Evaluation of indicators for desertification risk assessment in part of Thar Desert Region of Rajasthan using geospatial techniques

Desertification has emerged as a major economic, social and environmental problem in the western part of India. The best way of dealing with desertification is to take appropriate measures to arrest land degradation, especially in areas prone to desertification. This requires an early warning system for desertification based on scientific inputs. Hence, in the present study, an attempt has been made to develop a comprehensive model for the assessment of desertification risk in the Jodhpur district of Rajasthan, India, using 23 desertification indicators. Indicators including soil, climate, vegetation and socio-economic parameters were integrated into a GIS environment to get environmental sensitive areas (ESAs) to desertification. Desertification risk index (DRI) was calculated based on ESAs to desertification, the degree of land degradation and significant desertification indicators obtained from the stepwise multiple regression model. DRI was validated by using independent indicators such as soil organic matter content and cation exchange capacity. Multiple regression analysis shows that 16 indicators out of 23 were found to be significant for assessing desertification risk at a 99% confidence interval with \(R^{2}=0.83\). The proposed methodology provides a series of effective indicators that would help to identify where desertification is a current or potential problem, and what could be the actions to alleviate the problem over time.     

Spatial assessment of the potential of groundwater quality using fuzzy AHP in GIS

In this study, fuzzy AHP method is used for extracting the water quality indicators based on the Schuler standard and World Health Organization (WHO) guidelines during a 20-year period. For this purpose, the best fit of the zoning model was performed. Furthermore, by comparing the standard errors, the continuous Raster layer was extracted from the important parameters used in generating the qualitative potential assessment index. The classified layer was generated by integrating continuous layers in the GIS environment and with the use of Python programming. The similarity of the outputs of both methods indicates the presence of large sections of aquifers in the middle and southwestern regions of Iran in the “temporarily drinkable” and “bad” classes. The calculations showed that the majority of aquifers that were located in the “inappropriate” class during the first 10 years fell to less valuable class types. Based on the results of the model, there is a direct correlation between the drop in water resources and the decline in the quality indices. In addition, in the Urmia and Bushehr coastal aquifers, due to excessive water withdrawal and salty water penetration, the quality of the table water is in critical condition. Based on the results of the research, the aquifers in the range of Zagros and Alborz mountains show the least change in water quality. The reason for this is the depth of the aquifer and the ability to recharge it.     

基于Logistic-CA-Markov模型的石漠化空间变化规律研究

为了揭示岩溶地区石漠化发生、发展的一般规律,文章以贵州省六枝特区为例,获取了1990、2000、2010年石漠化数据。利用Logistic-CA-Markov模型探讨石漠化发生的驱动因子及各类型间的转移情况,并在两种情景模式下对研究区2020年石漠化空间分布进行模拟。结果表明:（1）利用Logistic模型回归分析石漠化驱动因子,能够较好的反映其分布状况,CA-Markov耦合模型模拟石漠化空间分布,精度达到理论要求。（2)无石漠化、潜在石漠化、轻度石漠化、中度石漠化演变过程中受人为因素影响大于自然因素,而强度和极强度石漠化则相反。（3）在现有石漠化演化速率情景下,各等级石漠化的演变轨迹为修复与恶化并存模式,最突出的是潜在和轻度石漠化。（4）在喀斯特山地生态产业修复和封山育林结合情景下,石漠化修复与恶化并存的双重轨迹模式改为以修复为主的单一轨迹模式,其中轻度和中度石漠化治理效果最为突出。因此石漠化治理措施重点应针对轻度和中度石漠化分布区,注重协调人地矛盾,防止利用过程中返回式演变。      

Development of a GIS-based catastrophe theory model (modified DRASTIC model) for groundwater vulnerability assessment

