Climate change impacts on the streamflow of Zarrineh River,Iran

Zarrineh River is located in the northwest of Iran, providing more than 40% of the total inflow into the Lake Urmia that is one of the largest saltwater lakes on the earth. Lake Urmia is a highly endangered ecosystem on the brink of desiccation. This paper studied the impacts of climate change on the streamflow of Zarrineh River. The streamflow was simulated and projected for the period 1992-2050 through seven CMIP5 (coupled model intercomparison project phase 5) data series (namely, BCC-CSM1-1, BNU-ESM, CSIRO-Mk3-6-0, GFDL-ESM2G, IPSL-CM5A-LR, MIROC-ESM and MIROC-ESM-CHEM) under RCP2.6 (RCP, representative concentration pathways) and RCP8.5. The model data series were statistically downscaled and bias corrected using an artificial neural network (ANN) technique and a Gamma based quantile mapping bias correction method. The best model (CSIRO-Mk3-6-0) was chosen by the TOPSIS (technique for order of preference by similarity to ideal solution) method from seven CMIP5 models based on statistical indices. For simulation of streamflow, a rainfall-runoff model, the hydrologiska byrans vattenavdelning (HBV-Light) model, was utilized. Results on hydro-climatological changes in Zarrineh River basin showed that the mean daily precipitation is expected to decrease from 0.94 and 0.96 mm in 2015 to 0.65 and 0.68 mm in 2050 under RCP2.6 and RCP8.5, respectively. In the case of temperature, the numbers change from 12.33°C and 12.37°C in 2015 to 14.28°C and 14.32°C in 2050. Corresponding to these climate scenarios, this study projected a decrease of the annual streamflow of Zarrineh River by half from 2015 to 2050 as the results of climatic changes will lead to a decrease in the annual streamflow of Zarrineh River from 59.49 m³/s in 2015 to 22.61 and 23.19 m³/s in 2050. The finding is of important meaning for water resources planning purposes, management programs and strategies of the Lake's endangered ecosystem.     

Monitoring and analysis of snow cover change in an alpine mountainous area in the Tianshan Mountains,China

Estimating the snow cover change in alpine mountainous areas(in which meteorological stations are typically lacking) is crucial for managing local water resources and constitutes the first step in evaluating the contribution of snowmelt to runoff and the water cycle. In this paper, taking the Jingou River Basin on the northern slope of the Tianshan Mountains, China as an example, we combined a new moderate-resolution imaging spectroradiometer(MODIS) snow cover extent product over China spanning ...     

气候变化情景下基于MaxEnt的麦瘟病在全球及中国的适生性分析

麦瘟病是小麦生产上的一种毁灭性真菌病害, 过去仅在南美洲流行?2016年该病害在亚洲的孟加拉国首次出现, 给世界尤其我国小麦生产带来重大潜在威胁?本研究基于麦瘟病当前在全球(包括孟加拉国)的分布数据和生物气候数据, 采用MaxEnt生态位模型和ArcGIS软件, 预测了当前气候条件下麦瘟病在全球特别是在我国的潜在适生区, 以及RCP2.6?RCP4.5?RCP6.0和RCP8.5 4种气候变化情景下2030s?2050s和2070s麦瘟病在中国潜在适生区分布范围, 进而以刀切法分析了影响其分布的主要气候因子, 并采用ROC对预测结果进行检验?结果表明, 在当前和未来不同气候情景下, 麦瘟病在中国的中风险和高风险区面积将呈增加趋势, 未来情景下与当前气候情景下相比, 中风险和高风险区的面积比例增加范围为0.08%~1.63%, 其中温度和湿度条件对麦瘟病的潜在分布区影响最大?此研究结果对于我国麦瘟病的检疫和防控提供了技术支撑?     

Modelling the impact of climate change on rangeland forage production using a generalized regression neural network: a case study in Isfahan Province,Central Iran

Monitoring of rangeland forage production at specified spatial and temporal scales is necessary for grazing management and also for implementation of rehabilitation projects in rangelands. This study focused on the capability of a generalized regression neural network(GRNN) model combined with GIS techniques to explore the impact of climate change on rangeland forage production. Specifically, a dataset of 115 monitored records of forage production were collected from 16 rangeland sites during the period 1998–2007 in Isfahan Province, Central Iran. Neural network models were designed using the monitored forage production values and available environmental data(including climate and topography data), and the performance of each network model was assessed using the mean estimation error(MEE), model efficiency factor(MEF), and correlation coefficient(r). The best neural network model was then selected and further applied to predict the forage production of rangelands in the future(in 2030 and 2080) under A1 B climate change scenario using Hadley Centre coupled model. The present and future forage production maps were also produced. Rangeland forage production exhibited strong correlations with environmental factors, such as slope, elevation, aspect and annual temperature. The present forage production in the study area varied from 25.6 to 574.1 kg/hm~2. Under climate change scenario, the annual temperature was predicted to increase and the annual precipitation was predicted to decrease. The prediction maps of forage production in the future indicated that the area with low level of forage production(0–100 kg/hm~2) will increase while the areas with moderate, moderately high and high levels of forage production(≥100 kg/hm~2) will decrease both in 2030 and in 2080, which may be attributable to the increasing annual temperature and decreasing annual precipitation. It was predicted that forage production of rangelands will decrease in the next couple of decades, especially in the western and southern parts of Isfahan Province. These changes are more pronounced in elevations between 2200 and 2900 m. Therefore, rangeland managers have to cope with these changes by holistic management approaches through mitigation and human adaptations.     

