Soil Erosion Rates Research Articles

Does soil thinning change soil erodibility? An exploration of long-term erosion feedback systems

Abstract. Soil erosion rates on arable land frequently exceed the pace at which new soil is formed. This imbalance leads to soil thinning (i.e. truncation), whereby subsoil horizons and their underlying parent material become progressively closer to the land surface. As soil erosion is a selective process and subsurface horizons often have contrasting properties to the original topsoil, truncation-induced changes to soil properties might affect erosion rates and runoff formation through a soil erosion feedback system. However, the potential interactions between soil erosion and soil truncation are poorly understood due to a lack of empirical data and the neglection of long-term erodibility dynamics in erosion simulation models. Here, we present a novel model-based exploration of the soil erosion feedback system over a period of 500 years using measured soil properties from a diversified database of 265 agricultural soil profiles in the UK. For this, we adapted the Modified Morgan–Morgan–Finney model (MMMF) to perform a modelling experiment in which topography, climate, land cover, and crop management parameters were held constant throughout the simulation period. As selective soil erosion processes removed topsoil layers, the model gradually mixed subsurface soil horizons into a 0.2 m plough layer and updated soil properties using mass-balance mixing models. Further, we estimated the uncertainty in model simulations with a forward error assessment. We found that modelled erosion rates in 99 % of the soil profiles were sensitive to truncation-induced changes in soil properties. The soil losses in all except one of the truncation-sensitive profiles displayed a decelerating trend, which depicted an exponential decay in erosion rates over the simulation period. This was largely explained by decreasing silt contents in the soil surface due to selective removal of this more erodible particle size fraction and the presence of clayey or sandy substrata. Moreover, the soil profiles displayed an increased residual stone cover, which armoured the land surface and reduced soil detachment. Contrastingly, the soils with siltier subsurface horizons continuously replenished the plough layer with readily erodible material, which prevented the decline of soil loss rates over time. Although our results are limited by the edaphoclimatic conditions represented in our data, as by our modelling assumptions, we have demonstrated how modelled soil losses can be sensitive to erosion-induced changes in soil properties. These findings are likely to affect how we calculate soil lifespans and make long-term projections of land degradation.

Increased precipitation weakenes the positive effect of vegetation greening on erosion

Soil erosion is a major global soil degradation problem that threatens land, freshwater and oceans. Rainfall erosivity has led to an increasing in the global soil erosion rate, while vegetation restoration is a safeguard measure to reduce soil erosion. Therefore, probing the influence of precipitation and vegetation on the spatial distribution of soil erosion is important for understanding the mechanism of erosion. In order to assess the degree of global soil erosion, based on the RUSLE model, a global soil erosion data set from 2000 to 2015 (0.25°× 0.25°) was created, showing that soil erosion was increasing in 70.80% of the study area, where precipitation was the dominant factor. Different grades of erosion showed that the soil erosion area of mild and above mild erosion increased by 44.88 106 ha, an increase of 5.39%. Spatial erosion is mainly distributed in Asia and North America. The difference from North America is that the erosion in Asia showed a decreasing trend during the study period. Different climatic zones show that erosion mainly occurs in the temperate zone, accounting for 39.97% of the area. Precipitation and vegetation increasing significantly in 24.43% and 16.74% of the regions. However, the proportion of regions where precipitation and vegetation had a negative contribution to erosion was 29.12% and 53.81%. Above results will deepen our understanding of the mechanism of erosion.

Soil erosion affected by trees in a tropical primary rain forest, Papua New Guinea

