关键词：
Dispersion coefficient;Turbulent flow;Eddy dispersion;Taylor diffusion;Capillary bundle model
摘要：
PurposeFor a homogeneous soil, the traditional laminar flow and well-known Taylor diffusion mechanism cannot interpret dispersivity (linear relationship between dispersion coefficient and pore-water velocity). The objective of this study was to propose a new mechanism and mathematical model based on fluid mechanics.MethodsDue to the roughness of the wall of a soil capillary tube, a new turbulent flow is proposed to be eddies at the wall and laminar flow at the main stream of a soil capillary tube. A new eddy dispersion mechanism is that the behavior of solute in the eddies follows random walks and the solute mixes instantly between the wall and main stream in a tube at the microscale. The new turbulent flow and eddy dispersion occur when the pore-water velocity is greater than a critical value. Transition to the new mechanism from a laminar flow in the tube and molecular diffusion is described by a plateau-linear model. It was tested by published datasets of pore-water velocity and dispersion coefficient in miscible displacement experiments on a loam and a sandy loam.ResultsThe plateau-linear model fit the published datasets. The estimate of dispersivity was 0.135 cm. The transition of water flow and dispersion process occurred at the critical pore-water velocity 0.216 cm h-1 or Reynolds number of the order of 10-6.ConclusionDispersivity in homogeneous soils was interpretated by the turbulent water flow and the eddy dispersion mechanism. It is determined by the structure of rough wall in a soil capillary tube at the miscroscale.
期刊：
GEOPHYSICAL RESEARCH LETTERS,2024年51(4) ISSN：0094-8276
通讯作者：
Yin, GF
作者机构：
[Wang, Cong] Cent China Normal Univ, Sch Urban & Environm Sci, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan, Peoples R China.;[Yin, Gaofei; Yin, GF; Yang, Yajie] Southwest Jiaotong Univ, Fac Geosci & Environm Engn, Chengdu, Peoples R China.;[Xie, Qiaoyun] Univ Western Australia, Sch Engn, Perth, WA, Australia.;[Xu, Baodong] Huazhong Agr Univ, Macro Agr Res Inst, Coll Resource & Environm, Wuhan, Peoples R China.;[Verger, Aleixandre] CSIC UV GV, CIDE, Valencia, Spain.
通讯机构：
[Yin, GF ] S;Southwest Jiaotong Univ, Fac Geosci & Environm Engn, Chengdu, Peoples R China.
摘要：
Abstract Remote sensing detection of autumn phenology is challenging and highly uncertain, as exemplified by the observed divergence in autumn phenology extracted from different proxies. Here, we compared the autumn phenology derived from Solar‐Induced chlorophyll Fluorescence (SIF), Chlorophyll/Carotenoid Index (CCI), Enhanced Vegetation Index (EVI), and Normalized Difference Vegetation Index (NDVI) over deciduous forest sites. We observed a clear temporal sequence in the derived autumn phenology from various proxies: SIF < CCI < EVI < NDVI. Comparison with field measurements supported that SIF, EVI, and NDVI can successfully capture the attenuation of photosynthetic activity, leaf coloration, and leaf fall, respectively. The sequence among the autumn phenology derived from those proxies was also consistent with their responses to climate cues, where SIF had the highest partial correlation coefficient to solar radiation in autumn, followed by CCI, EVI, and NDVI, while NDVI was more correlated with temperature, followed by EVI, CCI, and SIF.
期刊：
Science of The Total Environment,2024年921:171167 ISSN：0048-9697
通讯作者：
Fang, J
作者机构：
[Fang, Jian; Liu, Yuxin; Xu, Yating; Fang, J] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.;[Fang, Jian; Liu, Yuxin; Xu, Yating] Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan 430079, Peoples R China.;[Tao, Kai] Beijing Normal Univ, Fac Geog Sci, Beijing 100875, Peoples R China.;[Fang, Jiayi] Hangzhou Normal Univ, Inst Remote Sensing & Earth Sci, Sch Informat Sci & Technol, Hangzhou 311121, Peoples R China.
