1,450
Views
9
CrossRef citations to date
0
Altmetric
Original Articles

An experiment to gauge an ungauged catchment: rapid data assessment and eco-hydrological modelling in a data-scarce rural catchment

Expérience de jaugeage d’un bassin versant non jaugé: évaluation rapide des données et modélisation éco-hydrologique dans un bassin versant rural pauvre en données

, , &
Pages 2103-2125 | Received 14 Feb 2012, Accepted 07 Nov 2013, Published online: 03 Nov 2014

REFERENCES

  • Abbott, M., et al., 1986. An introduction to the European hydrological system – Système Hydrologique Européen, “SHE,” 1: history and philosophy of a physically-based, distributed modelling system. Journal of Hydrology, 87 (1–2), 45–59. doi:10.1016/0022-1694(86)90114-9.
  • Abrahamsen, P. and Hansen, S., 2000. Daisy: an open soil–crop–atmosphere system model. Environmental Modelling and Software with Environment Data News, 15 (3), 313–330. doi:10.1016/S1364-8152(00)00003-7.
  • Arnold, J.G., et al., 2010. Assessment of different representations of spatial variability on SWAT model performance. Transactions of the ASABE, 53 (5), 1433–1443. doi:10.13031/2013.34913.
  • Arnold, J.G., et al., 2012. SWAT: model use, calibration, and validation. Transactions of the ASABE, 55 (4), 1491–1508. doi:10.13031/2013.42256.
  • Baumgardner, M.F., Silvall, L.F., and Biehll, L.L., 1985. Reflectance properties of soils. Advances in Agronomy, 38. doi:10.1016/S0065–2113(08)60672–0.
  • Beven, K., 1989. Changing ideas in hydrology — the case of physically-based models. Journal of Hydrology, 105 (1–2), 157–172. doi:10.1016/0022-1694(89)90101-7.
  • Beven, K., 2000. Uniqueness of place and process representations in hydrological modelling. Hydrology and Earth System Sciences, 4 (2), 203–213.
  • Beven, K., 2006. Searching for the Holy Grail of scientific hydrology: Qt = H(S, R, ∆t)A as closure. Hydrology and Earth System Sciences, 10 (5), 609–618.
  • Beven, K. and Kirkby, M., 1979. A physically based, variable contributing area model of basin hydrology. Hydrological Sciences Bulletin, 24 (1), 43–69. doi:10.1080/02626667909491834.
  • Blöschl, G., et al., eds., 2013. Runoff predictions in ungauged basins – synthesis across processes, places and scales. Cambridge University Press. Available from: http://www.cambridge.org/9781107028180.
  • Blume, T., Zehe, E., and Bronstert, A., 2009. Use of soil moisture dynamics and patterns at different spatio-temporal scales for the investigation of subsurface flow processes. Hydrology and Earth System Sciences, 13 (7), 1215–1233.
  • Blume, T., et al., 2008. Investigation of runoff generation in a pristine, poorly gauged catchment in the Chilean Andes I: a multi-method experimental study. Hydrological Processes, 22, 3661–3675. doi:10.1002/hyp.6971.
  • Bonhomme, R., 2000. Bases and limits to using ‘degree day’ units. European Journal of Agronomy, 13, 1–10. doi:10.1016/S1161-0301(00)00058-7.
  • Boogaard, H., et al., 1998. WOFOST 7.1 - User’s guide for the WOFOST 7.1 crop growth simulation model and WOFOST Control Center 1.5. Wageningen: Alterra WUR.
  • Bouman, B.A.M., et al., 1996. The “School of de Wit” crop growth simulation models: a pedigree and historical overview. Agricultural Systems, 52, 171–198. doi:10.1016/0308-521X(96)00011-X.
  • Brocca, L., et al., 2007. Soil moisture spatial variability in experimental areas of central Italy. Journal of Hydrology, 333 (2–4), 356–373. doi:10.1016/j.jhydrol.2006.09.004.
