scholarly journals Drought Monitoring Based on the SPI and RDI Indices under Climate Change Scenarios (Case Study: Semi-Arid Areas of West Golestan Province)

Ecopersia ◽  
2016 ◽  
Vol 4 (4) ◽  
pp. 1585-1602 ◽  
Author(s):  
Morteza Akbari ◽  
◽  
Majid Ownegh ◽  
Hamidreza Asgari ◽  
Amir Sadoddin ◽  
...  
Keyword(s):  
Climate Change ◽  
Drought Monitoring ◽  
Climate Change Scenarios ◽  
Arid Areas ◽  
Golestan Province ◽  
Semi Arid

Is the impact of climate change on desertification predictable?

2020 ◽  
Author(s):  
YaoJie Yue ◽  
Min Li
Keyword(s):  
Climate Change ◽  
Inner Mongolia ◽  
North China ◽  
Evaluation Model ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Arid Areas ◽  
Sandy Land ◽  
Desertification Risk ◽  
Semi Arid

<p>Desertification, as one of the gravest ecological and environmental problems in the world, is affected both by climate change and human activities. As the consequences of global warming, the temperature in global arid and semi-arid areas is expected to increase by 1-3℃ by the end of this century. This change will significantly influence the spatial and temporal pattern of temperature, precipitation and wind speed in global arid and semi-arid areas, and in turn, ultimately impact the processing of desertification. Although current studies point out that future climate change tends to increase the risk of desertification. However, the future global or regional desertification risk under different climate change scenarios hasn’t been quantitively assessed. In this paper, we focused on this question by building a new model to evaluate this risk of desertification under an extreme climate change scenario, i.e. RCP8.5 (Representative Concentration Pathways, RCPs). We selected the northern agro-pastoral ecotone in China as the study area, where is highly sensitive to desertification. Firstly, the risk indicators of desertification were chosen in both natural and anthropic aspects, such as temperature, precipitation, wind speed, evaporation, and population. Secondly, the decision tree C5.0 algorithm of the machine learning technique was used to construct the quantitative evaluation model of land desertification risk based on the database of the 1:100,000 desertification map in China. Thirdly, with the support of the simulated meteorological data by General Circulation Models of HadGEM2-ES, the risk of desertification in the agro-pastoral ecotone in the north China under the RCP 8.5 scenario and SSP3 scenario (Shared Socioeconomic Pathways, SSPs) were predicted. The results show that the overall accuracy of the C5.0-based quantitative evaluation model for desertification risk is up to 83.32%, indicating that the C5.0 can better distinguish the risk of desertification according to the status of desertification impacting factors. Under the influence of future climate change, the agro-pastoral ecotone in northern China was estimated to be dominated by mild desertification risk, covering an area of more than 70%. Severe and moderate desertification risk is mainly distributed in the vicinity of Hulunbuir sandy land in the northeast of Inner Mongolia and the Horqin sandy land in the junction between Inner Mongolia, Jilin and Liaoning provinces. Compared with the datum period, the risk of desertification will decrease under the RCP8.5-SSP3 scenario. However, the desertification risk in Hulunbuir sandy land and that in the northwest of Jilin province will increase. The results of this study provide a scientific basis for developing more effective desertification control strategies to adapt to climate change in the agro-pastoral ecotone in north China. More importantly, it shows that the desertification risk can be predicted under the different climate change scenarios, which will help us to make a better understanding of the potential trend of desertification in the future, especially when the earth is getting warmer.</p>

scholarly journals CMIP5 climate projections and RUSLE-based soil erosion assessment in the central part of Iran

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Fatemeh Hateffard ◽  
Safwan Mohammed ◽  
Karam Alsafadi ◽  
Glory O. Enaruvbe ◽  
Ahmad Heidari ◽  
...  
Keyword(s):  
Climate Change ◽  
Soil Erosion ◽  
Climate Model ◽  
Sustainable Land Use ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
Arid Areas ◽  
Residential Areas ◽  
Atmospheric Variations ◽  
Semi Arid

AbstractSoil erosion (SE) and climate change are closely related to environmental challenges that influence human wellbeing. However, the potential impacts of both processes in semi-arid areas are difficult to be predicted because of atmospheric variations and non-sustainable land use management. Thus, models can be employed to estimate the potential effects of different climatic scenarios on environmental and human interactions. In this research, we present a novel study where changes in soil erosion by water in the central part of Iran under current and future climate scenarios are analyzed using the Climate Model Intercomparison Project-5 (CMIP5) under three Representative Concentration Pathway-RCP 2.6, 4.5 and 8.5 scenarios. Results showed that the estimated annual rate of SE in the study area in 2005, 2010, 2015 and 2019 averaged approximately 12.8 t ha−1 y−1. The rangeland areas registered the highest soil erosion values, especially in RCP2.6 and RCP8.5 for 2070 with overall values of 4.25 t ha−1 y−1 and 4.1 t ha−1 y−1, respectively. They were followed by agriculture fields with 1.31 t ha−1 y−1 and 1.33 t ha−1 y−1. The lowest results were located in the residential areas with 0.61 t ha−1 y−1 and 0.63 t ha−1 y−1 in RCP2.6 and RCP8.5 for 2070, respectively. In contrast, RCP4.5 showed that the total soil erosion could experience a decrease in rangelands by − 0.24 t ha−1 y−1 (2050), and − 0.18 t ha−1 y−1 (2070) or a slight increase in the other land uses. We conclude that this study provides new insights for policymakers and stakeholders to develop appropriate strategies to achieve sustainable land resources planning in semi-arid areas that could be affected by future and unforeseen climate change scenarios.

