Saline-alkali land in the Yellow River Delta: amelioration zonation based on GIS

Soil salinization is one of the major land degradation types and has greatly influenced sustainable agricultural development. Zonation of saline-alkali land is the precondition for effective amelioration. The present situation of saline-alkali land is monitored by remote sensing image processing. Causes for land salinization are analyzed, especially the two key factors, ground water depth and its mineralization degree, are analyzed by using long-term observation data. Previously, zonation of saline-alkali soil was made descriptively and artificially. Based on the present situation of saline-alkali land, ground water depth and ground water mineralization degree, the zonation of saline-alkali land for amelioration in the Yellow River Delta was completed quantitatively. Four different types of saline-alkali land amelioration zones are delineated, namely, easy ameliorated zone, relatively difficult ameliorated zone, difficult ameliorated zone and unfavorable ameliorated zone. Countermeasures for ameliorating saline-alkali soils are put forward according to ecological conditions of different saline-alkali land zones.

Information Extraction Method of Soil Salinity in Typical Areas of the Yellow River Delta Based on Landsat Imagery

In order to get RS method to extract soil salinity of the Yellow River Delta, we set Kenli County as typical Yellow River Delta to be research area and get data of soil salinity through field investigation. By using RS image of Landsat-8 of March 14, 2014 and analyzing information features of each band and surface spectral features of research areas, we select out sensitive bands and build Soil Salinity Information Extraction (SSIE) model and vegetation index NDVI model for comparison. And then, we accordingly classify grades of soil salinity and get soil salinity information by decision tree approach based on expert knowledge. The results show that overall accuracy of SSIE model is 93.04% and coefficient of Kappa is 0.7869, while overall accuracy of NDVI model is 83.67% and coefficient of Kappa is 0.7017 respectively. By comparing with measured proportions of each class, we see that results from SSIE model is more accurate, which indicates significant advantage for soil salinity information extraction. This research provides scientific basis to get and monitoring soil salinity of the Yellow River Delta region quickly and accurately.

Impacts of multi-scenario land use change on ecosystem services and ecological security pattern: A case study of the Yellow River Delta

The Yellow River Delta(YRD), a critical economic zone along China's eastern coast, also functions as a vital ecological reserve in the lower Yellow River. Amidst rapid industrialization and urbanization, the region has witnessed significant land use/cover changes(LUCC), impacting ecosystem services(ES) and ecological security patterns(ESP). Investigating LUCC's effects on ES and ESP in the YRD is crucial for ecological security and sustainable development. This study utilized the PLUS model to simulate 2030 land use scenarios, including natural development(NDS), economic development(EDS), and ecological protection scenarios(EPS). Subsequently, the InVEST model and circuit theory were applied to assess ES and ESP under varying LUCC scenarios from 2010 to 2030. Findings indicate:(1) Notable LUCC from 2010 to 2030, marked by decreasing cropland and increasing construction land and water bodies.(2) From 2010 to 2020, improvements were observed in carbon storage,water yield, soil retention, and habitat quality, whereas 2020–2030 saw increases in water yield and soil retention but declines in habitat quality and carbon storage. Among the scenarios, EPS showed superior performance in all four ES.(3) Between 2010 and 2030, ecological sources, corridors, and pinchpoints expanded, displaying significant spatial heterogeneity. The EPS scenario yielded the most substantial increases in ecological sources,corridors, and pinchpoints, totaling 582.89 km^(2), 645.03 km^(2),and 64.43 km^(2), respectively. This study highlights the importance of EPS, offering insightful scientific guidance for the YRD's sustainable development.

