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Prediction of Changing Climatic Effect and Risk Management by Using Simulation Approaches for Rice-wheat System in Bangladesh

M. K. HASAN
Chief Scientific Officer
Agricultural Statistics and ICT Division, Bangladesh Agricultural Research Institute (BARI), Gazipur-1701

S. AKHTER
Principal Scientific Officer
Soil Science Division, BARI, Gazipur-1701

M. A. H. CHOWDHURY
Former Director (Computer and GIS)
Bangladesh Agricultural Research Council (BARC), Dhaka-1215

A. K. CHAKI
Scientific Officer
On-Farm Research Division, BARI, Gazipur-1701

M. R. A. CHAWDHERY
Former Research Fellow
AgMIPIGB Project, Bangladesh Component, BARC, Dhaka-1215, Bangladesh.

T. ZAHAN
Chief Scientific Officer
Agricultural Statistics and ICT Division, Bangladesh Agricultural Research Institute (BARI), Gazipur-1701

Abstract/ Executive Summary:

A study was carried out on the impact of climate change in rice-wheat systems on farmers’ livelihood in Dinajpur region of Bangladesh to evaluate the usefulness of the implication of simulation approaches to predict climate change effect and to manage risk for this cropping system. Trade-off analysis for multidimensional impact assessment (TOA-MD) model was used in the study with a combination of simulated baseline production and future simulated yield using Decision Support Systems for Agro-technology Transfer (DSSAT) and Agricultural Production Systems SIMulator (APSIM) in rice and wheat production system. Five different climate scenarios of Global Circulation Models (GCMs) were considered. The projections showed to have a negative economic impact between 50 and 82% for the difference in the magnitude and in the impact of different GCMs which was not possible to overcome. The survey revealed that northwest region of Bangladesh is likely to be affected by climate change and has high levels of vulnerability due to limited access to alternative livelihood activities other than farming. Simulation results showed no additional economic gain from wheat cultivation under changed climatic conditions, but increased economic profit was obtained from rice cultivation due to increased productivity trend. Therefore, study suggests an adaptation package of 50 mm additional irrigation water for wheat cultivation that could be an appropriate strategy to mitigate climate change risk in wheat cultivation. This practice had a positive impact on projected per capita income gains of about 2.05%in the study area and reduced poverty rate by about 1.99%. The study also revealed that prediction of the APSIM model for adaptation impact of climate change on economic return and per capita income of farmers was superior to DSSAT model.

Keywords: Climate change, Crop modeling, Simulation, Risk management.

Location: Dinajpur district, Bangladesh

Start Date:

End Date:

Program Area: Risk Management in Agriculture

Commodity: Climate change, Data collection and collation, Cropping System

Objectives:

To assess the impacts of climate change in rice-wheat system by generating reasonable estimates and also to project future climatic effect for risk management.

Methodology:

