Watershed prioritization using morphometric and land use/land cover parameters: A remote sensing and GIS based approach

Jaggar watershed is a constituent of the Gambhir river basin, in eastern Rajasthan and covers an area of 352.82 km², representing arid climate. The drainage network is dendritic to sub-dendritic pattern however parallel to sub-parallel has also developed locally. The Jaggar watershed has been divided into fourteen sub-watersheds, designated as SW1 to SW14, for prioritization purpose. The prioritization of the sub-watersheds has been done on the basis of morphometric analysis and land use/land cover categories. Various morphometric parameters (linear and shape) have been determined for each sub-watershed and assigned rank on the basis of value/relationship with erodibility so as to arrive at a compound value for final ranking of the sub-watersheds. Land use/land cover mapping has been carried out using IRS LISS III data of 1998. Based on morphometric and land use/land cover analysis and their ranks, the subwatersheds have been classified into four categories as very high, high, medium and low in terms of priority for conservation and management of natural resources. The prioritization results based on morphometry reveal that only SW7 and SW10 fall under very high priority, whereas SW6, SW11 and SW13 fall under very high priority on the basis of land use/land cover analysis. However on the integration of morphometry and land use/land cover only SW14 show common priority whereas rest have little or no correlation.     

Aquifer hydraulic conductivity estimation from surface geoelectrical measurements for Krauthausen test site, Germany

The physical explanation is presented for two types of theoretical equations which encompass a direct and an inverse relationship between the hydraulic conductivity and electrical resistivity of an aquifer. Using the theory of direct current (DC) resistivity prospecting, it is shown that a direct relation exists if the bulk of the current flow is in the vertical direction, whereas the inverse relation exists if the current is in the horizontal direction. Consequently, the relation in question is direct in the case of a relatively conducting basement and inverse in the case of a comparatively resistive basement. Then, the aquifer hydraulic conductivity for the hydrogeologically well-studied area of Krauthausen in Germany is estimated by two different techniques using surface geoelectrical data. The estimated values are compared with those conventionally determined by a pump test experiment and it can be concluded that the estimation is better whenever geoelectrical data are used.     

Composition of selected heavy metals in road dust from Kuala Lumpur city centre

This study was carried out in order to determine the concentration of heavy metals, e.g., lead (Pb), cadmium (Cd), copper (Cu), zinc (Zn), iron (Fe), manganese (Mn), nickel (Ni) and chromium (Cr) in road dust in Kuala Lumpur’s city centre. Samples were collected from four sampling locations, each of which had four sampling points and three replications. Heavy metals from different fractions of particles separated by different diameter sizes: d < 63 μm (Fraction A), 63 < d < 125 μm (Fraction B) and 125 < d < 250 μm (Fraction C) were analyzed using inductively coupled plasma mass spectrometry. The results from this study showed that concentration of heavy metals was dominated by the smallest particle size: <63 μm and that Fe was the most abundant heavy metal overall, followed by Cu > Mn > Zn > Pb > Ni > Cr > Cd. The fact that Cd had the highest enrichment factor value (EF) for all particle sizes indicates that anthropogenic activities contributed to the presence of this metal. There was also a higher EF value for heavy metals in small particle (Fraction A), compared to Fraction B and C, which suggests that fine particles were being produced through anthropogenic activities. Cluster analysis and principal component analysis demonstrated the likelihood of the heavy metals detected in the road dust, originating from road traffic and industrial activities.     

Particle tracking analysis of river–aquifer interaction via bank infiltration techniques

Induced bank infiltration (BI) is commonly implemented in other countries, but remains new and unexplored in Malaysia. Increasing river pollution could affect drinking water resources. Given the threat of pollution to raw water sources, applying induced BI to sustain water management is essential. This paper presents a case study of the BI method, which evaluates the effects of groundwater pumping and BI operation on the installation of wells as well as determines the effect of pumping rate on flow paths, travel time, the size of the pumping and capture zone delineation, and groundwater mixing in a pumping well in Jenderam Hilir, Malaysia. The proposed method performs infiltration safely and achieves the ideal pumping rate. Numerical modeling packages, MODFLOW and MODPATH (particle tracking) were used. Results indicate that the migration of river water into the aquifer is generally slow and depends on the pumping rate and distance from well to the river. Most water arrives at the well by the end of a pumping period of 1–5 days at 3,072 m³/day for test wells DW1 and DW2, and during simultaneous pumping for DW2 and PW1 for a well located 36 and 18 m, respectively, from the river. During the 9.7-day pumping period, 33 % of the water pumped from the DW1 well was river water, and 38 % from DW2 throughout 4.6 days was river water. The models provide necessary information for water operators in the design and construction of pumping and sampling schedules of BI practices.     

