Documentation - Field Crops
Content
Inputs
The field specific inputs regarding site conditions and yield are read from simulation period specific files src_in_2011.csv and src_in_2031.csv. These files contain values for each yield period within a simulation period. The files also contain the inputs for short rotation coppices which are used in this section. The spatial polygons from fields.geojson (with ETRS84-UTM32N projection) representing an arable field can be joined by the column beastid.
The csv table should contain biomass yields in tons dry mass per year.
The yields of the harvestings have to be preprocessed and are then used in BEAST via the input files. This opens the possiblity to vary the yields in steps of yield periods for representing non-linear growth development as well as, e.g., taking into account climate change effects. Busch & Thiele (2015) presented a method to develop and apply grwoth/yield simulation models for Lower Saxony, Germany.
The following table shows the structure of the input files (src_in_2011.csv and src_in_2031.csv).
| Column | Type | Unit | Description |
|---|---|---|---|
| beastid | Integer | - | ID of corresponding polygon |
| startyear | Integer | a | Start year of harvesting interval |
| area | Integer | ha | Spatial size of the field |
| slope | Integer | % | Slope of the field |
| adminId | Integer | - | ID of the administrative unit the field falls into |
| ecologicalId | Integer | - | ID of the ecological unit the field falls into |
| soilQualityIndex | Integer | - | Index value of the soil quality (German: Ackerkennzahl) |
| soilMoistureIndex | Integer | - | Index value of the soil moisture |
| rotation | Text | - | Field crop rotation (separated by "-", like: wheat-rape-barley) |
| birdProtectionArea | Boolean | - | Is the field located in a bird protection area |
| ffhArea | Boolean | - | Is the field located in a FFH (Natura 2000) protection area |
| floodingArea | Boolean | - | Is the field located in a flooding area |
| natureConservationArea | Boolean | - | Is the field located in a nature conservation area |
| regionSpecificProtectionArea | Boolean | - | Is the field located in a region specific protection area |
| waterProtectionArea | Boolean | - | Is the field located in a water protection area |
| bufferArea | Boolean | - | Is the field located in a buffer area |
| erosion | Integer | t/ha/a | Susceptibility to (water) erosion value |
| areaComplexity | Integer | h/ha * 10 | Index value of area complexity |
| percolationWater | Integer | mm/m^2/a | Rate of percolation water |
| landscapeDiversity | Integer | m/ha | Index value of landscape diversity |
| nitrateLeaching | Integer | t N/ha/a | Index value of nitrate leaching risk |
| wheat1 | Integer | dt/ha/a | Annual (potential) yield of wheat for the first decade of simulation period on the corresponding field |
| wheat2 | Integer | dt/ha/a | Annual (potential) yield of wheat for the second decade of simulation period on the corresponding field |
| sugarBeet1 | Integer | dt/ha/a | Annual (potential) yield of sugarbeet for the first decade of simulation period on the corresponding field |
| sugarBeet2 | Integer | dt/ha/a | Annual (potential) yield of sugarbeet for the second decade of simulation period on the corresponding field |
| barley1 | Integer | dt/ha/a | Annual (potential) yield of barley for the first decade of simulation period on the corresponding field |
| barley2 | Integer | dt/ha/a | Annual (potential) yield of barley for the second decade of simulation period on the corresponding field |
| rape1 | Integer | dt/ha/a | Annual (potential) yield of rape seed for the first decade of simulation period on the corresponding field |
| rape2 | Integer | dt/ha/a | Annual (potential) yield of rape seed for the second decade of simulation period on the corresponding field |
| maize1 | Integer | dt/ha/a | Annual (potential) yield of maize for the first decade of simulation period on the corresponding field |
| maize2 | Integer | dt/ha/a | Annual (potential) yield of maize for the second decade of simulation period on the corresponding field |
| src1 | Integer | dt/ha/a | Annual (potential) yield of short rotation coppice for the first 5-year harvesting interval of simulation period on the corresponding field |
| src2 | Integer | dt/ha/a | Annual (potential) yield of short rotation coppice for the second 5-year harvesting interval of simulation period on the corresponding field |
| src3 | Integer | dt/ha/a | Annual (potential) yield of short rotation coppice for the third 5-year harvesting interval of simulation period on the corresponding field |
| src4 | Integer | dt/ha/a | Annual (potential) yield of short rotation coppice for the fourth 5-year harvesting interval of simulation period on the corresponding field |
Parameters
Following parameters from parameters.xml are used for the field crops submodel (section srcParams; shared with SRC submodel):
| Name | Unit | Description |
|---|---|---|
| startyear | a | Start year of period the parameters are valid for |
| periodLength | a | Length of simulation step |
| yieldPeriodLength | a | Length of yield period |
| interestRate | % | Imputed interest rate |
| tAtro2MWh | MWh/tons (dry) | Conversion factor from tons (dry) to MWh |
Additional, following parameters are specified for each crop seperately (wheat, sugarbeet, barley, oilseed rape, and maize):
| Name | Unit | Description |
|---|---|---|
| areaPayment | EUR/ha/a | Annual payment per hectar |
| basePrice | EUR/dt | Basic price at the beginning of simulation period |
| priceChange | % | Annual price change in simulation period |
| baseVarCosts | EUR | Basic variable costs |
| baseLabourCosts | EUR | Basic labour costs |
| varCostsChange | % | Annual change of variable costs |
| labourCostsChange | % | Annual change of labour costs |
| varCostsYieldBeta1 | - | Parameter beta of variable costs equation |
| varCostsYieldReference | dt/ha/a | Reference yield for basic variable costs |
| labourCostsYieldBeta1 | - | Parameter beta of labour costs equation |
| labourCostsYieldReference | dt/ha/a | Reference yield for basic labour costs |
| labourCostsSlopeFactor | - | Factor in slope correction term of labour costs |
| labourCostsSlopeExponent | - | Exponent in slope correction term of labour costs |
| labourCostsAreaBeta1 | - | Parameter beta in area correction term of labour costs |
| labourCostsAreaReference | ha | Reference area for basic labour costs |
| meanBaseYield | dt/ha/a | Mean annual base yield |
| baseYieldPercent | % | Yield correction percentage |
| yieldChange | % | Annual yield change in simulation period |
Busch & Thiele (2015) presented a method to derive parameter values for Lower Saxony, Germany.
