scholarly journals Evaluating and Adapting Climate Change Impacts on Rice Production in Indonesia: A Case Study of the Keduang Subwatershed, Central Java

Environments ◽  
2021 ◽  
Vol 8 (11) ◽  
pp. 117
Author(s):  
Andrianto Ansari ◽  
Yu-Pin Lin ◽  
Huu-Sheng Lur

Predicting the effect of climate change on rice yield is crucial as global food demand rapidly increases with the human population. This study combined simulated daily weather data (MarkSim) and the CERES-Rice crop model from the Decision Support System for Agrotechnology Transfer (DSSAT) software to predict rice production for three planting seasons under four climate change scenarios (RCPs 2.6, 4.5, 6.0, and 8.5) for the years 2021 to 2050 in the Keduang subwatershed, Wonogiri Regency, Central Java, Indonesia. The CERES-Rice model was calibrated and validated for the local rice cultivar (Ciherang) with historical data using GenCalc software. The model evaluation indicated good performance with both calibration (coefficient of determination (R2) = 0.89, Nash–Sutcliffe efficiency (NSE) = 0.88) and validation (R2 = 0.87, NSE = 0.76). Our results suggest that the predicted changing rainfall patterns, rising temperature, and intensifying solar radiation under climate change can reduce the rice yield in all three growing seasons. Under RCP 8.5, the impact on rice yield in the second dry season may decrease by up to 11.77% in the 2050s. Relevant strategies associated with policies based on the results were provided for decision makers. Furthermore, to adapt the impact of climate change on rice production, a dynamic cropping calendar, modernization of irrigation systems, and integrated plant nutrient management should be developed for farming practices based on our results in the study area. Our study is not only the first assessment of the impact of climate change on the study site but also provides solutions under projected rice shortages that threaten regional food security.

2018 ◽  
Vol 63 (03) ◽  
pp. 535-553 ◽  
Author(s):  
DAN WANG ◽  
YU HAO ◽  
JIANPEI WANG

Climate change is attracting increasing attention from the international community. To assess the impact of climate change on China’s rice production, this paper re-organizes the main rice-producing areas by adding up the annual production of the provincial level regions between 1979 and 2011, utilizes Cobb–Douglas function using daily weather data over the whole growing season. Our analysis of the panel data shows that minimum temperatures (Tmin), maximum temperatures (Tmax), temperature difference (TD) and precipitation (RP) are the four key climate determinants of rice production in China. Among these, temperature difference is surprisingly significant and all except maximum temperatures have positive effects. However, because the actual minimum temperatures and precipitation in China’s main rice-producing areas declined while the maximum temperatures and the temperature difference increased during our sample period, climate change has actually provided a negative contribution to the increase in China’s rice production.


2015 ◽  
Vol 17 (3) ◽  
pp. 594-606 ◽  

<div> <p>The impact of climate change on water resources through increased evaporation combined with regional changes in precipitation characteristics has the potential to affect mean runoff, frequency and intensity of floods and droughts, soil moisture and water supply for irrigation and hydroelectric power generation. The Ganga-Brahmaputra-Meghna (GBM) system is the largest in India with a catchment area of about 110Mha, which is more than 43% of the cumulative catchment area of all the major rivers in the country. The river Damodar is an important sub catchment of GBM basin and its three tributaries- the Bokaro, the Konar and the Barakar form one important tributary of the Bhagirathi-Hughli (a tributary of Ganga) in its lower reaches. The present study is an attempt to assess the impacts of climate change on water resources of the four important Eastern River Basins namely Damodar, Subarnarekha, Mahanadi and Ajoy, which have immense importance in industrial and agricultural scenarios in eastern India. A distributed hydrological model (HEC-HMS) has been used on the four river basins using HadRM2 daily weather data for the period from 2041 to 2060 to predict the impact of climate change on water resources of these river systems.&nbsp;</p> </div> <p>&nbsp;</p>


2016 ◽  
Vol 154 (7) ◽  
pp. 1153-1170 ◽  
Author(s):  
E. EBRAHIMI ◽  
A. M. MANSCHADI ◽  
R. W. NEUGSCHWANDTNER ◽  
J EITZINGER ◽  
S. THALER ◽  
...  

