APSIM Model Configuration

The APSIM model was configured or parameterised for field experimental soil, water and crop management (i.e. soil profile, and tillage practices with different mulch levels) and climate conditions, as described below. APSIM version 7.5 r 3008 was used to simulate the tillage/surface water management practices and varying mulch level effects on soil-water dynamics and maize growth. The model requires daily minimum and maximum temperature, daily mean precipitation and solar radiation

Chapter III: Impacts of Climate-Smart Practices on the Climate Resilience of the Limpopo Smallholder Farmers in Diverse Landscapes

were obtained from an on-farm automatic weather station, managed and quality controlled by Agricultural Research Council in South Africa. The missing records, owing to short period of operation length (less than 8 years, 3 January 2008 to date) and maintenance, were patched using an approach described by Warburton et al. (2012) for selection of a representative nearby stations with a reliable record and altitude (and mean annual precipitation) of the station similar to target station location.

The data used in the configuration of the model was soil physical parameters (Table 3.4 and Table 3.5), including layer-based bulk density, saturated water content, soil, and water at field capacity and wilting point. The simulations were initiated using the soil parameters outlined in Table 3.4 for a 0.7 m soil profile depth. The field management operations were input as part of the simulation treatments, i.e. uniform band place of nitrogen at planting and after 6 weeks, tillage practices, and mulch levels near flowering. Further, the simulation initialisation dates were set using dates shown in Table 3.1.

The initial plant available water (PAW) was set at 60 mm for Experiment 1 on the first cropping season and 27 mm for the second cropping season; while for Experiment 2 - 4 the initial soil-water was set at 100 %, to correspond with maize trial planting times over the cropping season.

Table 3.4 Soil-water holding capacity properties of the Syferkuil Research Farm, and the values used in specifying the APSIM model simulation at initialisation of cropping season

Layer number 1 2 3 4 5

* Data obtained from study by Whitbread and Ayisi (2004) at the same location,

a Air dry at depth of 60 cm that the sequence would be 50%, 70%, 90%, and then 100% of crop lower limit f or the remainder of the profile

The experiment was established each growing season at the same location. The drained upper limit (DUL), saturation (SAT), lower limit (LL) were derived from soil-water measurements made in the conventional tillage treatments. A sowing depth of 30 mm was used in the simulation in each tillage system. The average plant stand was 2.2 plants per m-2 and 1 m spacing for both growing seasons.

All treatments were kept weed free over the duration of the experiment.

3.2.3.1. Soil-water infiltration and movement module calibration

The soil-water (and solute) dynamics within the soil profile for a specific agricultural system were simulated in the APSIM environment through the soil-water infiltration and movement (SWIM3) model platform. Most of the soil parameters in this platform have been calibrated and used in semi-arid southern Africa region for various studies (Mupangwa et al, 2011). The main soil-water parameters considered in the calibration of the CT, NT and IRWH tillage practices were the volumetric water content, (LL), saturation (SAT), drained upper limit (DUL), bulk density (BD), and MSWCON or saturated hydraulic conductivity (Ks) at different soil layers, and surface pond (max_pond).

The tillage practices, particularly NT and IRWH, have a direct effect on mechanisms of lateral flow, infiltration, storage, runoff, redistribution and residence times, this was reported in studies by Kosgei et al. (2007) and Salem et al. (2015). To capture these soil-water movements through soil profile in the APSIM model for NT practice, NT specified in the model‘s crop management and soil water module, based on the above mentioned calibration parameters. These soil physical parameters required in APSIM calibration to simulate specific tillage practices were obtained from field observations and derivation based on observed soil properties from literature.

The SAT, DUL and LL values were used to describe the soil-water retention, while lateral soil-water outflow was described by the are slope and the lateral resistance (KLAT), the infiltration down the soil profile by the above saturation flow (i.e. MWCON or Ks values) were set as indicated in Table 3.6, to allow soil-water flow down profile when the soil-water rises above the saturation..

Table 3.6 Soil-water infiltration and movement calibration parameters used

Layer number Tillage 1 2 3 4 5

To simulate IRWH as a two-dimensional and distributed mode, with zero-till runoff generation and a Province collection area in SWIM3, an approach presented in Figure 3.1 was adopted. This approach is able to utilise the current one-dimensional and lumped mode SWIM3 parameters to represent a two-dimensional surface. The IRWH complex runoff generation and Province rainwater collection were simulated in two parts or model runs (cf. Figure 3.1). The model runs were interlinked through cascading process, based on the assumption that all soil-water outflows (i.e. surface runoff and subsurface lateral outflows) from the zero tillage runoff generation soil profile flows, at a slope less than 2 %, flows into the runoff collection Province profile. The maize crop is only planted on the runoff collection Province soil profile. This IRWH conceptual system of one runoff generation flowing into planted runoff collection areas was adopted from the PARCHED-THIRST model (Mzirai et al., 2004;

Mzirai and Tumbo, 2010). The represent the runoff collection Province in the field, the max_pond functionality (based on the Province dimensions) together with MWCON as indicated in Table 3.6 were used.

The main limitation in using APSIM model in simulating complex surface management system is in the process of multiple modelling runs requiring more detailed soil physics parameterisation. We attempted to perform such analyses using low data and relayed on other research literature to be able to mimic as close as possible the observations in the field experiments. The limitations of only having a tipping bucket soil-water module in APSIM model has implications on the simulations soil-water

Chapter III: Impacts of Climate-Smart Practices on the Climate Resilience of the Limpopo Smallholder Farmers in Diverse Landscapes

dynamics of complex systems, such as insitu-rainwater harvesting. This includes the inability of the model to simulate runon-runoff, and lateral flow based on natural soil layer breaks.

Figure 3.1 A crosssectional schematic of the insitu rainwater harvesting simulation as performed in the APSIM model