scholarly journals Local Melon and Watermelon Crop Populations to Moderate Yield Responses to Climate Change in North Africa

Climate ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 129
Author(s):  
Stuart Alan Walters ◽  
Mimouni Abdelaziz ◽  
Rachid Bouharroud
Keyword(s):  
Climate Change ◽  
Citrullus Lanatus ◽  
Pure Line ◽  
Future Climate Change ◽  
High Genetic Diversity ◽  
High Productivity ◽  
Crop Varieties ◽  
High Yields ◽  
Yield Responses ◽  
Semi Arid

Climate change is having a tremendous influence on world food production, with arid, semi-arid, and dry sub-humid areas especially susceptible. In these areas, locally adapted crop varieties or landraces can be used to mitigate the influence of climate change on current and future food security challenges. The high genetic diversity within these populations allows for crops to adapt to changing environments or other stresses that influence growth and productivity. Thus, local Moroccan melon (Cucumis melo) and watermelon (Citrullus lanatus) landraces were compared to pure-line varieties in southwestern Morocco to identify their adaptability and possible ability to mitigate current and future climate change. Results indicated that the melon and watermelon landraces evaluated most likely could help mitigate yield losses from climate change in this area of Morocco. ‘AitOulyad’, a local muskmelon type, and ‘Rasmouka Ananas’ were both outstanding melon landraces with high plant vigor and yields. For watermelon, ‘AitOulyad’ had extremely high yields but had high numbers of seed in the flesh, while ‘Rasmouka’ had a lower yield, fewer seeds in the flesh, and a higher fruit consistency. This research indicates that melon and watermelon landraces in this area of southwestern Morocco with a semi-arid to arid climate will continue to play a major role in crop adaptation to maintain high productivity under a rapidly changing environment.

scholarly journals As Experiências da Coalizão Adapta Sertão na Disseminação de Tecnologias e Estratégias de Adaptação à Mudança Climática para o Agricultor Familiar do Semiárido Brasileiro (The experience of the Adapta Sertão Coalition in Disseminating Climate Change...)

2012 ◽  
Vol 4 (6) ◽  
pp. 1336 ◽  
Author(s):  
Daniele Cesano ◽  
Emilio Lèbre La Rovere ◽  
Martin Obermaier ◽  
Thais Corral ◽  
Laise Santos da Silva ◽  
...  
Keyword(s):  
Climate Change ◽  
Production Systems ◽  
Public Policies ◽  
Climate Change Impacts ◽  
Future Climate Change ◽  
Small Farmers ◽  
Family Farming ◽  
Adaptation Measures ◽  
Access To Water ◽  
Semi Arid

Este artigo descreve a experiência da coalizão Adapta Sertão na experimentação e disseminação de sistemas produtivos que possam tornar o agricultor familiar do Semiárido mais resiliente aos impactos da variação climática atual e da mudança do clima no futuro. Durante as experimentações, a coalizão teve que enfrentar várias barreiras ligadas à falta de integração entre políticas públicas existentes e projetos pilotos em comunidades locais. Hoje, a adaptação à mudança do clima não está sendo considerada na implementação de obras hídricas de pequeno e médio porte, que são de grande importância porque, geralmente, conseguem beneficiar as faixas de população mais pobres e mais suscetíveis aos impactos climáticos. As experiências mostram que é preciso desenvolver, com urgência, políticas públicas inovadoras que consigam integrar o acesso à água com a disseminação de tecnologias de adaptação e de sistemas produtivos mais resilientes à seca.  Palavras - chave: medidas de adaptação, agricultura familiar, semiárido, tecnologia.  The experience of the Adapta Sertão Coalition in Disseminating Climate Change Adaptation Technologies and Strategies for Family Farmers in Semi Arid Brazil  ABSTRACTThis paper describes the experience of the Adapta Sertão coalition in testing and experimenting production systems that have the potential to make small farmers of semi-arid Brazil more resilient to current and future climate change impacts. During the different testing, the coalition had to overcome several barriers linked to a lack of integration between current public policies. For example, today climate change is not considered in the design and implementation of small and medium hydraulic infrastructures. This limits the benefits to the target groups (small farmers) that are more likely to be affected by climate change. The experiences show that it is urgent and necessary to develop public policies to better integrate access to water, dissemination of climate resilient technologies and implementation of production systems more adequate to the semi arid conditions.  Keywords: adaptation measures, family farming, semi-arid, technology.

