Search Results (6)

Climate change (CC) affects millions of people directly or indirectly. Especially, the effect of CC on the hydrological regime is extensive. Hence, understanding its impact is highly essential. In this study, the Bharathapuzha river basin (BRB) lying in the Western Ghats region of southern India is considered for CC impact assessment, as it is a highly complex and challenging watershed, due to its varying topographical features, such as soil texture, land use/land cover types, slope, and climatology, including rainfall and temperature patterns. To understand the CC impact on the hydrological variables at BRB in the future, five downscaled global circulation models (GCMs) were used, namely BNU-ESM, Can-ESM, CNRM, MPI-ESM MR, and MPI-ESM LR. These GCMs were obtained for two representative concentration pathway (RCP) scenarios: 4.5 representing normal condition and 8.5 representing the worst condition of projected carbon and greenhouse gases concentration on the lower atmosphere. To obtain the continuous simulation of hydrological variables, the SWAT hydrological model was adopted in this study. Results showed that rainfall pattern, evapotranspiration, and soil moisture will increase at moderate to significant levels in the future. This is especially seen during the far future period (i.e., 2071 to 2100). Similar results were obtained for surface runoff. For instance, surface runoff will increase up to 19.2% (RCP 4.5) and 36% (RCP 8.5) during 2100, as compared to the average historical condition (1981–2010). The results from this study will be useful for various water resources management and adaptation measures in the future, and the methodology can be adopted for similar regions. Full article

The global hydrological cycle is vulnerable to changing climatic conditions, especially in developing regions, which lack abundant resources and management of freshwater resources. This study evaluates the impacts of climate change on the hydrological regime of the Chirah and Dhoke Pathan sub catchments of the Soan River Basin (SRB), in Pakistan, by using the climate models included in the NEX-GDDP dataset and the hydrological model HBV-light. After proper calibration and validation, the latter is forced with NEX-GDDP inputs to simulate a historic and a future (under the RCP 4.5 and RCP 8.5 emission scenarios) streamflow. Multiple evaluation criteria were employed to find the best performing NEX-GDDP models. A different ensemble was produced for each sub catchment by including the five best performing NEX-GDDP GCMs (ACCESS1-0, CCSM4, CESM1-BGC, MIROC5, and MRI-CGCM3 for Chirah and BNU-ESM, CCSM4, GFDL-CM3. IPSL-CM5A-LR and NorESM1-M for Dhoke Pathan). Our results show that the streamflow is projected to decrease significantly for the two sub catchments, highlighting the vulnerability of the SRB to climate change. Full article

The energy industry is faced with important investment and optimization choices especially for wind power as a fuel of the future, especially for China which boasts the largest installed wind power capacity. This study therefore assessed the potential status of future wind power over China using Coupled Model Intercomparison Project phase 5 (CMIP5) models. Changes in wind power density relative to the current time period 1981–2005 were then analyzed using near-surface wind speeds extrapolated to hub-height of 90 m above ground level. The results showed relatively modest differences between the models and reanalysis. The majority of the models showed any two of location, shape, and size agreement for peak areas albeit models BCC-CSM-1-1-M, BNU-ESM, and CanESM2 tended to overestimate wind speed by up to 2.5 m/s. The multi-model ensemble mean performed better than most individual models in representing the wind characteristics over the study area. Future changes in wind power density showed an increase (decrease) over the coastal areas of the South China Sea and Bay of Bengal (areas along the 30°–40° N belt). In all, the changes were not significant enough to neither warrant a move away from wind energy nor threaten considerably the marketability and profitability under the present warming scenario rate. Full article

