scholarly journals Increasing the Efficiency of Detailed Soil Resource Mapping on Transitional Volcanic Landforms Using a Geomorphometric Approach

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Ahmad Priyo Sambodo ◽  
Tanwa Arpornthip

For developing countries, detailed soil resource data and maps are essential in land-use planning. Unfortunately, obtaining detailed soil data for mapping is expensive. Detailed soil studies and mapping in developing countries often use the grid method. In addition to being time-consuming, the grid method needs a lot of sample points and surveyors. Geomorphometry can be a less expensive alternative for detailed soil mapping. Geomorphometry uses computationally measured terrain characteristics to describe other hard-to-measure terrain and soil properties. In our study, landform arrangements and slopes were analyzed together to create a map of soil pH. Bompon watershed, Indonesia, was used as a case study. Soil mapping units with potentially similar soil pH were created based on a classification system of the two geomorphometric parameters. Soil samples were taken from each of the units. The samples' soil pH was measured and compared to the geomorphometric predicted result. Regression tests were performed to see the significance of geomorphometric parameters on soil pH conditions. Regression tests show that the results of p value of the four soil layers are 0.046, 0.019, 0.037, and 0.047, respectively, on a 5% confidence level. According to the test result, landform arrangements and slopes can indicate soil pH conditions in Bompon. Our estimate suggests that our geomorphometric method is cheaper than the grid method by a factor of seven. The ability to use geomorphometric parameters to describe other soil properties could enable a cheap and fast production of detailed soil maps for developing countries.

Chemosphere ◽  
2020 ◽  
pp. 128901
Author(s):  
Yin Liu ◽  
Qing Huang ◽  
Wen Hu ◽  
Jiemin Qin ◽  
Yingrui Zheng ◽  
...  

2021 ◽  
Vol 13 (11) ◽  
pp. 6221
Author(s):  
Muyuan Ma ◽  
Yaojun Zhu ◽  
Yuanyun Wei ◽  
Nana Zhao

To predict the consequences of environmental change on the biodiversity of alpine wetlands, it is necessary to understand the relationship between soil properties and vegetation biodiversity. In this study, we investigated spatial patterns of aboveground vegetation biomass, cover, species diversity, and their relationships with soil properties in the alpine wetlands of the Gannan Tibetan Autonomous Prefecture of on the Qinghai-Tibetan Plateau, China. Furthermore, the relative contribution of soil properties to vegetation biomass, cover, and species diversity were compared using principal component analysis and multiple regression analysis. Generally, the relationship between plant biomass, coverage, diversity, and soil nutrients was linear or unimodal. Soil pH, bulk density and organic carbon were also significantly correlated to plant diversity. The soil attributes differed in their relative contribution to changes in plant productivity and diversity. pH had the highest contribution to vegetation biomass and species richness, while total nitrogen was the highest contributor to vegetation cover and nitrogen–phosphorus ratio (N:P) was the highest contributor to diversity. Both vegetation productivity and diversity were closely related to soil properties, and soil pH and the N:P ratio play particularly important roles in wetland vegetation biomass, cover, and diversity.


2021 ◽  
Vol 3 (4) ◽  
Author(s):  
Gabriel Soropa ◽  
Olton M. Mbisva ◽  
Justice Nyamangara ◽  
Ermson Z. Nyakatawa ◽  
Newton Nyapwere ◽  
...  

AbstractA study was conducted to examine spatial variability of soil properties related to fertility in maize fields across varying soil types in ward 10 of Hurungwe district, Zimbabwe; a smallholder farming area with sub-humid conditions and high yield potential. Purposively collected and geo-referenced soil samples were analyzed for texture, pH, soil organic carbon (OC), mineral N, bicarbonate P, and exchangeable K. Linear mixed model was used to analyze spatial variation of the data. The model allowed prediction of soil properties at unsampled sites by the empirical best linear unbiased predictor (EBLUP). Evidence for spatial dependence in the random component of the model was evaluated by calculating Akaike’s information criterion. Soil pH ranged from 4.0 to 6.9 and showed a strong spatial trend increasing from north to south, strong evidence for a difference between the home and outfields with homefields significantly higher and between soil textural classes with the sand clay loam fraction generally higher. Soil OC ranged from 0.2 to 2.02% and showed no spatial trend, but there was strong evidence for a difference between home and outfields, with mean soil OC in homefields significantly larger, and between soil textural classes, with soil OC largest in the sandy clay loams. Both soil pH and OC showed evidence for spatial dependence in the random effect, providing a basis for spatial prediction by the EBLUP, which was presented as a map. There were significant spatial trends in mineral N, available P and exchangeable K, all increasing from north to south; significant differences between homefields and outfields (larger concentrations in homefields), and differences between the soil textural classes with larger concentrations in the sandy clay loams. However, there was no evidence for spatial dependence in the random component, so no attempt was made to map these variables. These results show how management (home fields vs outfields), basic soil properties (texture) and other factors emerging as spatial trends influence key soil properties that determine soil fertility in these conditions. This implies that the best management practices may vary spatially, and that site-specific management is a desirable goal in conditions such as those which apply in Ward 10 of Hurungwe district in Zimbabwe.


