Spatial and temporal variation in two rainfall simulators: implications for spatially explicit rainfall simulation experiments
Rainfall simulators are widely used yet there is little evidence in the literature to show that their spatial and temporal variability has been adequately taken into account. For experiments that are concerned only with some aggregate or mean effect of simulated rain then such variations may be unim...
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Published in | Earth surface processes and landforms Vol. 25; no. 7; pp. 709 - 721 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
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Chichester, UK
John Wiley & Sons, Ltd
01.07.2000
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Abstract | Rainfall simulators are widely used yet there is little evidence in the literature to show that their spatial and temporal variability has been adequately taken into account. For experiments that are concerned only with some aggregate or mean effect of simulated rain then such variations may be unimportant. However, where rainfall simulation is being used to study (and perhaps model) small‐scale processes that are themselves spatially variable (such as rill initiation) then knowledge of the simulator's inherent variability is vital. A first aim of this paper is therefore to examine this variability, and to appraise methodologies by which it may be quantified. A second aim is to evaluate the implications for spatially explicit rainfall simulation experiments.
Two simulators were used, a portable drip‐screen simulator and a laboratory‐based full‐cone nozzle simulator. Neither produced a spatially uniform distribution of rainfall depth: both produced distributional patterns that were fairly consistent despite varying intensities and run times. Small‐scale, apparently random variations were superimposed on these more deterministic patterns. However, despite this marked spatial variability, calculation of uniformity coefficients (1−SD/mean) resulted in high values. Thus it appears that the uniformity coefficient gives little real indication of the spatial uniformity of simulated rainfall, despite its established usage in the literature. Additionally, spatial distributions of raindrop size –and hence kinetic energy –were calculated for the full‐cone nozzle simulator. These show that zones of high rainfall amount do not necessarily relate to zones of high energy reaching the surface.
The presence of such variability raises a number of issues for spatially explicit rainfall simulation experiments. While there has been little work on the spatial variability of natural rainfall at field scale and smaller, it appears that the spatial heterogeneity of simulated rainfall depths observed in this study does not differ greatly from that of natural rain. But since a major attraction of rainfall simulation experiments is additional control over rainfall's many variables, the spatial non‐uniformity of depth observed in this study is unwelcome. The existence of an apparently deterministic component to this non‐uniformity nonetheless suggests that it can, at least in principle, be corrected by calibration. Less easily handled is the discrepancy between spatial distributions of rainfall depth and energy, since this will certainly affect rainfall simulation experiments that are, for example, concerned with erosion processes due to raindrop impact. Copyright © 2000 John Wiley & Sons, Ltd. |
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AbstractList | Rainfall simulators are widely used yet there is little evidence in the literature to show that their spatial and temporal variability has been adequately taken into account. For experiments that are concerned only with some aggregate or mean effect of simulated rain then such variations may be unimportant. However, where rainfall simulation is being used to study (and perhaps model) small‐scale processes that are themselves spatially variable (such as rill initiation) then knowledge of the simulator's inherent variability is vital. A first aim of this paper is therefore to examine this variability, and to appraise methodologies by which it may be quantified. A second aim is to evaluate the implications for spatially explicit rainfall simulation experiments.
Two simulators were used, a portable drip‐screen simulator and a laboratory‐based full‐cone nozzle simulator. Neither produced a spatially uniform distribution of rainfall depth: both produced distributional patterns that were fairly consistent despite varying intensities and run times. Small‐scale, apparently random variations were superimposed on these more deterministic patterns. However, despite this marked spatial variability, calculation of uniformity coefficients (1−SD/mean) resulted in high values. Thus it appears that the uniformity coefficient gives little real indication of the spatial uniformity of simulated rainfall, despite its established usage in the literature. Additionally, spatial distributions of raindrop size –and hence kinetic energy –were calculated for the full‐cone nozzle simulator. These show that zones of high rainfall amount do not necessarily relate to zones of high energy reaching the surface.
