Kajian daya dukung geologi rencana lokasi Tempat Pembuangan Akhir di Desa Botok, Magetan, Jawa Timur

Abstrak.Tempat Pembuangan Akhir (TPA) sampah Milangasri di Kabupaten Magetan telah mencapai daya tampung maksimum. Pemerintah Kabupaten Magetan berencana membangun TPA baru di Desa Botok. Penelitian ini bertujuan untuk melakukan kajian kelayakan daya dukung geologi rencana lokasi TPA baru. Kriteria daya dukung geologi mengacu pada SNI 03-3241-1994 tentang tata cara pemilihan lokasi TPA. Metode penelitian meliputi investigasi lapangan dan pengumpulan data sekunder. Penelitian lapangan meliputi pengamatan kondisi geologi, pemetaan topografi, survei geolistrik, pemboran inti dan uji permeabilitas lapangan serta pengamatan sumber air terdekat. Data sekunder meliputi informasi yang berkaitan dengan potensi bahaya geologi. Hasil penelitian menunjukkan bahwa kelulusan batuan antara 1,26 × 10-2 hingga 1,59 × 10-2 cm/detik tidak memenuhi kriteria. Sehingga secara alami, lokasi ini kurang layak dijadikan sebagai lokasi TPA. Namun demikian, rekayasa teknologi dengan memberikan lapisan kedap air pada alas TPA seperti compacted clay liner atau geosynthetic liner menjadikan area ini layak untuk TPA. Abstract.Current landfill in Milangasri nearly reach its maximum capacity. The government of Magetan regency plans to build a new landfill in Botok. This research aims to assess the land capability based on geological characteristics of the landfill location. The SNI 03-3241-1994 used as basic criteria for selecting landfill area. Research methods consist of field investigation supported by secondary data. Field investigation consist of geological observation, topography mapping, resistivity survey, core drilling and field permeability testing, and water source observation. Information of potential geological hazard collected as secondary data. The results show that the hydraulic conductivity of the quaternary deposit ranging of 1.26 × 10-2 to 1.59 × 10-2 cm/s, failed to meet the criteria. Therefore, by nature the location candidate not supported geologically as landfill location. However, application of compacted clay liner or geosynthetic liner as the base of the landfill is recommended to improve the capability.

Land Subsidence Prediction Induced by Multiple Factors Using Machine Learning Method

In the Beijing Plain, land subsidence is one of the most prominent geological problems, which is affected by multiple factors. Groundwater exploitation, thickness of the Quaternary deposit and urban development and construction are important factors affecting the formation and development of land subsidence. Here we choose groundwater level change, thickness of the Quaternary deposit and index-based built-up index (IBI) as influencing factors, and we use the influence factors to predict the subsidence amount in the Beijing Plain. The Sentinel-1 radar images and the persistent scatters interferometry (PSI) were adopted to obtain the information of land subsidence. By using Google Earth Engine platform and Landsat8 optical images, IBI was extracted. Groundwater level change and thickness of the Quaternary deposit were obtained from hydrogeological data. Machine learning algorithms Linear Regression and Principal Component Analysis (PCA) were used to investigate the relationship between land subsidence and influencing factors. Based on the results obtained by Linear Regression and PCA, a suitable machine learning algorithm was selected to predict the subsidence amount in the Beijing Plain in 2018 through influencing factors. In this study, we found that the maximum subsidence rate in the Beijing Plain had reached 115.96 mm/y from 2016 to 2018. The land subsidence was serious in eastern Chaoyang and northwestern Tongzhou. In addition, the area where thickness of the Quaternary deposit reached 150–200 m was prone to more serious land subsidence in the Beijing Plain. In groundwater exploitation, the second confined aquifer had the greatest impact on land subsidence. Through Linear Regression and PCA, we found that the relationship between land subsidence and influencing factors was nonlinear. XGBoost was feasible to predict subsidence amount. The prediction accuracy of XGBoost on the subsidence amount reached 0.9431, and the mean square error was controlled at 15.97. By using XGBoost to predict the subsidence amount, our research provides a new idea for land subsidence prediction.