Trees have the ability to distinctly determine soil evolution and hillslope processes through mechanical soil disturbances such as tree uprooting. Recent findings have resulted in new biogeomorphic state transition models for old-growth forests in the temperate climate zone. The situation in tropical forests, however, is mostly unknown. Here, we focus on determining short- (decades) and long-term (millennia) soil erosion rates and the biogeomorphic role of trees on hillslope dynamics in the species-rich Wanang primeval tropical forest, Papua New Guinea. We hypothesized that trees play a significant role in hillslope dynamics on a background of powerful soil erosion dominated by abiotic factors, and that this role has potentially intensified over the last decades.The long-term soil erosion was assessed using the meteoric 10Be levels in three soil profiles along the whole depth gradient along with one natural outcrop. The recent soil erosion rate was determined using 239+240Pu levels in the uppermost soil layers. The specific role of trees in hillslope processes was evaluated based on repeated tree censuses of 65,535 tree individuals, calculating the tree mortality rate and modeling the soil volume affected by uprooted trees and by the in situ decay of the root systems of broken trees.Soil erosion was 6.25 m3 ha−1 yr−1 over the long term and indeed did increase during the last decades. While this rate was significantly affected by trees, they were not the main factor, with circa 0.95 m3 ha−1 influenced annually by uprooting, and an additional 0.61 m3 ha−1 by the in situ decay of root systems. These results reflect a forest ecosystem that is currently in the biogeomorphic stage of biotic/abiotic feedbacks.

Estimation of soil erosion for a semi-urban watershed in Tamil Nadu, India using RUSLE and geospatial techniques

Soil erosion is basically the land degradation form, which is the natural process that affects landuse (LU), agricultural productivity, soil fertility, and water availability. The present investigation aims the multi-temporal average annual soil loss of the Manimuthanadhi sub-watershed utilizing RUSLE (revised universal soil loss equation), Remote Sensing (RS) and geographical information system (GIS). The annual average soil loss has been predicted for the combined impact of rainfall and LU changes. The rainfall erosivity factor (R) generated for the years 2004 (dry), 2009 (normal) and 2010 (wet) and the corresponding period cover management (C) factor map also derived. The results revealed that the mean annual soil erosion rate of 54.50 t ha−1 yr−1 in 2004. Soil erosion in 2009 is remarkably increased to 96.5 and 87.7 t ha−1 year−1 was observed in 2010 which is lower than in 2009. The erosion risk in the region increased by 43.52% from 2004 to 2009, whereas it reduced by 25.97% from 2009 to 2010. Further, the Prioritization analysis was carried out to identify the critical watershed, based on the results, Sub-watershed numbers 2, 6, and 8 were identified as very critical stages and require some conservation practices to control and manage soil erosion.

Sustainability Analysis of Soil Erosion Control in Rwanda: Case Study of the Sebeya Watershed

Soil erosion is a complex process that results in soil and fertility losses from agricultural land and, ultimately, leads to river sedimentation. This study aimed to assess various influential factors and processes affecting soil erosion and to recommend suitable site-based Soil Erosion Control Measures (SECM) for sustainable agriculture while minimizing the downstream rivers and reservoir sedimentation in the Sebeya watershed of Rwanda. The present research used a literature review, site visits, and focus groups to assess various SECM within the Sebeya watershed. As a result, various site-based SECM were evaluated, recommended, and simulated to alleviate high soil loss rates in the Sebeya watershed using the Universal Soil Erosion Equation (USLE) model. Simulating existing and proposed SECM, soil loss was reduced significantly from 73 t/ha/y to 29 t/ha/y. To highlight the implication of the site-based recommended SECM in improving agricultural productivity, this study suggests field investigations in soil erosion plots and prediction of crop yields from an established linear correlation model between soil loss and crop yields in the Sebeya watershed. For effective action in reducing high soil erosion rates to tolerable rates in the Sebeya watershed, the present research recommends implementing the site-based recommended SECM with mulching and drainage channels on the same farmland. However, lack of money and knowledge are the main limitations in implementing SECM in the Sebeya watershed. Therefore, governmental and non-governmental organizations should technically and financially help farmers in the Sebeya watershed.

Predicting Soil Erosion Rate at Transboundary Sub-Watersheds in Ali Al-Gharbi, Southern Iraq, Using RUSLE-Based GIS Model

