Soil salinization is a serious ecological and environmental problem because it adversely affects sustainable development worldwide, especially in arid and semi-arid regions. It is crucial and urgent that advanced tech...Soil salinization is a serious ecological and environmental problem because it adversely affects sustainable development worldwide, especially in arid and semi-arid regions. It is crucial and urgent that advanced technologies are used to efficiently and accurately assess the status of salinization processes. Case studies to determine the relations between particular types of salinization and their spectral reflectances are essential because of the distinctive characteristics of the reflectance spectra of particular salts. During April 2015 we collected surface soil samples(0–10 cm depth) at 64 field sites in the downstream area of Minqin Oasis in Northwest China, an area that is undergoing serious salinization. We developed a linear model for determination of salt content in soil from hyperspectral data as follows. First, we undertook chemical analysis of the soil samples to determine their soluble salt contents. We then measured the reflectance spectra of the soil samples, which we post-processed using a continuum-removed reflectance algorithm to enhance the absorption features and better discriminate subtle differences in spectral features. We applied a normalized difference salinity index to the continuum-removed hyperspectral data to obtain all possible waveband pairs. Correlation of the indices obtained for all of the waveband pairs with the wavebands corresponding to measured soil salinities showed that two wavebands centred at wavelengths of 1358 and 2382 nm had the highest sensitivity to salinity. We then applied the linear regression modelling to the data from half of the soil samples to develop a soil salinity index for the relationships between wavebands and laboratory measured soluble salt content. We used the hyperspectral data from the remaining samples to validate the model. The salt content in soil from Minqin Oasis were well produced by the model. Our results indicate that wavelengths at 1358 and 2382 nm are the optimal wavebands for monitoring the concentrations of chlorine and sulphate compounds, the predominant salts at Minqin Oasis. Our modelling provides a reference for future case studies on the use of hyperspectral data for predictive quantitative estimation of salt content in soils in arid regions. Further research is warranted on the application of this method to remotely sensed hyperspectral data to investigate its potential use for large-scale mapping of the extent and severity of soil salinity.展开更多
Hyperspectral data are an important source for monitoring soil salt content on a large scale. However, in previous studies, barriers such as interference due to the presence of vegetation restricted the precision of m...Hyperspectral data are an important source for monitoring soil salt content on a large scale. However, in previous studies, barriers such as interference due to the presence of vegetation restricted the precision of mapping soil salt content. This study tested a new method for predicting soil salt content with improved precision by using Chinese hyperspectral data, Huan Jing-Hyper Spectral Imager(HJ-HSI), in the coastal area of Rudong County, Eastern China. The vegetation-covered area and coastal bare flat area were distinguished by using the normalized differential vegetation index at the band length of 705 nm(NDVI705). The soil salt content of each area was predicted by various algorithms. A Normal Soil Salt Content Response Index(NSSRI) was constructed from continuum-removed reflectance(CR-reflectance) at wavelengths of 908.95 nm and 687.41 nm to predict the soil salt content in the coastal bare flat area(NDVI705 < 0.2). The soil adjusted salinity index(SAVI) was applied to predict the soil salt content in the vegetation-covered area(NDVI705 ≥ 0.2). The results demonstrate that 1) the new method significantly improves the accuracy of soil salt content mapping(R2 = 0.6396, RMSE = 0.3591), and 2) HJ-HSI data can be used to map soil salt content precisely and are suitable for monitoring soil salt content on a large scale.展开更多
