Influence of Topographic Conditions on Teak Growth Performance in Mountainous Landscapes of Lao PDR

Teak is a globally valuable hardwood tree species, as its growth performance is important for timber productivity. The purpose of this study was to establish an effective management system for teak plantations in the Lao PDR. Using diameter at breast height (DBH) and height growth as significant indicators of growth performance, we investigated the relationship between tree growth curve parameters of teak and topographic conditions. Stem analysis data for 81 sample trees (three trees selected in canopy trees with predominant height in each plot) were examined for growth performance using the Mitscherlich growth function. The results of Spearman’s partial rank correlation indicated that the upper limits of DBH and tree height growth had significant negative correlations with the slope gradient and stand density. The curvature of DBH and tree height growth curves showed significant positive correlations with the slope form. Moreover, the elevation and slope gradient showed significant negative correlations with the curvature of tree height growth curve. However, the time lag of DBH growth showed a significant negative correlation with the slope position, while the slope gradient was positively correlated with the time lag of tree height growth. These results suggest that teak planted at lower slopes has faster growth rates and that there is an interaction with the gentle concave slope of this area.

Effects of Land Use Land Cover and Slope Gradients on Soil Fertility at Kori Sub-Watershed, East Wollega, Ethiopia

BackgroundThe complex nature of the relationship and interaction between LULC and slope gradients resulted in the decline of soil fertility parameters, which aggravate the reduction of sustainable productivity in Ethiopia in general and the study area in particular. This study was aimed to determine the effects of land use land cover and slope gradients on the physicochemical properties of soil in study area A total of 27 composite soil samples were collected from 0-20cm depth under three dominant adjacent LULC across three slope with three replications. The collected soil samples were analyzed for selected soil physicochemical properties. Two-way ANOVA was used to test the mean differences of the soil fertility parameters. ResultThe mean values of soil physicochemical parameters showed that, SOC, TN, AvP, CEC, exchangeable bases (Ca2+ Mg2+, K+, and Na+), PBS, and percentage of clay contents of cultivated land and steep slope gradient (15-30%) were low and significantly different at (P≤0.05) than forest and grad grassland of the same slope gradient.. The gentle slope (3-8%) gradients of the forest lands had the lowest BD and high TP as compared to the others.ConclusionThe overall soil fertility status of the steep slope gradient (15-30%) of cultivated lands is lower than others and cultivating the steep slope is the cause for productivity loss in the study sub-watershed. Therefore, proper land-use planning and the use of integrated soil fertility management strategy give better production and keep the soil fertility status to a better level.

Application of Artificial Intelligence for Predicting Erosion of Biochar Amended Soils

Recently, incentives have been provided in developed countries by the government for commercial production of biochar for soil treatment, and other construction uses with an aim to reduce a significant amount of carbon emissions by 2030. Biochar is an important material for the development of circular economy. This study aims to develop a simple Artificial Neural Network (ANN) based model to predict erosion of biochar amended soils (BAS) under varying conditions (slope length, slope gradient, rainfall rate, degree of compaction (DoC), and percentage of biochar amendments). Accordingly, a model has been developed to estimate the total erosion rate and total water flow rate as a function of the above conditions. The model was developed based on available data from flume experiments. Based on ANN modelling results, it was observed that slope length was the most important factor in determining total erosion rate, followed by slope gradient, DoC, and percentage of biochar amendment. The percentage of biochar amendment was a leading factor in the total water flow rate determination as compared to other factors. It was also found that the reduction in erosion is relatively minimal during an increase in slope length up to 1.55 m, reducing sharply beyond that. At a slope length of 2 m, erosion is found to be reduced by 33% (i.e., 2.6 to 1.75), whereas the total flow rate decreases linearly from 1250 mL/m2/min to 790 mL/m2/min. The ANN model developed shows that soil biochar composite (SBC) with 5% biochar amendment gave the best results in reducing soil erosion. This study can be a helpful tool in providing preliminary guidelines for using biochar in erosion control.

