Pub Date : 2018-01-01DOI: 10.4172/2157-7617.1000470
A. Wondim, A. Genenew, G. Abaye, C. Demissie
The study was conducted in North Gonder Zone to identify the climate change variables and farmer’s indigenous climate change adaption strategies. The study took a sample of 130 farmers by using appropriate sampling techniques. Quantitative and qualitative data were collected from primary and secondary sources. Descriptive analysis was used to analyze farmer’s indigenous climate change adaption strategies quantitative. Besides, qualitative data were analyzed through narration. Different climate change variables, which affect livelihood of farmers, and variety of indigenous adaption strategies to minimize hazard due to climate change were identified. People living in the zone use indigenous adaption strategies based on Agro-ecology and farming system. The finding of research indicates that farmers adapt different strategies in response to different climatic change variables, and there are no best practices that can be used to tackle all climate change variables. Hence using a blend of the indigenous and scientific adaption strategies across the appropriate contexts is, therefore, of paramount importance.
{"title":"Indigenous Knowledge Adaption Strategies in Response to Climate Change: The Case of North Gondar, Ethiopia","authors":"A. Wondim, A. Genenew, G. Abaye, C. Demissie","doi":"10.4172/2157-7617.1000470","DOIUrl":"https://doi.org/10.4172/2157-7617.1000470","url":null,"abstract":"The study was conducted in North Gonder Zone to identify the climate change variables and farmer’s indigenous climate change adaption strategies. The study took a sample of 130 farmers by using appropriate sampling techniques. Quantitative and qualitative data were collected from primary and secondary sources. Descriptive analysis was used to analyze farmer’s indigenous climate change adaption strategies quantitative. Besides, qualitative data were analyzed through narration. Different climate change variables, which affect livelihood of farmers, and variety of indigenous adaption strategies to minimize hazard due to climate change were identified. People living in the zone use indigenous adaption strategies based on Agro-ecology and farming system. The finding of research indicates that farmers adapt different strategies in response to different climatic change variables, and there are no best practices that can be used to tackle all climate change variables. Hence using a blend of the indigenous and scientific adaption strategies across the appropriate contexts is, therefore, of paramount importance.","PeriodicalId":73713,"journal":{"name":"Journal of earth science & climatic change","volume":"9 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4172/2157-7617.1000470","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70384015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-01-01DOI: 10.4172/2157-7617.1000481
M. Gedefaw, A. Girma, Yan Denghua, W. Hao, G. Agitew
{"title":"Farmer's Perceptions and Adaptation Strategies to Climate Change, Its Determinants and Impacts in Ethiopia: Evidence from Qwara District","authors":"M. Gedefaw, A. Girma, Yan Denghua, W. Hao, G. Agitew","doi":"10.4172/2157-7617.1000481","DOIUrl":"https://doi.org/10.4172/2157-7617.1000481","url":null,"abstract":"","PeriodicalId":73713,"journal":{"name":"Journal of earth science & climatic change","volume":"9 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4172/2157-7617.1000481","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70384303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-01-01DOI: 10.4172/2157-7617.1000491
W. Legese, D. Koricha, K. Ture
{"title":"Perception of Farmers on Climate Change and their Adaptive Strategies over Bale Highlands, Southeastern Ethiopia","authors":"W. Legese, D. Koricha, K. Ture","doi":"10.4172/2157-7617.1000491","DOIUrl":"https://doi.org/10.4172/2157-7617.1000491","url":null,"abstract":"","PeriodicalId":73713,"journal":{"name":"Journal of earth science & climatic change","volume":"09 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4172/2157-7617.1000491","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70384727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-01-01DOI: 10.4172/2157-7617.1000492
Khalil Sa, A. Has
{"title":"Comparative and Evaluate of Empirical Models for Estimation Global Solar Radiation in Al-Baha, KSA","authors":"Khalil Sa, A. Has","doi":"10.4172/2157-7617.1000492","DOIUrl":"https://doi.org/10.4172/2157-7617.1000492","url":null,"abstract":"","PeriodicalId":73713,"journal":{"name":"Journal of earth science & climatic change","volume":"09 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4172/2157-7617.1000492","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70384804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-01-01DOI: 10.4172/2471-8556.1000503
R. Nedjai, A. Azaroual, K. Chlif, A. Bensaid, M. Al-Sayah, L. Ysbaa
{"title":"Impact of Ponds on Local Climate: A Remote Sensing and GIS Contribution Application to the Ponds of Brenne (France)","authors":"R. Nedjai, A. Azaroual, K. Chlif, A. Bensaid, M. Al-Sayah, L. Ysbaa","doi":"10.4172/2471-8556.1000503","DOIUrl":"https://doi.org/10.4172/2471-8556.1000503","url":null,"abstract":"","PeriodicalId":73713,"journal":{"name":"Journal of earth science & climatic change","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4172/2471-8556.1000503","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70314702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-01-01DOI: 10.4172/2157-7617.1000439