The empirical soil loss model, RUSLE, was used in conjunction with remotely sensed data and geographic information system technology to delineate the soil erosion and watershed priorities in terms of conservation practices at seven boundary sub-watersheds (labeled as SW-00, SW-01, …, SW-06) between Iraq and Iran in the district of Ali Al-Gharbi, southern Iraq. The six factors of the RUSLE model, i.e., the rainfall erosivity, the soil erodibility, the slope steepness length, the crop management, and management practice, were calculated or estimated using information from different data sources such as remotely sensed data and previous studies. The results revealed that the annual soil erosion loss ranges from 0 to 1890 (tons h−1 y−1) with an average of 0.66 (tons h−1 y−1). Values of soil erosion were classified into five classes: very low, low, moderate, high, and very high. The potential soil loss in the high and very high classes ranges from 14.84 to 1890 (tons h−1 y−1), and these classes occupy only 27 km2 of the study area, indicating that the soil loss is very low in the area being examined. In terms of the spatial distribution of soil loss, the northern and northeastern parts (mountains and hills) of the sub-watersheds where the slope is steeper are more likely to erode than the plain area in the southern and southeastern portions, indicating that slope, in addition to rainfall erosivity, has a dominant effect on the soil erosion rate. The study of soil erosion in the watersheds under consideration reveals that only the northern portions of the SW-00, SW-02, and SW-04 watersheds require high priority conservation plans; however, these portions are primarily located in mountain regions, making the implementation of conservation plans in these areas impractical. Due to low soil loss, other sub-watersheds, particularly SW-01, SW-03, SW-05, and SW-06, are given low priority.

Spatial Modeling of Vegetation Cover for Soil Erosion Control Based on Arc GIS and the RUSLE Models

Deforestation in the Serayu watershed, Central Java province, Indonesia for agriculture and other uses leaves only 0.73% of vegetation. It has triggered a number of problems such as soil loss (erosion), landslides, floods and sedimentation downstream. Environmental damage control needs to be applied through appropriate conservation programs. This study aims to understand the distribution of soil erosion and the effectiveness of soil erosion control by using vegetation cover. Soil erosion modeling and its correlation to vegetation cover was performed by using an Arc GIS based model of the Revised Universal Soil Loss Equation (RUSLE) through five scenarios of vegetation landscape cover such as 10%, 15%, 20%, 25%, and 30% of the total area of the study site. Five parameters namely rain erosivity (R), soil erodibility (K), slope-length (LS) and crop management (C) and conservation practices (P) factor were used to calculate soil erosion. The results indicated 82.25 tons/ha/year soil erosion reduction due to enhancement of vegetation cover from the actual condition 0.73% to the 30% vegetation cover condition. The increase of 5% vegetation landscape cover (forest) detracted the soil erosion rate by 10,20 tons /ha/year. Very high and high soil erosion hazard levels were found in the northern, east, and west watershed areasKeywords: Soil erosion, RUSLE model, GIS, Serayu watershed, Vegetation cover

The Influence of Ecological Environment Protection Mechanism on the Economic Development and Management Mechanism of Rural Enterprises

<p>The purpose is to analyze the economic development and management mechanism of rural enterprises, and explore the role of ecological environment protection mechanism in the economic development of rural enterprises. First, the related theories are analyzed and expounded; then, the participants of rural enterprise economy are analyzed, and the evaluation index system of rural enterprise economy is established. The economic and management mechanism of rural enterprises under the ecological environment protection mechanism is analyzed by using the model projection pursuit evaluation model under the real coded accelerated genetic algorithm. The results show that the ecological index coefficients are 0.0856, 0.1334, 0.1977, 0.2123 and 0.2543 respectively. In addition, the ecological economic index are 0.1932, 0.2168, 0.2693, 0.2168 and 0.1933. Irrigation level, effective control of soil erosion rate and forest coverage exert a significant impact on the economic development and management mechanism of rural enterprises; the small per capita water resources index indicates that it is essential to improve the water cycle; the occurrence rate of agricultural natural disasters exerts little influence on the development of agricultural circular economy, indicating that the ability of agriculture to resist natural disasters still needs to be improved. To sum up, this exploration can provide reference for the sustainable development of rural enterprise economy.</p>

Spatial distribution of soil erosion and its impacts on soil productivity in Songnen typical black soil region