This study developed a new paradigm for groundwater vulnerability assessment by modifying the standard DRASTIC index (DI) model based on catastrophe theory. The developed paradigm was called the catastrophe theory-based DI (CDI) model. The proposed model was applied to assess groundwater vulnerability to pollution index (GVPI) in Perak Province, Malaysia. The area vulnerability index was modeled by considering the DRASTIC multiple vulnerability causative factors (VCFs) obtained from different data sources. The weights and ranking of the VCFs were computed by using the inner fuzzy membership mechanism of the CDI model. The estimated vulnerability index values of the CDI model were processed in a geographic information system (GIS) environment to produce a catastrophe theory–DRASTIC groundwater vulnerability to pollution index (CDGVPI) map, which demarcated the area into five vulnerability zones. The produced CDGVPI map was validated by applying the water quality status–vulnerability zone relationship (WVR) approach and the relative operating characteristic (ROC) curve method. The performance of the developed CDI model was compared with that of the standard DI model. The validation results of the WVR approach exhibits 89.29% prediction accuracy for the CDI model compared with 75% for the DI model. Meanwhile, the ROC validation results for the CDI and DI models are 88.8% and 78%, respectively. The GIS-based CDI model demonstrated better performance than the DI model. The GVPI maps produced in this study can be used for precise decision making process in environmental planning and groundwater management.     

Chemostratigraphy of the Cenomanian-Turonian shallow-water carbonate: new correlation for the rudist levels from north Sinai,Egypt

The present study aims to provide carbon-isotope curves for the Cenomanian to Turonian rudist-dominated successions in north Sinai. The high-resolution carbon-isotope curves obtained from north Sinai sections provide new insight for calibrating the age of rudists as well as for evaluating the effects of the oceanic anoxic event 2 (OAE2) on rudist communities. The primary goals are (1) to provide a high-resolution sequence stratigraphic framework for the Cenomanian-Turonian succession, (2) to use rudist and ammonite biostratigraphic data to distinguish the stratigraphic levels of the rudist species, and (3) to integrate the chemostratigraphic (δ¹³C) profile and the rudist levels to improve the biostratigraphy based on the rudist distributions and the carbon-isotope data. The recognition of three ammonite zones through the Cenomanian-Turonian succession was utilized to identify four temporally significant rudist levels indicative of the Lower Cenomanian, Middle Cenomanian, Upper Cenomanian, and Middle Turonian, respectively. Most of the rudists occur in the highstand deposits of medium-scale sequences. Carbon- and oxygen-isotopic analyses were carried out on both rudists and surrounding carbonate units. Based on the variations in the carbon-isotope signals, 12 chronostratigraphic segments were identified in the studied sections. The Cenomanian carbon-isotope segments (C23–C30) were obtained from the Halal Formation at Gabal Yelleg and Gabal Maaza sections, while the Turonian segments (C30–C34) were measured from the Wata Formation at Gabal Yelleg section. The carbon-isotope record from the studied sections is consistent with the trends documented in previous studies of the Tethyan realm. The Cenomanian-Turonian boundary is placed at the onset of falling carbon-isotope values (δ¹³C) from 2.61 to ?0.25‰ in the upper part of OAE2 with the carbon-isotope segment C30 at Gabal Yelleg. The negative shift in δ¹³C values (C33) occurred in the Middle Turonian lowstand deposits characterizing the global sea level fall during this interval.     

Sinkhole hazard assessment in Minnesota using a decision tree model

An understanding of what influences sinkhole formation and the ability to accurately predict sinkhole hazards is critical to environmental management efforts in the karst lands of southeastern Minnesota. Based on the distribution of distances to the nearest sinkhole, sinkhole density, bedrock geology and depth to bedrock in southeastern Minnesota and northwestern Iowa, a decision tree model has been developed to construct maps of sinkhole probability in Minnesota. The decision tree model was converted as cartographic models and implemented in ArcGIS to create a preliminary sinkhole probability map in Goodhue, Wabasha, Olmsted, Fillmore, and Mower Counties. This model quantifies bedrock geology, depth to bedrock, sinkhole density, and neighborhood effects in southeastern Minnesota but excludes potential controlling factors such as structural control, topographic settings, human activities and land-use. The sinkhole probability map needs to be verified and updated as more sinkholes are mapped and more information about sinkhole formation is obtained.     

