The inadequacy of monitoring without modelling support

Delay in catchment nitrogen load to streams following restrictions on fertilizer application

A MIKE SHE hydrological-solute transport model including nitrate reduction is employed to evaluate the delayed response in nitrogen loads in catchment streams following the implementation of nitrogen mitigation measures since the 1980s. The nitrate transport lag times between the root zone and the streams for the period 1950-2011 were simulated for two catchments in Denmark and compared with observational data. Results include nitrogen concentration and mass discharge to streams. By automated baseflow separation, stream discharge was separated into baseflow and drain flow components, and the nitrogen concentration and mass discharge in baseflow and drain flow were determined. This provided insight on the development of stream nitrogen loads, with a short average lag time in drain flow and a long average lag time in baseflow. The long term effect of nitrogen mitigation measures was determined, with results showing that there is a 15 years long delay in the appearance of peak nitrogen loads in streams. This means that real time stream monitoring data cannot be used alone to assess the effect of nitrogen mitigation measures.

Review of scenario analyses to reduce agricultural nitrogen and phosphorus loading to the aquatic environment

Nutrient loadings of nitrogen (N) and phosphorus (P) to aquatic environments are of increasing concern globally for managing ecosystems, drinking water supply and food production. There are often multiple sources of these nutrients in the landscape, and the different hydrological flow patterns within stream or river catchments have considerable influence on nutrient transport, transformation and retention processes that all eventually affect loadings to vulnerable aquatic environments. Therefore, in order to address options to reduce nutrient loadings, quantitative assessment of their effects in real catchments need to be undertaken. This involves setting up scenarios of the possible nutrient load reduction measures and quantifying their impacts via modelling. Over the recent two decades there has been a great increase in the use of scenario-based analyses of strategies to combat excessive nutrient loadings. Here we review 130 published papers extracted from Web of Science for 1995 to 2014 that have applied models to analyse scenarios of agricultural impacts on nutrients loadings at catchment scale. The review shows that scenario studies have been performed over a broad range of climatic conditions, with a large focus on measures targeting land cover/use and land management for reducing the source load of N and P in the landscape. Some of the studies considered how to manage the flows of nutrients, or how changes in the landscape may be used to influence both flows and transformation processes. Few studies have considered spatially targeting measures in the landscape, and such studies are more recent. Spatially differentiated options include land cover/use modification and application of different land management options based on catchments characteristics, cropping conditions and climatic conditions. Most of the studies used existing catchment models such as SWAT and INCA, and the choice of the models may also have influenced the setup of the scenarios. The use of stakeholders for designing scenarios and for communication of results does not seem to be a widespread practice, and it would be recommendable for future scenario studies to have a more in-depth involvement of stakeholders for the elaboration and interpretation of scenarios, in particular to enhance their relevance for farm and catchment management and to foster better policies and incentives.

Influence of different nitrate-N monitoring strategies on load estimation as a base for model calibration and evaluation

Model-based predictions of the impact of land management practices on nutrient loading require measured nutrient flux data for model calibration and evaluation. Consequently, uncertainties in the monitoring data resulting from sample collection and load estimation methods influence the calibration, and thus, the parameter settings that affect the modeling results. To investigate this influence, we compared three different time-based sampling strategies and four different load estimation methods for model calibration and compared the results. For our study, we used the river basin model Soil and Water Assessment Tool on the intensively managed loess-dominated Parthe watershed (315 km(2)) in Central Germany. The results show that nitrate-N load estimations differ considerably depending on sampling strategy, load estimation method, and period of interest. Within our study period, the annual nitrate-N load estimation values for the daily composite data set have the lowest ranges (between 9.8% and 15.7% maximum deviations related to the mean value of all applied methods). By contrast, annual estimation results for the submonthly and the monthly data set vary in greater ranges (between 24.9% and 67.7%). To show differences between the sampling strategies, we calculated the percentage deviation of mean load estimations of submonthly and monthly data sets as related to the mean estimation value of the composite data set. For nitrate-N, the maximum deviation is 64.5% for the submonthly data set in the year 2000. We used average monthly nitrate-N loads of the daily composite data set to calibrate the model to achieve satisfactory simulation results [Nash-Sutcliffe efficiency (NSE) 0.52]. Using the same parameter settings with submonthly and monthly data set, the NSE dropped to 0.42 and 0.31, respectively. Considering the different results from the monitoring strategy and the load estimation method, we recommend both the implementation of optimized monitoring programs and the use of multiple load estimation methods to improve water quality characterization and provide appropriate model calibration and evaluation data.