SUMMARYClimate change is expected to affect optimum agricultural management practices for autumn-sown wheat, especially those related to sowing date and nitrogen (N) fertilization. To assess the direction and quantity of these changes for an important production region in eastern Austria, the agricultural production systems simulator was parameterized, evaluated and subsequently used to predict yield production and grain protein content under current and future conditions. Besides a baseline climate (BL, 1981–2010), climate change scenarios for the period 2035–65 were derived from three Global Circulation Models (GCMs), namely CGMR, IPCM4 and MPEH5, with two emission scenarios, A1B and B1. Crop management scenarios included a combination of three sowing dates (20 September, 20 October, 20 November) with four N fertilizer application rates (60, 120, 160, 200 kg/ha). Each management scenario was run for 100 years of stochastically generated daily weather data. The model satisfactorily simulated productivity as well as water and N use of autumn- and spring-sown wheat crops grown under different N supply levels in the 2010/11 and 2011/12 experimental seasons. Simulated wheat yields under climate change scenarios varied substantially among the three GCMs. While wheat yields for the CGMR model increased slightly above the BL scenario, under IPCM4 projections they were reduced by 29 and 32% with low or high emissions, respectively. Wheat protein appears to increase with highest increments in the climate scenarios causing the largest reductions in grain yield (IPCM4 and MPEH-A1B). Under future climatic conditions, maximum wheat yields were predicted for early sowing (September 20) with 160 kg N/ha applied at earlier dates than the current practice.


1970 ◽  
Vol 8 (3) ◽  
pp. 147-167 ◽  
Author(s):  
Yam K Rai ◽  
Bhakta B Ale ◽  
Jawed Alam

Climate change and global warming are burning issues, which significantly threat agriculture and global food security. Change in solar radiation, temperature and precipitation will influence the change in crop yields and hence economy of agriculture. It is possible to understand the phenomenon of climate change on crop production and to develop adaptation strategies for sustainability in food production, using a suitable crop simulation model. CERES-Rice model of DSSAT v4.0 was used to simulate the rice yield of the region under climate change scenarios using the historical weather data at Nepal Agriculture Research Council (NARC) Tarahara (1989-2008). The Crop Model was calibrated using the experimental crop data, climate data and soil data for two years (2000-2001) and was validated by using the data of the year 2002 at NARC Tarahara. In this study various scenarios were undertaken to analyze the rice yield. The change in values of weather parameters due to climate change and its effects on the rice yield were studied. It was observed that increase in maximum temperature up to 2°C and 1°C in minimum temperature have positive impact on rice yield but beyond that temperature it was observed negative impact in both cases of paddy production in ambient temperature. Similarly, it was observed that increased in mean temperature, have negative impacts on rice yield. The impact of solar radiation in rice yield was observed positive during the time of study period. Adjustments were made in the fertilizer rate, plant density per square meter, planting date and application of water rate to investigate suitable agronomic options for adaptation under the future climate change scenarios. Highest yield was obtained when the water application was increased up to 3 mm depth and nitrogen application rate was 140 kg/ha respectively. DOI: http://dx.doi.org/10.3126/jie.v8i3.5941 JIE 2011; 8(3): 147-167


2011 ◽  
Vol 2 (2) ◽  
pp. 493-529 ◽  
Author(s):  
M. Hirschi ◽  
S. Stoeckli ◽  
M. Dubrovsky ◽  
C. Spirig ◽  
P. Calanca ◽  
...  