  • Carsel, R.F. and Parrish, R.S., 1988. Developing joint probability distributions of soil water retention characteristics. Water Resources Research, 24 (5), 755–769. AGU. doi:10.1029/WR024i005p00755.
  • Chuanyana, Z., Zhongrena, N., and Zhaodong, F., 2004. GIS-assisted spatially distributed modeling of the potential evapotranspiration in semi-arid climate of the Chinese Loess Plateau. Journal of Arid Environments, 58, 387–403. doi:10.1016/j.jaridenv.2003.08.008.
  • Clark, M., Kavetski, D., and Fenicia, F., 2011. Pursuing the method of multiple working hypotheses for hydrological modeling. Water Resources Research, 47 (9), W09301. doi:10.1029/2010WR009827.
  • de Wit, A.M. and van Diepen, C.A., 2007. Crop model data assimilation with the Ensemble Kalman filter for improving regional crop yield forecasts. Agricultural and Forest Meteorology, 146, 38–56. doi:10.1016/j.agrformet.2007.05.004.
  • Dooge, J., 1986. Looking for hydrologic laws. Water Resources Research, 22 (9S), 46S–58S. doi:10.1029/WR022i09Sp0046S.
  • Droogers, P. and Allen, R.G., 2002. Estimating reference evapotranspiration under inaccurate data conditions. Irrigation and Drainage Systems, 16, 33–45. doi:10.1023/A:1015508322413.
  • Fenicia, F., Kavetski, D., and Savenije, H.H.G., 2011. Elements of a flexible approach for conceptual hydrological modeling: 1. Motivation and theoretical development. Water Resources Research, 47 (11), W11510. doi:10.1029/2010WR010174.
  • Francke, T., et al., 2008. Automated catena‐based discretization of landscapes for the derivation of hydrological modelling units. International Journal of Geographical Information Science, 22 (2), 111–132. doi:10.1080/13658810701300873.
  • Franke, G., 1994. Nutzpflanzen der Tropen und Subtropen, Vol. 1. Stuttgart: UTB.
  • Goldshleger, N., et al., 2004. Soil reflectance as a tool for assessing physical crust arrangement of four typical soils in Israel. Soil Science, 169 (10), 677–687. doi:10.1097/01.ss.0000146024.61559.e2.
  • Goudriaan, J. and Van Laar, H.H., 1994. Modelling potential crop growth processes. Dordrecht: Springer, 126. doi:10.1007/978-94-011-0750-1.
  • GSI, 1976. Geology and Mineral Resources of the States of India — Part XI. Madhya Pradesh: Geological Survey of India.
  • GSI, 1988. District Resource Map — Jhabua District. Madhya Pradesh: Geological Survey of India.
  • Güntner, A. and Bronstert, A., 2004. Representation of landscape variability and lateral redistribution processes for large-scale hydrological modelling in semi-arid areas. Journal of Hydrology, 297 (1–4), 136–161. doi:10.1016/j.jhydrol.2004.04.008.
  • Güntner, A., et al., 2004. Simple water balance modelling of surface reservoir systems in a large data-scarce semiarid region. Hydrological Sciences Journal, 49 (5), 901–918. doi:10.1623/hysj.49.5.901.55139.  
  • Gupta, H., et al., 2012. Towards a comprehensive assessment of model structural adequacy. Water Resources Research, 48 (8), 1–40. doi:10.1029/2011WR011044.
  • He, Y., Bárdossy, A., and Zehe, E., 2011. A review of regionalisation for continuous streamflow simulation. Hydrology and Earth System Sciences, 15 (11), 3539–3553. doi:10.5194/hess-15-3539-2011.
  • Hellebrand, H., et al., 2011. A process proof test for model concepts: modelling the meso-scale. Physics and Chemistry of the Earth, Parts A/B/C, 36 (1–4), 42–53. doi:10.1016/j.pce.2010.07.019.
