Determining storm sampling requirements for improving precision of annual load estimates of nutrients from a small forested watershed

Abstract

This study sought to determine the lowest number of storm events required for adequate estimation of annual nutrient loads from a forested watershed using the regression equation between cumulative load (∑L) and cumulative stream discharge (∑Q). Hydrological surveys were conducted for 4 years, and stream water was sampled sequentially at 15-60-min intervals during 24 h in 20 events, as well as weekly in a small forested watershed. The bootstrap sampling technique was used to determine the regression (∑L-∑Q) equations of dissolved nitrogen (DN) and phosphorus (DP), particulate nitrogen (PN) and phosphorus (PP), dissolved inorganic nitrogen (DIN), and suspended solid (SS) for each dataset of ∑L and ∑Q. For dissolved nutrients (DN, DP, DIN), the coefficient of variance (CV) in 100 replicates of 4-year average annual load estimates was below 20% with datasets composed of five storm events. For particulate nutrients (PN, PP, SS), the CV exceeded 20%, even with datasets composed of more than ten storm events. The differences in the number of storm events required for precise load estimates between dissolved and particulate nutrients were attributed to the goodness of fit of the ∑L-∑Q equations. Bootstrap simulation based on flow-stratified sampling resulted in fewer storm events than the simulation based on random sampling and showed that only three storm events were required to give a CV below 20% for dissolved nutrients. These results indicate that a sampling design considering discharge levels reduces the frequency of laborious chemical analyses of water samples required throughout the year.

Quantification of Phosphorus Exports from a Small Forested Headwater-Catchment in the Eastern Ore Mountains, Germany

“…It was observed that the event-based export of P can contribute up to 40% to the seasonal and 19% to the annual export fluxes, which highlights the importance of monitoring stormflow events for flux estimation and process understanding. These results support the findings of numerous studies [9,11,18,31] which have found that time discrete sampling schemes at the monthly or bi-weekly time scale are unable to capture short-term changes in solute concentrations, and therefore can lead to a bias in load calculations. Ide et al [18] suggested that a certain number of monitored stormflow events are necessary to quantify export fluxes with low bias.…”

“…These results support the findings of numerous studies [9,11,18,31] which have found that time discrete sampling schemes at the monthly or bi-weekly time scale are unable to capture short-term changes in solute concentrations, and therefore can lead to a bias in load calculations. Ide et al [18] suggested that a certain number of monitored stormflow events are necessary to quantify export fluxes with low bias. The results of our study also suggest that the differences in the flux estimates between the selected methods are smaller than the differences due to the sampling scheme (i.e., see the error bars in Figures 3 and 4).…”

“…These values are in the same range as previous studies for watersheds in other regions of Europe [4,5,16], but lower than findings for catchments dominated by monsoonal influence [10,18]. Further, the seasonality of the export is driven by high discharge due either to snow melt in the winter/spring or due to rainfall events following a dry period where P could accumulate in the soil.…”

“…A weekly or bi-weekly sampling scheme is therefore not able to entirely capture those changes, and does not provide an adequate enough representation of P dynamics necessary for process understanding [13]. This information gap will therefore increase process uncertainty [11], which will propagate into the estimation of P export fluxes [10,11,18]. Table 4 provides a summary of the evaluation criteria for each of the applied loadflex models.…”

“…For various catchments in Finland [4], export rates of TP-P as high as 90 g·ha −1 ·a −1 have been reported, depending on the catchment characteristics. For headwater catchments in Japan influenced by monsoon, export rates of TP-P from 44 to 280 g·ha −1 ·a −1 [17] and approximately 222 g·ha −1 ·a −1 [18] were found. However, no studies exist which analyze and quantify the impact of monitoring frequency and selected load calculation methods on the estimated P fluxes from forested catchments.…”