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Ranjit Kumar, M.
- Simulation Model for Predicting the Effects of Changes in Land Use on Watershed Hydrology
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1 Department of Civil Engineering, Government College of Technology, Coimbatore - 641013, Tamil Nadu, IN
2 Department of Agricultural Engineering, Agricultural College and Research Institute, Madurai - 625104, Tamil Nadu, IN
1 Department of Civil Engineering, Government College of Technology, Coimbatore - 641013, Tamil Nadu, IN
2 Department of Agricultural Engineering, Agricultural College and Research Institute, Madurai - 625104, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 2 (2016), Pagination:Abstract
Objective: Land use changes, driven by increase in population, and expansion of commercial interest, are happening in all parts of the world. Reductions in forest area were reported to have resulted in hydrologic changes and consequential disasters. Paired catchment studies were conducted in many parts of the world to assess the effects of changes in forest area on watershed hydrology, but the results from those studies were grounded to the locations of the study and could not be generalized and transferred to other locations. Such studies took very long time, and huge cost, despite many uncontrolled parameters between the catchments. Methods: Conceptual models have been recommended to develop scenarios for changes in land use. A newly developed Watershed Processes Simulation (WAPROS) model has been used for simulating scenarios for land use changes. The study design included: partial conversion of 0, 20, 40 and 60% of agriculture area to impervious area; 0, 20, 40 and 60% of forest area to agriculture; 0, 20, 40 and 60% of forest area to fallow; and complete conversion to forest, and to agriculture area. The reduction and expansion of forest area could be considered as equivalent to deforestation, and afforestation experiments. Findings: The capability of WAPROS model to generate all elemental processes was useful to interpret and link the causes and effects of changes. The scenario results showed: +60% change from forest to impervious area caused -100%, -28.5% and +4.6% changes in overland flow, baseflow and channel flow; +60% change from forest to agriculture caused +6%, -3.9%, and +7.8% changes in infiltration, peak flow and minimum flow. Comparison of 100% conversion to forest, and to agriculture showed higher channel flow and peak flow for full forest, and higher infiltration and evapotranspiration for full agriculture area. Applications/Improvements: The results supported studies that rejected the sponge theory attributed to forests.Keywords
Agriculture, Forest, Impervious Area, Land Use Changes, Modeling, ScenariosFull Text
- Macropore Flow as a Groundwater Component in Hydrologic Simulation:Modelling, Applications and Results
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PDF Views:79
Authors
Affiliations
1 Department of Civil Engineering, GCT, Coimbatore 641 013, IN
2 Department of Agricultural Engineering, AC&RI, Madurai 625 104, IN
1 Department of Civil Engineering, GCT, Coimbatore 641 013, IN
2 Department of Agricultural Engineering, AC&RI, Madurai 625 104, IN
Source
Current Science, Vol 112, No 06 (2017), Pagination: 1197-1207Abstract
Macropore flow carries water from the soil surface to deeper profile or groundwater, bypassing the intermediate soil profile. The phenomenon is ubiquitous and not rare. A theoretical framework of this flow has not been perfected so far, but ignoring this process may lead to incomplete conceptualization of soil-water flow. The macropore flow has been modelled based on observed data on morphometry, macropore size distribution and fractal dimensions of soil voids and stain patterns, and incorporated in the Watershed Processes Simulation (WAPROS) model. The performance of WAPROS model was evaluated to be good (NSE - hourly; daily = 0.8578; 0.9020), when applied to a real watershed. The sensitivity of macropore flow submodel showed that the adjustment factor was linearly related to macropore flow. Simulations were performed for five types of soil, namely sandy loam, sandy clay loam, sandy clay, clay loam and silty clay loam (A, B, C, D and E respectively). The values of macroporosity factors and fractal dimensions generated for the five types of soil have been presented. The model generated data for A, B, C, D and E soil types were: the number of macropores: 379, 3074, 3412, 153 and 0; the macropore flow (mm): 1.5121, 9.3667, 15.1728, 4.4055 and 0; the average pore flow (mm/pore): 0.0040, 0.0030, 0.0044, 0.0287 and 0; and the macropore flow to base flow ratio: 0.0055, 0.0474, 0.1908, 0.2759 and 0. The modelling methodology gives encouraging results. The model can be updated as and when better equations are made available.Keywords
Groundwater, Hydrologic Simulation, Macropore Flow Model, Sensitivity, Soil Types.Full Text
References
- Liu, H. and Lin, H., Frequency and control of subsurface preferential flow: from pedon to catchment scales. Soil Sci. Soc. Am. J., 2015, 79, 362–377.