Soil erosion is an important reason for land degradation. The black soil region of Northeast China is the main grain production base in China, however, the black soil productivity in this region is at risk and unsustainable now because there was few soil conservation measures in nearly 100 years of cultivation. To assess the impact of erosion on land productivity, both 210 sampling points for 137Cs measurement and 112 sampling points for soil profile features were laid out on cultivated land of Songnen typical black soil region in combination with the 2010 China land use map. The current soil erosion/deposition rate and land productivity index PI were calculated over the study area, and then the PI values were predicted erosion by 20, 50, 100, and 200 years without soil and water conservation measures based on the current erosion rate and soil profile characteristics. The results showed that the average soil erosion rate of cultivated land in the study area was 705.8 t/(km2⋅a), and 77.0% of the cultivated land had soil erosion rate larger than the soil loss tolerance of 200 t/(km2⋅a). Spatially, the soil erosion rate in the northern region was greater than that in the southern region significantly, which was mainly affected by slope steepness. The relationship between soil erosion rate (SL) and slope steepness (θ) in degree was established according to the results of 137Cs measured at 210 sample points: SL = 556.4∗θ or SL = 0.464∗θ in mm/a (given soil bulk density is 1200 kg/m3). The current mean value of PI for cultivated land was 0.59, decreasing significantly from north to south, which was mainly influenced by organic matter content. The predicted PI values decreased significantly with the increase of erosion years in the northern area. This is related to the topography of rolling and hills in the northern area with a greater soil loss rate, leading to a rapid decrease of organic matter content and the increase of sand content in the topsoil in the future. The spatial distributions of the current soil erosion rates and predicted PI values after years of erosion for cultivated land would be helpful for soil conservation policy-making.

Simulation of Rainfall Erosivity Dynamics in Romania under Climate Change Scenarios

Soil erosion is triggered by rainfall through the detachment of soil particles and their transport downslope, playing a key role in soil erosion models. Together with the vegetation cover, rainfall is a temporal dynamic factor, inducing corresponding time variations of erosion rates. Under current climate change, rainfall is also changing its characteristics and our study aimed to reveal whether these changes will significantly affect rainfall erosivity in Romania, and implicitly the soil erosion. To achieve this purpose, we developed a statistical non-parametric model for predicting rainfall erosivity on the basis on the modified Fournier index and applied it to future precipitation evolution scenarios. The precipitation data were extracted from the CHESLA database for the Romanian territory for two climate change contrasting scenarios (RCP 4.5 and 8.5). Average predictions from five selected climate models were used in order to minimize prediction uncertainty. The results show that rainfall erosivity is likely to increase, at least during the 2041–2060 period, especially in the south-western, western and eastern part of the country, which may cause a corresponding increase in soil erosion rates, with an average of 1–2 t ha−1 yr−1. During the 2061–2080 period, rainfall erosivity is likely to decrease in central and eastern Romania.

Soil Constraints in an Arid Environment—Challenges, Prospects, and Implications

Climate models project that many terrestrial ecosystems will become drier over the course of this century, leading to a drastic increase in the global extent of arid soils. In order to decrease the effects of climate change on global food security, it is crucial to understand the arid environment and the constraints associated with arid soils. Although the effects of aridity on aboveground organisms have been studied extensively, our understanding of how it affects soil processes and nutrient cycling is lacking. One of the primary agricultural constraints, particularly in arid locations, is water scarcity, due to which arid soils are characterized by sparse vegetation cover, low soil organic carbon, poor soil structure, reduced soil biodiversity, and a high rate of soil erosion via wind. Increased aridity will limit the availability of essential plant nutrients and crop growth, and subsequently pose serious threats to key ecological processes and services. The increasing rate of soil salinization is another major environmental hazard that further limits the agricultural potential of arid soils. These soil constraints can be ameliorated and the crop yields increased through case-specific optimization of irrigation and drainage management, enhancing the native beneficial soil microbes, and combinations of soil amendments, conditioners, and residue management. This review explores technologies to ameliorate soil constraints and increase yields to maintain crop output in arid soils.

