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Environmental Earth Sciences

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01-06-2019 | Thematic Issue

Quantifying the integrated water and carbon cycle in a data-limited karst basin using a process-based hydrologic model

Authors: Han Qiu, Jie Niu, Bill X. Hu

Published in: Environmental Earth Sciences | Issue 11/2019

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Abstract

Quantitative estimation of the terrestrial hydrologic fluxes in a karst basin is difficult due to the wide distribution of karst pores, the strong water conductivity of aquifer medium, and the complex groundwater dynamics. In this work, we attempt to estimate the water and carbon budgets of a data scarce karst basin using a process-based hydrological model. Without the knowledge of subsurface structure and rock medium, the karst pipes were simply treated as open channels. The model can generally predict the stream discharge and evapotranspiration, and reproduce the seasonal trend of the gross primary production (GPP) and net primary production (NPP) of the basin, with this simplification. The main hydrologic budgets were estimated and reveal how water partitions in the hydrologic cycle in this karst basin. The simulated results also indicate the main source (either baseflow or surface runoff) of the stream flow in different seasons. However, the simulation of the surface/subsurface hydrologic interactions, groundwater/stream flow exchange, and the vegetation root zone dynamics could be improved if the karst groundwater dynamics, especially for the area with complicated karst pipe system, are depicted in detail.

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Anderton S, Latron J, Gallart F (2002) Sensitivity analysis and multi-response, multi-criteria evaluation of a physically based distributed model. Hydrol Process 16:333–353. https://doi.org/10.1002/hyp.336 CrossRef

Beven KJ (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 CrossRef

Beven KJ, Binley A (1992) The future of distributed models: model calibration and uncertainty prediction. Hydrol Process 6:279–298. https://doi.org/10.1002/hyp.3360060305 CrossRef

Bonan GB, Levis S, Kergoat L, Oleson KW (2002) Landscapes as patches of plant functional types: an integrating concept for climate and ecosystem models. Glob Biogeochem Cycles 16:1021. https://doi.org/10.1029/2000gb001360 CrossRef

Borghi A, Renard P, Jenni S (2012) A pseudo-genetic stochastic model to generate karstic networks. J Hydrol 414–415:516–529. https://doi.org/10.1016/j.jhydrol.2011.11.032 CrossRef

Chen N, Gunzburger Max, Hu Bill X, XiaomingWang Celestine Woodruff (2012) Calibrating the exchange coefficient in the modified coupled continuum pipe-flow model for flows in karst aquifers. J Hydrol 414(pp294–301):2012

Dai Y, Dickinson RE, Wang YP (2004) A two-big-leaf model for canopy temperature, photosynthesis, and stomatal conductance. J Clim 17:2281–2299. https://doi.org/10.1175/1520-0442(2004)017%3c2281:atmfct%3e2.0.co;2 CrossRef

Davis JH (1996) Hydraulic investigation and simulation of ground-water flow in the Upper Floridan aquifer of north central Florida and southwestern Georgia and delineation of contributing areas for selected City of Tallahassee, Florida, water-supply wells: U.S. Geological Survey Water-Resources Investigations Report 95-4296, p 55

Davis JH, Katz BG (2007) Hydrogeologic investigation, water chemistry analysis, and model delineation of contributing areas for City of Tallahassee public-supply wells, Tallahassee, Florida: U.S. Geological Survey Scientific Investigations Report 2007-5070, p 67

de Rooij R, Perrochet P, Graham W (2013) From rainfall to spring discharge: coupling conduit flow, subsurface matrix flow and surface flow in karst systems using a discrete–continuum model. Adv Water Resour 61:29–41. https://doi.org/10.1016/j.advwatres.2013.08.009 CrossRef

Dessert C, Dupre B, Gaillardet J et al (2003) Basalt weathering laws and the impact of basalt weathering on the global carbon cycle. ChemGeol 202:257–273

Dreiss SJ (1982) Linear kernels for karst aquifers. Water Resour Res 38(10):865–876CrossRef

