How deep can forest vegetation cover extend their hydrological reinforcing contribution?

An experimental campaign was set up to quantify the contribution of evapotranspiration fluxes on hillslope hydrology and stability for different forest vegetation cover types. Three adjacent hillslopes, respectively, covered by hardwood, softwood, and grass were instrumented with nine access tubes each to monitor soil water dynamics at the three depths of 30, 60, and 100 cm, using a PR2/6 profile probe (Delta‐T Devices Ltd) for about 6 months including wet periods. Soil was drier under softwood and wetter under grass at all the three depths during most of the monitoring period. Matric suction derived via the soil moisture measurements was more responsive to changes in the atmospheric conditions and also recovered faster at the 30 cm depth. Results showed no significant differences between mean matric suction under hardwood (101.6 kPa) with that under either softwood or grass cover. However, a significant difference was found between mean matric suction under softwood (137.5 kPa) and grass (84.3 kPa). Results revealed that, during the wettest period, the hydrological effects from all three vegetation covers were substantial at the 30 cm depth, whereas the contribution from grass cover at 60 cm (2.0 kPa) and 100 cm (1.1 kPa) depths and from hardwood trees at 100 cm depth (1.2 kPa) was negligible. It is surmised that potential instability would have occurred at these larger depths along hillslopes where shallow hillslope failures are most likely to occur in the region. The hydrological effects from softwood trees, 8.1 and 3.9 kPa, were significant as the corresponding factor of safety values showed stable conditions at both depths of 60 and 100 cm, respectively. Therefore, the considerable hydrological reinforcing effects from softwood trees to the 100 cm depth suggest that a hillslope stability analysis would show that hillslopes with softwood trees will be stable even during the wet season.     

Soil water dynamics under different forest vegetation cover: Implications for hillslope stability

Though it is well known that vegetation affects the water balance of soils through canopy interception and evapotranspiration, its hydrological contribution to soil hydrology and stability is yet to be fully quantified. To improve understanding of this hydrological process, soil water dynamics have been monitored at three adjacent hillslopes with different vegetation covers (deciduous tree cover, coniferous tree cover, and grass cover), for nine months from December 2014 to September 2015. The monitored soil moisture values were translated into soil matric suction (SMS) values to facilitate the analysis of hillslope stability. Our observations showed significant seasonal variations in SMS for each vegetation cover condition. However, a significant difference between different vegetation covers was only evident during the winter season where the mean SMS under coniferous tree cover (83.6 kPa) was significantly greater than that under grass cover (41 kPa). The hydrological reinforcing contribution due to matric suction was highest for the hillslope with coniferous tree cover, while the hillslope with deciduous tree cover was second and the hillslope with grass cover was third. The greatest contributions for all cover types were during the summer season. During the winter season, the wettest period of the monitoring study, the additional hydrological reinforcing contributions provided by the deciduous tree cover (1.5 to 6.5 kPa) or the grass cover (0.9 to 5.4 kPa) were insufficient to avoid potential slope failure conditions. However, the additional hydrological reinforcing contribution from the coniferous tree cover (5.8 to 10.4 kPa) was sufficient to provide potentially stable hillslope conditions during the winter season. Our study clearly suggests that during the winter season the hydrological effects from both deciduous tree and grass covers are insufficient to promote slope stability, while the hydrological reinforcing effects from the coniferous tree cover are sufficient even during the winter season. Copyright © 2018 John Wiley & Sons, Ltd.     

Artificial recharge efficiency assessment by soil water balance and modelling approaches in a multi-layered vadose zone in a dry region

To assess recharge through floodwater spreading, three wells, approx. 30 m deep, were dug in a 35-year-old basin in southern Iran. Hydraulic parameters of the layers were measured. One well was equipped with pre-calibrated time domain reflectometry (TDR) sensors. The soil moisture was measured continuously before and after events. Rainfall, ponding depth and the duration of the flooding events were also measured. Recharge was assessed by the soil water balance method, and by calibrated (inverse solution) HYDRUS-1D. The results show that the 15 wetting front was interrupted at a layer with fine soil accumulation over a coarse layer at the depth of approx. 4 m. This seemed to occur due to fingering flow. Estimation of recharge by the soil water balance and modelling approaches showed a downward water flux of 55 and 57% of impounded floodwater, respectively.     

