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Bachelor’s thesisGeography, 15 Credits
Rice yields under water-saving irrigation management
A meta-analysis
Amanda Åberg
GG 1982017
Department of Physical Geography
Preface
This Bachelor’s thesis is Amanda Åberg’s degree project in Geography at the Department of
Physical Geography, Stockholm University. The Bachelor’s thesis comprises 15 credits (a
half term of full-time studies).
Supervisor has been Stefano Manzoni at the Department of Physical Geography, Stockholm
University. Examiner has been Steve Lyon at the Department of Physical Geography,
Stockholm University.
The author is responsible for the contents of this thesis.
Stockholm, 16 June 2017
Steffen Holzkämper
Director of studies
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Abstract
Water scarcity combined with an increasing world population is creating pressure to develop new methods for producing food using less water. Rice is a staple crop with a very high water demand. This study examined the success in maintaining yields under water-‐saving irrigation management, including alternate wetting and drying (AWD). A meta-‐analysis was conducted examining yields under various types of water-‐saving irrigation compared to control plots kept under continuous flooding. The results indicated that yields can indeed be maintained under AWD as long as the field water level during the dry cycles is not allowed to drop below -‐15 cm, or the soil water potential is not allowed to drop below -‐10 kPa. Yields can likewise be maintained using irrigation intervals of 2 days, but the variability increases. Midseason drainage was not found to affect yield, though non-‐flooded conditions when maintained throughout most of the crop season appeared to be detrimental to yields. Increasingly negative effects on yields were found when increasing the severity of AWD or the length of the drainage periods. Potential benefits and drawbacks of water-‐saving irrigation management with regards to greenhouse gas emissions, soil quality and nutrient losses were discussed to highlight the complexity of the challenges of saving water in rice production. Keywords: rice, yield, water scarcity, water-‐saving irrigation, WSI, alternate wetting and drying, AWD, soil organic matter, soil organic carbon.
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Table of contents
Abbreviations ..................................................................................................................................... 4
1. Introduction ........................................................................................................................... 5
2. Research questions and problem formulation ........................................................................ 6
3. Water management in rice farming ....................................................................................... 7 3.1 Field level water flows ................................................................................................................... 7 3.2 Field level irrigation management approaches .............................................................................. 7
3.2.1 Alternate wetting and drying, submergance-‐nonsubmergance and intermittent irrigation ........ 8 3.2.2. Saturated soil culture ................................................................................................................... 9 3.2.3. Controlled irrigation ..................................................................................................................... 9 3.2.4. Midseason drainage ..................................................................................................................... 9
3.3 Influence of water-‐saving irrigation management on rice yields and water savings ....................... 9
4. Methodology ....................................................................................................................... 10 4.1. Data collection ........................................................................................................................... 10 4.2. Data compilation and evaluation ................................................................................................ 11 4.3. Data analysis .............................................................................................................................. 13
5. Results ................................................................................................................................. 17 5.1. Yields under WSI management ................................................................................................... 17 5.2. Regional differences in WSI yield ................................................................................................ 18 5.3. Influence of severity of WSI management on yield ..................................................................... 19 5.4. Nitrogen fertilization effect on yields ......................................................................................... 21
6. Discussion ............................................................................................................................ 22 6.1. Rice yields under varying irrigation managements ...................................................................... 22 6.2. Environmental implications of water-‐saving irrigation ................................................................ 24
6.2.1. Greenhouse gas emissions and soil quality ................................................................................ 24 6.2.2. Nutrient and herbicide losses ..................................................................................................... 26
6.3. Implementation of water-‐saving irrigation management ............................................................ 27 6.4. Methodological and data weaknesses ........................................................................................ 27 6.5. Future research .......................................................................................................................... 28
7. Conclusions .......................................................................................................................... 29
Acknowledgements ................................................................................................................. 29
References ............................................................................................................................... 29
Appendix A .............................................................................................................................. 34
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Abbreviations
ASNS alternate submergance-‐nonsubmergance
AWD alternate wetting and drying
CF continuous flooding
FWL field water level
SOC soil organic carbon
SOM soil organic matter
SWP soil water potential
WSI water-‐saving irrigation
WUE water use effiency
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1. Introduction
Rice is a staple food for a large number of the human population and constitutes the largest food source as well as a significant income for inhabitants of developing countries (GRiSP, 2013). Worldwide rice-‐farming environments are oftentimes divided into four types: lowland irrigated rice, lowland rainfed rice, flood-‐prone rice and upland rice. Of these environments, the irrigated lowlands, covering approximately 93 million hectares of land, produce 75% of the total world rice production (Bouman et al., 2007; GRiSP, 2013). Rice receives about two to three times more water at the field level than most other crops, and these irrigated rice environments consume approximately 24-‐30% of the world's freshwater withdrawals. Meanwhile, decreases in water resources and declines in water quality are resulting in water scarcity. Combined with increased competition from urban and industrial sectors, this water scarcity poses a threat to the sustainability of rice production. New methods are thus required to deal with the challenges posed by water scarcity (Bouman et al., 2007). Saving water is rarely a voluntary decision made by farmers. It is more often either an imposed decision made at a higher level or a necessity dictated by physical water scarcity (Bouman et al., 2007). Due to the pivotal role of rice as a staple food for a large part of the world's population, many studies have examined the effect of different irrigation regimes on rice yields (Carrijo et al., 2017). Many of these studies have found a small decrease in yield accompanied by a significant increase in water productivity when water-‐saving irrigation (WSI) methods were used (see e.g. Bouman and Tuong, 2001 for a summary). Other studies found an insignificant difference in yield between continuous flooding and water-‐saving methods (e.g. Cabangon et al., 2001; Belder et al., 2004). The purpose of this study is to examine patterns in the relationship between rice yield and water management by systematically collating data from a number of studies. Bouman and Tuong published a meta-‐analysis in 2001, examining water-‐saving irrigation at the field level and its impact on yields. Their study provides an excellent opportunity to examine whether yield improvements under WSI management, relative to continuous flooding, have been documented in the 16 years that have passed since. A recently published meta-‐analysis conducted by Carrijo et al. (2017) will serve as a contemporary comparison. As has been stated by Linquist et al. (2015), though many studies have examined potential benefits of water-‐saving irrigation, the consequences are rarely evaluated concomitantly. Water management in rice farming has several environmental implications, aside from the challenge of water scarcity. Rice farming emits approximately four times as much greenhouse gas as wheat or maize and therefore has significant potential in terms of mitigating agricultural greenhouse gas contributions (Linquist et al., 2012). Reducing the amount of time the soil is kept under flooded anaerobic conditions has been found to decrease emissions of the strong greenhouse gas methane. However, the conversion to aerobic conditions instead leads to increased microbial activity and increased soil organic matter (SOM) decomposition and CO2 emissions (Sahrawat, 2005; Haque et al., 2016a). SOM has great importance for soil health and agricultural sustainability. The conversion to more aerobic conditions may therefore have significant implications for long-‐term soil fertility and rice farming sustainability. Furthermore, the implementation of water-‐saving irrigation has
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also been found to affect nutrient availability in the soil, as well as losses of fertilizers through surface runoff and seepage (Sahrawat, 2005; Yang et al., 2015). Hence, the implementation of water-‐saving irrigation has many implications that should be considered in addition to the challenges of water scarcity.
2. Research questions and problem formulation
The aim of this project is to examine the relationship between yields and water-‐saving irrigation in rice farming systems using a meta-‐analysis approach. This study will attempt to collate information from multiple studies to examine said relationship. Specifically, this project will attempt to answer the following questions: • Is rice yield consistently higher under continuous flooding compared to alternate wetting
and drying and other water-‐saving forms of irrigation management? • Can a spatial pattern be discerned, in which water-‐saving irrigation has been more
successful in any certain region of Asia? Through literature studies, some of the environmental implications of employing water-‐saving irrigation management will also be qualitatively examined and discussed. This study wishes to place water-‐saving irrigation in a larger context by providing a summary of both benefits and drawbacks of its implementation. Whether or not different levels of nitrogen fertilizer input affect the success of water-‐saving irrigation will also be briefly examined. There are many ways to save water aside from changing irrigation practices, such as proper land preparation and bund construction (Bouman et al., 2007), but these measures are largely outside the scope of this paper. No attempt will be made to quantitatively assess actual water savings, though potential water savings will be briefly discussed. The study will be limited to rice systems in East, South, and Southeast Asia. The relatively large spatial extent of field experiments included in this analysis is partly the result of the need to keep the collection of data objective and systematic. Limiting the spatial extent by using search words such as "Southeast Asia" resulted in a very limited results list. Furthermore, this approach enables an examination of whether the effects of WSI are the same over a range of different environmental conditions. Due to the necessity of being able to control the water input to implement WSI management, the focus is inevitably placed primarily on irrigated lowlands. In these environments farmers may, depending on the structure of the irrigation system, have the opportunity to influence not only drainage of water from the fields, but also the input of water (Bouman et al., 2007). Farmers can therefore to a certain degree influence the amount of water-‐stress experienced by plants during the growth period. A focus on these rice systems is deemed suitable for this study since irrigated lowlands are responsible for such a large part of the global rice production.