通讯机构：
[Fang, J ] C;Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.
关键词：
Flood seasonality;Spatial-temporal variation;Synchronous flood;Yangtze River basin
摘要：
Floods are some of the most frequent and severe natural hazards worldwide. In the context of climate change, the risk of extreme floods is expected to increase in the future. While, the trends in flood timing and risk for flood synchronization remain unclear. In this study, the seasonality of flood peaks, annual maximum rainfall, and annual maximum soil moisture in the Yangtze River Basin were examined using observational and reanalysis data from 1949 to 2020. Changes in the timing of extreme events may increase the possibility of concurrent flooding, therefore the risk for synchronous floods were further explored. The results indicate that the seasonality of floods has a strong consistency with that of annual maximum rainfall. In the southern Yangtze River Basin, floods usually occur between early June and early July, with a delayed trend. However, they occur slightly later in the north, generally from late July to early August, with a tendency of advance. Overall, the timing of floods is positively correlated with rainfall and soil moisture peaks, and the correlation is much stronger for annual maximum rainfall. However, for more intense floods or for larger catchments, soil moisture plays an important role in modulating the variations in flood timing. Reverse latitudinal changes in flood timing are expected to result in more synchronous floods. The synchrony frequency exceeded 60 % for most of the stations, and the frequency was increasing for nearly half of the region, especially in the middle reaches, Poyang Lake and south of Dongting Lake. In addition, the flood synchrony scale in the south of the basin showed significant upward trends. These findings would provide important implications for flood risk management and adaptive strategy development.
摘要：
The global trend of vegetation "greening" in the context of ecological restoration necessitates an urgent assessment of ecosystem services. As essential components of ecosystem services, the hydraulic functions of soil in infiltrating and retaining water following vegetation restoration remain unclear, especially in subtropical mountainous and hilly areas with complex topographies. From 2018 to 2021, soil moisture data collected at five-minute intervals were monitored for three restoration strategies in a hilly catchment of China's Three Gorges Reservoir area. The restoration strategies included planted forest (PF) and natural restoration (naturally regenerated forest, NF; deforested pasture, DP). The soil moisture response to rainfall under these strategies was evaluated using several metrics, including the time difference between peak rainfall intensity and peak soil moisture response (T-p2p), cumulative infiltration, and occurrence frequency of preferential flow (PRF). The results showed that the average soil moisture content (SMC) of PF was significantly (p < 0.05) lower than that of NF and DP in both dry and wet seasons, regardless of upslope or downslope location. However, the topographic position affected the difference in average SMC between DP and NF. At the downslope location, the average SMC of DP (0.39 cm(3) cm(-3)) was significantly higher than that of NF (0.33 cm(3) cm(-3)). Conversely, at the upslope location, the average SMC of DP (0.27 cm(3) cm(-3)) was lower than that of NF (0.30 cm(3) cm(-3)). These findings suggested that PF had a lower amount of soil water storage than NF and DP, which was supported by the lowest cumulative infiltration in PF during storm events. The response of soil moisture to storms in PF (T-p2p = 3.1 h) was slower than that in NF (T-p2p = 1.9 h) and DP (T-p2p = 2.5 h). This was consistent with the lower occurrence frequency of preferential flow in PF (PRF = 19.2 %) than NF (PRF = 39.2 %) and DP (PRF = 32.9 %). Therefore, longer response time and less preferential flow indicated that the PF had a relatively poor soil moisture responsiveness to storm events. Accordingly, this study highlights the insufficiency of afforestation in soil water infiltration and retention compared to natural restoration, meriting consideration when assessing soil hydraulic functions in vegetation restoration areas.