Well-aggregated soil has been shown to improve soil infiltration and reduce runoff and soil erosion, making well-aggregated soil important for productive, sustainable agriculture. One factor that may influence near-su...Well-aggregated soil has been shown to improve soil infiltration and reduce runoff and soil erosion, making well-aggregated soil important for productive, sustainable agriculture. One factor that may influence near-surface soil aggregate stability is fertilizer application. Rapid dissolution of fertilizers, which are mostly salts, can potentially disperse clays and destabilize aggregates. The objective of this study was to evaluate the potential effect of various fertilizer-phosphorus (P) and -nitrogen (N) sources [i.e., triple superphosphate (TSP), monoammonium phosphate (MAP), chemically precipitated struvite (CPST), electrochemically precipitated struvite (ECST), environmentally smart nitrogen (ESN)] and soil depth on water-stable aggregates (WSA) in furrow-irrigated rice on a silt-loam soil (Typic Albaqualf). Total WSA (TWSA) concentration was unaffected (P > 0.05) by fertilizer treatment or soil depth, while WSA concentration was numerically largest (P ∙g<sup>-1</sup>), which did not differ from CPST, ECST, and ESN in the 0 - 5 cm depth or the unamended control in the 0 - 5 and 5 - 10 cm depths, and was at least 1.7 times larger than ESN in the 5 - 10 cm depth (0.03 g∙g<sup>-1</sup>). Results indicated that WSA concentration among non-struvite fertilizer-P sources was generally similar to that from the struvite fertilizer materials. Principal component analysis determined that 32% of the variation of TWSA was mainly explained by changes in soil bulk density, pH, and electrical conductivity. Long-term, continual annual application of fertilizer-P and N could negatively impact soil aggregate stability, soil structure, and potentially erosion.展开更多
为了探索由咸水灌溉引发的次生盐渍化棉田适宜的土壤盐度控制指标,试验于2012年在5个不同次生盐渍化水平的小区开展,0-60 cm深土层的初始土壤电导率（土水质量比为1∶5）分别为0.29、0.32、0.55、0.79、0.99 d S/m,分别以处理1-5表示。...为了探索由咸水灌溉引发的次生盐渍化棉田适宜的土壤盐度控制指标,试验于2012年在5个不同次生盐渍化水平的小区开展,0-60 cm深土层的初始土壤电导率（土水质量比为1∶5）分别为0.29、0.32、0.55、0.79、0.99 d S/m,分别以处理1-5表示。研究分析了盐分对棉花＂三桃＂比例、产量和纤维品质的影响,并建立了棉花价格模型,最后通过拟合分段式作物耐盐函数得出土壤盐度控制指标。结果显示,在平水年时降雨基本满足棉花需水要求,而且土壤中很大一部分盐分被降雨淋洗出0-60 cm深土层,并被控制在100 cm以下的土层中,与试验初始相比,处理1-5的最大脱盐率分别为9.6%、19.8%、36.4%、42.4%和45.7%,最终脱盐率分别为9.4%、1.8%、21.0%、24.5%和31.7%。当0-60 cm深土层初始土壤电导率低于0.79 d S/m时,没有显著降低成铃数和籽棉产量,仅会改变＂三桃＂比例,随土壤盐度进一步增高,成铃数和籽棉产量显著降低。棉花衣分率和纤维品质指标受到采摘时间和土壤盐度的共同影响,仅马克隆值在3次调查中都随着土壤盐度增加呈增大的趋势。由棉花净收益决定的土壤盐度指标低于由籽棉产量决定的土壤盐度指标,证明考虑纤维品质指标的必要性。在与处理1的净收益相比不降低的情况下,棉花播种初始和生育期平均土壤电导率应该分别控制在0.71和0.67 d S/m以下。该研究为改善次生盐渍化棉田土壤盐度控制指标的确定方法提供了理论参考。展开更多
基金supported by the International Platform for Dryland Research and Education, Tottori University and the National Key R&D Program of China (2016YFC0500909)
文摘Soil salinization is a serious ecological and environmental problem because it adversely affects sustainable development worldwide, especially in arid and semi-arid regions. It is crucial and urgent that advanced technologies are used to efficiently and accurately assess the status of salinization processes. Case studies to determine the relations between particular types of salinization and their spectral reflectances are essential because of the distinctive characteristics of the reflectance spectra of particular salts. During April 2015 we collected surface soil samples(0–10 cm depth) at 64 field sites in the downstream area of Minqin Oasis in Northwest China, an area that is undergoing serious salinization. We developed a linear model for determination of salt content in soil from hyperspectral data as follows. First, we undertook chemical analysis of the soil samples to determine their soluble salt contents. We then measured the reflectance spectra of the soil samples, which we post-processed using a continuum-removed reflectance algorithm to enhance the absorption features and better discriminate subtle differences in spectral features. We applied a normalized difference salinity index to the continuum-removed hyperspectral data to obtain all possible waveband pairs. Correlation of the indices obtained for all of the waveband pairs with the wavebands corresponding to measured soil salinities showed that two wavebands centred at wavelengths of 1358 and 2382 nm had the highest sensitivity to salinity. We then applied the linear regression modelling to the data from half of the soil samples to develop a soil salinity index for the relationships between wavebands and laboratory measured soluble salt content. We used the hyperspectral data from the remaining samples to validate the model. The salt content in soil from Minqin Oasis were well produced by the model. Our results indicate that wavelengths at 1358 and 2382 nm are the optimal wavebands for monitoring the concentrations of chlorine and sulphate compounds, the predominant salts at Minqin Oasis. Our modelling provides a reference for future case studies on the use of hyperspectral data for predictive quantitative estimation of salt content in soils in arid regions. Further research is warranted on the application of this method to remotely sensed hyperspectral data to investigate its potential use for large-scale mapping of the extent and severity of soil salinity.
