite rainfall applications for surface hydrology. Springer, NetherlandsGoogle Scholar
  68. 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 CrossRefGoogle Scholar
  69. 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 CrossRefGoogle Scholar
  70. 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 PubMedCrossRefGoogle Scholar
  71. 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 CrossRefGoogle Scholar
  72. 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 CrossRefGoogle Scholar
  73. 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 CrossRefGoogle Scholar
  74. Klausmeier CA (1999) Regular and irregular patterns in semiarid vegetation. Science (80-) 284:1826–1828Google Scholar
  75. 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 CrossRefGoogle Scholar
  76. 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 CrossRefGoogle Scholar
  77. Li X, Ren L (2007) Effect of temporal resolution of ndvi on potential evapotranspiration estimation and hydrological model performance. Chin Geogra Sci 17(4):357–363CrossRefGoogle Scholar
  78. 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 CrossRefGoogle Scholar
  79. 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 CrossRefGoogle Scholar
  80. 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 CrossRefGoogle Scholar
  81. 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 168:94–116CrossRefGoogle Scholar
  82. 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 192:198–216CrossRefGoogle Scholar
  83. Lookingbill T, Urban D (2004) An empirical approach towards improved spatial estimates of soil moisture for vegetation analysis. Landsc Ecol 19:417–433CrossRefGoogle Scholar
  84. 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 CrossRefGoogle Scholar
  85. 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 CrossRefGoogle Scholar
  86. 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 CrossRefGoogle Scholar
  87. McGarigal K, Cushman SA, Ene E (2012) FRAGSTATS v4: spatial pattern analysis program for categorical and continuous maps. University of Massachusetts, Amherst, MAGoogle Scholar
  88. 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 CrossRefGoogle Scholar
  89. 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 CrossRefGoogle Scholar
  90. 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 CrossRefGoogle Scholar
  91. 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.Google Scholar
  92. 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 348:363–378CrossRefGoogle Scholar
  93. 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 CrossRefGoogle Scholar
  94. 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 58:1256–1275CrossRefGoogle Scholar
  95. 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 CrossRefGoogle Scholar
  96. 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 CrossRefGoogle Scholar
  97. 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 CrossRefGoogle Scholar
  98. 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 1–14Google Scholar
  99. 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 CrossRefGoogle Scholar
  100. 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 CrossRefGoogle Scholar
  101. Pickett STA, Cadenasso ML (1995) Landscape ecology: spatial heterogeneity in ecological systems. Science 269:331PubMedCrossRefGoogle Scholar
  102. 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 CrossRefGoogle Scholar
  103. 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 CrossRefGoogle Scholar
  104. 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 CrossRefGoogle Scholar
  105. Qiu J, Turner MG (2015) Importance of landscape heterogeneity in sustaining hydrologic ecosystem services in an agricultural watershed. Ecosphere 6:1–19CrossRefGoogle Scholar
  106. 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 CrossRefGoogle Scholar
  107. 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 231:427Google Scholar
  108. 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 CrossRefGoogle Scholar
  109. 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 PubMedCrossRefGoogle Scholar
  110. 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 CrossRefGoogle Scholar
  111. 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 273–296Google Scholar
  112. Rietkerk M, Van de Koppel J (2008) Regular pattern formation in real ecosystems. Trends Ecol Evol 23:169–175PubMedCrossRefGoogle Scholar
  113. 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 CrossRefGoogle Scholar
  114. Rodríguez-Iturbe I, Porporato A (2007) Ecohydrology of water-controlled ecosystems: soil moisture and plant dynamics. Cambridge University Press, CambridgeGoogle Scholar
  115. Rodríguez-Iturbe I, Rinaldo A (2001) Fractal river basins: chance and self-organization. Cambridge University Press, CambridgeGoogle Scholar
  116. Rodríguez-Iturbe I, Valdés JB (1979) The geomorphologic structure of hydrologic response. Water Resour Res 15:1409–1420.  https://doi.org/10.1029/WR015i006p01409 CrossRefGoogle Scholar
  117. 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 PubMedCrossRefGoogle Scholar
  118. 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 CrossRefGoogle Scholar
  119. 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 CrossRefGoogle Scholar
  120. Sanderson J (1999) Landscape ecology: a top down approach. CRC Press, Boca RatonGoogle Scholar
  121. 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 CrossRefGoogle Scholar
  122. 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 CrossRefGoogle Scholar
  123. 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 CrossRefGoogle Scholar
  124. 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 CrossRefGoogle Scholar