Project of “Three Networks Greening” based on optimal allocation in the Yellow River Delta,China (Dongying section)

We have used the Yellow River Delta （Dongying section） as our study area to address the project of ＂Three Networks Greening＂ （TNG）. With the use of GIS technology and from an ecological point of view, an optimal allocation scheme of land resources is constructed and applied to guide the adjustment of land resources. Given this scheme, we have calculated that the area of land suitable for forest and shrubs without greening is 2256 km^2. Simultaneously, acting on the layout of the TNG project, afforestation site types are prepared and improved. Soil types, microrelief, salinity and underwater levels are combined as major classification factors and irrigation conditions as a reference to classify sites into eight types. In this way, land suitable for forest and grass is afforested given particular planting patterns. Finally, by overlaying this forestry site type map with the TNG plan map, some suggestions and strategies are proposed and used to direct the TNG project. An ecological oasis of the Yellow River Delta should be the result.

Factors Influencing the Thermal Conductivity of Silt in the Yellow River Delta

The thermal conductivity of marine sediments is an important thermophysical parameter in the study of seafloor heat flow and marine engineering construction.Understanding the effect of thermal conductivity of marine sediments in the environment has a major engineering value and theoretical significance.In this work,a modified test method was used to measure the thermal conductivity of silt in the Yellow River Delta under different void ratios,moisture contents,temperatures,and salinities.Results showed that the thermal conductivity of silt in the Yellow River Delta decreased with the increase in the void ratio and increased with the water content.Compared with sand and clay,silt in the Yellow River Delta was the least affected by the void ratio and moisture content.Under low temperatures,the heat transfer of soil was controlled by the average velocity of the phonons;therefore,the thermal conductivity of silt in the Yellow River Estuary increased with temperature.The thermal conductivity of pore water decreased with increasing salinity.Moreover,certain salinity levels resulted in a phenomenon known as the‘compressing twin electrical layer’,which led to an increase in the contact area between soil particles.With the increase in salinity,the thermal conductivity of silt in the Yellow River Delta experiences an initial decline and a subsequent increase.The proposed thermal conductivity test method is more accurate than the existing technique,and the findings provide a basis for further study on the thermal characteristics of submarine sediments.

Study on Land Use Changes in the Yellow River Delta from 1980 to 2010

Taking the Yellow River Delta for example, this paper applied remote sensing and GIS to explore land use changes in the local area from 1980 to 2010. The results showed that arable land, and urban and rural construction land were major land use types in the Yellow River Delta, unused land also took a large ratio; land use changes occurred mainly in coastal regions, in terms of change matrix, 25.46% of the grassland was reclaimed as arable land, unused land also witnessed great changes, specifi cally, 11.14% turned to arable land, 23.25% to construction land. This study provided references for the land use planning and development of the local area.

Introduction and Selection of Salt-tolerant Wheat in Yellow River Delta

[Objective] This study was to screen a salt-tolerant wheat variety in Dongying, a city in the center of the Yellow River Delta with a large area of coastal saline soil. [Method] Total 9 salt-tolerant, stress-resistant and high-yielding wheat varieties （lines） were introduced, and they were cultivated in the saline soil with total salt content of 3-4 g/kg with Dekang 961 as the control. [Result] The yields of Jinan 18, Yanjian 14 and Shanrong 3 were all significantly higher than that of Dekang 961 （P〈0.05）. These three varieties （lines） all ripen before June 13 with moderate growth period that does not affect the seeding of next-season crop. [Conclusion] Jinan 18, Yanjian 14 and Shanrong 3 are suitable for planting in light and median saline soil in the Yellow River Delta.

