disaggregation_of_nitrogen_input
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disaggregation_of_nitrogen_input [2020/03/29 08:26] – created matsz | disaggregation_of_nitrogen_input [2020/03/30 07:06] – [Crop growth scaling factor] matsz | ||
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====Crop response curve==== | ====Crop response curve==== | ||
+ | |||
+ | Different crop response curves are proposed (Bodirsky and Müller, 2014; Godard et al., 2008). We base our response curve on the proposal of (Godard et al., 2008) in particular for the ‘saturation’ velocity(( | ||
+ | |||
+ | \begin{align} | ||
+ | \begin{split} | ||
+ | & | ||
+ | & | ||
+ | \end{split} | ||
+ | \end{align} | ||
+ | |||
+ | \begin{align} | ||
+ | \begin{split} | ||
+ | & | ||
+ | & | ||
+ | \end{split} | ||
+ | \end{align} | ||
+ | |||
+ | \(Y_{r, | ||
+ | \(Y_{r, | ||
+ | \(Y_{r, | ||
+ | \(f^{cropcurve}\) = Scaling factor [parameter, dimensionless] used in the crop response curve (Godard et al., 2008). We use a uniform value of \(f^{cropcurve}=0.008\). \\ | ||
+ | \(Q_{r, | ||
+ | |||
+ | ====Crop growth scaling factor==== | ||
+ | |||
+ | We use a constant factor \(f^{cropcurve}\) for all regions/ | ||
+ | |||
+ | * For \(f^{cropcurve}> | ||
+ | * For \(f^{cropcurve}< | ||
+ | |||
+ | Therefore, only a narrow range around a value of 0.008 seems plausible. | ||
+ | |||
+ | **Figure 44: Crop growth curves according to Godard et al. (2008) for different crop growth scaling factors.** | ||
+ | |||
+ | {{:: | ||
+ | |||
+ | **Figure 45: N input rates that give a yield of 80% of the maximum yield for different crop growth scaling factors according to Godard et al. (2008)** | ||
+ | {{: | ||
+ | |||
+ | **Lower efficiency for manure application** | ||
+ | |||
+ | We assume that manure is applied with less efficiency than mineral fertilizer. First, because we take into account lower nutrient availability in manure with respect to mineral fertilizer (due to reduced opportunity to target release of nutrients to crop demand, thus increasing the chance of nutrient releases in periods with enhanced risks of losses to the environment). Second, due to the fact that higher availability of manure often goes ahead with increased lack of surface where the manure can be applied in a reasonable manner. | ||
+ | |||
+ | Therefore, we assume a decrease of the NUE the higher the share of manure in the fertilizer mix. | ||
+ | |||
+ | We account for this fact by using a different crop response curve for mineral fertilizer and manure. This is realized by varying the theoretical crop curve’s maximum yield. | ||
+ | |||
+ | This is shown in figure below. | ||
+ | |||
+ | **Figure 46: Examples of crop response curves according to Godard et al. (2008).** | ||
+ | |||
+ | {{: | ||
+ | |||
+ | We introduce a dependency of y< | ||
+ | |||
+ | \begin{align} | ||
+ | \begin{split} | ||
+ | y_{h, | ||
+ | χ_{man, | ||
+ | \end{split} | ||
+ | \end{align} | ||
+ | |||
+ | \(y_{h, | ||
+ | \(y_{man, | ||
+ | \(y_{min, | ||
+ | \(χ_{man, | ||
+ | |||
+ | ===Manure availability=== | ||
+ | |||
+ | Manure can be traded between individual spatial units. Manure trade between regions (or even countries) is covered by the regional model of CAPRI and does not need to be considered here. | ||
+ | |||
+ | The availability of manure is obtained therefore from each spatial unit plus neighboring spatial units within the same region. The range of spatial units from which manure can be used is assumed to a region-specific variable and | ||
+ | |||
+ | \begin{align} | ||
+ | \begin{split} | ||
+ | \sum_{c} \{ q_{man, | ||
+ | d_{h, | ||
+ | \end{split} | ||
+ | \end{align} | ||
