DOI: 10.21421/d2/c0h1jl
title: Dataset of APSIM simulations estimating the ecosystem service impacts of alternative management practices in Maharashtra/India

description: The data were created in the GIZ funded project ‘Advancing Knowledge on the Costs and Benefits of Sustainable Soil Fertility Management in Maharashtra, India’. The objective of this project was to study the impact of cropping systems and soil fertility management practices on select ecosystem services. The study sites were Bhokardan (Jalna district), Sakri (Dhule district), Parner (Ahmednagar district), Morshi (Amravati district), and the Asoli Atmurdi and Devdhari clusters in Yavatmal. The Agricultural Production Systems sIMulator (APSIM) package was used to conduct crop model simulations. The major components of these models were vegetative and reproductive development, carbon, water, and nitrogen balance. The models simulated crop growth and development using a daily time step from sowing to maturity and ultimately predicted yield. Genotypic differences in growth, development, and yield of crop cultivars are affected through genetic coefficients (cultivar-specific parameters) that were input into the model in addition to crop-specific coefficients that were considered less changeable or more conservative in nature across crop cultivars. The physiological processes that were simulated describe the crop response to major weather factors, including temperature, precipitation, and solar radiation and include the effect of soil characteristics on water availability for crop growth. The soil water balance was a function of precipitation, irrigation, runoff from the soil surface, soil evaporation, transpiration and drainage from the bottom of the soil profile. Daily surface runoff of water was calculated using the U.S. Department of Agriculture (USDA) Soil Conservation Service curve number technique (Soil Conservation Service 1972). To compute soil water drainage, the model used a ‘tipping bucket’ approach when a layer’s water content is above a drained upper limit (DUL). In the model, high-temperature influences growth and development and the allocation of assimilates to the reproductive organs was reduced by decreased pod set and seed growth rate. The model’s prediction of elevated temperature effects on pod yield was tested and shown to be accurate against elevated temperature data. Increased CO2 concentrations in the atmosphere increased crop growth through increased leaf-level photosynthesis, which responds to CO2 concentration. The models need extensive parameterization and calibration before they can be put to use. We used AICRP (All India Coordinated Research project, ICAR) trial data to calibrate the simulation models. Long term trends in observed seasonal precipitation and temperature over Maharashtra were analyzed using IMD along with AgMERRA gridded rainfall and temperature at daily time scales to arrive at current baseline climatology for the time period 1980-2009 (30 years). For the purpose of modeling the study districts were cut into 90 girds of 200 km resolution. For each modeled grid cell, soil inputs to the model were obtained from a set of 90 soil profiles developed by blending and interpreting information from crop modeling studies conducted in India in various location and WISE database (Batjes 2009). We also used the soil profile datasets developed by NBSSLUP for Maharashtra. Simulations were run for all soils in each grid cell, and cell-specific output was computed from the area-weighted average based on the area share of each soil in the grid cell. We adopted the automatic planting procedure available in APSIM. The planting event of rainfed crops was triggered whenever cumulative rainfall after the onset of monsoon reached 50 mm. Other crop management practices were obtained from the survey data collected from the farmers in the study region. We identified location-specific fundamental classes of projected climate change. We characterized an individual model’s projected, location-specific temperature and precipitation changes in terms of its deviation from the ensemble median. Accordingly, we identified five individual GCMs that capture a profile of the full ensemble of temperature and precipitation changes with the annual season to select the five climate models out of 29 GCMs. A scatter plot was generated to represent climate models with their magnitude of future change. The scatter plot represents cool/wet, hot/wet, cool/dry and hot/dry models relative to the median of the model spread. This study simulated the impact of the hot dry and cool wet scenarios which are closest to the median. Both scenarios are warmer compared to the baseline, with the hot dry being hotter than the cool wet one. The precipitation of the hot dry scenario is only slightly above the baseline. It is significantly higher under the cool wet scenario.