Assessing and managing the spatial variability of hydropedological properties are important in environmental,agricultural,and geological sciences.The spatial variability of soil apparent electrical conductivity(ECa) m...Assessing and managing the spatial variability of hydropedological properties are important in environmental,agricultural,and geological sciences.The spatial variability of soil apparent electrical conductivity(ECa) measured by electromagnetic induction(EMI) techniques has been widely used to infer the spatial variability of hydrological and pedological properties.In this study,temporal stability analysis was conducted for measuring repeatedly soil ECa in an agricultural landscape in 2008.Such temporal stability was statistically compared with the soil moisture,terrain indices(slope,topographic wetness index(TWI),and profile curvature),and soil properties(particle size distribution,depth to bedrock,Mn mottle content,and soil type).Locations with great and temporally unstable soil ECa were also associated with great and unstable soil moisture,respectively.Soil ECa were greater and more unstable in the areas with great TWI(TWI > 8),gentle and concave slope(slope < 3%; profile curvature > 0.2).Soil ECa exponentially increased with depth to bedrock,and soil profile silt and Mn mottle contents(R2= 0.57),quadratically(R2 = 0.47),and linearly(R 2 = 0.47),respectively.Soil ECa was greater and more unstable in Gleysol and Nitosol soils,which were distributed in areas with low elevation(< 380 m),thick soil solum(> 3 m),and fluctuated water table(shallow in winter and spring but deep in summer and fall).In contrast,Acrisol,Luvisol,and Cambisol soils,which are distributed in the upper slope areas,had lower and more stable soil ECa.Through these observations,we concluded that the temporal stability of soil ECa can be used to interpret the spatial and temporal variability of these hydropedological properties.展开更多
Agronomic management practices that maximize monoculture switchgrass (Panicum virgatum L.) yield are generally well understood;however, little is known about corresponding effects of differing switchgrass management p...Agronomic management practices that maximize monoculture switchgrass (Panicum virgatum L.) yield are generally well understood;however, little is known about corresponding effects of differing switchgrass management practices on near-surface soil properties and processes. The objective of the study was to evaluate the effects of cultivar (“Alamo” and “Cave-in-Rock”), harvest frequency (1- and 2-cuts per year), fertilizer source (poultry litter and commercial fertilizer), and irrigation management (irrigated and non-irrigated) on near-surface soil properties and surface infiltration in a Leadvale silt loam (fine-silty, siliceous, semiactive, thermic, Typic Fragiudult) after four years (2008 through 2011) of consistent management in west-central Arkansas. Irrigating switchgrass increased (P 0.05) and averaged 0.79 mm?min?1. Results from this study indicate that management decisions to maximize switchgrass biomass production affect soil properties over relatively short periods of time, and further research is needed to develop local best management practices to maximize yield while maintaining or improving soil quality.展开更多
Traditionally, soil-testing laboratories have used a variety of methods to determine soil organic matter, yet they lack a practical method to predict potential N mineralization/immobilization from soil organic matter....Traditionally, soil-testing laboratories have used a variety of methods to determine soil organic matter, yet they lack a practical method to predict potential N mineralization/immobilization from soil organic matter. Soils with high micro-bial activity may experience N immobilization (or reduced net N mineralization), and this issue remains unresolved in how to predict these conditions of net mineralization or net immobilization. Prediction may become possible with the use of a more sensitive method to determine soil C:N ratios stemming from the water-extractable C and N pools that can be readily adapted by both commercial and university soil testing labs. Soil microbial activity is highly related to soil organic C and N, as well as to water-extractable organic C (WEOC) and water-extractable organic N (WEON). The relationship between soil respiration and WEOC and WEON is stronger than between respiration and soil organic C (SOC) and total organic N (TON). We explored the relationship between soil organic C:N and water-extractable organic C:N, as well as their relationship to soil microbial activity as measured by the flush of CO2 following rewetting of dried soil. In 50 different soils, the relationship between soil microbial activity and water-extractable organic C:N was much stronger than for soil organic C: N. We concluded that the water-extractable organic C:N was a more sensitive measurement of the soil substrate which drives soil microbial activity. We also suggest that a water-extractable organic C:N level > 20 be used as a practical threshold to separate those soils that may have immobilized N with high microbial activity.展开更多