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3. Water management in rice farming
3.1 Field level water flows
There are various ways in which water can enter and leave a rice field. Inflow occurs through rainfall, irrigation, and capillary rise, and outflow through percolation, seepage underneath bunds, overbund flow, evaporation and transpiration. Transpiration is the only type of outflow that contributes to crop growth and is therefore termed 'productive water use'. Capillary rise is generally negated by the constant downward flow of percolation in flooded rice fields. In a series of fields, both seepage and overbund flow can contribute to adjoining farmers' fields before draining into ditches or the groundwater. Even after entering the groundwater, this water may remain reusable through pumping (Bouman et al., 2007). The high water demand for rice differs from dryland crops and is the result of the daily percolation and seepage of water that occurs in flooded rice fields, along with evaporation from exposed water surfaces. The profuse percolation rates over long periods of time have in many places served to locally raise the groundwater surface. In some locations, the groundwater table is found within 20 cm from the soil surface, and the water is therefore available for direct uptake by the rice roots (Bouman et al., 2007). When the field water level (FWL) is at or above the soil surface and the soil is saturated, such as in flooded paddies, the soil water potential (SWP) near the surface will equal 0 kPa. When the soil is saturated, most of the water is held in large pores where the molecules are not strongly bound by the soil solids and are therefore able to easily move around. As the soil dries, the remaining water is increasingly held in smaller pores closer to the soil solids, where they are more tightly bound and harder for plant roots to extract, This change is measured as an increasingly negative SWP (Brady and Weil, 2008). If there is not enough water available, the rice plant will experience drought stress, expressed, for example, in the closing of stomata and ceasing of transpiration, which can in turn result in yield declines (Bouman et al., 2007).
3.2 Field level irrigation management approaches
Before rice is transplanted or seeded, the field is normally ploughed and puddled under wet conditions (Bouman et al., 2007). Puddling is a type of harrowing or rotavating that helps in controlling weeds, but also reduces soil permeability by destroying soil aggregates and creating a plough pan, usually at a depth of approximately 10 to 20 cm. The hydraulic conductivity decreases, and therefore also the loss of water through percolation (Arora et al., 2006; Bouman et al., 2007). Following puddling, fields are usually kept flooded before transplanting for a period ranging from a few days to four weeks, though it has been known to stretch as long as two months in large-‐scale systems. Once transplanted or seeded, the crop is traditionally kept flooded at a depth of 5 to 10 cm until one or two weeks before harvesting. Flooding following crop establishment helps to control weeds and pests (Bouman et al., 2007). Figure 1 provides an overview of the different growth stages of rice.
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Figure 1. Schematic overview of the different growth stages of the rice plant. Adapted from CGIAR, n.d.
For water-‐saving irrigation to be a feasible alternative, losses of water through seepage, percolation and evaporation must be addressed. Efforts can be made during land preparation by constructing appropriate field channels that enable the control of water levels in individual fields, maintaining good bunds, levelling the field, implementing tillage and minimising the time passing between land preparation and crop establishment (Bouman et al., 2007). Bouman et al. (2007) describe three types of water-‐saving irrigation; alternate wetting and drying (AWD), saturated soil culture (SSC), and aerobic rice (not covered here, predominantly used in upland environments). Which form is implemented depends on the type and severity of water scarcity, socioeconomical situation and how much control individual farmers can exercise over their irrigation. The implementation of AWD requires that a farmer can control water levels in their own field, or that a communal effort is made. With reduced water availability, saturated soil culture may be the first option, followed by AWD and then aerobic rice when faced with severe shortages (Bouman et al., 2007).
3.2.1 Alternate wetting and drying, submergance-‐nonsubmergance and intermittent irrigation
Alternate wetting and drying, sometimes referred to as alternate submergence-‐nonsubmergance (ASNS) (Belder et al., 2004) or intermittent irrigation (Lin et al., 2012), utilizes cycles of alternating flooded conditions and dry periods when the water is allowed to drop below field level. The length of the dry periods can vary from as little as one day to longer than 10 days (Bouman et al., 2007). Cabangon et al. (2001) state that AWD normally includes a midseason drainage of 10-‐15 days in the late tillering stage, and that the dry cycles between irrigation events are normally kept at lengths of two to four days. In practice, however, the pre-‐designed timing and length of drainages and dry cycles can be difficult to achieve due to the variability of rainfall events. Carrijo et al. (2017) have, in their meta-‐analysis, chosen to define AWD as any irrigation management that contains a minimum of one single dry cycle with soil conditions below saturation. Their definition differs from those found in most other sources. AWD primarily reduces water use by lessening the amount lost through seepage and percolation. In terms of practical implementation, the use of a field water tube to monitor water levels is recommended (Bouman et al., 2007; Yang et al., 2017). The field water tube also allows farmers to detect 'hidden' groundwater sources (Lampayan et al., 2015). When the water drops to a depth of -‐15 cm, the field should be re-‐irrigated to a ponded depth of approximately 5 cm. The AWD cycles can be implemented starting a few days after transplanting, after two to three weeks if weeds are prolific, or following panicle initiation
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which occurs around 50 days after sowing (Bouman et al., 2007; Cabangon et al., 2001; CGIAR, n.d.). Bouman et al. (2001; 2007) state that the timing of dry cycles with regards to growth stages generally has little to no effect on yield, with the exception that ponded water during flowering is required to avoid yield loss. According to Yang et al. (2017), however, different thresholds should be used at different growth stages due to the variable sensitivity of rice at different points in the crop cycle. The -‐15 cm field water depth is often referred to as 'safe AWD', because it keeps the root zone saturated. The water savings are generally around a modest 15%, but yield loss is avoided, and depending on local conditions farmers can experiment with longer dry cycles (Bouman et al., 2007). Though irrigation in AWD treatments is often scheduled based on FWL, other indicators are also in use, such as SWP thresholds or simply a set number of days following disappearance of previous irrigation from the soil surface.
3.2.2. Saturated soil culture
In saturated soil culture (SSC), irrigation is applied to achieve a water depth of approximately 1 cm following disappearance of the previous irrigation. The goal is to keep the soil as close to saturation as possible, which requires very frequent irrigation. The practice reduces the hydraulic head, resulting in decreased seepage and percolation (Bouman et al., 2007). Though examples of similar practices can be found in the academic literature, the term 'SSC' was rarely encountered during this study.
3.2.3. Controlled irrigation
The term 'controlled irrigation' is sometimes employed in the literature without a firm definition. When Yang et al. (2013, 2015) and Hou et al. (2012) employ the term, the management regime is described as including irrigation to keep the soil moist. However, graphs presented in their articles show that irrigation has been applied to reach a FWL of 1 to 4 cm in between regular dry cycles, in practice appearing to make the approach very similar to AWD.
3.2.4. Midseason drainage
'Midseason drainage' or 'intermittent drainage' are concomitantly used to describe the practice of draining the rice paddy midseason for an extended period, often lasting for about 30 days. The approach is mainly used as a means to achieve decreased methane emissions (Haque et al., 2016a, b), but has also been used as a water-‐saving measure (Rahman et al., 2013).
3.3 Influence of water-‐saving irrigation management on rice yields and water savings
Based on a number of studies, Bouman et al. (2007) concluded that although AWD has in some instances been found to increase yield, it more often decreases yield. Bouman and Tuong (2001) conducted a meta-‐analysis based on 31 field experiments using AWD or SSC conducted under various conditions. They found that average water savings under SSC amounted to 23% with small yield reductions of approximately 6%. When SWPs in the root zone were allowed to drop to -‐10 to -‐30 kPa, however, yield penalties of 10-‐40% were recorded (Bouman and Tuong, 2001). The variability in results identified in the study is attributed to soil and hydrological conditions and the varying length of dry periods in
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different experiments (Bouman et al., 2007). Carrijo et al. (2017) found a similar water use reduction of 23.4% under AWD across a selection of 56 studies, but with SWPs maintained above -‐20 kPa or FWL above -‐15 cm, with no yield penalty. Commenting on a several studies conducted in areas with shallow groundwater tables and fine textured soils, Bouman et al. (2007) concluded that the nearness of groundwater to the field level meant that the root zone remained saturated, supplying a hidden water source. A 15-‐30% lower water input could therefore be achieved without a significant penalty to rice yield. Where the groundwater table is very high and within reach of the roots, potentially negative effects of water-‐saving irrigation can be mitigated, and yields in relation to irrigation can therefore appear superficially high. The water savings in these environments are relatively small due to the losses already being low when using continuous flooding (CF) under such conditions. A number of studies conducted in loamier soils with deep groundwater tables presented higher water savings, exceeding 50%, but heavy yield penalties in excess of 20% (Bouman et al., 2007). Ye et al. (2013) draws on a number of studies to reason that modern rice varieties have been adapted to semi-‐aquatic conditions with only intermittent flooding. The aerated conditions assist in SOM mineralization and inhibition of N immobilization, promoting nutrient release and favouring good yields. Furthermore, based on recently conducted studies Yang et al. (2017) draw the conclusion that AWD within certain limits can increase yield by reducing redundant vegetative growth, elevating hormonal levels, improving canopy structure and root growth and enhancing carbon remobilization from vegetative tissues to grains. Yields have been found to increase in China under AWD, and decrease in tropical locations such as India and the Philippines; a difference that Belder et al. (2004) and Cabangon et al. (2004) reason may be the result of variable WSI practices, soil properties, groundwater depths, rice variety and crop management. AWD and other forms of WSI have been widely adopted in China where per capita fresh water availability is amongst the lowest in Asia, and is being recommended in parts of India and the Philippines (Cabangon et al., 2001; Bouman et al., 2007; Yang et al., 2013).