Processes
The simulation of crop yields and economic annuities is done as reference in comparison to short rotation coppices. The field crops are simulated as single crops as well as in crop rotation. The annuities of crop rotation is used to calculate the annuity diiference (see SRC submodel). Crop yield harvestings take place annually, therefore, within a 20 years simulation period 20 harvestings are executed.
The following calculations are processed for all field crops and every year in a loop:
First, a yield factor taking into account the yield niveau correction and the annual yield change is calculated:
$yieldFactor_t={baseYieldPercent \over 100} * ({1+{yieldChange \over 100}})^t$
with $t$ = distance in years from the beginning of the current simulation period
Next, prices for every year and crop are processed:
$price_t = basePrice * (1+{priceChange \over 100})^t$
Interecpts for yield correction functions of variable and labour costs are calculated as follows:
$varCostsIntercept=baseVarCosts-varCostsYieldBeta1*varCostsYieldReference$
$labourCostsIntercept=baseLabourCosts-labourCostsYieldBeta1$
$*labourCostsYieldReference$
The following steps are processed in a loop for all field polygons and crops:
First, the yield for every year is calculated based on the base yield (valid for 10 years) and corrected by the yield factor ($cropYield$ is replaced by the name of the crop and its value is take from input file):
$yield_t = cropYield_r*yieldFactor_t$
with $r=\begin{cases} {1} & \quad \text{, } 0 \leq t \lt 10\\ {2} & \quad \text{, } t \geq 10\\ \end{cases}$
Now, variable and labour costs are calculated for every year, because they depend on the (potentially) yearly changing yield:
$labourCostsSlopCorrection=1+(labourCostsSlopeFactor*e^{(labourCostsSlopeExponent*slope)})$
$labourCostsAreaCorrection={{area^{labourCostsAreaBeta1}} \over {labourCostsAreaReference^{labourCostsAreaBeta1}}}$
$varCosts_t=varCostsIntercept+varCostsYieldBeta1*yield_t$
$labourCosts_t=(labourCostsIntercept+labourCostsYieldBeta1*yield_t)*$
$labourCostsSlopCorrection*labourCostsAreaCorrection$
$varCosts_t=varCosts_t*(1+{varCostsChange \over 100})^t$
$labourCosts_t=labourCosts_t*(1+{labourCostsChange \over 100})^t$
Now, the annual contribution margin for every year of the simulation period can be calculated:
$cm_t=price_t*yield_t-varCosts_t-labourCosts_t$
Next, the contribution margins are discounted to the beginning of the simulation period. i.e. the net present values are calculated:
$cm_{discount_t}={{cm_t+areaPayment} \over {(1+{interestRate \over 100})^t}}$
Then, they are summed up to total net present value:
$netPresentValue = \sum_{t=0}^{periodLength-1} cm_{discount_t}$
Lastly, the total net present value is transformed into an annual annuity:
$annuity = \begin{cases} {netPresentValue * {{i^{(periodLength-1)} * (i - 1)} \over {i^{periodLength} - 1}}} & \quad \text{, if } interestRate > 0\\ {netPresentValue \over periodLength} & \quad \text{, else}\\ \end{cases} $
with $i = 1 + {interestRate \over 100}$
Here, the loop over the crops ends.
Now, the results from single crops are used to calculate an averaged annuity for the crop rotation:
$cropRotationAnnuity={{\sum_{f=0}^{ff} annuity_f} \over ff}$
with $ff$=Number of crops in rotation; $f$=Index of crop in rotation
References
Busch G., Thiele J.C. (2015) The Bioenergy Allocation and Scenario Tool (BEAST) to Assess Options for the Siting of Short Roation Coppice in Agricultural Landscapes: Tool Development and Case Study Results from the Göttingen District. In: D. Butler Manning, A. Bemmann, M. Bredemeier, N. Lamersdorf, C. Ammer (eds.): Bioenergy from Dendromass for the Sustainable Development of Rural Areas. Wiley-VCH, pp. 23-43.