Yes, I think there is no doubt.

Groundwater modeling has emerged as a powerful tool to help managers to optimize and predict the groundwater resources. Numerical modelling is a helpful tool in the assessment of groundwater resources and analysis of future exploitation scenarios. Groundwater models apply the advantages of recent advances in computer technology, provide real-time modeling, visualization and analysis of two and three-dimensional flow and transport software. User-friendly graphical interfaces make it easier for models to be used. Numerical groundwater models such as SEAWAT-2000 (and many others) have dominated the study of complex groundwater problems because of their ability to tie data and physical principles together into a useful picture of the studied area, capable to produce greater and accurate. Simulation of groundwater modeling is an excellent tool to understand the behavior of an aquifer system subjected to natural and artificial stresses such as pumping.

Regards

As I can see, this depends on your need and type of data you have or you can obtain. Numerical GW modelling can be utilized either by using a commercial, or public domain software such as MODFLOW, Vistas, GMS, etc. or by building your own modules. The draw back of the GW numerical modelling is mainly due to their high demand to data. In addition, building the conceptual model in these sofware, is an intensive time demanding task. If comprehensive aquifer data is available, and detailed aquifer study is required, then GW numerical modelling would be a suitable option. Otherwise, simpler conceptual approaches could be more appropriate for some cases.

Well,

Models most often give results, but they face great difficulty and important challenges, especially in allocating specific conditions, as they need high experience in the field of subsurface structural geology (real information derived from boreholes), in addition to hydrogeological facts, meaning that many assumptions are consistent with most of the laminar flow inhomogeneous media. in most cases, the model results express a general picture that not departs from reality. In real applications and when relying on the results of models, we need to raise the level of safety to meet the possible error rate caused by assumptions while running programs.

Regards

In my opinion, simple and 'almost simple' analytical means have not lost their value. As mentioned above, to apply a digital model you need a great number of data: the geofiltration parameters, the boundary conditions, etc., which you never know exactly. In many cases a simple equation or an easy-to-use app will give an answer that would be as near to reality (or as far from it) as a complex 3D numerical model taking a number of fine effects into account.

I think groundwater model if written with a skillfull molder with a complete set of geological, hydrogeological, and historical records of water levels, climatological data, very well defined boundary and initial conditions is best option to assess the performance of an aquifer in the future (prediction tool). Thus, groundwater flow model is not an assessment tool for the aquifers where insufficient data are available. There are several other better alternatives (e.g. hydro geological studies including drilling and aquifer testing, geophysical surveys and well logging, ..... )

The governing equation for groundwater flow is of partial differential nature with respect to time and space. Analytical solution is one dimensional perhaps with some parameters taken as zero for simplification. What an approximation?. Thus, an effective solution approach is the numerical method of which Finite Element is superior to Finite Difference. You may wish to further consult literature on groundwater modelling.

All the groundwater numerical models become nothing without field works as pumping test , static water level and the aquifer geological formation. So, without this data the results of aquifer assessment without any assurance.

sure, groundwater models are considered important tools to simulate the aquifer by building a conceptual model and predicting its behavior over a time period .these models require many hydrogeological data to solve the differential equation, but for the accurate prediction needs accurate input data to the model including topography, aquifer parameters from pumping test, data of aquifer geometry and accurate boundaries conditions to be determined. in recent times, the integration of groundwater models with geographic information systems and remote sensing has become very valuable in the groundwater aquifer assessment issues.

Groundwater is by far the largest unfrozen freshwater resource on the planet. It plays a critical

role as the bottom of the hydrologic cycle, redistributing water in the subsurface and supporting plants and

surface water bodies. However, groundwater has historically been excluded or greatly simplified in global

models. In recent years, there has been an international push to develop global scale groundwater modeling

and analysis. This progress has provided some critical first steps. Still, much additional work will be needed to

achieve a consistent global groundwater framework that interacts seamlessly with observational datasets and

other earth system and global circulation models. Here we outline a vision for a global groundwater platform

for groundwater monitoring and prediction and identify the key technological and data challenges that are

currently limiting progress. Any global platform of this type must be interdisciplinary and cannot be achieved

by the groundwater modeling community in isolation.

We envision a Global Groundwater Platform that will combine observations and models to provide spatially

and temporally continuous and consistent groundwater monitoring and prediction. We argue that such a system

is needed to address the critical gaps in our understanding and predictive capacity of the terrestrial hydrologic cycle outlined in Section 2. For example, fully coupled groundwater-to-atmosphere ensemble retrospective forecasts

carried out using different configurations (e.g., hydrogeological settings) would represent a viable way

to explore the underlying mechanisms that explain two-way feedbacks between global groundwater states and

natural modes of variability such as ENSO, which are dominant sources of sub seasonal-to-seasonal predictability.

The proposed framework will also provide the opportunity to assess the impact of long-debated issues in

groundwater modeling (e.g., scaling with grid resolution and uncertainty characterization) on the quality of the

atmospheric forecasts. Additionally, the sustainable management of groundwater resources is key to resolving

future challenges of global food and energy security in a world subject to population growth and climate change.

A consistent global groundwater framework is essential to global assessment of the effects of adaptation measures

that are mostly local in nature. Ultimately, this platform can help unlock the potential of groundwater as a source

of predictability in operational weather systems, and produce valuable information to a new and wider range of

decisions related to the water management, agricultural, and energy sectors.