Abstract. As a consequence of current and projected climate change in temperate regions of Europe, agricultural pests and diseases are expected to occur more frequently and possibly to extend to previously not affected regions. Given their economic and ecological relevance, detailed forecasting tools for various pests and diseases have been developed, which model their phenology depending on actual weather conditions and suggest management decisions on that basis. Assessing the future risk of pest-related damages requires future weather data at high temporal and spatial resolution. Here, we use a combined stochastic weather generator and re-sampling procedure for producing site-specific hourly weather series representing present and future (1980–2009 and 2045–2074 time periods) climate conditions in Switzerland. The climate change scenarios originate from the ENSEMBLES multi-model projections and provide probabilistic information on future regional changes in temperature and precipitation. Hourly weather series are produced by first generating daily weather data for these climate scenarios and then using a nearest neighbor re-sampling approach for creating realistic diurnal cycles. These hourly weather series are then used for modeling the impact of climate change on important life phases of the codling moth and on the number of predicted infection days of fire blight. Codling moth (Cydia pomonella) and fire blight (Erwinia amylovora) are two major pest and disease threats to apple, one of the most important commercial and rural crops across Europe. Results for the codling moth indicate a shift in the occurrence and duration of life phases relevant for pest control. In southern Switzerland, a 3rd generation per season occurs only very rarely under today's climate conditions but is projected to become normal in the 2045–2074 time period. While the potential risk for a 3rd generation is also significantly increasing in northern Switzerland (for most stations from roughly 1 % on average today to over 60 % in the future for the median climate change signal of the multi-model projections), the actual risk will critically depend on the pace of the adaptation of the codling moth with respect to the critical photoperiod. To control this additional generation, an intensification and prolongation of control measures (e.g., insecticides) will be required, implying an increasing risk of pesticide resistances. For fire blight, the projected changes in infection days are less certain due to uncertainties in the leaf wetness approximation and the simulation of the blooming period. Two compensating effects are projected, warmer temperatures favoring infections are balanced by a temperature-induced advancement of the blooming period, leading to no significant change in the number of infection days under future climate conditions for most stations.


2012 ◽  
Vol 3 (1) ◽  
pp. 33-47 ◽  
Author(s):  
M. Hirschi ◽  
S. Stoeckli ◽  
M. Dubrovsky ◽  
C. Spirig ◽  
P. Calanca ◽  
...  

Abstract. As a consequence of current and projected climate change in temperate regions of Europe, agricultural pests and diseases are expected to occur more frequently and possibly to extend to previously non-affected regions. Given their economic and ecological relevance, detailed forecasting tools for various pests and diseases have been developed, which model their phenology, depending on actual weather conditions, and suggest management decisions on that basis. Assessing the future risk of pest-related damages requires future weather data at high temporal and spatial resolution. Here, we use a combined stochastic weather generator and re-sampling procedure for producing site-specific hourly weather series representing present and future (1980–2009 and 2045–2074 time periods) climate conditions in Switzerland. The climate change scenarios originate from the ENSEMBLES multi-model projections and provide probabilistic information on future regional changes in temperature and precipitation. Hourly weather series are produced by first generating daily weather data for these climate scenarios and then using a nearest neighbor re-sampling approach for creating realistic diurnal cycles. These hourly weather series are then used for modeling the impact of climate change on important life phases of the codling moth and on the number of predicted infection days of fire blight. Codling moth (Cydia pomonella) and fire blight (Erwinia amylovora) are two major pest and disease threats to apple, one of the most important commercial and rural crops across Europe. Results for the codling moth indicate a shift in the occurrence and duration of life phases relevant for pest control. In southern Switzerland, a 3rd generation per season occurs only very rarely under today's climate conditions but is projected to become normal in the 2045–2074 time period. While the potential risk for a 3rd generation is also significantly increasing in northern Switzerland (for most stations from roughly 1% on average today to over 60% in the future for the median climate change signal of the multi-model projections), the actual risk will critically depend on the pace of the adaptation of the codling moth with respect to the critical photoperiod. To control this additional generation, an intensification and prolongation of control measures (e.g. insecticides) will be required, implying an increasing risk of pesticide resistances. For fire blight, the projected changes in infection days are less certain due to uncertainties in the leaf wetness approximation and the simulation of the blooming period. Two compensating effects are projected, warmer temperatures favoring infections are balanced by a temperature-induced advancement of the blooming period, leading to no significant change in the number of infection days under future climate conditions for most stations.


