Retrieving of Land Surface Temperature Using Thermal Remote Sensing and GIS Techniques in Kandaihimmat Watershed,Hoshangabad, Madhya Pradesh

Remotely sensed thermal infrared (TIR) data have been widely used to retrieve land surface temperature (LST). LST is an important parameter in the studies of urban thermal environment and dynamics. In the study, an attempt has been made using LANDSAT 8 thermal imagery to compute LST and the associated land cover parameters viz; land surface emissivity (LSE), normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI) and normalized difference water index (NDWI). Landsat 8 TIRS band 10 & 11 (thermal bands) during 21 Oct. 2016, 22 Nov.2016, 24 Dec. 2016 and 09 Jan. 2017 were processed for LST analysis. However, band 5 & band 4 of the imagery was processed for NDVI, band 6 & band 5 for NDBI and band 2 & band 5 for NDWI analysis. LST has been derived from both the bands 10 &11 and validated by in-situ observations on the date and time of satellite overpass from the study area. Band 10 derived LST have shown much temperature difference while comparing with the in-situ observations. However, LST derived from band 11 found similar & close to the in-situ measurements. Relationship between band 11 results and in-situ observed measurements were developed, which has showing a strong correlation with (r² = 0.991). Land surface emissivity were also evaluated which shows variation in different land cover surfaces like vegetation, settlement, forest cover and water body. The study has proven that land surface temperature derived from satellite band 11 is the actual surface temperature of the study area.     

Predicting groundwater level of wells in the Diyala River Basin in eastern Iraq using artificial neural network

Al-Mansourieh zone is a part of Al-Khalis City within the province of Diyala and located in the Diyala River Basin in eastern Iraq with a total area about 830 km2.Groundwater is the main water source for agriculture in this zone.Random well drilling without geological and hydraulic information has led the most of these wells to dry up quickly.Therefore,it is necessary to estimate the levels of groundwater in wells through observed data.In this study,Alyuda NeroIntelligance 2.1 software was applied to predict the groundwater levels in 244 wells using sets of measured data.These data included the coordinates of wells(x,y),elevations,well depth,discharge and groundwater levels.Three ANN structures(5-3-3-1,5-10-10-1 and 5-11-11-1)were used to predict the groundwater levels and to acquire the best matching between the measured and ANN predicted values.The coefficient of correlation,coefficient determination(R2)and sum-square error(SSE)were used to evaluate the performance of the ANN models.According to the ANN results,the model with the three structures has a good predictability and proves more effective for determining groundwater level in wells.The best predictor was achieved in the structure 5-3-3-1,with R2 about 0.92,0.89,0.84 and 0.91 in training,validation,testing and all processes respectively.The minimum average error in the best predictor is achieved in validation and testing processes at about 0.130 and 0.171 respectively.On the other hand,the results indicated that the model has the potential to determine the appropriate places for drilling the wells to obtain the highest level of groundwater.     

Dynamics of hourly sea level at Hillarys Boat Harbour,Western Australia: a chaos theory perspective

Water level forecasting using recorded time series can provide a local modelling capability to facilitate local proactive management practices. To this end, hourly sea water level time series are investigated. The records collected at the Hillarys Boat Harbour, Western Australia, are investigated over the period of 2000 and 2002. Two modelling techniques are employed: low-dimensional dynamic model, known as the deterministic chaos theory, and genetic programming, GP. The phase space, which describes the evolution of the behaviour of a nonlinear system in time, was reconstructed using the delay-embedding theorem suggested by Takens. The presence of chaotic signals in the data was identified by the phase space reconstruction and correlation dimension methods, and also the predictability into the future was calculated by the largest Lyapunov exponent to be 437 h or 18 days into the future. The intercomparison of results of the local prediction and GP models shows that for this site-specific dataset, the local prediction model has a slight edge over GP. However, rather than recommending one technique over another, the paper promotes a pluralistic modelling culture, whereby different techniques should be tested to gain a specific insight from each of the models. This would enable a consensus to be drawn from a set of results rather than ignoring the individual insights provided by each model.     

A spatio-temporal three-dimensional conceptualization and simulation of Dera Ismail Khan alluvial aquifer in visual MODFLOW: a case study from Pakistan

Dera Ismail Khan (DIK) is situated in the Lower Indus Basin of Pakistan. The land use has been changed in the canal command area due to irrigation activities near the Indus River. To check the current status and predict the groundwater levels in the area, the unconfined aquifer has been simulated in Visual MODFLOW for a period of 35 years, i.e., from 1985 to 2020. The 2900-km² area has been modeled with a grid of 500 by 500 m and the depth set to 100 m. The aquifer in the study area has been divided vertically and laterally into three and ten zones, respectively, for the characterization. Water wells and streams were used as the sinks and hydrologic boundaries, respectively. The model was successfully calibrated in steady and the non-steady state. The simulation revealed that the whole simulation can be divided into two phases, i.e., before and after the construction of the Chashma Right Bank Canal (CRBC), whereas the results were summarized in the form of water table depth maps and groundwater budget calculations. To determine the groundwater sustainability, a conjunctive use scenario has been employed to simulate the aquifer dynamics till 2020. The simulation revealed incremental drawdowns till the end.     