  • Hundecha, Y. and Bárdossy, A., 2004. Modeling of the effect of land use changes on the runoff generation of a river basin through parameter regionalization of a watershed model. Journal of Hydrology, 292 (1–4), 281–295. doi:10.1016/j.jhydrol.2004.01.002.
  • Ittersum, M.V., et al., 2003. On approaches and applications of the Wageningen crop models. European Journal of Agronomy, 18, 201–234. doi:10.1016/S1161-0301(02)00106-5.
  • Jackson, R., Jobbágy, E., and Nosetto, M., 2009. Ecohydrology in a human-dominated landscape. Ecohydrology, 2 (3), 383–389. doi:10.1002/eco.81.
  • Keshavamurty, R. and Rao, M.S., 1992. The physics of monsoons. New Delhi: Allied Publishers.
  • Kleidon, A., 2007. Thermodynamics and environmental constraints make the biosphere predictable — a response to Volk. Climatic Change, 85, 259–266. doi:10.1007/s10584-007-9320-x.
  • Klemeš, V., 1983. Conceptualization and scale in hydrology. Journal of Hydrology, 65, 1–23. doi:10.1016/0022-1694(83)90208-1.
  • Kroes, J. and van Dam, J., 2003. Reference Manual SWAP version 3.0.3.
  • Krysanova, V., Hattermann, F., and Wechsung, F., 2005. Development of the ecohydrological model SWIM for regional impact studies and vulnerability assessment. Hydrological Processes, 19 (3), 763–783. doi:10.1002/hyp.5619.
  • Kucharik, C.J. and Brye, K.R., 2003. Integrated BIosphere Simulator (IBIS) yield and nitrate loss predictions for Wisconsin maize receiving varied amounts of nitrogen fertilizer. Journal of Environment Quality. 32 (1), 247–268. doi:10.2134/jeq2003.2470.
  • Lei, H., et al., 2008. Modeling the crop transpiration using an optimality-based approach. Science in China Series E: Technological Sciences, 51, 60–75. doi:10.1007/s11431-008-6008-z.
  • Lindström, G., et al., 1997. Development and test of the distributed HBV-96 hydrological model. Journal of Hydrology, 201 (1–4), 272–288. doi:10.1016/S0022-1694(97)00041-3.
  • Love, D., et al., 2010. Rainfall–interception–evaporation–runoff relationships in a semi-arid catchment, northern Limpopo basin, Zimbabwe. Hydrological Sciences Journal, 55 (5), 687–703. doi:10.1080/02626667.2010.494010.
  • Martínez-Carreras, N., et al., 2010. A rapid spectral-reflectance-based fingerprinting approach for documenting suspended sediment sources during storm runoff events. Journal of Soils and Sediments, 10 (3), 400–413. doi:10.1007/s11368-009-0162-1.
  • Mayor, Á., Bautista, S., and Bellot, J., 2009. Factors and interactions controlling infiltration, runoff, and soil loss at the microscale in a patchy Mediterranean semiarid landscape. Earth Surface Processes and Landforms, 34 (12), 1702–1711. doi:10.1002/esp.1875.
  • McDonnell, J., et al., 2007. Moving beyond heterogeneity and process complexity: a new vision for watershed hydrology. Water Resources Research, 43, doi:10.1029/2006WR005467.
  • Montzka, C., et al., 2008. Modelling the water balance of a mesoscale catchment basin using remotely sensed land cover data. Journal of Hydrology, 353 (3–4), 322–334. doi:10.1016/j.jhydrol.2008.02.018.
  • Mueller, E., et al., 2009. Modelling the effects of land-use change on runoff and sediment yield for a meso-scale catchment in the Southern Pyrenees. CATENA, 79 (3), 288–296. doi:10.1016/j.catena.2009.06.007.