2021 ◽  
Author(s):  
Richard Mommertz ◽  
Lars Konen ◽  
Martin Schodlok

<p>Soil is one of the world’s most important natural resources for human livelihood as it provides food and clean water. Therefore, its preservation is of huge importance. For this purpose, a proficient regional database on soil properties is needed. The project “ReCharBo” (Regional Characterisation of Soil Properties) has the objective to combine remote sensing, geophysical and pedological methods to determine soil characteristics on a regional scale. Its aim is to characterise soils non-invasive, time and cost efficient and with a minimal number of soil samples to calibrate the measurements. Konen et al. (2021) give detailed information on the research concept and first field results in a presentation in the session “SSS10.3 Digital Soil Mapping and Assessment”. Hyperspectral remote sensing is a powerful and well known technique to characterise near surface soil properties. Depending on the sensor technology and the data quality, a wide variety of soil properties can be derived with remotely sensed data (Chabrillat et al. 2019, Stenberg et al. 2010). The project aims to investigate the effects of up and downscaling, namely which detail of information is preserved on a regional scale and how a change in scales affects the analysis algorithms and the possibility to retrieve valid soil parameter information. Thus, e.g. laboratory and field spectroscopy are applied to gain information of samples and fieldspots, respectively. Various UAV-based sensors, e.g. thermal & hyperspectral sensors, are applied to study soil properties of arable land in different study areas at field scale. Finally, airborne (helicopter) hyperspectral data will cover the regional scale. Additionally forthcoming spaceborne hyperspectral satellite data (e.g. Prisma, EnMAP, Sentinel-CHIME) are a promising outlook to gain detailed regional soil information. In this context it will be discussed how the multisensor data acquisition is best managed to optimise soil parameter retrieval. Sensor specific properties regarding time and date of acquisition as well as weather/atmospheric conditions are outlined. The presentation addresses and discusses the impact of a multisensor and multiscale remote sensing data collection regarding the results on soil parameter retrieval.</p><p> </p><p>References</p><p>Chabrillat, S., Ben-Dor, E. Cierniewski, J., Gomez, C., Schmid, T. & van Wesemael, B. (2019): Imaging Spectroscopy for Soil Mapping and Monitoring. Surveys in Geophysics 40:361–399. https://doi.org/10.1007/s10712-019-09524-0</p><p>Stenberg, B., Viscarra Rossel, R. A., Mounem Mouazen, A. & Wetterlind, J. (2010): Visible and Near Infrared Spectroscopy in Soil Science. In: Donald L. Sparks (editor): Advances in Agronomy. Vol. 107. Academic Press:163-215. http://dx.doi.org/10.1016/S0065-2113(10)07005-7</p>


1972 ◽  
Vol 52 (3) ◽  
pp. 427-438 ◽  
Author(s):  
A. J. MacLEAN ◽  
R. L. HALSTEAD ◽  
B. J. FINN

Liming of six acid soil samples in an incubation experiment with rates to raise the soil pH to 6.0 or above eliminated Al soluble in 0.01 M CaCl2, reduced soluble Mn and Zn, increased NO3-N markedly, and at the highest pH increased the amounts of NaHCO3-soluble P in some of the soils. In corresponding pot experiments, liming increased the yield of alfalfa and in three of the soils the yield of barley also. Liming reduced the concentrations of the metals in the plants and at the highest pH tended to increase the P content of the plants. Liming to a pH of about 5.3 eliminated or greatly reduced soluble Al and the soils were base saturated as measured by the replacement of Al, Ca, and Mg by a neutral salt. There was some evidence that liming to reduce soluble Al and possibly Mn was beneficial for plant growth. Gypsum increased the concentrations of Al, Mn, and Zn in 0.01 M CaCl2 extracts of the soils whereas phosphate reduced them. The changes in the Mn content of the plants following these treatments were in agreement with the amounts of Mn in the CaCl2 extracts.


Author(s):  
Juan Pablo Gonzalez ◽  
Andy Jarvis ◽  
Simon E. Cook ◽  
Thomas Oberthür ◽  
Mauricio Rincon-Romero ◽  
...  

2015 ◽  
Vol 12 (2) ◽  
pp. 34-38 ◽  
Author(s):  
Ashim Kumar Saha ◽  
Apu Biswas ◽  
Abdul Qayyum Khan ◽  
Md. Mohashin Farazi ◽  
Md. Habibur Rahman

Long-term tea cultivation has led to degradation of the soil. Old tea soils require rehabilitation for restoring soil health. Soil rehabilitation by growing different green crops can break the chain of monoculture of tea. An experiment was conducted at The Bangladesh Tea Research Institute (BTRI) Farm during 2008-2011 to find out the efficiency of different green crops on the improvement of soil properties. Four green crops such as Guatemala, Citronella, Mimosa and Calopogonium were grown to develop the nutritional value of the degraded tea soil. Soil samples were collected and analyzed before and at the end of experiment. Soil pH was increased in all four green crops treated plots with the highest increase in Citronella treated plots (from 4.1 to 4.5). Highest content of organic carbon (1.19%) and total nitrogen (0.119%) were found in Mimosa and Calopogonium treated plots, respectively. Concentration of available phosphorus, calcium and magnesium in all green crops treated plots were above the critical values, while available potassium content was above the critical value in Guatemala, Citronella and Mimosa treated plots. Changes in soil pH and available potassium were significant, while changes in organic carbon content, total nitrogen and available calcium were insignificant. Changes in available phosphorus and magnesium were significant. The Agriculturists 2014; 12(2) 34-38


2006 ◽  
Vol 63 (6) ◽  
pp. 558-563 ◽  
Author(s):  
Gláucia Cecília Gabrielli dos Santos ◽  
Ronaldo Severiano Berton ◽  
Otávio Antônio de Camargo ◽  
Mônica Ferreira de Abreu

The costs related to the construction and maintenance of industrial landfills, and the environmental risks that they may represent, have increased the interest of several types of industries in studying the possibility of applying residues to agricultural soils. This study evaluates the efficiency of flue dust as a zinc source for corn, and the zinc availability for corn evaluated by four methods. A greenhouse experiment carried out at Campinas, SP, Brazil, evaluated the effect of two zinc sources (flue dust and zinc sulphate), at three rates (5, 50 and 150 mg dm-3), in one soil (Rhodic Hapludox) under two pH conditions (5.0 and 6.0). The treatments were arranged in a randomized factorial scheme design with three replications. Zinc availability indexes were determined by the pH 7.3 DTPA, Mehlich-1, and Mehlich-3 methods. The free Zn2+ activity in soil solution was calculated by the MINTEQ computer model. The extraction methods and the activity of the free ion Zn2+ were equally reliable to evaluate zinc availability in the soil amended with flue dust. More than 70% of the total Zn present in the saturation extract was in the free ion form, and the remainder was mainly complexed to SO4(2-) and OH-, independent of soil pH. Flue dust is a zinc supplier to plants. All tested methods were efficient in evaluating Zn availability for corn, independently of soil pH.


2018 ◽  
pp. 1-14
Author(s):  
Alidad Karami ◽  
Sadegh Afzalinia

Aims: Determining effects of spatial variation of some soil properties on wheat quantity and quality variation in order that proper soil and inputs management can be applied for sustainable wheat production. Study Design: Analyzing data of a field with center pivot irrigation system and uniform management using the geostatistical method. Place and Duration of Study: Soil and Water Research Department, Fars Agricultural and Natural Resources Research and Education Center, Darab, Iran, from September 2013 to February 2014. Methodology: Wheat yield data harvested by class lexion 510 combine from 25 m2 plots (11340 locations) with the corresponding geographical location were used. Besides, soil properties and wheat yield were measured at 36 randomly selected points on the field. Interpolation of parameters was predicted with the best semi-variogram model using kriging, inverse distance weighted (IDW), and cokriging methods. Results: Results showed that wheat yield varied from 2 to 10.08 tons per hectare. Cokriging with cofactor of kernel weight interpolator had more accuracy compared to the combine default interpolator (kriging). A logical, linear correlation was found between different parameters. The best variogram model for pH, OC, and ρb was exponential, for EC, TNV, SP, soil silt and clay percentage was spherical, and for soil, percentage sand was Gaussian model. Data of soil sand, silt, and clay percentage, EC, TNV, and SP had strong spatial structure, and soil pH, OC, and ρb had moderate spatial structure. The best interpolation method for soil pH, EC, sand and silt percentage was kriging method; while, for TNV, SP, OC, ρb, and clay percentage was IDW. Conclusion: There was a close relationship between wheat yield variation and changes in the soil properties. Soil properties and wheat yield distribution maps provided valuable information which could be used for wheat yield improvement in precision agriculture.


2019 ◽  
Author(s):  
Xia Zhao ◽  
Yuanhe Yang ◽  
Haihua Shen ◽  
Xiaoqing Geng ◽  
Jingyun Fang

Abstract. Surface soils interact strongly with both climate and biota and provide fundamental ecosystem services that maintain food, climate, and human security. However, the quantitative linkages between soil properties, climate, and biota at the global scale remain unclear. By compiling a comprehensive global soil database, we mapped eight major soil properties (bulk density; clay, silt, and sand fractions; soil pH; soil organic carbon [SOC] density; soil total nitrogen [STN] density; and soil C : N mass ratios) in the surface (0–30 cm) soil layer based on machine learning algorithms, and demonstrated the quantitative linkages between surface soil properties, climate, and biota at the global scale (i.e., global soil-climate-biome diagram). On the diagram, bulk density increased significantly with higher mean annual temperature (MAT) and lower mean annual precipitation (MAP); soil clay fraction increased significantly with higher MAT and MAP; Soil pH decreased with higher MAP and lower MAT, and the critical MAP for the transition from alkaline to acidic soil decreased with decreasing MAT; SOC density and STN density both were jointly affected by MAT and MAP, showing an increase at lower MAT and a saturation tendency towards higher MAP. Surface soil physical and chemical properties also showed remarkable variations across biomes. The soil-climate-biome diagram suggests the co-evolution of the soil, climate, and biota under global environmental change.


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