摘要：
Although snow cover is a major factor affecting vegetation in alpine regions, it is rarely introduced into ecological niche models in alpine regions. Snow phenology over the Tibetan Plateau (TP) was estimated using a daily passive microwave snow depth dataset, and future datasets of snow depth and snow phenology were projected based on their sensitivity to temperature and precipitation. Furthermore, the potential habitats of five alpine vegetation types on the TP were predicted under two future climate scenarios (SSP245 and SSP585) by using a model with incorporated snow variables, and the driving factors of habitat change were analyzed. The results showed that the inclusion of snow variables improved the prediction accuracy of MaxEnt model, particularly in alpine meadow habitats. By the end of the 21st century, the potential habitats of steppes, meadows, shrubs, deserts, and coniferous forests on the TP will migrate to higher latitudes and altitudes, in which the potential habitats of alpine desert will recede (replaced by alpine steppe), and the potential habitats of other four vegetation types will expand. The random forest importance analysis showed that the recession of potential habitat was mainly driven by the increase in average annual temperature, and the expansion of potential habitat was mainly driven by the increase in precipitation. With the gradual increase in temperature and precipitation in the future, the snow depth and snow cover duration days will decrease, which may further lead to the transition of vegetation types from cold-adapted to warm-adapted on the TP. Our study highlights both that the prediction accuracy of alpine vegetation was improved by incorporating snow variables into the species distribution model, and that a changing climate will likely have a powerful influence on the distribution of alpine vegetation across the TP.
作者机构：
The Research Center of Soil and Water Conservation and Ecological Environment, Chinese Academy of Sciences and Ministry of Education, Yangling, China;State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation CAS and MWR, Yangling, China;University of Chinese Academy of Sciences, Beijing, China;[Yan Li; Chunyan Wu] Institute of Environment Resource and Soil Fertilizer, Zhejiang Academy of Agricultural Sciences, Hangzhou, China;[Tianyi Qiu; Haoran He] College of Natural Resources and Environment, Northwest A&F University, Yangling, China
通讯机构：
[Linchuan Fang] T;The Research Center of Soil and Water Conservation and Ecological Environment, Chinese Academy of Sciences and Ministry of Education, Yangling, China<&wdkj&>State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation CAS and MWR, Yangling, China<&wdkj&>CAS Center for Excellence in Quaternary Science and Global Change, Xi’an, China
摘要：
• N fertilizer altered bacterial community compositions by changing soil nutrients. • Bacterial ammonia oxidation became predominated with the increasing N rate. • Excessive N input caused the information of a more complex microbial network. • Intensified microbial competition by excessive N was due to negative link increase. Nitrogen (N) fertilization drives the structure and function of soil microbial communities, which are crucial for regulating soil biogeochemical cycling and maintaining ecosystem stability. Despite the N fertilizer effects on soil microbial composition and diversity have been widely investigated, it is generally overlooked that ecosystem processes are carried out via complex associations among microbiome members. Here, we examined the effects of five N fertilization levels (0, 135, 180, 225, and 360 kg N ha−1) on microbial co-occurrence networks and key functional taxa such as ammonia-oxidizers in paddy soils. The results showed that N addition altered microbial community composition, which were positively related to soil total N and available phosphorus (P) contents. The abundance of ammonia-oxidizing archaea (AOA) significantly decreased after N addition, whereas ammonia-oxidizing bacteria (AOB) increased in N360 treatment. Compared with low-N group (N0 and N135), the high-N group (N225 and N360) shaped more complex microbial webs and thus improved the stability of the microbial community. Partial least squares path modeling further revealed that N fertilizer had a higher effect on microbial network complexity in the high-N group (0.83) than the low-N group (0.49). Although there were more positive links across all microbial networks, the proportion of negative links significantly increased in the high-N network, suggesting that excess N addition aggravated the competition among microbial species. Disentangling these interactions between microbial communities and N fertilization advances our understanding of biogeochemical processes in paddy soils and their effects on nutrient supply to rice production. Our findings highlighted that highly N-enriched paddy soils have more stable microbial networks and can better sustain soil ecological functions to cope with the ongoing environmental changes.