Mapping Soil Salinity Using a Similarity-based Prediction Approach:A Case Study in Huanghe River Delta,China

Spatial distribution of soil salinity can be estimated based on its environmental factors because soil salinity is strongly affected and indicated by environmental factors. Different with other properties such as soil texture, soil salinity varies with short-term time. Thus, how to choose powerful environmental predictors is especially important for soil salinity. This paper presents a similarity-based prediction approach to map soil salinity and detects powerful environmental predictors for the Huanghe(Yellow) River Delta area in China. The similarity-based approach predicts the soil salinities of unsampled locations based on the environmental similarity between unsampled and sampled locations. A dataset of 92 points with salt data at depth of 30–40 cm was divided into two subsets for prediction and validation. Topographical parameters, soil textures, distances to irrigation channels and to the coastline, land surface temperature from Moderate Resolution Imaging Spectroradiometer(MODIS), Normalized Difference Vegetation Indices(NDVIs) and land surface reflectance data from Landsat Thematic Mapper(TM) imagery were generated. The similarity-based prediction approach was applied on several combinations of different environmental factors. Based on three evaluation indices including the correlation coefficient(CC) between observed and predicted values, the mean absolute error and the root mean squared error we found that elevation, distance to irrigation channels, soil texture, night land surface temperature, NDVI, and land surface reflectance Band 5 are the optimal combination for mapping soil salinity at the 30–40 cm depth in the study area(with a CC value of 0.69 and a root mean squared error value of 0.38). Our results indicated that the similarity-based prediction approach could be a vital alternative to other methods for mapping soil salinity, especially for area with limited observation data and could be used to monitor soil salinity distributions in the future.

Water-salt transport characteristics of saline soil under hydraulic remediation measures in the Yellow River Delta region of China

To understand the water-salt transport process of saline soils in the Yellow River Delta region under traditional hydraulic remediation measures and to determine its engineering parameters, in this study, laboratory investigations were made to measure the soil salt content using three remediation practices under simulated rainfall conditions. The results indicated that under the rainfall intensity of 100 mm/h, 6-8 h are needed when the soil salt content tends to be constant. The distribution of the salt content presents a typically symmetrical shape regardless of the position of the saline soil relative to the concealed pipe, the open ditch, and the vertical shaft. The two-parameter exponential function indicates the relationship between the soil desalination rate and the horizontal distance from the pipe, the ditch or the shaft. The maximum spacing to build the salt drainage engineering of the concealed pipe, the open ditch or the vertical shaft in the laboratory is 4.79 m, 2.88 m, and 2.19 m, respectively. The effectiveness of salt drainage for coastal saline soils can be ranked from largest to smallest as the concealed pipe, the open ditch and the vertical shaft. The findings provide an experimental basis and reference for the application of hydraulic measures to remediate saline soils in this region.

Effects of Soil Salinity on Microbial Biomass Nitrogen of Landscape Soil

Soil salinization can limit the development of agriculture in the Yellow River Delta.In this paper,saline and alkaline farmland in the Yellow River Delta was chosen as the research object,and effects of soil salinity on soil microbial biomass nitrogen(SMBN) under different conditions were investigated to study the response of soil nitrogen turnover to salt stress.There were four salinity gradients(S1:0.1%;S2:0.5%;S3:0.9%;S4:1.3%),and four substrates were added to the soil.The results showed that after the addition of various substrates,SMBN in treatments with high soil salinity(S3 and S4) was obviously lower than that in treatments with low soil salinity(S1 and S2).In comparison with treatment S1,the average of SMBN in treatments S3 and S4 decreased by 35.8% and 46.7% respectively when there was no substrate added to them;it declined by 55.6% and 56.1% respectively as the carbon source was added to them;it reduced by 24.6% and 28.3% when the nitrogen source was added to them;it dropped by 43.8% and 57.0% respectively as the carbon and nitrogen source were added to them.Compared with treatments without substrates,the addition of the nitrogen source could not improve SMBN;the addition of the carbon source or carbon and nitrogen source could enhance SMBN obviously,and it increased by 60.9% and 66.1%(or 110.8% and 140.2%) in treatments with low soil salinity(S1 and S2),while it changed slightly in treatments with high soil salinity(S3 and S4).In order to increase SMBN,it is needed to apply organic fertilizer or chemical fertilizer and organic fertilizer to maintain or improve soil fertility.

