Formation mechanism of hydrochemical and quality evaluation of shallow groundwater in the Upper Kebir sub-basin,Northeast Algeria

This study investigates the hydrochemical formation mechanism of shallow groundwater in the Upper Kebir upstream sub-basin(Northeastern Algeria).The objective is to evaluate water quality suitability for domestic purposes through the application of water quality index(WQI).A total of 24 water points(wells and borewells)evenly distributed in the basin were collected and analyzed in the laboratory for determining the major ions and other geochemical parameters in the groundwater.The groundwater hydrochemical types were identified as Cl–Na and Cl–HCO_(3)^(–)Na,with the dominant major ions were found in the order of Na^(+)>Ca^(2+)>Mg^(2+)for cations,and Cl^(−)>SO_(4)^(2−)>HCO_(3)^(–)>NO_(3)^(−)for anions.Results suggest that weathering,dissolution of carbonate,sulfate,salt rocks,and anthropogenic activities were the major contributors to ion content in the groundwater.The Water Quality Index(WQI)was calculated to assess the water quality of potable water.Approximately 50%of the sampled sites exhibited good water quality.However,the study highlights significant NO_(3)contamination in the study area,with 50%of samples exceeding permissible limits.Therefore,effective treatment measures are crucial for the safe consumption of groundwater.

A New Approach to Select Doubled Haploid Rice Lines under Salinity Stress Using Indirect Selection Index

This study determined the indirect selection index of doubled haploid(DH)rice using a multivariate analysis approach to select lines adaptive to salinity stress,comprising three experiments.The first experiment involved the selection of good agronomic characters in a field experiment conducted at an experimental station in Bogor,Indonesia.The second experiment involved salinity tolerance screening through hydroponic cultures using 0 and 120 mmol/L NaCl,conducted at a greenhouse in Bogor.The third experiment involved the validation of the indirect adaptability selection index(IASI)through a field experiment in Sukra(saline area).Field experiments followed a randomized complete block design(RCBD),whereas an RCBD nested factorial design was used for the greenhouse experiment.The first and second experiments used 56 DH lines and four check varieties with three replications.In the second experiment,Pokkali and IR29 varieties were also added as tolerant and sensitive checks of salinity,respectively.The third experiment used 28 selected DH lines,Inpari 29 and one sensitive DH line.The good agronomic index(GAI)was 0.465 yield+0.433 number of productive tillers+0.31 number of filled grains.This generated 24 DH rice lines with good agronomic traits.The salinity tolerance index(SaTI)was developed through the average of standardized salinity tolerance score and salinity selection index based on discriminant analysis.This generated 34 DH rice lines with good salinity stress tolerance.The IASI(IASI=GAI–SaTI)selected 28 DH rice lines adaptive to salinity stress and it was considered effective by Sukra validation.

Soil Salinity Mapping and Monitoring in Arid and Semi-Arid Regions Using Remote Sensing Technology: A Review

Soil salinity is a serious environmental problem especially in arid and semiarid areas. It either occurs naturally or is human-induced. High levels of soil salinity negatively affect crop growth and productivity leading land degradation ultimately. Thus, it is important to monitor and map soil salinity at an early stage to enact effective soil reclamation program that helps lessen or prevent future increase in soil salinity. Remote sensing has outperformed the traditional method for assessing soil salinity offering more informative and professional rapid assessment techniques for monitoring and mapping soil salinity. Soil salinity can be identified from remote sensing data obtained by different sensors by way of direct indicators that refer to salt features that are visible at the soil surface as well as indirect indicators such as the presence of halophytic plant and assessing the performance level of salt-tolerant crops. The purposes of this paper are to 1) discuss some soil salinity indicators;2) review the satellite sensors and methods used for remote monitoring, detecting and mapping of soil salinity, particularly in arid and semi-arid regions;3) review various spectral vegetation and salinity indices that have been developed and proposed for soil salinity detection and mapping, with an emphasis on soil salinity mapping and assessment in arid and semi-arid regions;and 4) highlight the most important issues limiting the use of remote sensing for soil salinity mapping, particularly in arid and semi-arid regions.