4. Methodology
4.1. Data collection
Meta-‐analyses provide a tool for examining the results of studies in the context of other studies (Borenstein et al., 2009), and has been used for purposes similar to those presented in this paper by e.g. Bouman and Tuong (2001) and Carrijo et al. (2017). In this study, a search of published studies was conducted to obtain raw data on rice yield, water management method, N fertilizer input, water input, soil organic carbon or soil organic matter (SOC/SOM), crop duration, number of dry cycles, rice variety, soil texture and/or classification, some climatic variables, and whether the crop was transplanted or direct-‐seeded, creating a varied dataset with potential for many applications.
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The article search was conducted in the Web of Science database, using the search term combinations "rice yield" AND water management AND irrigation, and "rice yield" AND water AND flood*. The abstracts of all results produced through these searches were examined, and those deemed likely to contain relevant information were obtained for more detailed study. Specific criteria considered relevant for inclusion into this study included the studies being original research based on field experiments conducted in East, Southeast or South Asia, and containing quantitative data on rice yields and information about water management methods, of which at least one had to be continuous flooding. Various WSI types have been included in the study, but in each case the irrigation approach had to be paired with a control in the form of aforementioned continuous flooding, where all other factors but water management were the same. The WSI treatment had to have a minimum of either one extended dry period, which should be more significant than the ~10-‐day drainage during tillering that is recommended in some locations for optimal yields under CF management (see e.g. Yang et al., 2013; 2015), or multiple shorter cycles where FWL was allowed to drop below the soil surface. The work process for the searches is visualized in figure 2.
Figure 2. Flowchart describing the stages of the data collection process. The terms 'AWD' or 'alternate wetting and drying' could not be used during the data collection process, as many other terms are often employed for similar water-‐saving irrigation techniques that are likely to be relevant for the purpose of this meta-‐analysis. Examples of these terms include 'alternate submergence-‐nonsubmergence', 'intermittent irrigation', and 'controlled irrigation'. The environmental implications of water-‐saving irrigation management were qualitatively assessed based on a literature review, and the findings are summarized and discussed in section 6.2. The review is mainly based on articles encountered during the data collection for the meta-‐analysis and is not intended to be exhaustive. Rather, the goal is to highlight the complexity of the interactions that are affected by WSI management.
4.2. Data compilation and evaluation
The data was compiled in Microsoft Excel, wherein all the analyses were conducted. Many of the included studies placed primary focus on issues such as greenhouse gas emissions or
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identifying optimal fertilizer regimes, but were oftentimes useful for providing the quantitative data needed for this analysis. Data on irrigation management and yield was frequently presented despite any differences having been deemed to be statistically insignificant by the author(s), due to the irrigation data simply being complementary to the main focus of the study. Belder et al. (2007) promised to contain valuable data, but the focus was placed on simulation using the ORYZA2000 model. For this reason, an additional search was made to acquire the original field data, which was then used in the meta-‐analysis (i.e. Belder et al., 2004). A few of the articles generated by the search were found to contain data based on the same set of experiments. This was the case with Hou et al. (2012), Xu et al. (2013), Yang et al. (2013) and Yang et al. (2015). Data was primarily taken from Yang et al. (2013, 2015), and these are therefore the articles that are referred to in the henceforth. A summary of all studies included in the analysis is displayed in table 1. In some instances, only part of the data came from plots fulfilling the above stated criteria. Plots that used relevant water management methods but deviated in other management aspects, thereby invalidating any comparison with a continuous flooding control plot, were excluded. Data was digitalized in those few cases where it was only presented in graphical form. A total of 21 articles, equalling 19 original studies, were included in the analysis, covering 41 sets of comparative field trials, and 179 side-‐by-‐side comparisons of WSI with CF, in a wide range of locations (figure 3).
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Figure 3. Approximate locations of the sites used for field experiments in all studies included in the meta-‐analysis.
4.3. Data analysis
The collected data was analysed using simple quantitative methods. Due to the variability in field conditions between different experiments, actual yields and water input values are generally not directly comparable across studies (Bouman and Tuong, 2001). For this reason, the relative differences between WSI treatments and corresponding CF treatments have been used. For each study, yield data for every WSI-‐plot (YWSI) was normalized by the corresponding CF control plot (YCF).
YN = YWSI / YCF (eq. 1) Due to the normalization, YN values >1 indicate that the yield was higher in the WSI plot compared to the corresponding CF plot, and values <1 indicate that WSI treatment resulted in a decreased yield. The mean normalized yield, used as 'effect size' or alternately 'treatment effect', was calculated for each study, along with the standard deviation, standard
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error of the mean and 95% confidence intervals. The mean normalized yield is a simple measure of the effect of specific WSI treatments on yield. The method has weaknesses, but will be used as an indicator in this study. The treatment effect and therefore the differences in yield between WSI and CF were considered significant if the 95% confidence intervals did not overlap the value 1. A summary effect was calculated for all studies included in the meta-‐analysis. The summary effect is based on the mean normalized yields for all WSI/CF pairs, and not on the mean effect of each study. This approach results in the weight of each study in the summary effect being proportional to the sample size. Using effect sizes has some significant advantages over statistical significance testing. Unlike significance testing, which can only tell us whether the effect is or is not zero and which is also affected by sample size, using effect sizes allows an estimation of the magnitude of that effect (Borenstein et al., 2009). In this study, it means that we can not only tell if WSI management affects the yield, but also how large that effect is, and if certain types of WSI have a greater effect.
Figure 4. Distribution of all normalized yield values from the 19 field studies.
Oftentimes in meta-‐analyses, the log of the normalized yield is the preferred metric (see e.g. Vico et al., 2016; Carrijo et al., 2017), as the log helps make a skewed distribution of values more Gaussian, and therefore more suitable for calculating confidence intervals. The effect size used here is essentially a response ratio, as described by Borenstein et al. (2009), who also state that the log should be used for all calculations. Both the log and the exponential of the normalized yields were considered for use in this meta-‐analysis, but did not achieve a more Gaussian distribution of values than the normalized yields (figure 4) and were therefore dismissed.
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Table 1. Summary of the 19 experiments included in the meta-‐analysis.
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Table 1 continued.
5. Results
5.1. Yields under WSI management
Of the 19 studies, eight (1, 5, 7, 9, 10, 15, 18, 19) showed a significant difference in yield between the WSI and CF treatments (not including 6 and 16 that lacked confidence intervals) (figure 5). Of these eight studies, seven displayed a significant decline in yields under WSI treatment, and only one (18) showed an increase in yields under WSI management. Of the remaining 11 studies, where the differences were not considered significant due to confidence intervals overlapping with 1, seven had a treatment effect below 1, potentially indicating a tendency toward decreased yields. Three lay above 1, and one had a treatment effect of exactly 1. The summary effect lay slightly below 1, indicating a trend of decreased yields under WSI management, and the confidence intervals indicated that this effect was significant.
Figure 5. Treatment effects with 95% confidence intervals for each study, along with the summary effect size. Studies 6 and 16 only had one side-‐by-‐side comparison of WSI and CF each, and therefore do not have any confidence intervals.
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5.2. Regional differences in WSI yield
The scatter plot in figure 6 displays the relationship between WSI and CF yields for each side-‐by-‐side comparison identified in the 19 field studies. The overall distribution appears to align well with the 1:1 line, though scattering is seen both above and below the line. When the yields deviate from the 1:1 line, the deviation tends to be more pronounced in the direction of higher yields under CF. The chart indicates that though yields were oftentimes maintained under WSI, they rarely increased. The values in figure 6 have also been categorized depending on if the field experiment was conducted in East Asia (China, Taiwan, Japan, South Korea), Southeast Asia (Vietnam, Philippines) or South Asia (India). The scattering indicates no obvious pattern in terms of the ability of WSI management to maintain yields in different regions. The highest yields appear to have been achieved in East Asia, but since the various studies' yields are not directly comparable due to varying environmental conditions and management approaches, the actual yields are not reliable values for analysis. Some yields produced in experiments in South Asia appear fictitiously low, with yields below 2 t ha-‐1. These low yields have been attributed to the rice variety used (Bhaduri, 2017, personal communication).
Figure 6. Relationship between WSI yields and corresponding CF yields in three major regions in Asia.
Figure 7 is based on the same data as figure 6, but provides the summary effects for the three regions. As expected based on figures 5 and 6, the overall effect of WSI treatment was a decrease in yield, though this effect was not significant for the experiments conducted in South Asia. The summary effect for East Asia was very similar to South Asia, but with lower variability. Southeast Asia displayed a significant decrease in yields under WSI management.
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Figure 7. Summary effects for groupings of side-‐by-‐side comparison into regions; South, East and Southeast Asia. Error bars correspond to a 95% confidence interval. The summary effects contain 72 side-‐by-‐side comparisons for South Asia, 48 for Southeast Asia, and 59 for East Asia.
5.3. Influence of severity of WSI management on yield
The different WSI treatments have been classified into a number of categories (figure 8). The mild, moderate and severe AWD treatments have been grouped with treatments using drainage periods of a maximum of 2, 4, and 7 days, respectively. Figure 8 demonstrates a very close alignment between the regression line for 'mild AWD/<=2-‐day drainage' and the 1:1 line, indicating that very similar yields were attained in these WSI treatments as compared to corresponding CF treatments. As the severity of the AWD management and the length of the drainage periods increased, the scattering and corresponding regression lines became increasingly displaced from the 1:1 line. The high R2 values for all three categories indicate that the regression lines incorporate much of the variability.