- Cullum, R. F., Macropore flow estimations under no-till and till systems. Catena, 2009, 78, 87–91.
- van Schaik, N. L. M. B., Bronstert, A., de Jong, S. M., Jetten, V. G., van Dam, J. C., Ritsema, C. J. and Schnabel, S., Process-based modelling of a headwater catchment in a semi-arid area: the influence of macropore flow. Hydrol. Process., 2014, 28, 5805–5816.
- Wienhofer, J. and Zehe, E., Predicting subsurface stormflow response of a forested hillslope – the role of connected flow paths. Hydrol. Earth Syst. Sci., 2014, 18, 121–138.
- Beven, K. and Germann, P., Macropores and water flow in soils revisited. Water Resour. Res., 2013, 49, 3071–3092; doi: 10.1002/wrcr.20156.
- Yu, X., Duffy, C., Baldwin, D. C. and Lin, H., The role of macropores and multi-resolution soil survey datasets for distributed surface–subsurface flow modeling. J. Hydrol., 2014; http://dx.doi.org/10.1016/j.jhydrol. 2014.02.055
- Germann, P. F., Macropores and macropore flow, kinematic wave approach. In Encyclopedia of Soils in the Environment (ed. Hillel, D.), Academic Press, New York, 2004, vol. 2, pp. 393–402.
- Nimmo, J. R., Aggregation: physical aspects. In Encyclopedia of Soils in the Environment (ed. Hillel, D.), Academic Press, New York, 2004, vol. 1, pp. 28–35.
- Saravanathiiban, D. S., Kutay M. E. and Khire, M. V., Effect of macropore tortuosity and morphology on preferential flow through saturated soil: a lattice Boltzmann study. Comput. Geotech., 2014, 59, 44–53.
- Clothier, B. E., Green, S. R. and Deurer, M., Preferential flow and transport in soil: progress and prognosis. Eur. J. Soil Sci., 2008, 59, 2–13.
- Hendrickx, J. M. H. and Flury, M., Uniform and preferential flow mechanisms in the vadose zone. In Conceptual Models of Flow and Transport in the Fractured Vadose Zone, National Research Council, National Academy of Sciences, Washington, DC, USA, 2001, pp. 149–187.
- Alaoui, A., Modelling susceptibility of grassland soil to macropore flow. J. Hydrol., 2015, 525, 536–546.
- Merdun, H., Types and modeling of preferential flow. KSU J. Sci. Eng., 2005, 8(1), 76–83.
- Buttle, J. M. and McDonald, D. J., Coupled vertical and lateral preferential flow on a forested slope. Water Resour. Res., 2002, 38(5), 1060, 10.1029/2001WR000773
- Lal, R. and Shukla, M. K., Principles of Soil Physics, Marcel Dekker Inc., New York, USA, 2004, p. 682.
- Hatano, R., Kawamura, N., Ikeda, J. and Sakuma, T., Evaluation of the effect of morphological features of flow paths on solute transport by using fractal dimensions of methylene blue staining pattern. Geoderma, 1992, 53, 31–44.
- Perret, J. S., Prasher, S. O. and Kacimov, A. R., Mass fractal dimension of soil macropores using computed tomography: from the box-counting to the cube-counting algorithm. Eur. J. Soil Sci., 2003, 54, 569–579.
- Buczko, U., Bens, O., Hangen, E., Brunotte, J. and Huttl, R. F., Infiltration and macroporosity of a silt loam soil under two contrasting tillage systems. Landbauforsch. Volkenrode, 2003, 53, 181–190.
- Jarvis, N. J., A review of non-equilibrium water flow and solute transport in soil macropores: principles, controlling factors and consequences for water quality. Eur. J. Soil Sci., 2007, 58, 523–546.
- Weiler, M. and Naef, F., An experimental tracer study of the role of macropores in infiltration in grassland soils. Hydrol. Process., 2003, 17, 477–493.
- Nieber, J. L. and Sidle, R. C., How do disconnected macropores in sloping soils facilitate preferential flow? Hydrol. Process., 2010, 24, 1582–1594.
