In this work, we measure the performance of the fixed stress split algorithm for the immiscible water-oil flow coupled with linear poromechanics. The two-phase flow equations are solved on general hexahedral elements using the multipoint flux mixed finite element method whereas the poromechanics equations are discretized using the conforming Galerkin method. We introduce a rigorous calculation of the update in poroelastic properties during the iterative solution of the coupled system equations. The effects of the coupling parameter on the performance of the fixed stress algorithm is demonstrated in two field studies: the Frio oil reservoir and the Cranfield injection site.

Jordan suffers from water scarcity and groundwater covers the majority of Jordan’s water supply. Therefore, there is an urgent need to manage this resource conscientiously. A regional numerical groundwater flow model, developed as part of a decision support system for the country of Jordan, allows for quantification of the overexploitation of groundwater resources and enables determination of the extent of unrecorded agricultural groundwater abstraction. Groundwater in Jordan is abstracted from three main aquifers partly separated by aquitards. With updated geological, structural, and hydrogeological data available in the country, a regional numerical groundwater flow model for the whole of Jordan and the southernmost part of Syria was developed using MODFLOW. It was first calibrated for a steady-state condition using data from the 1960s, when groundwater abstraction was negligible. After transient calibration using groundwater level measurements from all aquifers, model results reproduce the large groundwater-level declines experienced in the last decades, which have led to the drying out of numerous springs. They show a reversal of groundwater flow directions in some regions, due to over-abstraction, and demonstrate that documented abstractions are not sufficient to cause the observed groundwater-level decline. Only after considering irrigation water demand derived from remote sensing data, the model is able to simulate these declines. Illegal abstractions can be quantified and predictive scenarios show the potential impact of different management strategies on future groundwater resources.