Assessment of global warming impacts on paddy rice growth and yield using a process based numerical crop growth model matcro rice in thai binh province vietnam

VIETNAM NATONAL UNIVERSITY, HANOI VIETNAM JAPAN UNIVERSITY DAO THI THU HANG ASSESSMENT OF GLOBAL WARMING IMPACTS ON PADDY RICE GROWTH AND YIELD USING A PROCESS-BASED NUMERICAL CROP GRO

VIETNAM NATONAL UNIVERSITY, HANOI

VIETNAM JAPAN UNIVERSITY

DAO THI THU HANG

ASSESSMENT OF GLOBAL WARMING IMPACTS ON PADDY RICE GROWTH AND YIELD USING A PROCESS-BASED NUMERICAL CROP GROWTH MODEL

MATCRO-RICE IN THAI BINH

PROVINCE, VIETNAM

MASTER’S THESIS

VIETNAM NATONAL UNIVERSITY, HANOI

VIETNAM JAPAN UNIVERSITY

DAO THI THU HANG

ASSESSMENT OF GLOBAL WARMING IMPACTS ON PADDY RICE GROWTH AND YIELD USING A PROCESS-BASED NUMERICAL CROP GROWTH MODEL

MATCRO-RICE IN THAI BINH

PLEDGE

I assure that this thesis is the result of my own research and has not been published The use of other research’s result and other documents must comply with regulations The citations and references to documents, books, research papers, and websites must be in the list of references of the thesis

AUTHOR OF THE THESIS

DAO THI THU HANG

TABLE OF CONTENTS

PLEDGE i

LIST OF TABLES iv

LIST OF FIGURES v

LIST OF ABBREVIATIONS vi

ACKNOWLEDGEMENT vii

ABSTRACT viii

CHAPTER 1 INTRODUCTION 1

1.1 Overview 1

1.2 Research objectives 4

1.3 Structure of the Thesis 5

1.4 Learning Outcomes 7

CHAPTER 2 METHODOLOGY 10

2.1 Framework of the study 10

2.2 Study area 12

2.2.1 Location 12

2.2.2 Climate 13

2.2.3 Rice variety (Bac Thom No 7 cultivar_BT7) 17

2.3 MATCRO-Rice model 17

2.4 Data sources 20

2.4.1 Meteorological data 20

2.4.2 Crop management 21

2.5 Model parameterization 23

2.5.1 Phenology 23

2.5.2 Dry matter Partitioning 25

2.6 Nitrogen response 25

2.7 Model validation 27

2.8 Global warming impact assessment 27

CHAPTER 3 RESULTS 29

3.1 MATCRO-Rice parameterization and validation 29

3.1.1 The effect of parameterization to phenology 29

3.1.2 The effect of parameterization to Carbon partitioning 31

3.2 Yield and nitrogen response 34

3.3 Impact of temperature increase on rice yield 36

CHAPTER 4 DISCUSSION AND LIMITATION 38

4.1 Discussion 38

4.2 Limitations 41

4.2.1 Data gaps 41

4.2.2 Limitation of the parameterization 41

CHAPTER 5 CONCLUSION 42

REFERENCES 43

LIST OF TABLES

Table 2.1 Thai Binh province weather by month and weather averages 15

Table 2.2 Site information and input 18

Table 2.3 Meteorological variables 20

Table 2.4 Information of Site 1 and Site 2 21

Table 2.5 Crop calendar and field measurements 22

Table 3.1 Comparison of development stage index between simulation and global .29

Table 3.2 Timing of growth date (mm/dd/yr) 29

Table 3.3 Partitioning parameters 33

Table 3.4 The difference between before and after calibrated nitrogen response index 34

Table 3.5 Percentage different between observed and simulated yield 35

Table 3.6 The statistical analysis of rice yield 35

Table 3.7 Influence of temperature increase on rice yield 37

Table 4.1 Yield reduction 40

LIST OF FIGURES

Figure 2.1 Framework MATCRO-Rice model simulation 11

Figure 2.2 Map of Thai Binh administrative regions 13

Figure 2.3 Monthly average temperature (oC, line and left vertical axis) and monthly rainfall (mm, column and right axis) 14