- Luo, L., Lin, H. and Schmidt, J., Quantitative relationships between soil macropore characteristics and preferential flow and transport. Soil Sci. Soc. Am. J., 2010, 74, 1929–1937.
- Hamblin, A. P., The influence of soil structure on water movement, crop ischolar_main growth, and water uptake. In Advances in Agronomy (ed. Brady, N. C.), Academic Press, Orlando, 1985, vol. 38, pp. 95–158.
- Perret, J., Prasher, S. O., Kantzas, A. and Langford, C., Threedimensional quantification of macropore networks in undisturbed soil cores. Soil Sci. Soc. Am. J., 1999, 63, 1530–1543.
- Meek, B. D., Rechel, E. R., Carter, L. M. and DeTar, W. R., Changes in infiltration under alfalfa as influenced by time and wheel traffic. Soil Sci. Soc. Am. J., 1989, 53, 238–241.
- Edwards, W. M., Shipitalo, M. J. and Norton, L. D., Contribution of macroporosity to infiltration into a continuous corn no-tilled watershed: implications for contaminant movement. J. Contam. Hydrol., 1988, 3, 193–205.
- Weiler, M. and Naef, F., Simulating surface and subsurface initiation of macropore flow. J. Hydrol., 2003, 273, 139–154.
- Gimenez, D., Macroporosity. In Encyclopedia of Soil Science (ed. Lal, R.), Taylor & Francis, CRC Press, Boca Raton, Florida, USA, 2006, pp 1042–1044.
- Bouma, J. and Dekker, L. W., A case study on infiltration into dry clay soil. I. Morphological observations. Geoderma, 1978, 20, 27–40.
- Shakya, N. M. and Chander, S., Modelling of hillslope runoff processes. Environ. Geol., 1998, 35(2–3), 115–123.
- Booltink H. W. G. and Bouma, J., Sensitivity analysis on processes affecting bypass flow. Hydrol. Process., 1993, 7, 33–43.
- Kirkby, M., Hillslope runoff processes and models. J. Hydrol., 1988, 100, 315–339.
- Sklash, M. G., Beven, K. J., Gilman, K. and Darling, W. G., Isotope studies of pipe flow at Plynlimon, Wales, UK. Hydrol. Process., 1996, 10, 921–944.
- Kirchner, J. W., A double paradox in catchment hydrology and geochemistry. Hydrol. Process., 2003, 17, 871–874.
- McDonnell, J. J., A rationale for old water discharge through macropores in a steep, humid catchment. Water Resour. Res., 1990, 26(11), 2821–2832.
- Klaus, J., Zehe, E., Elsner, M., Kulls, C. and McDonnell, J. J., Macropore flow of old water revisited: experimental insights from a tile-drained hillslope. Hydrol. Earth Syst. Sci., 2013, 17, 103– 118.
- Addison, P. S., Fractals and chaos: an illustrated course, The Institute of Physics, London, 1997, p. 256.
- Perfect, E. and Kay, B. D., Applications of fractals in soil and tillage research: a review. Soil Tillage Res., 1995, 36, 1–20.
- Anderson, A. N., McBratney, A. B. and Crawford, J. W., Applications of fractals to soil studies. In Advances in Agronomy (ed. Donald Sparks), Academic Press, Orlando, 1998, vol. 63, pp. 1–76.
- Duiker, S. W., Aggregation. In Encyclopedia of Soil Science (eds Lal, R. and Shukla, M. K.), Taylor & Francis, 2006, pp. 49–51.
- Ogawa, S., Baveye, P., Parlange, J. Y. and Steenhuis, T., Preferential flow in the field soils. Forma, 2002, 17, 31–53.
- Beven, K. and Germann, P., Water flow in soil macropores II. A combined flow model. J. Soil Sci., 1981, 32, 15–29.
- Chen, C. and Wagenet, R. J., Simulation of water and chemicals in macropore soils. Part 1. Representation of the equivalent macropore influence and its effect on soil water flow. J. Hydrol., 1992, 130, 105–126.
- Simunek, J. and van Genuchten, M. Th., Modelingnon equilibrium flow and transport processes using HYDRUS. Vadose Zone J., 2008, 7, 782–797.
- Germann, P. F. and Beven, K., A distribution function approach to water flow in soil macropores based on kinematic wave theory. J. Hydrol., 1986, 83, 173–183.