Riverscape Approach and Forestry Interventions for Ganga River Rejuvenation

Rivers have been degraded globally due to various reasons over centuries and limiting their ecological health and value, including Ganga River in India. Riverscape approach can provide relevant information on riverine resources needed in river restoration programmes. We propose a conceptual riverscape model to rejuvenate the holy river Ganga in India through forestry interventions after due consideration of ecological processes, mosaic of landforms, communities and environment within the large landscape of Ganga basin. The select riverscape area includes the area of 5 km and 2 km on either side of the river Ganga and important tributaries, respectively, all along the rivers in five stakeholder states of Uttarakhand, Uttar Pradesh, Bihar, Jharkhand, and West Bengal in the country. The width of the riverscape was taken from the maximum bank line in recent years on either side of river in the concerned state. However, all micro-watersheds in the hills of Uttarakhand state, being the origin place of river, have been included in riverscape area up to Haridwar. Here riverscape is a mosaic of different land uses viz., natural ecosystems, rural and agricultural ecosystems and built-up urban environment including flood plain and is an ecologically sustained system developed during the last 30 years due to river meandering all along the river. Geospatial modelling and GIS data on land use pattern, soil erosion rates, slope of the topography, etc. were used to classify riverscape area into high, medium and low priority areas to implement forestry interventions in delineated riverscape. Thereafter, forestry interventions were planned and carried out in three identified landscapes viz., Natural (forests), Agriculture (agroforestry), and Urban along with conservation activities. Forestry interventions in delineated riverscape are expected to increase water recharge and decrease the sedimentation load in the Ganga River and its tributaries.

SOIL EROSION ASSESSMENT WITH INVEST MODEL: CASE STUDY IN WEE-OYA WATERSHED IN SRI LANKA

Human-induced soil erosion is one of the most significant types of land degradation in the Wee Oya watershed in Sri Lanka. The high intensity of rainfall, steep slopes, and inappropriate land use practices are strongly associated with soil erosion in the area. The prime aim of the study was to estimate soil erosion in the watershed and its seven sub-watersheds using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST), Sediment Delivery Ratio (SDR) model. Furthermore, a comprehensive household (HH) questionnaire survey (n=30) was conducted to ascertain key socio-economic information such as the farmer’s age, gender, education level, the extent of land for cultivation, and the degree of practicing soil and water conservation (SWC) measures. Then, the multiple regression analysis was applied to determine the significant socio-economic determinants of erosion in the watershed. The results of the assessment disclosed that the present average annual rate of human-induced soil erosion of the watershed is 167 t/ha/yr. Moreover, the most significant (p<0.05) socio-economic determinants of the soil erosion of the study area are the farmer’s age and family size. Furthermore, the study revealed that more than 50% of the farmers do have not a substantial perception of existing government policies’ implications concerning human-induced soil erosion. Finally, the outcome of the assessment has highlighted the necessity of human intervention for effective SWC measures in the study area.

SOIL EROSION BY HAND TOOLS FOR SMALL-SCALE TILLAGE ON HILLSLOPES ASSESSED THROUGH THE UNIVERSAL SOIL LOSS EQUATION

The objective of this study was to evaluate and compare the erosion rates generated by two types of hand tools for small-scale tillage on a hillslope, using experimental tests and the Universal Soil Loss Equation (USLE). The hand tools evaluated were a conventional hoe and a redesigned furrowing hoe. The experimental work was conducted in a 145 m2 plot with an average slope of 45% in Colombia. Three treatments were evaluated: a) Zero tillage and no herbicide (control); b) tillage with a conventional hoe plus herbicide; c) tillage with a furrowing hoe plus herbicide. Each treatment was represented by a sedimentation plot, using three repetitions in blocks (lower, middle, and upper parts of each plot), according to the maximum slope gradient. Both hand tillage tools generated high to extremely high erosion rates with differences of up to 8.1 times between them. Both types of tools accelerated soil erosion rates, being higher in furrowing hoe tillage. The USLE method showed no differences in erosion rates between the tillage methods, while differences were found in the experimental tests. This is explained by the lower sensitivity of the USLE to detect small-scale changes in factors such as soil type, cover, and slope.