Application of two fuzzy models using knowledge-based and linear aggregation approaches to identifying flooding-prone areas in Tehran

Flooding is one of the most problematic natural events affecting urban areas. In this regard, developing flooding models plays a crucial role in reducing flood-induced losses and assists city managers to determine flooding-prone areas (FPAs). The aim of this study is to investigate on the prediction capability of fuzzy analytical hierarchy process (FAHP) and Mamdani fuzzy inference system (MFIS) methods as two completely and semi-knowledge-based models to identify FPAs in Tehran, Iran. Six flooding conditioning factors including density of channel, distance from channel, land use, elevation, slope, and water discharge were extracted from various geo-spatial datasets. A total of 62 flooding locations were identified in the study area based on the existing reports and field surveys. Of these, 44 (70%) floods were randomly selected as training data and the remaining 18 (30%) cases were used for the validation purposes. After the data preparation step, data were processed by means of two statistical (FAHP) and soft computing (MFIS) methods. Unlike most statistical and soft computing approaches which use flooding inventory data for both training and evaluation of models, only conditioning factor was involved in data processing and inventory data were used in the current study to assess models prediction accuracy. Also, the efficiency of two approaches was evaluated by pixel matching (PM) and area under curve to validate the prediction capability of models. The prediction rate for MFIS and FAHP was 89% and 84%, respectively. Moreover, according to the results obtained from PM, it was found out that about 90% of known flooding locations fell in high-risk areas, whereas it was 83% for FAHP, indicating that flooding susceptibility map of MFIS has higher performance.

     

Random vibration of nonlinear structures with stiffness and strength deterioration by modified tail equivalent linearization method

In this research the tail equivalent linearization method(TELM) has been extended to study structures with degrading materials. The responses of such structures to excitations are non-stationary, even if the excitations are stationary. Non-stationary behavior of the system cannot be considered by conventional TELM. Applying the conventional TELM, the only distinction in the design point excitation for two stationary excitations with different durations is in the addition of a zero value part at the beginning of the design point of the longer excitation. This means that the failure probability is the same for the non-stationary systems under excitations with different durations. Therefore, this solution cannot be correct. In this study, in using TELM for systems with degrading materials, hysteretic energy is replaced by average hysteretic energy, calculated by averaging the obtained hysteretic energy of the structure subjected to a few random sample load realization. In this way, the degradation parameters under design point coincide with those under sample load realizations. Since the average of the hysteretic energy is converges very fast, the modified TELM only requires about tens to hundreds solutions of the response in addition to the ordinary calculations of conventional TELM.     

A new boundary element solution to evaluate the geometric effects of the canyon site on the displacement response spectrum

This paper presents a step-by-step procedure using the three-dimensional boundary element approach to study the behavior of semi-circular canyons under seismic shear waves. The boundary element code TDASC allows utilization for various canyon geometries, evaluation of concurrent seismic waves and calculation of the ground motions on canyons due to an excitation at any arbitrary point of the incident field. Considering the widening ratio of the canyon(including prismatic, semi-prismatic and non-prismatic canyons), wave characteristics(wavelength, dimensionless period, direction) and maximum amplification pattern, the solution was applied to carry out a series of parametric studies. It was shown that canyon form can significantly affect the displacement amplification, especially at the points located on its edges. By increasing the wave dimensionless frequency(η 1), the amplification pattern becomes more complex. On the basis of the results from a variety of considered cases, a new expression has been presented for the limiting wavelength beyond which the widening of the canyon will not have a major effect on the displacement amplification. To verify the reliability of the proposed approach, the obtained results, expressed in terms of displacement amplitude, were compared with those from the available published literature and a reasonably good agreement was observed.     

