Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the Bayesian Maximum Entropy (BME) algorithm, using soil temperature as auxiliary information, to stu...

Abstract The presence of an economical solution to predict soil behaviour is essential for new construction areas. This paper aims investigate the ultimate interpolation method predicting bearing capacity An-Najaf city-Iraq based on field investigation information. Firstly, engineering was calculated in-site N-SPT values using dynamic loading 464 boreholes with depths 0–2 m, Meyerhof formula. d...

In this paper, we aim to achieve two specific objectives. The first one is to examine the applicability of wavelet neural network (WNN) technique in ore grade estimation, which is based on integration between wavelet theory and Artificial Neural Network (ANN). Different wavelets are applied as activation functions to estimate Cu grade of borehole data in the hypogene zone of porphyry ore deposi...

Precipitation data provide a crucial input for examining hydrological issues, including watershed management and mitigation of the effects floods, drought, landslides. However, they are collected frequently from scarce often insufficient network ground-based rain-gauge stations to generate continuous precipitation maps. Recently, maps derived satellite have not been sufficiently linked rain gau...

When analysing data from computationally expensive simulation codes or process measurements, surrogate modelling methods are firmly established as facilitators for design space exploration, sensitivity analysis, visualisation and optimisation. Kriging is a popular surrogate modelling technique for data based on deterministic computer experiments. There exist several types of Kriging, mostly dif...

It is well known that climate and circulation model simulation output are often systematically biased. However, existing bias correction methods typically ignore spatial autocorrelation of the biases correct only overall mean variance, resulting in mismatched variability between bias-corrected simulations observations. In this study, we propose using regression kriging (RK) to for biased patter...

Abstract This study aims to assess the urban air quality, and map NO 2 , SO PM 10 profiles using two widely spatial interpolation methods, ordinary kriging (OK) inverse distance weighting (IDW) by estimating their concentrations at distinct non-monitored locations. Assessment mapping of pollutants in this help with policy formulation decision-making. Kota, industrial educational hub Rajasthan (...

Due to uncertain nature of grade in ore deposits, considering uncertainty is inevitable in geological modelling of resources and mine planning. In other words, uncertainty in grade of mineralized materials, is one of the most significant parameters need attention in mine planning. In this paper, a comparative procedure utilizing Sequential Gaussian Simulation (SGS) and traditional Ordinary Krig...