Derivation of salt content in salinized soil from hyperspectral reflectance data: A case study at Minqin Oasis, Northwest China

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.

Prediction of Soil Salinity Using Remote Sensing Tools and Linear Regression Model

Soil salinity is one of the most damaging environmental problems worldwide, especially in arid and semi-arid regions. Multispectral data Sentinel_2 are used to study saline soils in southern Tunisia. 34 soil samples were collected for ground truth data in the investigated region. A moderate correlation was found between electrical conductivity and the spectral indices from SWIR. Different spectral indices were used from original bands of Sentinel_2 data. Statistical correlation between ground measurements of Electrical Conductivity (EC), spectral indices and Sentinel_2 original bands showed that SWIR bands (b11 and b12) and the salinity index SI have the highest correlation with EC. Based on these results and combining these remotely sensed variables into a regression analysis model yielded a coefficient of determination R2 = 0.48 and an RMSE = 4.8 dS/m.

Sub-bandgap refractive indexes and optical properties of Sidopedβ-Ga_(2)O_(3) semiconductor thin films

In this article,we present a theoretical study on the sub-bandgap refractive indexes and optical properties of Sidopedβ-Ga_(2)O_(3) thin films based on newly developed models.The measured sub-bandgap refractive indexes ofβ-Ga_(2)O_(3) thin film are explained well with the new model,leading to the determination of an explicit analytical dispersion of refractive indexes for photon energy below an effective optical bandgap energy of 4.952 eV for theβ-Ga_(2)O_(3) thin film.Then,the oscillatory structures in long wavelength regions in experimental transmission spectra of Si-dopedβ-Ga_(2)O_(3) thin films with different Si doping concentrations are quantitively interpreted utilizing the determined sub-bandgap refractive index dispersion.Meanwhile,effective optical bandgap values of Si-dopedβ-Ga_(2)O_(3) thin films are further determined and are found to decrease with increasing the Si doping concentration as expectedly.In addition,the sub-bandgap absorption coefficients of Si-dopedβ-Ga_(2)O_(3) thin film are calculated under the frame of the Franz–Keldysh mechanism due to the electric field effect of ionized Si impurities.The theoretical absorption coefficients agree with the available experimental data.These key parameters obtained in the present study may enrich the present understanding of the sub-bandgap refractive indexes and optical properties of impurity-dopedβ-Ga_(2)O_(3) thin films.

Application of Remote Sensing and GIS Technology in Mapping Partition Saline Intrusion to Paddy Land:A Case Study at Phu Vang District,Thua Thien Hue Province

Adapting and restricting salinity intrusion in Vietnam is being concerned by more researchers as well as the local authorities.This study aimed to use remote sensing and geographic information system(GIS)technology for mapping paddy areas and salinity intrusion in spring crop 2015 at Phu Vang district,thereby helping precondition for assessing and monitoring changes in salinity intrusion to serve for salinization management in study area.Based on acquisition imagery,land use map and normalized difference vegetation index(NDVI)were extracted to interpolate the salinity of area by combining the laboratory analysis of collected soil samples from the field.The result showed that there were 1,067.107 ha of salinity land area accounting for 10.04%of the rice land in Phu Vang district,where the moderate salinity level was 180.67 ha and low salinity level was 866.431 ha.The salinity rice land was mainly distributed in Vinh Ha commune,Phu An commune and Phu Dien commune.The salinity in this area ranged from 0.4 mS/cm to 1.41 mS/cm and the moderate salinity was approximately 0.9 mS/cm.Besides,this research also showed that the salinity(electrical conductivity)and the development of vegetation(NDVI)were closely related with each other up to 61.4%.

