Rainfall and evapotranspiration are two vital elements for food production under rainfed agriculture. This study aims at investigating the combined changes in these variables in the form of aridly index in the souther...Rainfall and evapotranspiration are two vital elements for food production under rainfed agriculture. This study aims at investigating the combined changes in these variables in the form of aridly index in the southern Senegal. The temporal trends in annual and monthly (from May to October) aridity index, rainfall and evapotranspiration are examined and adaptation strategies to the vulnerability of rainfed rice cultivation to the changes are developed. The results show a significant decreasing trend in annual rainfall at all study locations for the period 1922-2015. When analyzing the trends in sub-periods, there are two clear patterns in the annual rainfall series: a decreasing trend for the period 1922-1979 and a reversal increasing trend for the period 1980-2015. An increasing trend is also observed in annual reference evapotranspiration. The results reveal that the region will be drier with a significant increase in aridity at the annual and most monthly series. Appropriate adaptation strategies should be implemented to diminish the adverse influence of the increasing aridity on rice productivity for a sustainable agriculture.展开更多
The economy of most rural locations in the semi-arid region of Llano Estacado in the southern United States is predominantly based on agriculture, primarily beef and wheat (Triticum aestivum L.) production. This regio...The economy of most rural locations in the semi-arid region of Llano Estacado in the southern United States is predominantly based on agriculture, primarily beef and wheat (Triticum aestivum L.) production. This region is prone to drought and is projected to experience a drier climate. Droughts that coincide with the critical phenological phases of a crop can be remarkably costly. Although drought cannot be prevented, its losses can be minimized through mitigation measures if it is predicted in advance. Predicting yield loss from an imminent drought is an important need of stakeholders. One way to fulfill this need is using an agricultural drought index, such as the Agricultural Reference Index for Drought (ARID). Being plant physiology-based, ARID can represent drought-yield relationships accurately. This study developed an ARID-based yield model for predicting the drought-induced yield loss for winter wheat in this region by accounting for its phenological phase-specific sensitivity to water stress. The reasonable values of the drought sensitivity coefficients of the yield model indicated that it could reflect the phenomenon of water stress decreasing the winter wheat yields in this region reasonably. The values of the various metrics used to evaluate the model, including Willmott Index (0.86), Nash-Sutcliffe Index (0.61), and percentage error (26), indicated that the yield model performed fairly well at predicting the drought-induced yield loss for winter wheat. The yield model may be useful for predicting the drought-induced yield loss for winter wheat in the study region and scheduling irrigation allocation based on phenological phase-specific drought sensitivity.展开更多
Wheat (Triticum aestivum L.) production is a major economic activity in most regional and rural areas in the Southern Plains, a semi-arid region of the United States. This region is vulnerable to drought and is projec...Wheat (Triticum aestivum L.) production is a major economic activity in most regional and rural areas in the Southern Plains, a semi-arid region of the United States. This region is vulnerable to drought and is projected to experience a drier climate in the future. Since the interannual variability in climate in this region is linked to an ocean-atmospheric phenomenon, called El Niño-Southern Oscillation (ENSO), droughts in this region may be associated with ENSO. Droughts that occur during the critical growth phases of wheat can be extremely costly. However, the losses due to an impending drought can be minimized through mitigation measures if it is predicted in advance. Predicting the yield loss from an imminent drought is crucial for stakeholders. One of the reliable ways for such prediction is using a plant physiology-based agricultural drought index, such as Agricultural Reference Index for Drought (ARID). This study developed ENSO phase-specific, ARID-based models for predicting the drought-induced yield loss for winter wheat in this region by accounting for its phenological phase-specific sensitivity to drought. The reasonable values of the drought sensitivity coefficients of the yield model for each ENSO phase (El Niño, La Niña, or Neutral) indicated that the yield models reflected reasonably well the phenomena of water stress decreasing the winter wheat yields in this region during different ENSO phases. The values of various goodness-of-fit measures used, including the Nash-Sutcliffe Index (0.54 to 0.67), the Willmott Index (0.82 to 0.89), and the percentage error (20 to 26), indicated that the yield models performed fairly well at predicting the ENSO phase-specific loss of wheat yields from drought. This yield model may be useful for predicting yield loss from drought and scheduling irrigation allocation based on the phenological phase-specific sensitivity to drought as impacted by ENSO.展开更多
