Spatial distribution of soil nutrients in a watershed of Himalayan landscape using terrain attributes and geostatistical methods

ABSTRACT Tropical Savannas cover an area of approximately 1.9 billion hectares around the word and are subject to regular fires every 1 to 4 years. This study aimed to evaluate the influence of burning windrow wood from Cerrado (Brazilian Savanna) deforestation on the spatial variability of soil chemical properties, in the field. The data were analysed by using geostatistical methods. The semivariograms for pH(H2O), pH(CaCl2), Ca, Mg and K were calculated according to spherical models, whereas the phosphorus showed a nugget effect. The cross semi-variograms showed correlations between pH(H2O) and pH(CaCl2) with other variables with spatial dependence (exchangeable Ca and Mg and available K). The spatial variability maps for the pH(H2O), pH(CaCl2), Ca, Mg and K concentrations also showed similar patterns of spatial variability, indicating that burning the vegetation after deforestation caused a well-defined spatial arrangement. Even after 20 years of use with agriculture, the spatial distribution of pH(H2O), pH(CaCl2), Ca, Mg and available K was affected by the wood windrow burning that took place during the initial deforestation.

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Geostatistical Analysis for delineating sterile inclusions in Sidi Chennane' phosphatic series, Morrocco

Earth Sciences Research Journal ◽

10.15446/esrj.v18n2.41173 ◽

2015 ◽

Vol 18 (2) ◽

pp. 143-148

Author(s):

Khadija Baba ◽

Lahcen Bahi ◽

Latifa Ouadif

Keyword(s):

Spatial Distribution ◽

Exponential Model ◽

Geostatistical Analysis ◽

Distribution Maps ◽

Geostatistical Methods ◽

Qualitative Interpretation ◽

Phosphate Deposit ◽

Squared Residuals ◽

Geoelectric Data ◽

Best Fit

The anomalies detected in phosphatic series of Sidi Chennane, one of phosphatic basins in Morocco, hinder the proper exploitation of phosphate levels and the assessing phosphate reserves seems incorrect. The purpose of this study was the evaluation of geostatistical methods for delimitation of these disturbances. To cover all the zones being able to be disturbed, we carried out, during the geophysical prospection in a parcel of 50 ha, 5151 resistivity measurements as horizontal profiling using the well-known Schlumberger array, in order to map the spatial distribution of the sterile hardpan inclusions.Geostatistical tools were used to quantify the spatial correlation between apparent resistivity data. Semivariograms were obtained using a classical Matheron semivariogram estimator and fit to the experimental semivariograms obtained. We have selected those with the best fit in terms of sum of squared residuals (SSR).Geostatistical analysis was performed using the software VESPER 1.63. Spatial distribution maps were made by ordinary kriging, the qualitative interpretation of these maps reflects that the exponential model is found to be the best model representing the spatial variability of our geoelectric data. The qualitative interpretation of the kriged resistivity maps allows defining resistivity contrast, consequently we have delimited the crossing dominate area from a “normal” into a “disturbed” area. Models of the geology were successfully obtained from geostatical method, which help mapping the phosphate deposit inclusions and the estimations of phosphate reserves were improved and better constrained. ResumenLas anomalías detectadas en las series fosfóricas de Sidi Chennane, una de las cuencas fosfóricas de Marruecos, dificultan la explotación apropiada de los niveles de fosfato y hacen parecer incorrectos los cálculos de las reservas. El propósito de este estudio es la evaluación de los métodos geoestadísticos para la delimitación de estas anomalías. Para cubrir todas las zonas donde se pueden presentar estas alteraciones se llevaron a cabo,durante la exploración geofísica en una parcela de 50 hectáreas, 5151 medidas de resistividad con perfileshorizontales a través del conocido sondeo Schlumberger, con el fin de mapear la distribución espacial de las inclusiones estériles de la capa sólida.Se utilizaron herramientas geoestadísticas para cuantificar la correlación espacial entre los datos de resistividad. Se obtuvieron semivariogramas a través del tradicional estimador de semivariogramas Matheron y se adecuaron a los semivariogramas experimentales obtenidos. La selección se basó en aquellos que mejor se acoplaban en términos de la suma de cuadrados residuales (SCE). Los análisis geoestadísticos se realizaron con el programa VESPER 1.63. Los mapas de distribución espacial se hicieron por Kriging regular, y la interpretación cualitativa de estos mapas refleja que el modelo exponencial es el que mejor representa la variablilidad espacial de estos datos geoeléctricos. La interpretación cualitativa de los mapas de resistividad obtenidos por la técnica del Kriging permite definir el contraste de resistencia, lo que fija el área entre los estándares de “normal” y “Con Alteraciones”. Los modelos geológicos fueron obtenidos del método geoestadístico, lo que ayudó a mapear los depósitos de inclusiones de fosfato y mejoró las estimaciones de las reservas a través de una mejor definición de estas.