Solomon Abirdew, G. Mamo, M. Mengesha
In Ethiopia where crop production overly depends on rainfall and temperature, studying the variability of these climate variables at a local scale is essential to devise proper strategies that enhance adaptive capacity. In light of this, a study was conducted in Abshege Woreda, Gurage Zone to determine crop water requirement of maize, which is major food crop of the area. Ten years i.e., (2006-2015) Indibir station climatological records of (sunshine duration hr/day), maximum and minimum temperature (OC), humidity (%) and wind speed (km/day) at 2 meters height were used in FAO Penman Monteith method. Secondary data were used to collect important soil parameters required for determination of crop water requirement in the study area such as field capacity (FC), permanent wilting point (PWP), initial soil moisture depletion (as % TAM) and available water holding capacity (mm/meter) while data for maximum rain infiltration rates (mm/day) and maximum rooting depth (cm) were obtained from literature based on similar textural class of the soil in the study area. Lengths of total growing periods of the crop was determined from ten years climate data and planting date was 10th May acquired from OAWBA and farmers of the area. Crop coefficients (kc), rooting depth, depletion level and other agronomic parameters were obtained from FAO guidelines (No 56) for each growth stage. The analyzed data indicated that Crop water requirement was estimated using CROPWAT 8.0 for window. A maize variety with a growing period of 140 days to maturity would requires 423 mm depth of water, while 101 mm would be required as supplementary irrigation depth.
{"title":"Determination of Crop Water Requirements for Maize in Abshege Woreda, Gurage Zone, Ethiopia","authors":"Solomon Abirdew, G. Mamo, M. Mengesha","doi":"10.4172/2157-7617.1000439","DOIUrl":"https://doi.org/10.4172/2157-7617.1000439","url":null,"abstract":"In Ethiopia where crop production overly depends on rainfall and temperature, studying the variability of these climate variables at a local scale is essential to devise proper strategies that enhance adaptive capacity. In light of this, a study was conducted in Abshege Woreda, Gurage Zone to determine crop water requirement of maize, which is major food crop of the area. Ten years i.e., (2006-2015) Indibir station climatological records of (sunshine duration hr/day), maximum and minimum temperature (OC), humidity (%) and wind speed (km/day) at 2 meters height were used in FAO Penman Monteith method. Secondary data were used to collect important soil parameters required for determination of crop water requirement in the study area such as field capacity (FC), permanent wilting point (PWP), initial soil moisture depletion (as % TAM) and available water holding capacity (mm/meter) while data for maximum rain infiltration rates (mm/day) and maximum rooting depth (cm) were obtained from literature based on similar textural class of the soil in the study area. Lengths of total growing periods of the crop was determined from ten years climate data and planting date was 10th May acquired from OAWBA and farmers of the area. Crop coefficients (kc), rooting depth, depletion level and other agronomic parameters were obtained from FAO guidelines (No 56) for each growth stage. The analyzed data indicated that Crop water requirement was estimated using CROPWAT 8.0 for window. A maize variety with a growing period of 140 days to maturity would requires 423 mm depth of water, while 101 mm would be required as supplementary irrigation depth.","PeriodicalId":73713,"journal":{"name":"Journal of earth science & climatic change","volume":"9 1","pages":"1-3"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4172/2157-7617.1000439","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70382484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-01-01DOI: 10.4172/2157-7617.1000454
Ming Cai, Tan Wenbing, Lei Wang, B. Xi, Lie-yu Zhang, Huilian Liu
China’s effort to mitigate soil organic carbon (SOC) loss caused by rapid land use changes over the last two decades faces great challenges. Generally, land use change projects in China have been performed without considering the mechanisms involved in the link between land use change and SOC dynamic. Such situation will likely increase the climatic and environmental risks brought by land use changes. In this paper, we illustrate why most studies over the past several decades in China have been unable to provide significant guiding information for what kind of land use can be adopted to benefit the climate and ecological environments. In addition, we recommend the combination of soil organic matter fractionation with radiocarbon assessment, which researchers are working on to better predict the dynamic trends of SOC under land use change and present several proposals in regard to how to sequester more carbon in soils after land use change.