Mid-western China is one of the most sensitive and fragile areas on the Earth.Evapotranspiration(ET)is a key part of hydrological cycle in these areas and is affected by both global climate change and human activities...Mid-western China is one of the most sensitive and fragile areas on the Earth.Evapotranspiration(ET)is a key part of hydrological cycle in these areas and is affected by both global climate change and human activities.The dynamic changes in ET and potential evapotranspiration(PET),which can reflect water consumption and demand,are still unclear,and there is a lack of predictive capacity on drought severity.In this study,we used global MODIS(moderate-resolution imaging spectroradiometer)terrestrial ET(MOD16)products,Morlet wavelet analysis,and simple linear regression to investigate the spatiotemporal variations of ET,PET,reference ET(ET0),and aridity index(AI)in mid-western pastoral regions of China(including Gansu Province,Qinghai Province,Ningxia Hui Autonomous Region,and part of Inner Mongolia Autonomous Region)from 2001 to 2016.The results showed that the overall ET gradually increased from east to southwest in the study area.Actual ET showed an increasing trend,whereas PET tended to decrease from 2001 to 2016.The change in ET was affected by vegetation types.During the study period,the average annual ET0 and AI tended to decrease.At the monthly scale within a year,AI value decreased from January to July and then increased.The interannual variations of ET0 and AI showed periodicity with a main period of 14 a,and two other periodicities of 11 and 5 a.This study showed that in recent years,drought in these pastoral regions of mid-western China has been alleviated.Therefore,it is foreseeable that the demand for irrigation water for agricultural production in these regions will decrease.展开更多
Aim to linking the variability of drought in northwest China to the oceanic influence of North Atlantic SSTs at the background of global warming and at the regional climate change shifting stages, year aridity index v...Aim to linking the variability of drought in northwest China to the oceanic influence of North Atlantic SSTs at the background of global warming and at the regional climate change shifting stages, year aridity index variations in northwest China and summer North Atlantic sea surface temperature （SST） variations are examined for the 44 a period of 1961-2004 using singular value decomposition （SVD） analysis. Results show that the SST anomalies （SSTA）in the North Atlantic in summer reflected three basic models. The first SVD mode of SST pattern shows a dipole - like variation with the positive center located at southwest and negative center at northeast of extratropical North Atlantic. And it strongly relates to the positive trend in AI variation in northwest China. The second coupled modes display the coherent positive anomalies in extratropical North Atlantic SST and the marked opposite trend of AI variability between north and south of Xinjiang. In addition, the lag correlation analysis of the first mode of SSTA and geopotential heights at 500 hPa variations also shows that the indication of the former influencing the latter configuration, which result in higher air temperature and less precipitation when the SSTA in the North Atlantic Ocean in summer motivated Eurasian circulation of EA pattern, further to influence the wet - dry variations in northwest China by the ocean-to - atmosphere forcing.展开更多
Based on the data of monthly precipitation and other monthly meteorological elements of 661 meteorological stations over China from 1961 to 2013, the temporal evolution characteristics of aridity in Hetao area of Nort...Based on the data of monthly precipitation and other monthly meteorological elements of 661 meteorological stations over China from 1961 to 2013, the temporal evolution characteristics of aridity in Hetao area of North China which is drying significantly were studied by using REOF, and the effects of summer monsoon and meteorological factors on the aridity index were discussed. The results showed that climatic aridity in Hetac area of North China tended to increase with time during 1961 -2013. The annual variation and overall trend of climatic aridity in Hetao area of North China was mainly influenced by /SASM1 before the 1990s, and the degree of the influence weakened with global warming. There were certain differ- ences between annual and decadal variations in the effects of the meteorological elements on climatic aridity. The impact of the thermal factors on aridity index was more significant than the dynamic factor after the 1990s, revealing that climate warming aggravated climatic aridity in Hetao area of North China.展开更多
This research extensively evaluates three leading mathematical software packages: Python, MATLAB, and Scilab, in the context of solving nonlinear systems of equations with five unknown variables. The study’s core obj...This research extensively evaluates three leading mathematical software packages: Python, MATLAB, and Scilab, in the context of solving nonlinear systems of equations with five unknown variables. The study’s core objectives include comparing software performance using standardized benchmarks, employing key performance metrics for quantitative assessment, and examining the influence of varying hardware specifications on software efficiency across HP ProBook, HP EliteBook, Dell Inspiron, and Dell Latitude laptops. Results from this investigation reveal insights into the capabilities of these software tools in diverse computing environments. On the HP ProBook, Python consistently outperforms MATLAB in terms of computational time. Python also exhibits a lower robustness index for problems 3 and 5 but matches or surpasses MATLAB for problem 1, for some initial guess values. In contrast, on the HP EliteBook, MATLAB consistently exhibits shorter computational times than Python across all benchmark problems. However, Python maintains a lower robustness index for most problems, except for problem 3, where MATLAB performs better. A notable challenge is Python’s failure to converge for problem 4 with certain initial guess values, while MATLAB succeeds in producing results. Analysis on the Dell Inspiron reveals a split in strengths. Python demonstrates superior computational efficiency for some problems, while MATLAB excels in handling others. This pattern extends to the robustness index, with Python showing lower values for some problems, and MATLAB achieving the lowest indices for other problems. In conclusion, this research offers valuable insights into the comparative performance of Python, MATLAB, and Scilab in solving nonlinear systems of equations. It underscores the importance of considering both software and hardware specifications in real-world applications. The choice between Python and MATLAB can yield distinct advantages depending on the specific problem and computational environment, providing guidance for researchers and practitioners in selecting tools for their unique challenges.展开更多
As an important factor that directly affects agricultural production, the social economy, and policy implementation,observed changes in dry/wet conditions have become a matter of widespread concern. However, previous ...As an important factor that directly affects agricultural production, the social economy, and policy implementation,observed changes in dry/wet conditions have become a matter of widespread concern. However, previous research has mainly focused on the long-term linear changes of dry/wet conditions, while the detection and evolution of the non-linear trends related to dry/wet changes have received less attention. The non-linear trends of the annual aridity index, obtained by the Ensemble Empirical Mode Decomposition(EEMD) method, reveal that changes in dry/wet conditions in China are asymmetric and can be characterized by contrasting features in both time and space in China. Spatially, most areas in western China have experienced transitions from drying to wetting, while opposite changes have occurred in most areas of eastern China. Temporally, the transitions occurred earlier in western China compared to eastern China. Research into the asymmetric spatial characteristics of dry/wet conditions compensates for the inadequacies of previous studies, which focused solely on temporal evolution;at the same time, it remedies the inadequacies of traditional research on linear trends over centennial timescales. Analyzing the non-linear trend also provides for a more comprehensive understanding of the drying/wetting changes in China.展开更多
文摘Rainfall and evapotranspiration are two vital elements for food production under rainfed agriculture. This study aims at investigating the combined changes in these variables in the form of aridly index in the southern Senegal. The temporal trends in annual and monthly (from May to October) aridity index, rainfall and evapotranspiration are examined and adaptation strategies to the vulnerability of rainfed rice cultivation to the changes are developed. The results show a significant decreasing trend in annual rainfall at all study locations for the period 1922-2015. When analyzing the trends in sub-periods, there are two clear patterns in the annual rainfall series: a decreasing trend for the period 1922-1979 and a reversal increasing trend for the period 1980-2015. An increasing trend is also observed in annual reference evapotranspiration. The results reveal that the region will be drier with a significant increase in aridity at the annual and most monthly series. Appropriate adaptation strategies should be implemented to diminish the adverse influence of the increasing aridity on rice productivity for a sustainable agriculture.
文摘The economy of most rural locations in the semi-arid region of Llano Estacado in the southern United States is predominantly based on agriculture, primarily beef and wheat (Triticum aestivum L.) production. This region is prone to drought and is projected to experience a drier climate. Droughts that coincide with the critical phenological phases of a crop can be remarkably costly. Although drought cannot be prevented, its losses can be minimized through mitigation measures if it is predicted in advance. Predicting yield loss from an imminent drought is an important need of stakeholders. One way to fulfill this need is using an agricultural drought index, such as the Agricultural Reference Index for Drought (ARID). Being plant physiology-based, ARID can represent drought-yield relationships accurately. This study developed an ARID-based yield model for predicting the drought-induced yield loss for winter wheat in this region by accounting for its phenological phase-specific sensitivity to water stress. The reasonable values of the drought sensitivity coefficients of the yield model indicated that it could reflect the phenomenon of water stress decreasing the winter wheat yields in this region reasonably. The values of the various metrics used to evaluate the model, including Willmott Index (0.86), Nash-Sutcliffe Index (0.61), and percentage error (26), indicated that the yield model performed fairly well at predicting the drought-induced yield loss for winter wheat. The yield model may be useful for predicting the drought-induced yield loss for winter wheat in the study region and scheduling irrigation allocation based on phenological phase-specific drought sensitivity.
文摘Wheat (Triticum aestivum L.) production is a major economic activity in most regional and rural areas in the Southern Plains, a semi-arid region of the United States. This region is vulnerable to drought and is projected to experience a drier climate in the future. Since the interannual variability in climate in this region is linked to an ocean-atmospheric phenomenon, called El Niño-Southern Oscillation (ENSO), droughts in this region may be associated with ENSO. Droughts that occur during the critical growth phases of wheat can be extremely costly. However, the losses due to an impending drought can be minimized through mitigation measures if it is predicted in advance. Predicting the yield loss from an imminent drought is crucial for stakeholders. One of the reliable ways for such prediction is using a plant physiology-based agricultural drought index, such as Agricultural Reference Index for Drought (ARID). This study developed ENSO phase-specific, ARID-based models for predicting the drought-induced yield loss for winter wheat in this region by accounting for its phenological phase-specific sensitivity to drought. The reasonable values of the drought sensitivity coefficients of the yield model for each ENSO phase (El Niño, La Niña, or Neutral) indicated that the yield models reflected reasonably well the phenomena of water stress decreasing the winter wheat yields in this region during different ENSO phases. The values of various goodness-of-fit measures used, including the Nash-Sutcliffe Index (0.54 to 0.67), the Willmott Index (0.82 to 0.89), and the percentage error (20 to 26), indicated that the yield models performed fairly well at predicting the ENSO phase-specific loss of wheat yields from drought. This yield model may be useful for predicting yield loss from drought and scheduling irrigation allocation based on the phenological phase-specific sensitivity to drought as impacted by ENSO.
基金This work was supported by the earmarked fund for China Agriculture Research System of Ministry of Finance and Ministry of Agriculture and Rural Affairs(CARS-34)the National Key Research and Development Program of China(2016YFC0400302).
文摘Mid-western China is one of the most sensitive and fragile areas on the Earth.Evapotranspiration(ET)is a key part of hydrological cycle in these areas and is affected by both global climate change and human activities.The dynamic changes in ET and potential evapotranspiration(PET),which can reflect water consumption and demand,are still unclear,and there is a lack of predictive capacity on drought severity.In this study,we used global MODIS(moderate-resolution imaging spectroradiometer)terrestrial ET(MOD16)products,Morlet wavelet analysis,and simple linear regression to investigate the spatiotemporal variations of ET,PET,reference ET(ET0),and aridity index(AI)in mid-western pastoral regions of China(including Gansu Province,Qinghai Province,Ningxia Hui Autonomous Region,and part of Inner Mongolia Autonomous Region)from 2001 to 2016.The results showed that the overall ET gradually increased from east to southwest in the study area.Actual ET showed an increasing trend,whereas PET tended to decrease from 2001 to 2016.The change in ET was affected by vegetation types.During the study period,the average annual ET0 and AI tended to decrease.At the monthly scale within a year,AI value decreased from January to July and then increased.The interannual variations of ET0 and AI showed periodicity with a main period of 14 a,and two other periodicities of 11 and 5 a.This study showed that in recent years,drought in these pastoral regions of mid-western China has been alleviated.Therefore,it is foreseeable that the demand for irrigation water for agricultural production in these regions will decrease.
基金The National Natural Science Foundation of China under contract No.904110017
文摘Aim to linking the variability of drought in northwest China to the oceanic influence of North Atlantic SSTs at the background of global warming and at the regional climate change shifting stages, year aridity index variations in northwest China and summer North Atlantic sea surface temperature （SST） variations are examined for the 44 a period of 1961-2004 using singular value decomposition （SVD） analysis. Results show that the SST anomalies （SSTA）in the North Atlantic in summer reflected three basic models. The first SVD mode of SST pattern shows a dipole - like variation with the positive center located at southwest and negative center at northeast of extratropical North Atlantic. And it strongly relates to the positive trend in AI variation in northwest China. The second coupled modes display the coherent positive anomalies in extratropical North Atlantic SST and the marked opposite trend of AI variability between north and south of Xinjiang. In addition, the lag correlation analysis of the first mode of SSTA and geopotential heights at 500 hPa variations also shows that the indication of the former influencing the latter configuration, which result in higher air temperature and less precipitation when the SSTA in the North Atlantic Ocean in summer motivated Eurasian circulation of EA pattern, further to influence the wet - dry variations in northwest China by the ocean-to - atmosphere forcing.
基金Supported by the State Key Development Program for Basic Research of China(2013CB430200)
文摘Based on the data of monthly precipitation and other monthly meteorological elements of 661 meteorological stations over China from 1961 to 2013, the temporal evolution characteristics of aridity in Hetao area of North China which is drying significantly were studied by using REOF, and the effects of summer monsoon and meteorological factors on the aridity index were discussed. The results showed that climatic aridity in Hetac area of North China tended to increase with time during 1961 -2013. The annual variation and overall trend of climatic aridity in Hetao area of North China was mainly influenced by /SASM1 before the 1990s, and the degree of the influence weakened with global warming. There were certain differ- ences between annual and decadal variations in the effects of the meteorological elements on climatic aridity. The impact of the thermal factors on aridity index was more significant than the dynamic factor after the 1990s, revealing that climate warming aggravated climatic aridity in Hetao area of North China.
文摘This research extensively evaluates three leading mathematical software packages: Python, MATLAB, and Scilab, in the context of solving nonlinear systems of equations with five unknown variables. The study’s core objectives include comparing software performance using standardized benchmarks, employing key performance metrics for quantitative assessment, and examining the influence of varying hardware specifications on software efficiency across HP ProBook, HP EliteBook, Dell Inspiron, and Dell Latitude laptops. Results from this investigation reveal insights into the capabilities of these software tools in diverse computing environments. On the HP ProBook, Python consistently outperforms MATLAB in terms of computational time. Python also exhibits a lower robustness index for problems 3 and 5 but matches or surpasses MATLAB for problem 1, for some initial guess values. In contrast, on the HP EliteBook, MATLAB consistently exhibits shorter computational times than Python across all benchmark problems. However, Python maintains a lower robustness index for most problems, except for problem 3, where MATLAB performs better. A notable challenge is Python’s failure to converge for problem 4 with certain initial guess values, while MATLAB succeeds in producing results. Analysis on the Dell Inspiron reveals a split in strengths. Python demonstrates superior computational efficiency for some problems, while MATLAB excels in handling others. This pattern extends to the robustness index, with Python showing lower values for some problems, and MATLAB achieving the lowest indices for other problems. In conclusion, this research offers valuable insights into the comparative performance of Python, MATLAB, and Scilab in solving nonlinear systems of equations. It underscores the importance of considering both software and hardware specifications in real-world applications. The choice between Python and MATLAB can yield distinct advantages depending on the specific problem and computational environment, providing guidance for researchers and practitioners in selecting tools for their unique challenges.
基金supported by the National key research and development program (2019YFA0607104)National Natural Science Foundation of China (Grant Nos. 41991231, 42275034, 41975076, 42075029, 42075017, and 42075018)the Gansu Provincial Science and Technology Project (22JR5RA405)。
文摘As an important factor that directly affects agricultural production, the social economy, and policy implementation,observed changes in dry/wet conditions have become a matter of widespread concern. However, previous research has mainly focused on the long-term linear changes of dry/wet conditions, while the detection and evolution of the non-linear trends related to dry/wet changes have received less attention. The non-linear trends of the annual aridity index, obtained by the Ensemble Empirical Mode Decomposition(EEMD) method, reveal that changes in dry/wet conditions in China are asymmetric and can be characterized by contrasting features in both time and space in China. Spatially, most areas in western China have experienced transitions from drying to wetting, while opposite changes have occurred in most areas of eastern China. Temporally, the transitions occurred earlier in western China compared to eastern China. Research into the asymmetric spatial characteristics of dry/wet conditions compensates for the inadequacies of previous studies, which focused solely on temporal evolution;at the same time, it remedies the inadequacies of traditional research on linear trends over centennial timescales. Analyzing the non-linear trend also provides for a more comprehensive understanding of the drying/wetting changes in China.
