scholarly journals Impact Assessment of Climate Change on Paddy Yield: A Case Study of Nepal Agriculture Research Council (NARC), Tarahara, Nepal

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

2017 ◽  
Vol 34 (04) ◽  
pp. 304-312 ◽  
Author(s):  
Md. Abdur Rashid Sarker ◽  
Khorshed Alam ◽  
Jeff Gow

AbstractThis paper uses the framework of the Just–Pope production function to evaluate the impacts of climate change on yields of the rainfed Aman rice crop in Bangladesh. It analyses disaggregated district-level data on climate variables and Aman rice yield over a 48 year time horizon. The results reveal that changes in maximum temperatures have had positive and negative effects on yield in the linear and quadratic functional forms, respectively. However, the elasticity values in the variance function confirm that maximum temperature is risk-increasing for Aman rice while minimum temperature is likely to decrease yield variability. Rainfall has become risk-increasing for Aman rice. Based on three climate change scenarios, this paper also reveals that future climate change is expected to increase the variability of Aman rice yields. Finally, statistically significant dummies for different in-country climate zones require zone-specific adaptation policies to reduce the adverse impacts of climate change.


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.


2021 ◽  
Vol 23 (3) ◽  
pp. 292-298
Author(s):  
HARPINDER SINGH ◽  
SUDHIR KUMAR MISHRA ◽  
KULDEEP SINGH ◽  
KULVIR SINGH ◽  
R. K. PAL ◽  
...  

The present study was performed at three diverse agro-climatic zones of Indian Punjab. A validated DSSAT-CANEGRO model was used to simulate the response of different climate change scenarios on cane yield of four sugarcane varieties (CoPb 91, CoJ 88, Co 118 and Co 238) for each zone. Results described that elevated and lowered minimum temperature upto 3.0°C may alter cane yield by -17.9 to 18.0 per cent. Similarly, ±3.0°C altered maximum temperature may change the cane yield by -17.6 to 17.5 per cent. The sugarcane yield may be decreased by 2.4 to 14.4 per cent, 3.3 to 17.6% and 0.3 to15.4 per cent with 2.5 to 15 per cent reduced solar radiation and increase in the same unit may enhance the yield by 1.9 to 9.0 per cent, 1.3 to 13.6 per cent and 2.0 to 12.3 per cent at Faridkot, Gurdaspur and Kapurthala, respectively. A±30 mm rainfall may change the cane yield by 9.2 to 18.0 % similarly, rise and fall in CO2 by 5 to 30 ppm was able to increase and decrease the cane yield by 2.4- 22.6 and 3.5 - 27.8 per cent, at different regions. This study confirmed that for sugarcane cultivation in Punjab CoPb 91 should be preferred. However, CoJ 88 and Co 238 may suffer cane yield loss of 7.8 and 9.9 per cent respectively.


2006 ◽  
Vol 27 ◽  
pp. 103-110 ◽  
Author(s):  
LP Amgain ◽  
NR Devkota ◽  
J Timsina ◽  
B Bijay-Singh

Recent trends of a decline or stagnation in the yield of rice and wheat in rice-wheat (RW) systems of the Indo-Gangetic Plains (IGP) have raised serious concerns about the regional food security. The effect of future climate change on crop production adds to this complex problem. The validated CSM-CERES-Rice and CSM-CERES-Wheat (Ver. 4.0) data were used to test the sensitivity of the models in Punjab, India. The models were sensitive to climatic parameters (temperature, CO2 concentration, solar radiation and rainfall) on yields of both crops. Simulated rice yields were sensitive to weather as there was 13% less yield of rice in 1999 than in 2001. Similarly, simulated wheat yields were also sensitive to weather, with the highest yield in 2001, and the lowest in 2003. Increments in both maximum and minimum temperatures by 4°C, decreased rice yield by 34% and wheat yield by 4% as compared to base scenario with current weather data. By increasing 4°C for both maximum and minimum temperature along with an increase in solar radiation by 1MJ/m2/day, rice yield decreased by 32% as compared to base scenario while wheat yields were not affected. With the increase in maximum and minimum temperatures by 4°C, and also an increase in CO2 concentration by 20 ppm from the standard CO2 concentration of 335 ppm, the reduction in rice yield was 33%, but in wheat yield was only 3%. Rainfed wheat yield increased by 7%, by increasing daily rainfall by 1.5 times, and by 13%, by doubling the rainfall, both after 96 days of sowing (DAS) to maturity. Lowering rainfall to zero, for each day after 96 DAS to until maturity reduced wheat yield by 18%. The increasing maximum and minimum temperatures irrespective of whether the CO2 concentration increased or not, seemed to have more adverse effects on rice than to wheat. Simulations demonstrated that CSM-CERES-Rice and CSM-CERES- Wheat are sensitive to CO2 and climatic parameters, and can be used to study the impact of future climate change on rice and wheat productivity in RW systems in Asia. Key words: CSM-CERES-Rice, CSM-CERES-Wheat, climate change, yield, phenology J. Inst. Agric. Anim. Sci. 27:103-110 (2006)


