Development of a flood forecasting system using IFAS: a case study of scarcely gauged Jhelum and Chenab river basins

Development of a well-calibrated, distributed hydrological model for flood forecasting based on rainfall and snowmelt is quite challenging, especially when in situ data is limited or unavailable. This paper presents the study carried out to parameterise the Integrated Flood Analysis System (IFAS) model for the trans-boundary, scarcely gauged catchments of Jhelum and Chenab rivers in Pakistan. Rainfall-runoff analysis was performed with a two-layered tank configuration, integrating snowmelt and dam and barrage operation from the very upstream in India to Trimmu Barrage in Pakistan. A grid size of 5?×?5 km was considered. Global map topography, land cover and soil data was utilised. The model was tested considering different magnitudes of floods of the years 2014, 2015 and 2017. The results showed that the satellite rainfall product, i.e. Global Satellite Mapping of Precipitation (GSMaP-NRT), underestimated the rainfall volume, compared to the ground-gauged rainfall. The GSMaP-IF correction method showed poor performance owing to the lack of ground observatory rainfall data for correcting the trans-boundary part of the basin. The GSMaP-Type1 correction method showed good results, except for the confluence point where complex flow conditions were not properly reproduced by the model. In addition, the incorporation of dam and barrages in the model improved the simulated flow results. It is concluded that the satellite rainfall estimates must be corrected to improve the results. Snowmelt module estimated the snowmelt contribution as 3 to 7% and 4 to 23% of the average daily discharge during the monsoon season at Mangla Dam and Marala Barrage, respectively, during 2014 and 2015. This study assessed various correction methods and concluded that the model and methodology used in the study functioned well with suitable precipitation.     

Seismic based characterization of total organic content from the marine Sembar shale,Lower Indus Basin,Pakistan

The exploration and production of unconventional resources has increased significantly over the past few years around the globe to fulfill growing energy demands. Hydrocarbon potential of these unconventional petroleum systems depends on the presence of significant organic matter; their thermal maturity and the quality of present hydrocarbons i.e. gas or oil shale. In this work, we present a workflow for estimating Total Organic Content (TOC) from seismic reflection data. To achieve the objective of this study, we have chosen a classic potential candidate for exploration of unconventional reserves, the shale of the Sembar Formation, Lower Indus Basin, Pakistan. Our method includes the estimation of TOC from the well data using the Passey’s ΔlogR and Schwarzkofp’s methods. From seismic data, maps of Relative Acoustic Impedance (RAI) are extracted at maximum and minimum TOC zones within the Sembar Formation. A geostatistical trend with good correlation coefficient (R²) for cross-plots between TOC and RAI at well locations is used for estimation of seismic based TOC at the reservoir scale. Our results suggest a good calibration of TOC values from seismic at well locations. The estimated TOC values range from 1 to 4% showing that the shale of the Sembar Formation lies in the range of good to excellent unconventional oil/gas play within the context of TOC. This methodology of source rock evaluation provides a spatial distribution of TOC at the reservoir scale as compared to the conventional distribution generated from samples collected over sparse wells. The approach presented in this work has wider applications for source rock evaluation in other similar petroliferous basins worldwide.     

Bayesian inversion of synthetic AVO data to assess fluid and shale content in sand-shale media

Reservoir characterization of sand-shale sequences has always challenged geoscientists due to the presence of anisotropy in the form of shale lenses or shale layers. Water saturation and volume of shale are among the fundamental reservoir properties of interest for sand-shale intervals, and relate to the amount of fluid content and accumulating potentials of such media. This paper suggests an integrated workflow using synthetic data for the characterization of shaley-sand media based on anisotropic rock physics (T-matrix approximation) and seismic reflectivity modelling. A Bayesian inversion scheme for estimating reservoir parameters from amplitude vs. offset (AVO) data was used to obtain the information about uncertainties as well as their most likely values. The results from our workflow give reliable estimates of water saturation from AVO data at small uncertainties, provided background sand porosity values and isotropic overburden properties are known. For volume of shale, the proposed workflow provides reasonable estimates even when larger uncertainties are present in AVO data.     

