Hydrogeologic assessment of escalating groundwater exploitation in the Indus Basin, Pakistan

Groundwater development has contributed significantly to food security and reduction in poverty in Pakistan. Due to rapid population growth there has been a dramatic increase in the intensity of groundwater exploitation leading to declining water tables and deteriorating groundwater quality. In such prevailing conditions, the hydrogeological appraisal of escalating groundwater exploitation has become of paramount importance. Keeping this in view, a surface water–groundwater quantity and quality model was developed to assess future groundwater trends in the Rechna Doab (RD), a sub-catchment of the Indus River Basin. Scenario analysis shows that if dry conditions persist, there will be an overall decline in groundwater levels of around 10 m for the whole of RD during the next 25 years. The lower parts of RD with limited surface water supplies will undergo the highest decline in groundwater levels (10 to 20 m), which will make groundwater pumping very expensive for farmers. There is a high risk of groundwater salinization due to vertical upconing and lateral movement of highly saline groundwater into the fresh shallow aquifers in the upper parts of RD. If groundwater pumping is allowed to increase at the current rate, there will be an overall decline in groundwater salinity for the lower and middle parts of RD because of enhanced river leakage.     

Shallow and deep aquifer hydrochemistry and chemical variability of water quality at Shariatpur district, Bangladesh

Water quality and hydrochemistry of Shariatpur district were evaluated in terms of hydrochemical composition and some important physico-chemical parameters. The groundwater of the study area is good for drinking, domestic as well as for irrigation purposes. Among the major ions, shallow tube well waters give higher concentration of Ca²⁺ which ranges from 24 to 260 mg/L. The deep tubewell waters show higher concentration of Na⁺ which varies from 74 to 582 mg/L during dry season. Among the trace elements most of the shallow aquifer samples show higher concentration of Fe²⁺, Mn²⁺ and As. Concentration of Fe²⁺ varies from 0.655 to 18.8 mg/L, and Mn²⁺ from trace to 0.868 mg/L during dry period. Hydrochemical analyses reveal significant seasonal variation in water quality of shallow aquifer. Both the shallow aquifer and the surface water of the study area are predominantly of Ca–Mg–HCO₃ type, while the deep aquifer water is mainly of Na–K–Cl–SO₄ type with slight inclination to Ca–Mg–HCO₃ type. The study area is suitable for groundwater development if comprehensive and holistic approaches towards water resource management are taken into consideration.     

Modelling Short‐Scale Variability and Uncertainty During Mineral Resource Estimation Using a Novel Fuzzy Estimation Technique

For mineral resource assessment, techniques based on fuzzy logic are attractive because they are capable of incorporating uncertainty associated with measured variables and can also quantify the uncertainty of the estimated grade, tonnage etc. The fuzzy grade estimation model is independent of the distribution of data, avoiding assumptions and constraints made during advanced geostatistical simulation, e.g., the turning bands method. Initially, fuzzy modelling classifies the data using all the component variables in the data set. We adopt a novel approach by taking into account the spatial irregularity of mineralisation patterns using the Gustafson–Kessel classification algorithm. The uncertainty at the point of estimation was derived through antecedent memberships in the input space (i.e., spatial coordinates) and transformed onto the output space (i.e., grades) through consequent membership at the point of estimation. Rather than probabilistic confidence intervals, this uncertainty was expressed in terms of fuzzy memberships, which indicated the occurrence of mixtures of different mineralogical phases at the point of estimation. Data from different sources (other than grades) could also be utilised during estimation. Application of the proposed technique on a real data set gave results that were comparable to those obtained from a turning bands simulation.     

Effects of convective available potential energy,temperature and humidity on the variability of thunderstorm frequency over Bangladesh

Theoretical and Applied Climatology - The present study examines the effects of convective available potential energy (CAPE), temperature and humidity on the spatiotemporal variation of...     