摘要：
Located in the northwestern edge of the modern Asian summer monsoon (ASM), the northeastern Tibetan Plateau (NETP) is sensitive to changes of the ASM climate. However, variations of climate and vegetation during the Holocene remain unclear in this marginal region of the monsoon climate. Here we present a Holocene highresolution pollen record from Lake Gahai in the NETP since 11.4 (+/- 0.3) ka BP to reconstruct regional vegetation history. A quantitative reconstruction of precipitation is also tried using fossil pollen assemblages. Results suggested that before 10.2 (+/- 0.4) ka BP in the early Holocene, the vegetation cover was low and the climate was arid. A relatively wet climate indicated by high A/C ratio values occurred between 10.2 (+/- 0.4) and 7.4 (+/- 0.2) ka BP. After 7.4 (+/- 0.2) ka BP, the A/C ratio decreased, indicating that the climate was getting drier. The overall environment of the basin has become similar to modern conditions since 5.4 (+/- 0.1) ka BP. The reconstructed precipitation is not comparable with the tree-ring-based reconstruction from the Delingha region, although the reconstruction processes passed significance tests statistically. In addition to abundant surface pollen data and gradually improved quantitative reconstruction techniques, other factors such as the environmental settings and vegetation dynamics also affect the reliability of the pollen-based quantitative reconstruction of regional precipitation. Therefore, the applicability of pollen data for quantitative precipitation reconstruction in arid regions should be assessed and the results should be treated cautiously.
期刊：
Global Change Biology,2024年30(1):e17027- ISSN：1354-1013
通讯作者：
Fang, LC
作者机构：
[Fang, Linchuan; Ma, Dengke; Jin, Xiaolian; Fang, LC; Ju, Wenliang; Guo, Liang] Chinese Acad Sci, Inst Soil & Water Conservat, State Key Lab Soil Eros & Dryland Farming Loess Pl, Minist Water Resources, Yangling 712100, Peoples R China.;[Ju, Wenliang] Tsinghua Univ, Sch Environm, Beijing, Peoples R China.;[Fang, Linchuan] Wuhan Univ Technol, Key Lab Green Utilizat Crit Nonmet Mineral Resourc, Minist Educ, Wuhan, Peoples R China.;[Shen, Guoting; Blagodatskaya, Evgenia] UFZ Helmholtz Ctr Environm Res, Dept Soil Ecol, Halle, Saale, Germany.;[Delgado-Baquerizo, Manuel; Zhou, Guiyao] Inst Recursos Nat & Agrobiol Sevilla IRNAS, Lab Biodivers & Funcionamiento Ecosistem, CSIC, Seville, Spain.
通讯机构：
[Fang, LC ] C;Chinese Acad Sci, Inst Soil & Water Conservat, State Key Lab Soil Eros & Dryland Farming Loess Pl, Minist Water Resources, Yangling 712100, Peoples R China.
关键词：
carbon sequestration;grasslands;grazing exclusion;microbial communities and functions;nitrogen and phosphorus accumulation;soil aggregates
摘要：
We linked the soil microscale‐associated microbiomes with the carbon sequestration and biogeochemical cycling of livestock excluded grasslands for up to 36 years. Long‐term grazing exclusion reduced microbial diversity, community stability, and microbial functional genes associated with carbon sequestration and nutrient cycling. Moreover, we emphasize that the interaction between grazing exclusion and longevity as well as the structure of soil aggregates have substantial impacts the grassland biogeochemical cycles and global climate change in which the soil microbiome is involved. Abstract Grazing exclusion alters grassland soil aggregation, microbiome composition, and biogeochemical processes. However, the long‐term effects of grazing exclusion on the microbial communities and nutrient dynamics within soil aggregates remain unclear. We conducted a 36‐year exclusion experiment to investigate how grazing exclusion affects the soil microbial community and the associated soil functions within soil aggregates in a semiarid grassland. Long‐term (36 years) grazing exclusion induced a shift in microbial communities, especially in the <2 mm aggregates, from high to low diversity compared to the grazing control. The reduced microbial diversity was accompanied by instability of fungal communities, extended distribution of fungal pathogens to >2 mm aggregates, and reduced carbon (C) sequestration potential thus revealing a negative impact of long‐term GE. In contrast, 11–26 years of grazing exclusion greatly increased C sequestration and promoted nutrient cycling in soil aggregates and associated microbial functional genes. Moreover, the environmental characteristics of microhabitats (e.g., soil pH) altered the soil microbiome and strongly contributed to C sequestration. Our findings reveal new evidence from soil microbiology for optimizing grazing exclusion duration to maintain multiple belowground ecosystem functions, providing promising suggestions for climate‐smart and resource‐efficient grasslands.
