Elena Valkama

A Simple Dynamic Model of Soil Test Phosphorus Responses to Phosphorus Balances

Soil test P (STP) concentration indicates whether annual P applications can be expected to give yield increases and can also indicate an elevated risk of P mobilization and potential for P transfer to surface waters and groundwater from a particular field. Changes in STP with time thus project agronomic benefits and environmental risks of different P use strategies. To predict STP changes with time, we constructed a simple dynamic model for which the input variables are P balance and initial STP. The model parameters (soil type-specific constants) were fitted using data originating from 44 P fertilizer experiments with different P rates. Model performance was evaluated using independent data sets that either had reasonably accurate input values ( = 103) or were obtained from farmers through interviews ( = 638). The simulations were in agreement with measured STP changes for both evaluation data sets when fittings were performed separately for four main soil types (clays, silts, coarse mineral soils, and organic soils). Statistical analysis confirmed that the model captured the trends in STP (NHOAc test) with acceptable accuracy and precision, with of 0.83 and 0.66 for the data with more accurate input and for farmer interview data, respectively; the corresponding model efficiency statistics were 0.88 and 0.66. The model is not restricted to use with one soil test, as fittings for several different types of soil tests can be generated. In this study, we fitted the model for Olsen P data retrieved from the literature. Agronomic use of the model includes evaluation of P use strategies, e.g., when a certain STP level is targeted or when long-term economy of P use is calculated. In an environmental context, the model can be used to predict STP changes with time under variable P balance regimes, which is essential for realistic assessment of changes in the potential for dissolved P losses.

A Meta-Analysis on Nitrogen Retention by Buffer Zones

Buffer zones, established between agricultural fields and water bodies, are widely used as a measure to reduce N in surface runoff and groundwater. However, the literature indicates inconsistent results on the N removal efficiency of buffer zones between studies. We performed a weighed meta-analysis on the buffer zone effects on NO-N and total N in surface runoff and groundwater by summarizing 46 studies published between 1980 and 2017. The overall effects of buffer zones were a 33 (-48 to -17%, = 25) and 70% (-78 to -62%, = 38) NO-N reduction in surface runoff and in groundwater, respectively, compared with controls with no buffer zone. In addition, buffer zones reduced the total N in surface runoff by 57% (-68 to -43%, = 16). The effects of buffer zones on N retention were consistent across continents and in different climates. Nitrogen retention increased with increasing initial N concentrations discharged from the source of pollution. According to a meta-regression, the N removal efficiency in surface runoff decreased in consort with increasing buffer zone age. Otherwise, the meta-analysis revealed no effects of buffer zone characteristics such as the width or species number (for grass buffer zones) on the N retention in surface runoff and groundwater. Unlike groundwater quality, which responded equally well regardless of the source of pollution, buffer zone type, or buffer zone age, surface water quality is more sensitive, and it might not be satisfactorily improved by tree buffer zones or aged buffer zones, or when the source of pollution originates from grass production fields.