Mapping of Salinity Ingress Using Galdit Model for Sirkali Coastal Region: A Case Study

A model is traced to evaluate and enumerate the significance of vulnerability to seawater intrusion due to excessive ground water withdrawals and some anthropogenic activities at coastal aquifers. So taking these issues into account few thematic maps which were influencing the saline water intrusion were prepared and overlaid using Geographical Information Systems (GIS). Based on GALDIT method, the groundwater vulnerability cartography has been assessed. To reckon the GALDIT index it requires six parameters like aquifer type, aquifer hydraulic conductivity, depth to groundwater level (AMSL), distance from the shore, impact of existing status of seawater intrusion and thickness of the aquifer. This GALDIT is the indicator scores and summing them and dividing by the total weight for determining the relative role of each one. Apart from this an identification of saltwater intruded area is done by using indicators of saltwater intrusion like Cl/(HCO3 + CO3) ratio and Na/Cl ratio. The vulnerability areas are classified as moderate with an area of 147.31 sq. km and low covering an area of 168.72 sq. km respectively based on the thematic maps. The final thematic map can be used for management of the coastal ground water resources.

Investigation of Connecting Wind Turbine to Radial Distribution System on Voltage Stability Using SI Index and λ - V Curves

The growth of wind energy penetration level in distribution system raises the concern about its impact on the operation of the power system, especially voltage stability and power loss. Among the major concerns, this paper studied the impact of connecting wind Turbine (WT) in radial distribution system with different penetration levels and different power factor (lead and lag) on power system voltage stability and power loss reduction. Load flow calculation was carried out using forward-backward sweep method. The analysis proceeds on 9- and 33-bus radial distribution systems. Results show that voltage stability enhancement and power loss reduction should be considered as WT installation objective.

Investigation of Electrical Parameters of Fresh Water and Produced Mixed Injection in High-Salinity Reservoirs

Assuming a reservoir with a typical salt-lake background in the Qaidam Basin as a testbed,in this study the var-iation law of the rock electrical parameters has been determined through water displacement experiments with different salinities.As made evident by the results,the saturation index increases with the degree of water injec-tion.When the salinity of the injected water is lower than 80000 ppm,the resistivity of the rock samplefirst decreases,then it remains almost constant in an intermediate stage,andfinally it grows,thereby giving rise to a‘U’profile behavior.As the salinity decreases,the water saturation corresponding to the inflection point of the resistivity becomes lower,thereby leading to a wider‘U’type range and a higher terminal resistivity.For dif-ferent samples,higher initial resistivity of the sample in the oil-bearing state,and higher resistivity after low-sali-nity water washing are obtained when a thicker lithology is considered.

基于Sentinel-1/2改进极化指数和纹理特征的土壤含盐量反演模型

目前Sentinel-1/2协同反演植被土壤含盐量的研究大多是基于Sentinel-2光谱信息和Sentinel-1后向散射系数,没有考虑Sentinel-2光谱信息容易受土壤亮度等信息影响,Sentinel-1后向散射系数容易受土壤粗糙度和水分影响。为进一步提高Sentinel-1/2协同反演植被土壤含盐量的精度,用水云模型对雷达卫星后向散射系数进行校正,消除植被影响;然后协同Sentinel-2纹理特征,基于VIP、OOB、PCA 3种变量筛选和RF、ELM、Cubist 3种机器学习回归模型构建植被土壤含盐量反演模型。研究结果表明:经过水云模型去除植被影响后的雷达后向散射系数及其极化组合指数与土壤含盐量的相关性有一定程度的提高。不同变量选择方法与不同机器学习方法耦合模型在反演土壤含盐量中,OOB变量筛选方法与RF、ELM和Cubist 3种机器学习方法的耦合模型精度最佳,建模集和验证集的R2都在0.750以上,且验证集的RMSE和MAE均最小;其中OOB-Cubist耦合模型精度最高,且R_(v)^(2)/R_(c)^(2)为0.955,具有良好的鲁棒性。研究可为机器学习协同物理模型、光学卫星协同雷达卫星在土壤含盐量反演中的进一步应用提供思路。