The presence of such variability raises a number of issues for spatially explicit rainfall simulation experiments. While there has been little work on the spatial variability of natural rainfall at field scale and smaller, it appears that the spatial heterogeneity of simulated rainfall depths observed in this study does not differ greatly from that of natural rain. But since a major attraction of rainfall simulation experiments is additional control over rainfall's many variables, the spatial non‐uniformity of depth observed in this study is unwelcome. The existence of an apparently deterministic component to this non‐uniformity nonetheless suggests that it can, at least in principle, be corrected by calibration. Less easily handled is the discrepancy between spatial distributions of rainfall depth and energy, since this will certainly affect rainfall simulation experiments that are, for example, concerned with erosion processes due to raindrop impact. Copyright © 2000 John Wiley & Sons, Ltd. Rainfall simulators are widely used yet there is little evidence in the literature to show that their spatial and temporal variability has been adequately taken into account. For experiments that are concerned only with some aggregate or mean effect of simulated rain then such variations may be unimportant. However, where rainfall simulation is being used to study (and perhaps model) small-scale processes that are themselves spatially variable (such as rill initiation) then knowledge of the simulator's inherent variability is vital. A first aim of this paper is therefore to examine this variability, and to appraise methodologies by which it may be quantified. A second aim is to evaluate the implications for spatially explicit rainfall simulation experiments. Two simulators were used, a portable drip-screen simulator and a laboratory-based full-cone nozzle simulator. Neither produced a spatially uniform distribution of rainfall depth: both produced distributional patterns that were fairly consistent despite varying intensities and run times. Small-scale, apparently random variations were superimposed on these more deterministic patterns. However, despite this marked spatial variability, calculation of uniformity coefficients (1-SD/mean) resulted in high values. Thus it appears that the uniformity coefficient gives little real indication of the spatial uniformity of simulated rainfall, despite its established usage in the literature. Additionally, spatial distributions of raindrop size -and hence kinetic energy -were calculated for the full-cone nozzle simulator. These show that zones of high rainfall amount do not necessarily relate to zones of high energy reaching the surface. The presence of such variability raises a number of issues for spatially explicit rainfall simulation experiments. While there has been little work on the spatial variability of natural rainfall at field scale and smaller, it appears that the spatial heterogeneity of simulated rainfall depths observed in this study does not differ greatly from that of natural rain. But since a major attraction of rainfall simulation experiments is additional control over rainfall's many variables, the spatial non-uniformity of depth observed in this study is unwelcome. The existence of an apparently deterministic component to this non-uniformity nonetheless suggests that it can, at least in principle, be corrected by calibration. Less easily handled is the discrepancy between spatial distributions of rainfall depth and energy, since this will certainly affect rainfall simulation experiments that are, for example, concerned with erosion processes due to raindrop impact. |
Author | Parsons, Anthony J. Lascelles, Bruce Guerra, Antonio J.T. Favis-Mortlock, David T. |
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Cites_doi | 10.1002/(SICI)1096-9837(199804)23:4<365::AID-ESP851>3.0.CO;2-6 10.1029/WR026i003p00501 10.1006/jare.1997.0342 10.13031/2013.39599 10.1002/(SICI)1096-9837(199612)21:12<1073::AID-ESP640>3.0.CO;2-8 10.1016/0933-3630(95)00004-2 10.1016/S0169-555X(98)00033-6 10.1029/98WR01471 10.1016/S0341-8162(98)00092-7 10.1023/A:1000243312103 10.1016/S0169-555X(98)00107-X 10.1016/S0933-3630(89)80002-9 10.1002/(SICI)1099-1085(199901)13:1<89::AID-HYP677>3.0.CO;2-T 10.1016/S0022-1694(97)00034-6 10.1016/S0167-1987(98)00196-2 10.1007/BF00546881 10.1016/S0098-3004(97)00116-7 10.1016/S0341-8162(98)00075-7 10.1016/0022-1694(86)90099-5 10.1002/(SICI)1099-1085(199611)10:11<1527::AID-HYP399>3.0.CO;2-F 10.1016/S0933-3630(97)00013-5 |