Figure 8. Patterns in the relationship between yield and WSI method used. Mild AWD -‐ SWP potential >-‐10kPa or FWL >-‐15 cm, moderate AWD -‐ SWP between -‐10 and -‐30 kPa or FWL between -‐15 and -‐30 cm, severe AWD -‐ SWP <-‐30 kPa. Data from studies 7, 8, 11, 13, 16, 17, 19 and parts of study 14 was excluded due to not suiting any of the designated categories.
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The category 'mild AWD' corresponds to the safe AWD defined by Bouman et al. (2007), whereby the field water level should stay within -‐15 cm from the surface (figure 8). The -‐15 cm FWL has been paired with a SWP limit of -‐10 kPa, as the SWP normally stays above -‐10 kPa (measured at 15 cm depth) at a FWL of -‐15 cm (Lampayan et al., 2015). Bouman and Tuong (2001) found that yield decreases often became noticeable at SWPs between -‐10 and -‐30 kPa, and Brady and Weil (2008) have stated that field capacity often corresponds to SWPs ranging from -‐10 to -‐30 kPa. As rice is classified as a semiaquatic plant (GRiSP, 2013) and in the examined lowland settings is most commonly grown under submerged conditions (Lampayan et al., 2015), SWPs at field capacity have been classified as 'moderate AWD'. When using only the data from plots that were specifically stated to have been kept under 'mild AWD' conditions, the yields corresponded almost perfectly to those achieved under CF management (figure 9).
Figure 9. AWD treatments specifically stated to have been kept above a SWP of -‐10kPa and field water level depth of -‐15 cm.
When all categories were examined individually, some additional variability was discovered. Mild AWD and midseason drainage displayed yields on par with CF plots with relatively high precision (figure 10). It is worth noting that the midseason drainage category was based on a small sample made up of seven side-‐by-‐side comparisons. Yields appeared to have increased under the <=2-‐day drainage treatments, and have been maintained almost on par with CF yields under 4-‐day drainage treatments, though neither of these treatment effects were deemed significant at the 95% level. Significant yield decreases were seen for moderate and severe AWD, as well as for 7-‐day drainage periods. It is clear that the yields achieved under WSI management gradually decreased from mild, to moderate, to severe AWD, as well as when drainage periods were increased from 2, to 4, to 7-‐day intervals. Likewise, though yields were maintained under midseason drainage treatment, they decreased when the non-‐flooded conditions were maintained throughout the growing season.
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Figure 10. Summary effects and 95% confidence intervals for various WSI categories. Mild AWD -‐ SWP potential >-‐10kPa or FWL >-‐15 cm, moderate AWD -‐ SWP between -‐10 and -‐30 kPa or FWL between 15 and 30 cm, severe AWD -‐ SWP <-‐30 kPa. Data from studies 13 and 17 that lacked the necessary information to categorize the treatments were excluded. Number of side-‐by-‐side comparisons: mild AWD -‐ 53, moderate AWD -‐ 12, severe AWD -‐ 21, <=2-‐day drainage -‐ 36, 3 to 4-‐day drainage -‐ 25, 5 to 7-‐day drainage -‐ 6, midseason drainage -‐ 7, non-‐flooded -‐ 7.
5.4. Nitrogen fertilization effect on yields
Plotting yield against nitrogen (N) input showed an overall increase in yield with increasing N inputs, though the variability was large (figure 11). The regression lines indicate that the trend does not differ between CF and WSI management, with both irrigation treatments showing yields increasing at similar rates under increased N input.
Figure 11. Relationship between nitrogen input and yield in all CF and WSI plots. Studies 3, 15 and 19 lacked data on nitrogen and are not represented.
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6. Discussion
6.1. Rice yields under varying irrigation managements
If the effect sizes for the studies included in a meta-‐analysis display consistency a summary effect size is usually calculated, and otherwise the focus is shifted to estimating the dispersion of effect sizes (Borenstein et al., 2009). In this study the effect sizes are relatively consistent with 58% of the study effect sizes in the interval between 0.9 and 1.0, and 89% between 0.8 and 1.1 (figure 5). Calculating a summary effect size was therefore deemed suitable. The summary effect size for the 19 studies was established as 0.970 with the upper confidence interval limit at 0.0996 and the lower limit at 0.944 (95% confidence level). As can be seen in figure 5 the precision of the summary effect was considerably higher than for many of the individual studies. The summary effect indicated that there was an overall decrease in yields for plots under WSI treatments and that this difference was small though significant. However, the WSI treatments used in the different studies are highly variable making it more suitable to divide the treatments into categories and looking at the summary effect for these, which was done in figures 8, 9 and 10. Figures 8, 9 and 10 demonstrate that yield was not necessarily higher under continuous flooding compared to WSI management as long as one stayed within the limits of mild or 'safe' AWD, in this case defined as a minimum field water level of -‐15 cm or soil water potential of -‐10 kPa. The precision for mild AWD was high, indicating that the risk of yield penalty is likely to be low. Since the category included data from various experiments the precision also indicates that this is true across a range of different locations. Carrijo et al. (2017) used fewer classes and classified SWPs of -‐20 kPa as mild AWD, but when plotting data from treatments using SWP between -‐10 and -‐20 kPa in this study a decrease in yield was exhibited (data not shown). Carrijo et al.'s study did, however, contain a considerably larger number of side-‐by-‐side comparisons, indicating that the negative effect on yields of SWPs at -‐20 kPa may be non-‐significant over a larger sample size. Dividing the WSI types into the number of categories used in figure 10 resulted in several categories having relatively few observations, making the summary effects somewhat weaker. The non-‐flooded treatment exhibited high variability, which is probably a result of it being a broad category with low precision in terms of WSI approach. In figure 10, cycles using drainages with a maximum duration of 2 days appeared to actually increase yield for unknown reasons though the difference compared to CF was non-‐significant. The FWL or SWP reached during these treatments was difficult to estimate. Drainage rates and soil water retention capacities are influenced by soil texture and structure with coarser fractions resulting in faster drainage (Brady and Weil, 2008). The actual SWP or FWL achieved during the drainage periods can therefore differ from site to site depending on soil texture. The mild AWD and <=2-‐day drainage categories each had a similar number of observations. The higher variability found in the latter likely indicates that a set number of days of drainage is a considerably more
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unreliable measure compared to SWP or FWL in terms of judging the level of stress placed on the rice plants. The reliability of using set drainage periods is likely to be higher when local soil texture and water retention capacity is taken into consideration and adjustments are made accordingly. As discovered by Carrijo et al. (2017) who classified AWD treatments based on SWP and FWL, soil texture had no influence on yield. Their result is not surprising since a sandier soil using irrigation at -‐20 kPa would most likely have received slightly more frequent irrigations than needed in a soil with loamier or more clayey texture, resulting in similar success in terms of yields. If, on the other hand, irrigations are scheduled based on a regular interval of dry days as seen in some studies included in this meta-‐analysis, the SWP or FWL reached during those intervals will likely differ between a coarser sandy soil and a finer loamy soil, and thereby also affect the perceived success of any WSI management. In figure 10, a gradual decrease in yields is seen when going from mild to moderate to severe AWD and from 2-‐, to 4-‐, to 7-‐day drainage. The yield decline for severe AWD was much stronger than for 4-‐ or 7-‐ day drainage, again indicating that a set number of days is not easily equated to a certain degree of water stress as measured by SWP and FWL. In the mild AWD category Ye et al. (2013) had dry cycles extending for as long as 12 to 15 days, but due to the soil properties and the shallow groundwater table the SWP never dropped below -‐10kPa. Meanwhile, Kumar et al. (2016) reached a SWP of -‐30 kPa in less than four days. In essence, one of the most important factors for the success of WSI management is not strictly the duration of dry periods but perhaps rather the level of water stress experienced as mediated by dry cycle length and soil water retention capacity. As in this study, Bouman and Tuong (2001) identified differences in yields between experiments using the same level of water stress. The authors attributed the differences to rice variety drought response and variability in the number of dry cycles used as a result of weather variability and differing seepage and percolation rates between sites. This variability in the moderating variables is likewise a factor in this meta-‐analysis and is at least in part demonstrated by the scattering in figure 9 and to a certain extent the width of the confidence intervals in figure 10. It is of course possible that some of the variability which points to increased yields under WSI could be attributed to the beneficial effects of aerated conditions on certain aspects of rice growth. These effects include, for example, the nutrient release and decrease in redundant vegetative growth that has been identified by Ye at al. (2013) and Yang et al. (2017). A significant decrease in yields under WSI management was displayed by experiments conducted in Southeast Asia (figure 7). This summary effect is likely skewed as a result of this category containing data from study 5 by Cabangon et al. (2011), which contains plots with some of the most severe soil drying found in any of the studies in this meta-‐analysis, with soil water potentials allowed to drop to -‐50 and -‐80 kPa. The increase in yields that Belder et al. (2004) and Cabangon et al. (2004) mention with regards to AWD
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in China is not evident in figure 7. However, though most of the data in the East Asia category comes from China, some experiments were also conducted in Japan, South Korea and Taiwan, thereby possibly hiding any yield-‐increase trends in China. From a visual estimation, however, the yields in Japan and South Korea appear to be on par with those achieved in China with the few plots in Taiwan possibly being slightly less successful (appendix A for raw data). Based on the studies included in this analysis it does not seem as if the yields were on average higher in China under WSI management, though they were oftentimes maintained. The effect of nitrogen input on yields did not appear to differ between water managements. Yields under WSI management increased with increased N input at the same rate as under CF management. The findings are in accordance with the recommendations by Bouman et al. (2007) that N fertilizer management does not need to be altered when transitioning from continuous flooding to WSI, or more specifically, AWD management.
