Soil erosion modelling: A bibliometric analysis.

Soil erosion can present a major threat to agriculture due to loss of soil, nutrients, and organic carbon. Therefore, soil erosion modelling is one of the steps used to plan suitable soil protection measures and detect erosion hotspots. A bibliometric analysis of this topic can reveal research patterns and soil erosion modelling characteristics that can help identify steps needed to enhance the research conducted in this field. Therefore, a detailed bibliometric analysis, including investigation of collaboration networks and citation patterns, should be conducted. The updated version of the Global Applications of Soil Erosion Modelling Tracker (GASEMT) database contains information about citation characteristics and publication type. Here, we investigated the impact of the number of authors, the publication type and the selected journal on the number of citations. Generalized boosted regression tree (BRT) modelling was used to evaluate the most relevant variables related to soil erosion modelling. Additionally, bibliometric networks were analysed and visualized. This study revealed that the selection of the soil erosion model has the largest impact on the number of publication citations, followed by the modelling scale and the publication's CiteScore. Some of the other GASEMT database attributes such as model calibration and validation have negligible influence on the number of citations according to the BRT model. Although it is true that studies that conduct calibration, on average, received around 30% more citations, than studies where calibration was not performed. Moreover, the bibliographic coupling and citation networks show a clear continental pattern, although the co-authorship network does not show the same characteristics. Therefore, soil erosion modellers should conduct even more comprehensive review of past studies and focus not just on the research conducted in the same country or continent. Moreover, when evaluating soil erosion models, an additional focus should be given to field measurements, model calibration, performance assessment and uncertainty of modelling results. The results of this study indicate that these GASEMT database attributes had smaller impact on the number of citations, according to the BRT model, than anticipated, which could suggest that these attributes should be given additional attention by the soil erosion modelling community. This study provides a kind of bibliographic benchmark for soil erosion modelling research papers as modellers can estimate the influence of their paper.

Nitrogen dynamics as a function of soil types, compaction, and moisture.

In this study, the complex interactions between soil types, compaction, and moisture on nitrogen (N) transformation processes such as ammonia (NH3) volatilization, ammonification, nitrification, and denitrification were examined over a 30-day period using a simulated column approach. Two soil types: loam, and sandy loam, were subjected to three compaction treatments-control, surface, and sub-surface compaction-and two moisture regimes, dry and wet. Liquid urea ammonium nitrate (32-0-0) was used as the N fertilizer source at a rate of 200 kg N ha-1. Key indicators of N transformations were measured, including residual concentrations of ammonium (NH4-N) and nitrate (NO3-N), NO3-N leaching, NH3 volatilization, and nitrous oxide (N2O) emissions. Findings revealed that compaction significantly increased residual NH4-N concentrations in deeper soil profiles, with the highest 190.80 mg kg-1 recorded in loam soil under sub-surface compaction and dry conditions. Nitrification rates decreased across both soil types due to compaction, evidenced by elevated residual NH4-N levels. Increased NO3-N leaching was observed in loam soil (178.06 mg L-1), greater than sandy loam (81.11 mg L-1), due to initial higher residual NO3- in loam soil. The interaction of compaction and moisture most affected N2O emissions, with the highest emissions in control treatments during dry weather at 2.88 kg ha -1. Additionally, higher NH3 volatilization was noted in moist sandy loam soil under control conditions at 19.64 kg ha -1. These results highlight the necessity of considering soil texture, moisture, and compaction in implementing sustainable N management strategies in agriculture and suggest recommendations such as avoiding broadcast application in moist sandy loam and loam soil to mitigate NH3 volatilization and enhance N use efficiency, as well as advocating for readjustment of fertilizer rate based on organic matter content to reduce potential NO3-N leaching and N2O emissions, particularly in loam soil.

Potassium nutrient response in the rice-wheat cropping system in different agro-ecozones of Nepal.

Most of the soils of Nepal had a higher potassium (K, expressed as K2O) level inherently. Later in 1976, the Government of Nepal has recommended K fertilizer rate at 30 kg K2O ha-1 in rice-wheat cropping systems. However, those crops began showing K deficiency symptoms in recent decades, which could be due to a large portion of soils with depleted K level or the insufficient input of K fertilizer for crop production. This study explored a limitation of K nutrient in the crops by establishing field trials from 2009-2014 at three agro-ecozones i.e., inner-Terai (2009-2010), high-Hills (2011-2012), and Terai (2012-2014) in Nepal. Seven rates of K fertilizer at 0, 15, 30, 45, 60, 75, and 90 kg K2O ha-1 were replicated four times in a randomized complete block design, where crop yields and yield-attributing parameters of rice-wheat cropping system were recorded. Results revealed that an increase in K rates from 45 to 75 kg K2O ha-1 under inner-Terai and Terai conditions and 45 to 60 kg ha-1 under high-Hills conditions produced significantly higher grain yields compared to the recommended K dose. Economically, the optimum rate of K fertilizer should not exceed 68 kg K2O ha-1 for rice in all agro-ecozones, or 73 kg K2O ha-1 for wheat in inner-Terai and 60 kg K2O ha-1 for wheat in high-Hills and Terai. Our findings suggest to increase potassium application in between 1.5 to 2.5 times of the current K fertilizer rate in rice-wheat cropping system of Nepal that need to be tested further in different locations and crop varieties.