摘要：
Over the past decade, China has experienced a decline in atmospheric reactive nitrogen (Nr) emissions. Given that China's subtropical region is a significant nitrogen (N) deposition hotspot, it is essential to accurately quantify the ten-year variations in dry and wet N depositions in the context of reductions in atmospheric Nr emissions. Here, we evaluated the spatiotemporal variation in N deposition on forest, paddy field and tea field ecosystems in a typical subtropical agricultural catchment from 2011 to 2020. Our findings indicated a significant decrease in total N deposition in both the tea field ecosystem (41.5-30.5kgNha(-1)) and the forest ecosystem (40.8-25.7kgNha(-1)) (P<0.05), but no significant change in the paddy field ecosystem (29.3-32.9kgNha(-1)). Specifically, dry N deposition exhibited significant declines except in the paddy field ecosystem, whereas wet N deposition had no significant change. The reduction in total oxidized and reduced N depositions in forest and tea field ecosystems is attributed to the decrease in NO(x) and NH(3) emissions. Additionally, The ratio of NH(x) deposition to total N deposition all exceeded 0.5 in three ecosystems and the NH(x)/NO(y) ratio had an increasing trend (P<0.05) in the paddy field, indicating that reactive N emissions from agricultural sources were the primary contributor to overall N deposition. Our study emphasizes that despite the decreasing trend in N deposition, it still exceeds the critical loads of natural ecosystems and requires stringent N emissions control, particularly from agricultural sources, in the future.
通讯机构：
[Xu, BD ] H;Huazhong Agr Univ, Macro Agr Res Inst, Coll Resources & Environm, Wuhan 430070, Peoples R China.
关键词：
MODIS;Reflectivity;Vegetation mapping;Land surface;Remote sensing;Indexes;Spatial resolution;Leaf area index (LAI);Moderate Resolution Imaging Spectroradiometer (MODIS);multiscale data;spatial heterogeneity;subpixel information
摘要：
High-frequency leaf area index (LAI) dataset is essential for vegetation dynamic monitoring and crop yield estimation; however, due to the negative impacts of land surface heterogeneity, current hectometric-resolution LAI products cannot satisfy the uncertainty requirement of LAI dataset in practice. Here, we proposed a method named "use of subpixel information" (USPI) that leverages fine-scale remote sensing data to improve the accuracy of hectometric-resolution LAI retrieval. Specifically, based on machine learning (ML) models trained by representative samples, we retrieved the USPI LAI from Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance by incorporating the subpixel information from Sentinel-2 LAI estimates. The USPI LAI was comprehensively evaluated using 30-m LAI reference maps in three aspects: the performance of different ML models, the comparison with MODIS LAI products, and the potential correction of USPI LAI for clumping effect. Results showed that the Gaussian process regression (GPR) model outperformed other ML models for deriving LAI estimates; furthermore, USPI LAI exhibited better performance than MODIS LAI product, with bias, root mean square error (RMSE), and $R<^>{2}$ of -0.308, 0.593, and 0.826, respectively, especially for pixels contaminated by atmospheric conditions. The underestimation of USPI LAI should be, nevertheless, noted because the effective LAI provided by Sentinel-2 was involved in the GPR training process; thus, it is necessary to introduce the accurate clumping index (CI) dataset for further improvement of USPI LAI retrievals. Our study indicates that incorporating the subpixel information from decametric-resolution data can effectively reduce the uncertainty of hectometric-resolution LAI retrieval, which is promising for generating the high-accuracy LAI time series dataset.
