Drought is one of the most significant environmental disasters,especially in arid and semi-arid regions.Drought indices as a tool for management practices seeking to deal with the drought phenomenon are widely used ar...Drought is one of the most significant environmental disasters,especially in arid and semi-arid regions.Drought indices as a tool for management practices seeking to deal with the drought phenomenon are widely used around the world.One of these indicators is the Palmer drought severity index(PDSI),which is used in many parts of the world to assess the drought situation and continuation.In this study,the drought state of Fars Province in Iran was evaluated by using the PDSI over 1995-2014 according to meteorological data from six weather stations in the province.A statistical downscaling model(SDSM)was used to apply the output results of the general circulation model in Fars Province.To implement data processing and prediction of climate data,a statistical period 1995-2014 was considered as the monitoring period,and a statistical period 2019-2048 was for the prediction period.The results revealed that there is a good agreement between the simulated precipitation(R2>0.63;R2,determination coefficient;MAE<0.52;MAE,mean absolute error;RMSE<0.56;RMSE,Root Mean Squared Error)and temperature(R2>0.95,MAE<1.74,and RMSE<1.78)with the observed data from the stations.The results of the drought monitoring model presented that dry periods would increase over the next three decades as compared to the historical data.The studies showed the highest drought in the meteorological stations Abadeh and Lar during the prediction period under two future scenarios representative concentration pathways(RCP4.5 and RCP8.5).According to the results of the validation periods and efficiency criteria,we suggest that the SDSM is a proper tool for predicting drought in arid and semi-arid regions.展开更多
In order to explore the climate change in the Dawen River basin,based on the data of six weather stations in the Dawen River basin from 1966 to 2017,Mann-Kendall test and wavelet analysis were used to study the temper...In order to explore the climate change in the Dawen River basin,based on the data of six weather stations in the Dawen River basin from 1966 to 2017,Mann-Kendall test and wavelet analysis were used to study the temperature and precipitation trends,mutations and cycles in the region.In addition,based on the three scenarios of RCP2.6,RCP4.5,and RCP8.5 under the CanESM2 model,SDSM was used to compare and analyze the future climate change of the Dawen River basin.The results revealed that:the annual mean temperature of the Dawen River basin had increased significantly since 1966(p<0.01);in different scenarios,the spatial distribution of the projected maximum temperature,minimum temperature and precipitation will hardly change compared with that in history;the temperature and precipitation in the Dawen River basin will generally increase in the future.The rising trend of maximum and minimum temperature under the three scenarios is in the EP<MP<LP,and June and November was the months with the highest increase;the future precipitation will have the highest increase in July and August.Under the RCP4.5 and RCP8.5 scenarios,the annual maximum and minimum temperatures in the future will increase with the increase in time scale.展开更多
