Estimation of phosphorus loads with sparse data for agricultural watersheds in the Czech Republic

Abstract

Agricultural watersheds in the Czech Republic are one of the primary sources of non-point-source phosphorus (P) loads in receiving waters. Since such non-point sources are generally located in headwater catchments, streamflow and P concentration data are sparse. We show how very short daily streamflow and P concentration records can be combined with nearby longer existing daily streamflow records to result in reliable estimates of daily and annual P concentrations and loads. Maintenance of variance streamflow record extension methods (MOVE) can be employed to extend short streamflow records. Constituent load regressions are used to predict daily P constituent loads from streamflow and other time varying characteristics. Annual P loads are then estimated for individual watersheds. Resulting annual P load estimates ranged from 0.21 to 95.4 kg year -1 with a mean value of 11.77 kg year -1 . Similarly annual P yield estimates ranged from 0.01 to 0.3 kg ha -1 year -1 with an average yield of 0.07 kg ha -1 year -1. We document how short records of daily streamflow and P concentrations can be combined with a national network of daily streamflow records in the Czech Republic to arrive at meaningful and reliable estimates of annual P loads for small agricultural watersheds.

Analysis of efficiency of pollution reduction measures in rural basin using MIKE Basin model. Case study: Olšava River Basin

“…However, these percentages are affected by incomplete information on discharge from local municipal point sources, which are unlisted in the integrated pollution register. These results are in line with the findings reported by different authors (Beránková et al, 2010;Langhammer, 2004). The high shares of non-point pollution, especially in nutrients, are common in rural basins.…”

“…Another source of uncertainty is the sparse network of discharge and water quality monitoring on small streams, as they are necessary as data sources for boundary conditions and for model calibration. The monitoring networks in small basins are usually sparse, time series are short and the monitoring interval is infrequent (Beránková et al 2010). The missing quantitative information must be taken from the most similar or the nearest profile.…”

Quantifying Water Pollution Sources in a Small Tile‐drained Agricultural Watershed

“…These uncertainties and NPS dynamics are also confirmed by the results from various modelling techniques used to distinguish water pollution sources and to test the efficiency of diffuse pollution abatement measures in small to larger areas . Most of the studies applying diverse methods in order to quantify contributions of NPS to surface water pollution in temperate zone largely consent on the essential contribution of episodic phosphorus (P) on the P water loads , emitted to water via surface and subsurface runoff namely during the rainfall–runoff (R–R) events of various extent . The pattern of nitrate nitrogen (NO 3 ‐N) loss from soil as well as its loads from NPS is fairly different compared to that of P. Nevertheless, extensive NO 3 ‐N loads predominantly happen during R–R events or during wet periods .…”

“…For NO 3 ‐N, the elevated concentrations are reported to be governed by arable land ratio and extent of tile drainage systems as worsening factors and water surfaces and/or permanent cultures (grassland, forest) ratios as improving factors in a catchment . For most P forms in water, the urbanization gradient and character of wastewater treatment (or other point sources) are often mentioned as the responsible variables during low flows while the extent of arable land threatened by erosion, application of excessive fertilizers or intensive grazing have weighty impact during wetter periods . Tile drainage, built to remove excess water in agricultural land, shortens water residence time in soil/catchment, makes the soil more aerobic, reduces denitrification and often is a substantial source of NO 3 ‐N in a catchment's water environment .…”