Soil erosion prediction and risk assessment using RUSLE model and GIS techniques in the Nangka watershed

Soil erosion in the Nangka watershed has always been a matter of concern. Over the last decade, soil erosion has led to continuous environmental problems. A thorough examination of the extent of the problem was required to identify an appropriate soil conservation strategy within the watershed. This study was conducted to observe erosion rates and map out the erosion hazard level. Erosion predictions were analysed by using the Revised Universal Soil Loss Equation (RUSLE) model with the help of ArcGIS software. RUSLE was selected because of its quantitative ability to estimate average annual soil erosion and its compatibility with the GIS interface. The potential hazard of soil erosion was classified and ranked into five class categories as set by the national authority. The results reveal that the Nangka watershed is prone to soil erosion with the annual average values ranging from 1.33 Mg·ha –1·y –1 to 2472.29 Mg·ha –1·y –1. High soil erosion rates of 9.8% are in severe (class IV) and very severe (class V) conditions, primarily in the upper course of the watershed. The low annual average of soil erosion (class I and class II), which accounted for 75.95% of the total erosion, mostly took place in the steepness below 35%. The remaining area of 14.25% within the watershed is in moderate condition (class III). It is expected that the results of this study will help the authority in the implementation of soil conservation measures.

Soil Erosion under Future Climate Change Scenarios in a Semi-Arid Region

The Mediterranean Region is presumed to be one of the locations where climate change will have the most effect. This impacts natural resources and increases the extent and severity of natural disasters, in general, and soil water erosion in particular. The focus of this research was to assess how climate change might affect the rate of soil erosion in a watershed in the High Atlas of Morocco. For this purpose, high-resolution precipitation and temperature data (12.5 × 12.5 km) were collected from EURO-CORDEX regional climate model (RCM) simulations for the baseline period, 1976–2005, and future periods, 2030–2060 and 2061–2090. In addition, three maps were created for slopes, land cover, and geology, while the observed erosion process in the catchment was determined following field observations. The erosion potential model (EPM) was then used to assess the impacts of precipitation and temperature variations on the soil erosion rate. Until the end of the 21st century, the results showed a decrease in annual precipitation of −32% and −46% under RCP 4.5 for the periods 2030–2060 and 2061–2090, respectively, −28% and −56% under RCP 8.5 for the same periods, respectively, and a large increase in temperature of +2.8 °C and +4.1 °C for the RCP 4.5 scenario, and +3.1 °C and +5.2 °C for the RCP 8.5 scenario for the periods 2030–2060 and 2061–2090, respectively. The aforementioned changes are anticipated to significantly increase the soil erosion potential rate, by +97.11 m3/km2/year by 2060, and +76.06 m3/km2/year by 2090, under the RCP 4.5 scenario. The RCP 8.5 predicts a rise of +124.64 m3/km2/year for the period 2030–2060, but a drop of −123.82 m3/km2/year for the period 2060–2090.

Integration of GIS and Remote Sensing with RUSLE Model for Estimation of Soil Erosion

Globally, soil erosion is a significant problem contributing to nutrient loss, water quality degradation, and sand accumulation in water bodies. Currently, various climate factors are affecting the natural resources entire worldwide. Agricultural intensification, soil degradation, and some other human impacts all contribute to soil erosion, which is a significant issue. Management and conservation efforts in a watershed can benefit from a soil erosion study. Modeling can establish a scientific and accurate method to calculate sediment output and soil erosion below a variety of circumstances. The measured soil loss tolerance was compared to the risk of soil erosion (T value).In this study, GIS and remote sensing techniques have been integrated with the Revised Universal Soil Loss Equation (RUSLE) model to estimate soil loss in the Mayurakshi river basin of eastern India. To determine soil erosion-prone areas, rainfall, land use, and land cover maps, as well as a digital elevation model (DEM), were used as input. The annual soil loss in the basin area is estimated to be 4,629,714.8 tons. Accordingly, the study basin was categorized into five soil loss severity classes: very low (40.92%), low (49%), moderate (6.5%), high (2.4%) and very high (1.18%) risk classes. Soil erosion rates ranged from very slight to slight throughout the majority of the region. The section of the basin’s lower plain has been discovered to be least affected by soil loss. The results of study area can be helpful to conservation of soil management practices and watershed development program in the basin area.