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 Assessment of Streamflow from EURO-CORDEX Regional Climate Simulations in Semi-Arid Catchments Using the SWAT Model

2021 ◽  
Vol 13 (13) ◽  
pp. 7120
Author(s):  
Alberto Martínez-Salvador ◽  
Agustín Millares ◽  
Joris P. C. Eekhout ◽  
Carmelo Conesa-García
Keyword(s):  
Climate Change ◽  
Assessment Tool ◽  
Swat Model ◽  
Regional Climate ◽  
Future Climate Change ◽  
Historical Period ◽  
Climate Change Scenarios ◽  
Rcp 8.5 ◽  
The Impact ◽  
Semi Arid

This research studies the effect of climate change on the hydrological behavior of two semi-arid basins. For this purpose, the Soil and Water Assessment Tool (SWAT) model was used with the simulation of two future climate change scenarios, one Representative Concentration Pathway moderate (RCP 4.5) and the other extreme (RCP 8.5). Three future periods were considered: close (2019–2040), medium (2041–2070), and distant (2071–2100). In addition, several climatic projections of the EURO-CORDEX model were selected, to which different bias correction methods were applied before incorporation into the SWAT model. The statistical indices for the monthly flow simulations showed a very good fit in the calibration and validation phases in the Upper Mula stream (NS = 0.79–0.87; PBIAS = −4.00–0.70%; RSR = 0.44–0.46) and the ephemeral Algeciras stream (NS = 0.78–0.82; PBIAS = −8.10–−8.20%; RSR = 0.4–0.42). Subsequently, the impact of climate change in both basins was evaluated by comparing future flows with those of the historical period. In the RCP 4.5 and RCP 8.5 scenarios, by the end of the 2071–2100 period, the flows of the Upper Mula stream and the ephemeral Algeciras stream will have decreased by between 46.3% and 52.4% and between 46.6% and 55.8%, respectively.

scholarly journals Evaluating the Impact of Climate Change on Water Productivity of Maize in the Semi-Arid Environment of Punjab, Pakistan

2020 ◽  
Vol 12 (9) ◽  
pp. 3905
Author(s):  
Muhammad Mohsin Waqas ◽  
Syed Hamid Hussain Shah ◽  
Usman Khalid Awan ◽  
Muhammad Waseem ◽  
Ishfaq Ahmad ◽  
...  
Keyword(s):  
Climate Change ◽  
Statistical Downscaling ◽  
Water Productivity ◽  
Maximum Temperature ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Farming Practices ◽  
Impact Of Climate Change ◽  
Swap Model ◽  
Semi Arid

Impact assessments on climate change are essential for the evaluation and management of irrigation water in farming practices in semi-arid environments. This study was conducted to evaluate climate change impacts on water productivity of maize in farming practices in the Lower Chenab Canal (LCC) system. Two fields of maize were selected and monitored to calibrate and validate the model. A water productivity analysis was performed using the Soil–Water–Atmosphere–Plant (SWAP) model. Baseline climate data (1980–2010) for the study site were acquired from the weather observatory of the Pakistan Meteorological Department (PMD). Future climate change data were acquired from the Hadley Climate model version 3 (HadCM3). Statistical downscaling was performed using the Statistical Downscaling Model (SDSM) for the A2 and B2 scenarios of HadCM3. The water productivity assessment was performed for the midcentury (2040–2069) scenario. The maximum increase in the average maximum temperature (Tmax) and minimum temperature (Tmin) was found in the month of July under the A2 and B2 scenarios. The scenarios show a projected increase of 2.8 °C for Tmax and 3.2 °C for Tmin under A2 as well as 2.7 °C for Tmax and 3.2 °C for Tmin under B2 for the midcentury. Similarly, climate change scenarios showed that temperature is projected to decrease, with the average minimum and maximum temperatures of 7.4 and 6.4 °C under the A2 scenario and 7.7 and 6.8 °C under the B2 scenario in the middle of the century, respectively. However, the highest precipitation will decrease by 56 mm under the A2 and B2 scenarios in the middle of the century for the month of September. The input and output data of the SWAP model were processed in R programming for the easy working of the model. The negative impact of climate change was found under the A2 and B2 scenarios during the midcentury. The maximum decreases in Potential Water Productivity (WPET) and Actual Water Productivity (WPAI) from the baseline period to the midcentury scenario of 1.1 to 0.85 kgm−3 and 0.7 to 0.56 kgm−3 were found under the B2 scenario. Evaluation of irrigation practices directs the water managers in making suitable water management decisions for the improvement of water productivity in the changing climate.

scholarly journals Future climate change scenario in hot semi-arid climate of Saurashtra, Gujarat by using statistical downscaling by LARS-WG model