{"title":"What Should we do in the Context of Land Use Change Occurring Frequently in China","authors":"Ming Cai, Tan Wenbing, Lei Wang, B. Xi, Lie-yu Zhang, Huilian Liu","doi":"10.4172/2157-7617.1000454","DOIUrl":"https://doi.org/10.4172/2157-7617.1000454","url":null,"abstract":"China’s effort to mitigate soil organic carbon (SOC) loss caused by rapid land use changes over the last two decades faces great challenges. Generally, land use change projects in China have been performed without considering the mechanisms involved in the link between land use change and SOC dynamic. Such situation will likely increase the climatic and environmental risks brought by land use changes. In this paper, we illustrate why most studies over the past several decades in China have been unable to provide significant guiding information for what kind of land use can be adopted to benefit the climate and ecological environments. In addition, we recommend the combination of soil organic matter fractionation with radiocarbon assessment, which researchers are working on to better predict the dynamic trends of SOC under land use change and present several proposals in regard to how to sequester more carbon in soils after land use change.","PeriodicalId":73713,"journal":{"name":"Journal of earth science & climatic change","volume":"9 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4172/2157-7617.1000454","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70383762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-01-01DOI: 10.4172/2157-7617.1000474
T. Abrahama, A. Woldemicheala, A. Muluneha, B. Abateb
This study predicts future runoff conditions under changing climate using multi model outputs from Coupled Model Intercomparison Project Phase 5 (CMIP5) over Lake Ziway Catchment. The River system is located in the Central Rift Valley of Ethiopia which serves for wide range of socio-economic activity, but recently different water use sectors are increasing their pressure on the water balance of the catchment. Bias corrected precipitation, maximum and minimum temperature data from three climate models HadGEM2-ES, CSIRO-MK-3-6-0 and CCSM4 under representative concentration pathways RCP 8.5 and RCP 4.5 were used as input for the hydrologic model. A calibrated and validated HBV model is used to simulate the future inflow from Katar River and Meki River towards Lake Ziway. The result revealed that the maximum and minimum temperature increased under RCP 8.5 and RCP 4.5 scenarios. However, precipitation showed a decreasing trend. The percentage change in monthly average precipitation showed extremes for HadGEM2-ES model which range between -51.19% during January 2050s and +23.15% during February 2080s under RCP 8.5. The model output showed an annual decrement in runoff depth on Katar River up to 19.45% during RCP 8.5 on CSIRO MK-3-6-0 model and maximum reduction was recorded for RCP 4.5 at 17.49% for CCSM4 model. Meki River has shown maximum annual reduction of 20.28% during 2080s on RCP 8.5 for HadGEM2-ES model and seasonally during Bulg maximum increment was recorded for the same model which ranges up to 10.23% on 2050s for RCP 4.5. However seasonal maximum reduction is obtained from Bulg season by 40.27% on HadGEM2-ES model during 2050s. From the study, a reduction in rainfall has brought larger effects on runoff reduction than evapotranspiration components. Due to future reduction of River flow on the region optimal allocations for water use purposes at all levels of water resource development projects are crucial for future water planning and management.