A continuous time delay-difference type model (CTDDM) applied to stock assessment of the southern Atlantic albacore <Emphasis Type="Italic">Thunnus alalunga</Emphasis>

A continuous time delay-diff erence model (CTDDM) has been established that considers continuous time delays of biological processes. The southern Atlantic albacore (Thunnus alalunga) stock is the one of the commercially important tuna population in the marine world. The age structured production model (ASPM) and the surplus production model (SPM) have already been used to assess the albacore stock. However, the ASPM requires detailed biological information and the SPM lacks the biological realism. In this study, we focus on applying a CTDDM to the southern Atlantic albacore (T. alalunga) species, which provides an alternative method to assess this fishery. It is the first time that CTDDM has been provided for assessing the Atlantic albacore (T. alalunga) fishery. CTDDM obtained the 80% confidence interval of MSY (maximum sustainable yield) of (21 510 t, 23 118t). The catch in 2011 (24 100 t) is higher than the MSY values and the relative fishing mortality ratio (F ₂₀₁₁/F _MSY) is higher than 1.0. The results of CTDDM were analyzed to verify the proposed methodology and provide reference information for the sustainable management of the southern Atlantic albacore stock. The CTDDM treats the recruitment, the growth, and the mortality rates as all varying continuously over time and fills gaps between ASPM and SPM in this stock assessment.     

Strengthening crushed coarse aggregates using bio-grouting

This paper focuses on using urea hydrolysis as a bio-grouting process to increase the strength of crushed aggregates commonly used in stone columns. Various reagent phases (2, 4, 6 and 12 phases) consisted of alternately percolating solutions containing bacterial suspension and cementation solution through the soil column. In addition, a multi-soil lift strategy with options of up to four soil lifts was undertaken to test the applicability of bio-grout to cement crushed aggregate columns. While the average amount of calcium carbonate precipitation was roughly unchanged in both techniques, the distribution within the crushed aggregate columns was heterogeneous. However, the distribution of the precipitated calcium carbonate is almost uniform in crushed aggregates treated by a two-soil lift strategy and a four-phase treatment strategy. It is also deducted that both techniques can be combined to gain a uniform calcium carbonate and strength along a long sand/stone column. Furthermore, a one-soil lift resulted in higher strength than using multi-soil lifts, and a maximum strength of approximately 2.3 MPa was achieved using 4-reagent phase treatment strategy. Scanning electron microscopy and electron dispersive spectroscopy analysis validate that calcium carbonate was deposited as white crystals on the surface of the crushed aggregate particles.     

Effect of particle size distribution on the bio-cementation of coarse aggregates

The effect of grain size distribution on the unconfined compressive strength (UCS) of bio-cemented granular columns is examined. Fine and coarse aggregates were mixed in various percentages to obtain five different grain size distributions. A four-phase percolation strategy was adopted where a bacterial suspension and a cementation solution (urea and calcium chloride) were percolated sequentially. The results show that a gap-graded particle size distribution can improve the UCS of bio-cemented coarser granular materials. A maximum UCS of approximately 575 kPa was achieved with a particle size distribution containing 75% coarse aggregate and 25% fine aggregate. Furthermore, the minimum UCS obtained has applications where mitigation of excessive bulging of stone/sand columns, and possible slumping that might occur during their installation, is needed. The finding also implies that the amount of biochemical treatments can be reduced by adding fine aggregate to coarse aggregate resulting in effective bio-cementation within the pore matrix of the coarse aggregate column as it could substantially reduce the cost associated with bio-cementation process. Scanning electron microscopy results confirm that adding fine aggregate to coarse aggregate provides more bridging contacts (connected by calcium carbonate precipitation) between coarse aggregate particles, and hence, the maximum UCS achieved was not necessarily associated with the maximum calcium carbonate precipitation.