Figure 2.4 MATCRO-Rice model structure 18

Figure 2.5 The relationship between specific leaf nitrogen and DVS 27

Figure 3.1 Heading date of simulation and global data 30

Figure 3.2 Heading date of simulation and global data 31

Figure 3.3 Partitioning ratio of glucose to organs including leaves (a), panicles (b) within shoots and root (c) 33

Figure 3.4 Correlation between the observed and simulated yields The orange line is the 1:1 line 36

Figure 3.5 Comparison between simulated yield, yield at 4 warming scenarios applied for 3 nitrogen cases (high, medium and low) 37

Figure 4.1 Menu for adaptation options on agriculture 39

Figure 4.2 Influence of N fertilizer levels on rice yield at different temperature increase scenarios 40

LIST OF ABBREVIATIONS

CGM: Crop growth model

DVS: Development stages index

GSO: General statistic office

hGDH: Growing degree hour from seedling to heading

mGDH: Growing degree hour from seedling to harvest

MONRE: Ministry of Natural Resources and Environment

RRD: Red River Delta

SLN: Specific leaf nitrogen

UNFCCC: United Nations Framework Convention on Climate Change

ACKNOWLEDGEMENT

I would like to express my sincere gratitude to my supervisors Dr Yuji Masutomi - Ibaraki University and Dr Mai Van Trinh - Director of Institute for Agricultural Environment for providing the invaluable guidance, comments and suggestions throughout my thesis

I would special thank Dr Akihiko Kotera for scientific consulting and constantly motivating me to work harder I am also grateful to all the lectures in the Vietnam Japan University and Ibaraki University for their support towards the successful completion of my studies in Vietnam and Japan

Without the financial support of the Vietnamese and Japanese Government which offered me a scholarship for graduate studies, this work would not have been possible Special thanks go to all the lecturers and staffs at the Institute for Global Climate Adaptation Science (ICAS) and department of Agriculture in Ibaraki University for providing me an internship in Japan in two months which I had an opportunity to research with professionals and enjoy culture exchange I am really grateful to them

In addition, I would also like to thank my friends and colleagues at the Institute for Agricultural Environment for supporting me during the entire data collection period and creating best conditions for me to balance my work and study

Finally, I want to dedicate my success to my family for the encouragement and support throughout my research process I give special thanks to my parents for helping me take care of my children, providing logistical support and encouragement that no one to help me cannot complete my work

I submit this thesis of mine with great humility and regards

ABSTRACT

Rice is directly feeding more people than any other crops Vietnam is one of the largest exporters of rice with the main supply from Red River Delta Rice production in Red River Delta is susceptible to yield reduction from rising temperature Thus, understanding the impacts of global warming on rice production

is essential to food security in Vietnam in the near future This research used a reliable data of crop management in Thai Binh, located province in Red River Delta To simulate the rice production, I used the crop growth model, MATCRO-Rice, first the model needs to be parameterized the phenology and dry matter partitioning, then I validated by comparing the simulated yield to observe yield Next, the model was used to predict the changes of rice production under 4 warming scenarios (1.5 oC, 2 oC, 3 oC and 4 oC) Results show that the yield reduction happened in all of warming scenarios and decline up to 39% compare with observe yields The yield will be improved by adding more fertilizer, but this application cannot offset the losses due to rising temperature This research got some limitation from both data and model, but it can contribute to the development

of a national adaptation plan with a scientific basis

Keywords: global warming scenarios, rice production, crop growth model

CHAPTER 1 INTRODUCTION

1.1 Overview

According to the IPCC in 2014, climate change that was caused by global warming, has recorded high impacts on human and natural systems during the past few decades (IPCC, 2014) At the end of the twentieth century, the temperature was recorded 0.7 oC higher than the nineteenth century According to the conclusion of the Paris Agreement in 2015, all countries under the United Nations Framework Convention on Climate Change (UNFCCC) seek the long term temperature target to protect the climate (UNFCCC, 2015) to limit future global warming to less than 2.0

oC above the pre-industrial levels (1861 – 1880) Ideally, global temperature rising will be kept under 1.5 oC (UNFCCC, 2015) due to the adverse effects of climate change that have been observed worldwide It is necessary to evaluate climate change impacts, especially global warming to implement adaptation plans at national scale