盐碱胁迫下薄皮木苗期生理响应分析

以薄皮木组培苗为试材,采用不同浓度(50、100、150、200、250 mmol·L^(-1))盐碱胁迫,以不加盐碱溶液为对照,测定薄皮木叶片丙二醛(MDA)、过氧化物酶(POD)、过氧化氢酶(CAT)及叶绿素含量的动态变化,研究盐碱胁迫对薄皮木幼苗生理特性的影响,确定薄皮木幼苗耐盐碱能力,以期为其引种栽培提供参考依据。结果表明:随着盐碱胁迫浓度的增加和胁迫时间的延长,丙二醛含量变化呈上升趋势;随着盐碱浓度的增加和胁迫时间的延长,CAT活性均呈先上升后下降趋势;随着盐浓度的增加和胁迫时间的延长,POD活性呈先升后降趋势,盐胁迫峰值为50 mmol·L^(-1),随着碱浓度的增加和胁迫时间的延长,POD活性变化不一致;随着盐碱胁迫浓度的增加和胁迫时间的延长,叶绿素含量呈下降趋势,碱胁迫下,50、100 mmol·L^(-1)与对照无显著差异,说明薄皮木幼苗具有一定的耐盐碱能力。在盐碱浓度50 mmol·L^(-1)时,可以通过自身生理生化变化来保护植株对环境的适应性,在盐碱浓度大于150 mmol·L^(-1)时,薄皮木幼苗会受到伤害,影响植株正常生长过程。

养殖池塘水体异味物质土臭素与环境因子关系解析

本研究旨在分析淡水鱼产品消费和加工中的主要障碍之一——土腥味,特别是其关键异味物质土臭素(GSM)的影响因素。通过对江苏省84个养殖池塘的GSM浓度及其水体环境因子(包括盐度、pH、溶氧、温度、总悬浮物、总氮、总磷和高锰酸盐指数)的检测,采用相关性分析和通径分析方法,筛选出影响GSM的关键环境因子。结果显示,全部池塘中GSM检出率高达97.6%,检出的含量均值为(27.83±20.06)ng/L,大范围超过人类感知阈值;盐度和高锰酸盐指数对GSM产生较大的负向影响,且盐度和高锰酸盐指数的直接作用都大于间接作用,2个因子较为独立地对养殖池塘中的GSM起着负调控作用。因此,在水产养殖管理过程中,可以将盐度和高锰酸盐指数作为养殖池塘水体环境监测的重点环境因子,针对性地采取管理措施,进而改善养殖池塘水质,更有效、更方便地解决养殖水体和养殖产品的土腥味问题。

基于NDVI-SI特征空间的土壤盐渍化遥感模型

同时考虑植被和土壤信息,构建盐渍化遥感信息提取模型。选取具有长期研究基础的塔里木南缘于田绿洲为研究靶区,综合分析归一化差值植被指数(NDVI)、盐分指数(SI)二者之间的关系,在此基础之上提出NDVI-SI特征空间概念,并构建土壤盐渍化遥感监测指数模型(SDI),结果表明:土壤表层含盐量与SDI相关性较高,其R2=0.8596。非盐渍地、轻度盐渍地、中度盐渍地、重度盐渍地的SDI平均值分别为0.399,0.763,0.974和1.201,差异较大;经差异性矩阵分析,亦表明SDI能够很好的区分研究区内不同盐渍化程度地类的分布范围。SDI能反映盐渍化土壤地表盐量组合及其变化,具有明确的生物物理意义,并且指标简单、易于获取、有利于盐渍化定量分析与监测,对今后干旱区盐渍地信息提取以及动态监测研究具有重要意义。

