Retrieving soil temperature profile by assimilating MODIS LST products with ensemble Kalman filter

Proper estimation of initial state variables and model parameters are vital importance for determining the accuracy of numerical model prediction. In this work, we develop a one-dimensional land data assimilation scheme based on ensemble Kalman filter and Common Land Model version 3.0 (CoLM). This scheme is used to improve the estimation of soil temperature profile. The leaf area index (LAI) is also updated dynamically by MODIS LAI production and the MODIS land surface temperature (LST) products are assimilated into CoLM. The scheme was tested and validated by observations from four automatic weather stations (BTS, DRS, MGS, and DGS) in Mongolian Reference Site of CEOP during the period of October 1, 2002 to September 30, 2003. Results indicate that data assimilation improves the estimation of soil temperature profile about 1 K. In comparison with simulation, the assimilation results of soil heat fluxes also have much improvement about 13 W m^− 2 at BTS and DGS and 2 W m^− 2 at DRS and MGS, respectively. In addition, assimilation of MODIS land products into land surface model is a practical and effective way to improve the estimation of land surface variables and fluxes.     

作物残体去向与利用及对土壤氮素转化的影响

近年来,作物残体还田受到了很大的关注,一方面它可以改进土壤氮素的动态变化,减少硝态氮淋失;另一方面可作为提高耕地土壤作为潜在氮储库的一种手段。作物残体是碳、氮的重要源和库,因此还田后会影响土壤中的氮素循环。本文综述了作物残体还田后对土壤氮素转化的影响及残体氮素的利用与去向问题。具体阐述了以下几个方面内容:作物残体的降解过程及影响因素,残体氮素的利用率及去向问题,以及作物残体对土壤无机氮库、有机氮库、微生物特征的影响。     

除草剂草甘膦对土壤过氧化氢酶活性的影响

研究了草甘膦对土壤过氧化氢酶活性的影响。结果表明:草甘瞵对土壤中过氧化氢酶的活性有明显的影响,随着浓度的升高,对过氧化氢酶活性抑制作用有所增强,草甘瞵对离体过氧化氢酶有一定的抑制作用。高浓度时对大棚土壤过氧化氢酶活性的抑制作用明显高于对农田土壤的抑制作用。实验结果表明:草甘瞵在农业生产实际用量下属于低毒或无实际危害的农药。     

江河源区高寒嵩草草甸土壤氨基酸成分和含量特征分析

通过高效液相色谱技术分析了青海省果洛州达日县窝赛乡原生嵩草草甸、严重退化草地及人工草地三类植被土壤中各种氨基酸成分及含量。结果表明:(1)三种类型土壤中都检测出19种常见氨基酸:精氨酸、天冬氨酸、丝氨酸、谷氨酸、苏氨酸、丙氨酸、甘氨酸、氨基丁酸、脯氨酸、蛋氨酸、缬氨酸、苯丙氨酸、异亮氨酸、亮氨酸、胱氨酸、组氨酸、鸟氨酸、赖氨酸、酪氨酸;(2)测定结果表明原生嵩草草甸土壤的氨基酸总量显著高于人工恢复重建草地和严重退化土壤氨基酸,而后两者之间差异不显著。原生高寒草地的土壤(6316.28μgg-1)严重退化草地土壤(2977.10μgg-1)人工恢复重建草地土壤(2975.90μgg-1)。(3)原生高寒草地土壤氨基酸总体呈现下降趋势:5月氨基酸含量最高,随后6月7月的显著下降,8月稍微有所回升,9月氨基酸含量到达最低;严重退化草地土壤与人工恢复重建草地土壤氨基酸含量季节变化相似,氨基酸总量在6月份到达最高点,随后7月8月显著下降,9月份稍微有所回升。     

苯磺隆和2,4-D胁迫对土壤微生物影响的研究

以盆栽试验研究了除草剂苯磺隆、2,4-D对石灰性褐土中土壤微生物群落的影响。结果表明,在供试浓度下,土壤微生物对两种除草剂的感应存在一定的差异性。苯磺隆高浓度处理在最初3d极显著地抑制细菌生长,之后对土壤细菌具有刺激作用,特别是培养结束时激活率还高达917.6%,低浓度处理呈极显著的刺激作用;苯磺隆对土壤放线菌具有显著的刺激作用,对土壤真菌有强烈的抑制作用,最高抑制率达100%,到培养结束时(60d)真菌数量还未恢复到对照水平。2,4-D处理对土壤放线菌具有明显的抑制、激活的波动性,对土壤细菌、真菌有强烈的抑制作用。     

利用植被覆盖度-地表温度特征空间提取厦门市土壤湿度信息

土壤湿度是水文学、气象学以及农业科学研究领域的一个重要参数。利用1989年和1996年两个时相Landsat TM遥感卫星影像来获取厦门的植被覆盖度和地表温度,并由此构建了植被覆盖度和地表温度组成的特征空间,最后利用该特征空间反演了土壤湿度,并分析湿度在两个时相中的变化情况。结果显示,在所研究的时间段内,厦门西南老城区的湿度得到增加。但是在东北部城市建成区扩展的地区,土壤湿度则明显降低。     