Groundwater vulnerability and contamination risk assessment of the Weining Plain,using a modified DRASTIC model and quantized pollution loading method

Groundwater resources have become more vulnerable to contamination due to rapid population growth and economic development. This study aimed to assess the groundwater contamination risk in the Weining Plain, China. Based on the specific conditions of the Weining Plain, a new model DRTSWI with a weighting scheme determined by analytic hierarchy process was developed to evaluate the intrinsic groundwater vulnerability for the study area. An integrated approach, combining the toxicity, the release possibility, and the potential release quantity of the pollutants, was used to estimate the pollution loading. The groundwater contamination risk results were obtained by overlaying the intrinsic vulnerability and pollution loading maps. These indicated that two industrial parks pose the main threat to groundwater quality, due to their unfavorable hydrogeological setting and potential pollution sources on the surface. Some areas in and around the industrial parks exhibit groundwater pollution, which was identified on the contamination risk map using buffer analysis. High risk areas are industries with high or medium vulnerability. The vulnerability and contamination risk maps developed for this study are valuable tools for environmental planning and can be used for predictive management of groundwater resources.     

Spatial pattern of Karst rock desertification in the Middle of Guizhou Province,Southwestern China

Karst rocky desertification is a typical type of land degradation in the Southwestern China. It has great ecological and economical implications for the local people. Landsat images from the middle of Guizhou Province collected in 1974, 1993 and 2001 were used for change detection of the pattern of Karst rocky desertification. The results show the following findings: (1) Desertification area expanded drastically in 27 years, at an increasing rate about 116.2 km²/year. (2) High areas (900–1,500 m) are the most affected. (3) Areas with the slope <5° or >25° are also easily tend to be Karst rocky deserted. (4) The process of Karst rocky desertification is nearly irreversible. Few areas of Karst rocky desertification could be meliorated to non-desertification land. (5) Most of the degraded lands are located in the south and the central of the study region, and the meliorated land areas are sparsely located in the east and the west part of the region. All these findings would provide bases for the decision-making of the local government to improve the Karst rocky desertification     

陕西大柳塔煤矿区土地沙漠化时空演变研究

通过野外路线穿越调查和地面分辨率为2.5m的1:25 000 SPOT5遥感影像解译,查明了研究区2005年沙漠化土地现状,采用TM遥感影像解译对比了1986年煤矿建设初期、1996年开发中期同时段土地沙漠化程度及面积.研究表明:20年来研究区土地沙漠化面积减少了11.67km2.主要煤矿塌陷区土地沙漠化变化与研究区趋势相同,即重度、中度面积逐渐缩小,采煤塌陷区土地沙漠化没有出现加剧的现象.这一结论为该区大规模开发煤炭资源,同时保护生态地质环境提供了科学依据.     

Tsunami vulnerability assessment in urban areas using numerical model and GIS

Natural disasters can neither be predicted nor prevented. Urban areas with a high population density coupled with the construction of man-made structures are subjected to greater levels of risk to life and property in the event of natural hazards. One of the major and densely populated urban areas in the east coast of India is the city of Chennai (Madras), which was severely affected by the 2004 Tsunami, and mitigation efforts were severely dampened due to the non-availability of data on the vulnerability on the Chennai coast to tsunami hazard. Chennai is prone to coastal hazards and hence has hazard maps on its earth-quake prone areas, cyclone prone areas and flood prone areas but no information on areas vulnerable to tsunamis. Hence, mapping has to be done of the areas where the tsunami of December 2004 had directly hit and flooded the coastal areas in Chennai in order to develop tsunami vulnerability map for coastal Chennai. The objective of this study is to develop a GIS-based tsunami vulnerability map for Chennai by using a numerical model of tsunami propagation together with documented observations and field measurements of the evidence left behind by the tsunami in December 2004. World-renowned and the second-longest tourist beach in the world “Marina” present in this region witnessed maximum death toll due to its flat topography, resulting in an inundation of about 300 m landward with high flow velocity of the order of 2 m/s.     