MAUSAM ◽  
2021 ◽  
Vol 68 (4) ◽  
pp. 589-596
Author(s):  
JAYANTA SARKAR ◽  
J. R. CHICHOLIKAR
Keyword(s):  
Climate Change ◽  
Statistical Downscaling ◽  
Minimum Temperature ◽  
Daily Rainfall ◽  
Arid Climate ◽  
Weather Data ◽  
Maximum Temperature ◽  
Future Climate Change ◽  
Semi Arid ◽  
Far Future

Climate change is considered to be the greatest challenge faced by mankind in the twenty first century which can lead to severe impacts on different major sectors of the world such as water resources, agriculture, energy and tourism and are likely to alter trends and timing of precipitation and other weather drivers. Analyses and prediction of change in critical climatic variables like rainfall and temperature are, therefore, extremely important. Keeping this in mind, this study aims to verify the skills of LARS-WG (Long Ashton Research - Weather Generator), a statistical downscaling model, in simulating weather data in hot semi-arid climate of Saurashtra and analyze the future changes of temperature (maximum and minimum) and precipitation downscaled by LARS-WG based on IPCC SRA2 scenario generated by seven GCMs' projections for the near (2011-2030), medium (2046-2065) and far (2080-2099) future periods. Rajkot (22.3° N, 70.78° E) observatory of IMD, representing hot semi-arid climate of Saurashtra, Gujarat state was chosen for this purpose. Daily rainfall, maximum and minimum temperature data for the period of 1969-2013 have been utilized.             LARS-WG is found to show reasonably good skill in downscaling daily rainfall and excellent skill in downscaling maximum and minimum temperature. The downscaled rainfall indicated no coherent change trends among various GCMs’ projections of rainfall during near, medium and far future periods. Contrary to rainfall projections, simulations from the seven GCMs have coherent results for both the maximum and minimum temperatures. Based on the ensemble mean of seven GCMs, projected rainfall at Rajkot in monsoon season (JJAS) showed an increase in near future, i.e., 2011-2030, medium future (2046-2065) and far future (2080-2099) periods to the tune of 2, 11 and 14% respectively compared to the baseline value. Model studies indicating tropospheric warming leading to enhancement of atmospheric moisture content could be the reason for this increasing trend. Further, at the study site summer (MAM) maximum temperature is projected to increase by 0.5, 1.7 and 3.3°C during 2011-2030, 2046-2065 and 2080-2099 respectively and winter (DJF) minimum temperature is projected to increase by 0.8, 2.2 and 4.5 °C during 2011-2030, 2046-2065 and 2080-2099 respectively.  

scholarly journals Evaluating impacts of climate change on future water scarcity in an intensively managed semi-arid region using a coupled model of biophysical processes and water rights

2018 ◽  
Author(s):  
Bangshuai Han ◽  
Shawn G. Benner ◽  
Alejandro N. Flores
Keyword(s):  
Climate Change ◽  
Water Scarcity ◽  
Water Rights ◽  
Future Climate Change ◽  
Climate Projections ◽  
Modeling Framework ◽  
Stochastic Weather Generator ◽  
Biophysical Processes ◽  
Intensively Managed ◽  
Semi Arid

Abstract. In semiarid and arid regions with intensively managed water supplies, water scarcity is a product of interactions between complex biophysical processes and human activities. Evaluating water scarcity under climate change necessitates modeling how these coupled processes interact and redistribute waters in the system under alternative climate conditions. A particular challenge on the climate input lies in adequately capturing the plausible range of variability of future climate change along with central tendencies. This study generates a large ensemble of daily climate realizations by combining a stochastic weather generator, historical climate observations, and statistically downscaled General Circulation Model projections. Three climate change scenario groups, reflecting the historical, RCP4.5, and RCP8.5 conditions, are developed. A modeling framework is built using the Envision alternative futures modeling platform to 1) explicitly capture the spatiotemporally varying irrigation activities as constrained by local water rights; and 2) project water scarcity patterns under climate change. The study area is the Treasure Valley, an irrigation-intensive semi-arid human-environment system. Climate projections for the region show future increases in both precipitation and temperature. The projected increase in temperature has a significant influence on the increase of the allocated and unsatisfied irrigation amount. Projected changes in precipitation produce more modest responses. The scenarios identify spatially distinct areas more sensitive to water scarcity, highlight the importance of climate change as a driver of scarcity, and identify potential shortcomings of the current water management. The approach of creating climate ensembles overcomes deficiencies of using a few or mean values of individual GCM realizations.

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