Fan Y, Li H, Miguez-Macho G (2013) Global patterns of groundwater table depth. Science 339:940. https://doi.org/10.1126/science.1229881 CrossRef

Fang JY, Guo ZD, Piao SL et al (2007) Estimation of terrestrial vegetable carbon sink at 1981–2000, CHina. Sci hina (Ser D Earth Sci) 37(6):804–881

Feng X, Liu G, Chen JM, Chen M, Liu J, Ju WM, Sun R, Zhou W (2007) Net primary productivity of China’s terrestrial ecosystems from a process model driven by remote sensing. J Environ Manag 85(3):563–573. https://doi.org/10.1016/j.jenvman.2006.09.021 CrossRef

Gilabert MA, Moreno A, Maselli F, Martínez B, Chiesi M, Sánchez-Ruiz S, García-Haro FJ, Pérez-Hoyos A, Campos-Taberner M, Pérez-Priego O, Serrano-Ortiz P, Carrara A (2015) Daily GPP estimates in Mediterranean ecosystems by combining remote sensing and meteorological data. ISPRS J Photogramm Remote Sens 102:184–197. https://doi.org/10.1016/j.isprsjprs.2015.01.017 CrossRef

Gill LW, Naughton O, Johnston PM (2013) Modeling a network of turloughs in lowland karst. Water Resour Res 49:3487–3503. https://doi.org/10.1002/wrcr.20299 CrossRef

Guan KY et al (2015) Photosynthetic seasonality of global tropical forests constrained by hydroclimate. Nat Geosci 8:284–289. https://doi.org/10.1038/ngeo2382 CrossRef

Guber AK, Pachepsky YaA, vanGenuchten MTh, Rawls WJ, Simunek J, Jacques D, Nicholson TJ, Cady RE (2006) Field-scale water flow simulations using ensembles of pedotransfer functions for soil water retention. Vadose Zone J 5:234–247. https://doi.org/10.2136/vzj2005.0111 CrossRef

Guber AK, Pachepsky YaA, van Genuchten MTh, Simunek J, Jacques D, Nemes A, Nicholson TJ, Cady RE (2009) Multimodel simulation of water flow in a field soil using pedotransfer functions. Vadose Zone J 8(1):1CrossRef

Hu BX (2010) Examining a Coupled Continuum Pipe-Flow Model for Groundwater Flow and Solute Transport in a Karst aquifer. Acta Carsolog 39(2):347–359CrossRef

Hu BX, Hua F, Gunzburger M, Wang X, Yan C (2012) Experimental and computational validation and verification of the Stokes-Darcy and continuum pipe flow models for a karst aquifers with dual porosity structure. Hydrol Process 26(13):2031–2040CrossRef

Ji X, Shen C, Riley WJ (2015) Temporal evolution of soil moisture statistical fractal and controls by soil texture and regional groundwater flow. Adv Water Resour 86:155–169. https://doi.org/10.1016/j.advwatres.2015.09.027 CrossRef

Krause P, Boyle DP, Bӓse F (2005) Comparison of different efficiency criteria for 956 hydrological model assessment. Adv Geosci 5:89–97CrossRef

Kuniansky EL (2008) U.S. Geological Survey Karst Interest Group Proceedings, Bowling Green, Kentucky, May 27-29, 2008. U.S. Geological Survey Scientific Investigations Report 2008–5023, p 142

Labat D, Ababou R, Mangin A (2000) Rainfall-runoff relations for karstic springs, Part I: convolution and spectral analyses. J Hydrol 238:123–148CrossRef

Lawrence DM et al (2011) Parameterization improvements and functional and structural advances in version 4 of the community land model. J Adv Model Earth Syst 3:M03001. https://doi.org/10.1029/2011ms00045 CrossRef

Li GQ, Field MS (2014) A mathematical model for simulating spring discharge and estimating sinkhole porosity in a karst watershed. Grundwasser Zeitschrift der Fachsektion Hydrogeologie 19:51–60CrossRef