Fossil fuel and biomass burning are the main causes to increase carbon dioxide (CO2) in atmosphere as the main greenhouse gas So far, the CO2concentration has increased from 280 ppm to around 400 ppm and mainly caused climate change On the other hand, rising CO2 concentration also roots of rising temperature and changing in precipitation and this still continues in the future (IPCC, 2014)

There have been many researches on assessing the range of global warming based on the 2015 Paris Agreement on many fields across the globe (Mitchell et al., 2017) and agriculture is strongly influenced by it across the world (Faye et al., 2018; Liu et al., 2018; Schleussner et al., 2018) The scientists have made efforts on mitigation of global warming to ensure the food stability in context of the population continues to rise in the next decades (Gaupp et al., 2019)

Rice (Oryza sativa L.) is the most important food crop in the world in general

and in Asia in particular (Clauss et al., 2018), directly feeding more people than any other crop There have been a number of past studies to examine the effects of global warming on rice growth and yield in global or regional scales (Zhai and Zhuang, 2009; Chen, McCarl, & Chang, 2011; Rosenzweig et al., 2014; Zhao et al., 2016; Lobell and Asseng, 2017) The exceeding temperature during the rice growth will impact on photosynthesis capacity (Cai et al., 2018), root length (Sanchez et al., 2014), increasing the rate of unfilled grain and others (Prasad et al., 2006) When the temperature is higher, it will promote the reproductive development, thus shortening the rice growth time (Lu et al., 2008) and leading to decrease the rice yield (Prasad et al., 2006) According to Peng et al., 2004, with 1 oC increase in nighttime, rice yield will reduce by about 10% and the reasons come from the decrease of solar radiation Other researches have shown that the future reduction in rice yields will be more evident at low latitudes than medium or high latitudes, since warmer temperatures at low latitude result in higher thermal stress for rice (Rosenzweig and Parry, 1994) Almost previous studies have shown that rice yield has been reduced due to climate change, but the extent of the reduction and the spatial variability of impacts have been controversial so far (Yang et al., 2014) Therefore, in the future global warming could seriously threaten rice yield to feed future generation in global scale, especially

in Asia

Vietnam is a developing country in which agriculture is a traditional economic sector Currently, Vietnam is one of the world’s richest agricultural regions and is the second largest exporter worldwide and the world’s seventh largest consumer of rice Rice cultivation accounts for more than three-quarters of the country’s total annual harvested agricultural area and employs about two-thirds of the rural labor force which has been making a significant contribution to rural livelihood (Vu and Glewwe, 2009; Nguyen, 2006) Agricultural production could

be easily affected on climate variability and according to the Ministry of Natural Resources and Environment (MONRE), an average annual temperature has tended

to increase by about 0.62 oC since 1958 (MONRE, 2016) It is estimated that by the end of the 21st century, compared with the average of the period 1980-1999, the average temperature in Vietnam may increase by 2.3 oC, annual rainfall increases

by 5% and the sea level may rise 75cm (MONRE, 2016) As a result, global warming has caused the instability in rice production in the country (Yu et al., 2010) Therefore, it is essential to quantify the projected impact of rising temperature on rice yield to contribute the literature on food stability and security Vietnam needs to proactively assess, forecast and adapt to the impacts of climate change, in order to have timely appropriate solution and agricultural economic development

