Regional Variability in Climate-Rice Yield Relationships Across Java, Indonesia: A 30-Year Spatial-Temporal Analysis

Climate change presents a substantial challenge to Indonesia, an archipelagic nation characterized by diverse ecosystems and highly dependent on climate-sensitive sectors such as agriculture, fisheries, and forestry. Due to its geography and socio-economic conditions, the country is particularly vulnerable to climate-induced risks, including threats to food security and economic stability. As the world’s fourth-largest rice producer, Indonesia’s agricultural sector—especially rice production—is particularly susceptible to the impacts of climate change. Rice has an optimal temperature range for growth and development, generally between 25-35℃. Rice growth is also affected by climate-induced changes in rainfall, which will impact the availability of soil moisture, which is essential for optimal physiological function [1]. Variations in precipitation, rising temperatures, and extreme weather events have been shown to reduce agricultural productivity and increase crop failure rates [2-4]. Projections suggest that by 2050, climate change could reduce rice productivity by 14% in South Asia, 10% in East Asia, and 15% in Sub-Saharan Africa, with Indonesia likely facing similar declines [5]. Other staple crops like cassava and sweet potatoes are also at risk, as climatic factors such as temperature and rainfall variability significantly affect their production [6].

The socio-economic implications of these agricultural challenges are profound. Agriculture employs a significant portion of Indonesia’s population, and climate-induced disruptions threaten the livelihoods of millions, especially in rural areas. Reduced crop yields contribute to food insecurity and poverty, while agricultural economic losses undermine national development [3, 5]. Furthermore, human activities like deforestation and industrialization exacerbate Indonesia’s vulnerabilities to climate change [6, 7].

Indonesia has implemented comprehensive adaptation strategies in response to these challenges, including developing National Adaptation Plans (NAPs). These plans emphasize climate-smart agricultural practices, such as adopting resilient crop varieties, improved water management, and sustainable farming techniques [8, 9]. Java Island, the country’s most populous and agriculturally significant region, provides a critical example of the challenges climate change poses to rice production. The island’s tropical monsoon climate, fertile volcanic soils, and diverse topography have long supported traditional and improved rice varieties [3, 10]. However, shifting rainfall patterns, rising temperatures, and increasing salinity in coastal agricultural lands due to sea-level rise threaten this agricultural landscape [11, 12]. Amidst the threat of global climate change, understanding how climate factors influence rice production spatially and temporally is very important, especially for formulating region-based adaptation strategies. Additionally, understanding climate variations is critical for the long-term sustainability of the agricultural sector and ensuring sufficient food supplies for a growing population [13]. So far, adaptation policies are often generic and do not consider local variations in the response of agricultural systems to climate change. Therefore, assessing regional variability in the impact of temperature and rainfall on rice production is not only scientifically important but is also practically relevant for planning agricultural policies and food security that are more adaptive and responsive to changing climate dynamics. Previous studies have proven that climate change, especially increasing temperatures and fluctuations in rainfall, has a real impact on the productivity of food crops, including rice. Studies such as research [14-17] show that global climate change has hampered the growth of rice productivity in various parts of the world.

Despite the growing body of literature examining the impact of climate change on agriculture, particularly rice production, there remains a lack of comprehensive studies that analyse the spatial and temporal variability of climatic factors, especially at the regional level. Most studies have focused on the global or national scale, often overlooking the diverse impacts of climate change on different regions within a country like Indonesia. Additionally, previous research has failed to employ long-term time-series data (spanning multiple decades) to assess how regional climate factors—such as precipitation, maximum temperature, and minimum temperature—interact to influence rice yields across distinct districts in Java.

This study, with its comprehensive 30-year dataset (1994-2023), aims to fill this gap and provide a thorough understanding of the nuanced climatic influences on rice production in Java’s key rice-producing districts. This study is novel in its empirical approach, as it uses a comprehensive, 30-year time-series dataset to explore the regional disparities in climate-rice dynamics in Java, Indonesia. Unlike most previous studies that analyse climate impacts at a national level, the findings of this research provide location-specific insights, which are crucial for developing tailored climate adaptation strategies. Strategies inform agricultural policy and climate adaptation strategies significantly. Understanding the specific climatic factors that most affect rice yields in each district will allow for the development of region-specific policies that can effectively mitigate the adverse effects of climate change on rice production, thereby safeguarding food security and rural livelihoods in Indonesia.

