Keeping the water table at a favorable level is quite significant for a sustainable management of groundwater plans. Various management measures need to know the spatial and temporal behavior of groundwater. Therefore, the measurement of groundwater levels are generally carried out at spatially random locations in the field; whereas, most of the groundwater models requires these measurement at ...

estimation of gold reserves and resources has been of interest to mining engineers and geologists for ages. the existence of outlier values shows the economic part of the deposits subject to the fact that don’t depend on the human or technical errors. the presence of these high values causes a pseudo dramatically increment in variance estimation of economical blocks when applying conventional m...

In this work a methodology is presented for the rigorous optimization of nonlinear programming problems in which the objective function and (or) some constraints are represented by noisy implicit black box functions. The special application considered is the optimization of modular process simulators in which the derivatives are not available and some units operations introduce noise preventing...

drought monitoring is a fundamental component of drought risk management. it is normally performed using various drought indices that are effectively continuous functions of rainfall and other hydrometeorological variables. in many instances, drought indices are used for monitoring purposes. geostatistical methods allow the interpolation of spatially referenced data and the prediction of values...

the measurement of wheat crop yield in large areas is time consuming and requires high expenses. one way to save time and cost, using geostatistical methods for mapping crop yield. in this research principle component analysis were used for identifying variables that have correlation with each other, and kriging and cokriging were used to map crop yield prediction. fourty six samples were used ...

The benefits of an integrated geographical information system (GIS) and a geostatistics approach to accurately model the spatial distribution pattern of precipitation are known. However, the determination of the most appropriate geostatistical algorithm for each case is usually neglected, i.e. it is important to select the best interpolation technique for each study area to obtain accurate resu...

Kriging is a spatial interpolation algorithm which provides the best unbiased linear prediction of an observed phenomena by taking a weighted average of samples within a neighbourhood. It is widely used in areas such as geo-statistics where, for example, it may be used to predict the quality of mineral deposits in a location based on previous sample measurements. Kriging has been identified as ...