Field-specific simulations of net N mineralization based on digitally available soil and weather data. I. Temperature and soil water dependency of the rate coefficients

Abstract

Including field-or even site-specific estimates of current net N mineralization into N fertilizer strategy is essential in order to further reduce N surpluses while maintaining crop yields, but adequate estimates are not available. Simulation models could account for many influencing factors, yet are not easily adjustable to different soil and site characteristics. Nowadays important input data for N mineralization models are digitally available. Thus, our objectives were (1) to experimentally determine specific temperature and soil water dependency functions for the rate coefficients of net N mineralization that could be allocated via digitally mapped data and (2) to find out the least necessary discrimination between soils. Specific and general functions for the rate coefficients of two organic N pools with first-order kinetics were derived using laboratory long-and short-term incubations from a broad variety of soils. Functions were evaluated using comparisons to field incubations of undisturbed soil columns from 27 sites. Interestingly, a differentiation between specific functions of not more than three soil groups was necessary for quite accurate simulations (r 2 = 0.87, P \ 0.001; RMSE = 23 kg N ha -1 , n-RMSE = 29%). The two criteria for grouping, soil texture (loess vs. sandy/loamy classes) and humus content class (applies only to temperature functions for sandy textures), can be taken from digital soil maps. Field studies, especially under suboptimal water contents, with plant cover and N-fertilization, will have to further prove the applicability of the derived functions. Pedotransfer functions for the pool sizes also based on digitally available data are needed for automatically calculating specific estimates of net N mineralization.

Fallow replacement and alternative nitrogen management for reducing nitrate leaching in a semiarid region

“…Net nitrate production model R statistical software (The R Foundation for Statistical Computing, Vienna, Austria, 2013) was used to estimate a linear regression specification of NNP at the subfield level, which characterizes a more practical model for assessing and making insights about farmlevel management decisions than NNP at specific 0.6 m 2 sampling locations. Existing literature describes a number of variables that influence N mineralization and denitrification rates; those cited most often include soil temperature (Stanford et al 1973(Stanford et al , 1975Curtin et al 2012), soil water content (Paul et al 2003;Heumann et al 2011) and soil TN (Vigil et al 2002). Other variables discussed in the literature include crop residue C:N ratio (Booth et al 2005;Patron et al 2007), soil organic matter (Booth et al 2005;Heumann et al 2014) and previous crop (Soon and Arshad 2002).…”

Field-specific simulations of net N mineralization based on digitally available soil and weather data: II. Pedotransfer functions for the pool sizes

“…2), whereas they were zero for T B 0°C. Specific, multiple temperature functions were derived in part I of this paper (Heumann et al 2011), yielding quite accurate simulations for in situ mineralization in undisturbed soil columns (r 2 = 0.87, P \ 0.001; RMSE = 23 kg N ha -1 ). The two criteria for classification of specific soil groups, soil texture (loess vs. sandy/loamy classes) and humus content class, can be taken from digital soil maps.…”

“…Paul et al 2003) and were derived in part I of this paper (Heumann et al 2011) for the range of soils studied. Here, just one criterion for grouping, soil texture (loess vs. sandy/loamy classes), was necessary (Heumann et al 2011). Further, no experimental evidence for significant interactions between temperature and soil water content were found, thus confirming Eq.…”

“…Recently, adequate field-specific parameterization of the temperature and water functions of a simple net N mineralization submodel was achieved by differentiating between not more than three soil groups according to digitally available soil data, i.e. soil texture and humus class (Heumann et al 2011). As the need for field-specific parameterization of N models also applies to pool sizes of mineralizable organic N (Kersebaum 2007), further experimental data and evaluations might be necessary.…”

“…informations on the previous crop. Employing also the above mentioned specific temperature and water functions (Heumann et al 2011), field-or even site-specific simulations of current net N mineralization could be obtained. The objective of this paper was to experimentally determine pedotransfer functions for the pool sizes of two organic N pools that (1) could be calculated via digitally mapped data, (2) need a minimum set of easily accessible management data, and (3) are applicable for a variety of different soil and site characteristics under winter wheat in NW-Germany.…”