骨骼肌质量指数、肌少症指数与呼吸危重症患者营养状态及预后的关系分析

目的探讨骨骼肌质量指数(Skeletal muscle mass index,SMI)、肌少症指数(Sarcope-nia index,SI)与呼吸危重症患者营养状态及预后的关系。方法选取2021年9月至2023年8月南通市第一人民医院收治的呼吸危重患者132例。采用改良危重症营养风险评分表(The modi-fied nutrition risk in critically ill,mNUTRIC)评估患者营养状况,根据评分结果分为低风险患者(n=83)、高风险患者(n=49),比较低风险患者与高风险患者的SMI、SI。以离开ICU为时间终点评估预后,分为死亡组(n=37)和存活组(n=95),比较死亡组与存活组患者的一般资料,采用多因素Logistic回归模型分析影响呼吸危重症患者死亡的因素,受试者工作特征(Receiver operator characteristic,ROC)曲线分析SMI、SI预测呼吸危重症患者死亡的风险价值。结果与低风险患者相比,高风险患者的SMI、SI降低(P<0.05)。以离开重症监护室(Intensive care unit,ICU)为评估时间终点,与存活组相比,死亡组年龄、入院24 h内的急性生理评分、年龄评分及慢性健康评分(Acute physiology and chronic health evaluation scoring system,APACHEⅡ)评分及降钙素原(Procalcitonin,PCT)水平较高,白蛋白(Albumin,ALB)、SI和SMI则较低(P<0.05)。多因素Logistic回归模型显示,高APACHEⅡ评分及低SMI、SI值是影响呼吸危重症死亡的独立危险因素。ROC曲线显示,SMI、SI单独预测呼吸危重症患者死亡的曲线下面积(Area under curve,AUC)为0.784(0.720~0.839)、0.726(0.657~0.788),采用SMI、SI联合预测AUC为0.890(0.835~0.938),联合预测效能较单独预测效能更好(P<0.05)。结论SMI、SI与呼吸危重症患者营养状态关系密切,两者联合预测呼吸危重症患者死亡的临床价值高于单独预测。

基于Sentinel-2影像的黄河南岸典型改良示范区土壤含盐量反演模型

土壤盐渍化严重制约农田土壤环境的循环发展,高效准确地监测土壤盐分动态变化对盐碱地改良利用具有重要意义。为及时、有效地监测盐渍化土壤含盐量,以内蒙古黄河南岸灌区的4个典型盐碱化耕地改良示范区为例,利用Sentinel-2多光谱遥感影像,同步采集示范区内表层土壤的含盐量数据,通过相关性分析筛选敏感光谱指标,基于偏最小二乘回归(PLSR)、逐步回归(SR)、岭回归(RR)3种简单机器学习模型和深度学习Transformer模型建模,最后进行精度评价并优选出最佳含盐量反演模型。结果表明:示范区土壤反射率的可见光、红边、近红外波段反射率均与土壤含盐量呈正相关,短波红外波段反射率与土壤含盐量呈负相关,引入光谱指数能够有效提升Sentinel-2遥感影像与示范区表层土壤含盐量的相关性(相关系数绝对值不小于0.32);对比不同模型发现深度学习Transformer模型优于简单机器学习模型,验证集决定系数R~2和均方根误差(RMSE)分别为0.546和2.687 g/kg;含盐量反演结果与实地结果相吻合,为更精准反演内蒙古黄河南岸灌区盐渍化程度提供了参考。

基于光谱指数建模的沙井子灌区土壤盐分反演

为了快速准确地获取干旱地区表层土壤盐分信息,以沙井子灌区为研究区,利用地面采集的0~10 cm和10~20 cm深度的土壤盐分数据,以及同步获取的Landsat 9 OLI遥感影像上相应点位的波段反射率值,组合两波段和三波段光谱指数,建立低植被度覆盖下盐渍化监测SDI1、SDI2、SDI3、SDI4模型,并检验4类模型对不同土层深度土壤盐分的反演精度。结果表明:(1)当土层深度为0~10 cm时,4类盐渍化监测模型对土壤盐渍化等级分类精度分别为73.56%、66.35%、43.75%和74.52%;而当土层深度为10~20 cm时,相应的分类精度分别为61.06%、62.50%、66.35%和64.42%,说明灌区内土层最佳反演深度为0~10 cm。(2)三波段光谱指数构建的SDI4模型优于双波段光谱指数构建的其余3种模型,能够有效反演沙井子灌区土壤盐渍化程度。研究结果可为灌区土壤盐渍化治理和防治提供有效的技术参考。

