California is severely exposed to drought and damage due to the climate change and drought belt, which has a major impact on agriculture. So, after the drought crisis, there are various reactions from farmers. The extent of the damage caused by the socioeconomic, environment and the extent of the resistance of farmers to this crisis is manifested in a variety of ways. Recognizing the population’s resilience and the involved human groups is a tool for preventing a catastrophe-based increase in life-threatening areas in high-risk areas. Sometimes the inability to manage this phenomenon (especially under the climate change) leads to farmers’ desertification and agricultural land release, which itself indicates a low level of resilience and resilience to the crisis. The recent drought under the climate change condition in California and the severity of the damage sustained by farmers continue to be vulnerable. The present study seeks to prioritize and prioritize resilience of farmers to the crisis under the climate change. This study simulated drought condition with using PDSI value for current and future time period. In order to calculate PDSI values, the climatic parameters extracted from CMIP5 models and downscaled under the scenario of RCP 8.5. Also in order to understand the resilience of the agriculture activities under the climate change, this study was performed using statistical tests and data from the questionnaire completed in the statistical population of 320 farmers in the Tulare region in California. The findings of the research by t test showed that the average level of effective factors in increasing the resilience of farmers in the region is low. This is particularly significant in relation to the factors affecting government policies and support. So that only the mean of five variables is higher than the numerical desirability of the test and the other 15 variables do not have a suitable status for increasing the resilience of the farmers. Also, the results of the Vikor model showed that most of the impact on their resilience to drought and climate change was the development of agricultural insurance, the second important impact belongs to drought monitoring system, climate change and damage assessment, and variable of attention to knowledge is in third place of the important factor.
Climate change and global warming are the biggest challenges in the current century. Methane gas is one of the most important greenhouse gases which can contribute to creating warming weather (about 19%). In this research, satellite data from GOSAT and MODIS and also climatic data of precipitation, temperature and humidity are used to analyze monthly and seasonal methane changes in 2012 to 2018 in North America. The results show that the methane gas has increased during this period and it increases from 1789 to 1824 ppb. The gas has monthly fluctuation and in October and September has the maximum concentration and in March and April has the minimum value. The relationship between the methane gas and temperature and LST is positive, and the relationship between the methane gas and NDVI, precipitation and humidity is negative. This verifies that the increase in methane concentration has significant relationship with low vegetation cover and high temperature. Therefore, conservation of vegetation cover can help to reduce the methane concentration.
Climate change is an important environmental issue, as progression of melting glaciers and snow cover is sensitive to climate alteration. The aim of this research was to model climate alterations forecasts, and to assess potential changes in snow cover and snow-melt runoff under the different climate change scenarios in the case study of the Zayandeh-rud River Basin. Three cluster models for climate change (NorESM1-M, IPSL-CM5A-LR and CSIRO-MK3.6.0) were applied under RCP 8.5, 4.5 and 2.6 scenarios, to examine climate influences on precipitation and temperature in the basin. Temperature and precipitation were determined for all three scenarios for four periods of 2021-2030, 2031-2040, 2041-2050 and 2051-2060. MODIS (MOD10A1) was also applied to examine snow cover using temperature and precipitation data. The relationship between snow-covered area, temperature and precipitation was used to forecast future snow cover. For modeling future snow melt runoff, a hydrologic model of SRM was used including input data of precipitation, temperature and snow cover. The results indicated that all three RCP scenarios lead to an increase in temperature, and reduction in precipitation and snow cover. Investigation in snowmelt runoff throughout the observation period (November 1970 to May 2006) showed that most of annual runoff is derived from snow melting. Maximum snowmelt runoff is generated in winter. The share of melt water in the autumn and spring runoff is estimated at 35 and 53%, respectively. The results of this study can assist water manager in making better decisions for future water supply.
Isfahan industrial province with its numerous industrial estates in its area and consequently the amount of wastewater produced by these settlements is very difficult to deal with. Therefore, the need for proper wastewater treatment and efficient management of industrial waste water from the industrial estates of this province should be seriously addressed and followed up by the authorities. The purpose of this study is the feasibility of reuse of wastewater from industrial settlements for agricultural and irrigation purposes. The present study is a descriptive cross-sectional study. In this study, the average values obtained from the sampling and the results of the experiments on waste water from the industrial waste water treatment plant in Isfahan, 2017, have been used. Average values of BOD5, COD, TSS and so on were compared with the standards set by the Environmental Protection Agency and analyzed in Excel software. According to the results, the average values of COD, BOD5, TSS, SO4, pH and catalyst quality parameters were determined from wastewater effluents of 315,162,93,164 (mg / L), 8.3 and 32.5 (NTU) respectively. The results of the study show that the average values of the quality parameters examined from the effluent of the treatment plant other than BOD5 and COD are within the standard range and the limit for agricultural and irrigation purposes, which may lead to undesirable environmental performance of these two parameters.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.