作者机构：
[Liu, Wenbin; Li, Shu] MWR, Changjiang Inst Survey Tech Res, Wuhan 430011, Hubei, Peoples R China.;[Yin, Guoying; Liu, Xiangyu; Xia, Yu; Liu, Wenbin] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & Re, Wuhan 430072, Hubei, Peoples R China.;[Tao, Jianbin] Cent China Normal Univ, Sch Urban & Environm Sci, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan 430079, Hubei, Peoples R China.;[Wang, Ting] Hubei Res Inst Spatial Planning, Wuhan 430064, Hubei, Peoples R China.;[Zhang, Hongyan; Zhang, HY] China Univ Geosci, Sch Comp Sci, Wuhan 430074, Hubei, Peoples R China.
通讯机构：
[Zhang, HY ] C;China Univ Geosci, Sch Comp Sci, Wuhan 430074, Hubei, Peoples R China.
摘要：
Rapeseed is a critical cash crop globally, and understanding its distribution can assist in refined agricultural management, ensuring a sustainable vegetable oil supply, and informing government decisions. China is the leading consumer and third-largest producer of rapeseed. However, there is a lack of widely available, long-term, and large-scale remotely sensed maps on rapeseed cultivation in China. Here this study utilizes multi-source data such as satellite images, GLDAS environmental variables, land cover maps, and terrain data to create the China annual rapeseed maps at 30 m spatial resolution from 2000 to 2022 (CARM30). Our product was validated using independent samples and showed average F1 scores of 0.869 and 0.971 for winter and spring rapeseed. The CARM30 has high spatial consistency with existing 10 m and 20 m rapeseed maps. Additionally, the CARM30-derived rapeseed planted area was significantly correlated with agricultural statistics (R(2) = 0.65-0.86; p < 0.001). The obtained rapeseed distribution information can serve as a reference for stakeholders such as farmers, scientific communities, and decision-makers.
摘要：
Approximately 1 billion people worldwide currently inhabit slum areas. The UN Sustainable Development Goal (SDG 11.1) underscores the imperative of upgrading all slums by 2030 to ensure adequate housing for everyone. Geo-locations of slums help local governments with upgrading slums and alleviating urban poverty. Remote sensing (RS) technology, with its excellent Earth observation capabilities, can play an important role in slum mapping. Deep learning (DL)-based RS information extraction methods have attracted a lot of attention. Currently, DL-based slum mapping studies typically uses three optical bands to adapt to existing models, neglecting essential geo-scientific information, such as spectral and textural characteristics, which are beneficial for slum mapping. Inspired by the geoscience-aware DL paradigm, we propose the Geoscience-Aware Network for slum mapping (GASlumNet), aiming to improve slum mapping accuracies via incorporating the DL model with geoscientific prior knowledge. GASlumNet employs a two-stream architecture, combining ConvNeXt and UNet. One stream concentrates on optical feature representation, while the other emphasizes geo-scientific features. Further, the feature-level and decision-level fusion mechanisms are applied to optimize deep features and enhance model performance. We used Jilin-1 Spectrum 01 and Sentinel-2 images to perform experiments in Mumbai, India. The results demonstrate that GASlumNet achieves higher slum mapping accuracy than the comparison models, with an intersection over union (IoU) of 58.41%. Specifically, GASlumNet improves the IoU by 4.60 similar to 5.97% over the baseline models, i.e., UNet and ConvNeXt-UNet, which exclusively utilize optical bands. Furthermore, GASlumNet enhances the IoU by 10.97% compared to FuseNet, a model that combines optical bands and geo-scientific features. Our method presents a new technical solution to achieve accurate slum mapping, offering potential benefits for regional and global slum mapping and upgrading initiatives.