While global efforts to operationalize soil spectroscopy are progressing,cooperation is needed to fully leverage its potential for generating digital soil information to support sustainable soil management worldwide.T...While global efforts to operationalize soil spectroscopy are progressing,cooperation is needed to fully leverage its potential for generating digital soil information to support sustainable soil management worldwide.The Global Soil Laboratory Network’s soil spectroscopy initiative(GLOSOLANSpec),led by the Food and Agriculture Organization of the United Nations(FAO)through its Global Soil Partnership(GSP),is dedicated to the further development and adoption of soil spectroscopy by fostering international collaboration via a scientific community of practice to produce accurate and reliable soil information for sustainable soil management and decision-making.To support this effort,we,a global consortium of soil scientists under the auspices of the International Union of Soil Sciences(IUSS)and GLOSOLAN-Spec,aim to address seven key challenges hindering the adoption of soil spectroscopy worldwide.Here,we offer perspectives on what is needed to advance soil spectroscopy as a routine soil analysis method,emphasizing its potential to generate new and reliable spatial and temporal soil data.展开更多
Machine learning(ML)is becoming an ever more important tool in hydrologic modeling.Previous studies have shown the higher prediction accuracy of those ML models over traditional process-based ones.However,there is ano...Machine learning(ML)is becoming an ever more important tool in hydrologic modeling.Previous studies have shown the higher prediction accuracy of those ML models over traditional process-based ones.However,there is another advantage of ML which is its lower computational demand.This is important for the applications such as hydraulic soil erosion estimation over a large area and at a finer spatial scale.Using traditional models like Rangeland Hydrology and Erosion Model(RHEM)requires too much computation time and resources.In this study,we designed an Artificial Neural Network that is able to recreate the RHEM outputs(annual average runoff,soil loss,and sediment yield and not the daily storm event-based values)with high accuracy(Nash-Sutcliffe Efficiency≈1.0)and a very low computational time(13 billion times faster on average using a GPU).We ran the RHEM for more than a million synthetic scenarios and train the Emulator with them.We also,fine-tuned the trained Emulator with the RHEM runs of the real-world scenarios(more than 32,000)so the Emulator remains comprehensive while it works specifically accurately for the real-world cases.We also showed that the sensitivity of the Emulator to the input variables is similar to the RHEM and it can effectively capture the changes in the RHEM outputs when an input variable varies.Finally,the dynamic prediction behavior of the Emulator is statistically similar to the RHEM.展开更多
Nutrient loss from agricultural fields is one of the main factors influencing surface-and ground-water quality.Typical fertilizer nitrogen(N)consumption rates in vegetable production systems and horticultural crops in...Nutrient loss from agricultural fields is one of the main factors influencing surface-and ground-water quality.Typical fertilizer nitrogen(N)consumption rates in vegetable production systems and horticultural crops in Puerto Rico fluctuate between 112 and 253 kg N/ha.The nitrogen use efficiency of vegetable crops is low,increasing the potential for nitrogen losses and high residual soil nitrate content.Quantification of residual soil N and N losses to the environment can be a difficult task.Simulation models such as the USDA-ARS N Index can be used to identify the relative magnitude of varying N-loss pathways and to identify best management practices.Field studies were conducted to quantify residual soil N and crop N removal,and to validate the Nitrogen Index in onion,tropical pumpkin and tomato production systems in the Lajas Valley in southwestern Puerto Rico.Relationships between observed and simulated values were determined to examine the capability of the model for evaluating N losses.There was good correlation between observed and predicted values for residual soil N(r=0.88)and crop N removal(r=0.99)(p<0.05).In the production systems evaluated,the N volatilization losses ranged from 1 to 4 kg N/ha,the denitrification losses ranged from 18 to 46 kg N/ha,the leaching losses ranged from 155 to 779 kg N/ha,and the residual soil nitrate ranged from 64 to 401 kg N/ha.The N use efficiency ranged from 15% to 39%.The results obtained showed that the Nitrogen Index tool can be a useful tool for evaluating N transformations in vegetable production systems of Puerto Rico's semi-arid zone.展开更多
Thirty-nine soils were studied on Holocene and late Pleistocene geomorphic surfaces.Granodiorite, sandstone, and alluvium derived from these rocks are the parent materials. Climateis Mediterranean. Chamise （Adenostom...Thirty-nine soils were studied on Holocene and late Pleistocene geomorphic surfaces.Granodiorite, sandstone, and alluvium derived from these rocks are the parent materials. Climateis Mediterranean. Chamise （Adenostoma faciculatum） is on the drier sites and redwood （Sequoiasempervirens） on the moister sites. Our objectives are twofold, （1） Find if today’s two-season wet-dry, subhumid climate explains the general noncalcic nature of the soils, or if not （2） accept thattheir noncalcic nature results from more moist past climates and define some indicator soilproperties. The depth to carbonate in the soils formed in calcareous materials on Holocenesurfaces corresponds roughly to the average annual depth of water movement, not to the predictedwettest years. We accept then, that the relict paleosols formed under one or more pluvial cyclesbecause they are free of carbonate below their B horizons. Defined levels of pedon clayaccumulation, dithionite-citrate extractable Fe （Fe<sub>d</sub>） accumulation in the B horizons, cationexchange capacity at pH 7 （CEC<sub>7</sub>） to clay ratios, and the minimum base saturation at pH 7 （BS<sub>7</sub>） inthe pedons are useful properties for separating these relict paleosols from the Holocene age soils.A further evidence of the relict nature of the soils on the Pleistocene surfaces is the weatheringreversal noted in these previously weathered materials.展开更多