  • Mueller, E.N., Wainwright, J., and Parsons, A.J., 2007. Impact of connectivity on the modeling of overland flow within semiarid shrubland environments. Water Resources Research, 43, (9). doi:10.1029/2006WR005006.
  • Norman, M., Pearson, C., and Searle, P., 1995. The ecology of tropical food crops, Vol. 1. Cambridge University Press.
  • Parajka, J., Merz, R., and Blöschl, G., 2005. A comparison of regionalisation methods for catchment model parameters. Hydrology and Earth System Sciences, 9 (3), 157–171. doi:10.5194/hess-9-157-2005.
  • Pauwels, V.R.N., et al., 2007. Optimization of a coupled hydrology-crop growth model through the assimilation of observed soil moisture and leaf area index values using an ensemble Kalman filter. Water Resources Research, 43, (4). doi:10.1029/2006WR004942.
  • Pilgrim, D., Chapman, T., and Doran, D., 1988. Problems of rainfall–runoff modelling in arid and semiarid regions. Hydrological Sciences Journal, 33 (4), 379–400. doi:10.1080/02626668809491261.
  • Rehm, S. and Espig, G. 1991. The cultivated plants of the tropics and subtropics. Champaign, IL: Balogh Scientific Books.
  • Renard, K., et al., 2008. A brief background on the US Department of Agriculture Agricultural Research Service Walnut Gulch Experimental Watershed. Water Resources Research, 44 (5), W05S02. doi:10.1029/2006WR005691.
  • Rodriguez-Iturbe, I., 2000. Ecohydrology: a hydrologic perspective of climate-soil-vegetation dynamies. Water Resources Research, 36 (1), 3–9. doi:10.1029/1999WR900210.
  • Rodriguez-Iturbe, I., et al., 1999. On the spatial and temporal links between vegetation, climate, and soil moisture. Water Resources Research, 35, 3709–3722. doi:10.1029/1999WR900255.
  • Samaniego, L., Kumar, R., and Attinger, S., 2010. Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale. Water Resources Research, 46 (5), W05523. doi:10.1029/2008WR007327.
  • Schaap, M.G., Leij, F.J., and van Genuchten, M.T., 2001. Rosetta: a computer program for estimating soil hydraulic parameters with hierarchical pedotransfer functions. Journal of Hydrology, 251 (3–4), 163–176. doi:10.1016/S0022–1694(01)00466–8.
  • Schulla, J. and Jasper, K., 2007. Model description WaSiM-ETH. Technical report. Zürich: ETH Zürich.
  • Schymanski, S., et al., 2009. An optimality-based model of the dynamic feedbacks between natural vegetation and the water balance. Water Resources Research, 45. doi:10.1029/2008WR006841.
  • Schymanski, S.J., 2008. Optimality as a concept to understand and model vegetation at different scales. Geography Compass, 2 (5), 1580–1598. doi:10.1111/j.1749-8198.2008.00137.x.
  • Shuttleworth, W. and Wallace, J., 2007. Evaporation from sparse crops-an energy combination theory. Quarterly Journal of the Royal Meteorological Society, 111 (469), 839–855. doi:10.1002/qj.49711146910.
  • Simunek, J., van Genuchten, M., and Sejna, M., 2008. Development and applications of the HYDRUS and STANMOD software packages and related codes. Vadose Zone Journal, 7 (2), 587–600. doi:10.2136/vzj2007.0077.
  • Singh, A.K., 2004. Towards decision support models for an ungauged catchment in India, the case of Anas catchment. Mitteilungen des Instituts für Wasserwirtschaft und Kulturtechnik der Universität Karlsruhe (TH), 225.
  • Sivapalan, M., et al., 2003. IAHS Decade on Predictions in Ungauged Basins (PUB), 2003–2012: shaping an exciting future for the hydrological sciences. Hydrological Sciences Journal, 48 (6), 857–880. doi:10.1623/hysj.48.6.857.51421.
