Water resources management in the context of future climate and development changes: a South African case study

2015 ◽  
Vol 6 (4) ◽  
pp. 772-786 ◽  
Author(s):  
S. K. Mantel ◽  
D. A. Hughes ◽  
A. S. Slaughter

Modelling uncertainty under future climate change and socio-economic development is essential for adaptive planning and sustainable management of water resources. This is the first study in South Africa incorporating uncertainty within climate and development scenario modelling for understanding the implications on water availability through comparison of the resulting uncertainty. A Water Evaluation and Planning model application was developed for the Amatole system (South Africa), which consists of three catchments with inter-basin transfers. Outputs for three sets of scenarios are presented, namely development-only, climate-change-only and climate-and-development scenarios. Near future (2046–2065) development uncertainty was estimated from three scenarios (lower, intermediate and upper) and climate change uncertainty from nine downscaled global climate models under the A2 emissions scenario. Consideration of development increased the uncertainty associated with climate-change-only scenarios, particularly at low flows. Water deficits are projected in the future for the Amatole system as the present water infrastructure cannot meet water demands under the near future intermediate and upper development scenarios. The deficits are likely to be exacerbated by inclusion of environmental flows (not included in the model). The recommended strategy is that of adaptive management, in combination with continual monitoring of climate and development changes, for reducing future uncertainty.

2014 ◽  
Vol 5 (1) ◽  
pp. 617-647
Author(s):  
Y. Yin ◽  
Q. Tang ◽  
X. Liu

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.


2013 ◽  
Vol 70 (2) ◽  
pp. 159-168 ◽  
Author(s):  
Richard D. Hedger ◽  
Line E. Sundt-Hansen ◽  
Torbjørn Forseth ◽  
Ola Ugedal ◽  
Ola H. Diserud ◽  
...  

We predict an increase in parr recruitment and smolt production of Atlantic salmon (Salmo salar) populations along a climate gradient from the subarctic to the Arctic in western and northern Norway in response to future climate change. Firstly, we predicted local stream temperature and discharge from downscaled data obtained from Global Climate Models. Then, we developed a spatially explicit individual-based model (IBM) parameterized for the freshwater stage, with combinations of three different postsmolt survival probabilities reflecting different marine survival regimes. The IBM was run for three locations: southern Norway (∼59°N), western Norway (∼62°N), and northern Norway (∼70°N). Increased temperatures under the future climate regimes resulted in faster parr growth, earlier smolting, and elevated smolt production in the western and northern locations, in turn leading to increased egg deposition and elevated recruitment into parr. In the southern location, density-dependent mortality of parr resulting from low summer wetted-areas reduced predicted future smolt production in comparison to the other locations. It can be inferred, therefore, that climate change may have both positive and negative effects on anadromous fish abundance within the subarctic–Arctic according to geographical region.


2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Abu Reza Md. Towfiqul Islam ◽  
Shuanghe Shen ◽  
Zhenghua Hu ◽  
M. Atiqur Rahman

Drought hazard is one of the main hindrances for sustaining food security in Bangladesh, and climate change may exacerbate it in the next several decades. This study aims to evaluate drought hazard at current and future climate change conditions in theBoropaddy cultivated areas of western Bangladesh using simulated climate data from the outputs of three global climate models (GCMs) based on the SRES A1B scenario for the period between 2041 and 2070. The threshold level of Standardized Precipitation Evapotranspiration Index (SPEI) was employed to identify drought events and its probability distribution function (PDF) was applied to create the drought hazard index. The study demonstrates that enhancement of potential evapotranspiration (PET) will surpass that of precipitation, resulting in intensified drought events in future. In addition, the PDFs of drought events will move the upper tail in future period compared to the baseline. The results showed that the southwestern region was more severe to the drought hazard than the northwestern region during the period of 1984 to 2013. From the results of three GCMs, in the mid-century period, drought hazard will slightly increase in the northwestern region and flatten with a decrease in the southwestern region. The outcomes will help to allocate agricultural adaptation plans under climate change condition in Bangladesh.


2012 ◽  
Vol 16 (9) ◽  
pp. 3341-3349 ◽  
Author(s):  
R. S. Crosbie ◽  
D. W. Pollock ◽  
F. S. Mpelasoka ◽  
O. V. Barron ◽  
S. P. Charles ◽  
...  

Abstract. The Köppen-Geiger climate classification has been used for over a century to delineate climate types across the globe. As it was developed to mimic the distribution of vegetation, it may provide a useful surrogate for making projections of the future distribution of vegetation, and hence resultant hydrological implications, under climate change scenarios. This paper developed projections of the Köppen-Geiger climate types covering the Australian continent for a 2030 and 2050 climate relative to a 1990 historical baseline climate using 17 Global Climate Models (GCMs) and five global warming scenarios. At the highest level of classification for a +2.4 °C future climate (the upper limit projected for 2050) relative to the historical baseline, it was projected that the area of the continent covered by – tropical climate types would increase from 8.8% to 9.1%; – arid climate types would increase from 76.5% to 81.7%; – temperate climate types would decrease from 14.7% to 9.2%; – cold climate types would decrease from 0.016% to 0.001%. Previous climate change impact studies on water resources in Australia have assumed a static vegetation distribution. If the change in projected climate types is used as a surrogate for a change in vegetation, then the major transition in climate from temperate to arid in parts of Australia under a drier future climate could cause indirect effects on water resources. A transition from annual cropping to perennial grassland would have a compounding effect on the projected reduction in recharge. In contrast, a transition from forest to grassland would have a mitigating effect on the projected reduction in runoff.