Water ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 219 ◽  
Author(s):  
Antonio-Juan Collados-Lara ◽  
David Pulido-Velazquez ◽  
Rosa María Mateos ◽  
Pablo Ezquerro

In this work, we developed a new method to assess the impact of climate change (CC) scenarios on land subsidence related to groundwater level depletion in detrital aquifers. The main goal of this work was to propose a parsimonious approach that could be applied for any case study. We also evaluated the methodology in a case study, the Vega de Granada aquifer (southern Spain). Historical subsidence rates were estimated using remote sensing techniques (differential interferometric synthetic aperture radar, DInSAR). Local CC scenarios were generated by applying a bias correction approach. An equifeasible ensemble of the generated projections from different climatic models was also proposed. A simple water balance approach was applied to assess CC impacts on lumped global drawdowns due to future potential rainfall recharge and pumping. CC impacts were propagated to drawdowns within piezometers by applying the global delta change observed with the lumped assessment. Regression models were employed to estimate the impacts of these drawdowns in terms of land subsidence, as well as to analyze the influence of the fine-grained material in the aquifer. The results showed that a more linear behavior was observed for the cases with lower percentage of fine-grained material. The mean increase of the maximum subsidence rates in the considered wells for the future horizon (2016–2045) and the Representative Concentration Pathway (RCP) scenario 8.5 was 54%. The main advantage of the proposed method is its applicability in cases with limited information. It is also appropriate for the study of wide areas to identify potential hot spots where more exhaustive analyses should be performed. The method will allow sustainable adaptation strategies in vulnerable areas during drought-critical periods to be assessed.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Alizée Chemison ◽  
Gilles Ramstein ◽  
Adrian M. Tompkins ◽  
Dimitri Defrance ◽  
Guigone Camus ◽  
...  

AbstractStudies about the impact of future climate change on diseases have mostly focused on standard Representative Concentration Pathway climate change scenarios. These scenarios do not account for the non-linear dynamics of the climate system. A rapid ice-sheet melting could occur, impacting climate and consequently societies. Here, we investigate the additional impact of a rapid ice-sheet melting of Greenland on climate and malaria transmission in Africa using several malaria models driven by Institute Pierre Simon Laplace climate simulations. Results reveal that our melting scenario could moderate the simulated increase in malaria risk over East Africa, due to cooling and drying effects, cause a largest decrease in malaria transmission risk over West Africa and drive malaria emergence in southern Africa associated with a significant southward shift of the African rain-belt. We argue that the effect of such ice-sheet melting should be investigated further in future public health and agriculture climate change risk assessments.


Author(s):  
Hevellyn Talissa dos Santos ◽  
Cesar Augusto Marchioro

Abstract The small tomato borer, Neoleucinodes elegantalis (Guenée, 1854) is a multivoltine pest of tomato and other cultivated solanaceous plants. The knowledge on how N. elegantalis respond to temperature may help in the development of pest management strategies, and in the understanding of the effects of climate change on its voltinism. In this context, this study aimed to select models to describe the temperature-dependent development rate of N. elegantalis and apply the best models to evaluate the impacts of climate change on pest voltinism. Voltinism was estimated with the best fit non-linear model and the degree-day approach using future climate change scenarios representing intermediary and high greenhouse gas emission rates. Two out of the six models assessed showed a good fit to the observed data and accurately estimated the thermal thresholds of N. elegantalis. The degree-day and the non-linear model estimated more generations in the warmer regions and fewer generations in the colder areas, but differences of up to 41% between models were recorded mainly in the warmer regions. In general, both models predicted an increase in the voltinism of N. elegantalis in most of the study area, and this increase was more pronounced in the scenarios with high emission of greenhouse gases. The mathematical model (74.8%) and the location (9.8%) were the factors that mostly contributed to the observed variation in pest voltinism. Our findings highlight the impact of climate change on the voltinism of N. elegantalis and indicate that an increase in its population growth is expected in most regions of the study area.


