Estimation of nonpoint source loadings with data obtained from limited sampling programs

Abstract

The feasibility of estimating nonpoint source loadings with data obtained from limited sampling programs was analyzed in conjunction with a study of sediment and nutrient loadings in a Swedish river basin. The study showed that different loading estimation methods can yield significantly different results, even if sampling during events (e.g. peak flows) occurs. This was particularly true for the temporal distribution of the estimated loadings. The estimated spatial distribution of loadings in the monitored subbasins was more independent of the applied estimation technique. Theoretical calculations showed that sampling strategies with evenly spaced sampling intervals may systematically over- or underestimate the true loading.The study basin was characterized by a pronounced snowmelt period and partly erosion-controlled nutrient loadings. Guidelines for the estimation of nonpoint loadings in such basins are summarized in a matrix. Factors influencing the choice of estimation method include the characteristics of the collected data, the relative influence of point sources, and the desired detail of loading estimates. Possible correlations between flow and concentration, and the presence of extreme events (and whether or not the events were sampled), also determine the appropriateness of the different methods.

Characterizing Dependence of Pesticide Load in Surface Water on Precipitation and Pesticide Use for the Sacramento River Watershed

“…The regression analysis used weekly or biweekly moving average of daily loads as the dependent variable. To obtain daily pesticide load, the original concentration data in the Surface Water Database were used first to obtain the estimated concentrations for the unsampled days using linear interpolation (10):…”

Methods for water quality sampling and load estimation in monitoring of Norwegian agricultural catchments

“…Low sampling frequency can introduce serious errors in load estimates for streams and small rivers (Rekolainen et al 1991;Reinelt and Grimvall 1992;Kronvang and Bruhn 1996). However, this problem is less pronounced for large rivers, as has been demonstrated by Tonderski et al (1995), who studied large rivers in Eastern and Western Europe, and by Grimvall (1996), who performed a similar investigation of data on Swedish rivers.…”

“…Secondly, both better precision and more stable accuracy were achieved when analysing total nitrogen, as compared to phosphorus and suspended solids, which is in accordance with the findings of Rekolainen (1989) regarding phosphorus and the results reported by Walling and Webb (1981), Richards and Holloway (1987) and Webb et al (1997) concerning suspended sediment yields. It has previously been shown that event sampling and sampling during high flows are important components of small-scale monitoring programmes (Rekolainen et al 1991;Reinelt and Grimvall 1992), particularly when a substantial part of the annual load occurs during a few rain periods (Grimvall 1996), even though Kronvang and Bruhn (1996) have maintained that stratified sampling (i.e. intensive sampling under certain flow conditions) does not necessarily increase the accuracy and precision compared to regular, temporally equidistant sampling.…”

Uncertainties in selected river water quality data

“…Compared to large rivers the uncertainties associated with load estimates based on infrequent samples will increase for small basins. Furthermore in small rivers, where single events play a relatively more important role, the problem of calculating transports is of a different character (Rekolainen et al, 1991;Reinelt and Grimvall, 1991).…”