To estimate initial soil water content for crop simulations, the implemented approach is to start a pseudo crop simulation starting with a full soil moisture profile long before the actual crop simulation. Using this approach, recharge of the soil moisture by rainfall and water use of the pseudo crop will help to find a more representative estimate of the soil moisture level when the actual crop simulation for the year of interest starts.
The pseudo crop simulation has been implemented by a simplified model which only implements leaf area index dynamics, root growth and evapotranspiration. For root growth and evapotranspiration modules from WOFOST were taken and parameterized for a typical cereal crop. The leaf dynamics are described by the Canopy Structural Development Model (CSDM, Koetz et al., 2005) which describes LAI growth and senescence by a combination of a logistic and exponential curve. The difference with the original CSDM is that the pseudo crop uses the day number as its internal state to calculate LAI, while in the original version a temperature accumulation is used. Finally, a loose coupling to the soil water balance has been established which allows switching the crop simulation on and off while still keeping the integrity of the soil moisture balance intact. At the end of the pseudo crop run, the amount of available soil moisture is updated in the SOIL_INITIAL_WATER table (WAV parameter). Thereafter, the BIOMA crop simulation is run, using more realistic initial soil water content.
The ISW is developed in python. To be able to run the package in parallel, it is connected to a tasks administration system that should be configured before estimating initial soil water content. Each instance of ISW picks up a pending task. Once picked up, it cannot be handled by another instance. Together all instances handle the pending tasks one by one until all tasks of the task list are finished. The tasks can be created by the COPdate package as in the operational production line for the RUK window, or inserted during a manual set-up as in the operational production line for the EUR window.
The ISW is built using components already available in the python implementation of WOFOST (PCSE). Below figure shows the relationships between the components in the ISW. At the highest level is the ISW interface, which arranges some administrative matter and exposes its interface. Within ISW, the SoilCropSimulation object takes care of the actual simulation loop by making the appropriate calls to the Timer, AgroManagement, FakeCropSimulation and WaterbalanceFD routines. This includes the initialisation step, the calculation of rate variables, integration of states and the finalisation step.
Required objects inside the oracle schema where the ISW is applied (e.g. CGMS14RUK):
The implementation of the ISW consists for four components:
- The soil water balance which is an exact implementation of the CGMS/WOFOST soil water balance for free drainage conditions.
- The root dynamics module which simulates linear root growth up to a maximum depth as is done by CGMS/WOFOST.
- The soil evaporation and crop transpiration as is done by CGMS/WOFOST with a reduction in transpiration based on the soil moisture content and the drought sensitivity of the crop.
- The leaf dynamics module which is based on prescribed LAI trajectory based on the Canopy Structural Development Model (Koetz et al., 2005). A consequence of using a fixed LAI trajectory is that there is no leaf death as a result of moisture stress which is simulated by WOFOST.
Given that the first three components are identical to the WOFOST components, we refer to the WOFOST documentation. The Canopy Structural Development Model (CSDM) is used to define a fixed LAI trajectory based on combination of a logistic function to describe the increasing part of the LAI trajectory, and an exponential function describing the decreasing part of the LAI trajectory. The difference with the original CSDM is that in our implementation the thermal time as driving variable has been replace with the day number. This way we could easily define a fixed length growing season without any calibration of thermal time. Our implementation of the CSDM is the following:
Where LAIt is green leaf area index on day number t, the latter is the day number counted since the start of the CSMD model. See the figure below for an example of the LAI trajectory simulated by the CSDM. We have chosen for a relatively low maximum LAI in the model assuming relatively extensive crop managements which leads to relatively thin canopy cover. Moreover, a very high LAI would lead to high water extraction which would be unrealistic given general yield levels in Russia and Kazakhstan.
Parameters used for the CSDM model (see equation above) and there representation in the model code of the ISW.
|CSDMmin||CSDM_MIN||Minimum LAI at the start||0.15||-|
|CSDMmax||CSDM_MAX||Amplitude of LAI, roughly the maximum value of LAI||4||-|
|A||CSDM_A||Shape parameter in the exponential model||0.085||-|
|B||CSDM_B||Shape parameter in the logistic model||0.045||-|
|t1||CSDM_T1||Time of maximum increase of logistic model||40||Days|
|t2||CSDM_T2||Total length of the growing season (LAI=0)||120||Days|
Other parameters used for the ISW. These values are taken from a spring-wheat crop and are hardcoded in the model.
|KDIF||Extinction coefficient for diffuse visible light||0.6||-|
|CFET||Correction factor evapotranspiration||1.0||-|
|DEPNR||Crop group number for soil water depletion||4.5||-|
|RDI||Initial rooting depth||10||cm|
|RRI||Maximum daily increase in rooting depth||1.2||cm|
|RDMCR||Maximum rooting depth of crop||120||cm|
- add -