Diffuse phosphorus models in the United States and europe: their usages, scales, and uncertainties.

Today there are many well-established computer models that are being used at different spatial and temporal scales to describe water, sediment, and P transport from diffuse sources. In this review, we describe how diffuse P models are commonly being used in the United States and Europe, the challenge presented by different temporal and spatial scales, and the uncertainty in model predictions. In the United States, for water bodies that do not meet water quality standards, a total maximum daily load (TMDL) of the pollutant of concern must be set that will restore water quality and a plan implemented to reduce the pollutant load to meet the TMDL. Models are used to estimate the current maximum daily and annual average load, to estimate the contribution from different nonpoint sources, and to develop scenarios for achieving the TMDL target. In Europe, the EC-Water Framework Directive is the driving force to improve water quality and models are playing a similar role to that in the United States, but the models being used are not the same. European models are more likely to take into account leaching of P and the identification of critical source areas. Scaling up to the watershed scale has led to overparameterized models that cannot be used to test hypotheses regarding nonpoint sources of P or transport processes using the monitoring data that is typically available. There is a need for more parsimonious models and monitoring data that takes advantage of the technological improvements that allow nearly continuous sampling for P and sediment. Tools for measuring model uncertainty must become an integral part of models and be readily available for model users.

Uncertainties in data and models to describe event dynamics of agricultural sediment and phosphorus transfer.

Mathematical models help to quantify agricultural sediment and phosphorus transfers and to simulate mitigation of pollution. This paper develops empirical models of the dominant sediment and phosphorus event dynamics observed at high resolution in a drained and undrained, intensive grassland field-scale lysimeter (1 ha) experiment. The uncertainties in model development and simulation are addressed using Generalized Likelihood Uncertainty Estimation. A comparison of suspended solids (SS) and total phosphorus (TP) samples with a limited number of manual repeats indicates larger data variability at low flows. Quantitative uncertainty estimates for discharge (Q) are available from another study. Suspended solids-discharge (SS-Q) hysteresis is analyzed for four events and two drained and two undrained fields. Hysteresis loops differ spatially and temporally, and exhaustion is apparent between sequential hydrograph peaks. A coherent empirical model framework for hysteresis, where SS is a function of Q and rate of change of Q, is proposed. This is evaluated taking the Q uncertainty into account, which can contribute substantially to the overall uncertainty of model simulations. The model simulates small hysteresis loops well but fails to simulate exhaustion of SS sources and flushing at the onset of events. Analysis of the TP-SS relationship reveals that most of the variability occurs at low flows, and a power-law relationship can explain the dominant behavior at higher flows, which is consistent across events, fields, and pathways. The need for further field experiments to test hypotheses of sediment mobilization and to quantify data uncertainties is identified.

Spatial variability of soil phosphorus in relation to the topographic index and critical source areas: sampling for assessing risk to water quality.

A measure of soil P status in agricultural soils is generally required for assisting with prediction of potential P loss from agricultural catchments and assessing risk for water quality. The objectives of this paper are twofold: (i) investigating the soil P status, distribution, and variability, both spatially and with soil depth, of two different first-order catchments; and (ii) determining variation in soil P concentration in relation to catchment topography (quantified as the "topographic index") and critical source areas (CSAs). The soil P measurements showed large spatial variability, not only between fields and land uses, but also within individual fields and in part was thought to be strongly influenced by areas where cattle tended to congregate and areas where manure was most commonly spread. Topographic index alone was not related to the distribution of soil P, and does not seem to provide an adequate indicator for CSAs in the study catchments. However, CSAs may be used in conjunction with soil P data for help in determining a more "effective" catchment soil P status. The difficulties in defining CSAs a priori, particularly for modeling and prediction purposes, however, suggest that other more "integrated" measures of catchment soil P status, such as baseflow P concentrations or streambed sediment P concentrations, might be more useful. Since observed soil P distribution is variable and is also difficult to relate to nationally available soil P data, any assessment of soil P status for determining risk of P loss is uncertain and problematic, given other catchment physicochemical characteristics and the sampling strategy employed.