Adaptive forecasting of phytoplankton communities.

The global proliferation of harmful algal blooms poses an increasing threat to water resources, recreation and ecosystems. Predicting the occurrence of these blooms is therefore needed to assist water managers in making management decisions to mitigate their impact. Evaluation of the potential for forecasting of algal blooms using the phytoplankton community model PROTECH was undertaken in pseudo-real-time. This was achieved within a data assimilation scheme using the Ensemble Kalman Filter to allow uncertainties and model nonlinearities to be propagated to forecast outputs. Tests were made on two mesotrophic lakes in the English Lake District, which differ in depth and nutrient regime. Some forecasting success was shown for chlorophyll a, but not all forecasts were able to perform better than a persistence forecast. There was a general reduction in forecast skill with increasing forecasting period but forecasts for up to four or five days showed noticeably greater promise than those for longer periods. Associated forecasts of phytoplankton community structure were broadly consistent with observations but their translation to cyanobacteria forecasts was challenging owing to the interchangeability of simulated functional species.

Controls on catchment-scale patterns of phosphorus in soil, streambed sediment, and stream water.

Many models of phosphorus (P) transfer at the catchment scale rely on input from generic databases including, amongst others, soil and land use maps. Spatially detailed geochemical data sets have the potential to improve the accuracy of the input parameters of catchment-scale nutrient transfer models. Furthermore, they enable the assessment of the utility of available, generic spatial data sets for the modeling and prediction of soil nutrient status and nutrient transfer at the catchment scale. This study aims to quantify the unique and joint contribution of soil and sediment properties, land cover, and point-source emissions to the spatial variation of P concentrations in soil, streambed sediments, and stream water at the scale of a medium-sized catchment. Soil parent material and soil chemical properties were identified as major factors controlling the catchment-scale spatial variation in soil total P and Olsen P concentrations. Soil type and land cover as derived from the generic spatial database explain 33.7% of the variation in soil total P concentrations and 17.4% of the variation in Olsen P concentrations. Streambed P concentrations are principally related to the major element concentrations in streambed sediment and P delivery from the hillslopes due to sediment erosion. During base flow conditions, the total phosphorus (<0.45 microm) concentrations in stream water are mainly controlled by the concentrations of P and the major elements in the streambed sediment.

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.