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References | Abrahams AD, Parsons AJ. 1990. Determining the mean depth of overland flow in field studies of flow hydraulics. Water Resources Research 26(3): 501-503. Cerdà, A. 1998b. Effect of climate on surface flow along a climatological gradient in Israel: a field rainfall simulation approach. Journal of Arid Environments 38: 145-159. Arazi A, Sharon D, Khain A, Huss A, Mahrer Y. 1997. The windfield and rainfall distribution induced within a small valley: field observations and 2-D numerical modelling. Boundary-Layer Meteorology 83: 349-374. Gabriels D. 1999. The effect of slope length on the amount and size distribution of eroded silt loam soils: short slope laboratory experiments on interrill erosion. Geomorphology 28: 169-172. Abrahams AD, Parsons AJ, Luk S-H. 1986. Resistance to overland flow on desert hillslopes. Journal of Hydrology 88: 343-363. Bergkamp G. 1998. A hierarchical view of the interactions of runoff and infiltration and microtopography in semiarid shrublands. Catena 33: 201-220. Blijenberg HM, De Graaf PJ, Hendricks MR, De Ruiter JF, Van Tetering AAA. 1996. Investigation of infiltration characteristics and debris flow initiation conditions in debris flow source areas using a rainfall simulator. Hydrological Processes 10: 1527-1543. Parsons AJ, Stromberg SGL, Greener M. 1998. Sediment-transport competence of rain-impacted interrill overland flow. Earth Surface Processes and Landforms 23: 365-375. Chappell NA, Ternan JL, Bidin K. 1999. Correlation of physicochemical properties and sub-erosional landforms with aggregate stability variations in a tropical Ultisol disturbed by forestry operations. Soil and Tillage Research 50: 55-71. Sharon D, Arazi A. 1997. The distribution of wind-driven rainfall in a small valley; an emperical basis for numerical model verification. Journal of Hydrology 201: 21-48. Bergkamp G, Cammeraat LH, Martinez-Fernandez J. 1996. Water movement and vegetation patterns on shrubland and an abandoned field in two desertification-threatened areas in Spain. Earth Surface Processes and Landforms 21: 1073-1090. Morgan RPC, McIntyre K, Vickers AW, Quinton JN, Rickson RJ. 1997. A rainfall simulation study of soil erosion on rangeland in Swaziland. Soil Technology 11: 291-299. Bowyer-Bower TAS, Burt TP. 1989. Rainfall simulators for investigating soil response to rainfall. Soil Technology 2: 1-16. Morin J, Goldberg I, Seginer I. 1967. A rainfall simulator with a rotating disk. Transactions of the American Society of Agricultural Engineers 10: 74-79. Hudson NW. 1963. Raindrop size distribution in high intensity storms. Rhodesian Journal of Agricultural Research 1: 6-11. Favis-Mortlock DT. 1998. A self-organising dynamic systems approach to the simulation of rill initiation and development on hillslopes. Computers and Geosciences 24(4): 353-372. Eldridge DJ. 1998. Trampling of microphytic crusts on calcareous soils, and its impact on erosion under rain-impacted flow. Catena 33: 221-239. Rodda JC. 1967. The systematic error in rainfall measurement. Journal of the Institute of Water Engineers 21: 173-177. Cerdà A. 1998a. Relationships between climate and soil hydrological and erosional characteristics along climatic gradients in Metiterranean limestone areas. Geomorphology 25: 123-134. Favis-Mortlock DT, Boardman J, Parsons AJ, Lascelles B. 2000. Emergence and erosion: a model for rill initiation and development. Hydrological Processes (in press). Parsons AJ, Stromberg SGL. 1998. Experimental analysis of size and distance of travel of unconstrained particles in interrill flow. Water Resources Research 34(9): 2377-2381. Hignett CT, Gusli S, Cass A, Besz W. 1995. An automated laboratory rainfall simulation system with controlled rainfall intensity, raindrop energy and soil drainage. Soil Technology 8: 31-42. Poesen J. 1986. 