Vietnam has two large rice production delta regions including Mekong delta to the south and Red River delta (RRD) to the north, which are vital to the domestic food supply Although, each delta has different geographical characteristics, both of them are suffering from rice yield reduction because of changing climate Climate change impacts on rice growth and yield in the Mekong delta and central part of Vietnam (Kontgis et al., 2019; Deb et al., 2015; Yu et al., 2010), however, little attention has been paid on rice production in RRD, especially in Thai Binh province which has provided largest rice in the North of Vietnam Moreover, with a population

of 1.7 million (GSO, 2012) and more than 70% of the income share comes from farming activities, rising temperature could have detrimental effect on rice production

in this province, and this has led to a decline in the quality of livelihoods of people living here who rely on rice cultivation Therefore, it is important to predict and create adaptation plans due to climate change and temperature is the key factor of climate issues

Prediction and assessment of climate change impacts on rice production can

be implemented by process-based numerical crop growth models which have been increasingly developed in the recent years (Xiong et al., 2014) Some crop growth models are used as much by researchers such as ORYZA2000 (Sheehy et al., 2006), CERES-Rice (Kim et al., 2013), DSSAT (Hoogenboom et al., 2010) which have

judged rice growth and yield changes under different climate change scenarios In recent years, they have tended to apply model to large areas to figure out the impacts of climate change (IPCC, 2014; Ruane et al., 2014), productivity gaps between the region and food security (Bezner et al., 2019), carbon sequestration (Arunrat et al., 2018), however, there is a few of studies providing enough information or data to assess the performance of the models There are many kinds

of crop growth model (CGM) but it is difficult to compare the accuracy between models across larger scale because each model used different plant model and input data In this study, we used the process-based numerical crop growth model MATCRO – Rice model which was developed by Professor Yuji Masutomi (Masutomi et al., 2016) to measure the effects of global warming on rice growth and yield

With all of these above reasons, I chose the topic: “Assessment of global warming impacts on paddy rice growth and yield using a process-based numerical crop growth model MATCRO-Rice in Thai Binh province, Vietnam” to aim for evaluation of rising temperature impacts on the main crop in one of the highest rice production area in Vietnam My research results provide policymakers with valuable information in making the global warming adaptation strategies for rice production in Thai Binh province

1.2 Research objectives

The research is necessary to choose a suitable model for climate change impact evaluation on rice production in Thai Binh province – one of the largest rice production provinces in the Red River Delta My thesis aims to solve three research questions:

How to develop an appropriate and efficient parameterization of crop growth model (CGM) performance for improvement of crop simulation?

How much rice yield will increase or decrease with global warming scenarios?

Which adaptation measures are preferred to address global warming in rice production in Vietnam?

To answer these questions, this research used the crop growth Rice model First, the model was parameterized using the crop management data for local cultivar named Bac Thom number 7 (BT7) which is one of the most major local varieties in the Northern of Vietnam in general and in Thai Binh province in particular Next, the temperature increase scenarios were used to identify the impact

MATCRO-on rice productiMATCRO-on The specific activities of this thesis were:

(1) to collect the data of rice crop management in Thai Binh province and climate data in this region;

(2) to parameterize and validate the model to figure out the parameters which could simulate model closely to the observation data;

(3) to simulate rice growth and yield by MATCRO-Rice;

(4) to predict the future rice by rising temperature scenarios;

(5) to suggest some adaptations strategies for climate change in Vietnam in general and in Red River Delta in particular

1.3 Structure of the Thesis

My thesis is organized in 5 chapters as below:

Chapter 2: Material and Method

Framework of the study

Overview of study area

Introduction the crop growth model MATCRO-Rice

Data source to study

Method to parameterize and validate the model

Method to assess the impact of global warming on rice growth and production

1.4 Learning Outcomes

Program Learning Outcomes (PLOs) of the MCCD Results of the Master’s thesis

PLO1: Mastering the fundamental, interdisciplinary knowledge

and methodologies to assess and address actual problems (fate

and features) related to CC mitigation, adaptation for

sustainable development at global, national and local levels

The thesis gave the measure strategies to adapt with the reduction of rice yield due to climate change such as changing in agricultural management (example: planting date, fertilizer, etc ), changing in planting crop, do the early warning system, seasonal forecasting system, changing the variety (breeding new variety), developing the irrigation system…