  • Stull, R.B., 2001. An introduction to boundary layer meteorology. Berlin: Springer.
  • Tian, F., et al., 2006. Extension of the representative elementary watershed approach for cold regions via explicit treatment of energy related processes. Hydrology and Earth System Sciences, 10 (5), 619–644. doi:10.5194/hess-10-619-2006.
  • Tietjen, B., et al., 2010. Effects of climate change on the coupled dynamics of water and vegetation in drylands. Ecohydrology, 3, 226–237. doi:10.1002/eco.70.
  • Tietjen, B. and Jeltsch, F., 2007. Semi-arid grazing systems and climate change: a survey of present modelling potential and future needs. Journal of Applied Ecology, 44 (2), 425–434. doi:10.1111/j.1365-2664.2007.01280.x.
  • Tietjen, B., Zehe, E., and Jeltsch, F., 2009. Simulating plant water availability in dry lands under climate change: a generic model of two soil layers. Water Resources Research, 45. doi:10.1029/2007WR006589.
  • Tolson, B. and Shoemaker, C., 2007. Dynamically dimensioned search algorithm for computationally efficient watershed model calibration. Water Resources Research, 43 (1), W01413. doi:10.1029/2005WR004723.
  • Tomar, V., Gupta, G., and Kaushal, G., 1995. Soil resources and agroclimatic zones of Madhya Pradesh.
  • Tsuji, G.Y., Hoogenboom, G., and Thornton, P.K. 1998. Understanding options for agricultural production. Dordrecht: Kluwer Academic Press.
  • Ustin, S., ed., 2004. Manual of remote sensing, remote sensing for natural resource management and environmental monitoring, Vol. 4. Hoboken, NJ: Wiley.
  • van Dam, J.C. and Malik, R.S., 2003. Water productivity of irrigated crops in Sirsa district, India. Technical Report by WUR. Wageningen: WUR.
  • van Dam, J.C., et al., 2008. Advances of modeling water flow in variably saturated soils with SWAP. Vadose Zone Journal, 7 (2), 640–653. doi:10.2136/vzj2007.0060.
  • Xavier, A.C. and Vettorazzi, C.A., 2004. Monitoring leaf area index at watershed level through NDVI from Landsat-7/ETM+ data. Scientia Agricola, 61, 243–252. scielo. doi:10.1590/S0103-90162004000300001.
  • Yadav, M., Wagener, T., and Gupta, H., 2007. Regionalization of constraints on expected watershed response behavior for improved predictions in ungauged basins. Advances in Water Resources, 30 (8), 1756–1774. doi:10.1016/j.advwatres.2007.01.005.
  • Yatheendradas, S., et al., 2008. Understanding uncertainty in distributed flash flood forecasting for semiarid regions. Water Resources Research, 44 (5), W05S19. doi:10.1029/2007WR005940.
  • Zehe, E. and Blöschl, G., 2004. Predictability of hydrologic response at the plot and catchment scales: role of initial conditions. Water Resources Research, 40 (10). doi:10.1029/2003WR002869.
  • Zehe, E. and Sivapalan, M., 2009. Threshold behaviour in hydrological systems as (human) geo-ecosystems: manifestations, controls, implications. Hydrology and Earth System Sciences, 13 (7), 1273–1297.
  • Zehe, E., et al., 2001. Modeling water flow and mass transport in a loess catchment. Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere, 26 (7–8), 487–507. doi:10.1016/S1464-1909(01)00041-7.
  • Zehe, E., et al., 2007. Patterns of predictability in hydrological threshold systems. Water Resources Research, 43, (7). doi:10.1029/2006WR005589.
  • Zehe, E., et al., 2010. Plot and field scale soil moisture dynamics and subsurface wetness control on runoff generation in a headwater in the Ore Mountains. Hydrology and Earth System Sciences, 14 (6), 873–889. doi:10.5194/hess-14-873-2010.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.