6.2. Environmental implications of water-‐saving irrigation
6.2.1. Greenhouse gas emissions and soil quality
Flooded rice fields are a source of methane and a sink for CO2 (Bouman et al., 2007). Under the anaerobic conditions found in flooded rice paddy environments, emissions of the strong greenhouse gas methane are inherent (Liping and Erda, 2001). More aerobic conditions instead lead to increases in CO2 emissions (Linquist et al., 2015). Haque et al. (2016a) found that though implementing a 30-‐day midseason drainage period during the growth season increased the CO2 emissions, the decreases in methane emissions reduced the global warming potential of the rice paddies by 17-‐31% whilst maintaining yields. According to Linquist et al. (2015) the contribution of CO2 from rice farming to the global warming potential of agricultural emissions in negligible. Kumar et al. (2010) have found, however, that using AWD with a soil-‐drying threshold of SWP -‐30 kPa increased the emissions of CO2 and nitrous oxide, another strong greenhouse gas, enough to offset the beneficial effects of AWD on methane. Despite the claim that the CO2 emissions are negligible, Linquist et al. (2015) have also stated that transitioning from flooded rice monocropping where the soil carbon sequestration is high to more aerobic conditions could lead to losses of SOC (Wu et al., 2011). Sahrawat (2005) highlights the various benefits to soil fertility of growing rice under flooded conditions. The beneficial effects of flooding include neutralized soil pH, increased mineralization and availability of nutrients, and increased SOM content. These benefits could potentially be lost under aerobic soil conditions. Bouman et al. (2007) state that the beneficial effects of flooding on soil quality gradually decrease when soils are no longer kept flooded but claim that negative changes are not present when staying within the limits of safe AWD. The discussion on water-‐saving irrigation efforts should include careful consideration of consequences for soil fertility and the sustainability of rice production (Sahrawat, 2005; Yang et al., 2017). Lal (2010) emphasises the great importance of the SOC pool for maintaining soil quality and its role in achieving high
25
agricultural production. SOC plays an important role in improving soil structure and aggregation, water and nutrient retention, biomass production, mitigating non-‐point source pollution and decreasing erosion (Brady and Weil, 2008; Lal, 2010). Carrijo et al. (2017) found that yield decreases under both mild and severe AWD were greater in soils with SOC <1% compared to those found in soils with SOC >1%. Hence, though mild AWD might not negatively influence the SOM content of the soil, the SOM content likely has an effect on the success of AWD. Rice paddy systems have been shown to sequester organic carbon more effectively than land devoted to other uses such as arable cropping and orchards (Wu, 2011). By analysing 2700 samples taken in subtropical China, Wu found that the SOC contents were considerably higher in paddy field soils. Additionally, Wu found that the carbon stocks had increased by a factor of 1.67 between 1979 and 2003, attributing this change to the increase in rice production that occurred during the same period and concluding that rice paddy ecosystems have potential in terms of sequestering carbon. Likewise, Pan et al. (2010) investigated SOC accumulation in China's croplands, comparing soil monitoring data from rice paddy soils and dryland crop soils. Over the study period, increases in SOC stocks were found in ~70% of both soil types. Pan et al. (2010) suggest that the positive trend may in part be attributed to crop residue return and good fertilization practices. However, both the initial SOC stocks and the accumulation rates were considerably higher in the rice paddy soils, again displaying a significantly higher sequestration potential. In contrast, we have the findings of Witt et al. (2000) comparing a rice-‐rice cropping system with a rice-‐maize rotation. The rice-‐rice system where the crops were grown in submerged conditions experienced a 10-‐14% increase in SOC during a two-‐year period. In the rice-‐maize rotation, however, where one of the crops were grown under upland conditions a slight decrease was instead found due to a 33-‐41% increase in carbon mineralization as a result of increased microbial activity. Witt et al.'s study is certainly relevant and provides an example of the potential risks to the SOC pool of growing crops under aerobic conditions. However, the findings of Pan et al. (2010) and Wu (2011) are based on large amounts of soil monitoring data covering much longer time periods. Their results indicate that though SOC accumulate faster in rice paddies, achieving a positive SOC/SOM balance under more aerobic conditions is not impossible under the right management. According to Dawe et al. (2000) who compared 30 long-‐term experiments in rice-‐upland systems and rice monocultures, yields remained stable in the majority of experiments in both systems. The yield declines that did occur were attributed to the depletion of nutrients and the effects of prolonged wetness on soil properties. More specifically, yield declines in some rice-‐upland experiments were attributed to a decrease in the indigenous N supply as a result of a decline in the SOM content; an effect that was not seen in the rice monocultures. In some of the rice monocultures, however, frequent cropping cycles with very limited aerobic fallow periods in between led to accumulation of large amounts of partly decomposed lignin residues and an increased phenolic
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content in the SOM, negatively impacting N mineralization and therefore also yields (Dawe et al., 2000). From Dawe et al.'s (2000), Pan et al.'s (2010), and Wu's (2011) findings it seems clear that continuous submergence during the rice growth period has beneficial effects in terms of promoting the accumulation of SOM in the soil. However, the same submergence can also result in changes in SOM composition that instead have a negative influence on soil nutrient status and yields. It could perhaps be speculated that flooding during the crop period is beneficial for SOM accumulation if the soil is allowed to dry and become aerated in the fallow periods between crops. Straw incorporation has been recommended as a measure to increase carbon sequestration as well as crop yields in agricultural soils (Lu, 2015). The practice is widely employed to improve soil fertility. However, straw application provides more substrate for methane production and has also been found to stimulate methane emissions from both SOM and rice root organic carbon (Yuan et al., 2014). The increased carbon sequestration has beneficial effects in terms of mitigating greenhouse gas emissions, but is offset by the increase in methane production. The result is an increase in the global warming potential by an estimated factor of ~2.16 following straw return (Lu et al., 2010). If WSI does have a negative effect on the SOC pool in rice paddy soils, and other beneficial characteristics maintained under flooded conditions, the effects could be significant. As Carrijo et al. (2017) found that yields under AWD were positively affected by higher SOM content, any decreases in SOM caused by aerobic conditions under AWD could in turn negatively impact the success of the AWD itself. In other words, implementing WSI management might in the future lead to decreased soil quality, threatening the ability to maintain WSI yields in the long run.
6.2.2. Nutrient and herbicide losses
Agricultural non-‐point pollution causes significant environmental problems including eutrophication, which is an urgent challenge in, for example, the agriculturally intensive Taihu Lake Region in China (Yang et al., 2013). WSI has been found to significantly reduce the amount of non-‐point source pollution from rice paddies, thereby exhibiting potential for improving water quality in surrounding environments (Choi et al., 2015). Liang et al. (2013) found that compared to continuously flooded fields AWD decreased cumulative N and P losses via surface runoff by ~23 to 30 and ~27 to 32%, respectively. According to Yang et al. (2013) controlled irrigation reduced N export through ammonia volatilization, runoff and leaching by ~21 to 26% compared to continuous flooding. Site-‐specific nutrient management when combined with AWD led to further decreases in N and P losses. The reductions in runoff export were attributed to fewer runoff events under AWD, as a result of the lower field water levels acting as a buffer during heavy rainfall events (Liang et al., 2013; Yang et al., 2013).
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On the other hand, standing water in combination with puddling and transplanting tends to control weeds well in continuously flooded rice plots. The implementation of water-‐saving irrigation can result in farmers facing more issues with weeds and therefore lead to higher herbicide uses in the fields, resulting in an increased spread of herbicide residues to surrounding environments (Bouman et al., 2007). Hence, WSI management is likely to have both positive and negative effects on water quality in surrounding environments.
6.3. Implementation of water-‐saving irrigation management
There are a number of potential practical reasons AWD irrigation has not been widely adopted worldwide. In many places rice is predominantly grown in lowlands during the wet season, making it impossible to drain the fields. Furthermore, when connected to an irrigation system individual farmers may not be able to control water levels in their fields, and if growing rice under rainfed conditions it is risky to drain the field in case of drought (Linquist et al., 2015). Water-‐saving irrigation techniques as presented in the academic literature appear to often have been developed with the primary purpose of decreasing water use. Hence, they are perhaps suitable in situations of imposed, physical water scarcity where a small yield decline is an acceptable trade-‐off. To make self-‐imposed water-‐saving initiatives attractive to farmers it would seem likely that the maintenance of yields is necessary. As has been expressed by Cabangon et al. (2011), if yields are maintained with a water saving rate of 20% (-‐10 kPa), as found in their experiment, WSI is likely to appeal to farmers. However, at a slightly higher degree of water stress resulting yield penalties are unlikely to make AWD an appealing option unless water is very scarce. Individual farmers have to weigh potential yield decreases against water savings when judging the financial implications of implementing AWD (Bouman et al., 2007). Though finding relatively small savings at the field level using WSI methods, Belder et al. (2004) reason that the savings become significant when scaled up. If water saved in one field is used to irrigate new land the total rice production can be increased (Bouman et al., 2001). The constant increase in the world's population places pressure on us to produce "more rice with less water" (Tuong et al., 2005, p. 231). A similar sentiment is echoed by Lal (2010), who emphasizes the need for eco-‐efficiency in agricultural production. In essence, the challenge is to produce more food using less of our resources, which can only be done by minimising input losses and maintaining the land's sustainability. There is a global need for soil restoration to increase agricultural sustainability by balancing inputs and outputs, improving currently negative nutrient and carbon cycles, and ensuring the provision of ecosystem services (Lal, 2010).
