Understanding hydrological processes of glacierized catchments in the western Himalayas by a multi-year tracer-based hydrograph separation analysis

Snow and glacier melt are significant contributors to streamflow in Himalayan catchments, and their increasing contributions serve as key indicators of climate change. Consequently, the quantification of these streamflow components holds significant importance for effective water resource management. In this study, we utilized the spatio-temporal variability of isotopic signatures in stream water, rainfall, winter fresh snow, snowpack, glaciers, springs, and wells, in conjunction with hydrometeorological observations and Snow Cover Area (SCA) data, to identify water sources and develop a conceptual understanding of streamflow dynamics in three catchments (Lidder, Sindh, and Vishow) within the western Himalayas. The following results were obtained: (a) endmember contributions to the streamflow exhibit significant spatial and seasonal variability across the three catchments during 2018–2020; (b) snowmelt dominates streamflow, with average contributions across the entire catchment varying: 59% ± 9%, 55% ± 4%, 56% ± 6%, and 55% ± 9% in Lidder, 43% ± 6%, 38% ± 6%, 32% ± 4%, and 33% ± 5% in Sindh and 45% ± 8%, 40% ± 6%, 39% ± 6%, and 32% ± 5% in Vishow during spring, summer, autumn, and winter seasons, respectively; (c) glacier melt contributions can reach ~30% to streamflow near the source regions during peak summer; (d) The primary uncertainties in streamflow components are attributed to the spatiotemporal variability of tracer signatures of winter fresh snow/snowpack (±1.9% to ±20%); (e)regarding future streamflow components, if the glacier contribution were to disappear completely, the annual average streamflow in Lidder and Sindh could decrease up to ~20%. The depletion of the cryosphere in the region has led to a rapid increase in runoff (1980–1900), but it has also resulted in a significant streamflow reduction due to glacier mass loss and changes in peak streamflow over the past three decades (1990–2020). The findings highlight the significance of environmental isotope analysis, which provides insights into water resources and offers a critical indication of the streamflow response to glacier loss under a changing climate.     

Multi-criteria decision-making analysis in selecting suitable plotting positions for IDF curves of storm events

Selecting suitable distributions for rainfall data is usually subjective and complex since it requires decision-makers to consider results from various measures of goodness-of-fit indices. In this study, the VIKOR method in multi-criteria decision-making analysis is modified to select the most suitable plotting positions to represent extreme storm intensities in order to build the intensity–duration–frequency (IDF) curves of storm events. This is done by considering the rankings provided by all goodness-of-fit indices used to obtain a compromise solution. Nine plotting positions are considered: Weibull (W), Adamowski (A), Gringorten (G), Hazen (H) and Gumbel (EV I) and two known plotting positions for generalized extreme value (GEV) distribution using Pearson’s skewness and another two using L-skewness. The IDF curves obtained are compared to a reference IDF curves which was found using the GEV distribution. The mean and median for three goodness-of-fit indices, the coefficient of variation of root mean square error, CV_RMSE, the mean percentage of difference, Δ, and the coefficient of determination, R ², are taken as the criteria for selection process. The results show that six plotting positions, A, H, W, G and the two plotting positions with L-skewness, are equally superior compared to the other three plotting positions.     

Computerised development control and approval system for City Hall of Kuala Lumpur

This paper will discuss the computerised development control and approval system being developed for the Planning and Development Control Department, City Hall of Kuala Lumpur, with stress on the GIS architecture developed within the system. The prospects and challenges towards implementation of the system are also discussed.     

Behavior of Weak Soils Reinforced with End-Bearing Soil-Cement Columns Formed by the Deep Mixing Method

This article reports on a series of small-scale, plane strain, 1 g physical model tests designed to investigate the bearing capacity and failure mechanics of end-bearing soil-cement columns formed via Deep Mixing (DM). Pre-formed soil-cement columns, 24 mm in diameter and 200 mm in length, were installed in a soft clay bed using a replacement method; the columns represented improvement area ratios, a_p, of 17%, 26%, and 35% beneath a rigid foundation of width 100 mm. Particle Image Velocimetry (PIV) was implemented in conjunction with close-range photogrammetry in order to track soil displacement during loading, from which the failure mechanisms were derived. Bearing capacity performance was verified using Ultimate Limit State numerical analysis, with the results comparing favorably to the analytical static and kinematic solutions proposed by previous researchers. A new equation for bearing capacity was derived from this numerical analysis based on the improvement area ratio and cohesion ratio of the soil column and ground model.     

