scholarly journals PEMANFAATAN MODEL PROYEKSI IKLIM DAN SIMULASI TANAMAN DALAM PENGUATAN ADAPTASI SISTEM PERTANIAN PADI TERHADAP PENURUNAN PRODUKTIVITAS AKIBAT PERUBAHAN IKLIM: STUDI KASUS DI KABUPATEN SUMEDANG, JAWA BARAT

2016 ◽  
Vol 23 (2) ◽  
pp. 159
Author(s):  
Candradijaya A
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Climate Models ◽  
Rice Yield ◽  
Local Level ◽  
Irrigation Scheduling ◽  
Yield Reduction ◽  
Planting Time ◽  
Near Future ◽  
Far Future

Despite the well-documented model-simulated adverse climate change impact on rice yields reported elsewhere, interventions to address the issue seem to be still limited, particularly at local level. This links to the uncertainty that entails to climate projection and its likely future impact, which varies across regions and climate models. The study analyzes climate change-induced rice yield reduction and the adequacy of current adaptations, to cope with a large range of impact under various climate models. Seventeen General Circulation Models (GCMs) under Representative Concentration Pathways (RCPs) climate change with scenarios of RCP8.5 and RCP4.5, combined with CROPWAT model for near-future (2011-2040) and far-future (2041-2070) projections. The study was conducted in November-December 2013, in Ujungjaya Subdistrict, the District of Sumedang. The output confirms yield reduction to occur in the near-future, to the extent variable across the GCMs. At the highest estimation, rice yield decreases by 32.00% and 31.81%, in comparison to baseline, for near-future under RCP8.5 and RCP4.5, respectively. The reduction extends, with a slightly higher degree, to the far-future. The reduction is sensitive to variation in farming practices of the local farmers, in particular that in planting time and irrigation scheduling. The shifting of planting time to better match rainfall pattern reduces the rice yield by 12.95% for rainfed and 14.07% for the irrigated farming. Meanwhile, improved irrigation scheduling reduces the yield reduction by 16.16%. The findings provide valuable inputs for relevant authorities to understand the climate change-induced rice yield reduction, and to formalate intervention strategies for spesific-location adaptation.

scholarly journals Susceptibility of Hydropower Generation to Climate Change: Karun III Dam Case Study

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 1025 ◽  
Author(s):  
Maryam Beheshti ◽  
Ali Heidari ◽  
Bahram Saghafian
Keyword(s):  
Climate Change ◽  
Power Generation ◽  
General Circulation ◽  
Average Power ◽  
Circulation Model ◽  
Precipitation Trend ◽  
Hydropower Generation ◽  
Near Future ◽  
Far Future

Climate change can cause serious problems for future hydropower plant projects and make them less economically justified. Changing precipitation patterns, rising temperatures, and abrupt snow melting affect river stream patterns and hydropower generation. Thus, study of climate change impacts during the useful life of a hydropower dam is essential and its outcome should be considered in assessing long-term dam feasibility. The aim of this research is to evaluate the impacts of climate change on future hydropower generation in the Karun-III dam located in the southwest region of Iran in two future tri-decadal periods: near (2020–2049) and far (2070–2099). Had-CM3 general circulation model predictions under A2 and B2 SRES scenarios were applied, and downscaled by a statistical downscaling model (SDSM). An artificial neural network (ANN) and HEC-ResSim reservoir model respectively simulated the rainfall–runoff process and hydropower generation. The projections showed that the Karun-III dam catchment under the two scenarios will generally become warmer and wetter with a slightly larger increase in annual precipitation in the near than the far future. Runoff followed the precipitation trend by increasing in both periods. The runoff peak also switched from April to March in both scenarios, due to higher winter precipitation, and earlier snowmelt, which was caused by temperature rise. According to both scenarios, hydropower generation increased more in the near future than in the far future. Annual average power generation increased gradually by 26.7–40.5% under A2 and by 17.4–29.3% under B2 in 2020–2049. In the far period, average power generation increased by 1.8–8.7% in A2 and by 10.5–22% under B2. In the near future, A2 showed energy deduction in the months of June and July, while B2 revealed a decrease in the months of April and June. Additionally, projections in the 2070–2099 under A2 exhibited energy reduction in the months of March through July, while B2 revealed a decrease in April through July. The framework utilized in this study can be exploited to analyze the susceptibility of hydropower production in the long term.