Tenfold cross validation artificial neural network modeling of the settlement behavior of a stone column under a highway embankment

Construction of embankments in engineering structures on soft clay soils normally encounters problems related to excessive settlement issues. The conventional methods are inadequate to analyze and predict the surface settlement when the necessary parameters are difficult to determine in the field and in the laboratory. In this study, artificial neural network systems (ANNs) were used to predict settlement under embankment load using soft soil properties together with various geometric parameters as input for each stone column (SC) arrangement and embankment condition. Data from a highway project called Lebuhraya Pantai Timur2 in Terengganu, Malaysia, were investigated. The FEM package of Plaxis v8 program analysis was utilized. The actual angle of internal friction, spacing between SC, diameter of SC, length of SC, and height of embankment were used as the input parameters, and the settlement was used as the main output. Non cross validation (NCV) and tenfold cross validation (TFCV) were used to build the ANN model. The results of the TFCV model were more accurate than those of the NCV model. Comparisons made with the predictions of the Priebe model showed that the proposed TFCV model could provide better predictions than conventional methods.     

Assessing the effect of future landslide on ecosystem services in Aqabat Al-Sulbat region,Saudi Arabia

Natural Hazards - Co-occurrence events of droughts and heatwaves characterized by abnormal low soil moisture (SM) and high temperatures may cause more significant impacts on society and natural...     

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 \(50\, \hbox {t ha}^{-1 }\,\hbox {yr}^{-1}\).     

Geochemistry of the Miocene Zoumi flysch thrust-top basin (External Rif,Morocco): new constraints on source area weathering,recycling processes,and paleoclimate conditions

This study focuses on the Lower-Middle Miocene syn-orogenic flysch deposits of the Zoumi basin to infer source area paleoclimatic conditions, the intensity of source rocks paleoweathering, and mechanical sorting and recycling effects. The mudrocks are enriched in Al₂O₃, Fe₂O₃, CaO, and TiO₂ relative to PAAS and depleted in the other mobile major elements. There are high positive correlations between SiO₂, Al₂O₃, and TiO₂ and negative correlations between SiO₂ and CaO. Geochemically, the mudstones are mainly classified as shales, Fe-shales, and wackes. Various discriminant diagrams were used to reveal the inferred tectonics, source paleoweathering intensity, and paleoclimatic conditions. Chemical index of alteration (CIA) and chemical index of weathering (CIW) values for Lower-Middle Miocene vary from 50 to 80% indicating low to moderate degree of source area weathering compatible with non-steady-state weathering under wet and humid paleoclimatic conditions. Locally (Zoumi mid-section) CIA values are higher (>?80) reflecting intense source area weathering, which may be attributed to high tectonic impulses and more humid conditions during deposition. The combination of ICV-CIA, Al₂O₃-Zr-TiO₂, and Th/Sc-Zr/Sc values suggests the bulk rock is chemically immature and has experienced modest physical sorting and recycling reflecting little transportation until the final deposition.     

Groundwater beneath the urban area of Khan Younis City,southern Gaza Strip (Palestine): hydrochemistry and water quality

Arabian Journal of Geosciences - This paper presents the results of a groundwater hydrochemical assessment in the urban area of Khan Younis City in the southern Gaza Strip by measuring its...     

Heavy metal resistant endophytic fungi isolated from Nypa fruticans in Kuching Wetland National Park

Heavy metal pollution is an environmental issue globally and the aim of this study was to isolate endophytic fungi from mangrove wetlands of Sarawak to assess and test their ability to grow in the presence of various heavy metals (copper (Cu), zinc (Zn), lead (Pb), and chromium (Cr)). Samples of Nypa fruticans were collected from Kuching Wetland National Park (KWNP) for subsequent endophyte isolation. Ninety-three (93) isolates were obtained and assessed and the most resistant isolates (growing at concentrations up to 1000 ppm) were identified using fungal primers ITS 1 and ITS 4. All of the endophytic fungi were identified to be closely related to Pestalotiopsis sp. and this is to our knowledge the first study reporting the ability of Pestalotiopsis sp. to grow at high concentrations of copper, lead, zinc and chromium. Our results highlight the potential of using endophytic fungi for the treatment of heavy metal pollution, for example as biosorbents.