Assessment of Erosion Characteristics in Purple and Yellow Soils Using Simulated Rainfall Experiments

Soil erosion of sloped lands is one of the important sources of substantive sediments in watersheds. In order to investigate erosion characteristics of sloped lands during rainfall events in the Three Gorges Reservoir Area, erosion processes of purple and yellow soils under different slope gradients and rainfall intensities were studied by using a rainfall simulator. The results showed that the sediment concentration in runoff was closely correlated with rainfall intensity. The sediment concentration in runoff gradually rose to a peak with time, and then gradually declined and approach a steady rate during simulation rainfall events. The particle size distribution of surface soils before the rainfall was different from that after the rainfall. Soil erosion mainly resulted in the loss of fine particles of surface soil through runoff, and the fine particles of soil were enriched in sediments. Soil erosion rates were gradually increased with the slope gradient when the slope gradient was less than 10°, and significantly increased when the slope gradient was more than 10°. The slope factor of yellow soil could be fitted well to that calculated by the formula of Universal Soil Loss Equation (USLE). The trend of the slope factor of purple soil was similar to that of the slope factor that was derived from USLE. Therefore, the effect of slope gradients on soil erosion need to be further researched when USLE was applied to predict erosion in purple soil area.

Risk Assessment of Runoff Generation Using Artificial Neural Network and Field Plots in The Area of Roads and Forest Lands

Runoff generation potential (RGP) on hillslopes is an important issue in the forest roads network monitoring process. In this study, the artificial neural network (ANN) was used to predict RGP in forest road hillslopes. We trained, optimized, and tested the ANN by using field plot data from the Shirghalaye watershed located in the southern part of the Caspian Sea (Iran). 45 plots were installed to measure actual runoff volume (RFP) in different environmental conditions including land cover, slope gradient, soil texture, and soil moisture. A multi-layer perceptron (MLP) network was implemented. The runoff volume was the output variable and the ground cover, slope gradient, initial moisture of soil, soil texture (clay, silt, and sand percentage) were the network inputs. The results showed that ANN can predict runoff volume within the values of an appropriate level in the training (R2=0.95, MSE= 0.009) and test stages (R2=0.80, MSE= 0.01). Moreover, the tested network was used to predict the runoff volume on the forest road hillslopes in the study area. Finally, an RGP map was generated based on the results of the prediction of the ANNs and the GIS capabilities. The results showed that using both an ANN and a GIS is a good tool to predict the RGP in the forest road hillslopes.

Mechanism and Evolution of Soil Organic Carbon Coupling with Rocky Desertification in South China Karst

To study the spatial distribution characteristics of soil organic carbon (SOC) coupled with rocky desertification, 1212 soil samples from 152 soil profiles were sampled from different karst landforms, including karst low hills/virgin forest (KLH) in Libo County, a karst peak-cluster depression (KPCD) in Xingyi County, a karst canyon (KC) in Guanling County, a karst plateau basin (KPB) in Puding County and a karst trough valley (KTV) in Yinjiang County. The spatial distribution characteristics of the responses of SOC, SOC density (SOCD), rocky desertification and soil bulk density (SBD) to different influencing factors were analyzed. The relationships among SOC, SOCD, rocky desertification and SBD were analyzed using Pearson correlation analysis. The SOC storage capacity was characterized by using SOCD, and then the SOC storage capacity in different evolution stages of karst landforms was assessed. The SOC contents of KLH, KPCD, KC, KPB and KTV ranged from 6.16 to 38.20 g·kg−1, 7.42 to 27.08 g·kg−1, 6.28 to 35.17 g·kg−1, 4.62 to 23.79 g·kg−1 and 5.24 to 37.85 g·kg−1, respectively, and their average SOCD values (0–100 cm) were 7.37, 10.79, 7.06, 8.51 and 7.84 kg·m−2, respectively. The karst landforms as ordered by SOC storage capacity were KPCD > KPB > KLH > KTV > KC. The SOC content was negatively correlated with the SBD; light rocky desertification may lead to SOC accumulation. The rocky desertification degree and SBD were closely associated with slope position and gradient. Rocky desertification first increased, then decreased from mountain foot to summit, and increased with increasing slope gradient. However, the SBD decreased from mountain foot to summit and with increasing slope gradient. The SOC contents on the northern aspect of the mountains were generally higher than the other aspects. In summary, rock outcrops controlled the SOC contents in the studied regions. The slope position, gradient and aspect influenced the composition and distribution of vegetation, which influenced the evolution of rocky desertification. Therefore, these factors indirectly affected the SOC content. Additionally, the SOCD decreased with increasing rocky desertification. During the different evolution stages of karst landforms, the SOC storage capacity first decreases, then increases.