scholarly journals Climate Change Influences of Temporal and Spatial Drought Variation in the Andean High Mountain Basin

Atmosphere ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 558 ◽  
Author(s):  
Dario Zhiña ◽  
Martín Montenegro ◽  
Lisseth Montalván ◽  
Daniel Mendoza ◽  
Juan Contreras ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Climate Impacts ◽  
Global Climate Models ◽  
Return Periods ◽  
Base Period ◽  
Rcp 8.5 ◽  
Near Future ◽  
Far Future

Climate change threatens the hydrological equilibrium with severe consequences for living beings. In that respect, considerable differences in drought features are expected, especially for mountain-Andean regions, which seem to be prone to climate change. Therefore, an urgent need for evaluation of such climate conditions arises; especially the effects at catchment scales, due to its implications over the hydrological services. However, to study future climate impacts at the catchment scale, the use of dynamically downscaled data in developing countries is a luxury due to the computational constraints. This study performed spatiotemporal future long-term projections of droughts in the upper part of the Paute River basin, located in the southern Andes of Ecuador. Using 10 km dynamically downscaled data from four global climate models, the standardized precipitation and evapotranspiration index (SPEI) index was used for drought characterization in the base period (1981–2005) and future period (2011–2070) for RCP 4.5 and RCP 8.5 of CMIP5 project. Fitting a generalized-extreme-value (GEV) distribution, the change ratio of the magnitude, duration, and severity between the future and present was evaluated for return periods 10, 50, and 100 years. The results show that magnitude and duration dramatically decrease in the near future for the climate scenarios under analysis; these features presented a declining effect from the near to the far future. Additionally, the severity shows a general increment with respect to the base period, which is intensified with longer return periods; however, the severity shows a decrement for specific areas in the far future of RCP 4.5 and near future of RCP 8.5. This research adds knowledge to the evaluation of droughts in complex terrain in tropical regions, where the representation of convection is the main limitation of global climate models (GCMs). The results provide useful information for decision-makers supporting mitigating measures in future decades.

scholarly journals Monitoring and Prediction of Climate Change Impact on 24-h Probable Maximum Precipitation in the Southeast of Caspian Sea

2021 ◽  
Author(s):  
Zahra Afzali-Gorouh ◽  
Alireza Faridhosseini ◽  
Bahram Bakhtiari ◽  
Abolfazl Mosaedi ◽  
Nasrin Salehnia
Keyword(s):  
Climate Change ◽  
Caspian Sea ◽  
Climate Change Impact ◽  
General Circulation ◽  
Climatic Data ◽  
Probable Maximum Precipitation ◽  
Maximum Precipitation ◽  
Change Impact ◽  
Near Future ◽  
Far Future

Abstract Due to the impacts of climate change on Probable Maximum Precipitation (PMP), and its importance in designing hydraulic structures, PMP estimation is crucial. In this study, the effect of climate change on 24-h probable maximum precipitation (PMP24) was investigated in a part of the Qareh-Su basin located in the Southeast of Caspian Sea. So far, there are no studies emphasizing on climate change impact on hydrological (physical) PMP values have been conducted in the study area. For this purpose, the climatic data were applied during the years 1988–2017. To generate future data, the outputs of the CanESM2 (Second Generation Canadian Earth System Model) model as a general circulation model (GCM) under optimistic (RCP2.6), middle (RCP4.5), and pessimistic (RCP8.5) emission scenarios, and statistical downscaling model (SDSM) were used in the near (2019-2048) and the far (2049-2078) future periods. The PMP24 values were estimated using a physical method in the baseline and future periods under the three scenarios. The PMP24 value was estimated at 143 mm for the baseline-period, using a physical approach. These values were 98, 105, and 109 for the near-future and 129, 122, and 126mm for the far-future period. The results showed that the physical approach's PMP24 values tend to fall at 14-38%. Overall, the PMP24 values decrease in the future, and the rate of decrease in the near-future was more than the rate of the far-future. The spatial distribution maps of PMP24 in the baseline and future-periods showed that the PMP24 values decreased from west to east.

