Modeling Climate Change Impacts on Rice Growth and Yield under Global Warming of 1.5 and 2.0 °C in the Pearl River Delta, China

Abstract

In this study, the potential climate change impacts on rice growth and rice yield under 1.5 and 2.0 °C warming scenarios, respectively, are simulated using the Ceres-Rice Model based on high-quality, agricultural, experimental, meteorological and soil data, and the incorporation of future climate data generated by four Global Climate Models (GCMs) in the Pearl River Delta, China. The climatic data is extracted from four Global Climate Models (GCMs) namely: The Community Atmosphere Model 4 (CAM4), The European Centre for Medium-Range Weather Forecasts-Hamburg 6 (ECHAM6), Model for Interdisciplinary Research On Climate 5 (MIROC5) and the Norwegian Earth System Model 1 (NorESM1). The modeling results show that climate change has major negative impacts on both rice growth and rice yields at all study sites. More specifically, the average of flowering durations decreases by 2.8 days (3.9 days), and the maturity date decreases by 11.0 days (14.7 days) under the 1.5 °C and (2.0 °C) warming scenarios, respectively. The yield for early mature rice and late mature rice are reduced by 292.5 kg/ha (558.9 kg/ha) and 151.8 kg/ha (380.0 kg/ha) under the 1.5 °C (2.0 °C) warming scenarios, respectively. Adjusting the planting dates of eight days later and 15 days earlier for early mature rice and late mature rice are simulated to be adaptively effective, respectively. The simulated optimum fertilizer amount is about 240 kg/ha, with different industrial fertilizer and organic matter being applied.

Effects of long-term high-temperature stress on reproductive growth and seed development in development inBrassica napus

“…Severe weather incidents analysed for the period 1964-2007 were shown to profoundly affect crop harvest worldwide due to drought and heat (Lesk et al ., 2016). This has been reported in rice (Peng et al, 2004; Guo et al , 2019), maize (Liu et al , 2020), wheat (Liu et al , 2016), soybean (Zhao et al , 2017), tomato (Singh et al , 2017), and cotton (Singh et al , 2007). Predicted increase of temperatures in the future will deepen problems with crop yield (Zhao et al, 2017), which encourages scientific efforts in the production of thermotolerant (or stress-tolerant) cultivars.…”

Comparison of Multi-Methods for Identifying Maize Phenology Using PhenoCams

“…However, field observation is time consuming and labor intensive and there is lack of recording of the continuous phenological developments during the long-term growth cycle under a standard procedure [31]. Alternatively, a crop model such as CERES-maize can be conducted to simulate the daily dynamic growth of crops with high accuracy, but most models relay on highly resolved data, including daily precipitation, temperature, soil property, management practices and crop cultivars [32][33][34][35][36]. Besides, models can hardly handle extreme events, as the in-built mechanisms have no consideration of those scenarios [37,38].…”

Evaluating the Sensitivity of Growing Degree Days as an Agro-Climatic Indicator of the Climate Change Impact: A Case Study of the Russian Far East

“…Secondly, to quantify climate changes caused by CO 2 and other trace gases, physical methods using numerous global climate models, such as three-dimensional general circulation models under different emissions scenarios, are applied to construct climate scenarios [8,45,[72][73][74][75][76]. Their main disadvantage is based on the ultra-complicated and complex character of the actual climate system and the inherent inability to construct a model that can be its perfect copy [8].…”

“…A popular approach is to modify the climatic input data to a model by regular increments above or below the baseline values, e.g., at intervals of 1 • C for temperatures, and (or) 10% for precipitation, and to examine responses of an exposure unit to these changes using linear shifts in the "long-term average" scenario [8,12]. For example, modest arbitrary changes in temperatures of +0.5, +1.0 and +1.5 • C were adopted to simulate situations of hypothetical regional warming, representing conditions intermediate between the present and 2 × CO 2 climates [11,76,77].…”

“…With the above in mind, synthetic scenarios are a useful tool to suggest the magnitude of future spatial and temporal climatic changes at a regional scope [8,[10][11][12]24,57,76,77]. Three warming scenarios +1, +2 and +3 • C are suggested for application, as they represent simulations of temperature changes in the regions under different emission scenarios based on the consensus of the World Climate Research Programme Coupled Model Intercomparison Project [1][2][3][4][5][72][73][74][75][76][78][79][80][81][82].…”