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 inEarth surface processes and landforms Vol. 25; no. 7; pp. 709 - 721
Main Authors Lascelles, Bruce, Favis-Mortlock, David T., Parsons, Anthony J., Guerra, Antonio J.T.
Format Journal Article
LanguageEnglish
Published 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.
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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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.
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Snippet Rainfall simulators are widely used yet there is little evidence in the literature to show that their spatial and temporal variability has been adequately...
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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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