Estimating potential yield of wheat production in china based on cross-scale data-model fusion

Abstract

The response of the agro-ecological system to the environment includes the response of individual crop's physiological process and the adaption of the crop community to the environment and its change. Observation and simulation at the single scale level cannot fully explain the above process. It is necessary to develop cross-scale agro-ecological models and study the interaction of agro-ecological processes across different scales. Two typical agro-ecological models (DSSA T and AEZ) are employed in this study and a framework for effective cross-scale data-model and model-model fusion is proposed and illustrated based on the application of DSSAT and AEZ models. The site-specific crop model is up-scaled by using this data-model fusion method, observed data from 36 different agricultural observation stations nationwide and historical weather stations observations (1962-1990) are employed and average crop productivity are estimated.Comparison of the estimation results shows the major consistency across the two models and also indicates specific directions for further improvement. This would help the future efforts in cross-scale crop model fusion.

Analysis of Agricultural Production Potential and Enhancement Strategy in the Qaidam Basin Based on the Agro-Ecological Zone Method

“…These models can be divided into two main categories: process-based crop growth dynamics and agro-ecological productivity models (Tian et al, 2012). Process-based crop models, such as the decision-support system for agro-technology transfer model, simulate processes that occur during the crop growth cycle after parameter calibration using multi-year site-level observations (Zhan et al, 2014). Such models simulate dynamic biophysiological processes occurring during the crop growth cycle in a day-by-day stepwise manner and have been applied to assess crop yield responses to climate change, crop varieties and management (Huang et al, 2009;Xiong et al, 2009).…”

“…Even if the model simulation parameters have been determined, the model performance can be severely affected by altered sowing dates and seasonal changes (Wang J. et al, 2012). Furthermore, parameters often vary over large areas within the same region, and it is almost impossible for researchers to fully understand the variation among parameters; therefore, the model often produces problematic results when used for crop simulations over large areas (Butt et al, 2005;Zhan et al, 2014). In contrast, agro-ecological productivity models such as the agro-ecological zone (AEZ) model use simple and reliable crop models involving standardised calculations to derive crop production potential by determining the limitations imposed by climatic factors on crops (Fischer et al, 2012).…”