- Simunek, J., Jarvis, N. J., van Genuchten, M. Th. and Gardenas, A., Review and comparison of models for describing nonequilibrium and preferential flow and transport in the vadose zone. J. Hydrol., 2003, 272, 14–35.
- Jarvis, N., Koestel, J., Messing, I., Moeys, J. and Lindahl, A., Influence of soil, land use and climatic factors on the hydraulic conductivity of soil. Hydrol. Earth Syst. Sci., 2013, 17, 5185–5195.
- Soares, A. et al., Effects of soil compaction and organic carbon content on preferential flow in loamy field soils. Soil Sci., 2015, 180, 10–20.
- Mossadeghi-Björklunda, M., Arvidssona, J., Kellera, T., Koestela, J., Lamandéc, M., Larsboa, M. and Jarvis, N., Effects of subsoil compaction on hydraulic properties and preferential flow in a Swedish clay soil. Soil Tillage Res., 2016, 156, 91–98.
- Booltink, H. W. G., Hatano, R. and Bouma, J., Measurement and simulation of bypass flow in a structured clay soil: a physicomorphological approach. J. Hydrol., 1993, 148; 149–168.
- Germann, P. F. and Beven, K., Water flow in soil macropores I. An experimental approach. J. Soil Sci., 1981, 32, 1–13.
- Timlin, D. J., Ahuja, L. R., Pachepsky, Ya., Williams, R. D., Gimenez, D. and Rawls, W., Use of Brooks–Corey parameters to improve estimates of saturated conductivity from effective porosity. Soil Sci. Soc. Am. J., 1999, 63, 1086–1092.
- Fredlund, M. D., Wilson, G. W. and Fredlund, D. G., Use of the grain size distribution for estimation of soil water characteristic curve. Can. Geotech. J., 2002, 39, 1103–1117.
- Rawls, W. J., Ahuja, L. R., Brakensiek, D. L. and Shirmohammadi, A., Infiltration and soil water movement. In Handbook of Hydrology (ed. Maidment, D.), McGraw Hill Professional, 1993, p. 1424.
- Hatano, R. and Booltink, H. W. G., Using fractal dimensions of stained flow patterns in a clay soil to predict bypass flow. J. Hydrol., 1992, 135, 121–131.
- Droogers, P., Stein, A., Bouma, J. and de Boer, G., Parameters for describing soil macroporosity derived from staining patterns. Geoderma, 1998, 83, 293–308.
- Perfect, E., Estimating soil mass fractal dimensions from water retention curves. Geoderma, 1999, 88, 221–231.
- Huang, G. H., Zhang, R. D. and Huang, Q. Z., Modeling soil water retention curve with a fractal method. Pedosphere, 2006, 16(2), 137–146.
- Unified Framework for Water Balance and Hydrologic Simulation:Part I-Theoretical Development
Abstract Views :161 |
PDF Views:106
Authors
Affiliations
1 Department of Civil Engineering, Govt. College of Technology, Coimbatore-641013, Tamil Nadu, IN
2 Department of Agricultural Engineering, Agricultural College & Research Institute, Madurai-625104, Tamil Nadu, IN
1 Department of Civil Engineering, Govt. College of Technology, Coimbatore-641013, Tamil Nadu, IN
2 Department of Agricultural Engineering, Agricultural College & Research Institute, Madurai-625104, Tamil Nadu, IN
Source
International Journal of Earth Sciences and Engineering, Vol 9, No 3 (2016), Pagination: 993-1003Abstract
In this paper a unified framework is proposed to dovetail water balance model into a hydrologic simulation model. The additive and depletive nature of process operations, including the requirement for feedback and retraction, are discussed. The need to breakdown lumped processes into constituent elemental processes for water balance is discussed. The development of storage-process interaction matrix and its convergence towards water balance model are presented. The formulation of WAPROS model and its capability to generate storage-based water balance, process-based water balance, storage-level closure error, model-level closure error and water balance ratios, besides other hydrologic processes are outlined. The distinctions between model error and simulation error and the effects of interactions between them are also highlighted. A hierarchy of errors ‘simulation error-model error-storage closure error’ is proposed for error handling in simulation modelling. In this paper, theoretical development of unified framework is explained.Keywords
Water Balance Model, Hydrologic Simulation, Model Closure, Closure Error, Model Error, Simulation Error, Hierarchy of Errors, Water Balance Ratios.Full Text