2013 ◽  
Vol 52 (9) ◽  
pp. 2033-2050 ◽  
Author(s):  
K. P. Devkota ◽  
A. M. Manschadi ◽  
M. Devkota ◽  
J. P. A. Lamers ◽  
E. Ruzibaev ◽  
...  

AbstractRice is the second major food crop in central Asia. Climate change may greatly affect the rice production in the region. This study quantifies the effects of projected increases in temperature and atmospheric CO2 concentration on the phenological development and grain yield of rice using the “ORYZA2000” simulation model. The model was parameterized and validated on the basis of datasets from three field experiments with three widely cultivated rice varieties under various seeding dates in the 2008–09 growing seasons in the Khorezm region of Uzbekistan. The selected rice varieties represent short-duration (SD), medium-duration (MD), and long-duration (LD) maturity types. The model was linked with historical climate data (1970–99) and temperatures and CO2 concentrations projected by the Intergovernmental Panel on Climate Change for the B1 and A1F1 scenarios for the period 2040–69 to explore rice growth and yield formation at eight emergence dates from early May to mid-July. Simulation results with historical daily weather data reveal a close relationship between seeding date and rice grain yield. Optimal emergence dates were 25 June for SD, 5 June for MD, and 26 May for LD varieties. Under both climate change scenarios, the seeding dates could be delayed by 10 days. Increased temperature and CO2 concentration resulted in higher rice grain yields. However, seeding rice before and after the optimal seeding dates reduced crop yield and yield stability significantly because of spikelet sterility induced by both high and low temperatures. As the grain yield of SD varieties could be adversely affected by climate change, rice breeding programs for central Asia should focus on developing appropriate heat-tolerant MD and LD varieties.


Agriculture ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. 441
Author(s):  
Wenjian He ◽  
Yiyang Liu ◽  
Huaping Sun ◽  
Farhad Taghizadeh-Hesary

The global warming phenomenon has undoubtedly brought unprecedented challenges to rice production, vital for food security in Southeast Asian countries and China. Most studies on this topic have focused narrowly on the direct effect of climate change on rice yield, neglecting the indirect effect. Using panel data from 30 provinces in China from 1990 to 2016, in this paper, we propose and test a mediational effect model to examine the mechanisms of how climate change affects rice yield. We find that climate change leads to changes in functional irrigation areas, farmers’ fertilizing behavior, and agricultural labor supply, and it is these mediating factors that effectively transmit the impact of climate change to China’s rice production. The positive indirect impact of climate change on the factors of production often partially or overly compensates for the adverse direct effect of climate change on rice yield, leading to a surprising observation of the association of climate change with increased rice yield, at least in the short run. We also provide some preliminary policy advice based on the analysis.


Author(s):  
Diana Fiorillo ◽  
Zoran Kapelan ◽  
Maria Xenochristou ◽  
Francesco De Paola ◽  
Maurizio Giugni

AbstractAssessing the impact of climate change on water demand is a challenging task. This paper proposes a novel methodology that quantifies this impact by establishing a link between water demand and weather based on climate change scenarios, via Coupled General Circulation Models. These models simulate the response of the global climate system to increasing greenhouse gas concentrations by reproducing atmospheric and ocean processes. In order to establish the link between water demand and weather, Random Forest models based on weather variables were used. This methodology was applied to a district metered area in Naples (Italy). Results demonstrate that the total district water demand may increase by 9–10% during the weeks with the highest temperatures. Furthermore, results show that the increase in water demand changes depending on the social characteristics of the users. The water demand of employed users with high education may increase by 13–15% when the highest temperatures occur. These increases can seriously affect the capacity and operation of existing water systems.


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