PLO2: Understanding and developing systematic thinking;

necessary knowledge on science, technology, innovation and

governance related to CC response for development;

identifying, analyzing, assessing and forecasting the issues

related to CC and CCR; predicting the developing trend of CC

science

The thesis used the crop growth modeling which has been simulated for global scale I calibrated the parameters to fit with small regional scale and to predict the trend of rice production under global warming scenario

PLO3: Applying knowledge to solve the problems in CC and

CCR: planning and approaching the works in field of CC;

proposing the initiatives as well as the researches on CC;

implementing the solutions on science, technology, mechanism,

policy and finance for CCR and development

PLO4: Having skills of cooperation with personal, agencies,

organizations domestically and internationally to solve the CC

issues, communication in works, projects on CC; and

organizing, managing and administrating advanced career

development

To calibrate the model, I need to collect the rice yield data and crop management data, hence I need to cooperate with Institute of Agricultural Environment to use the data of one project

PLO5: Accumulating soft skills to self-directed and adapt to

competitive working environment such as English proficiency

(at level 4/6 according to English competencies Framework for

Vietnam), Japanese communication skills; having skills on time

management; using the basic computer skills proficiently;

working and researching independently; having skills of

research and development; and using technologies creatively in

academic and professional fields

The crop growth model is written by R programing and the user need to understand and practice some commands from easy to difficult Besides other computer skills are improved after the thesis course

Working with Japanese professors requires student complete deadline in time, time management and self-discipline in research

Besides using English in communicate and writing reports, thesis; knowing a little Japanese will make the friendly environment between student and other Japanese professors

PLO6: Having social/community’s responsibility and

professional morality, especially for the scientific research

results; being able to adapt to multicultural environment, ensure

the harmony between the stakeholders, CCR and development;

having good social morality, assist the vulnerable people to

climate change; compliance with the law; discipline at work and

positive lifestyle; having good attitude to their career in climate

change response for sustainable development

The thesis results show the effect of climate change to food security and sustainable agriculture and especially strongly impact to the vulnerable people such as farmers and the poor Therefore, giving measure adaptation strategies is one

of the social responsibilities

CHAPTER 2 METHODOLOGY

2.1 Framework of the study

Figure 2.1 illustrates the framework to assess global warming impacts on rice production in local area using crop growth model MATCRO-Rice This research used the phenological and biomass data of two sites in Dong Co commune, Tien Hai district, Thai Binh province and both sites applied three different amount of fertilizer application with low, medium and high nitrogen To simulate the rice yield, we used the process-based crop growth model MATCRO-Rice Based on these data, we made the parameterization for BT7 cultivar phenological and partitioning parameters After the parameterization, we run the model and the model output is the simulated yield and then we validated by compared with the simulated yield with the observed yield This process will be repeated if the simulated rice yields do not match the observation data Finally, we simulated four global warming scenarios (rising 1.5 oC, 2 oC, 3 oC and 4.0 oC) impacts on rice yield which can support the policy makers in conducting the adaptation strategies for rice production

in Vietnam

Figure 2.1 Framework MATCRO-Rice model simulation

Simulation the Rice growth and yield in Thai Binh Province

Impact of global warming on Rice production in Thai Binh province

Phenology calibration and

Global warming scenarios

Adaptation measures Running MATCRO-Rice model

Weather data: air pressure, precipitation, humidity, solar radiation, air temperature, wind speed

Date of plant, heading, harvest

Biomass of each growth stages: stem, leaf, panicle and root Study area information

2.2 Study area

2.2.1 Location

Red River Delta (RRD) is the second largest in Vietnam which is located in the northern part formed by the Red river and its distributaries merging with the Thai Binh River RRD is a rich agriculture area in which the agriculture land is cultivated paddy rice RRD covers eight provinces and the capital Hanoi and Hai Phong city with a population of approximately 23 million (GSO, 2012) and densely populated 80% of the population are employed in agriculture, but the agricultural lands of the delta amount to only about 0.3 - 0.5 hectares per household, making the limited supply of arable lands a significant constraint to improve living standards RRD is the second most important rice-producing area in Vietnam, accounting for 20% of the national crop Production of rice is close to optimal with very little yield gap to exploit and employ double cropping techniques to achieve close to maximum yields