2021 ◽  
Vol 13 (12) ◽  
pp. 2249
Author(s):  
Sadia Alam Shammi ◽  
Qingmin Meng

Climate change and its impact on agriculture are challenging issues regarding food production and food security. Many researchers have been trying to show the direct and indirect impacts of climate change on agriculture using different methods. In this study, we used linear regression models to assess the impact of climate on crop yield spatially and temporally by managing irrigated and non-irrigated crop fields. The climate data used in this study are Tmax (maximum temperature), Tmean (mean temperature), Tmin (minimum temperature), precipitation, and soybean annual yields, at county scale for Mississippi, USA, from 1980 to 2019. We fit a series of linear models that were evaluated based on statistical measurements of adjusted R-square, Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). According to the statistical model evaluation, the 1980–1992 model Y[Tmax,Tmin,Precipitation]92i (BIC = 120.2) for irrigated zones and the 1993–2002 model Y[Tmax,Tmean,Precipitation]02ni (BIC = 1128.9) for non-irrigated zones showed the best fit for the 10-year period of climatic impacts on crop yields. These models showed about 2 to 7% significant negative impact of Tmax increase on the crop yield for irrigated and non-irrigated regions. Besides, the models for different agricultural districts also explained the changes of Tmax, Tmean, Tmin, and precipitation in the irrigated (adjusted R-square: 13–28%) and non-irrigated zones (adjusted R-square: 8–73%). About 2–10% negative impact of Tmax was estimated across different agricultural districts, whereas about −2 to +17% impacts of precipitation were observed for different districts. The modeling of 40-year periods of the whole state of Mississippi estimated a negative impact of Tmax (about 2.7 to 8.34%) but a positive impact of Tmean (+8.9%) on crop yield during the crop growing season, for both irrigated and non-irrigated regions. Overall, we assessed that crop yields were negatively affected (about 2–8%) by the increase of Tmax during the growing season, for both irrigated and non-irrigated zones. Both positive and negative impacts on crop yields were observed for the increases of Tmean, Tmin, and precipitation, respectively, for irrigated and non-irrigated zones. This study showed the pattern and extent of Tmax, Tmean, Tmin, and precipitation and their impacts on soybean yield at local and regional scales. The methods and the models proposed in this study could be helpful to quantify the climate change impacts on crop yields by considering irrigation conditions for different regions and periods.


2015 ◽  
Vol 7 (1) ◽  
pp. 39-51 ◽  
Author(s):  
Ali Fares ◽  
Ripendra Awal ◽  
Samira Fares ◽  
Alton B. Johnson ◽  
Hector Valenzuela

The impact of potential future climate change scenarios on the irrigation water requirements (IRRs) of two major agricultural crops (coffee and seed corn) in Hawai'i was studied using the Irrigation Management System (IManSys) model. In addition to IRRs calculations, IManSys calculates runoff, deep percolation, canopy interception, and effective rainfall based on plant growth parameters, site specific soil hydrological properties, irrigation system efficiency, and long-term daily weather data. Irrigation water requirements of two crops were simulated using historical climate data and different levels of atmospheric CO2 (330, 550, 710 and 970 ppm), temperature (+1.1 and +6.4 °C) and precipitation (±5, ±10 and ±20%) chosen based on the Intergovernmental Panel on Climate Change (IPCC) AR4 projections under reference, B1, A1B1 and A1F1 emission scenarios. IRRs decreased as CO2 emission increased. The average percentage decrease in IRRs for seed corn is higher than that of coffee. However, runoff, rain canopy interception, and deep percolation below the root zone increased as precipitation increased. Canopy interception and drainage increased with increased CO2 emission. Evapotranspiration responded positively to air temperature rise, and as a result, IRRs increased as well. Further studies using crop models will predict crop yield responses to these different irrigation scenarios.


2018 ◽  
pp. 70-79 ◽  
Author(s):  
Le Viet Thang ◽  
Dao Nguyen Khoi ◽  
Ho Long Phi

In this study, we investigated the impact of climate change on streamflow and water quality (TSS, T-N, and T-P loads) in the upper Dong Nai River Basin using the Soil and Water Assessment Tool (SWAT) hydrological model. The calibration and validation results indicated that the SWAT model is a reasonable tool for simulating streamflow and water quality for this basin. Based on the well-calibrated SWAT model, the responses of streamflow, sediment load, and nutrient load to climate change were simulated. Climate change scenarios (RCP 4.5 and RCP 8.5) were developed from five GCM simulations (CanESM2, CNRM-CM5, HadGEM2-AO, IPSL-CM5A-LR, and MPI-ESM-MR) using the delta change method. The results indicated that climate in the study area would become warmer and wetter in the future. Climate change leads to increases in streamflow, sediment load, T-N load, and T-P load. Besides that, the impacts of climate change would exacerbate serious problems related to water shortage in the dry season and soil erosion and degradation in the wet season. In addition, it is indicated that changes in sediment yield and nutrient load due to climate change are larger than the corresponding changes in streamflow.


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