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References_xml | – reference: Cerdà A. 1998a. Relationships between climate and soil hydrological and erosional characteristics along climatic gradients in Metiterranean limestone areas. Geomorphology 25: 123-134. – reference: Parsons AJ, Stromberg SGL. 1998. Experimental analysis of size and distance of travel of unconstrained particles in interrill flow. Water Resources Research 34(9): 2377-2381. – reference: Hudson NW. 1963. Raindrop size distribution in high intensity storms. Rhodesian Journal of Agricultural Research 1: 6-11. – reference: Abrahams AD, Parsons AJ, Luk S-H. 1986. Resistance to overland flow on desert hillslopes. Journal of Hydrology 88: 343-363. – reference: Bergkamp G, Cammeraat LH, Martinez-Fernandez J. 1996. Water movement and vegetation patterns on shrubland and an abandoned field in two desertification-threatened areas in Spain. Earth Surface Processes and Landforms 21: 1073-1090. – reference: Hignett CT, Gusli S, Cass A, Besz W. 1995. An automated laboratory rainfall simulation system with controlled rainfall intensity, raindrop energy and soil drainage. Soil Technology 8: 31-42. – reference: Rodda JC. 1967. The systematic error in rainfall measurement. Journal of the Institute of Water Engineers 21: 173-177. – reference: Eldridge DJ. 1998. Trampling of microphytic crusts on calcareous soils, and its impact on erosion under rain-impacted flow. Catena 33: 221-239. – reference: Gabriels D. 1999. The effect of slope length on the amount and size distribution of eroded silt loam soils: short slope laboratory experiments on interrill erosion. Geomorphology 28: 169-172. – reference: Blijenberg HM, De Graaf PJ, Hendricks MR, De Ruiter JF, Van Tetering AAA. 1996. Investigation of infiltration characteristics and debris flow initiation conditions in debris flow source areas using a rainfall simulator. Hydrological Processes 10: 1527-1543. – reference: Cerdà, A. 1998b. Effect of climate on surface flow along a climatological gradient in Israel: a field rainfall simulation approach. Journal of Arid Environments 38: 145-159. – reference: Abrahams AD, Parsons AJ. 1990. Determining the mean depth of overland flow in field studies of flow hydraulics. Water Resources Research 26(3): 501-503. – reference: Boix C, Calvo A, Imeson AC, Schoorl JM, Soto S, Tiemessen IR. 1995. Properties and erosional response of soils in a degraded ecosystem in Crete (Greece). Environmental Monitoring and Assessment 37: 79-92. – reference: Jayawardena AW, Rahman Bhuiyan R. 1999. Evaluation of an interrill soil erosion model using laboratory catchment data. Hydrological Processes 13: 89-100. – reference: Favis-Mortlock DT, Boardman J, Parsons AJ, Lascelles B. 2000. Emergence and erosion: a model for rill initiation and development. Hydrological Processes (in press). – reference: Sharon D, Arazi A. 1997. The distribution of wind-driven rainfall in a small valley; an emperical basis for numerical model verification. Journal of Hydrology 201: 21-48. – reference: Poesen J. 1986. Field measurement of splash erosion to validate a splash transport model. Zeitschrift für Geomorphologie N.F. Supplement 58: 81-91. – reference: Bergkamp G. 1998. A hierarchical view of the interactions of runoff and infiltration and microtopography in semiarid shrublands. Catena 33: 201-220. – reference: Favis-Mortlock DT. 1998. A self-organising dynamic systems approach to the simulation of rill initiation and development on hillslopes. Computers and Geosciences 24(4): 353-372. – reference: Morgan RPC, McIntyre K, Vickers AW, Quinton JN, Rickson RJ. 1997. A rainfall simulation study of soil erosion on rangeland in Swaziland. Soil Technology 11: 291-299. – reference: Morin J, Goldberg I, Seginer I. 1967. A rainfall simulator with a rotating disk. Transactions of the American Society of Agricultural Engineers 10: 74-79. – reference: Parsons AJ, Stromberg SGL, Greener M. 1998. Sediment-transport competence of rain-impacted interrill overland flow. Earth Surface Processes and Landforms 23: 365-375. – reference: Bowyer-Bower TAS, Burt TP. 1989. Rainfall simulators for investigating soil response to rainfall. Soil Technology 2: 1-16. – reference: Arazi A, Sharon D, Khain A, Huss A, Mahrer Y. 1997. The windfield and rainfall distribution induced within a small valley: field observations and 2-D numerical modelling. Boundary-Layer Meteorology 83: 349-374. – reference: Chappell NA, Ternan JL, Bidin K. 1999. Correlation of physicochemical properties and sub-erosional landforms with aggregate stability variations in a tropical Ultisol disturbed by forestry operations. 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SubjectTerms | erosion modelling rainfall energy rainfall simulation soil erosion spatial variability temporal variability |
Title | Spatial and temporal variation in two rainfall simulators: implications for spatially explicit rainfall simulation experiments |
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