This research focused on Thai Binh province belonging to the RRD (Figure 2.2) Thai Binh is the main paddy rice production area in the RRD with more than 80% of land in the province under the rice farming The agriculture in this area is characterized by small land size (0.04 ha per rural capita or 0.2 ha per household on average) and complex farming like VAC system (FAO, 2001) which is an abbreviation of Vietnamese phrase meaning horticulture – aquaculture – animal husbandry

Figure 2.2 Map of Thai Binh administrative regions

Thai Binh is the only province in the country with three sides of the river and one side to the sea which is located in the direct influence area of the economic growth triangle Hanoi - Hai Phong - Quang Ninh The area of agricultural land is over 105,700 ha, mainly alluvial by two main river systems Red River and Thai Binh River system, which is favorable for transplanting rice and other annual crops

- especially in the direction of intensive cultivation and developing high-tech agriculture Like other provinces in Northern Vietnam, rice is grown in two seasons: spring (January to late May) and summer (mid-June to early October) This study focuses on the summer growing season in 2012

2.2.2 Climate

Thai Binh belongs to typical monsoon area with one rainy season which starts in May and ends in October The total rainfall in the rainy season is up to 1,445 millimeter (mm), accounting for approximately 85% of the total annual

rainfall of 1,704 mm The yearly average temperature across the year is from 19 oC

to 32 oC

Figure 2.3 Monthly average temperature (oC, line and left vertical axis) and

monthly rainfall (mm, column and right axis)

The driest month is December, with 24 mm of rain With an average of 355

mm, the most precipitation falls in September

July is the hottest month of the year with the average temperature is 29.8 °C and January has the lowest average temperature of the year which is around 17.8

°C

Table 2.1 Thai Binh province weather by month and weather averages

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Avg Temperature

in Thai Binh, extremely cold event directly affecting agriculture - forestry - fishery production Pests and diseases have spread on a large scale losed investment in production development, slow-growing plants and seasonal effects The prolonged hot weather due to the impact

of climate change in recent years, has led to the seawater intrusion into the land causing saline land for cultivation If the sea level rises by

of flooding in the province is 11.8%; if raised to 100 cm, there will be about 31.4%

of the area at risk of flood In which, 2 districts: Thai Thuy and Tien Hai are hardest hit, with flooded areas of 31.86 km2 and 35.91 km2 respectively, followed by Kien Xuong, Dong Hung, Quynh Phu, Vu Thu, Hung Ha districts and Thai Binh City

2.2.3 Rice variety

The cultivar Bac thom No 7 (BT7) is a common rice variety grown in the Northern Vietnam in general and in Thai Binh province in particular BT7 is highly economical compared to conventional rice varieties and due to high Amylose 13% this variety has high quality

BT7 can grow in two seasons: Spring crop (125 – 135 days) and Summer crop (105 – 110 days) It has 100 – 105 cm plant height but it is easy to fall, good tillering and the mass of 1000 seeds is 18.5 – 19.5 grams The average yield is 50 –

55 quintals/ha, but good intensive farming reaches to 60 – 65 quintals/ha

2.3 MATCRO-Rice model

To simulate global warming on rice yield, the process-based crop growth model MATCRO-Rice was used This model is combined by two models: land surface model (LSM) and crop growth model (CGM) This model can simulate latent heat flux, sensible heat flux, net carbon uptake by crop and crop yield by exchange variables between the LSM and CGM (Masutomi et al., 2016) However,

in the thesis framework, this research used only crop growth model (CGM) in simulation of rice yield This model has simulated rice growth and yield in global and regional scale In addition, the model’s author has also studied the impact of global warming on rice yield in Indonesia by using meteorological data in this area which effects on phenology and physiological rice Here is the structure of CGM in MATCRO-Rice: