The Loess Plateau has a typical semi-arid climate, and the area suffers from very harsh ecological environment, severe soil erosion and water runoff, and uneven distributed precipitation. Due to the relatively low hol...The Loess Plateau has a typical semi-arid climate, and the area suffers from very harsh ecological environment, severe soil erosion and water runoff, and uneven distributed precipitation. Due to the relatively low holding capacity, current rainwater-collecting and conservation facilities can only supplement a maximum of18 mm of water for crop production in each irrigation. In this study, mathematical models were constructed to identify the water requirement critical period of maize crop by evaluating response of each individual developmental stage to supplemental irrigation with harvested rainwater. In the transformed Jensen model, ETmin/Eta was used as the index of relative evapotranspiration. The use of relative yield and relative crop evapotranspiration was able to eliminate influences from unintended environmental factors. A BP neural network crop-water model for extreme water deficit condition was constructed using the index of relative evapotranspiration as the input and the index of relative yield as the output after iterative training and adjustment of weight values. Comparison of measured maize yields to those predicted by the two models confirmed that the BP neural network crop-water model is more accurate than the transformed Jensen model in predicting the sensitivity index to waterdeficit at various growth stages and maize yield when provided with supplemental irrigation with harvested rainwater.展开更多
The study was undertaken to develop and evaluate evapotranspiration model for black gram (Vigna Mungo L.) crop under climatic conditions of Udaipur, India. Pan evaporation data for the duration of twenty three years (...The study was undertaken to develop and evaluate evapotranspiration model for black gram (Vigna Mungo L.) crop under climatic conditions of Udaipur, India. Pan evaporation data for the duration of twenty three years (1978-2001) and measured black gram evapotranspiration data by electronic lysimeter for duration of kharif season of 2001 were used for analysis. Black gram is an important crop of Udaipur region. No sys-tematic study on modelling of black gram evapotranspiration was conducted in past under above said cli-matic conditions. Therefore, stochastic model was developed for the estimation of daily black gram evapotranspiration using 24 years data. Validation of the developed models was done by the comparison of the estimated values with the measured values. The developed stochastic model for black gram evapotran-spiration was found to predict the daily black gram evapotranspiration very accurately.展开更多
Accurate models to simulate the soil water balance in semiarid cropping systems are needed to evaluate management practices for soil and water conservation in both irrigated and dryland production systems. The objecti...Accurate models to simulate the soil water balance in semiarid cropping systems are needed to evaluate management practices for soil and water conservation in both irrigated and dryland production systems. The objective of this study was to evaluate the application of the Precision Agricultural Landscape Modeling System (PALMS) model to simulate soil water content throughout the growing season for several years and for three major soil series of the semiarid Texas Southern High Plains (SHP). Accuracy of the model was evaluated by comparing measured and calculated values of soil water content and using root mean squared difference (RMSD), squared bias (SB), squared difference between standard deviations (SDSD), and lack of correlation weighted by the standard deviation (LCS). Different versions of the model were obtained by modifying soil hydraulic properties, including saturated hydraulic conductivity (Ks) and residual (θr) and saturated (θs) soil volumetric water content, which were calculated using Rosetta pedotransfer functions. These modifications were combined with updated routines of the soil water solver in PALMS to account for rapid infiltration into dry soils that often occur in the SHP. Field studies were conducted across a wide range of soil and water conditions in the SHP. Soil water content was measured by neutron attenuation and gravimetrically throughout the growing seasons at each location to compare absolute values and the spatial distribution of soil water with PALMS calculated values. Use of Rosetta calculated soil hydraulic properties improved PALMS soil water calculation from 1% - 13% of measured soil volumetric water content (θv) depending on soil type. Large-scale models such as PALMS have the potential to more realistically represent management effects on soil water availability in agricultural fields. Improvements in PALMS soil water calculations indicated that the model may be useful to assess long-term implications of management practices designed to conserve irrigation water and maximize the profitability of dryland and irrigated cropping systems in the SHP.展开更多
Crop models often require extensive input data sets to realistically simulate crop growth. Development of such input data sets can be difficult for some model users. The objective of this study was to evaluate the imp...Crop models often require extensive input data sets to realistically simulate crop growth. Development of such input data sets can be difficult for some model users. The objective of this study was to evaluate the importance of variables in input data sets for crop modeling. Based on published hybrid performance trials in eight Texas counties, we developed standard data sets of 10-year simulations of maize and sorghum for these eight counties with the ALMANAC (Agricultural Land Management Alternatives with Numerical Assessment Criteria) model. The simulation results were close to the measured county yields with relative error only 2.6% for maize, and - 0.6% for sorghum. We then analyzed the sensitivity of grain yield to solar radiation, rainfall, soil depth, soil plant available water, and runoff curve number, comparing simulated yields to those with the original, standard data sets. Runoff curve number changes had the greatest impact on simulated maize and sorghum yields for all the counties. The next most critical input was rainfall, and then solar radiation for both maize and sorghum, especially for the dryland condition. For irrigated sorghum, solar radiation was the second most critical input instead of rainfall. The degree of sensitivity of yield to all variables for maize was larger than for sorghum except for solar radiation. Many models use a USDA curve number approach to represent soil water redistribution, so it will be important to have accurate curve numbers, rainfall, and soil depth to realistically simulate yields.展开更多
[目的]探究不同年型下饲用燕麦产量对各生育期降水变化的响应,为饲用燕麦抗旱与高效生产提供参考。[方法]利用作物生长机理模型APSIM(agricultural production systems simulator),以山西省朔州市右玉县1980—2009年的历史气候气象数据...[目的]探究不同年型下饲用燕麦产量对各生育期降水变化的响应,为饲用燕麦抗旱与高效生产提供参考。[方法]利用作物生长机理模型APSIM(agricultural production systems simulator),以山西省朔州市右玉县1980—2009年的历史气候气象数据作为原始情景,将饲用燕麦生育期划分为4个阶段[阶段1(播种—拔节)、阶段2(拔节—抽穗)、阶段3(抽穗—灌浆)、阶段4(灌浆—收获)],并提取典型气候条件(干旱、平水、丰水)建立12个新的气候情景并进行模拟,分析饲用燕麦产量受降水变化的影响。[结果]在干旱情景(DS)中,产量与水分利用效率(water use efficiency,WUE)较原始情景分别下降了38.0%~60.9%与31.8%~16.9%(P<0.01),其中,抽穗—灌浆期采用历史数据时,指标的下降幅度最小。对于平水情景(NS)来说,产量相对原始情景的变化为-3.4%~20.0%,WUE为0~10.0%,拔节—抽穗期及灌浆—收获期采用历史数据时指标的变化显著(P<0.05)。丰水情景(WS)中,饲用燕麦产量与WUE相对原始情景均显著提升(P<0.01),幅度分别达到33.3%~60.5%与6.8%~14.8%,且播种—拔节期的降水变化对指标有相对明显的影响(R^(2)=0.3777,P<0.01)。[结论]饲用燕麦产草量和水分利用效率WUE在干旱、平水、丰水年型中都对灌浆—收获期的降水变化没有明显的敏感性;在干旱和平水年型下,饲草产量对抽穗—灌浆期的干旱更为敏感,WUE则对拔节—抽穗期及抽穗—灌浆期的干旱更为敏感;在丰水年型下,燕麦饲草产量对干旱最敏感的时期是播种—拔节期。有限的灌溉条件下,可将灌溉集中于WUE对降水变化最为敏感的阶段3(抽穗—灌浆)。展开更多
基金Supported by Inner Mongolia water conservancy"Twelfth five-year"Major Science and Technology Demonstration Project-scientific Support Project for New Water-saving Irrigation Area of Four ten Million mu in Inner Mongolia in China(20121036)the National Natural Science Foundation of China(No.51469026,2012MS0621)the Guided Reward Fund for Scientific and Technological Innovation,Inner Mongolia,China
文摘The Loess Plateau has a typical semi-arid climate, and the area suffers from very harsh ecological environment, severe soil erosion and water runoff, and uneven distributed precipitation. Due to the relatively low holding capacity, current rainwater-collecting and conservation facilities can only supplement a maximum of18 mm of water for crop production in each irrigation. In this study, mathematical models were constructed to identify the water requirement critical period of maize crop by evaluating response of each individual developmental stage to supplemental irrigation with harvested rainwater. In the transformed Jensen model, ETmin/Eta was used as the index of relative evapotranspiration. The use of relative yield and relative crop evapotranspiration was able to eliminate influences from unintended environmental factors. A BP neural network crop-water model for extreme water deficit condition was constructed using the index of relative evapotranspiration as the input and the index of relative yield as the output after iterative training and adjustment of weight values. Comparison of measured maize yields to those predicted by the two models confirmed that the BP neural network crop-water model is more accurate than the transformed Jensen model in predicting the sensitivity index to waterdeficit at various growth stages and maize yield when provided with supplemental irrigation with harvested rainwater.
文摘The study was undertaken to develop and evaluate evapotranspiration model for black gram (Vigna Mungo L.) crop under climatic conditions of Udaipur, India. Pan evaporation data for the duration of twenty three years (1978-2001) and measured black gram evapotranspiration data by electronic lysimeter for duration of kharif season of 2001 were used for analysis. Black gram is an important crop of Udaipur region. No sys-tematic study on modelling of black gram evapotranspiration was conducted in past under above said cli-matic conditions. Therefore, stochastic model was developed for the estimation of daily black gram evapotranspiration using 24 years data. Validation of the developed models was done by the comparison of the estimated values with the measured values. The developed stochastic model for black gram evapotran-spiration was found to predict the daily black gram evapotranspiration very accurately.