Characterization of spatial patterns in river water quality using chemometric pattern recognition techniques

This study employed three chemometric data mining techniques (factor analysis (FA), cluster analysis (CA), and discriminant analysis (DA)) to identify the latent structure of a water quality (WQ) dataset pertaining to Kinta River (Malaysia) and to classify eight WQ monitoring stations along the river into groups of similar WQ characteristics. FA identified the WQ parameters responsible for variations in Kinta River's WQ and accentuated the roles of weathering and surface runoff in determining the river's WQ. CA grouped the monitoring locations into a cluster of low levels of water pollution (the two uppermost monitoring stations) and another of relatively high levels of river pollution (the mid-, and down-stream stations). DA confirmed these clusters and produced a discriminant function which can predict the cluster membership of new and/or unknown samples. These chemometric techniques highlight the potential for reasonably reducing the number of WQVs and monitoring stations for long-term monitoring purposes.     

Experimental investigation of spatially varying effect of ground motions on bridge pounding

Pounding between adjacent bridge structures with insufficient separation distance has been identified as one of the primary causes of damage in many major earthquakes. It takes place because the closing relative movement is larger than the structural gap provided between the structures. This relative structural response is controlled not only by the dynamic properties of the participating structures but also by the characteristics of the ground excitations. The consequence of the spatial variation of ground motions has been studied by researchers; however, most of these studies were performed numerically. The objective of the present research is to experimentally evaluate the influence of spatial variation of ground motions on the pounding behaviour of three adjacent bridge segments. The investigation is performed using three shake tables. The input spatially varying ground excitations are simulated based on the New Zealand design spectra for soft soil, shallow soil and strong rock using an empirical coherency loss function. Results confirm that the spatially nonniform ground motions increase the relative displacement of adjacent bridge girders and pounding forces. Copyright © 2012 John Wiley & Sons, Ltd.     

Agrobiodiversity of Muda Rice Agroecosystem:A case Study in Largest Granary Area of Malaysia

A survey was carried out at the largest rice cultivation area in Peninsular Malaysia,the Muda rice agroecosystem.The main objective of this study was to document the overall biodiversity associated with this unique agroecosystem by using a combination of sampling techniques in order to record different groups of fauna and flora.The total number of biota recorded and identified from the rice field ecosystem during the study period consisted of 46 species of zooplankton,81 species of aquatic insects,5 species of rodents,7 species of bats,87 species of birds,11 species of fishes and 58 species of weeds.A long-term study should be carried out as more species are expected to be recorded when more of the Muda rice agroecosystem area has been sampled to obtain sufficient information on the Muda rice agrobiodiversity.     

Geospatial and geostatistical approach for groundwater potential zone delineation

Over the past few decades, groundwater has become an essential commodity owing to increased demand as a result of growing population, industrialization, urbanization and so on. The water supply situation is expected to become more severe in the future because of continued unsustainable water use and projected change in hydrometeorological parameters due to climate change. This study is based on the integrated approach of remote sensing, geographical information system and multicriteria decision‐making techniques to determine the most important contributing factors that affect the groundwater resources and to delineate the groundwater potential zones. Ten thematic layers, namely, geomorphology, geology, soil, topographic elevation (digital elevation model), land use/land cover, drainage density, lineament density, proximity of surface water bodies, surface temperature and post‐monsoon groundwater depth, were considered for the present study. These thematic layers were selected for groundwater prospecting based on the literature; discussion with the experts of the Central Ground Water Board, Government of India; field observations; geophysical investigation; and multivariate techniques. The thematic layers and their features were assigned suitable weights on Saaty's scale according to their relative significance for groundwater occurrence. The assigned weights of the layers and their features were normalized by using the analytic hierarchy process and eigenvector method. Finally, the selected thematic maps were integrated using a weighted linear combination method to create the final groundwater potential zone map. The final output map shows different zones of groundwater potential, namely, very good (16%), good (35%), moderate (28%) low (17%) and very low (2.1%). The groundwater potential zone map was finally validated using the discharge and groundwater depth data from 28 and 98 pumping wells, respectively, which showed good correlation. Copyright © 2014 John Wiley & Sons, Ltd.