Succession of bacterial community along with the removal of heavy crude oil pollutants by multiple biostimulation treatments in the Yellow River Delta,China

Multiple biostimulation treatments were applied to enhance the removal of heavy crude oil pollutants in the saline soil of Yellow River Delta.Changes of the soil bacterial community were monitored using the terminal restriction fragment length polymorphism （T-RFLP） and clone library analyses.The 140-day microcosm experiments showed that low C：N：P ratio,high availability of surfactant and addition of bulking agent significantly enhanced the performance,leading to the highest total petroleum hydrocarbon removal.Meanwhile,the bacterial community was remarkably changed by the multiple biostimulation treatments,with the Deltaproteobacteria,Firmicutes,Actinobacteria,Acidobacteria and Planctomycetes being inhibited and the Alphaand Beta-proteobacteria and some unknown Gammaproteobacteria bacteria being enriched.In addition,different hydrocarbon-degraders came to power in the following turn.At the first stage,the Alcanivorax-related Gammaproteobacteria bacteria dominated in the biostimulated soil and contributed mainly to the biodegradation of easily degradable portion of the heavy crude oil.Then the bacteria belonging to Alphaproteobacteria,followed by bacteria belonging to Candidate division OD1,became the dominant oil-degraders to degrade the remaining recalcitrant constituents of the heavy crude oil.

Analysis of relationships between land surface temperature and land use changes in the Yellow River Delta

This study analyzed land use and land coverchanges and their impact on land surface temperature usingLandsat 5 Thematic Mapper and Landsat 8 OperationalLand Imager and Thermal Infrared Sensor imagery of theYellow River Delta. Six Landsat images comprising twotime series were used to calculate the land surfacetemperature and correlated vegetation indices. The YellowRiver Delta area has expanded substantially because of thedeposited sediment carried from upstream reaches of theriver. Between 1986 and 2015, approximately 35% of theland use area of the Yellow River Delta has beentransformed into salterns and aquaculture ponds. Overall,land use conversion has occurred primarily from poorlyutilized land into highly utilized land. To analyze thevariation of land surface temperature, a mono-windowalgorithm was applied to retrieve the regional land surfacetemperature. The results showed bilinear correlationbetween land surface temperature and the vegetationindices （i.e., Normalized Difference Vegetation Index,Adjusted-Normalized Vegetation Index, Soil-AdjustedVegetation Index, and Modified Soil-Adjusted VegetationIndex）. Generally, values of the vegetation indices greaterthan the inflection point mean the land surface temperatureand the vegetation indices are correlated negatively, andvice versa. Land surface temperature in coastal areas isaffected considerably by local seawater temperature andweather conditions.

Geospatial-temporal analysis of land-use changes in the Yellow River Delta during the last 40 years

Comprehensive study on land-use change of spatial pattern and temporal process is the key component in land use/land cover changes (LUCC) study nowadays. According to the theories and methods of Geo-information Tupu (Carto-methodology in Geo-information, CMGI) for geospatial and temporal analysis and integration models of spatial pattern and temporal processes in GIS, the paper puts forward Tupu methodology of land-use change and names the basic synthetic unit of spatial-temporal information Tupu unit. Tupu unit is the synthetic unit for geospatial-temporal analysis, which is synthesized by “space·attribute·process”features and composed of relatively homogeneous geographic unit and temporal unit. Based on the spatial features of 4 stages of land-use change in 1956, 1984, 1991, and 1996, a series of Tupu on land-use change in the Yellow River Delta (YRD) are created and studied in the paper, which includes 3 temporal units of spatial-temporal Tupu, process Tupu of land-use changes during the last 40 years, and reconstructions of a series of “arisen”Tupu, “arisen”process Tupu and pattern Tupu on land-use changes in the last 40 years by remapping tables of a reclassifying system. There are 3 methods of Tupu analysis on land-use change that are used to disclose change processes of land-use spatial conversion in YRD, such as spatial query and statistics, order of Tupu units by area and land-use conversion matrixes. In order to reveal the spatial pattern of land-use change processes, we analyze spatial-temporal changes of each Tupu above in various temporal units and spatial difference of pattern Tupu in the last 40 years by dynamic Tupu units. Tupu analysis on regional land-use is a promising trial on the comprehensive research of “spatial pattern of dynamic process”and “temporal process of spatial pattern”in LUCC research. The geo-information Tupu methodology would be a powerful and efficient tool on integrated studies of spatial pattern and temporal process in geoscience.