Dynamics of seasonal recharge beneath a semiarid vegetation on the gnangara mound,Western Australia

To estimate seasonal changes in recharge to the underlying sandy aquifer, the soil water dynamics of the unsaturated zone was monitored down to a depth of 20 m over a period of three years (1985 to 1987). The measurements were made by a neutron probe at eight locations beneath a native vegetation in a semiarid region, Western Australia, receiving precipitation of 775 mm yr^?1. A relatively simple method, based on the analyses of sequentially measured soil water profiles involving utilization of zero flux plane in the unsaturated zone, is presented and used to compute seasonal recharge rates. Drainage fluxes (recharge rates) below two specified depths were estimated. These were: R₁ (water flux at a depth of 10 m, just below the maximum rooting depth) and R₂ (water flux at a depth of 18 m, just above the water table). These two estimates were significantly different both on a seasonal and annual basis, but their cumulative values for the three year period were very similar. While the annual precipitation varied from 525 to 850 mm yr^?1, the corresponding spatially averaged R₁ varied from 34 to 149 mm yr^?1, and R₂ varied from 65 to 80 mm yr^?1. A significant difference in recharge between the upslope and downslope positions on a hillslope was ascribed to differences in vegetation density of the understorey and differences in hydraulic properties of subsoils. For the three year period, the average R₁ and R₂ were 13 per cent and 10 per cent of the precipitation respectively. These values compare favourably with a long-term estimate based on an environmental tracer technique.     

Outlier identification and correction for GRACE aggregated data

Gravity measurements within the Gravity Recovery and Climate Experiment (GRACE) provide a direct measure of monthly changes in mass over the Earth’s land masses. As such changes in mass mainly correspond to water storage changes, these measurements allow to close the continental water balance on large spatial scales and on a monthly time scale within the respective error bounds. When quantifying uncertainties, positive and negative peaks are detected in GRACE aggregated monthly time series (from different data providers) that do not correspond to hydrological or hydro-meteorological signals. These peaks must be interpreted as outliers, which carry the danger of signal degradation. In this paper an algorithm is developed to identify outliers and replace them with hydrologically plausible values. The algorithm is based on a statistical approach in which hydrological and hydro-meteorological signals are used to control the algorithm. The procedure of outlier detection is verified by evaluating catchment based aggregated GRACE monthly signals with ground truth from hydrology and hydro-meteorological signals. The results show improvement in the correlation of GRACE versus hydrometeorological and hydrological signals in most catchments. Also, the noise level is significantly reduced over 255 largest catchments.     

Comparison and Hydrochemical Characterization of Groundwater Resources in the Arabian Peninsula: A Case Study of Al-Baha and Al-Qassim in Saudi Arabia

Water Resources - The objective of this study was to compare and assess the quality and study the hydrochemistry of groundwater in the Al-Baha and Al-Qassim areas, representing the Arabian Shield...     

Drained cavity expansions in soils of finite radial extent subjected to two boundary conditions

The problem of drained cavity expansion in soils of finite radial extent is investigated. Cylindrical and spherical cavities expanded from zero radius subjected to either constant stress or zero displacement at the finite boundary are considered. The generalised analytical solution procedure presented enables more advanced constitutive models to be implemented than have been possible in previous studies. Results generated for Sydney quartz sand highlight substantial differences between cavity limit pressures for the two boundary conditions and for boundaries of finite and infinite radial extent. This is of significance in accounting for boundary effects when interpreting cone penetration tests conducted in calibration chambers. Copyright © 2011 John Wiley & Sons, Ltd.     

Benthic nutrient fluxes along the Laurentian Channel: Impacts on the N budget of the St. Lawrence marine system

Water column concentrations and benthic fluxes of dissolved inorganic nitrogen (DIN) and oxygen (DO) were measured in the Gulf of St. Lawrence and the Upper and Lower St. Lawrence Estuary (USLE and LSLE, respectively) to assess the nitrogen (N) budget in the St. Lawrence (SL) system, as well as to elucidate the impact of bottom water hypoxia on fixed-N removal in the LSLE. A severe nitrate deficit, with respect to ambient phosphate concentrations (N*∼−10 μmol L⁻¹), was observed within and in the vicinity of the hypoxic bottom water of the LSLE. Given that DO concentrations in the water column have remained above 50 μmol L⁻¹, nitrate reduction in suboxic sediments, rather than in the water column, is most likely responsible for the removal of fixed N from the SL system. Net nitrate fluxes into the sediments, derived from pore water nitrate concentration gradients, ranged from 190 μmol m⁻² d⁻¹ in the hypoxic western LSLE to 100 μmol m⁻² d⁻¹ in the Gulf. The average total benthic nitrate reduction rate for the Laurentian Channel (LC) is on the order of 690 μmol m⁻² d⁻¹, with coupled nitrification-nitrate reduction accounting for more than 70%. Using average nitrate reduction rates derived from the observed water column nitrate deficit, the annual fixed-N elimination within the three main channels of the Gulf of St. Lawrence and LSLE was estimated at 411 × 10⁶ t N, yielding an almost balanced N budget for the SL marine system.