This study specifically focuses on the role of climatic factors in determining rice productivity, while deliberately excluding non-climatic influences such as the adoption of agricultural technologies, the use of improved crop varieties, input-related policies, and infrastructure development. Many previous studies have combined both climatic and non-climatic variables within a single analytical framework without first isolating long-term trends attributed to non-climatic factors. This approach may introduce bias in estimating the true effects of climate, as year-to-year yield improvements are often driven by technological progress and human interventions [16-18]. Therefore, applying a detrending method is essential to remove non-climatic trends from yield data, allowing a more accurate assessment of the relationship between climate variability and crop performance—without the confounding influence of ongoing technological advancements.

The objective of this study is to investigate the relationship between climatic factors—precipitation, maximum temperature, and minimum temperature—and rice yields across six key rice-producing districts in Java: Karawang, Indramayu, Cilacap, Grobogan, Ngawi, and Lamongan Districts. This research hypothesizes that precipitation will emerge as the most significant climatic factor influencing rice yields in these regions, with temperature variables exhibiting varying impacts depending on the district. The study also aims to assess the spatial heterogeneity of these relationships and provide insights into how different regions experience and adapt to climate variability.

Table 1. Summary statistics of the climate and rice yield variables for the 1994-2023 period

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Similarly, Figure 4(b) for Indramayu displays a parallel trend, where rice yield increases with both rainfall and Tmax. Although the magnitude of increase is slightly lower than Cilacap, the shape of the surface indicates a synergistic effect—higher rainfall appears to amplify the positive effect of Tmax on yield. This may reflect local adaptation to moderately warm conditions with adequate moisture availability.

In contrast, Figure 4(c) shows the response surface for Lamongan, where rainfall and minimum temperature (Tmin) jointly influence yield. Here, the yield index increases sharply as Tmin rises from 23.0℃ to 26.0℃, especially when rainfall exceeds 300 mm. This steep incline suggests a strong dependency on nighttime temperature, likely due to its role in preventing cold-induced sterility during flowering. The interaction appears more convex, implying a non-linear boost in yield under warm, humid conditions. Overall, these visualizations confirm that climate-yield relationships are both spatially and interactively complex. While higher Tmax benefits rice production in some regions, Tmin plays a more dominant role in others. Rainfall remains a key amplifier of temperature effects across all districts.

Although Lamongan had the lowest growing season average minimum temperature, maximum temperature, and rainfall relative to other districts, it, however, recorded the highest rice output per hectare. Minimum temperature significantly improves rice yield in the Lamongan district but not in the other four districts. This result is similar to studies [32], which found that rice yield is significantly enhanced by minimum temperature. Rice yield in the southeastern United States was shown to rise by 22.40% with a 1℃ increase in Tmin [33]. Incidentally, the Lamongan district has the highest average minimum growing season temperature of approximately 24.90℃ relative to the four other districts. Higher minimum temperatures in Lamongan have a large production boost, which is probably due to favorable agroecological circumstances, adaptable local practices, and overnight temperatures that correspond with the physiological optimum for rice. According to research [18], raising the nighttime temperature above about 27℃ decreases grain weight per panicle, indicating that ideal nighttime temperatures of 24 to 25℃ are essential for preserving spikelet fertility and rice reproductive development in general. Above 25℃, high night temperatures can negatively impact rice growth phases by increasing spikelet sterility and decreasing biomass, grain development, and seed germination [34]. Thus, suggesting that temperature values below 24.90℃ could have a net zero or detrimental effect on rice yields in Java.

Decreasing minimum temperatures generally has a negative impact on rice yields. Study [35] found that grain yield declined by 10% for each 1℃ decrease in growing-season minimum temperature during the dry season. Similarly, study [36] reported that lower minimum temperatures during the grain-filling phase significantly reduced grain yield and quality, affecting parameters such as chalkiness, starch content, and mineral nutrient composition. Average growing season maximum temperature, on the other hand, significantly improved rice yield in Indramayu and Cilacap districts only, with a stronger and more reliable influence in Cilacap district. Akin to the earlier observation for Lamongan district, Cilacap district has the lowest average growing season maximum temperatures relative to the other four districts. Thus, it suggests that growing season maximum temperature values exceeding 31.10℃ could have a net zero or detrimental effect on the yield of rice in Java. Increased maximum temperatures generally lead to a decline in rice yield. For instance, a 1℃ rise in temperature can reduce irrigated rice yield by 6.6% to 11.1% and rainfed rice yields by 4.6% to 9.4% [36]. Similarly, study [37] asserted that grain yield decreased by 38.3% to 54.5% with a temperature increase of 4.5℃ to 5.8℃ from ambient levels. Average growing season monthly total rainfall significantly improved rice yields across the five districts where the OLS model was significant.