Soil erosion assessment on hillslope of GCE using RUSLE model

A new method for obtaining the C factor (i.e., vegetation cover and management factor) of the RUSLE model is proposed. The method focuses on the derivation of the C factor based on the vegetation density to obtain a more reliable erosion prediction. Soil erosion that occurs on the hillslope along the highway is one of the major problems in Malaysia, which is exposed to a relatively high amount of annual rainfall due to the two different monsoon seasons. As vegetation cover is one of the important factors in the RUSLE model, a new method that accounts for a vegetation density is proposed in this study. A hillslope near the Guthrie Corridor Expressway (GCE), Malaysia, is chosen as an experimental site whereby eight square plots with the size of \(8\times 8\) and \(5\times 5\) m are set up. A vegetation density available on these plots is measured by analyzing the taken image followed by linking the C factor with the measured vegetation density using several established formulas. Finally, erosion prediction is computed based on the RUSLE model in the Geographical Information System (GIS) platform. The C factor obtained by the proposed method is compared with that of the soil erosion guideline Malaysia, thereby predicted erosion is determined by both the C values. Result shows that the C value from the proposed method varies from 0.0162 to 0.125, which is lower compared to the C value from the soil erosion guideline, i.e., 0.8. Meanwhile predicted erosion computed from the proposed C value is between 0.410 and \(3.925\, \hbox {t ha}^{-1 }\,\hbox {yr}^{-1}\) compared to 9.367 to \(34.496\, \hbox {t ha}^{-1}\,\hbox {yr}^{-1 }\) range based on the C value of 0.8. It can be concluded that the proposed method of obtaining a reasonable C value is acceptable as the computed predicted erosion is found to be classified as a very low zone, i.e. less than \(10\, \hbox {t ha}^{-1 }\,\hbox {yr}^{-1}\) whereas the predicted erosion based on the guideline has classified the study area as a low zone of erosion, i.e., between 10 and \(50\, \hbox {t ha}^{-1 }\,\hbox {yr}^{-1}\).     

Probabilistic stability assessment of slopes using high dimensional model representation

This paper presents a new computational tool for probabilistic stability assessment of earth slopes/embankments. The method involves high dimensional model representation (HDMR) that facilitates lower dimensional approximation of the original limit state, response surface generation of HDMR component functions, and Monte Carlo simulation. HDMR is a general set of quantitative model assessment and analysis tools for capturing the high-dimensional relationships between sets of input and output model variables. It is a very efficient formulation of the system response, if higher-order variable correlations are weak, allowing the physical model to be captured by the first few lower-order terms. Once the approximate form of the original limit state is defined, the failure probability can be obtained by statistical simulation. Results of four numerical examples indicate that the proposed method provides accurate and computationally efficient estimates of the failure probability of earth slopes/embankments.     

贵州贞丰—关岭花江喀斯特石漠化地区土壤厚度的空间分布特征

土壤厚度与石漠化发展程度有着密切的关系,土壤也是石漠化地区生态恢复以及农业生产的基础。为了研究典型高原峡谷中-强度石漠化地区的土壤厚度空间分布规律,在土壤厚度野外调查的基础上,利用地统计学方法分析了贵州典型石漠化地区——贞丰—关岭花江小流域土壤厚度空间分布特征及主要影响因素。结果表明：（1）研究区土壤平均厚度仅为26 cm,土壤平均厚度表现为坡耕地>荒地>林地;（2）土壤厚度空间变异性以强度为主,荒地的土壤厚度空间分布连续程度优于林地和坡耕地,林地的土壤厚度空间分布有明显突变性,坡耕地的土壤厚度具有点状分布特征,有耕作物附近土壤厚度较大;（3）土壤厚度与海拔、基岩裸露率、坡度之间均有明显负相关关系;（4）自然和人为因素综合影响下的土壤强侵蚀是研究区土壤厚度分布极为不均的主要原因,对该区域石漠化的治理可以采用工程措施与生物措施相结合的方法。研究结果对研究区石漠化因地制宜地防治及其他地区水土流失防治、生态恢复、农业合理生产具有一定的参考价值。     

Nonlinear analysis of laterally loaded single piles in sand using modified strain wedge model

This paper proposes a modified strain wedge model for the nonlinear analysis of laterally loaded single piles in sandy soils by using the Duncan–Chang model as well as the Mohr–Coulomb model to describe the stress–strain behavior of soils in the strain wedge. The input soil property for sandy soils only needs a relative density which can be easily estimated from in situ tests. The strain wedge depth is calculated by an iterative process and the subgrade reaction modulus below the strain wedge is assumed to increase linearly with depth, though it does not change with the lateral load applied to the pile. Seven case histories are used to verify the applicability of the proposed method. The results show the following: (1) good agreements are found between the predicted and the measured results of full scale tested piles; (2) the predicted deflections and moments using the Duncan–Chang model are almost the same as those using the Mohr–Coulomb model; and (3) the size effect of the pile diameter or width on the subgrade reaction modulus should be considered.     