Influence of non-stationarity and auto-correlation of climatic records on spatio-temporal trend and seasonality analysis in a region with prevailing arid and semi-arid climate,Iran

Trend and stationarity analysis of climatic variables are essential for understanding climate variability and provide useful information about the vulnerability and future changes, especially in arid and semi-arid regions. In this study, various climatic zones of Iran were investigated to assess the relationship between the trend and the stationarity of the climatic variables. The Mann-Kendall test was considered to identify the trend, while the trend free pre-whitening approach was applied for eliminating serial correlation from the time-series. Meanwhile, time series stationarity was tested by Dickey-Fuller and Kwiatkowski-Phillips-Schmidt-Shin tests. The results indicated an increasing trend for mean air temperature series at most of the stations over various climatic zones, however, after eliminating the serial correlation factor, this increasing trend changes to an insignificant decreasing trend at a 95% confidence level. The seasonal mean air temperature trend suggested a significant increase in the majority of the stations. The mean air temperature increased more in northwest towards central parts of Iran that mostly located in arid and semi-arid climatic zones. Precipitation trend reveals an insignificant downward trend in most of the series over various climatic zones; furthermore, most of the stations follow a decreasing trend for seasonal precipitation. Furthermore, spatial patterns of trend and seasonality of precipitation and mean air temperature showed that the northwest parts of Iran and margin areas of the Caspian Sea are more vulnerable to the changing climate with respect to the precipitation shortfalls and warming. Stationarity analysis indicated that the stationarity of climatic series influences on their trend; so that, the series which have significant trends are not static. The findings of this investigation can help planners and policy-makers in various fields related to climatic issues, implementing better management and planning strategies to adapt to climate change and variability over Iran.     

Impacts of climate change and human activities on water resources in the Ebinur Lake Basin,Northwest China

Changing climatic conditions and extensive human activities have influenced the global water cycle. In recent years, significant changes in climate and land use have degraded the watershed ecosystem of the Ebinur Lake Basin in Xinjiang, Northwest China. In this paper, variations of runoff, temperature, precipitation, reference evapotranspiration, lake area, socio-economic water usage, groundwater level and water quality in the Ebinur Lake Basin from 1961 to 2015 were systematically analyzed by the Mann-Kendall test methods(M-K) mutation test, the cumulative levelling method, the climate-sensitive method and land-use change index. In addition, we evaluated the effects of human activities on land use change and water quality. The results reveal that there was a significant increase in temperature and precipitation from 1961 to 2015, despite a decrease in reference evapotranspiration. The Wenquan station was not significantly affected by human activities as it is situated at a higher altitude. Runoff at this station increased significantly with climate warming. In contrast, runoff at the Jinghe station was severely affected by numerous human activities. Runoff decreased without obvious fluctuations. The contributions of climate change to runoff variation at the Jinghe and Wenquan stations were 46.87% and 58.94%, respectively; and the contributions of human activities were 53.13% and 41.06%, respectively. Land-use patterns in the basin have changed significantly between 1990 and 2015: urban and rural constructed lands, saline-alkali land, bare land, cultivated land, and forest land have expanded, while areas under grassland, lake, ice/snow and river/channel have declined. Human activities have dramatically intensified land degradation and desertification. From 1961 to 2015, both the inflow into the Ebinur Lake and the area of the lake have declined year by year; groundwater levels have dropped significantly, and the water quality has deteriorated during the study period. In the oasis irrigation area below the runoff pass, human activities mainly influenced the utilization mode and quantity of water resources. Changes in the hydrology and quantity of water resources were driven primarily by the continuous expansion of cultivated land and oasis, as well as the growth of population and the construction of hydraulic engineering projects. After 2015, the effects of some ecological protection projects were observed. However, there was no obvious sign of ecological improvement in the basin, and some environmental problems continue to persist. On this basis, this study recommends that the expansion of oasis should be limited according to the carrying capacity of the local water bodies. Moreover, in order to ensure the ecological security of the basin, it is necessary to determine the optimal oasis area for sustainable development and improve the efficiency of water resources exploitation and utilization.     

Drought trend analysis in a semi-arid area of Iraq based on Normalized Difference Vegetation Index,Normalized Difference Water Index and Standardized Precipitation Index

Drought was a severe recurring phenomenon in Iraq over the past two decades due to climate change despite the fact that Iraq has been one of the most water-rich countries in the Middle East in the past.The Iraqi Kurdistan Region(IKR)is located in the north of Iraq,which has also suffered from extreme drought.In this study,the drought severity status in Sulaimaniyah Province,one of four provinces of the IKR,was investigated for the years from 1998 to 2017.Thus,Landsat time series dataset,including 40 images,were downloaded and used in this study.The Normalized Difference Vegetation Index(NDVI)and the Normalized Difference Water Index(NDWI)were utilized as spectral-based drought indices and the Standardized Precipitation Index(SPI)was employed as a meteorological-based drought index,to assess the drought severity and analyse the changes of vegetative cover and water bodies.The study area experienced precipitation deficiency and severe drought in 1999,2000,2008,2009,and 2012.Study findings also revealed a drop in the vegetative cover by 33.3%in the year 2000.Furthermore,the most significant shrinkage in water bodies was observed in the Lake Darbandikhan(LDK),which lost 40.5%of its total surface area in 2009.The statistical analyses revealed that precipitation was significantly positively correlated with the SPI and the surface area of the LDK(correlation coefficients of 0.92 and 0.72,respectively).The relationship between SPI and NDVI-based vegetation cover was positive but not significant.Low precipitation did not always correspond to vegetative drought;the delay of the effect of precipitation on NDVI was one year.