Pengaruh Kemiringan Lereng terhadap Kerusakan Tanah di Giritontro, Wonogiri

The Effect of Slope Gradient of land on the Soil Damage in Giritontro, Wonogiri. Soil degradation is one of the problems in agriculture that affects the level of quality and carrying capacity of the soil for certain land uses. This study aims to analyse the status of soil degradation, the effect of slope, the determinant factor, and recommendation for land management.It was conducted in Giritontro District, Wonogiri Regencywith survey methods by field verification, taking soil samples and laboratoryanalysis based on Regulation of The Government of Indonesia Number 150 of 2000. Analysis unit is land map unit (LMU) which obtained from an overlay of mapssoil types, slope, rainfall, and land use. There were 12 LMU, and repeated 3 site samplings in each it. The result shows that the status of soil degradation was classified as slightly degraded (R.I) in all area research of 5.016.37 ha. The slope has a very significant effect on soil degradation. Slope 26-40% has significant highest score of soil degradration. Determinant factors were soil bulk density and porosity, therefore giving organic matter and optimizing tillage were recommended to improve land quality.

The Effect of Rainfall, Soil Type and Slope on the Processes and Mechanism of Rainfall-Induced Landslide

Landslides are serious geological hazards that become a disaster worldwide, causing a large number of casualties and economic losses every year. There are many factors affecting landslide susceptibility, such as rainfall, soil and slope. Each of them has an important role in the process of slope losing stability. In this paper, the effects of rainfall intensity, rainfall pattern, slope gradient and soil type on landslide susceptibility are studied. In the process of rainfall-induced landslide, the relevant physical quantities of soil changes continuously. Their values and processes are closely related to the time of landslide occurrence. Hence, the variation of soil volumetric water content, matrix suction, pore water pressure and total stress throughout the rainfall are measured. As the results, soil type, slope gradient and rainfall intensity have a large influence on landslide susceptibility. The occurrence of landslides has a prerequisite that the slope is greater than or equal to 15°. The rainfall intensity needs to be not less than 80 mm/h. The difference of rainfall pattern also affects the landslide susceptibility. The rainfall pattern with rainfall intensity peak at the later stage is more likely to induce landslide. Coarser soils with gravels are prone to landslides when other conditions are the same. Steeper slopes, stronger rainfall, and coarser soils can all increase the amount of sediment yield.

Impact of Data Processing and DTM Resolution on Determining of Small Erosional Landforms

Small erosional landforms are characterised by a dynamics closely related to the occurrence and changes in precipitation and water flowing down the slopes. Triggered by water, the erosion processes are controlled by the other environmental conditions like slope gradient, lithology, land cover and land use. Studying the changes in the topography gives information about the spatiotemporal dynamics of erosion and can contribute to a more effective assessment of erosion susceptibility and mitigation measures at the earliest stage of the process development. Usually in the initial stages, the changes in the topography are hardly noticeable and using high resolution digital terrain models (DTMs) is of high importance. In this relation, the aim of the current research is to determine to what extent the resolution of the models influences the results of delineating the flow lines, rills and gullies. For this purpose, a terrain survey was carried out and data was acquired by UAS (uncrewed aerial system) DJI Phantom 4RTK. DTMs in horizontal resolution of 0.05, 0.1, 0.2, 0.5 and 1 m are created and analysed. Special attention is given to the analysis of surface curvature as an indicator for flow convergence and divergence. The research is done on a slope area covered mainly by grass and some rare bushes and trees. Despite the observed variations, the results show a general trend of decrease in the flow length with decreasing DTMs resolution. Considering the plan curvature and concave areas, the differences are smallest between the models with cell size 0.1 and 0.2 m.