Soil Salinity Index Research Articles

Water quality monitoring of selected dug wells of central India with special

Dug wells water is frequently used for irrigation of crops in India. The huge quantity of various toxic pollutants enters to ground water through anthropogenic and geogenic sources, which make the ground water, unfit for irrigation. Such water if used for irrigation may pose a serious risk to quality and quantity of crops and other things. The present study highlights the water quality monitoring of selected dug wells of Central India (Rajaula ward of Chitrakoot town). Different water quality parameters such as pH, electrical conductivity, Ca ++ , Mg ++ , Na + , K + , HCO 3 − , CO 3 − - chloride, sulfate, sodium percentage (Na %), magnesium hazards, sodium absorption ratio (SAR), residual sodium carbonate (RSC), potential soil salinity and permeability index were investigated for monitoring of t0 assess its suitability for irrigation. Some models, i.e. Wilcox Diagram, U.S. Salinity diagrams, Doneen criterion, etc. were also used for conformation of dug well water quality for irrigation purpose. Results of the study indicated that all selected wells have mostly medium and high salinity, under limit of SAR, medium Na%, medium Mg hazards, under limit of RSC and low Cl − quantity.

Soil salinity prediction in the Lower Cheliff plain (Algeria) based on remote sensing and topographic feature analysis

Soil salinity and ground surface morphology in the Lower Cheliff plain (Algeria) can directly or indirectly impact the stability of environments. Soil salinization in this area is a major pedological problem related to several natural factors, and the topography appears to be important in understanding the spatial distribution of soil salinity. In this study, we analyzed the relationship between topographic parameters and soil salinity, giving their role in understanding and estimating the spatial distribution of soil salinity in the Lower Cheliff plain. Two satellite images of Landsat 7 in winter and summer 2013 with reflectance values and the digital elevation model (DEM) were used. We derived the elevation and slope gradient values from the DEM corresponding to the sampling points in the field. We also calculated the vegetation and soil indices (i.e. NDVI (normalized difference vegetation index), RVI (ratio vegetation index), BI (brightness index) and CI (color index)) and soil salinity indices, and analyzed the correlations of soil salinity with topography parameters and the vegetation and soil indices. The results showed that soil salinity had no correlation with slope gradient, while it was significantly correlated with elevation when the EC (electrical conductivity) values were less than 8 dS/m. Also, a good relationship between the spectral bands and measured soil EC was found, leading us to define a new salinity index, i.e. soil adjusted salinity index (SASI). SASI showed a significant correlation with elevation and measured soil EC values. Finally, we developed a multiple linear regression for soil salinity prediction based on elevation and SASI. With the prediction power of 45%, this model is the first one developed for the study area for soil salinity prediction by the combination of remote sensing and topographic feature analysis.

Assessing soil salinity using soil salinity and vegetation indices derived from IKONOS high-spatial resolution imageries: Applications in a date palm dominated region

In saline soils, the spectral reflectance of either salt features at the surface or of vegetation that was negatively affected by salt varies with different salinity levels. Thus, several indices for vegetation and soil salinity have been developed. This study was conducted to assess the soil salinity levels in the Al-Hassa Oasis, which is dominated by date palm vegetation, in the eastern province of Saudi Arabia. Ground and remote sensing data were used to determine if any existing vegetation and soil salinity indices could be used to assess the soil salinity of communities vegetated with date palm. A systematic regular grid-sampling approach was used to collect a total of 149 composite soil samples from the study area. Thirteen broadband indices, which encompassed vegetation and soil salinity indices, were extracted from IKONOS satellite images. The predictive power of these indices for soil salinity was examined. The study area was dominated by areas of high salinity. Among the investigated indices, the Soil-Adjusted Vegetation Index (SAVI), Normalized Differential Salinity Index (NDSI) and Salinity Index (SI-T) yielded the best results for assessing the soil salinity of cultivated lands with dense and uniform vegetation. In contrast, the NDSI and SI-T exhibited the highest significant correlation with salinity for less densely vegetated lands and bare soils. Generally, the soil salinity in the areas that were dominated by date palms was successfully assessed by broadband vegetation and soil salinity indices that were extracted from the IKONOS satellite images.