基金supported by the USDA National Research Initiative(Grant No.2002-35102-12547)supported by National Natural Science Foundation of China(Grant No.41271109)Leading Edge Project of Nanjing Institute of Geography and Limnology,Chinese Academy of Sciences(Grant No.NIGLAS2011YJ01)
文摘Assessing and managing the spatial variability of hydropedological properties are important in environmental,agricultural,and geological sciences.The spatial variability of soil apparent electrical conductivity(ECa) measured by electromagnetic induction(EMI) techniques has been widely used to infer the spatial variability of hydrological and pedological properties.In this study,temporal stability analysis was conducted for measuring repeatedly soil ECa in an agricultural landscape in 2008.Such temporal stability was statistically compared with the soil moisture,terrain indices(slope,topographic wetness index(TWI),and profile curvature),and soil properties(particle size distribution,depth to bedrock,Mn mottle content,and soil type).Locations with great and temporally unstable soil ECa were also associated with great and unstable soil moisture,respectively.Soil ECa were greater and more unstable in the areas with great TWI(TWI > 8),gentle and concave slope(slope < 3%; profile curvature > 0.2).Soil ECa exponentially increased with depth to bedrock,and soil profile silt and Mn mottle contents(R2= 0.57),quadratically(R2 = 0.47),and linearly(R 2 = 0.47),respectively.Soil ECa was greater and more unstable in Gleysol and Nitosol soils,which were distributed in areas with low elevation(< 380 m),thick soil solum(> 3 m),and fluctuated water table(shallow in winter and spring but deep in summer and fall).In contrast,Acrisol,Luvisol,and Cambisol soils,which are distributed in the upper slope areas,had lower and more stable soil ECa.Through these observations,we concluded that the temporal stability of soil ECa can be used to interpret the spatial and temporal variability of these hydropedological properties.
文摘Agronomic management practices that maximize monoculture switchgrass (Panicum virgatum L.) yield are generally well understood;however, little is known about corresponding effects of differing switchgrass management practices on near-surface soil properties and processes. The objective of the study was to evaluate the effects of cultivar (“Alamo” and “Cave-in-Rock”), harvest frequency (1- and 2-cuts per year), fertilizer source (poultry litter and commercial fertilizer), and irrigation management (irrigated and non-irrigated) on near-surface soil properties and surface infiltration in a Leadvale silt loam (fine-silty, siliceous, semiactive, thermic, Typic Fragiudult) after four years (2008 through 2011) of consistent management in west-central Arkansas. Irrigating switchgrass increased (P 0.05) and averaged 0.79 mm?min?1. Results from this study indicate that management decisions to maximize switchgrass biomass production affect soil properties over relatively short periods of time, and further research is needed to develop local best management practices to maximize yield while maintaining or improving soil quality.
文摘Traditionally, soil-testing laboratories have used a variety of methods to determine soil organic matter, yet they lack a practical method to predict potential N mineralization/immobilization from soil organic matter. Soils with high micro-bial activity may experience N immobilization (or reduced net N mineralization), and this issue remains unresolved in how to predict these conditions of net mineralization or net immobilization. Prediction may become possible with the use of a more sensitive method to determine soil C:N ratios stemming from the water-extractable C and N pools that can be readily adapted by both commercial and university soil testing labs. Soil microbial activity is highly related to soil organic C and N, as well as to water-extractable organic C (WEOC) and water-extractable organic N (WEON). The relationship between soil respiration and WEOC and WEON is stronger than between respiration and soil organic C (SOC) and total organic N (TON). We explored the relationship between soil organic C:N and water-extractable organic C:N, as well as their relationship to soil microbial activity as measured by the flush of CO2 following rewetting of dried soil. In 50 different soils, the relationship between soil microbial activity and water-extractable organic C:N was much stronger than for soil organic C: N. We concluded that the water-extractable organic C:N was a more sensitive measurement of the soil substrate which drives soil microbial activity. We also suggest that a water-extractable organic C:N level > 20 be used as a practical threshold to separate those soils that may have immobilized N with high microbial activity.
基金supported by the Food and Agriculture Organization’s“SoilFER-VACS Framework-Enhancing Integrated Soil-Crop Management for Sustainable Food Systems in Africa”project,funded by the Ministry of Foreign Affairs of Japan.