The paper describes the application of SDSM （statistical downscaling model） and ANNs （artificial neural networks） models for prediction of the hydrological trend due to the climate-change. The SDSM has been calibr...The paper describes the application of SDSM （statistical downscaling model） and ANNs （artificial neural networks） models for prediction of the hydrological trend due to the climate-change. The SDSM has been calibrated and generated for the possible future scenarios of meteorological variables, which are temperature and rainfall by using GCMs （global climate models）. The GCM used is SRES A2. The downscaled meteorological variables corresponding to SDSM were then used as input to the ANNs model calibrated with observed station data to simulate the corresponding future streamflow changes in the sub-catchment of Kurau River. This study has discovered the hydrological trend over the catchment. The projected monthly streamflow has shown a decreasing trend due to the increase in the, mean of temperature for overall months, except the month of August and November.展开更多
在第2代加拿大地球系统模型(the second generation Canadian earth system model,CanESM2)中的3种典型浓度路径(representative concentration pathways,RCPs)情景(RCP2.6、RCP4.5和RCP8.5)下,基于统计降尺度模型(statistical down sca...在第2代加拿大地球系统模型(the second generation Canadian earth system model,CanESM2)中的3种典型浓度路径(representative concentration pathways,RCPs)情景(RCP2.6、RCP4.5和RCP8.5)下,基于统计降尺度模型(statistical down scaling model,SDSM)研究兰江流域未来年份温度和降水量的变化趋势。结果表明:1)SDSM在兰江流域具有较好的适用性,各站点最高温度、最低温度、降水量的解释方差分别为70.62%~79.74%、69.61%~78.76%、28.56%~41.45%;2)3种RCPs情景下温度均呈上升趋势,且上升幅度随辐射强迫度上升而同步增大,至21世纪末,RCP2.6、RCP4.5、RCP8.5情景下的最高温度分别较基准期上升0.06℃、1.22℃、2.76℃,最低温度分别较基准期上升0.35℃、1.15℃、3.01℃;3)RCP2.6情景下的降水量总体呈下降趋势,至2080—2100年下降0.98%,RCP4.5情景下的降水量呈先上升后下降趋势,至2050—2079年达到峰值,较基准期上升12.03%,RCP8.5情景下的降水量呈先下降后快速上升趋势,至2080—2100年上升38.08%。研究结果可为兰江流域内水资源管理、生态文明建设及社会经济可持续发展提供依据和理论支持。展开更多
雅砻江流域是中国第三大水电基地,准确模拟雅砻江流域未来气候变化情况可以为流域内合理高效开发水资源提供科学依据。为了评估该流域不同情景下未来气候变化情况,使用1970-2005年雅砻江流域13个气象站数据,采用CMIP5(Coupled Model Int...雅砻江流域是中国第三大水电基地,准确模拟雅砻江流域未来气候变化情况可以为流域内合理高效开发水资源提供科学依据。为了评估该流域不同情景下未来气候变化情况,使用1970-2005年雅砻江流域13个气象站数据,采用CMIP5(Coupled Model Intercomparison Project phase 5)中MIROC气候模式数据,经过SDSM(Statistical DownScaling Model)模型将低分辨率的栅格数据降尺度至站点数据,同时采用系数订正法、频率匹配法耦合订正日降水量的偏差和频率分布,最后使用订正后的数据分析雅砻江流域未来气候变化情况。结果表明:(1)订正后的日尺度降水的确定性系数从0.12提高到0.2;(2)雅砻江流域未来气温和降水总体均呈上升趋势;(3)在3种不同的代表性浓度路径(RCP2.6、RCP4.5、RCP8.5)这3种排放情景下雅砻江流域未来最高气温分别增加0.71、1.16、1.35℃,且9,11,12月增加较为明显;未来最低气温分别增加0.72、0.83、1.08℃,且8,9,12月增加较为明显;(4)在2022-2100年未来时期3种排放情景下,雅砻江流域未来降水均呈增加趋势,日均降水分别增加117.6%、131.7%、124.2%;春季RCP4.5降水增幅最大,夏季辐射强迫越强,雅砻江流域降水增加越明显。雅砻江流域未来气温升高、降水增多将会提高极端气候事件出现的频率。未来水资源分布不均程度将进一步加剧,气候变暖带来的干旱,洪水等自然灾害将会对水电站的建设和运行产生不利影响,分析结果可以为雅砻江水电基地水资源开发提供科学依据。展开更多
文摘Drought is one of the most significant environmental disasters,especially in arid and semi-arid regions.Drought indices as a tool for management practices seeking to deal with the drought phenomenon are widely used around the world.One of these indicators is the Palmer drought severity index(PDSI),which is used in many parts of the world to assess the drought situation and continuation.In this study,the drought state of Fars Province in Iran was evaluated by using the PDSI over 1995-2014 according to meteorological data from six weather stations in the province.A statistical downscaling model(SDSM)was used to apply the output results of the general circulation model in Fars Province.To implement data processing and prediction of climate data,a statistical period 1995-2014 was considered as the monitoring period,and a statistical period 2019-2048 was for the prediction period.The results revealed that there is a good agreement between the simulated precipitation(R2>0.63;R2,determination coefficient;MAE<0.52;MAE,mean absolute error;RMSE<0.56;RMSE,Root Mean Squared Error)and temperature(R2>0.95,MAE<1.74,and RMSE<1.78)with the observed data from the stations.The results of the drought monitoring model presented that dry periods would increase over the next three decades as compared to the historical data.The studies showed the highest drought in the meteorological stations Abadeh and Lar during the prediction period under two future scenarios representative concentration pathways(RCP4.5 and RCP8.5).According to the results of the validation periods and efficiency criteria,we suggest that the SDSM is a proper tool for predicting drought in arid and semi-arid regions.