Estimating soil salinity in Pingluo County of China using QuickBird data and soil reflectance spectra

Soil salinization is a worldwide environmental problem with severe economic and social consequences. In this paper, estimating the soil salinity of Pingluo County, China by a partial least squares regression (PLSR) predictive model was carried out using QuickBird data and soil reflectance spectra. At first, a relationship between the sensitive bands of soil salinity acquired from measured reflectance spectra and the spectral coverage of seven commonly used optical sensors was analyzed. Secondly, the potentiality of QuickBird data in estimating soil salinity by analyzing the correlations between the measured reflectance spectra and reflectance spectra derived from QuickBird data and analyzing the contributions of each band of QuickBird data to soil salinity estimation Finally, a PLSR predictive model of soil salinity was developed using reflectance spectra from QuickBird data and eight spectral indices derived from QuickBird data. The results indicated that the sensitive bands covered several bands of each optical sensor and these sensors can be used for soil salinity estimation. The result of estimation model showed that an accurate prediction of soil salinity can be made based on the PLSR method (R2=0.992, RMSE=0.195). The PLSR model's performance was better than that of the stepwise multiple regression (SMR) method. The results also indicated that using spectral indices such as intensity within spectral bands (Int1, Int2), soil salinity indices (SI1, SI2, SI3), the brightness index (BI), the normalized difference vegetation index (NDVI) and the ratio vegetation index (RVI) as independent model variables can help to increase the accuracy of soil salinity mapping. The NDVI and RVI can help to reduce the influences of vegetation cover and soil moisture on prediction accuracy. The method developed in this paper can be applied in other arid and semi-arid areas, such as western China.

Delimitation of the Coastal Transition Zone in the Gulf of Guayaquil, Ecuador

The article presents a methodology for the delimitation of the coastal transition zone (CTZ) and the identification of zones with distinct soil properties in the Gulf of Guayaquil (GG), Ecuador. The Gulf was chosen as study area for its urban, economic and ecological potential, more in particular for its rich marine and agricultural resources, and biodiversity. Soil physical and chemical methods, such as soil salinity indices, physical and chemical parameters, coupled with multivariate analysis enabled the delimitation of the CTZ and the grouping of the studied soil transets in three clusters with distinct properties, located in the GG from the limit of the mangrove swamp. Whereas the average conductance in the swamp area is around 27.17 mS cm-1, inland to the isoline called the coastal transit zone soil salinity on average is 4 mS cm-1. The coastal transition zone has an average width of 4.2 km, which can be characterized by three clusters. Clusters 1 and 2 show similarities in their physical and chemical soil parameters, clearly different from the soil properties of cluster 3. The characteristics of each cluster is related to its location within the study area.

새만금 신간척지 토양의 염농도별 식생특성

간척지를 농업용지로 개발하는데 간척지에 자생하는 식생의 이용가능성에 관한 기초 자료를 얻고자 새만금 간척지 내 계화지구에서 식생군락에 따라 식물종을 분류하고 토양 화학성과의 관계를 분석한 결과는 다음과 같다. 담수면 토양을 기점으로 조사된 위치별 토양염농도는 담수면 인접부가 22.3dS <TEX>$m^{-1}$</TEX> 로 가장 높았고 육지쪽으로 진행될수록 낮아져 해수면에서 2km이상 되는 지점에서는 1.1~3.44dS <TEX>$m^{-1}$</TEX>를 나타냈다. 자생하는 식물은 6과 26종이 조사되었으며, 식물종별 발생빈도는 갯개미취, 비짜루국화가 61.5로 가장 높은 빈도를 나타냈고, 이어 갈대와 갯꾸러미풀이 53.8이었다. 식생의 발생은 토양 염농도 14dS <TEX>$m^{-1}$</TEX> 지점에서 시작되었고 주로 명아주과 염생식물들인 퉁퉁마디, 나문재, 칠면초, 해홍나물 등이 나타났다. 이후 6.7dS <TEX>$m^{-1}$</TEX> 지점에서부터 화본과 식물인 갈대, 갯꾸러미풀 등이 나타났고, 5dS <TEX>$m^{-1}$</TEX> 에서 사초과 식물이 나타났다. 3dS <TEX>$m^{-1}$</TEX>이하에서는 비짜루국화, 갈대, 피, 갯잔디, 망초 등 중성식물들이 나타났다. 식생 종수는 염생식물과 중생식물이 동시에 나타나는 5dS <TEX>$m^{-1}$</TEX> 지점에서 많았고, Biomass는 갈대가 우점한 식생구가 가장 많았으며, 다음으로는 갈대+자귀풀이 우점한 식생에서 많았다. 식생의 생장량은 토양 염농도와는 부의상관을 나타냈고, 유기물함량과는 정의상관을 나타냈으며, pH와 식생의 우점도간에는 부의 상관을 나타냈다. This study was conducted to survey vegetation changes and soil characteristics in Saemangeum new reclaimed tidal land. Soil salinity in border area to tidal land was 22.3 dS <TEX>$m^{-1}$</TEX> but showed 1.1~3.44 dS <TEX>$m^{-1}$</TEX> over the distance of 2 km from border line. The vascular plants in survey sites were recorded as total 26 taxa in 6 families. The frequency of species appearance of Aster tripolium, A. subulatus var. sandwicensis were highest by 61.5 and that of Phragmites communis, Puccinellia nipponica were 53.8. The almost vegetations occurred in the patch which range of soil salinity 14 dS <TEX>$m^{-1}$</TEX> were halophytes as Salicornia europaea, Suaeda asparagoides, S. japonica. As lowed soil salinity as 6.7 dS <TEX>$m^{-1}$</TEX>, mixed vegetation of halophytes with P. communis, P. nipponica, Carex pumila were occurred. Dominant species in the range of 3.0 dS <TEX>$m^{-1}$</TEX> area were A. subulatus var. sandwicensis, P. communis, Echinochloa spp., Zoysia sinica and Conyza canadensis. Biomass production was the highest in the area of dominant vegetation with P. communis, and mixed zone with P. communis and Aeschynomene indica are followed. The correlation between vegetation biomass and soil salinity, soil pH and dominance index of vegetation were negative. But that of vegetation biomass and soil organic content were positive.

