Coastal erosion risk assessment of Hainan Island, China

Coastal erosion on islands is increasing due to sea level rise,frequent extreme events,and anthropogenic activities.However,studies on the multifactorial coastal erosion risk and the vulnerability of islands are limited.In this study,the Coastal Erosion Risk Assessment(CERA)method was applied for the first time to the study area in China to assess the erosion risk on the coast of Hainan Island;to explore the effects of coastal ocean dynamics,sediment movement characteristics,and anthropogenic construction;and to discuss the suitability of the method and countermeasures for coastal protection.The results show that the coast of Hainan Island shows high sensitivity,high value,low exposure,and moderate erosion.The whole island showed high vulnerability but low erosion risk,with the eastern region being more affected by erosion,particularly the eastern side of Wulong Port and Yalin Bay in Wenchang,and the shore section of Yalong Bay in Sanya,having a very high risk of coastal erosion.In addition,Monte Carlo simulation was used to check the applicability of the CERA method,and it was found that the rate of shoreline change,population density,and number of storms significantly contributed to coastal erosion,but only the short-term effects of sea level rise were considered.The effects of sea level rise and sediment grain size were primarily analyzed as influencing factors.The effects of sea level rise continue to strengthen,with coastal retreat expected to be greater than 2 m by the mid-21st century.Moreover,Hainan Island is primarily composed of the fine and medium sand types,which have little resistance to coastal erosion.Currently,the impact of sediment grain size is rarely considered in coastal erosion risk assessment studies.However,it can be incorporated into the indicator system in the future,and the spatial variation of indicators can be fully considered to strengthen the refinement study.

Optimal parameter selection for qualitative regional erosion risk monitoring:A remote sensing study of SE Ethiopia

Arid and semi-arid regions are susceptible to high levels of erosion. A rapid and cost effective methodological erosion assessment for these regions is required to describe and monitor the processes that control erosion. This study uses remote sensing to describe the contribution of several factors that control erosion. Topography, land use, vegetation density, soil properties and climatic proxies are used to determine erosion risk and to provide basic maps of water and soil conservation practices. A hierarchical decision tree is used to sum and combine the weight of parameters controlling the erosion. The assigned weights of each spatial unit express the susceptibility to erosion. We focus on the catchment basin of the Maleka Wakena reservoir, located in the southeastern portion of the main Ethiopian Rift, where erosion is the major environmental problem. Three different combinations of the dominant controlling factors are yielded in this study. In order to optimize the qualitative erosion risk assessment, each combination is discussed and evaluated depending on the contribution of parameters involved in the erosion process.

Assessing and mapping soil erosion risk zone in Ratlam District, central India

Evaluation of physical and quantitative data of soil erosion is crucial to the sustainable development of the environment. The extreme form of land degradation through different forms of erosion is one of the major problems in the sub-tropical monsoon-dominated region. In India, tackling soil erosion is one of the major geo-environmental issues for its environment. Thus, identifying soil erosion risk zones and taking preventative actions are vital for crop production management. Soil erosion is induced by climate change, topographic conditions, soil texture, agricultural systems, and land management. In this research, the soil erosion risk zones of Ratlam District was determined by employing the Geographic Information System(GIS), Revised Universal Soil Loss Equation(RUSLE), Analytic Hierarchy Process(AHP), and machine learning algorithms(Random Forest and Reduced Error Pruning(REP) tree). RUSLE measured the rainfall eosivity(R), soil erodibility(K), length of slope and steepness(LS), land cover and management(C), and support practices(P) factors. Kappa statistic was used to configure model reliability and it was found that Random Forest and AHP have higher reliability than other models. About 14.73%(715.94 km^(2)) of the study area has very low risk to soil erosion, with an average soil erosion rate of 0.00-7.00×10^(3)kg/(hm^(2)·a), while about 7.46%(362.52 km^(2)) of the study area has very high risk to soil erosion, with an average soil erosion rate of 30.00×10^(3)-48.00×10^(3)kg/(hm^(2)·a). Slope, elevation, stream density, Stream Power Index(SPI), rainfall, and land use and land cover(LULC) all affect soil erosion. The current study could help the government and non-government agencies to employ developmental projects and policies accordingly. However, the outcomes of the present research also could be used to prevent, monitor, and control soil erosion in the study area by employing restoration measures.

Soil erosion risk evaluation using GIS in the Yuanmou County,a dry-hot valley of Yunnan, China

Soil erosion is a major threat to sustainable agriculture. Evaluating regional erosion risk is increasingly needed by national and in-ternational environmental agencies. This study elaborates a model (using spatial principal component analysis [SPCA]) method for the evaluation of soil erosion risk in a representative area of dry-hot valley (Yuanmou County) at a scale of 1:100,000 using a spatial database and GIS. The model contains seven factors: elevation, slope, annual precipitation, land use, vegetation, soil, and population density. The evaluation results show that five grades of soil erosion risk: very low, low, medium, high, and very high. These are divided in the study area, and a soil erosion risk evaluation map is created. The model may be applicable to other areas of China because it utilizes spatial data that are generally available.

Water erosion risk mapping using derived parameters from digital elevation model and remotely sensed data

The aim of this study is to map the areas exposed to water erosion risks in the High Atlas Mountains of Morocco around the Hassan-I dam.The methodology is based on the analysis of the water power index(WPI)as a hydrological parameter,the vegetation cover,and the litho-logical units.The WPI was derived from a Digital Elevation Model(DEM)and the litho-logical units and vegetation cover were derived from Advanced Land Imager sensor on the Earth Observing-1 satellite platform.The image was corrected from radiometric and atmospheric effects,and geometrically rectified using a DEM and grounds control points.These variables were integrated in a Geographical Information Systems environment,and Multi-Criteria Analyses were used to derive the water erosion risks map pointing out the most exposed areas requiring the implementation of suitable conservation measures.The validation of the obtained results shows the simplicity and the potential of this approach for water erosion risks mapping.