Spatial and Temporal Pattern Changes and Driving Forces:Analysis of Salinization in the Yellow River Delta from 2015 to 2020

China’s Yellow River Delta represents a typical area with moist semi-humid soil salinization,and its salinization has seriously affected the sustainable use of local resources.The use of remote sensing technology to understand changes in the spatial and temporal patterns of salinization is key to combating regional land degradation.In this study,a feature space model was constructed for remote sensing and monitoring land salinization using Landsat 8 OIL multi-spectral images.The feature parameters were paired to construct a feature space model;a total of eight feature space models were obtained.An accuracy analysis was conducted by combining salt-loving vegetation data with measured data,and the model demonstrating the highest accuracy was selected to develop salinization inversion maps for 2015 and 2020.The results showed that:(1)The total salinization area of the Yellow River Delta displayed a slight upward trend,increasing from 4244 km^(2) in 2015 to 4629 km^(2) in 2020.However,the area’s salting degree reduced substantially,and the areas of saline soil and severe salinization were reduced in size;(2)The areas with reduced salinization severity were mainly concentrated in areas surrounding cities,and primarily comprised wetlands and some regions around the Bohai Sea;(3)Numerous factors such as the implementation of the“Bohai Granary”cultivation engagement plan,increase in human activities to greening local residential living environments,and seawater intrusion caused by the reduction of sediment contents have impacted the distribution of salinization areas in the Yellow River Delta;(4)The characteristic space method of salinization monitoring has better applicability and can be promoted in humid-sub humid regions.

基于Landsat TM/ETM影像的黄河三角洲盐渍土动态变化分析

通过Landsat系列卫星的TM和ETM数据的光谱特性研究和盐碱地信息模型的构建,研究了在黄河三角洲地区通过遥感手段实现对盐渍化土地退化信息提取的可行性。研究结果表明,黄河三角洲近10a来盐碱地呈现重度盐渍化加重的趋势,2007年较2003年加重趋势要比2011年较2007年加重趋势大,而2011年加重趋势趋缓,但比2003年要重,土地退化明显,即土壤盐渍化有持续加重趋势,这与人类活动紧密相关,主要表现在孤东油田的不断建设忽略了对土地的保护和合理利用,滨海区域卤水晒盐和养殖池塘的建设上;轻度盐渍化区域面积也不断增加,与人工灌区的开挖,引入黄河径流及水利工程措施有关。人类活动对土壤盐渍化影响既有积极一面,也有消极作用。

应用INSAR进行黄河三角洲地面沉降监测研究

在分析黄河三角洲的地面沉降状况及其对国民经济造成的影响的基础上,说明了对黄河三角洲进行地面沉降研究的必要性。综述了合成孔径雷达干涉测量的基本原理,针对近年来国内外干涉合成孔径雷达(INSAR)技术在地面沉降方面的研究和应用成果,分析了合成孔径雷达干涉测量技术应用于黄河三角洲地面沉降研究的可行性。