Remote Sensing Techniques for Salt Affected Soil Mapping: Application to the Oran Region of Algeria

Satellite remote sensing of land affected by salinity, is a useful tool for decision support system through digital image processing for materials delineation (crystallography, detection of rocks, mineralogy, etc.). Today, with the advent of technology integration, merger, with optical data radar (InSAR and Signal Processing) actively contributed to the modelling of radar backscattering coefficient for the quantitative and qualitative salinity (modelled coefficients for models in relation to soil moisture, surface roughness). Thus, our approach has been to exploit the multi-spectral optical data from the LANDSAT ETM + (Enhanced Thematic Mapper) to map surface states, including indices of salinity and sodicity as: (BI: Brightness Index), NDSI: Normalized Difference Salinity Index, SI: Salinity Index, ASI: Aster Salinity Index (Agriculture), Index of Salinity (using GIS Geographic Information System and remote sensing), and finally the SSSI “Soil Salinity and Sodicity Index”. These indicators of salinity were tested for the Oran region in accordance with the spectral sensor ALI (Advanced Land Imager) satellite EO-1 (NASA from 2002 to 2006). Remote sensing helps identify salts are highly reflective and improved mapping of saline soil surface. Reports of More frequently used is the combined near infrared and visible (4 / 1 ETM), or bands in the infrared (7 / 4 or 7 / 5 ETM). Consequently, the spectral curves of the satellite ALI EO-1 show a match for saline soils and two test plots were chosen (Aquifer of Es-Sénia) to study corresponding with the measured data in-situ (electrical conductivity and pH) for the classification of saline soils [2]. The confusions that arise between the effects of salt stress and water stress are removed followed by seasonal applying the Geo-statistical analysis with the Geo-modelling approach in GIS techniques investigation and monitoring the variation of the electrical conductivity in the alluvial aquifer of Es-Sénia for the salt affected soil and segmentation accuracy model.

Soil and vegetation recovery after a well blowout and salt water release in northeastern British Columbia

Leskiw, L. A., Sedor, R. B., Welsh, C. M. and Zeleke, T. B. 2012. Soil and vegetation recovery after a well blowout and salt water release in northeastern British Columbia. Can. J. Soil Sci. 92: 179–190. The impact of brine release on soil and vegetation due to a gas well blowout in December 1999 near Fort Nelson, British Columbia was evaluated over a 10 year period. The objectives were to study spatial and temporal distribution of soil salinity and vegetation and determine whether reclamation would occur through a natural recovery process. Soil salinity and vegetation diversity indices were measured on six study sites and one control. Average electrical conductivity declined with time from approximately 3.0 dS m−1 and has remained below 2.0 dS m−1 since 2002. Cycling of ions between leaf litter and plant tissue resulted in high variability in topsoil electrical conductivity. Sodium adsorption ratio in the leaf litter and A horizons was low (&lt;7), but remained high in B and C horizons (&gt;14) after 2004. From 2002 to 2010 moss cover increased 40%, whereas shrubs decreased 30%. The most impacted plot showed higher diversity than the least impacted plots and the control (Shannon diversity index = 1.49, 1.36, 1.11 for most impacted, least impacted and control, respectively). Soil and vegetation indicated salt-affected plots were recovering naturally. Results from this study could potentially provide guidelines for future remediation and reclamation practices.