文摘Accurate models to simulate the soil water balance in semiarid cropping systems are needed to evaluate management practices for soil and water conservation in both irrigated and dryland production systems. The objective of this study was to evaluate the application of the Precision Agricultural Landscape Modeling System (PALMS) model to simulate soil water content throughout the growing season for several years and for three major soil series of the semiarid Texas Southern High Plains (SHP). Accuracy of the model was evaluated by comparing measured and calculated values of soil water content and using root mean squared difference (RMSD), squared bias (SB), squared difference between standard deviations (SDSD), and lack of correlation weighted by the standard deviation (LCS). Different versions of the model were obtained by modifying soil hydraulic properties, including saturated hydraulic conductivity (Ks) and residual (θr) and saturated (θs) soil volumetric water content, which were calculated using Rosetta pedotransfer functions. These modifications were combined with updated routines of the soil water solver in PALMS to account for rapid infiltration into dry soils that often occur in the SHP. Field studies were conducted across a wide range of soil and water conditions in the SHP. Soil water content was measured by neutron attenuation and gravimetrically throughout the growing seasons at each location to compare absolute values and the spatial distribution of soil water with PALMS calculated values. Use of Rosetta calculated soil hydraulic properties improved PALMS soil water calculation from 1% - 13% of measured soil volumetric water content (θv) depending on soil type. Large-scale models such as PALMS have the potential to more realistically represent management effects on soil water availability in agricultural fields. Improvements in PALMS soil water calculations indicated that the model may be useful to assess long-term implications of management practices designed to conserve irrigation water and maximize the profitability of dryland and irrigated cropping systems in the SHP.
文摘Crop models often require extensive input data sets to realistically simulate crop growth. Development of such input data sets can be difficult for some model users. The objective of this study was to evaluate the importance of variables in input data sets for crop modeling. Based on published hybrid performance trials in eight Texas counties, we developed standard data sets of 10-year simulations of maize and sorghum for these eight counties with the ALMANAC (Agricultural Land Management Alternatives with Numerical Assessment Criteria) model. The simulation results were close to the measured county yields with relative error only 2.6% for maize, and - 0.6% for sorghum. We then analyzed the sensitivity of grain yield to solar radiation, rainfall, soil depth, soil plant available water, and runoff curve number, comparing simulated yields to those with the original, standard data sets. Runoff curve number changes had the greatest impact on simulated maize and sorghum yields for all the counties. The next most critical input was rainfall, and then solar radiation for both maize and sorghum, especially for the dryland condition. For irrigated sorghum, solar radiation was the second most critical input instead of rainfall. The degree of sensitivity of yield to all variables for maize was larger than for sorghum except for solar radiation. Many models use a USDA curve number approach to represent soil water redistribution, so it will be important to have accurate curve numbers, rainfall, and soil depth to realistically simulate yields.
文摘[目的]探究不同年型下饲用燕麦产量对各生育期降水变化的响应,为饲用燕麦抗旱与高效生产提供参考。[方法]利用作物生长机理模型APSIM(agricultural production systems simulator),以山西省朔州市右玉县1980—2009年的历史气候气象数据作为原始情景,将饲用燕麦生育期划分为4个阶段[阶段1(播种—拔节)、阶段2(拔节—抽穗)、阶段3(抽穗—灌浆)、阶段4(灌浆—收获)],并提取典型气候条件(干旱、平水、丰水)建立12个新的气候情景并进行模拟,分析饲用燕麦产量受降水变化的影响。[结果]在干旱情景(DS)中,产量与水分利用效率(water use efficiency,WUE)较原始情景分别下降了38.0%~60.9%与31.8%~16.9%(P<0.01),其中,抽穗—灌浆期采用历史数据时,指标的下降幅度最小。对于平水情景(NS)来说,产量相对原始情景的变化为-3.4%~20.0%,WUE为0~10.0%,拔节—抽穗期及灌浆—收获期采用历史数据时指标的变化显著(P<0.05)。丰水情景(WS)中,饲用燕麦产量与WUE相对原始情景均显著提升(P<0.01),幅度分别达到33.3%~60.5%与6.8%~14.8%,且播种—拔节期的降水变化对指标有相对明显的影响(R^(2)=0.3777,P<0.01)。[结论]饲用燕麦产草量和水分利用效率WUE在干旱、平水、丰水年型中都对灌浆—收获期的降水变化没有明显的敏感性;在干旱和平水年型下,饲草产量对抽穗—灌浆期的干旱更为敏感,WUE则对拔节—抽穗期及抽穗—灌浆期的干旱更为敏感;在丰水年型下,燕麦饲草产量对干旱最敏感的时期是播种—拔节期。有限的灌溉条件下,可将灌溉集中于WUE对降水变化最为敏感的阶段3(抽穗—灌浆)。