侵蚀地貌公路隧道施工坍塌风险分析

钻爆是采矿和隧道掘进中广泛使用的开挖方法,特别是在硬岩条件下。由于钻爆法施工工序复杂,爆破会造成围岩的扰动,从而导致隧道的坍塌。隧道塌方灾害成为隧道建设中的一个关键问题,必须对其进行充分分析,以防止经济损失和人员伤亡。研究基于量化分级体系和显著影响隧道塌方危险性的影响因素,进行了隧道塌方危险性分析,并根据其风险源提出相对应的处理措施。文章可为后续的地貌相似的公路隧道坍塌提供一些参考。

Development of a landscape index to link landscape pattern to runoff and sediment

Linking landscape indexes to ecological processes is the key topic of landscape ecology.However,traditional landscape metrics based on the Patch-Mosaic Model have no ecological significance.In this study,the runoff-sediment landscape index coupling land use,topography,soil,and vegetation factors was constructed to link landscape patterns to runoff and sediment.In the study area,the runoffsediment landscape index at the class scale showed an increasing trend from 0.10 in 1995 to 0.26 in 2015.Cropland had a higher runoff-sediment landscape index compared to grassland or forestland.At the landscape scale,the runoff-sediment landscape index showed a decreasing trend since 1995;furthermore,it decreased by 36.24%in 2015 compared with the index in 1990.The runoff-sediment landscape index had higher correlations with runoff and sediment compared with traditional landscape metrics.Redundancy analysis showed that the runoffsediment landscape index had a higher contribution to runoff and sediment compared to traditional landscape metrics,explaining 90.1%of the variability.The soil erosion risk assessed by the runoff-sediment landscape index showed an increasing trend upstream of the Dali River watershed.More attention should be paid to this area in future vegetation restoration attempts,as exploring the impact of landscape pattern changes on ecological processes,especially hydrological processes,plays an important role in comprehensive watershed management.

RISK ANALYSIS OF EROSION BELOW THE DAM OF ER TEN PROJECT

The erosion risk below the dam of Er Tan project, which comes from the flood relief of the spillway and mid- dle outlet spillway, is analysed by risk analysis theory. According to the analysis results, it is imperative that the stilling pool below the dam should be adopted to protect river bed from erosion. From the view of risk-protection and economy, the Er Tan project design scheme that adopted the stilling pool is coincident with safe and economical rules. It is efficient and scientific. The erosion risk analysis method used in the paper can be used in other projects. The results are certainly of reference value and great significance for engineering design.

In-depth analysis of soil management and farmers’perceptions of related risks in two olive grove areas in southern Spain

This manuscript presents a questionnaire-based study aimed to provide a detailed analysis on the different soil management carried out by olive farmers in two representative olive-growing areas in southern Spain(Cordoba and Estepa),their perceptions on cover crop use and the possible influence of the different types of farms and farmers’typologies on these perceptions.Our results show a relatively large variability of soil management,with fourteen options,as a result of a combination of different alternatives for bare soil and cover crops with the use or not of pruning residues,but with a great similarity between both areas.The results indicate a high adoption of soil conservation measures in the two study areas,with 63%of farmers using cover crops and 80%a mulch of pruning residues,higher than that reported in previous studies in Southern Spain,and a trend of lower use of these techniques by less experienced and younger farmers.This high penetration of soil conservation measures resulted in a significant reduction of soil erosion risk,as indicated by the relatively low values for the cover and management factor(C)of RUSLE,also calculated and presented in this study,but also the possibility of focusing further efforts on fanners with less experience.Our results indicate the persistence of a minor,but relevant,percentage of farmers using bare soil management(37%)and no mulching(20%),with a moderate concern on the impact of soil erosion on soil degradation and provision of ecosystem services.This suggests the need to concentrate efforts also on this cluster of farmers to enhance the success of what seems to be a remarkable expansion of the use of soil conservation measures in recent decades in Southern Spain,but also in similar areas in the Mediterranean basin.

黄河中游1978-2010年间土壤侵蚀风险的动态监测研究（英文）

Soil erosion has become a significant environmental problem that threatens eco- systems globally. The risks posed by soil erosion, the trends in the spatial distribution in soil erosion, and the status, intensity, and conservation priority level in the middle reaches of the Yellow River Basin were identified from 1978 to 2010. This study employed a multi-criteria evaluation method integrated with GIS and multi-source remote sensing data including land use, slope gradient and vegetation fractional coverage （VFC）. The erosion status in the study region improved from 1978 to 2010; areas of extremely severe, more severe, and severe soil erosion decreased from 0.05%, 0.94%, and 11.25% in 1978 to 0.04%, 0.81%, and 10.28% in 1998, respectively, and to 0.03%, 0.59%, and 6.87% in 2010, respectively. Compared to the period from 1978 to 1998, the area classed as improvement grade erosion increased by about 47,210.18 km2 from 1998 to 2010, while the area classed as deterioration grade ero- sion decreased by about 17,738.29 km2. Almost all severe erosion regions fall in the 1st and 2rid conservation priority levels, which areas accounted for 3.86% and 1.11% of the study area in the two periods, respectively. This study identified regions where soil erosion control is required and the results provide a reference for policymakers to implement soil conservation measures in the future.