基金National Natural Science Foundation of China(41471160)。
文摘In order to explore the climate change in the Dawen River basin,based on the data of six weather stations in the Dawen River basin from 1966 to 2017,Mann-Kendall test and wavelet analysis were used to study the temperature and precipitation trends,mutations and cycles in the region.In addition,based on the three scenarios of RCP2.6,RCP4.5,and RCP8.5 under the CanESM2 model,SDSM was used to compare and analyze the future climate change of the Dawen River basin.The results revealed that:the annual mean temperature of the Dawen River basin had increased significantly since 1966(p<0.01);in different scenarios,the spatial distribution of the projected maximum temperature,minimum temperature and precipitation will hardly change compared with that in history;the temperature and precipitation in the Dawen River basin will generally increase in the future.The rising trend of maximum and minimum temperature under the three scenarios is in the EP<MP<LP,and June and November was the months with the highest increase;the future precipitation will have the highest increase in July and August.Under the RCP4.5 and RCP8.5 scenarios,the annual maximum and minimum temperatures in the future will increase with the increase in time scale.
文摘The paper describes the application of SDSM （statistical downscaling model） and ANNs （artificial neural networks） models for prediction of the hydrological trend due to the climate-change. The SDSM has been calibrated and generated for the possible future scenarios of meteorological variables, which are temperature and rainfall by using GCMs （global climate models）. The GCM used is SRES A2. The downscaled meteorological variables corresponding to SDSM were then used as input to the ANNs model calibrated with observed station data to simulate the corresponding future streamflow changes in the sub-catchment of Kurau River. This study has discovered the hydrological trend over the catchment. The projected monthly streamflow has shown a decreasing trend due to the increase in the, mean of temperature for overall months, except the month of August and November.
文摘在第2代加拿大地球系统模型(the second generation Canadian earth system model,CanESM2)中的3种典型浓度路径(representative concentration pathways,RCPs)情景(RCP2.6、RCP4.5和RCP8.5)下,基于统计降尺度模型(statistical down scaling model,SDSM)研究兰江流域未来年份温度和降水量的变化趋势。结果表明:1)SDSM在兰江流域具有较好的适用性,各站点最高温度、最低温度、降水量的解释方差分别为70.62%~79.74%、69.61%~78.76%、28.56%~41.45%;2)3种RCPs情景下温度均呈上升趋势,且上升幅度随辐射强迫度上升而同步增大,至21世纪末,RCP2.6、RCP4.5、RCP8.5情景下的最高温度分别较基准期上升0.06℃、1.22℃、2.76℃,最低温度分别较基准期上升0.35℃、1.15℃、3.01℃;3)RCP2.6情景下的降水量总体呈下降趋势,至2080—2100年下降0.98%,RCP4.5情景下的降水量呈先上升后下降趋势,至2050—2079年达到峰值,较基准期上升12.03%,RCP8.5情景下的降水量呈先下降后快速上升趋势,至2080—2100年上升38.08%。研究结果可为兰江流域内水资源管理、生态文明建设及社会经济可持续发展提供依据和理论支持。