文摘While global efforts to operationalize soil spectroscopy are progressing,cooperation is needed to fully leverage its potential for generating digital soil information to support sustainable soil management worldwide.The Global Soil Laboratory Network’s soil spectroscopy initiative(GLOSOLANSpec),led by the Food and Agriculture Organization of the United Nations(FAO)through its Global Soil Partnership(GSP),is dedicated to the further development and adoption of soil spectroscopy by fostering international collaboration via a scientific community of practice to produce accurate and reliable soil information for sustainable soil management and decision-making.To support this effort,we,a global consortium of soil scientists under the auspices of the International Union of Soil Sciences(IUSS)and GLOSOLAN-Spec,aim to address seven key challenges hindering the adoption of soil spectroscopy worldwide.Here,we offer perspectives on what is needed to advance soil spectroscopy as a routine soil analysis method,emphasizing its potential to generate new and reliable spatial and temporal soil data.
基金supported by the U.S.Department of Agriculture,Natural Resources Conservation Service,Conservation Effects Assessment Project(CEAP)Grazing Lands Component,under agreement number NR193A750007C002。
文摘Machine learning(ML)is becoming an ever more important tool in hydrologic modeling.Previous studies have shown the higher prediction accuracy of those ML models over traditional process-based ones.However,there is another advantage of ML which is its lower computational demand.This is important for the applications such as hydraulic soil erosion estimation over a large area and at a finer spatial scale.Using traditional models like Rangeland Hydrology and Erosion Model(RHEM)requires too much computation time and resources.In this study,we designed an Artificial Neural Network that is able to recreate the RHEM outputs(annual average runoff,soil loss,and sediment yield and not the daily storm event-based values)with high accuracy(Nash-Sutcliffe Efficiency≈1.0)and a very low computational time(13 billion times faster on average using a GPU).We ran the RHEM for more than a million synthetic scenarios and train the Emulator with them.We also,fine-tuned the trained Emulator with the RHEM runs of the real-world scenarios(more than 32,000)so the Emulator remains comprehensive while it works specifically accurately for the real-world cases.We also showed that the sensitivity of the Emulator to the input variables is similar to the RHEM and it can effectively capture the changes in the RHEM outputs when an input variable varies.Finally,the dynamic prediction behavior of the Emulator is statistically similar to the RHEM.
文摘Nutrient loss from agricultural fields is one of the main factors influencing surface-and ground-water quality.Typical fertilizer nitrogen(N)consumption rates in vegetable production systems and horticultural crops in Puerto Rico fluctuate between 112 and 253 kg N/ha.The nitrogen use efficiency of vegetable crops is low,increasing the potential for nitrogen losses and high residual soil nitrate content.Quantification of residual soil N and N losses to the environment can be a difficult task.Simulation models such as the USDA-ARS N Index can be used to identify the relative magnitude of varying N-loss pathways and to identify best management practices.Field studies were conducted to quantify residual soil N and crop N removal,and to validate the Nitrogen Index in onion,tropical pumpkin and tomato production systems in the Lajas Valley in southwestern Puerto Rico.Relationships between observed and simulated values were determined to examine the capability of the model for evaluating N losses.There was good correlation between observed and predicted values for residual soil N(r=0.88)and crop N removal(r=0.99)(p<0.05).In the production systems evaluated,the N volatilization losses ranged from 1 to 4 kg N/ha,the denitrification losses ranged from 18 to 46 kg N/ha,the leaching losses ranged from 155 to 779 kg N/ha,and the residual soil nitrate ranged from 64 to 401 kg N/ha.The N use efficiency ranged from 15% to 39%.The results obtained showed that the Nitrogen Index tool can be a useful tool for evaluating N transformations in vegetable production systems of Puerto Rico's semi-arid zone.
文摘Thirty-nine soils were studied on Holocene and late Pleistocene geomorphic surfaces.Granodiorite, sandstone, and alluvium derived from these rocks are the parent materials. Climateis Mediterranean. Chamise （Adenostoma faciculatum） is on the drier sites and redwood （Sequoiasempervirens） on the moister sites. Our objectives are twofold, （1） Find if today’s two-season wet-dry, subhumid climate explains the general noncalcic nature of the soils, or if not （2） accept thattheir noncalcic nature results from more moist past climates and define some indicator soilproperties. The depth to carbonate in the soils formed in calcareous materials on Holocenesurfaces corresponds roughly to the average annual depth of water movement, not to the predictedwettest years. We accept then, that the relict paleosols formed under one or more pluvial cyclesbecause they are free of carbonate below their B horizons. Defined levels of pedon clayaccumulation, dithionite-citrate extractable Fe （Fe<sub>d</sub>） accumulation in the B horizons, cationexchange capacity at pH 7 （CEC<sub>7</sub>） to clay ratios, and the minimum base saturation at pH 7 （BS<sub>7</sub>） inthe pedons are useful properties for separating these relict paleosols from the Holocene age soils.A further evidence of the relict nature of the soils on the Pleistocene surfaces is the weatheringreversal noted in these previously weathered materials.