6.4. Methodological and data weaknesses
Factors that are likely of the highest importance to the success of WSI methods are rarely documented in the literature, making it difficult to compare studies and interpret results. Such factors include, for example, the duration and frequency of dry cycles and
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the degree of water stress experienced during these cycles (Belder et al., 2004, Carrijo et al., 2017). Similar problems were encountered during the data collection process, leading to the exclusion of multiple articles for not providing sufficient information on the specifics of water management in the experiments. Publication bias is an oft-‐mentioned problem in meta-‐analysis (Borenstein et al., 2009). No assessment of publication bias was conducted in this study, but the effect is hopefully relatively mild since much data was taken from studies where focus was placed on other factors than water management. For this reason data was often reported even if the effect of water management on yield was deemed to be non-‐significant by the author. It did occasionally occur, however, that studies initially deemed to be relevant had to be excluded entirely due to the authors excluding data on water management specifics after finding its effect on rice yield to be non-‐significant. The amounts of water saved through the implementation of WSI in the various studies are difficult to compare due to some studies failing to report such data and many authors measuring water saved in different ways that are not easily standardised. Such data could most likely be extracted and converted in many cases but would more easily have been examined if 'water savings' had been used as a criterion for inclusion into the analysis. The analysis conducted in this study could, with more comprehensive statistical methods, be done in a more robust fashion producing results with higher precision and reliability, and preferably include an estimate of publication bias. The results are, despite this, hopefully relevant and serve as an indication of the success and potential challenges of implementing WSI management in rice farming.
6.5. Future research
The data set produced for this study contains considerably more data than has been used in the analysis and has potential for a number of other applications. As previously mentioned it also includes information on SOM/SOC, soil texture and classification, number of dry cycles, timing of N input, irrigation water input and rice variety used. As is evident from this study and the meta-‐analyses conducted by Bouman and Tuong (2001) and Carrijo (2017), much research interest has been shown in the potential of various forms of water-‐saving irrigation in terms of maintaining yields, saving water and minimizing greenhouse gas emissions. Separately, plenty of research has been conducted on the carbon sequestration abilities of rice paddies compared to other soils (e.g. Pan et al., 2010; Wu, 2011). Meanwhile, it has long since been shown that exposing soils to aerobic conditions increases soil microbial activity and therefore also affects nutrient balances and soil organic matter content (Sahwrawat, 2005). Yet, few studies seem to have been conducted on the consequences of WSI techniques with intermittent or extended cycles of aerobic soil conditions on SOM levels and subsequent consequences for soil fertility and sustainability. With growing populations leading to
29
increasing food consumption, the ability of these soils to continuously produce high yields becomes an urgent issue. This area warrants increased interest.
7. Conclusions
Carefully managed water-‐saving irrigation where the soil water potential was kept above -‐10 kPa or the field water level above -‐15 cm maintained yields whilst saving water. Yields were likewise maintained when using short drainage intervals of up to two or possibly four days, though the influence of soil texture made it difficult to judge what level of water-‐stress was reached during the dry cycles. Based on a small number of side-‐by-‐side comparisons, yields were also maintained when implementing a 30-‐day midseason drainage. These findings are believed to be relatively consistent for a wide range of settings in East, Southeast and South Asia. When increasing the severity of the water-‐saving efforts, negative effects on yields emerged and became increasingly pronounced. WSI management also comes with a number of environmental implications that should be considered in addition to saving water. Various forms of WSI management have frequently been stated to decrease the global warming potential of rice farming and have also been found to decrease the amounts of fertilizers that are lost from the field. Whether or not SOM content, and therefore soil fertility, can be maintained when transitioning to WSI from continuous flooding is not clear but should be examined further. In addition, decreased flooding duration could potentially lead to more weeds and higher herbicide use and therefore more herbicide residues spreading to the environment. These various interactions should be more thoroughly considered in the discussion of the implementation of WSI management and special attention should be paid to the connection between WSI and long-‐term soil quality.
Acknowledgements
Thank you to my thesis supervisor, Stefano Manzoni, for all your support and ideas throughout the course of this degree project and for helping me explore methods that I had previously not encountered. Thank you also to Steve Lyon for the valuable feedback, and to Lars-‐Ove Westerberg for practical advice both on matters relating to this degree project, as well as career-‐related goals. Finally, thank you to Anders Fridfeldt for your enthusiasm and presence throughout my time at the Geography programme.
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Appendix A
34
Appendix A ID Study Plot Location Coordinates Year Crop
period WSI type Rice
yield SOC/SOM
Irriga-‐tion input
Water input (I+R)
N input
1 Arora et al., 2006 1 Punjab Agricultural University Research Farm, Ludhiana, India
