Roving revisited, towards an optimum throughfall sampling design

Abstract

AbstractAdditional aspects regarding the optimum fixed and roving sampling techniques, to those already explored in a previous authors’ throughfall study, are further investigated here. The roving technique consists in the random repositioning, with a frequency fr, of N throughfall gauges among M positions (M > N), oppositely to the fixed or stationary arrangement where N = M. Both fixed and roving optimum sampling techniques of 100 monitored throughfall events sampled with 200 fixed gauges under a semideciduous tropical rain forest in Panama were investigated by means of Monte‐Carlo numerical experiments. Mean dispersion was shown to be always smaller in the roving versus the fixed gauge arrangement, independently of the relocation frequency studied (fr = 0.1, 0.2, 0.5, 1), such that all roving schemes with N ≥ 50 gauges lay within ±5% of the mean cumulative throughfall. Results indicated that a low variability, high precision, and accuracy are obtained with a modest relocation frequency fr = 0.2 (i.e. a relocation every five episodes of the original 100 measured events) and N = 30 roving gauges, with no significant improvement worth the extra field work beyond fr > 0.2 and N >30. Only by increasing the number of roving positions from M < < 200 to M = 200, the precision and accuracy of the mean estimate were improved without comprising additional labour. Hence, a roving sampling scheme which relocates gauges over completely new fresh sites each roving cycle is recommended for future throughfall studies. Finally, we designed an a priori sampling strategy which permitted us to conclude that using only the first 20 out of the total 100 measuring events, for the remaining 80 throughfall field measurements, N = 40 roving gauges (i.e. five time less than the originally 200 gauges displayed) would have been sufficient for ensuring ≤5% error, expressed as percentage of the mean cumulative throughfall. Copyright © 2012 John Wiley & Sons, Ltd.