A review of rainfall interception modelling

Abstract

s u m m a r yThis paper is a review of physically-based rainfall interception modelling. Fifteen models were selected, representing distinct concepts of the interception process. Applications of these models to field data sets published before March 2008 are also analysed. We review the theoretical basis of the different models, and give an overview of the models' characteristics. The review is designed to help with the decision on which model to apply to a specific data set. The most commonly applied models were found to be the original and sparse Gash models (69 cases) and the original and sparse Rutter models (42 cases). The remaining 11 models have received much less attention, but the contribution of the Mulder model should also be acknowledged. The review reveals the need for more modelling of deciduous forest, for progressively more sparse forest and for forest in regions with intensive storms and the consequent high rainfall rates. The present review also highlights drawbacks of previous model applications. Failure to validate models, the few comparative studies, and lack of consideration given to uncertainties in measurements and parameters are the most outstanding drawbacks. Finally, the uncertainties in model input data are rarely taken into account in rainfall interception modelling.

The Runoff Declining Process and Water Quality in Songhuajiang River Catchment, China under Global Climatic Change

“…Further analysis reveals that although the trend of change in rainfall is the same as that in runoff in almost all the stations in the two decline periods, the rainfall Mann-Kendall values are much smaller than runoff values. This confirms that human activity, rather than change in rainfall, is the main driving factor of abrupt runoff decline [11][12][13][14][15][16][17][18][19][28][29][30][31][32].…”

“…As to the human activities, several forms has been noticed, however, how to quantify the effect of various human activities on runoff has so far not been fully understood [17][18][19][20]. All these processes influence water quality and manipulation of water management performance in the catchment in the world [21][22][23][24][25].…”

Instrumental method for reducing error in compression-derived measurements of rainfall interception for individual trees

“…Instrumental method for reducing error in compression-derived measurements of rainfall interception for individual trees INTRODUCTION Intercepted rainfall stored by, and evaporated from, canopy bark and foliar surfaces can diminish incident precipitation inputs beneath the forest canopy by as much as 50% (Muzylo et al 2009), depending on species and season (Crockford and Richardson 2000, Levia and Frost 2003, Keim et al 2006, Llorens and Domingo 2007. However, estimates of canopy water storage and evaporation are primarily based on indirect methods and model estimates which are capable of producing >30% error (Muzylo et al 2009).…”

“…However, estimates of canopy water storage and evaporation are primarily based on indirect methods and model estimates which are capable of producing >30% error (Muzylo et al 2009). Error is compounded further if these indirectly-derived interception components are falsely linked to net precipitation measurements by simply treating interception as a "black-box" process (Pollacco and Angulo-Jaramilo 2009), or when splash droplet evaporation is neglected (Murakami 2006, 2007, Dunkerley 2009).…”

“…The installation procedure outlined in Friesen et al (2008) hand-aligns mechanical Wind and the weight of intercepted rainfall upon unevenlydistributed canopies will produce bending-and torquerelated anomalies within stem compression data. (Huang et al 2005, Zhang et al 2006, Muzylo et al 2009 displacement sensors, enhancing the potential for human error. Recognizing this shortcoming, Friesen et al (2008) suggested the need for a precision mounting method which could quickly and accurately determine orthogonal, neutral bending axes and the placement of sensors.…”