scholarly journals High-Resolution Climate Projections for a Densely Populated Mediterranean Region

2020 ◽  
Vol 12 (9) ◽  
pp. 3684
Author(s):  
Mohamed Salem Nashwan ◽  
Shamsuddin Shahid ◽  
Eun-Sung Chung
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Bias Correction ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Future Climate Change ◽  
Climate Projections ◽  
Near Future ◽  
Far Future

The present study projected future climate change for the densely populated Central North region of Egypt (CNE) for two representative concentration pathways (RCPs) and two futures (near future: 2020–2059, and far future: 2060–2099), estimated by a credible subset of five global climate models (GCMs). Different bias correction models have been applied to correct the bias in the five interpolated GCMs’ outputs onto a high-resolution horizontal grid. The 0.05° CNE datasets of maximum and minimum temperatures (Tmx, and Tmn, respectively) and the 0.1° African Rainfall Climatology (ARC2) datasets represented the historical climate. The evaluation of bias correction methodologies revealed the better performance of linear and variance scaling for correcting the rainfall and temperature GCMs’ outputs, respectively. They were used to transfer the correction factor to the projections. The five statistically bias-corrected climate projections presented the uncertainty range in the future change in the climate of CNE. The rainfall is expected to increase in the near future but drastically decrease in the far future. The Tmx and Tmn are projected to increase in both future periods reaching nearly a maximum of 5.50 and 8.50 °C for Tmx and Tmn, respectively. These findings highlighted the severe consequence of climate change on the socio-economic activities in the CNE aiming for better sustainable development.

scholarly journals Projection of Hydro-Climatic Extreme Events under Climate Change in Yom and Nan River Basins, Thailand

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 665
Author(s):  
Chanchai Petpongpan ◽  
Chaiwat Ekkawatpanit ◽  
Supattra Visessri ◽  
Duangrudee Kositgittiwong
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Extreme Events ◽  
River Basins ◽  
Annual Rainfall ◽  
Extreme Floods ◽  
Extreme Flood ◽  
Rcp 8.5 ◽  
Near Future ◽  
Far Future

Due to a continuous increase in global temperature, the climate has been changing without sign of alleviation. An increase in the air temperature has caused changes in the hydrologic cycle, which have been followed by several emergencies of natural extreme events around the world. Thailand is one of the countries that has incurred a huge loss in assets and lives from the extreme flood and drought events, especially in the northern part. Therefore, the purpose of this study was to assess the hydrological regime in the Yom and Nan River basins, affected by climate change as well as the possibility of extreme floods and droughts. The hydrological processes of the study areas were generated via the physically-based hydrological model, namely the Soil and Water Assessment Tool (SWAT) model. The projected climate conditions were dependent on the outputs of the Global Climate Models (GCMs) as the Representative Concentration Pathways (RCPs) 2.6 and 8.5 between 2021 and 2095. Results show that the average air temperature, annual rainfall, and annual runoff will be significantly increased in the intermediate future (2046–2070) onwards, especially under RCP 8.5. According to the Flow Duration Curve and return period of peak discharge, there are fluctuating trends in the occurrence of extreme floods and drought events under RCP 2.6 from the future (2021–2045) to the far future (2071–2095). However, under RCP 8.5, the extreme flood and drought events seem to be more severe. The probability of extreme flood remains constant from the reference period to the near future, then rises dramatically in the intermediate and the far future. The intensity of extreme droughts will be increased in the near future and decreased in the intermediate future due to high annual rainfall, then tending to have an upward trend in the far future.