不同土壤湿度和雨强下径流曲线模型的改进

前期土壤湿度条件和降雨强度是影响径流曲线（SCS-CN）模型径流量预测精度的重要因素。分析不同流域下二者对SCS-CN模型性能的影响,对提高模型预测精度至关重要。基于5个半干旱半湿润和湿润流域的降雨径流资料,利用偏相关分析和K-均值聚类改进SCS-CN模型。结果表明：在重新划分前期土壤湿度条件区间后,模型预测能力大幅度提升,有效降低模型平均偏差,纳什效率系数平均提高42.8%。基于最大10 min雨强对SCS-CN模型改进后,纳什效率系数得到一定提高,且半干旱半湿润流域的提升幅度略大于湿润流域。改进的模型在研究流域都取得较好的效果,平均偏差均低于7 mm;除呈村流域非汛期外纳什效率系数均达到0.93,平均提升89%;均方根误差平均降低29.2 mm。     

Soil moisture estimation over vegetated terrains using multitemporal remote sensing data

A new method for retrieving soil moisture content over vegetated fields, employing multitemporal radar and optical images, is presented. It is based on the integration of the temporal series of radar data within an inversion scheme and on the correction of the vegetation effects. The retrieval algorithm uses the Bayesian maximum posterior probability and assumes the existence of a relation among the soil conditions at the different times of the series. The correction of the vegetation effects models the variation, with respect to the initial time of the series, of the component of the backscattering coefficient due to the soil characteristics as function of the variations of the measured backscattering coefficient and of the biomass. The method is tested on the data acquired throughout the SMEX02 experiment. The results show that measured and estimated soil moistures are fairly well correlated and that the performances of multitemporal retrieval algorithm are better than those obtained by employing one radar acquisition, especially in terms of capability to detect soil moisture changes. Although the approach to correct the vegetation effects on radar observations needs to be further assessed on different sets of data, this finding demonstrates that the proposed method has a potential to improve the quality of the soil moisture retrievals.     

An improved algorithm for disaggregating microwave-derived soil moisture based on red, near-infrared and thermal-infrared data

Accurate high-resolution soil moisture data are needed for a range of agricultural and hydrologic activities. To improve the spatial resolution of ∼ 40 km resolution passive microwave-derived soil moisture, a methodology based on 1 km resolution MODIS (MODerate resolution Imaging Spectroradiometer) red, near-infrared and thermal-infrared data has been implemented at 4 km resolution. The three components of that method are (i) fractional vegetation cover, (ii) soil evaporative efficiency (defined as the ratio of actual to potential evaporation) and (iii) a downscaling relationship. In this paper, 36 different disaggregation algorithms are built from 3 fractional vegetation cover formulations, 3 soil evaporative efficiency models, and 4 downscaling relationships. All algorithms differ with regard to the representation of the nonlinear relationship between microwave-derived soil moisture and optical-derived soil evaporative efficiency. Airborne L-band data collected over an Australian agricultural area are used to both generate ∼ 40 km resolution microwave pixels and verify disaggregation results at 4 km resolution. Among the 36 disaggregation algorithms, one is identified as being more robust (insensitive to soil, vegetation and atmospheric variables) than the others with a mean slope between MODIS-disaggregated and L-band derived soil moisture of 0.94. The robustness of that algorithm is notably assessed by comparing the disaggregation results obtained using composited (averaged) Terra and Aqua MODIS data, and using data from Terra and Aqua separately. The error on disaggregated soil moisture is systematically reduced by compositing daily Terra and Aqua data with an error of 0.012 vol./vol.     

Effects of soil composition and mineralogy on remote sensing of crop residue cover

The management of crop residues (non-photosynthetic vegetation) in agricultural fields influences soil erosion and soil carbon sequestration. Remote sensing methods can efficiently assess crop residue cover and related tillage intensity over many fields in a region. Although the reflectance spectra of soils and crop residues are often similar in the visible, near infrared, and the lower part of the shortwave infrared (400-1900 nm) wavelength region, specific diagnostic chemical absorption features are evident in the upper shortwave infrared (1900-2500 nm) region. Two reflectance band height indices used for estimating residue cover are the Cellulose Absorption Index (CAI) and the Lignin-Cellulose Absorption (LCA) index, both of which use reflectances in the upper shortwave infrared (SWIR). Soil mineralogy and composition will affect soil spectral properties and may limit the usefulness of these spectral indices in certain areas. Our objectives were to (1) identify minerals and soil components with absorption features in the 2000 nm to 2400 nm wavelength region that would affect CAI and LCA and (2) assess their potential impact on remote sensing estimates of crop residue cover. Most common soil minerals had CAI values ≤ 0.5, whereas crop residues were always > 0.5, allowing for good contrast between soils and residues. However, a number of common soil minerals had LCA values > 0.5, and, in some cases, the mineral LCA values were greater than those of the crop residues, which could limit the effectiveness of LCA for residue cover estimation. The LCA of some dry residues and live corn canopies were similar in value, unlike CAI. Thus, the Normalized Difference Vegetation Index (NDVI) or similar method should be used to separate out green vegetation pixels. Mineral groups, such as garnets and chlorites, often have wide ranges of CAI and LCA values, and thus, mineralogical analyses often do not identify individual mineral species required for precise CAI estimation. However, these methods are still useful for identifying mineral soils requiring additional scrutiny. Future advanced multi- and hyperspectral remote sensing platforms should include CAI bands to allow for crop residue cover estimation.