Suction Monitoring and Stability of Volcanic-Residual Soil Slope during Rainfall

Some slopes in Yogyakarta, Indonesia, were covered by volcanic soil of the quaternary deposit of Merapi volcano. Typically, the soil layers of the slope consist of fine sand or silty sand. During the wet season (November – February), the slope is prone to instability due to rainfall infiltration. This paper presents the field suction monitoring of silty-sand slope. A 2.57 m high slope at Universitas Muhammadiyah Yogyakarta campus was instrumented with a mini tensiometer, moisture probe, and rain gauge to study the effect of suction on the slope stability during rainfall in wet season. The investigation shows that the rainfall decreases the suction and increase the moisture of soil. This situation leads to slope instability. The factor of safety fluctuates corresponding to the rainfall intensity. The lowest factor of safety was attained on 30 December, in which the rainfall intensity is the highest, i.e. 48 mm/day.

CORE LOG AND CONE PENETRATION TEST APPROACH FOR BEARING CAPACITY ANALYSIS OF QUATERNARY DEPOSIT AND ITS CORRELATION TO FACIES DISTRIBUTION IN SOUTHERN BALI

Area development deals with optimal land use and the reduction of the risk of geological disasters. The coastal area of South Bali is prone to land settlement hazards. In order to mitigate the risk, it is important to understand the depositional environment of the area related to its bearing capacity and geological hazard risks. The aim of this research is to understand the subsurface depositional environment and quantifying its bearing capacity. Quantitative modeling was carried out to obtain the sediment-bearing capacity of the Pendungan area in Bali, Indonesia. The methods used in this research were the observation of borehole cores, the identification of the cone penetration test (CPTu) curves pattern, the sediment index property test, the soil strength laboratory, and bearing capacity analysis. Based on lithologic association, the CPTu curve pattern, and grain size analysis, there are three facies developing in the study area with different bearing capacity values. Generally, beach ridge sand has a higher bearing capacity (N-SPT value of 8 – 52) for shallow foundation than fluvial clay. Meanwhile, floodplain facies has the lowest bearing capacity (N-SPT value of 2 – 20).

Automated Stability Analysis of Soil Slopes

Herein there is a description of algorithm of the automated forecast of stability for soil slope structures including input of initial data regarding physical and mechanical properties and geometrical parameters of a structure, building of the most intense sliding face, computation of the slope stability by the polygon of forces method. Developed on algorithm basis, The Stable Slope software package has been implemented in open pit located in the Altai region. There are calculation results of the parameters of the Eastern steady side (slope angle at a given height) depending on the inclination angle of contact of the friable Quaternary deposit with a parent rock. Recommendations can improve work safety under adverse natural and man-made conditions causing formation of unstable water-saturated zones.

Assessing threats to shallow groundwater quality from soil pollutants in Glasgow, UK: development of a new screening tool

ABSTRACTA new GIS-based screening tool to assess threats to shallow groundwater quality has been trialled in Glasgow, UK. The GRoundwater And Soil Pollutants (GRASP) tool is based on a British Standard method for assessing the threat from potential leaching of metal pollutants in unsaturated soil/superficial materials to shallow groundwater, using data on soil and Quaternary deposit properties, climate and depth to groundwater. GRASP breaks new ground by also incorporating a new Glasgow-wide soil chemistry dataset. GRASP considers eight metals, including chromium, lead and nickel at 1622 soil sample locations. The final output is a map to aid urban management, which highlights areas where shallow groundwater quality may be at risk from current and future surface pollutants. The tool indicated that 13% of soil sample sites in Glasgow present a very high potential threat to groundwater quality, due largely to shallow groundwater depths and high soil metal concentrations. Initial attempts to validate GRASP revealed partial spatial coincidence between the GRASP threat ranks (low, moderate, high and very high) and groundwater chemistry, with statistical correlation between areas of high soil and groundwater metal concentrations for both Cr and Cu (r2>0.152; P<0.05). Validation was hampered by a lack of, and inconsistency in, existing groundwater chemistry data. To address this, standardised subsurface data collection networks have been trialled recently in Glasgow. It is recommended that, once available, new groundwater depth and chemistry information from these networks is used to validate the GRASP model further.