scholarly journals Impact of climate change on sediment yield in the Mekong River basin: a case study of the Nam Ou basin, Lao PDR

2013 ◽  
Vol 17 (1) ◽  
pp. 1-20 ◽  
Author(s):  
B. Shrestha ◽  
M. S. Babel ◽  
S. Maskey ◽  
A. van Griensven ◽  
S. Uhlenbrook ◽  
...  
Keyword(s):  
Climate Change ◽  
Sediment Yield ◽  
General Circulation ◽  
Climate Models ◽  
Greenhouse Gas Emission ◽  
Circulation Model ◽  
Sediment Flux ◽  
Seasonal Temperature ◽  
Impact Of Climate Change ◽  
The Impact

Abstract. This paper evaluates the impact of climate change on sediment yield in the Nam Ou basin located in northern Laos. Future climate (temperature and precipitation) from four general circulation models (GCMs) that are found to perform well in the Mekong region and a regional circulation model (PRECIS) are downscaled using a delta change approach. The Soil and Water Assessment Tool (SWAT) is used to assess future changes in sediment flux attributable to climate change. Results indicate up to 3.0 °C shift in seasonal temperature and 27% (decrease) to 41% (increase) in seasonal precipitation. The largest increase in temperature is observed in the dry season while the largest change in precipitation is observed in the wet season. In general, temperature shows increasing trends but changes in precipitation are not unidirectional and vary depending on the greenhouse gas emission scenarios (GHGES), climate models, prediction period and season. The simulation results show that the changes in annual stream discharges are likely to range from a 17% decrease to 66% increase in the future, which will lead to predicted changes in annual sediment yield ranging from a 27% decrease to about 160% increase. Changes in intra-annual (monthly) discharge as well as sediment yield are even greater (−62 to 105% in discharge and −88 to 243% in sediment yield). A higher discharge and sediment flux are expected during the wet seasons, although the highest relative changes are observed during the dry months. The results indicate high uncertainties in the direction and magnitude of changes of discharge as well as sediment yields due to climate change. As the projected climate change impact on sediment varies remarkably between the different climate models, the uncertainty should be taken into account in both sediment management and climate change adaptation.

scholarly journals Drivers of future water demand in Sydney, Australia: examining the contribution from population and climate change

2020 ◽  
Author(s):  
Adrian Barker ◽  
Andrew Pitman ◽  
Jason P. Evans ◽  
Frank Spaninks ◽  
Luther Uthayakumaran
Keyword(s):  
Climate Change ◽  
Water Demand ◽  
Global Climate Models ◽  
Future Climate ◽  
Present Climate ◽  
Demand Model ◽  
Stochastic Weather Generator ◽  
Near Future ◽  
Far Future ◽  
Sydney Australia

Abstract We examine the relative impact of population increases and climate change in affecting future water demand for Sydney, Australia. We use the Weather and Research Forecasting model, a water demand model and a stochastic weather generator to downscale four different global climate models for the present (1990–2010), near (2020–2040) and far (2060–2080) future. Projected climate change would increase median metered consumption, at 2019/2020 population levels, from around 484 GL under present climate to 484–494 GL under near future climate and 495–505 GL under far future climate. Population changes from 2014/2015 to 2024/2025 have a far larger impact, increasing median metered consumption from 457 to 508 GL under the present climate, 463 to 515 GL under near future climate and from 471 to 524 GL under far future climate. The projected changes in consumption are sensitive to the climate model used. Overall, while population growth is a far stronger driver of increasing water demand than climate change for Sydney, both act in parallel to reduce the time it would take for all storage to be exhausted. Failing to account for climate change would therefore lead to overconfidence in the reliability of Sydney's water supply.