Li Z, Chen Y, Wang Y, Fang G (2016) Dynamic changes in terrestrial net primary production and their effects on evapotranspiration. Hydrol Earth Syst Sci 20(6):2169–2178. https://doi.org/10.5194/hess-20-2169-2016 CrossRef

Liedl R, Sauter M, Hückinghaus D, Clemens T, Teutsch G (2003) Simulation of the development of karst aquifers using a coupled continuum pipe flow model. Water Resour Res. https://doi.org/10.1029/2001wr001206 CrossRef

Liu Z, Zhao J (2000) Contribution of carbonate rock weathering to the atmospheric CO2 sink. Environ Geol 39:1053–1058CrossRef

Liu Z, Shao Q, Liu J (2015) The performances of MODIS-GPP and -ET products in China and their sensitivity to input data (FPAR/LAI). Remote Sens 7:135–152. https://doi.org/10.3390/rs70100135 CrossRef

Long YQ, Cui TT, Yang ZP et al (2013) A coupled Karst-porous groundwater model based on the adapted general head boundary. Environ Eng Manag J 12:1757–1762CrossRef

Loper DE, Werner CL, Chicken E, Davies G, Kincaid T (2005) Coastal carbonate aquifer sensitivity to tides. Eos Trans AGU 86(39):353–357CrossRef

Lu CP, Shu LC, Wen ZH et al (2013) Interpretation of a short-duration pumping test in the mixed flow karst system using a three-reservoir model. Carbonates Evaporites 28:149–158CrossRef

Lv Q, Hu B, Cao J, Huang F, Zhu Z (2017) Aquifer structure of karst areas derived from borehole pumping and tracer tests. Carsol Sin 36(5):727–735. https://doi.org/10.11932/karst2017y29 CrossRef

Morton DC, Nagol J, Carabajal CC, Rosette J, Palace M, Cook BD, Vermote EF, Harding DJ, North PRJ (2014) Amazon forests maintain consistent canopy structure and greenness during the dry season. Nature 506:221–224. https://doi.org/10.1038/nature13006 CrossRef

Mu Q, Zhao M, Running SW (2011) Improvements to a MODIS global terrestrial evapotranspiration algorithm. Remote Sens Environ 115:1781–1800. https://doi.org/10.1016/j.rse.2011.02.019 CrossRef

Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models part I—a discussion of principles. J Hydrol 10:282–290. https://doi.org/10.1016/0022-1694(70)90255-6 CrossRef

Niu J, Phanikumar MS (2015) Modeling watershed-scale solute transport using an integrated, process-based hydrologic model with applications to bacterial fate and transport. J Hydrol 529(Part 1):35–48. https://doi.org/10.1016/j.jhydrol.2015.07.013 CrossRef

Niu J, Shen C, Li S-G, Phanikumar MS (2014) Quantifying storage changes in regional Great Lakes watersheds using a coupled subsurface-land surface process model and GRACE. MODIS Prod Water Resour Res 50:7359–7377. https://doi.org/10.1002/2014WR015589 CrossRef

Niu J, Shen Chaopeng, Chambers Jeffery Q, Melack John M, Riley William J (2017) Interannual variation in hydrologic budgets in an Amazonian watershed with a coupled subsurface-land surface process model. J Hydrometeorol 18(9):2597–2617CrossRef

Oleson KW et al (2010) Technical description of version 4.0 of the Community Land Model (CLM). NCAR Tech. Note NCAR/TN-4781STR, p 257. https://doi.org/10.5065/d6fb50wz

Oleson KW et al (2013) Technical description of version 4.5 of the Community Land Model (CLM). NCAR Tech. Note NCAR/TN-5031STR, p 420. https://doi.org/10.5065/d6rr1w7m

Pau GSH, Shen C, Riley WJ, Liu Y (2016) Accurate and efficient prediction of fine-resolution hydrologic and carbon dynamic simulations from coarse-resolution models. Water Resour Res 52:791–812. https://doi.org/10.1002/2015wr017782 CrossRef