Water sustainability model for estimation of groundwater availability in Kemuning district,Riau-Indonesia

There are rising interests in the utility of groundwater in various aspects,which is capable of triggering problematic issues.The excessive exploitation for anthropologic uses,without regards to aquifer capacity,will decreases the water table as well as capacity of groundwater in the aquifer.This research was aimed to provide aquifer model of underground water by consideration of various environmental factors,with the propensity of being modeled,in an attempt to predict groundwater conditions in subsequent years.The purpose of this research was to forecast water requirements,availability,as well as three-dimensional model of groundwater depth in Kemuning,Indragiri Hilir Regency-Indonesia between 2015 and 2022.Furthermore,various environmental factors,from aquifer profiles to anthropologic demand,are taken into account in the evaluated model,including water requirements,encompassing recharge and aquifer parameters,which consists of storativity and transmissivity.From anthropologic side are domestic requirements,trade,public facilities,agriculture,and livestock.The results show that groundwater availability in Kemuning is to be safe condition,and average difference is 1.06×108 m3/yr.The coefficient of storativity and transmissivity are 16.514 m2/day and 9897.26 m2/day,respectively,while the average depth was recorded as 2.8965 m to 10.4927 m.     

Performance of CMORPH,TMPA, and PERSIANN rainfall datasets over plain,mountainous, and glacial regions of Pakistan

The present study aims at the assessment of six satellite rainfall estimates (SREs) in Pakistan. For each assessed products, both real-time (RT) and post adjusted (Adj) versions are considered to highlight their potential benefits in the rainfall estimation at annual, monthly, and daily temporal scales. Three geomorphological climatic zones, i.e., plain, mountainous, and glacial are taken under considerations for the determination of relative potentials of these SREs over Pakistan at global and regional scales. All SREs, in general, have well captured the annual north-south rainfall decreasing patterns and rainfall amounts over the typical arid regions of the country. Regarding the zonal approach, the performance of all SREs has remained good over mountainous region comparative to arid regions. This poor performance in accurate rainfall estimation of all the six SREs over arid regions has made their use questionable in these regions. Over glacier region, all SREs have highly overestimated the rainfall. One possible cause of this overestimation may be due to the low surface temperature and radiation absorption over snow and ice cover, resulting in their misidentification with rainy clouds as daily false alarm ratio has increased from mountainous to glacial regions. Among RT products, CMORPH-RT is the most biased product. The Bias was almost removed on CMORPH-Adj thanks to the gauge adjustment. On a general way, all Adj versions outperformed their respective RT versions at all considered temporal scales and have confirmed the positive effects of gauge adjustment. CMORPH-Adj and TMPA-Adj have shown the best agreement with in situ data in terms of Bias, RMSE, and CC over the entire study area.     

Analysis and farmers’ perception of climate change in the Kashmir Valley,India

Theoretical and Applied Climatology - Analysis of climatic variables is important for the detection and attribution of climate change trends and has received considerable attention from researchers...     

Empirical assessment of rockfall and debris flow risk along the Karakoram Highway,Pakistan

Natural Hazards - The Karakoram Highway links north Pakistan with southwest China. It passes through unique geomorphological, geological and tectonic setting. This study focused 200-km-long section...     

A new magnitude category disaggregation approach for temporal high‐resolution rainfall intensities

Simulation of quick runoff components such as surface runoff and associated soil erosion requires temporal high‐resolution rainfall intensities. However, these data are often not available because such measurements are costly and time consuming. Current rainfall disaggregation methods have shortcomings, especially in generating the distribution of storm events. The objectives of this study were to improve point rainfall disaggregation using a new magnitude category rainfall disaggregation approach. The procedure is introduced using a coupled disaggregation approach (Hyetos and cascade) for multisite rainfall disaggregation. The new procedure was tested with ten long‐term precipitation data sets of central Germany using summer and winter precipitation to determine seasonal variability. Results showed that dividing the rainfall amount into four daily rainfall magnitude categories (1–10, 11–25, 26–50, >50 mm) improves the simulation of high rainfall intensity (convective rainfall). The Hyetos model category approach (Hyetos_Cat) with seasonal variation performs representative to observed hourly rainfall compared with without categories on each month. The mean absolute percentage accuracy of standard deviation for hourly rainfall is 89.7% in winter and 95.6% in summer. The proposed magnitude category method applied with the coupled Hyetos_Cat–cascade approach reproduces successfully the statistical behaviour of local 10‐min rainfall intensities in terms of intermittency as well as variability. The root mean square error performance statistics for disaggregated 10‐min rainfall depth ranges from 0.20 to 2.38 mm for summer and from 0.12 to 2.82 mm for the winter season in all categories. The coupled stochastic approach preserves the statistical self‐similarity and intermittency at each magnitude category with a relatively low computational burden. Copyright © 2014 John Wiley & Sons, Ltd.