Soil and vegetation recovery after a well blowout and salt water release in northeastern British Columbia

Leskiw, L. A., Sedor, R. B., Welsh, C. M. and Zeleke, T. B. 2012. Soil and vegetation recovery after a well blowout and salt water release in northeastern British Columbia. Can. J. Soil Sci. 92: 179-190. The impact of brine release on soil and vegetation due to a gas well blowout in December 1999 near Fort Nelson, British Columbia was evaluated over a 10 year period. The objectives were to study spatial and temporal distribution of soil salinity and vegetation and determine whether reclamation would occur through a natural recovery process. Soil salinity and vegetation diversity indices were measured on six study sites and one control. Average electrical conductivity declined with time from approximately 3.0 dS m-1 and has remained below 2.0 dS m-1 since 2002. Cycling of ions between leaf litter and plant tissue resulted in high variability in topsoil electrical conductivity. Sodium adsorption ratio in the leaf litter and A horizons was low ( 14) after 2004. Fro...

Reflectance spectroscopy for the assessment of soil salt content in soils of the Yellow River Delta of China

There has been growing interest in the use of reflectance spectroscopy as a rapid and inexpensive tool for soil characterization. In this study, we collected 95 soil samples from the Yellow River Delta of China to investigate the level of soil salinity in relation to soil spectra. Sample plots were selected based on a field investigation and the corresponding soil salinity classification map to maximize variations of saline characteristics in the soil. Spectral reflectances of air‐dried soil samples were measured using an Analytical Spectral Device (ASD) spectrometer (350–2500 nm) with an artificial light source. In the Yellow River Delta, the dominant chemical in the saline soil was NaCl and MgCl2. Soil spectra were analysed using two‐thirds of the available samples, with the remaining one‐third withheld for validation purposes. The analysis indicated that with some preprocessing, the reflectance at 1931–2123 nm and 2153–2254 nm was highly correlated with soil salt content (S SC). In the spectral region of 1931–2123 nm, the correlation R ranged from −0.80 to −0.87. In the region of 2153–2254 nm, the S SC was positively correlated with preprocessed reflectance (0.79–0.88). The preprocessing was done by fitting a convex hull to the reflectance curve and dividing the spectral reflectance by the value of the corresponding convex hull band by band. This process is called continuum removal, and the resulting ratio is called continuum removed reflectance (CR reflectance). However, the S SC did not have a high correlation with the unprocessed reflectance, and the correlation was always negative in the entire spectrum (350–2500 nm) with the strongest negative correlation at 1981 nm (R = −0.63). Moreover, we found a strong correlation (R = 0.91) between a soil salinity index (S SI: constructed using CR reflectance at 2052 nm and 2203 nm) and S SC. We estimated S SC as a function of S SI and S SI′ (S SI′: constructed using unprocessed reflectance at 2052 nm and 2203 nm) using univariate regression. Validation of the estimation of S SC was conducted by comparing the estimated S SC with the holdout sample points. The comparison produced an estimated root mean squared error (RMSE) of 0.986 (S SC ranging from 0.06 to 12.30 g kg−1) and R 2 of 0.873 for S SC with S SI as independent variable and RMSE of 1.248 and R 2 of 0.8 for S SC with S SI′ as independent variable. This study showed that a soil salinity index developed for CR reflectance at 2052 nm and 2203 nm on the basis of spectral absorption features of saline soil can be used as a quick and inexpensive method for soil salt‐content estimation.

Development of Comprehensive Soil Salinity Index

Crop yield is a function of many agroclimatic factors. However, excessive wetness, dryness, or soluble salts in the root zone are three important stresses that inhibit crop growth and reduce yield. Stress due to wetness can be expressed by an index such as SEW\D30\N (sum of excess water over 30 cm); however, a similar index is not available for stress due to soil salinity. An index, the sum of excess salinity over threshold (SES\i\dT), is proposed here. This index represents the cumulative salinity status of the root zone with respect to a specific crop in excess of the crop’s threshold level. Specifically, it incorporates the sum of daily salinity excesses over the threshold salinity level of the crop at different points in the root zone and over a specific crop-growth stage (or over an entire cropping period). The proposed salinity index, however, needs to be evaluated with field data before it can be used to characterize salt buildup in soil under different irrigation regimes.