基金Under the auspices of National Natural Science Foundation of China(No.41230751,41101547)Scientific Research Foundation of Graduate School of Nanjing University(No.2012CL14)
文摘Hyperspectral data are an important source for monitoring soil salt content on a large scale. However, in previous studies, barriers such as interference due to the presence of vegetation restricted the precision of mapping soil salt content. This study tested a new method for predicting soil salt content with improved precision by using Chinese hyperspectral data, Huan Jing-Hyper Spectral Imager(HJ-HSI), in the coastal area of Rudong County, Eastern China. The vegetation-covered area and coastal bare flat area were distinguished by using the normalized differential vegetation index at the band length of 705 nm(NDVI705). The soil salt content of each area was predicted by various algorithms. A Normal Soil Salt Content Response Index(NSSRI) was constructed from continuum-removed reflectance(CR-reflectance) at wavelengths of 908.95 nm and 687.41 nm to predict the soil salt content in the coastal bare flat area(NDVI705 < 0.2). The soil adjusted salinity index(SAVI) was applied to predict the soil salt content in the vegetation-covered area(NDVI705 ≥ 0.2). The results demonstrate that 1) the new method significantly improves the accuracy of soil salt content mapping(R2 = 0.6396, RMSE = 0.3591), and 2) HJ-HSI data can be used to map soil salt content precisely and are suitable for monitoring soil salt content on a large scale.
文摘Well-aggregated soil has been shown to improve soil infiltration and reduce runoff and soil erosion, making well-aggregated soil important for productive, sustainable agriculture. One factor that may influence near-surface soil aggregate stability is fertilizer application. Rapid dissolution of fertilizers, which are mostly salts, can potentially disperse clays and destabilize aggregates. The objective of this study was to evaluate the potential effect of various fertilizer-phosphorus (P) and -nitrogen (N) sources [i.e., triple superphosphate (TSP), monoammonium phosphate (MAP), chemically precipitated struvite (CPST), electrochemically precipitated struvite (ECST), environmentally smart nitrogen (ESN)] and soil depth on water-stable aggregates (WSA) in furrow-irrigated rice on a silt-loam soil (Typic Albaqualf). Total WSA (TWSA) concentration was unaffected (P > 0.05) by fertilizer treatment or soil depth, while WSA concentration was numerically largest (P ∙g<sup>-1</sup>), which did not differ from CPST, ECST, and ESN in the 0 - 5 cm depth or the unamended control in the 0 - 5 and 5 - 10 cm depths, and was at least 1.7 times larger than ESN in the 5 - 10 cm depth (0.03 g∙g<sup>-1</sup>). Results indicated that WSA concentration among non-struvite fertilizer-P sources was generally similar to that from the struvite fertilizer materials. Principal component analysis determined that 32% of the variation of TWSA was mainly explained by changes in soil bulk density, pH, and electrical conductivity. Long-term, continual annual application of fertilizer-P and N could negatively impact soil aggregate stability, soil structure, and potentially erosion.
文摘为了探索由咸水灌溉引发的次生盐渍化棉田适宜的土壤盐度控制指标,试验于2012年在5个不同次生盐渍化水平的小区开展,0-60 cm深土层的初始土壤电导率（土水质量比为1∶5）分别为0.29、0.32、0.55、0.79、0.99 d S/m,分别以处理1-5表示。研究分析了盐分对棉花＂三桃＂比例、产量和纤维品质的影响,并建立了棉花价格模型,最后通过拟合分段式作物耐盐函数得出土壤盐度控制指标。结果显示,在平水年时降雨基本满足棉花需水要求,而且土壤中很大一部分盐分被降雨淋洗出0-60 cm深土层,并被控制在100 cm以下的土层中,与试验初始相比,处理1-5的最大脱盐率分别为9.6%、19.8%、36.4%、42.4%和45.7%,最终脱盐率分别为9.4%、1.8%、21.0%、24.5%和31.7%。当0-60 cm深土层初始土壤电导率低于0.79 d S/m时,没有显著降低成铃数和籽棉产量,仅会改变＂三桃＂比例,随土壤盐度进一步增高,成铃数和籽棉产量显著降低。棉花衣分率和纤维品质指标受到采摘时间和土壤盐度的共同影响,仅马克隆值在3次调查中都随着土壤盐度增加呈增大的趋势。由棉花净收益决定的土壤盐度指标低于由籽棉产量决定的土壤盐度指标,证明考虑纤维品质指标的必要性。在与处理1的净收益相比不降低的情况下,棉花播种初始和生育期平均土壤电导率应该分别控制在0.71和0.67 d S/m以下。该研究为改善次生盐渍化棉田土壤盐度控制指标的确定方法提供了理论参考。
