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A methodology to assess input-variable sensitivity for sediment transport relations is presented. The Mean Value First Order Second Moment Method (MVFOSM) is applied to two bed load transport equations showing that it may be used to rank all input variables in terms of how their specific variance affects the overall variance of the sediment transport estimation. In sites where data are scarce or nonexistent, the results obtained may be used to (i) determine what variables would have the largest impact when estimating sediment loads in the absence of field observations and (ii) design field campaigns to specifically measure those variables for which a given transport equation is most sensitive; in sites where data are readily available, the results would allow quantifying the effect that the variance associated with each input variable has on the variance of the sediment transport estimates. An application of the method to two transport relations using data from a tropical mountain river in Costa Rica is implemented to exemplify the potential of the method in places where input data are limited. Results are compared against Monte Carlo simulations to assess the reliability of the method and validate its results. For both of the sediment transport relations used in the sensitivity analysis, accurate knowledge of sediment size was found to have more impact on sediment transport predictions than precise knowledge of other input variables such as channel slope and flow discharge.

Plain Language Summary Estimation of accurate sediment loads in rivers is challenging; particularly in areas where data needed to use sediment transport relations are scarce. Variability of the input parameters implies difficulty in the ability to constrain the range of possible sediment transport estimates obtained. Are all input parameters equally responsible for the variability or is there one that contributes more to it? This paper presents a simple and useful methodology to rank the importance of each variable in a given sediment transport relation. The results of the method, applicable to any sediment transport equation, specifically indicate how sensitive the relation is to each input parameter. This knowledge provides useful guidance when planning or conducting field measurements within a research or engineering project, in order to prioritize available resources so as to better constrain the variability of the input parameters and, therefore, that of the sediment transport estimates.