Agriculture needs to produce more food to feed the growing population in the 21st century.It makes the reference crop water requirement(WREQ)a major challenge especially in regions with limited water and high water de...Agriculture needs to produce more food to feed the growing population in the 21st century.It makes the reference crop water requirement(WREQ)a major challenge especially in regions with limited water and high water demand.Iran,with large climatic variability,is experiencing a serious water crisis due to limited water resources and inefficient agriculture.In order to overcome the issue of uneven distribution of weather stations,gridded Climatic Research Unit(CRU)data was applied to analyze the changes in potential evapotranspiration(PET),effective precipitation(EFFPRE)and WREQ.Validation of data using in situ observation showed an acceptable performance of CRU in Iran.Changes in PET,EFFPRE and WREQ were analyzed in two 30-a periods 1957-1986 and 1987-2016.Comparing two periods showed an increase in PET and WREQ in regions extended from the southwest to northeast and a decrease in the southeast,more significant in summer and spring.However,EFFPRE decreased in the southeast,northeast,and northwest,especially in winter and spring.Analysis of annual trends revealed an upward trend in PET(14.32 mm/decade)and WREQ(25.50 mm/decade),but a downward trend in EFFPRE(-11.8 mm/decade)over the second period.Changes in PET,EFFPRE and WREQ in winter have the impact on the annual trend.Among climate variables,WREQ showed a significant correlation(r=0.59)with minimum temperature.The increase in WREQ and decrease in EFFPRE would exacerbate the agricultural water crisis in Iran.With all changes in PET and WREQ,immediate actions are needed to address the challenges in agriculture and adapt to the changing climate.展开更多
In the past few decades,meteorological datasets from remote sensing techniques in agricultural and water resources management have been used by various researchers and managers.Based on the literature,meteorological d...In the past few decades,meteorological datasets from remote sensing techniques in agricultural and water resources management have been used by various researchers and managers.Based on the literature,meteorological datasets are not more accurate than synoptic stations,but their various advantages,such as spatial coverage,time coverage,accessibility,and free use,have made these techniques superior,and sometimes we can use them instead of synoptic stations.In this study,we used four meteorological datasets,including Climatic Research Unit gridded Time Series(CRU TS),Global Precipitation Climatology Centre(GPCC),Agricultural National Aeronautics and Space Administration Modern-Era Retrospective Analysis for Research and Applications(AgMERRA),Agricultural Climate Forecast System Reanalysis(AgCFSR),to estimate climate variables,i.e.,precipitation,maximum temperature,and minimum temperature,and crop variables,i.e.,reference evapotranspiration,irrigation requirement,biomass,and yield of maize,in Qazvin Province of Iran during 1980-2009.At first,data were gathered from the four meteorological datasets and synoptic station in this province,and climate variables were calculated.Then,after using the AquaCrop model to calculate the crop variables,we compared the results of the synoptic station and meteorological datasets.All the four meteorological datasets showed strong performance for estimating climate variables.AgMERRA and AgCFSR had more accurate estimations for precipitation and maximum temperature.However,their normalized root mean square error was inferior to CRU for minimum temperature.Furthermore,they were all very efficient for estimating the biomass and yield of maize in this province.For reference evapotranspiration and irrigation requirement CRU TS and GPCC were the most efficient rather than AgMERRA and AgCFSR.But for the estimation of biomass and yield,all the four meteorological datasets were reliable.To sum up,GPCC and AgCFSR were the two best datasets in this study.This study suggests the use of meteorological datasets in water resource management and agricultural management to monitor past changes and estimate recent trends.展开更多
文摘Agriculture needs to produce more food to feed the growing population in the 21st century.It makes the reference crop water requirement(WREQ)a major challenge especially in regions with limited water and high water demand.Iran,with large climatic variability,is experiencing a serious water crisis due to limited water resources and inefficient agriculture.In order to overcome the issue of uneven distribution of weather stations,gridded Climatic Research Unit(CRU)data was applied to analyze the changes in potential evapotranspiration(PET),effective precipitation(EFFPRE)and WREQ.Validation of data using in situ observation showed an acceptable performance of CRU in Iran.Changes in PET,EFFPRE and WREQ were analyzed in two 30-a periods 1957-1986 and 1987-2016.Comparing two periods showed an increase in PET and WREQ in regions extended from the southwest to northeast and a decrease in the southeast,more significant in summer and spring.However,EFFPRE decreased in the southeast,northeast,and northwest,especially in winter and spring.Analysis of annual trends revealed an upward trend in PET(14.32 mm/decade)and WREQ(25.50 mm/decade),but a downward trend in EFFPRE(-11.8 mm/decade)over the second period.Changes in PET,EFFPRE and WREQ in winter have the impact on the annual trend.Among climate variables,WREQ showed a significant correlation(r=0.59)with minimum temperature.The increase in WREQ and decrease in EFFPRE would exacerbate the agricultural water crisis in Iran.With all changes in PET and WREQ,immediate actions are needed to address the challenges in agriculture and adapt to the changing climate.
文摘In the past few decades,meteorological datasets from remote sensing techniques in agricultural and water resources management have been used by various researchers and managers.Based on the literature,meteorological datasets are not more accurate than synoptic stations,but their various advantages,such as spatial coverage,time coverage,accessibility,and free use,have made these techniques superior,and sometimes we can use them instead of synoptic stations.In this study,we used four meteorological datasets,including Climatic Research Unit gridded Time Series(CRU TS),Global Precipitation Climatology Centre(GPCC),Agricultural National Aeronautics and Space Administration Modern-Era Retrospective Analysis for Research and Applications(AgMERRA),Agricultural Climate Forecast System Reanalysis(AgCFSR),to estimate climate variables,i.e.,precipitation,maximum temperature,and minimum temperature,and crop variables,i.e.,reference evapotranspiration,irrigation requirement,biomass,and yield of maize,in Qazvin Province of Iran during 1980-2009.At first,data were gathered from the four meteorological datasets and synoptic station in this province,and climate variables were calculated.Then,after using the AquaCrop model to calculate the crop variables,we compared the results of the synoptic station and meteorological datasets.All the four meteorological datasets showed strong performance for estimating climate variables.AgMERRA and AgCFSR had more accurate estimations for precipitation and maximum temperature.However,their normalized root mean square error was inferior to CRU for minimum temperature.Furthermore,they were all very efficient for estimating the biomass and yield of maize in this province.For reference evapotranspiration and irrigation requirement CRU TS and GPCC were the most efficient rather than AgMERRA and AgCFSR.But for the estimation of biomass and yield,all the four meteorological datasets were reliable.To sum up,GPCC and AgCFSR were the two best datasets in this study.This study suggests the use of meteorological datasets in water resource management and agricultural management to monitor past changes and estimate recent trends.