{"title":"Hydrological Responses of Climate Change on Lake Ziway Catchment, Central Rift Valley of Ethiopia","authors":"T. Abrahama, A. Woldemicheala, A. Muluneha, B. Abateb","doi":"10.4172/2157-7617.1000474","DOIUrl":"https://doi.org/10.4172/2157-7617.1000474","url":null,"abstract":"This study predicts future runoff conditions under changing climate using multi model outputs from Coupled Model Intercomparison Project Phase 5 (CMIP5) over Lake Ziway Catchment. The River system is located in the Central Rift Valley of Ethiopia which serves for wide range of socio-economic activity, but recently different water use sectors are increasing their pressure on the water balance of the catchment. Bias corrected precipitation, maximum and minimum temperature data from three climate models HadGEM2-ES, CSIRO-MK-3-6-0 and CCSM4 under representative concentration pathways RCP 8.5 and RCP 4.5 were used as input for the hydrologic model. A calibrated and validated HBV model is used to simulate the future inflow from Katar River and Meki River towards Lake Ziway. The result revealed that the maximum and minimum temperature increased under RCP 8.5 and RCP 4.5 scenarios. However, precipitation showed a decreasing trend. The percentage change in monthly average precipitation showed extremes for HadGEM2-ES model which range between -51.19% during January 2050s and +23.15% during February 2080s under RCP 8.5. The model output showed an annual decrement in runoff depth on Katar River up to 19.45% during RCP 8.5 on CSIRO MK-3-6-0 model and maximum reduction was recorded for RCP 4.5 at 17.49% for CCSM4 model. Meki River has shown maximum annual reduction of 20.28% during 2080s on RCP 8.5 for HadGEM2-ES model and seasonally during Bulg maximum increment was recorded for the same model which ranges up to 10.23% on 2050s for RCP 4.5. However seasonal maximum reduction is obtained from Bulg season by 40.27% on HadGEM2-ES model during 2050s. From the study, a reduction in rainfall has brought larger effects on runoff reduction than evapotranspiration components. Due to future reduction of River flow on the region optimal allocations for water use purposes at all levels of water resource development projects are crucial for future water planning and management.","PeriodicalId":73713,"journal":{"name":"Journal of earth science & climatic change","volume":"10 1","pages":"1-16"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4172/2157-7617.1000474","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70384117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-01-01DOI: 10.4172/2157-7617.1000475
Rahman Hashmi Mzu, Shamseldin Ay, Melville Bw
Statistical downscaling has become an important part in most of the watershed scale climate change investigations. It is usually performed using multiple regression-based models. Basic working principle of such models is to develop a suitable relationship between the large scale (predictors) and the local climatic parameters called predictands. The development of such relationships using linear regression becomes very challenging when the local parameter to be downscaled is complex in nature such as precipitation. For this reason, use of nonlinear data driven techniques including Artificial Neural Networks (ANNs) is becoming more and more popular. Therefore, an attempt has been made in the study presented here to introduce a new Multi-Layer Perceptron (MLP) ANN-based scheme to develop a robust predictors-predictand relationship to be used as a downscaling model at daily time scale. The efficiency of this model has been compared with a popularly used model called Statistical Down Scaling Model (SDSM), for daily precipitation at the Clutha watershed in New Zealand. The results show that the model developed based on ANN scheme exhibits better performance than the SDSM. Hence, it is concluded that the use of artificial intelligence techniques such as ANN can greatly help in developing more efficient predictor-predictand models for even for precipitation being the toughest climate variable to model
{"title":"Comparison of MLP-ANN Scheme and SDSM as Tools for Providing Downscaled Precipitation for Impact Studies at Daily Time Scale","authors":"Rahman Hashmi Mzu, Shamseldin Ay, Melville Bw","doi":"10.4172/2157-7617.1000475","DOIUrl":"https://doi.org/10.4172/2157-7617.1000475","url":null,"abstract":"Statistical downscaling has become an important part in most of the watershed scale climate change investigations. It is usually performed using multiple regression-based models. Basic working principle of such models is to develop a suitable relationship between the large scale (predictors) and the local climatic parameters called predictands. The development of such relationships using linear regression becomes very challenging when the local parameter to be downscaled is complex in nature such as precipitation. For this reason, use of nonlinear data driven techniques including Artificial Neural Networks (ANNs) is becoming more and more popular. Therefore, an attempt has been made in the study presented here to introduce a new Multi-Layer Perceptron (MLP) ANN-based scheme to develop a robust predictors-predictand relationship to be used as a downscaling model at daily time scale. The efficiency of this model has been compared with a popularly used model called Statistical Down Scaling Model (SDSM), for daily precipitation at the Clutha watershed in New Zealand. The results show that the model developed based on ANN scheme exhibits better performance than the SDSM. Hence, it is concluded that the use of artificial intelligence techniques such as ANN can greatly help in developing more efficient predictor-predictand models for even for precipitation being the toughest climate variable to model","PeriodicalId":73713,"journal":{"name":"Journal of earth science & climatic change","volume":"9 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4172/2157-7617.1000475","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70384125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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