Peng B, Guan K, Chen M, Lawrence DM, Pokhrel Y, Suyker A, Arkebauer T, Lu Y (2018) Improving maize growth processes in the community land model: implementation and evaluation. Agric For Meteorol 250–251:64–89. https://doi.org/10.1016/j.agrformet.2017.11.012 CrossRef

Piao SL, Ito A, Li SG, Huang Y, Ciais P, Wang XH, Peng SS, Nan HJ, Zhao C, Ahlström A, Andres RJ, Chevallier F, Fang JY, Hartmann J, Huntingford C, Jeong S, Levis S, Levy PE, Li JS, Lomas MR, Mao JF, Mayorga E, Mohammat A, Muraoka H, Peng CH, Peylin P, Poulter B, Shen ZH, Shi X, Sitch S, Tao S, Tian HQ, Wu XP, Xu M, Yu GR, Viovy N, Zaehle S, Zeng N, Zhu B (2012) The carbon budget of terrestrial ecosystems in East Asia over the last two decades. Biogeosciences 9:3571–3586. https://doi.org/10.5194/bg-9-3571-2012 CrossRef

Price K, Storn RM, Lampinen JA (2005) Differential evolution: a practical approach to global optimization. Springer, Berlin, p 539. https://doi.org/10.1007/3-540-31306-0 CrossRef

Qiu H, Blaen P, Comer-Warner S, Hannah DM, Krause S, Phanikumar MS (2019a) Evaluating a coupled phenology-surface energy balance model to understand stream- subsurface temperature dynamics in a mixed-use farmland catchment. Water Resour Res. https://doi.org/10.1029/2018wr023644 CrossRef

Qiu H, Niu J, Phanikumar MS (2019b) Quantifying the space-time variability of water balance components in an agricultural basin using a process-based hydrologic model and the Budyko framework. Sci Total Environ 676:176–189CrossRef

Reimann T, Geyer T, Shoemaker WB, Liedl R, Sauter M (2011) Effects of dynamically variable saturation and matrix-conduit coupling of flow in karst aquifers. Water Resour Res. https://doi.org/10.1029/2011wr010446 CrossRef

Restrepo-Coupe N et al (2013) What drives the sea- sonality of photosynthesis across the Amazon basin? A cross- site analysis of eddy flux tower measurements from the Brasil flux network. Agric For Meteor 182–183:128–144. https://doi.org/10.1016/j.agrformet.2013.04.031 CrossRef

Riley WJ, Shen C (2014) Characterizing coarse-resolution watershed soil moisture heterogeneity using fine-scale simulations. Hydrol Earth Syst Sci 18:2463–2483. https://doi.org/10.5194/hess-18-2463-2014 CrossRef

Safaie A, Dang C, Qiu H, Radha H, Phanikumar MS (2017) Manifold methods for assimilating geophysical and meteorological data in Earth system models and their components. J Hydrol 544:383–396. https://doi.org/10.1016/j.jhydrol.2016.11.009 CrossRef

Saleska Scott R, Miller Scott D, Matross Daniel M, Goulden Michael L, Wofsy Steven C, da Rocha Humberto R, de Camargo Plinio B, Crill Patrick, Daube Bruce C, de Freitas Helber C, Hutyra Lucy, Keller Michael, Kirchhoff Volker, Mary Menton J, Munger William, Pyle Elizabeth Hammond, Rice Amy H, Silva Hudson (2003) Carbon in Amazon forests: unexpected seasonal fluxes and disturbance-induced losses. Science 302(5650):1554–1557. https://doi.org/10.1126/science.1091165 CrossRef

Saller SP, Ronayne MJ, Long AJ (2013) Comparison of a karst groundwater model with and without discrete conduit flow. Hydrogeol J 21:1555–1566CrossRef

Sanford WE, Konikow LF (1989) Simulation of calcite dissolution and porosity changes in saltwater mixing zones in coastal aquifers. Water Resour Res 25(4):655–667CrossRef