Ensemble climate predictions using climate models and observational constraints

2007 ◽  
Vol 365 (1857) ◽  
pp. 2029-2052 ◽  
Author(s):  
Peter A Stott ◽  
Chris E Forest
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Climate Changes ◽  
Climate Models ◽  
State Of The Art ◽  
General Circulation Models ◽  
Computationally Efficient ◽  
Temperature Changes ◽  
Large Ensembles ◽  
Past Climate Change

Two different approaches are described for constraining climate predictions based on observations of past climate change. The first uses large ensembles of simulations from computationally efficient models and the second uses small ensembles from state-of-the-art coupled ocean–atmosphere general circulation models. Each approach is described and the advantages of each are discussed. When compared, the two approaches are shown to give consistent ranges for future temperature changes. The consistency of these results, when obtained using independent techniques, demonstrates that past observed climate changes provide robust constraints on probable future climate changes. Such probabilistic predictions are useful for communities seeking to adapt to future change as well as providing important information for devising strategies for mitigating climate change.

scholarly journals Simulating Climate Change Impacts and Adaptive Measures for Rice Cultivation in Hunan Province, China

2016 ◽  
Vol 55 (6) ◽  
pp. 1359-1376 ◽  
Author(s):  
Yamei Li ◽  
Wenxiang Wu ◽  
Quansheng Ge ◽  
Yang Zhou ◽  
Chenchen Xu
Keyword(s):  
Climate Change ◽  
Adverse Effect ◽  
Rice Yield ◽  
Ensemble Average ◽  
Hunan Province ◽  
Future Climate Change ◽  
Yield Reduction ◽  
Average Yield ◽  
Fertilization Effects ◽  
Impacts Of Climate Change

AbstractClimate change will inevitably continue for the next few decades and will have an impact on climate-sensitive agricultural production, emphasizing the need to design effective adaptive strategies to cope with climate risk or take advantage of potential climatic benefits. In this study, the latest version of the Crop Environment Resource Synthesis-Rice (CERES-Rice) model was applied to assess the impacts of climate change and carbon dioxide (CO2) fertilization on rice yield, as well as the effectiveness of two popularly adopted adaptive measures in Hunan Province, the main rice-production location in China. The simulation spanned 30 years of baseline (1981–2010) as well as three future periods (2011–40, 2041–70, and 2071–99) with climate data generated by five general circulation models under the newly developed representative concentration pathway (RCP) 4.5 and 8.5 scenarios. The simulation results showed that, in comparison with average rice yield during the baseline (1981–2010), the ensemble-average yield of all cultivars during the 2020s, 2050s, and 2080s would decrease under both RCPs without CO2 fertilization effects. The ensemble-average yield reduction during the 2080s was alleviated under both RCPs if CO2 fertilization effects were accounted for. Adaptation simulations indicated that two adaptive measures (switching cultivars and changing planting dates) could mitigate the adverse effect to different extents. The intermodel variability under both RCPs was generally small. These findings may provide useful insight into the potential impacts of climate change on rice yield and effective adaptive measures to mitigate the adverse effect of future climate change in Hunan Province.

scholarly journals Impacts of future climate change on potential yields of major crops in China

2014 ◽  
Vol 5 (1) ◽  
pp. 617-647
Author(s):  
Y. Yin ◽  
Q. Tang ◽  
X. Liu
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Future Climate ◽  
Future Climate Change ◽  
Yield Reduction ◽  
Climate Data ◽  
Potential Yield ◽  
Crop Models

Abstract. Climate change may affect crop development and yield, and consequently cast a shadow of doubt over China's food self-sufficiency efforts. In this study we used the model projections of a couple of global gridded crop models (GGCMs) to assess the effects of future climate change on the potential yields of the major crops (i.e. wheat, rice, maize and soybean) over China. The GGCMs were forced with the bias-corrected climate data from 5 global climate models (GCMs) under the Representative Concentration Pathways (RCP) 8.5 which were made available by the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). The results show that the potential yields of rice may increase over a large portion of China. Climate change may benefit food productions over the high-altitude and cold regions where are outside current main agricultural area. However, the potential yield of maize, soybean and wheat may decrease in a large portion of the current main crop planting areas such as North China Plain. Development of new agronomic management strategy may be useful for coping with climate change in the areas with high risk of yield reduction.

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