30°54'N, 75°48'E
2000 June-‐April
CF 8.7 0.3 g hg-‐1 SOC -‐ -‐ 120
2 CF 8.5 -‐ -‐ 120 3 II 7.9 -‐ -‐ 120 4 II 8 -‐ -‐ 120 5 2001 June-‐
April CF 7 -‐ -‐ 120
6 CF 7.5 -‐ -‐ 120 7 CF 7.2 -‐ -‐ 120 8 II 6.6 -‐ -‐ 120 9 II 6.9 -‐ -‐ 120 10 II 7.2 -‐ -‐ 120 11 CF 6.6 -‐ -‐ 120 12 CF 6.8 -‐ -‐ 120 13 CF 7.1 -‐ -‐ 120 14 II 6.5 -‐ -‐ 120 15 II 6.8 -‐ -‐ 120 16 II 6.8 -‐ -‐ 120 17 2002 June-‐
April CF 7.7 -‐ -‐ 120
18 CF 7.3 -‐ -‐ 120 19 CF 8 -‐ -‐ 120 20 II 6.8 -‐ -‐ 120 21 II 7.4 -‐ -‐ 120 22 II 7.4 -‐ -‐ 120 23 July-‐April CF 7 -‐ -‐ 120 24 CF 7 -‐ -‐ 120 25 CF 7.5 -‐ -‐ 120 26 II 6.5 -‐ -‐ 120 27 II 6.9 -‐ -‐ 120 28 II 6.4 -‐ -‐ 120 2 Belder et al., 2004 29 Tuanlin, Hubei province,
China 30°52'N, 112°11'E
1999 Summer CF 9.2 1.03 % SOM 588 mm 965 mm 180
30 CF 8.4 588 mm 965 180 31 CF 8.1 588 mm 965 180 32 AWD 6.8 501 mm 878 180 33 AWD 8 501 mm 878 180 34 AWD 8.4 501 mm 878 180 35 Muñoz, Nueva Ecija 15°40'N, 2001 Dry CF 4.4 1.77 % SOM 511 mm 602 0
35
Province, Philippines 120°54'E season 36 CF 6.7 511 mm 602 90 37 CF 7.2 511 mm 602 180 38 AWD 4.1 427 mm 518 0 39 AWD 6.4 427 mm 518 90 40 AWD 7.6 427 mm 518 180 41 AWD part
season 5 489 mm 580 0
42 AWD part season
6.7 489 mm 580 90
43 AWD part season
7.7 489 mm 580 180
3 Bhaduri et al., 2014 44 Indian Agricultural Research Institute, New Delhi, India
28°38'13''N, 77°09'46''E
2008 July-‐Oct CF 0.56 4.8 g kg-‐1 -‐ -‐
45 CF 0.77 -‐ -‐ 46 CF 0.94 -‐ -‐ 47 CF 0.89 -‐ -‐ 48 CF 0.72 -‐ -‐ 49 CF 0.62 -‐ -‐ 50 CF 0.69 -‐ -‐ 51 CF 0.68 -‐ -‐ 52 CF 0.65 -‐ -‐ 53 CI 1d 0.68 -‐ -‐ 54 CI 1d 1.1 -‐ -‐ 55 CI 1d 1.41 -‐ -‐ 56 CI 1d 1.12 -‐ -‐ 57 CI 1d 0.88 -‐ -‐ 58 CI 1d 0.75 -‐ -‐ 59 CI 1d 0.74 -‐ -‐ 60 CI 1d 0.74 -‐ -‐ 61 CI 1d 1.24 -‐ -‐ 62 CI 3d 0.72 -‐ -‐ 63 CI 3d 1.02 -‐ -‐ 64 CI 3d 1.22 -‐ -‐ 65 CI 3d 1.11 -‐ -‐ 66 CI 3d 0.94 -‐ -‐ 67 CI 3d 0.9 -‐ -‐ 68 CI 3d 0.92 -‐ -‐ 69 CI 3d 0.83 -‐ -‐ 70 CI 3d 0.98 -‐ -‐ 71 CF 0.09 -‐ -‐ 72 CF 0.15 -‐ -‐ 73 CF 0.17 -‐ -‐ 74 CF 0.16 -‐ -‐
36
75 CF 0.13 -‐ -‐ 76 CF 0.11 -‐ -‐ 77 CF 0.12 -‐ -‐ 78 CF 0.12 -‐ -‐ 79 CF 0.1 -‐ -‐ 80 CI 1d 0.08 -‐ -‐ 81 CI 1d 0.15 -‐ -‐ 82 CI 1d 0.16 -‐ -‐ 83 CI 1d 0.16 -‐ -‐ 84 CI 1d 0.12 -‐ -‐ 85 CI 1d 0.12 -‐ -‐ 86 CI 1d 0.11 -‐ -‐ 87 CI 1d 0.12 -‐ -‐ 88 CI 1d 0.1 -‐ -‐ 89 CI 3d 0.06 -‐ -‐ 90 CI 3d 0.1 -‐ -‐ 91 CI 3d 0.1 -‐ -‐ 92 CI 3d 0.1 -‐ -‐ 93 CI 3d 0.09 -‐ -‐ 94 CI 3d 0.09 -‐ -‐ 95 CI 3d 0.09 -‐ -‐ 96 CI 3d 0.09 -‐ -‐ 97 CI 3d 0.07 -‐ -‐ 4 Cabangon et al.,
2004 98 Jinhua, Zhejiang
Province, China 29°5'N, 119°47'E
1999 Apr-‐July CF 4.3 2.03 % SOC 124 mm 934 mm 0
99 CF 5.3 124 mm 934 mm 150 100 CF 5.4 124 mm 934 mm 150 101 CF 5.6 124 mm 934 mm 150 102 AWD 4.1 124 mm 934 mm 0 103 AWD 5.3 124 mm 934 mm 150 104 AWD 5.4 124 mm 934 mm 150 105 AWD 5.5 124 mm 934 mm 150 106 Aug-‐Oct CF 4.4 239 mm 570 mm 0 107 CF 5.5 239 mm 570 mm 150 108 CF 5.7 239 mm 570 mm 150 109 CF 5.7 239 mm 570 mm 150 110 AWD 4.3 224 mm 554 mm 0 111 AWD 5.6 224 mm 554 mm 150 112 AWD 5.4 224 mm 554 mm 150 113 AWD 5.6 224 mm 554 mm 150 114 2000 Apr-‐July CF 3.2 272 mm 863 mm 0 115 CF 5.3 272 mm 863 mm 150 116 CF 5.8 272 mm 863 mm 150 117 CF 5.4 272 mm 863 mm 150 118 AWD 3.4 229 mm 820 mm 0
37
119 AWD 5.5 229 mm 820 mm 150 120 AWD 5.8 229 mm 820 mm 150 121 AWD 5.5 229 mm 820 mm 150 122 Aug-‐Oct CF 3.7 295 mm 698 mm 0 123 CF 4.8 295 mm 698 mm 150 124 CF 4.5 295 mm 698 mm 150 125 CF 4.9 295 mm 698 mm 150 126 AWD 3.7 203 mm 605 mm 0 127 AWD 4.6 203 mm 605 mm 150 128 AWD 5 203 mm 605 mm 150 129 AWD 5.1 203 mm 605 mm 150 Also in Belder et al.,
2004 130 Tuanlin, Hubei Province,
China 30°52'N, 112°11'E
May-‐Sep CF 4.4 1.03 % SOC 415 mm 863 mm 0
131 CF 8.2 415 mm 863 mm 180 132 CF 8.1 415 mm 863 mm 180 133 CF 8.7 415 mm 863 mm 180 134 AWD 4.5 339 mm 787 mm 0 135 AWD 8.9 339 mm 787 mm 180 136 AWD 8.4 339 mm 787 mm 180 137 AWD 8.7 339 mm 787 mm 180 5 Cabangon et al.,
2011 138 International Rice
Research Institute, Los Baños, Philippines
14°30'N, 121°01'E
2004 Dry season
CF 3.9 19.8 g kg -‐1 C 774 mm 840 mm -‐
139 CF 6.1 774 mm 840 mm 180 140 CF 5.8 774 mm 840 mm 110 141 CF 5.6 774 mm 840 mm 150 142 CF 6.4 774 mm 840 mm 250 143 AWD-‐20SWP 3.2 714 mm 780 mm -‐ 144 AWD-‐20SWP 5.4 714 mm 780 mm 180 145 AWD-‐20SWP 5 714 mm 780 mm 110 146 AWD-‐20SWP 5.6 714 mm 780 mm 150 147 AWD-‐20SWP 5.6 714 mm 780 mm 190 148 AWD-‐80SWP 2.6 592 mm 658 mm -‐ 149 AWD-‐80SWP 4.5 592 mm 658 mm 180 150 AWD-‐80SWP 4.5 592 mm 658 mm 110 151 AWD-‐80SWP 4.3 592 mm 658 mm 130 152 AWD-‐80SWP 4.8 592 mm 658 mm 170 153 2005 Dry
season CF 4.7 939 mm 1071 mm -‐
154 CF 6.7 939 mm 1071 mm 180 155 CF 5.8 939 mm 1071 mm 75 156 CF 5.9 939 mm 1071 mm 105 157 CF 6.7 939 mm 1071 mm 135 158 CF 4.6 939 mm 1071 mm -‐ 159 CF 6.8 939 mm 1071 mm 180
38
160 CF 5.3 939 mm 1071 mm 75 161 CF 6.3 939 mm 1071 mm 105 162 CF 7.5 939 mm 1071 mm 135 163 AWD-‐10SWP 3.5 798 mm 930 mm -‐ 164 AWD-‐10SWP 6.7 798 mm 930 mm 180 165 AWD-‐10SWP 5.1 798 mm 930 mm 85 166 AWD-‐10SWP 5.9 798 mm 930 mm 105 167 AWD-‐10SWP 6.5 798 mm 930 mm 135 168 AWD-‐10SWP 4 798 mm 930 mm -‐ 169 AWD-‐10SWP 7.2 798 mm 930 mm 180 170 AWD-‐10SWP 5.5 798 mm 930 mm 75 171 AWD-‐10SWP 6.2 798 mm 930 mm 105 172 AWD-‐10SWP 6.9 798 mm 930 mm 135 173 AWD-‐50SWP 3.6 765 mm 897 mm -‐ 174 AWD-‐50SWP 5.9 765 mm 897 mm 180 175 AWD-‐50SWP 4.8 765 mm 897 mm 75 176 AWD-‐50SWP 5.2 765 mm 897 mm 105 177 AWD-‐50SWP 6 765 mm 897 mm 135 178 AWD-‐50SWP 3.7 765 mm 897 mm -‐ 179 AWD-‐50SWP 6.1 765 mm 897 mm 180 180 AWD-‐50SWP 5 765 mm 897 mm 75 181 AWD-‐50SWP 5.9 765 mm 897 mm 105 182 AWD-‐50SWP 5.6 765 mm 897 mm 135 6 Choi et al., 2015 183 Kangwon National
University, northeastern Korea
37°52'11N, 127°44'36''E
2011 May-‐Sept CF 0.134 28 g kg-‐1 6213.4 m3 ha-‐1
110
184 SRI 0.157 3266.7 m3 ha-‐1
110
7 Haque et al., 2016a 185 Gyeongsang National University Experimental Farm, Jinju, South Korea
36°50'N, 128°26'E
2013 June-‐Oct CF 5.5 20.4 g kg-‐1 SOM -‐ 90
186 CF 8.7 -‐ 90 187 CF 7.3 -‐ 90 188 CF 6.7 -‐ 90 189 ID 5.3 -‐ 90 190 ID 8.5 -‐ 90 191 ID 7.3 -‐ 90 192 ID 6.6 -‐ 90 8 Haque et al., 2016b 193 Gyeongsang National
University Experimental Farm, Jinju, South Korea
36°50'N, 128°26'E
2011 June-‐Oct CF 6.8 8.5 g kg-‐1 SOC -‐ -‐ 90
194 MD 6.7 -‐ -‐ 90 195 2012 June-‐Oct CF 6.5 -‐ -‐ 90 196 MD 6.6 -‐ -‐ 90 9 Jalota et al., 2011 197 Punjab Agricultural 30°56'N 2008 July-‐ CF 7.56 -‐ 1975 mm -‐ 0