玉米杂交种耐盐碱性的主成分分析及综合评价

【目的】筛选适合宁夏引黄灌区盐碱化土壤种植的耐盐碱玉米杂交种。【方法】采用宁夏农科院选育的30份玉米杂交种株高、穗位高、茎粗、穗长、穗粗、单穗质量、出苗率等14个性状指标,基于主成分分析和聚类分析综合筛选耐盐碱玉米杂交种。【结果】主成分分析结果表明,将14农艺性状转化成5个主成分因子,代表原始数据信息量85.57%,并选出单穗质量、穗行数、出籽率、茎粗、出苗率5个耐盐碱评价指标;宁禾1822、宁禾2021、宁禾1948、宁禾2035和先玉1225这5份玉米杂交种耐盐碱性较好。聚类分析将30份耐盐碱品种分为3种类型,结果与主成分分析基本一致。【结论】通过2种分析方法筛选出5份耐盐碱性较强的杂交种,给宁夏平罗盐碱地玉米种植提供理论参考。

14份小黑麦种质萌发期对盐碱胁迫的响应

为探究小黑麦种质萌发期对盐碱胁迫的响应,本实验采用4种盐(NaHCO_(3)、NaCl、Na2SO_(4)、Na_(2)CO_(3))配置成4个浓度的盐碱溶液,测定盐碱胁迫对14份小黑麦种质萌发各项指标的影响。结果表明,小黑麦的萌发指标均随盐碱浓度的升高而下降;甘农4号的耐盐碱能力最好,其次是甘农2号,中饲1048的耐盐碱性能力最弱;聚类分析结果表明,青饲麦5、甘农2号和甘农4号为强耐盐碱组;雷神、优能、1771、青饲麦1、青饲麦2、青饲麦4和C23为耐盐碱中间组;藏饲1号、C24、C25和中饲1048为盐碱敏感组。

施用蚓粪对滨海盐碱地土壤有机碳库及其稳定性的影响

为探讨施用蚯蚓粪后滨海盐碱地土壤有机碳库及其稳定性的变化,选择江苏省南通市如东县栟茶镇方凌垦区的滨海盐碱地,于2019年10月将蚯蚓粪以0、25、50、100、200 t/hm^(2)施用量一次性施于田间,2022年10月采集耕层(0~20 cm)土壤样品,测定其可溶性有机碳、钙结合有机碳、易氧化有机碳、颗粒态及矿物结合态有机碳的含量,计算碳库管理指数,并采用固体核磁共振波谱分析土壤有机碳的官能团结构。结果表明:与不施用蚯蚓粪相比,施用超过50 t/hm^(2)的蚯蚓粪后,土壤有机碳库变化显著,土壤有机碳含量增加了35%~97%,可溶性有机碳含量增加了27%~104%,钙结合有机碳含量增加了19%~26%,易氧化有机碳含量增加了6%~94%,颗粒态和矿物结合态有机碳分别增加了14%~124%和37%~85%,土壤碳库管理指数提高了6%~92%;土壤中脂肪族碳与芳香族碳的比值减小,烷基碳/O-烷基碳以及疏水碳/亲水碳的比值增大,表明土壤有机碳的结构稳定性有所提升。综上,施用蚯蚓粪对提高滨海盐碱地土壤有机碳库及其稳定性具有显著作用,且在50和100 t/hm^(2)施用量下效果最佳。