Soil erosion modelling: A global review and statistical analysis.

To gain a better understanding of the global application of soil erosion prediction models, we comprehensively reviewed relevant peer-reviewed research literature on soil-erosion modelling published between 1994 and 2017. We aimed to identify (i) the processes and models most frequently addressed in the literature, (ii) the regions within which models are primarily applied, (iii) the regions which remain unaddressed and why, and (iv) how frequently studies are conducted to validate/evaluate model outcomes relative to measured data. To perform this task, we combined the collective knowledge of 67 soil-erosion scientists from 25 countries. The resulting database, named 'Global Applications of Soil Erosion Modelling Tracker (GASEMT)', includes 3030 individual modelling records from 126 countries, encompassing all continents (except Antarctica). Out of the 8471 articles identified as potentially relevant, we reviewed 1697 appropriate articles and systematically evaluated and transferred 42 relevant attributes into the database. This GASEMT database provides comprehensive insights into the state-of-the-art of soil- erosion models and model applications worldwide. This database intends to support the upcoming country-based United Nations global soil-erosion assessment in addition to helping to inform soil erosion research priorities by building a foundation for future targeted, in-depth analyses. GASEMT is an open-source database available to the entire user-community to develop research, rectify errors, and make future expansions.

Optimum rates of surface-applied coal char decreased soil ammonia volatilization loss.

Fertilizer N losses from agricultural systems have economic and environmental implications. Soil amendment with high C materials, such as coal char, may mitigate N losses. Char, a coal combustion residue, obtained from a sugar factory in Scottsbluff, NE, contained 29% C by weight. A 30-d laboratory study was conducted to evaluate the effects of char addition on N losses via nitrous oxide (N2 O) emission, ammonia (NH3 ) volatilization, and nitrate (NO3 -N) leaching from fertilized loam and sandy loam soils. Char was applied at five different rates (0, 6.7, 10.1, 13.4, and 26.8 Mg C ha-1 ; char measured in C equivalent) to soils fertilized with urea ammonium nitrate (UAN) at 200 kg N ha-1 . In addition, there were two negative-UAN control treatments: no char (no UAN) and char at 26.8 Mg C ha-1 (no UAN). Treatment applied at 6.7 and 10.1 Mg C ha-1 in fertilized sandy loam reduced NH3 volatilization by 26-37% and at 6.7, 10.1, and 13.4 Mg C ha-1 in fertilized loam soils by 24% compared with no char application. Nitrous oxide emissions and NO3 -N leaching losses were greater in fertilized compared with unfertilized soil, but there was no effect of char amendment on these losses. Because NO3 -N leaching loss was greater in sandy loam than in loam, soil residual N was twofold higher in loam than in sandy loam. This study suggests that adding coal char at optimal rates may reduce agricultural reactive N to the atmosphere by decreasing NH3 volatilization from fertilized soils.

Digital soil mapping in the Bara district of Nepal using kriging tool in ArcGIS.

Digital soil mapping has been widely used to develop statistical models of the relationships between environmental variables and soil attributes. This study aimed at determining and mapping the spatial distribution of the variability in soil chemical properties of the agricultural floodplain lands of the Bara district in Nepal. The study was carried out in 23 Village Development Committees with 12,516 ha total area, in the southern part of the Bara district. A total of 109 surface soil samples (0 to 15 cm depth) were collected and analyzed for pH, organic matter (OM), nitrogen (N), phosphorus (P, expressed as P2O5), potassium (K, expressed as K2O), zinc (Zn), and boron (B) status. Descriptive statistics showed that most of the measured soil chemical variables (other than pH and P2O5) were skewed and non-normally distributed and logarithmic transformation was then applied. A geostatistical tool, kriging, was used in ArcGIS to interpolate measured values for those variables and several digital map layers were developed based on each soil chemical property. Geostatistical interpolation identified a moderate spatial variability for pH, OM, N, P2O5, and a weak spatial variability for K2O, Zn, and B, depending upon the use of amendments, fertilizing methods, and tillage, along with the inherent characteristics of each variable. Exponential (pH, OM, N, and Zn), Spherical (K2O and B), and Gaussian (P2O5) models were fitted to the semivariograms of the soil variables. These maps allow farmers to assess existing farm soils, thus allowing them to make easier and more efficient management decisions and maintain the sustainability of productivity.