39
University, Ludhiana, India
75°52'E Nov/Dec
198 CF 8.39 -‐ 1975 mm -‐ 60 199 CF 9.59 -‐ 1975 mm -‐ 120 200 CF 9.73 -‐ 1975 mm -‐ 180 201 2-‐day drainage 7.77 -‐ 1695 mm -‐ 0 202 2-‐day drainage 8.29 -‐ 1695 mm -‐ 60 203 2-‐day drainage 9.2 -‐ 1695 mm -‐ 120 204 2-‐day drainage 9.4 -‐ 1695 mm -‐ 180 205 4-‐day drainage 7.14 -‐ 1375 mm -‐ 0 206 4-‐day drainage 7.69 -‐ 1375 mm -‐ 60 207 4-‐day drainage 8.39 -‐ 1375 mm -‐ 120 208 4-‐day drainage 8.42 -‐ 1375 mm -‐ 180 209 6-‐day drainage 6.57 -‐ 1135 mm -‐ 0 210 6-‐day drainage 7.56 -‐ 1135 mm -‐ 60 211 6-‐day drainage 8.35 -‐ 1135 mm -‐ 120 212 6-‐day drainage 8.34 -‐ 1135 mm -‐ 180 10 Kumar et al., 2016 213 Central Rice Research
Institute, Cuttack, India 20°27'07.45''N, 85°56'31.60''E
2014 Dec2013-‐April
CF 4.80 0.49 % SOC 1220 mm 1302.3 mm 100
214 AWD-‐20SWP 4.72 828 mm 910.3 mm 100 215 AWD-‐30SWP 4.69 684 mm 766.3 mm 100 216 AWD-‐40SWP 3.75 656 mm 738.3 mm 100 217 AWD-‐50SWP 3.13 624 mm 706.3 mm 100 218 AWD-‐60SWP 2.35 585 mm 667.3 mm 100 219 2015 Dec2014-‐
April CF 5.08 1180 mm 1252 mm 100
220 AWD-‐20SWP 4.97 852 mm 924 mm 100 221 AWD-‐30SWP 4.92 768 mm 840 mm 100 222 AWD-‐40SWP 3.81 690 mm 762 mm 100 223 AWD-‐50SWP 3.30 661 mm 733 mm 100 224 AWD-‐60SWP 2.76 630 mm 702 mm 100 11 Li et al., 2007 225 Diangqiao township,
Haining City, Zheijang province, Chiina
30°26'N, 120°39'E
2001 June-‐? CF 7.11 23.11
g kg-‐1 SOM 733 mm 1388 mm 135
226 NF 7.02 201 mm 856 mm 135 227 Guodian township,
Haining city, Zheijang province, China
30°27'N, 120°36'E
2001 June-‐? CF 7.065 23.30
g kg-‐1 SOM 735 mm 1408 mm 135
228 NF 7.92 250 mm 923 mm 135 229 Yuanpu township,
Hangzhou city, Zheijang province, China
30°16'N, 120°12'E
2001 June-‐? CF 6.225 34.9 g kg-‐1 SOM 668 mm 1360 mm 135
230 NF 5.91 278 mm 970 mm 135
40
231 Duntou Town of Lanxi, Zheijang province, China
29°19'N, 119°43'E
2001 June-‐? CF 9 23.79
g kg-‐1 SOM 947 mm 1554 mm 135
232 NF 8.67 310 mm 917 mm 135 233 Dengtan Town of
Xincheng county, Zheijang province, China
29°25'N, 120°46'E
2001 June-‐? CF 7.47 26.6 g kg-‐1 SOM 858 mm 1388 mm 135
234 NF 4.26 0 mm 530 mm 135 12 Liang et al., 2013 235 Jingshan Agricultural
Research Station, China 30°21'N, 119°53'E
2009 July-‐Oct CF 7.125 28.6 g kg -‐1 SOM
576 mm -‐ 240
236 AWD 7.078 499 mm -‐ 240 237 CF 7.256 700 mm -‐ 240 238 AWD 7.187 600 mm -‐ 240 239 Shuangqiao Agricultural
Research Station, China 30°50'N, 120°40'E
2010 July-‐Oct CF 7.306 35.3 g kg -‐1 SOM
497 mm -‐ 200
240 AWD 7.234 360 mm -‐ 200 13 Lin et al., 2012 241 Ecological Experiment
Station of Red Soil, Chinese Academy of Sciences, Yingtan, Jiangxi Province, China
28°15'N, 116°55'E
2008/09
July-‐Nov CF 5.7 -‐ 650? mm -‐ 150
242 AWD 5.4 -‐ 480? mm -‐ 150 243 CF 4.9 -‐ 715? mm -‐ 150 244 AWD 4.6 -‐ 560? mm -‐ 150 14 Nhan et al., 2016 245 Hai Truong, Ta Danh
village, Tri Ton district, An Giang Province, Vietnam
10°24'43''N, 105°06'19''
2011-‐12
Dec-‐March
CF 6.3 15.94
% SOM 1871 ± 328
m3 ha-‐1
-‐ 115
246 AWD -‐15cm 6.8 881 ± 61
m3 ha-‐1
-‐ 115
247 AWD -‐30cm 6.4 641 ± 16
m3 ha-‐1
-‐ 115
248 2012 May-‐July CF 6.2 -‐ -‐ 115 249 AWD -‐15cm 6.4 -‐ -‐ 115 250 AWD -‐30cm 6.2 -‐ -‐ 115 251 2012 Aug-‐Nov CF 4.9 -‐ -‐ 115 252 AWD -‐15cm 5.0 -‐ -‐ 115 253 AWD -‐30cm 4.6 -‐ -‐ 115 254 2012
-‐13 Nov-‐feb/March
CF 7.4 3336 m3 ha-‐1
-‐ 115
255 AWD -‐15cm 7.7 2863 m3 ha-‐1
-‐ 115
256 AWD -‐30cm 7.3 2096 m3 ha-‐1
-‐ 115
257 2013 March-‐ CF 5.4 4030 m3 -‐ 115
41
July ha-‐1 258 AWD -‐15cm 5.2 3436 m3
ha-‐1 -‐ 115
259 AWD -‐30cm 5.3 2944 m3 ha-‐1
-‐ 115
260 2013 July-‐Nov CF 4.7 -‐ -‐ 115 261 AWD -‐15cm 4.8 -‐ -‐ 115 262 AWD -‐30cm 4.7 -‐ -‐ 115 15 Pascual and Wang,
2017 263 National Pingtung
University of Science and Technology, Taiwan
22°38'39''N, 120°36'35''E
2016 Jan-‐June CF 9.72 -‐ 59300 m3 ha-‐1
5720 m3 ha-‐1
-‐
264 II-‐3 8.04 -‐ 26400 m3 ha-‐1
5720 m3 ha-‐1
-‐
265 II-‐7 7.46 -‐ 15600 m3 ha-‐1
5720 m3 ha-‐1
-‐
266 CF 10.46 -‐ 59300 m3 ha-‐1
5720 m3 ha-‐1
-‐
267 II-‐3 10.26 -‐ 26400 m3 ha-‐1
5720 m3 ha-‐1
-‐
268 II-‐7 9.83 -‐ 15600 m3 ha-‐1
5720 m3 ha-‐1
-‐
16 Rahman et al., 2013 269 Takasaka, near Yamagata University, Tsuruoka, Japan
38°43'18''N, 139°49'19'E
2011/12
May-‐Sept CF 5.774 25.7 g kg-‐1 -‐ -‐ 50
270 CF-‐S 6.228 -‐ -‐ 50 271 NF 5.66 -‐ -‐ 50 17 Yang et al., 2015,
Yang et al., 2013 272 Kunshan Irrigation and
Drainage Experiment Station, Taihu Lake region, China
31°15'15''N, 120°57'43''E
2009 June-‐Oct CF + FFP 10.3 21.9 g kg-‐1 635 mm -‐ 324.6
273 CF + SSNM 9.98 635 mm -‐ 184.88
274 CI + FFP 9.89 233 mm -‐ 324.6 275 CI + SSNM 9.65 233 mm -‐ 184.8
8 276 2010 June-‐Oct CF + FFP 9.26 645 mm -‐ 302.7 277 CF + SSNM 9.07 645 mm -‐ 198 278 CI + FFP 9.36 263 mm -‐ 302.7 279 CI + SSNM 9.17 263 mm -‐ 198 18 Ye et al., 2013 280 Qianxi village, Yuhang
town of Zheijian Province, Taihu Lake region, China
30°21'N, 119°53'E
2010 June-‐Nov CF 4.6451 21.75
g kg-‐1 443.6 mm 1023 mm 0
281 CF 7.5211 443.6 mm 1023 mm 240 282 CF 7.2828 443.6 mm 1023 mm 240
42
283 CF 8.3717 443.6 mm 1023 mm 240 284 AWD 4.8986 257.8 mm 837.2 mm 0 285 AWD 7.9615 257.8 mm 837.2 mm 240 286 AWD 7.6539 257.8 mm 837.2 mm 240 287 AWD 8.8856 257.8 mm 837.2 mm 240 288 2011 July-‐Nov CF 4.4082 414.3 mm 1078 mm 0 289 CF 7.5622 414.3 mm 1078 mm 240 290 CF 7.3517 414.3 mm 1078 mm 240 291 CF 8.3861 414.3 mm 1078 mm 240 292 AWD 4.6456 298.2 mm 962.7 mm 0 293 AWD 8.0356 298.2 mm 962.7 mm 240 294 AWD 7.7944 298.2 mm 962.7 mm 240 295 AWD 9.0783 298.2 mm 962.7 mm 240 19 Yu and Chen, 2004 296 Shenyang Experimental
Station of Ecology, Chinese Academy of Sciences
41°32'N, 122°23'E
-‐ May-‐Oct CF 9.7 1.51 % SOM -‐ -‐
297 CF 11.5 2.12 % SOM -‐ -‐ 298 NF 8.8 1.51 % SOM -‐ -‐ 299 NF 10.9 2.12 % SOM -‐ -‐ AWD = alternate wetting and drying CF = continuous flooding CF-‐S = continuous flooding w/ shallow water depth CI = controlled irrigation FFP = farmers´fertilization practice ID = intermittent drainage II = intermittent irrigation MD = midseason drainage (only if extended) NF = non-‐flooded SRI = system of rice intensification (water only) SSNM = site-‐specific nutrient management TD = terminal drainage -‐ = data not found in original source