Evaluation of the Impact of Land Use Changes on Soil Erosion in the Tropical Maha Oya River Basin, Sri Lanka

Soil degradation is a serious environmental issue in many regions of the world, and Sri Lanka is not an exception. Maha Oya River Basin (MORB) is one of the major river basins in tropical Sri Lanka, which suffers from regular soil erosion and degradation. The current study was designed to estimate the soil erosion associated with land use changes of the MORB. The Revised Universal Soil Loss Equation (RUSLE) was used in calculating the annual soil erosion rates, while the Geographic Information System (GIS) was used in mapping the spatial variations of the soil erosion hazard over a 30-year period. Thereafter, soil erosion hotspots in the MORB were also identified. The results of this study revealed that the mean average soil loss from the MORB has substantially increased from 2.81 t ha−1 yr−1 in 1989 to 3.21 t ha−1 yr−1 in 2021, which is an increment of about 14.23%. An extremely critical soil erosion-prone locations (average annual soil loss > 60 t ha−1 yr−1) map of the MORB was developed for the year 2021. The severity classes revealed that approximately 4.61% and 6.11% of the study area were in high to extremely high erosion hazard classes in 1989 and 2021, respectively. Based on the results, it was found that the extreme soil erosion occurs when forests and vegetation land are converted into agricultural and bare land/farmland. The spatial analysis further reveals that erosion-prone soil types, steep slope areas, and reduced forest/vegetation cover in hilly mountain areas contributed to the high soil erosion risk (16.56 to 91.01 t ha−1 yr−1) of the MORB. These high soil erosional areas should be prioritized according to the severity classes, and appropriate land use/land cover (LU/LC) management and water conservation practices should be implemented as recommended by this study to restore degraded lands.

Sequential Extraction of 239+240Pu and the Vertical Distribution of 239+240Pu, 137Cs, and Heavy Metals in Chang-Bai Mountains’ Grassland Soil

To establish a 239+240Pu, 137Cs, and heavy metal reference soil site in Northeast China, three grassland soil cores were collected from the Lao-Ye-Ling Mountain, which is a branch of the Chang-Bai Mountains. The activities were in the range of 0.041–2.752 mBq/g for 239+240Pu and in the range of 0.2–57.6 mBq/g for 137Cs. The 240Pu/239Pu atomic ratios were 0.161–0.186, showing that 239+240Pu in the study area originated from the global fallout. Also, 239+240Pu, 137Cs, and excess 210Pb were enriched in the surface soil. The convective–dispersion equation model provided the lower apparent dispersion coefficients (D) and apparent convection velocities (v) for both 239+240Pu and 137Cs. The soil erosion rate in this study area was estimated by an erosion model, which was lower than that in the other area of Northeast China. 239+240Pu in the different soil fractions was analyzed by a sequential extraction method, and the result showed that 239+240Pu was mainly adsorbed by Fe/Mn oxides and their associated organic matter (NOMFe/Mn-oxides fraction). Except for Fe, all other heavy metals from the anthropogenic source were enriched in the surface soil. The pollution level of heavy metals in this study area was lower. In general, the alpine grassland soil of the Lao-Ye-Ling Mountain can be used as a reference soil site to study environmental pollution and soil erosion and provided some reference baselines for future multidisciplinary studies in Northeast Asia.

Analyzing Water Poverty Components Using Geospatial Tools: Resource and Environmental Constraint in Kathmandu District

This current paper examines water poverty situation in Kathmandu district in terms of water resource and environment constraints. Integrated methodology was adopted for the study. Water source sample survey was carried out using GPS tool. Study area comprised total of 13 water sample sites. Household questionnaire survey was carried out for water poverty mapping and analysis. Resource component of water poverty comprised indicators, namely seasonal variation in water availability, water supply frequency and groundwater recharge potential. The environment constraint component comprised water quality rate of soil erosion and topographic wetness index. The result show that the average calculated value of water resource limitation component is 6.31 and out of 13 studied communities, 7 communities fall below average. It is found that environmental constraint is less associated with urban housing density. It is found that environmental constraint is less associated with urban housing density. The average calculated value of environmental component is 3.43 and out of 13 studied communities, 8 communities fall below average. Spatial variability in water poverty is prominent and highest water poverty is found in urban cores. Communities with lower water poverty are found in peri-urban location near the foothills. The average calculated value of water poverty is 9.74 and out of 13 studied communities, 9 communities fall below the average. The study concluded that water poverty index and resultant map is a very effective tool to visualize the distribution of water poverty at local spatial scale and to present the complex nature of water poverty.