2020 ◽  
Vol 12 (9) ◽  
pp. 3684
Author(s):  
Mohamed Salem Nashwan ◽  
Shamsuddin Shahid ◽  
Eun-Sung Chung

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.


2012 ◽  
Vol 9 (6) ◽  
pp. 7415-7440 ◽  
Author(s):  
R. S. Crosbie ◽  
D. W. Pollock ◽  
F. S. Mpelasoka ◽  
O. V. Barron ◽  
S. P. Charles ◽  
...  

Abstract. The Köppen-Geiger climate classification has been used for over a century to delineate climate types across the globe. As it was developed to mimic the distribution of vegetation it may provide a useful surrogate for making projections of the future distribution of vegetation, and hence resultant hydrological implications, under climate change scenarios. This paper developed projections of the Köppen-Geiger climate types covering the Australian continent for a 2030 and 2050 climate relative to a 1990 historical baseline climate using 17 Global Climate Models (GCMs) and five global warming scenarios. At the highest level of classification for a +2.4 °C future climate (the upper limit projected for 2050) relative to the historical baseline, it was projected that the area of the continent covered by: – Tropical climate types would increase from 8.8% to 9.1% – Arid climate types would increase from 76.5% to 81.7% – Temperate climate types would decrease from 14.7% to 9.2% – Cold climate types would decrease from 0.016% to 0.001%. Previous climate change impact studies on water resources in Australia have assumed a static vegetation distribution. If the change in projected climate types is used as a surrogate for a change in vegetation, then the major transition in climate from Temperate to Arid in parts of Australia under a drier future climate could cause indirect effects on water resources. For a transition from annual cropping to perennial grassland this would have a compounding effect on the projected reduction in recharge. In contrast, a transition from forest to grassland would have a mitigating effect on the projected reduction in runoff.


2017 ◽  
Vol 9 (1) ◽  
pp. 137-155 ◽  
Author(s):  
Hashim Isam Jameel Al-Safi ◽  
P. Ranjan Sarukkalige

Abstract The conceptual rainfall–runoff (HBV model) is applied to evaluate impacts of future climate changes on the hydrological system of the Richmond River catchment, Australia. Daily observed rainfall, temperature and discharge and long-term monthly mean potential evapotranspiration from the hydro-meteorological stations within the catchment over the period 1972–2014 were used to run, calibrate and validate the HBV model before the simulation. Future climate signals were extracted from a multi-model ensemble of eight global climate models (GCMs) of the CMIP5 under three scenarios (RCP2.6, RCP4.5 and RCP8.5). The calibrated HBV model was forced with the downscaled rainfall and temperature to simulate future streamflow at catchment outlet for the near-future (2016–2035), mid (2046–2065) and late (2080–2099) 21st century. A baseline run, with baseline climate period 1971–2010, was used to represent current climate status. Almost all GCMs’ scenarios predict slight increase in annual mean rainfall during the beginning of the century and decrease towards the mid and late century. Modelling results also show positive trends in annual mean streamflow during the near-future (13–23%), and negative trends in the mid (2–6%) and late century (6–16%), under all scenarios compared to the baseline-run. Findings could assist in managing future water resources in the catchment.


Climate ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 16
Author(s):  
Suzanna Meeussen ◽  
Anouschka Hof

Climate change is expected to have an impact on the geographical distribution ranges of species. Endemic species and those with a restricted geographic range may be especially vulnerable. The Persian jird (Meriones persicus) is an endemic rodent inhabiting the mountainous areas of the Irano-Turanian region, where future desertification may form a threat to the species. In this study, the species distribution modelling algorithm MaxEnt was used to assess the impact of future climate change on the geographic distribution range of the Persian jird. Predictions were made under two Representative Concentration Pathways and five different climate models for the years 2050 and 2070. It was found that both bioclimatic variables and land use variables were important in determining potential suitability of the region for the species to occur. In most cases, the future predictions showed an expansion of the geographic range of the Persian jird which indicates that the species is not under immediate threat. There are however uncertainties with regards to its current range. Predictions may therefore be an over or underestimation of the total suitable area. Further research is thus needed to confirm the current geographic range of the Persian jird to be able to improve assessments of the impact of future climate change.


2017 ◽  
Vol 30 (17) ◽  
pp. 6701-6722 ◽  
Author(s):  
Daniel Bannister ◽  
Michael Herzog ◽  
Hans-F. Graf ◽  
J. Scott Hosking ◽  
C. Alan Short

The Sichuan basin is one of the most densely populated regions of China, making the area particularly vulnerable to the adverse impacts associated with future climate change. As such, climate models are important for understanding regional and local impacts of climate change and variability, like heat stress and drought. In this study, climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are validated over the Sichuan basin by evaluating how well each model can capture the phase, amplitude, and variability of the regionally observed mean, maximum, and minimum temperature between 1979 and 2005. The results reveal that the majority of the models do not capture the basic spatial pattern and observed means, trends, and probability distribution functions. In particular, mean and minimum temperatures are underestimated, especially during the winter, resulting in biases exceeding −3°C. Models that reasonably represent the complex basin topography are found to generally have lower biases overall. The five most skillful climate models with respect to the regional climate of the Sichuan basin are selected to explore twenty-first-century temperature projections for the region. Under the CMIP5 high-emission future climate change scenario, representative concentration pathway 8.5 (RCP8.5), the temperatures are projected to increase by approximately 4°C (with an average warming rate of +0.72°C decade−1), with the greatest warming located over the central plains of the Sichuan basin, by 2100. Moreover, the frequency of extreme months (where mean temperature exceeds 28°C) is shown to increase in the twenty-first century at a faster rate compared to the twentieth century.


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