  125. 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 10:967–979CrossRefGoogle Scholar
  126. 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 CrossRefGoogle Scholar
  127. 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 CrossRefGoogle Scholar
  128. 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 CrossRefGoogle Scholar
  129. 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 CrossRefGoogle Scholar
  130. 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 40:5212–5217CrossRefGoogle Scholar
  131. 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 CrossRefGoogle Scholar
  132. 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 CrossRefGoogle Scholar
  133. 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 CrossRefGoogle Scholar
  134. 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 49:6834–6846CrossRefGoogle Scholar
  135. 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 CrossRefGoogle Scholar
  136. 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 8:1–42CrossRefGoogle Scholar
  137. 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 CrossRefGoogle Scholar
  138. Tang Q, Gao H, Lu H, Lettenmaier DP (2009) Remote sensing: hydrology. Prog Phys Geogr 33:490–509.  https://doi.org/10.1177/0309133309346650 CrossRefGoogle Scholar
  139. 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 CrossRefGoogle Scholar
  140. 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 CrossRefGoogle Scholar
  141. 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 CrossRefGoogle Scholar
  142. 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 51:4903–4922CrossRefGoogle Scholar
  143. Turner MG, Gardner RH (2015) Landscape ecology in theory and practice: pattern and process. Springer, New York, USA, p 482Google Scholar
  144. 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 CrossRefGoogle Scholar
  145. 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 322:739–742PubMedCrossRefGoogle Scholar
  146. Van Nieuwenhuyse BHJ, Antoine M, Wyseure G, Govers G (2011) Pattern-process relationships in surface hydrology: hydrological connectivity expressed in landscape metrics. Hydrol Process 25:3760–3773CrossRefGoogle Scholar
  147. 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 CrossRefGoogle Scholar
  148. 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 20:1737–1751CrossRefGoogle Scholar
  149. Vivoni ER, Ivanov VY, Bras RL, Entekhabi D (2005) On the effects of triangulated terrain resolution on distributed hydrologic model response. Hydrol Process 19:2101–2122CrossRefGoogle Scholar
  150. Wagener T, McIntyre N, Lees MJ, Wheater HS, Gupta HV (2003) Towards reduced uncertainty in conceptual rainfall-runoff modelling: dynamic identifiability analysis. Hydrol Process 17:455–476CrossRefGoogle Scholar
  151. 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 9:38CrossRefGoogle Scholar
  152. 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 CrossRefGoogle Scholar
  153. 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 CrossRefGoogle Scholar
  154. 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 CrossRefGoogle Scholar
  155. 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 20:1459–1481CrossRefGoogle Scholar
  156. Wierda A, Fresco LFM, Grootjans AP, van Diggelen R (1997) Numerical assessment of plant species as indicators of the groundwater regime. J Veg Sci 8:707–716CrossRefGoogle Scholar
  157. 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 CrossRefGoogle Scholar
  158. 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 CrossRefGoogle Scholar
  159. 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):1403–1413CrossRefGoogle Scholar
  160. 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 CrossRefGoogle Scholar
  161. Wu J (2013) Key concepts and research topics in landscape ecology revisited: 30 years after the Allerton Park workshop. Landsc Ecol 28:1–11CrossRefGoogle Scholar
  162. Wu J, David JL (2002) A spatially explicit hierarchical approach to modeling complex ecological systems: theory and applications. Ecol Modell 153:7–26CrossRefGoogle Scholar
  163. Wu J, Hobbs RJ (2007) Key topics in landscape ecology. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  164. 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 CrossRefGoogle Scholar
  165. 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 CrossRefGoogle Scholar
  166. 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 CrossRefGoogle Scholar
  167. Zehe E, Flühler H (2001) Preferential transport of isoproturon at a plot scale and a field scale tile-drained site. J Hydrol 247:100–115CrossRefGoogle Scholar
  168. 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 CrossRefGoogle Scholar
  169. 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 CrossRefGoogle Scholar
  170. 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 CrossRefGoogle Scholar
  171. 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 CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Key Laboratory of Geographic Information Science (Ministry of Education)East China Normal UniversityShanghaiChina
  2. 2.School of Geographic SciencesEast China Normal UniversityShanghaiChina
  3. 3.Future H2O, Knowledge Enterprise DevelopmentArizona State UniversityTempeUSA
  4. 4.Key Laboratory for Mountain Hazards and Earth Surface Process, Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengduChina
  5. 5.Guangdong Engineering Technology Research Center of Water Security Regulation and Control for Southern ChinaSun Yat-sen UniversityGuangzhouChina
  6. 6.Flathead Lake Biological StationUniversity of MontanaPolsonUSA

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