Conditional spectrum bidirectional record selection for risk assessment of 3D structures using scalar and vector IMs

Several proposals are explored for the hazard and intensity measure (IM) consistent selection of bidirectional ground motions to assess the performance of 3D structural models. Recent studies have shown the necessity of selecting records that thoroughly represent the seismicity at the site of interest, as well as the usefulness of efficient IMs capable of estimating the response of buildings with low scatter. However, the advances realized are mostly geared towards the structural analysis of 2D models. Few are the combined record, and IM selection approaches suggested expressly for nonlinear dynamic analysis of 3D structural models, especially when plan asymmetry and torsion sensitivity come into play. Conditional spectrum selection is leveraged and expanded here to offer a suite of approaches based on both scalar and vector IMs that convey information from two orthogonal horizontal components of the ground motion. Applications on multiple 3D building models highlight the importance of (a) employing the same IM for both record selection and response assessment and (b) maintaining hazard consistency in both horizontal components, when using either a scalar or a vector IM. All tested approaches that respect these conditions can be viable, yet the one based on the geometric mean of multiple spectral ordinates from both components over a period range seems to hold the most promise for general use.     

An integrated object-based image analysis and CA-Markov model approach for modeling land use/land cover trends in the Sarab plain

The present paper is an attempt to integrate a semi-automated object-based image analysis (OBIA) classification framework and a cellular automata-Markov model to study land use/land cover (LULC) changes. Land use maps for the Sarab plain in Iran for the years 2000, 2006, and 2014 were created from Landsat satellite data, by applying an OBIA classification using the normalized difference vegetation index, salinity index, moisture stress index, soil-adjusted vegetation index, and elevation and slope indicators. The classifications yielded overall accuracies of 91, 93, and 94% for 2000, 2006, and 2014, respectively. Finally, using the transition matrix, the spatial distribution of land use was simulated for 2020. The results of the study revealed that the number of orchards with irrigated agriculture and dry-farm agriculture in the Sarab plain is increasing, while the amount of bare land is decreasing. The results of this research are of great importance for regional authorities and decision makers in strategic land use planning.     

Assessment of H<Subscript>2</Subscript>S emission hazards into tunnels: the Nosoud tunnel case study from Iran

The presence of a gassy ground condition is an important problem in tunneling. In this study, the effects of groundwater H₂S and CH₄ emissions are investigated and characterized together with the factors that created these conditions in Nosoud tunnel in Iran. Through the geological investigations, the presence of these gasses was not detected prior to the construction of the tunnel. Groundwater sampling indicated that about 1 L of H₂S is released per 100 L of the water inflow into the Nosoud tunnel under normal conditions. However, the volume of the released gas was varying with the changes in the groundwater discharge rate. Thus, estimation of groundwater inflow into the tunnel is necessary for predicting the volume of gas emission. Based on the experience of the Nosoud tunnel excavations, there are several geological and hydrogeological factors that must be considered as the indicators of gas emissions during tunneling. Considering the importance of ground water gas emission into the tunnels located in gassy conditions, the present work was conducted to predict the H₂S seepage before the excavation using geological and hydrogeological indicators.     

Landfill site selection using combination of fuzzy logic and multi-attribute decision-making approach

During the last decades, growth of urbanization and industrialization led to an increase in solid waste generation. Landfilling is the most prevalent ultimate disposal method for the municipal solid wastes in developing countries. The rapid municipal solid waste generation in Markazi province (central part of Iran) causes the need for precision in finding a suitable landfill site selection. In the present study, 12 factors (environmental and socioeconomic factors) have been applied to select the landfill site in Markazi province, Iran. The different methods including the analytic network process (ANP) combined with fuzzy linguistic quantifier, ordered weighted average (OWA), and weighted linear combination (WLC) approach in geographic information system was applied to find an appropriate landfill site. The OWA operator function permits the evaluation of the wide spectrum of consequences (with different scenario) obtained from different management strategies. Results revealed that integration of fuzzy logic, ANP, and OWA provides flexible and better ideas compared to the Boolean logic and WLC to select a suitable landfill site.