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Importance of terrain attributes in relation to the spatial distribution of soil properties at the micro scale: a case study

Canadian Journal of Soil Science ◽

10.1139/cjss-2017-0128 ◽

2018 ◽

Vol 98 (2) ◽

pp. 292-305 ◽

Cited By ~ 6

Author(s):

Vivekananthan Kokulan ◽

Olalekan Akinremi ◽

Alan Pierre Moulin ◽

Darshani Kumaragamage

Keyword(s):

Spatial Distribution ◽

Soil Properties ◽

Micro Scale ◽

Terrain Attributes

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Biocrust landscape‐scale spatial distribution is strongly controlled by terrain attributes: Topographic thresholds for colonization in a semiarid badland system

Earth Surface Processes and Landforms ◽

10.1002/esp.4706 ◽

2019 ◽

Vol 44 (14) ◽

pp. 2771-2779 ◽

Cited By ~ 5

Author(s):

Emilio Rodríguez‐Caballero ◽

José Raúl Román ◽

Sonia Chamizo ◽

Beatriz Roncero Ramos ◽

Yolanda Cantón

Keyword(s):

Spatial Distribution ◽

Landscape Scale ◽

Terrain Attributes

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Effect of Soil Orders and Land Uses on Available Soil Nutrients in Meghalaya, India

International Journal of Plant & Soil Science ◽

10.9734/ijpss/2020/v32i330260 ◽

2020 ◽

pp. 62-71

Author(s):

Chandan Goswami ◽

Naorem Janaki Singh ◽

Bijoy Krishna Handique

Keyword(s):

Land Use ◽

Spatial Distribution ◽

Soil Nutrients ◽

Land Management ◽

Mean Value ◽

Soil Samples ◽

Land Uses ◽

Sustainable Land Management ◽

P2o5 Content ◽

Zn Content

Understanding of spatial distribution of available soil nutrients is important for sustainable land management. An attempt has been made to assess the spatial distribution of available soil nutrients under different soil orders and land uses of RiBhoi, Meghalaya, India using geo-statistical techniques. Seven Land Use Land Cover (LULC) classes were selected from LULC map on 1:50,000 scale prepared by National Remote Sensing Centre (NRSC) viz. Abandoned Jhum (AJ), Current Jhum (CJ), Deciduous Forest (DF), Double Crop (DC), Evergreen Forest (EF), Kharif Crop (KC) and Wastelands (WL). Again, three soil orders were identified by National Bureau of Soil Survey and Land Use Planning (NBSS&LUP) in RiBhoi district of Meghalaya, India viz. Alfisols, Inceptisols and Ultisols. 105 soil samples were collected, 5 replicated soil samples from 21 strata derived from 7 LULC and 3 soil orders. Soil samples were analyzed for available nitrogen (N), available phosphorus (P2O5), available potassium (K2O) and available zinc (Zn) using standard procedures. One way ANOVA was carried out using IBM SPSS Statistics 20.0 software. Significance levels were tested at p≤0.05. N content varied from low (215.50 kg/ha) to medium (414.30 kg/ha) with mean value of 291.50 kg/ha. On the other hand, P2O5 content varied from low (19.90 kg/ha) to high (68.30 kg/ha) with mean value of 43.52 kg/ha. Similarly, K2O content varied from low (112.09 kg/ha) to high (567.84 kg/ha) with mean value of 273.68 kg/ha. Again, Zn also varied from low (0.26 ppm) to high (1.46 ppm) with mean value of 0.64 ppm. In Alfisols, N was found to be higher in EF, AJ & CJ than DF, DC, KC and WL. KC has been found to have lower N than all other LULC classes. Higher P2O5 has been found under EF over KC and WL. AJ has been found to have higher K2O than all other LULC classes. K2O has also been found to be higher in CJ over DC, KC and WL. DF and EF have been found to have higher K2O than KC and WL. Zn has been found to be higher in EF over CJ, DC and WL. In Inceptisols, higher amount of N was observed under EF over all other LULC classes. Higher N has also been found under CJ over DF, DC, KC and WL. P2O5 content was found to be higher under DF over all other LULC classes. Higher P2O5 content was also found under AJ, CJ and DC than KC and WL. Higher amount of K2O has been found under AJ over all other LULC. K2O content of soil under DF was also higher than CJ, EF, KC and WL. Zn has been found to be higher under EF over all other LULC classes. Zn content under CJ has also been found to be higher than AJ, DF, KC and WL. In Ultsols, higher amount of N has been found under EF compared to all other LULC classes. Lowest N content was found under KC. P2O5 content was found to be higher under EF, DF and AJ over all other LULC. K2O content has been found to be higher under CJ in comparison to all other LULC classes. K2O content of EF and DF were also found to be higher than AJ, DC, KC and WL. Again, K2O content has been found to be higher under DC compared to AJ, KC and WL. Zn content under EF and AJ was found to be higher than all other LULC classes. CJ, DF, DC, KC and WL have been found to have lower Zn content. It has been observed that P2O5 content is significantly higher in inceptisols irrespective of LULC classes. The study has highlighted the spatial distribution of available soil nutrients as a function of soil orders and LULC. This will be a useful input in sustainable land management programmes.

