Groundwater is the main source of water in many countries all over the world. Prevention of the pollution of this source is essential for a sustainable utilization. Nitrate pollution of groundwater is a common problem due to the association between intensive agriculture to achieve food security and fertilization. For an efficient management of groundwater pollution from nitrate, the first step would be to quantify the different sources of nitrogen in the aquifer of concern. This paper aims at demonstrating a general approach based on Geographic Information Systems (GIS) to characterize the spatial distribution of the nitrogen amounts in the area of the Eocene aquifer (Palestine). The aquifer is heavily utilized for agricultural and domestic water supply. Fertilization in the study area is a widespread practice. As a result, the aquifer is undergoing a nitrate pollution problem. The methodology relies mainly on specifying all the sources of nitrogen in the aquifer area using GIS to account for spatiality. Thereafter, GIS attribute tables and Excel spreadsheets were utilized to quantify the magnitudes of nitrogen from the different sources. Maps of the corresponding on-ground nitrate, ammonium, organic nitrogen and total nitrogen were developed for the study area. The results indicate that the total on-ground annual nitrogen loading in the study area is about 3260 tons of which 38% is attributed to fertilizers (chemical and manure) where the dominant form of nitrogen is NH₄ (58.3%). The average total on-ground nitrogen loading is 7028 kg-N/km²·year. The estimated annual nitrate leaching to the aquifer is 1968 kg-N/km². The areas of high sources of nitrogen have long-term impacts on the degradation of the water quality of the aquifer. It is therefore essential to build up on the outcomes of this work and to develop a nitrate fate and transport model for the Eocene aquifer. This model will enable the stakeholders to arrive at the efficient alternatives to manage the nitrate contamination of the aquifer.

Groundwater is a crucial resource for water supply and irrigation in many parts of the world, especially in the Middle East. The Eocene aquifer, located in the northern part of the West Bank, Palestine, is threatened by unsustainable groundwater abstractions and on-ground pollution. Analysis and management of this aquifer are challenging because of limited data availability. This research contributes to the long-term sustainability of the aquifer by model-based design of future abstraction strategies considered within an uncertainty analysis framework. The methodology employed started with development of a single-layer steady-state MODFLOW groundwater model of the area, followed by uncertainty analysis of model parameters using Monte Carlo simulations. The same model was afterwards coupled with a Successive Linear Programming (SLP) optimization algorithm, implemented in the Groundwater Management tool (GWM) of the United States Geological Survey (USGS). The purpose of optimization was deriving five optimal abstraction strategies, each aiming to maximize groundwater abstraction, subject to different constraints regarding groundwater depletion. Given the uncertainty of model parameters, the sensitivity and reliability of these optimal strategies were then tested. Sensitivity was checked for two optimal strategies by performing re-optimization with different values of uncertain model parameters (one at a time). Reliability of the five strategies was tested by analyzing the extent of constraints’ violation for each strategy when varying the uncertain parameters using Monte Carlo simulations. Finally, the model was used for determining capture zones of wells for the five optimal abstraction strategies, land-use in these capture zones, and the associated estimates of on-ground nitrogen loading. The developed strategies were then deployed in a web-based decision support application (named Groundwater Decision Support System—GDSS), together with other relevant information. Users can analyze results of different optimal strategies in terms of groundwater level variations and total water balance results, and test consequences of uncertain parameters. Capture zones of wells for different abstraction strategies, together with land-use and on-ground nitrogen loading in these capture zones, are also presented. Results show that critical uncertain parameters are recharge, hydraulic conductivity, and conductance at key boundary condition locations. Optimal abstraction strategies results indicate that an increase in total abstractions could be between 5% and 20% from the current level (estimated at about 56 × 10⁶ m³/year, which is about 74% of estimated annual recharge). The uncertain parameters, however, are impacting the sensitivity and the reliability of the optimal strategies to variable degrees. Recharge and hydraulic conductivity are the most critical uncertain parameters regarding sensitivity of the optimal strategies, while reliability is also impacted by the level of abstraction proposed in a given strategy (number, locations, and abstraction rates of new wells). The main novelty and contribution of this research is in combining modelling, uncertainty analysis, and optimization techniques in a comprehensive decision support system for the area of the Eocene aquifer, characterized with limited data availability.