基于Landsat的黄河三角洲地区土地利用变化动态监测

土地利用的动态监测及其影响因子的分析,有助于了解地区发展的一般特征及趋势,提高城市用地规划的科学性与合理性。本文以黄河三角洲为研究区,基于RS技术,利用3期Landsat遥感影像(2009、2015和2019年),采用监督分类方法提取了黄河三角洲地区的土地利用类型,依据提取结果对10年间土地利用类型进行了动态变化监测与分析。结果表明,2009—2019年期间,盐田、建筑用地和耕地的面积持续增加,分别增加了952.56、605.99和302.54 km^(2);盐碱地、植被、滩涂与水产池塘等地类面积持续减少,分别减少了1033.56、377.53、110.77和336.14 km^(2);其他地类面积或有增减,变化不大。

黄河三角洲Sentinel-3高精度时空连续海陆表面温度反演

海陆表面温度是理解全球变化与人类活动的关键参数。针对已有温度反演产品海陆边界时空不连续的问题,本文采用Sentinel-3海陆表面温度辐射计(SLSTR)光学与热红外影像,通过植被指数阈值法逐像元计算陆表与海表发射率,基于分裂窗算法反演得到黄河三角洲陆海表面时空连续温度产品。结合地面温度观测和欧洲中期天气预报中心提供的全球中等分辨率数值大气再分析产品,验证了本文陆海温度产品(均方根误差优于1.1K)反演精度高于现有公开的全球产品,可为全球时空连续温度产品反演提供参考。

玉米种植改变了引黄灌区盐渍化土壤细菌多样性与功能

为了明确植物修复对盐渍化土壤细菌群落结构及多样性的影响,本文对宁夏引黄灌区盐渍化土壤玉米种植地根际和非根际土壤以及荒地土壤细菌多样性、群落结构及功能、细菌群落与环境因子之间的相关关系等进行研究。结果表明:玉米种植能够增加盐渍化土壤细菌物种数(OTU, Operational Taxonomic Unit)和多样性,各土壤细菌总物种数和特有物种数(OTU)从高到低依次为:非根际土壤>根际土壤>荒地土壤;土壤细菌多样性(即ACE指数、Chao1指数、Simpson指数与Shannon指数)由大到小均依次为:根际土壤>非根际土壤>荒地土壤, 3种土壤细菌多样性之间差异不显著。玉米种植改变了盐渍化土壤细菌群落结构和功能多样性,玉米种植显著提高了变形菌门(Proteobacteria)与放线菌门(Actinobacteria)两种优势菌门的相对丰度;丛毛单胞菌属(Comamonadaceae)、丝状菌属(Hyphomircobiales)和根瘤菌属(Rhizobiaceae)为3种土壤组间差异贡献最大的物种;玉米种植增加了盐渍化土壤中细菌参与新陈代谢功能与遗传信息处理功能物种的相对丰度,且有效磷、全磷、速效氮、全盐和pH是影响二级功能相对丰度的重要因子。玉米种植后其根际和非根际土壤细菌群落在生态位上与荒地之间存在明显分异。种植玉米修复盐渍化土壤能够改变土壤细菌群落结构、功能和多样性,对改善盐渍化土壤微环境,促进盐渍化土壤微生物功能发挥和盐渍化土壤种植结构优化具有重要意义。

Spatial-temporal variation and attribution of salinization in the Yellow River Basin from 2015 to 2020

Under the pressure of SDG15.3.1 compliance,it is imperative to solve the land salinization degradation problem in the Yellow River Basin as China’s granary.From the view of geographical scale,six zoning units were divided in the Yellow River Basin with‘climate-meteorology-geomorphology’as the main controlling factor,and a salinization inversion model was constructed for each zoning unit.Appropriate surface parameters were selected to construct a three-dimensional feature space according to the individual geographical zones.Based on the cloud data processing capability of the Google Earth Engine platform,a feature space inversion process was applied for automatic inversion of salinization.Salinization distribution maps of the Yellow River Basin in 2015 and 2020 were obtained at 30 m resolution by classifying the salinization inversion result.The distribution and spatiotemporal variation of salinization as well as the causes of salinization were analyzed.Reasonable prevention and control suggestions were subsequently proposed.This study could also be scaled up to larger and more complex geographical regions.