关键词：
biochar;coastal saline soils;polyacrylamide;soil microstructure;water and salt transport
摘要：
Increasing scientific knowledge on the improvement of coastal saline soils is critical for spatially expanding coastal development. Biochar and polyacrylamide (PAM) are popular soil amendments, however, it remains unclear how they affect water and salt transport by regulating soil microstructure characteristics. In this study, we conducted a five-year rice barrel trial and investigated the changes in the aggregates and microstructure of saline soils after adding biochar with three different application rates (B1 = 0%, B2 = 2%, and B3 = 5%, mass ratio) and PAM with three different application rates (P1 = 0%, P2 = 0.4 parts per thousand, and P3 = 1.0 parts per thousand, mass ratio), and simulated the water and salt transport. Results showed that at B1 and B2 treatments, soil mu-CT porosity in 2020 increased by 89.8% and 208.0%, respectively, with respect to that in 2016. The development of soil mesopore structure was promoted at B2 treatments, whereas the P2 and P3 treatments promoted the development of the soil macrostructure. Compared with those of the blank control, soil internal mean water flow rate increased by 22.2% at B2 treatments and 69.2% at P2 treatments, respectively. However, their increases were less pronounced at B3 treatments and the water flow rate decreased by 50.5% at P3 treatments. It might be reasonably attributed to the reason that porous biochar helped the formation of soil pore structure while an excessive amount of biochar blocked soil pores. Furthermore, PAM amendment helped to form soil aggregates while an excessive amount of viscous PAM might block soil pores or form a viscous layer. The time corresponding to the maximum salt concentration was negatively correlated with soil mu-CT porosity (R2 = 0.27) and pore connectivity density (R2 = 0.29). Our findings indicate that appropriate amounts of biochar and PAM can help improve saline soil structure in coastal areas, improve their hydraulic properties, and alleviate salt stress.
摘要：
Crop lodging detrimentally affects crop yield and mechanical harvest efficiency. Traditional remote sensingbased methods primarily focus on the identification and area extraction of lodging using image texture and spectrum. However, the response of image texture and spectrum to lodging is indirect and varies under diverse conditions. Moreover, other important finer details of lodging phenotyping, such as lodging angle and lodging type, have frequently been neglected. In this study, a robust and accurate method was developed for investigating lodging phenotypes in the field. The method was based on the three-dimensional morphological information of rapeseed (Brassica napus L.) canopy reconstructed from unmanned aerial vehicle (UAV) images. In contrast to traditional remote sensing methods that only identify lodging targets and their respective areas, the novel method in this study calculated the total lodging angle (TLA), root lodging angle (RLA), stem lodging angle (SLA = TLA - RLA), and lodging types according to a morphological method and a lodging classification model. Initially, the method employed a geometric model to characterize the stalk shape of lodged rapeseed. After assessing numerous lodging samples from individual rapeseed plants, the circle function was identified as the optimal geometric model. With this optimal function, the canopy height derived from the UAV images was found effective in calculating TLA, RLA, and SLA across 24 rapeseed cultivars in five climatic zones within the Yangtze River Basin (YRB) in China. Results showed that the average root mean square error (RMSE) was 8.3 degrees for TLA and 7.4 degrees for RLA. Subsequently, based on field measured data of SLA and RLA, a decision tree model was constructed to classify lodging types and an accuracy of 95.4% was achieved. Using the classification model and estimated values of RLA and SLA, the spatial distribution information and specific area estimates for different lodging types were obtained. Based on the analysis of these results, the rapeseed cultivars Zhongshuang 11 and Dadi 199 were determined to be the dominant cultivars with lodging resistance in the YRB, even though they did not achieve the mean high yields in multiple climatic zones. However, the lodging -prone cultivars such as Qinyou7 and Qinyou33 fell under the low -yield level in all climatic zones. The robust and cost-effective method proposed in this study for acquiring detailed crop lodging phenotyping data has the potential to enhance mechanized harvesting, accurately estimate the risk of low yield, and assess the lodging status of various crops.