+ | |||
+ | \(q_{man, | ||
+ | \(a_{h, | ||
+ | \(e_{man, | ||
+ | \(n_{h, | ||
+ | \(d_{h, | ||
+ | \(D_r^{mx}\) = Maximum distance [variable, km] for which transport of manure is allowed in region //r//. \\ | ||
+ | |||
+ | Obviously, the total manure available for application must be exhausted: | ||
+ | |||
+ | \begin{equation} | ||
+ | \sum_{h, | ||
+ | \end{equation} | ||
+ | |||
+ | ====Fertilization distribution model==== | ||
+ | |||
+ | ===Recover regional N flows=== | ||
+ | |||
+ | For each flow of nitrogen and crop, the sum of flows over all spatial units must recover the total flow at regional level for each crop. | ||
+ | |||
+ | This holds both for input flows and output flows (i.e. harvest, surplus). | ||
+ | |||
+ | ===Potential yield=== | ||
+ | |||
+ | The maximum (potential) yield is proportional to the relative potential yield (without water limitation). | ||
+ | |||
+ | \begin{equation} | ||
+ | y_{h, | ||
+ | \end{equation} | ||
+ | |||
+ | \(y_{h, | ||
+ | \(r_{h, | ||
+ | \(F_{r, | ||
+ | |||
+ | ===Crop growth curve=== | ||
+ | |||
+ | Total input of nitrogen is obtained from the observed yield for the crop in the spatial unit (parameter, calculated in the yield and irrigation module) and the maximum yield obtainable in the crop in the spatial unit (variable). | ||
+ | |||
+ | \begin{equation} | ||
+ | q_{h,c} = -\frac{1}{x}\cdot ln \left\{ \frac{y_{h, | ||
+ | \end{equation} | ||
+ | |||
+ | ===Nitrogen source=== | ||
+ | |||
+ | Once the total N input per crop and spatial unit is determined, the individual N sources need to be calculated. We have: | ||
+ | * Biological N fixation: this is directly calculated from the crop type and yield and is ‘fixed’ | ||
+ | * Atmospheric deposition: this is obtained from external data and cannot be modified | ||
+ | * Mineralization of soil organic matter. We have no data yet for calculating mineralization of soil organic matter at the regional level, thus it is not possible to include this term in the disaggregation. If there were data on soil organic mineralization, | ||
+ | * Mineralization of soil organic matter occurs in extensive fields, thus at low application rates of mineral fertilizer and irrigation rates | ||
+ | * Manure is able to replenish soil organic matter. It is thus unlikely that mineralization of soil organic matter occurs where manure is applied or deposited by grazing animals. | ||
+ | |||
+ | ====Data preparation==== | ||
+ | |||
+ | ===Collecting information=== | ||
+ | |||
+ | At Nuts2 level, //y// and //f// are known and y< | ||
+ | |||
+ | \begin{equation} | ||
+ | y_{r, | ||
+ | \end{equation} | ||
+ | |||
+ | For each spatial unit, the yield is given from the distribution of irrigation shares and yield. | ||
+ | |||
+ | We can assume that the potential yield y< | ||
+ | |||
+ | \begin{equation} | ||
+ | y_{h, | ||
+ | \end{equation} | ||
+ | |||
+ | \(r_{h, | ||
+ | |||
+ | === Calculation of relative potential yield per spatial unit === | ||
+ | |||
+ | \begin{equation} | ||
+ | r_{h, | ||
+ | \end{equation} | ||
+ | |||
+ | \(r_{h, | ||
+ | \(\overline{y_{h, | ||
+ | |||
+ | \begin{equation} | ||
+ | \overline{y_{h, | ||
+ | \end{equation} | ||
+ | |||
+ | ===Calculation of distances between HSUs=== | ||
+ | |||
+ | Update pending | ||
+ | |||
+ | ===Calculation of manure availability=== | ||
+ | |||
+ | Excretion net of all volatilization must be back-calculated so that emissions from applications are not subtracted. | ||
+ | |||
+ | Update pending | ||
+ | |||
+ | ===Consideration of mitigation options=== | ||
+ | |||
+ | Update pending | ||
disaggregation_of_nitrogen_input.txt · Last modified: 2022/11/07 10:23 by 127.0.0.1