Location and farming system: Dinajpur district was considered as the study area which is situated at the northwest part of Bangladesh located in between 25°22' and 26°06´ north latitudes and in between 89°31´ and 88°38´ east longitudes. The total area of this district is 3,437.98 km². Rice-wheat is the dominant cropping system that occupies a major portion of that region (Sarker et al., 2014). The annual average highest temperature of Dinajpur district was 33.5 °C and the lowest was 10.5°C with an annual rainfall of 2536 mm. Soil profile-wise data were compiled from different Reconnaissance Soil Survey Reports (SRDI, 2016). A total of 45 different soil series profiles (i.e., AGMIP13001, AGMIP13002 to AGMIP13045) were created as input for DSSAT and APSIM models. The area coverage of rice and wheat in Dinajpur district is 0.77 million and 0.023 million hectares; and production is 2.42 million and 0.072 million tonnes, respectively (BBS, 2017). Double cropped Rice-Wheat system is dominant in that region which covers about 67% of total area. Representative Agricultural Pathways (RAPs): The Representative Agricultural Pathways (RAPs) is an overall narrative description of a plausible future development pathway that contains key variables with qualitative storylines and quantitative trends, consistent with higher-level pathways (Valdivia and Antle, 2014). These scenarios represent a set of technology and management of adaptations to climate change. A day-long workshop was organized to develop RAPs and reviewed the current and future changes in agricultural practices and in socio-economic aspects regarding of climate change. Forty-three participants from National Agricultural Research System (NARS) Institutes, Bangladesh Meteorological Department (BMD) and civil society were participated in the workshop. After threadbare discussion final version of the RAPs was adopted. The finalized RAPs during the workshop were used for TOA-MD analysis. This helped to answer three core questions as selected by AgMIP for Integrated Regional Assessment. The questions were the following: 1. What is the sensitivity of current agricultural production systems to climate change? 2. What is the impact of climate change on future agricultural production systems? 3. What are the benefits of climate change adaptations?. Climate and climate projections Daily agrometeorological data (daily maximum and minimum temperature, daily sunshine hour, etc.) of historical time series (1980-2009) were collected from BMD. Since the model requires solar radiation data (MJ/m² /day), bright sunshine data were converted to solar radiation based on Allen et al. (1998). To assess the impact of future climate scenarios and to make inter-comparisons between APSIM and DSSAT for rice and wheat, yield performance at base 30 years weather was compared with 30 years of future climate scenarios. This was carried out using six sets of climate data, one (OXXX) for current climate and the other five (IEXA, IIXA, IKXA, IOXA, IRXA) scenarios with elevated CO₂ at 571 ppm. Besides the observed (OXXX) climate of 30 years (1980-2009), twenty GCMs data were generated using the AgMIP Climate Scenario Generation Tools with R (ACSGTR 2.1) for RCP 8.5 (2040-2069 time period; Mid-Century). Five other climate data sets (GCM-based climate change scenarios using mean-only delta scenarios) namely-IEXA, IIXA, IKXA, IOXA, IRXA for the median future scenarios were chosen for conducting the crop simulation runs. Where, the first letter stands for RCP 8.5 (2040-2069 time period; Mid-Century); E=CCSM4, I=GFDL-ESM2M, K=HadGEM2-ES, O=MIROC5, R=MPI-ESMMR and type of scenario: X=Observations (no scenario) and A=Mean change from GCM. Household survey: For integrated assessment through household survey was also carried out during May-September 2013 to collect data from randomly selected 50 farms from four Upazilas (sub-districts) of Dinajpur district to cover the major cropping pattern i.e. Rice (transplanted in rainy season) - Wheat (sowing in winter season) pattern. A pre-designed questionnaire was used in this purpose. Crop-model calibration (DSSAT and APSIM): Although the AgMIP project deals with the inter-comparison of various simulations models for different crops and their sensitivity, locations, etc., this report considered only two crops (rice and wheat). Crop models used in the study were: CERES-Rice and CERES-Wheat for DSSAT Ver. 4.5.1.023-Stub and APSIM 7.5-Oryza and APSIM-Wheat for each location.

Source of Information: Bangladesh J. Agril. Res. 44(2): 311-326, June 2019 ISSN 0258-7122 (Print), 2408-8293 (Online)

Article Link (Online Journal):

Funding Source:

Total Budget (Tk.) :

Achievement/Findings:

Climate change is likely to have adverse effects on the livelihoods of the smallholder farmers in Dinajpur district ranged between 50 and 82% that being affected and might not be able to cope up. Northwest region of Bangladesh is likely to be affected by climate change and has high levels of vulnerability due to limited access to alternative livelihood activities other than farming. Simulation results showed no additional economic gains from wheat cultivation due to decreasing yield trend by the years, but rice cultivation had increased yield and showed increasing trend of productivity. Therefore, an adaptation package of 50 mm additional irrigation water for wheat cultivation is likely to be an appropriate strategy for adapting to climate change. Moreover, both DSSAT-CERES-Wheat and APSIM-Wheat models predict more wheat yields than the observed yields, even DSSAT-CERES-Wheat model projects higher yield than APSIM-Wheat model. However, APSIM model is found less efficient to predict uncertainty in yields associated with different farms than DSSAT model. In case of predicting adaptation impact of climate change on economic return and per capita income of farmers, performance of APSIM model is superior to DSSAT model. Moreover, both models predict a positive impact of adaptation on projected per capita income that will be increased by about 2.05% and poverty rate will be reduced by about 1.99%. Finally, this study appreciates the prediction capability of both simulation models that might be helpful for farmers to reduce the risk of climate change on agriculture of Bangladesh.

Knowledge Management: Journal