Shen CP, Phanikumar Mantha S (2010) A process-based, distributed hydrologic model based on a large-scale method for surface–subsurface coupling. Adv Water Resour 33(2010):1524–1541CrossRef

Shen C, Niu J, Phanikumar MS (2013) Evaluating controls on coupled hydrologic and vegetation dynamics in a humid continental climate watershed using a subsurface-land surface processes model. Water Resour Res 49:2552–2572. https://doi.org/10.1002/wrcr.20189 CrossRef

Shen C, Niu J, Fang K (2014) Quantifying the effects of data integration algorithms on the outcomes of a subsurface–land surface processes model. Environ Modell Softw 59:146–161. https://doi.org/10.1016/j.envsoft.2014.05.006 CrossRef

Shen C, Riley WJ, Smithgall KR, Melack JM, Fang K (2016) The fan of influence of streams and channel feed- backs to simulated land surface water and carbon dynamics. Water Resour Res 52(2):880–902. https://doi.org/10.1002/2015wr018086 CrossRef

Shoemaker WB, Kuniansky EL, Birk S, Bauer S, Swain ED (2008) Documentation of a conduit flow process (CFP) for MODFLOW-2005. US Geological Survey Techniques and Methods, Book 6, Chapter A24, p 50

Sivapalan M (2006) Pattern, process and function: elements of a unified theory of hydrology at the catchment scale. In: Anderson MG, McDonnell JJ (eds) Encyclopedia of hydrological sciences. Wiley, Chichester, pp 193–219. https://doi.org/10.1002/0470848944.hsa012 CrossRef

Tomasella J, Hodnett MG (1998) Estimating soil water retention characteristics from limited data in Brazilian Amazonia. Soil Sci 163:190–202. https://doi.org/10.1097/00010694-199803000-00003 CrossRef

Wang H, Li X, Ma M, Geng L (2019) Improving estimation of gross primary production in dryland ecosystems by a model-data fusion approach. Remote Sens 11(3):225. https://doi.org/10.3390/rs11030225 CrossRef

Wu J, Albert LP, Lopes AP, Restrepo-Coupe N, Hayek M, Wiedemann KT, Guan K, Stark SC, Christoffersen B, Prohaska N, Tavares JV, Marostica S, Kobayashi H, Ferreira ML, Campos KS, da Silva R, Brando PM, Dye DG, Huxman TE, Huete AR, Nelson BW, Saleska SR (2016) Leaf development and demography explain photosynthetic seasonality in Amazon evergreen forests. Science 351(6276):972–976. https://doi.org/10.1126/science.aad5068 CrossRef

Xu Z, Hu B (2016) Development of a discrete-continuum VDFST-CFP numerical model for simulating seawater intrusion to a coastal karst aquifer with a conduit system. Water Resour Res. https://doi.org/10.1002/2016wr018758 CrossRef

Xu ZX, Hu BX, Davis H, Cao JH (2015) Simulating long term nitrate-N contamination processes in Woodville Karst plain using CFPv2 with UMT3D. J Hydrol 52:72–88CrossRef

Xu Z, Massei N, Padilla I, Hartmann A, Hu B (2018) Characterization, modeling, and remediation of karst in a changing environment. Environ Earth Sci 77:476. https://doi.org/10.1007/s12665-018-7660-7 CrossRef

Zhang Y, Yu Q, Jiang J, Tang Y (2008) Calibration of Terra/MODIS gross primary production over an irrigated cropland on the North China Plain and an alpine meadow on the Tibetan Plateau. Glob Change Biol 14(4):757–767. https://doi.org/10.1111/j.1365-2486.2008.01538.x CrossRef

Title: Quantifying the integrated water and carbon cycle in a data-limited karst basin using a process-based hydrologic model
Authors: Han Qiu
Jie Niu
Bill X. Hu
Publication date: 01-06-2019
Publisher: Springer Berlin Heidelberg
Published in: Environmental Earth Sciences / Issue 11/2019
Print ISSN: 1866-6280
Electronic ISSN: 1866-6299
DOI: https://doi.org/10.1007/s12665-019-8324-y

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