TY - JOUR
T1 - The case for increased validation of rainfall simulation as a tool for researching runoff, soil erosion, and related processes
AU - Dunkerley, David
PY - 2021/7
Y1 - 2021/7
N2 - Rainfall simulation is a versatile and widely-used research tool. It confers control and convenience to the complex task of building an understanding of landsurface hydrologic and geomorphic processes from field or laboratory experimentation. However, rainfall simulation experiments may not adequately capture natural processes, but the magnitude of any bias is largely unknown. This leads to a need for the systematic validation of rainfall simulation protocols, to establish the extent to experimental outcomes do or do not correspond to natural processes and process rates. This validation appears rarely to have been attempted. This review presents an overview of what has been found in validation studies of rainfall simulation experiments targeting infiltration, runoff, soil erosion, and nutrient and agrochemical washoff, and related processes. It provides comments on the challenges and possible pathways to further and more wide-ranging validation studies to support and develop protocols for rainfall simulation experiments. The validation process is itself complex, and poses significant technical challenges, but studies generally find significant discrepancies between processes and rates under simulated and natural rainfall. Some studies suggest that after suitable scaling and other adjustments are made, rainfall simulation data can approximate results collected under natural rainfall, but the number of such studies is small, and validation has not been attempted at all for some rainfall simulation protocols. Rainfall simulation results most closely approximate those seen under natural rainfall if the rainfall simulation involves intensity fluctuations. Scaling effects are problematic, and there appear to be no validation studies for rainfall simulation experiments that rely on 'microplots' as small as ~ 0.07 m2.
AB - Rainfall simulation is a versatile and widely-used research tool. It confers control and convenience to the complex task of building an understanding of landsurface hydrologic and geomorphic processes from field or laboratory experimentation. However, rainfall simulation experiments may not adequately capture natural processes, but the magnitude of any bias is largely unknown. This leads to a need for the systematic validation of rainfall simulation protocols, to establish the extent to experimental outcomes do or do not correspond to natural processes and process rates. This validation appears rarely to have been attempted. This review presents an overview of what has been found in validation studies of rainfall simulation experiments targeting infiltration, runoff, soil erosion, and nutrient and agrochemical washoff, and related processes. It provides comments on the challenges and possible pathways to further and more wide-ranging validation studies to support and develop protocols for rainfall simulation experiments. The validation process is itself complex, and poses significant technical challenges, but studies generally find significant discrepancies between processes and rates under simulated and natural rainfall. Some studies suggest that after suitable scaling and other adjustments are made, rainfall simulation data can approximate results collected under natural rainfall, but the number of such studies is small, and validation has not been attempted at all for some rainfall simulation protocols. Rainfall simulation results most closely approximate those seen under natural rainfall if the rainfall simulation involves intensity fluctuations. Scaling effects are problematic, and there appear to be no validation studies for rainfall simulation experiments that rely on 'microplots' as small as ~ 0.07 m2.
KW - Intensity profile
KW - Natural rainfall
KW - Rainfall simulation
KW - Runoff plots
KW - Validation
UR - http://www.scopus.com/inward/record.url?scp=85102874512&partnerID=8YFLogxK
U2 - 10.1016/j.catena.2021.105283
DO - 10.1016/j.catena.2021.105283
M3 - Review Article
AN - SCOPUS:85102874512
SN - 0341-8162
VL - 202
JO - Catena
JF - Catena
M1 - 105283
ER -