北方集中供热系统气象风险评估初探

供热管网爆裂、跑冒滴漏是北方集中供热城市面临的常见问题,供热管网出现大型故障往往是在室外寒冷的隆冬时节,如果间断或限额供热时间过长,将会造成严重的社会和经济影响。同时在极端低温情况下,可能会造成热源供应不足,出现限额供热现象,不能保证室内舒适度,影响人们的正常生活。本文提出了能源供应气象风险评估和热网维修寒冷风险评估方法,并进行了案例评估,以期为未来进行相关风险评估提供参考。     

Groundwater vulnerability assessment in shallow aquifer of Kathmandu Valley using GIS-based DRASTIC model

In this paper, groundwater aquifer vulnerability map has been developed by incorporating the major geological and hydro-geological factors that affect and control the groundwater contamination using GIS based DRASTIC model. This work demonstrates the potential of GIS to derive a map by overlying various spatially referenced digital data layers that portrays cumulative aquifer sensitivity ratings across the Kathmandu Valley, Nepal, providing a relative indication of groundwater vulnerability to contamination. In fact, the groundwater is the major natural resources in Kathmandu for drinking purpose. The decline in groundwater levels due to the over exploitation and thus extracted water from shallow aquifer has been contaminated by the infiltration of pollutants from polluted river and land surface is continuous and serious. As the demand for water for human and industrial use has escalated and at the same time, the engineering and environmental costs are much higher for new water supplies than maintaining the existing sources already in use. Management of groundwater source and protecting its quality is therefore essential to increase efficient use of existing water supplies. Aquifer vulnerability maps developed in this study are valuable tools for environmental planning and predictive groundwater management. Further, a sensitivity analysis has been performed to evaluate the influence of single parameters on aquifer vulnerability assessment such that some subjectivity can be reduced to some extent and then new weights have been computed for each DRASTIC parameters.     

Notatudiadema and Aegyptiaris: Two new regular echinoids genera with two new species from the Cenomanian of north Sinai,Egypt

Revision of the Cenomanian echinoids deposited in the Cairo Geological Museum resulted in the erection of two new genera with two new species of regular echinoids. The first, Notatudiadema rekeibensis gen. and sp. nov. is established for specimens from the Cenomanian of Gabal El-Rekeib, southeast the Maghara massif, north Sinai to accommodate diadematoid echinoids having hemi-crenulate ambital and sub-ambital interambulacral tubercles with the adapical part of platform non-crenulate and the adoral one of same tubercle coarsely crenulate. The second is Aegyptiaris halalensis gen. and sp. nov., erected for material from the lower Cenomanian of Gabal El-Halal, northeast Sinai as an emiratiid echinoid with throughout polyporus ambulacra and extremely reduced adapical ambulacral tubercles. The functional morphology and paleobiology of these taxa are also discussed. A new family is established: family Monodiadematidae fam. nov.     

基于高分辨率遥感影像的典型区水蚀荒漠化时空演变特征

借助"3S"技术,以水蚀荒漠化的形成机理为切入点,利用美国侦察卫星和SPOT6卫星获取的高分辨率遥感影像对吉林松原地区近50年来的水蚀荒漠化在不同驱动因子扰动下的时空变化规律进行分析。结果表明:研究区在1969—2015年水蚀荒漠化土地面积呈增长趋势,增加面积为11.09km~2。降水量、坡度及岩性是影响该区水蚀荒漠化土地面积变化的主要驱动因子。     

Shallow landslide hazard assessment using a three-dimensional deterministic model in a mountainous area

Shallow landslides are common in mountainous areas after intense rainfall. Of all landslide hazard assessment methods, deterministic methods provide the best quantitative information on landslide hazard. However, they require a large amount of detailed in situ data, derived from laboratory tests and field measurements, and therefore it is difficult to apply them over large areas. One of the most important input parameters is soil depth. For large areas, it is impossible to obtain soil depth through field measurements. To overcome this difficulty, a statistics-based regression analysis is used to evaluate soil depths. All the terrain attributes that control soil depths are selected as influential factors. By using multi-linear regression, the soil depths at each location can be predicted. Slope stability analysis can then be performed using deterministic methods with the evaluated soil depths. The study area is divided into slope units. For each slope unit, Monte-Carlo simulation and a GIS-based 3D limit equilibrium model are used to locate the critical slip surface and calculate the corresponding safety factor. The effectiveness of the proposed method has been tested by applying it to a mountainous area in Japan.