scholarly journals Tidal flood area mapping in the face of climate change scenarios: case study in a tropical estuary in the Brazilian semi-arid region

2021 ◽  
Vol 21 (11) ◽  
pp. 3353-3366
Author(s):  
Paulo Victor N. Araújo ◽  
Venerando E. Amaro ◽  
Leonlene S. Aguiar ◽  
Caio C. Lima ◽  
Alexandre B. Lopes
Keyword(s):  
Climate Change ◽  
Flood Risk ◽  
Arid Region ◽  
Risk Mapping ◽  
Climate Change Scenarios ◽  
Management Actions ◽  
The Face ◽  
Semi Arid Region ◽  
Semi Arid

Abstract. Previous studies on tidal flood mapping are mostly through continental- and/or global-scale approaches. Moreover, the few works on local-scale perception are concentrated in Europe, Asia, and North America. Here, we present a case study approaching a tidal flood risk mapping application in the face of climate change scenarios in a region with a strong environmental and social appeal. The study site is an estuarine cut in the Brazilian semi-arid region, covering part of two state conservation units, which has been suffering severe consequences from tidal flooding in recent years. In this case study, we used high-geodetic-precision data (lidar DEM), together with robust tidal return period statistics and data from current sea level rise scenarios. We found that approximately 327.60 km2 of the estuary is under tidal flood risk and in need of mitigation measures. This case study can serve as a basis for future management actions, as well as a model for applying risk mapping in other coastal areas.

scholarly journals Potential Impacts of Future Climate Change Scenarios on Ground Subsidence

Water ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 219 ◽  
Author(s):  
Antonio-Juan Collados-Lara ◽  
David Pulido-Velazquez ◽  
Rosa María Mateos ◽  
Pablo Ezquerro
Keyword(s):  
Climate Change ◽  
Land Subsidence ◽  
Ground Subsidence ◽  
Lower Percentage ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Fine Grained ◽  
Fine Grained Material ◽  
The Impact

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.

Short Communication: Climate change and biofuel wheat: A case study of southern Saskatchewan

2012 ◽  
Vol 92 (3) ◽  
pp. 421-425 ◽  
Author(s):  
Hong Wang ◽  
Yong He ◽  
Budong Qian ◽  
Brian McConkey ◽  
Herb Cutforth ◽  
...  
Keyword(s):  
Climate Change ◽  
Grain Yield ◽  
Short Communication ◽  
Weather Data ◽  
Yield Reduction ◽  
Climate Change Scenarios ◽  
Communication Climate ◽  
Stochastic Weather Generator ◽  
Ipcc Sres

Wang, H., He, Y., Qian, B., McConkey, B., Cutforth, H., McCaig, T., McLeod, G., Zentner, R., DePauw, R., Lemke, R., Brandt, K., Liu, T., Qin, X., White, J., Hunt, T. and Hoogenboom, G. 2012. Short Communication: Climate change and biofuel wheat: A case study of southern Saskatchewan. Can. J. Plant Sci. 92: 421–425. This study assessed potential impacts of climate change on wheat production as a biofuel crop in southern Saskatchewan, Canada. The Decision Support System for Agrotechnology Transfer-Cropping System Model (DSSAT-CSM) was used to simulate biomass and grain yield under three climate change scenarios (CGCM3 with the forcing scenarios of IPCC SRES A1B, A2 and B1) in the 2050s. Synthetic 300-yr weather data were generated by the AAFC stochastic weather generator for the baseline period (1961–1990) and each scenario. Compared with the baseline, precipitation is projected to increase in every month under all three scenarios except in July and August and in June for A2, when it is projected to decrease. Annual mean air temperature is projected to increase by 3.2, 3.6 and 2.7°C for A1B, A2 and B1, respectively. The model predicted increases in biomass by 28, 12 and 16% without the direct effect of CO2 and 74, 55 and 41% with combined effects (climate and CO2) for A1B, A2 and B1, respectively. Similar increases were found for grain yield. However, the occurrence of heat shock (>32°C) will increase during grain filling under the projected climate conditions and could cause severe yield reduction, which was not simulated by DSSAT-CSM. This implies that the future yield under climate scenarios might have been overestimated by DSSAT-CSM; therefore, model modification is required. Several measures, such as early seeding, must be taken to avoid heat damages and take the advantage of projected increases in temperature and precipitation in the early season.

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