Investigating long-term drought trends is of great importance in coping with the adverse effects of global warming. However, little attention has been focused on studying the detailed spatial variability and attribution of drought variation in China. In this study, we first generated a 1 km resolution monthly climate dataset for the period 1901–2100 across China using the delta spatial downscaling method to assess the variability of the Standardized Precipitation Evaporation Index (SPEI). We then developed a simple approach to quantifying the contributions of water supply (precipitation) and demand (potential evapotranspiration, PET) on SPEI variability, according to the meaning of the differentiating SPEI equation. The results indicated that the delta framework could accurately downscale and correct low-spatial-resolution monthly temperatures and precipitation from the Climatic Research Unit and general circulation models (GCMs). Of the 27 GCMs analyzed, the BNU-ESM, CESM1-CAM5, and GFDL-ESM2M were found to be the most accurate in modeling future temperatures and precipitation. We also found that, compared with the past (1901–2017), the climate in the future (2018–2100) will tend toward significant droughts, although both periods showed a high spatial heterogeneity across China. Moreover, the proportion of areas with significantly decreasing SPEI trends was far greater than the proportion of those with increasing trends in most cases, especially for northwestern and northern China. Finally, the proposed approach to quantifying precipitation and PET contributions performed well according to logical evaluations. The percentage contributions of precipitation and PET on SPEI variability varied with study periods, representative concentration pathway scenarios, trend directions, and geographic spaces. In the past, PET contributions for significant downward trends and precipitation contributions for significantly upward trends accounted for 95% and 72%, while their future contributions were 57 ± 22%–149 ± 20% and 95 ± 27%–190 ± 58%, respectively. Overall, our results provide detailed insights for planning flexible adaptation and mitigation strategies to cope with the adverse effects of climate drought across China. Full article

The total phosphorus (TP) concentration, as the primary limiting eutrophication factor in the Mahabad Dam reservoir in Iran, was studied, considering the combined impacts of climate change, as well as the scenarios on changes in upstream TP loadings and downstream dam water allocations. Downscaled daily projected climate data were obtained from the Beijing Normal University Earth System Model (BNU-ESM) under moderate (RCP4.5) and extreme (RCP8.5) scenarios. These data were used as inputs of a calibrated Soil and Water Assessment Tool (SWAT) model of the watershed in order to determine the effects of climate change on runoff yields in the watershed from 2020 to 2050. The SWAT model was calibrated/validated using the SUFI-2 algorithm in the SWAT Calibration Uncertainties Program (SWAT-CUP). Moreover, to model TP concentration in the reservoir and to investigate the effects of upstream/downstream scenarios, along with forecasted climate-induced changes in streamflow and evaporation rates, the System Dynamics (SD) model was implemented. The scenarios covered a combination of changes in population, agricultural and livestock farming activities, industrialization, water conservation, and pollution control. Relative to the year 2011 in which the water quality data were available, the SD results showed the highest TP concentrations in the reservoir under scenarios in which the inflow to the reservoir had decreased, while the upstream TP loadings and downstream dam water allocations had increased (+29.9%). On the other hand, the lowest TP concentration was observed under scenarios in which upstream TP loadings and dam water allocations had decreased (−18.5%). Full article

Climate policy plays an important role in keeping global temperature rises below the target of 1.5–2 °C above pre-industrial levels, and technological innovations are key to determining the effectiveness of climate policy. In this study, we investigated the climate impact of the USA’s policy choices using the enforced multi-factor regional climate and economy system (EMRICES,) and the Earth system model from Beijing Normal University (BNU-ESM). Three emission scenarios were designed based on the assumption of whether or not the US follows its proposed nationally determined contribution (NDC) and makes use of technological innovations. The results showed that if the US does not implement the NDC and had no technological progress, there would be an extra 176.7 Gt of cumulative carbon emissions by the end of the 21st century compared to that of all the countries that follow their NDC. The additional emissions would lead to an increase of 62 ppm in CO₂ concentration and a 0.4 °C increase in global warming by 2100. It would also lead to a 2% loss for the US and Chinese economies, compared to the NDC scenario. The Earth system model results also show that even if all the countries follow the DNC, it would be difficult to keep the temperature from increasing less than 1.5 °C. This study implies that the US withdrawal from the Paris Agreement and their refusal to adopt technological progress is not conducive to achieving the 1.5 °C goal, and more stringent emission reduction targets or technology innovations would be required for the world to control global warming to a level below 1.5 °C. Full article