The regression results show that rainfall significantly affects rice yields in five out of six districts (p < 0.05). Specifically, a 1mm increase in rainfall during the growing season is associated with an estimated yield increase of 0.08% in Indramayu and Cilacap, 0.09% in Lamongan, 0.12% in Ngawi, and 0.13% in Grobogan. These coefficients are statistically significant at the 1-5% level. In Karawang, however, the rainfall coefficient was positive but not statistically significant, suggesting that rainfall variability may play a lesser role in yield variation, possibly due to stable irrigation systems.

However, the strongest effects were observed for Grobogan and Ngawi districts, which received a moderate amount of rainfall relative to other districts. Incidentally, these two districts have the lowest rice yield and are not significantly impacted by growing season maximum and minimum temperatures, thus highlighting the critical role of increasing rainfall in determining the outcome of rice yield. Although increasing rainfall significantly improved rice yield in all the regions except Karawang, the improvements in rice yield occasioned by rising minimum and maximum temperatures are of greater magnitude. Rice yields in Indramayu, Cilacap, and Lamongan districts are more susceptible to the influence of climate variability than rice yields in Grobogan and Ngawi districts. Grobogan and Ngawi are experiencing significant temperature increases and variable rainfall patterns. By 2010, maximum and minimum temperatures are projected to rise by 3.5% and 4.9%, respectively, with even greater increases expected by 2050. This warming trend may shorten rice growing periods and reduce yields [38]. Additionally, the combination of higher temperatures and drought conditions could lead to an estimated annual decline of approximately 1% in rice yields across East Java, including the Ngawi district [23]. Rice yield in the Karawang district is not significantly affected by climate variability from rainfall and temperature. However, the overall increase in rainfall during the growing season in most districts, except for Karawang, has serious implications for rice production on Java Island. Our findings show how changing climatic factors, particularly rainfall, influence rice yield.

Rainfall is the most important factor affecting rice production across major rice-growing districts in Java, with a significant impact in five out of six districts. In some cases, increased rainfall has been positively correlated with higher rice output. A 10% increase in rainfall can lead to a 0.4% increase in rice output, indicating that adequate rainfall is crucial for optimal rice production [35]. Moreover, while some climatic factors greatly affect rice yield in certain districts, they have no impact in others. Therefore, policies aimed at mitigating the negative effects of climate change on crop yields in Java or Indonesia should be tailored to specific regions, as climatic influences vary across different areas. These results are similar to the study in Vietnam, which showed that the impact of climate variability on crop yield varied among crops as well as provinces, with rainfall being the most critical factor, especially in water-limited regions [27]. Meanwhile, in the Northeast of Thailand, rice yield is primarily influenced by minimum seasonal temperatures, which have a positive correlation, while rainfall shows inconsistent effects. Additionally, non-climatic factors such as improved farm management practices, seed quality, and fertilizer use play a substantial role in determining rice yields [23].

Although this study did not explicitly include interaction terms between temperature and precipitation in the regression models, we acknowledge that such interactions may significantly affect rice yield outcomes under varying climate conditions. Real-world climatic events often co-occur, where high temperatures combined with low rainfall can lead to compounded stress, which may not be fully captured by additive models. Studies such as study [39] have shown that during critical stages of rice growth, particularly during the reproductive phase (flowering and grain filling), high temperatures can exacerbate the impact of drought stress, leading to spikelet sterility, reduced grain filling, and ultimately lower yields. Similarly, study [40] emphasizes that the combination of temperature and precipitation influences rice yield and physiological responses, with low rainfall significantly reducing nitrogen use efficiency and further intensifying the effects of heat.

In our study, Figure 4 implicitly visualizes how combinations of temperature (Tmax or Tmin) and rainfall interact to affect rice yields across districts. Although our analysis focuses on additive effects for model simplicity, we recognize this as a limitation. Future research could address this by incorporating interaction terms or adopting nonlinear models, such as generalized additive models (GAMs), to better capture the complex climate-yield dynamics in tropical monsoon regions like Java.