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Vegetation richness, height, coverage and spatial distribution mediate grasshopper abundance in the upper reaches of Heihe River, China

10.7287/peerj.preprints.3485 ◽

2017 ◽

Author(s):

Lili Li ◽

Chengzhang Zhao ◽

Tingjun Zhang ◽

dawei wang ◽

yuxing li ◽

...

Keyword(s):

Spatial Distribution ◽

Distribution Pattern ◽

Species Interactions ◽

Horizontal Distribution ◽

Heihe River ◽

Vegetation Community ◽

Altitude Gradient ◽

Geostatistical Methods ◽

Relationship Of ◽

The Relationship

Species interactions are often context-dependent and complex, such as the grasshopper community and phytoecommunity. The adoption of grasshopper abundance and vegetation community was determined by topographical heterogeneity. However, it remains vague about how vegetation community, such as coverage abundance and height, influence the spatial distribution pattern of grasshopper abundance at the altitude gradient. Using Geostatistical methods in natural grassland of the upper reaches of Heihe River to quantitatively study the relationship of spatial correlation. A 3 years investigation was shown that 3149 grasshoppers were collected, belonging to 3 families, 10 genera, and 13 species. The semivariable function of grasshopper abundance and vegetation community followed a nonlinear model. Meanwhile, horizontal distribution of two communities was a clear flaky and plaque distribution pattern, especially at the altitude gradient. The abundance of grasshoppers is opposite to the height and coverage of vegetation and the overall followability of coverage, while the local following is consistent. Such as grasshopper abundance, the above 2750m sample with the opposite trend, the following areas are consistent. Finally, grasshoppers have the different choice on different vegetation characteristics in different directions, formed of specific trend characteristics; and the spatial distribution trend is different even with the same community indicators, formed of embedded striped patches structure.

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Distribution Analysis of Heavy Metal Contaminants in Soil With Geostatistic Methods; Paper Review

Eduvest - Journal Of Universal Studies ◽

10.36418/edv.v1i7.111 ◽

2021 ◽

Vol 1 (7) ◽

pp. 620-628

Author(s):

Stefan Daniel Maramis ◽

Rika Ernawati ◽

Waterman Sulistyana Bargawa

Keyword(s):

Heavy Metals ◽

Heavy Metal ◽

Spatial Distribution ◽

Salt Spray ◽

Regional Scale ◽

Volcanic Eruptions ◽

Distribution Analysis ◽

Metal Contaminants ◽

Geostatistical Methods ◽

Heavy Metal Contaminants

Heavy metal contaminants in the soil will have a direct effect on human life. The spatial distribution of naturally occurring heavy metals is highly heterogeneous and significantly increased concentrations may be present in the soil at certain locations. Heavy metals in areas of high concentration can be distributed to other areas by surface runoff, groundwater flow, weathering and atmospheric cycles (eg wind, sea salt spray, volcanic eruptions, deposition by rivers). More and more people are now using a combination of geographic information science (GIS) with geostatistical statistical analysis techniques to examine the spatial distribution of heavy metals in soils on a regional scale. The most widely used geostatistical methods are the Inverse Distance Weighted, Kriging, and Spatial Autocorrelation methods as well as other methods. This review paper will explain clearly the source of the presence of heavy metals in soil, geostatistical methods that are often used, as well as case studies on the use of geostatistics for the distribution of heavy metals. The use of geostatistical models allows us to accurately assess the relationship between the spatial distribution of heavy metals and other parameters in a map.

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