In the arid region of the Dead Sea, water shortage and the inability to satisfy the increasing domestic water demand threatens sustainable development. In such situations, domestic rainwater harvesting is considered an efficient way to combat water poverty. This paper aims to develop domestic water poverty (DWP) and domestic rainwater harvesting suitability (DRWHS) maps for the West Bank, Palestine. The analytical hierarchy process (AHP) and the GIS-based weighted overlay summation process (WOSP) were utilized in the development of these maps. Results of the DWP map indicate that 57 % of the West Bank is under high to very high poverty of domestic water. The DRWHS map shows that 60 % of the West Bank is highly suitable for domestic rainwater harvesting. Spatial intersection (combined mapping) between DWP and DRWHS maps indicates that around 31 % of the total West Bank areas could be classified as high potential locations (hotspot areas) for adopting rainwater harvesting techniques for domestic purposes. The developed maps are valuable to the stakeholders to better identify the best areas of rainwater harvesting in the West Bank.

In most arid regions of the world, the increasing agricultural water supply–demand gap jeopardizes sustainable agricultural development and, as such, undermines local food security. In such situations, unconventional water resource practices such as agricultural rainwater harvesting (ARWH) can be potentially used to tackle agricultural water poverty (AWP). This study aims to integrate AWP and agricultural rainwater harvesting suitability (ARWHS) maps to identify locations where ARWH can be of the most benefit to the West Bank, Palestine. These maps were developed under the GIS environment. The weighted overlay summation process (WOSP), supported by the analytical hierarchy process (AHP), was utilized. Research findings of the AWP map indicate that high to very high AWP covers about 61% of the study area, whereas, the findings of the ARWHS map shows that highly suitable ARWH areas cover 65% of the total study area. Further, 31% of the study area has highly suitable sites for the implementation of proper ARWH techniques. Finally, the combined mapping between the ARWHS map and agricultural lands indicates that high to very high ARWH-suitable areas cover 53% of the rough grazing areas (62% of the entire West Bank area). Thus, the implementation of proper ARWH techniques in such areas is seen to be a sustainable water management option for achieving agricultural sustainability and, accordingly, improved food security in the West Bank, Palestine.

This paper presents a smart rainwater harvesting (RWH) system to address water scarcity in Palestine. This system aims to improve the water harvesting capacity by using a shared harvesting system at the neighborhood level and digital technology. The presentation of this system is organized as follows: (i) identification of the challenges of the rainwater harvesting at the neighborhood level, (ii) design of the smart RWH system architecture that addresses the challenges identified in the first phase, (iii) realization of a simulation-based reliability analysis for the smart system performance. This methodology was applied to a residential neighborhood in the city of Jenin, Palestine. The main challenges of smart water harvesting included optimizing the shared tank capacity, and the smart control of the water quality and leakage. The smart RWH system architecture design is proposed to imply the crowdsourcing-based and automated-based smart chlorination unit to control and monitor fecal coliform and residual chlorine: screens, filters, and the first flush diverter address RWH turbidity. Water level sensors/meters, water flow sensors/meters, and water leak sensors help detect a water leak and water allocation. The potential time-based reliability (R_e) and volumetric reliability (R_v) for the smart RWH system can reach 38% and 41%, respectively. The implication of the smart RWH system with a dual water supply results in full reliability indices (100%). As a result, a zero potable water shortage could be reached for the dual water supply system, compared to 36% for the municipal water supply and 59% for the smart RWH system. Results show that the smart RWH system is efficient in addressing potable water security, especially when combined with a dual water supply system.

Water governance deals with the steering, organisation and guidance of water resources management. Alongside encouraging technical solutions, effective water governance addresses organisational, legal, financial, socioeconomic and political issues. This paper applies governance matrix, which was tailored to the local context of Palestine. Setting of the matrix dimensions and related evaluation criteria, the questions and indicators were identified based on sectorial gaps using authors' knowledge and experiences in the sector and the review of available documents and reports. The matrix includes 13 dimensions: levels and scales, actors and networks, organisations and organisational capacity, problem perspectives and goal ambitions, water quality, strategies and instruments, rules enforcement, responsibilities and resources, technology systems, funding, infrastructure, political status, and social status. Findings indicate that the two most supportive dimensions, or the least in need of improvement, were water quality and responsibilities and resources, and the two most restrictive dimensions were political status and social status.

Groundwater NO₃ contamination (GNC) threatens the drinkability of water in many countries worldwide. It could cause serious health problems and sometimes lead to death. This paper aims to introduce a comprehensive approach that combines GIS, statistics and Machine Learning (ML) for the groundwater quality management including both water quality assessment and prediction. The performances of this approach are discussed through its application on assessing and predicting nitrate (NO₃) concentrations in the Eocene Aquifer, Palestine. Spatiotemporal records of NO₃ over the period 1982–2019 are integrated in a database and used in this research. The database includes the following factors: well depth, well use, anthropogenic on-ground activities, watersheds, soil type and land use. Geo-statistical assessment using GIS and statistical boxplots is employed to assess the variability of NO₃ concentrations and how they are affected by the independent indicators. Assessment outcomes (NO₃ distribution and the influencing factors) were used to build the Random Forest (RF) prediction model. Such model is used to predict GNC level in groundwater based on multi-influencing factors. Assessment results indicate increasing and decreasing trends of GNC in the southern and middle parts of the study area, respectively. It also provides the RF model by the main influencing factors affecting GNC in the study area which are: well depth, well use, anthropogenic on-ground activities, watersheds and land use. Results indicate that RF has an average and maximum prediction accuracy of 88.5 and 91.7%, respectively. The well depth has the highest influence on GNC. This research could support water authority decision-makers toward the adoption of sustainable groundwater protection plans in Palestine.

This paper aims to assess groundwater potability and palatability in the West Bank, Palestine. It combines the adjusted weighted arithmetic water quality index method (AWAWQIM), a close-ended questionnaire, and step-wise assessment ratio analysis (SWARA) to develop groundwater potability (PoGWQI) and palatability (PaGWQI) indices. Both a geographic information system (GIS) and the kriging interpolation method (KIM) are employed to create spatiotemporal mapping of PoGWQI and PaGWQI. The research is based on data from 79 wells, which were provided by the Palestinian Water Authority (PWA). Data include fecal coliform (FC), nitrate (NO₃), pH, chloride (Cl), sulfate (SO₄), bicarbonate (HCO₃), total dissolved solids (TDS), turbidity, and hardness. Results indicate that 2% and 5% of water samples were unpotable and unpalatable, respectively. Unpotable samples were found in areas with poor sewer networks and intensive use of agrochemicals. All groundwater samples (100%) in the eastern part of the West Bank were unpalatable because of seawater intrusion. Unconfined aquifers were more vulnerable to potability and palatability contamination. It was noticed that PoGWQI is sensitive to FC and NO_3, while PaGWQI is sensitive to HCO₃, TDS, and Cl. Consequently, these quality parameters should be monitored well. The proposed method is of great interest to water decision-makers in Palestine for establishing strategies to protect water resources.