Water scarcity, a critical issue impacting human society and ecosystems, is exacerbated by climate change and increasing water demand from urbanization and agriculture. While existing assessments primarily focus on water quantity, this study investigates the combined effects of water quantity and quality, specifically nitrogen pollution, on future water scarcity. The limited availability of freshwater, approximately 0.02% of Earth's total water, necessitates a thorough understanding of its availability and limitations. While global annual water withdrawals are currently lower than discharge, spatial and temporal variations cause regional mismatches leading to scarcity. Future water scarcity is projected to worsen due to climate change altering hydrological patterns and socioeconomic changes like land-use change, irrigation, and dam construction which impact water discharge and demand. Anthropogenic alterations in major economic areas significantly exceed the effects of climate change alone, further diminishing runoff. Population growth and economic expansion contribute to heightened food and energy demands, driving up water consumption. This research addresses the gap in understanding by incorporating water pollution into a global assessment of future water scarcity.

Existing global water scarcity studies predominantly focus on water quantity, neglecting the significant contribution of water quality degradation. While indicators like water quality dilution (WQD) and Quantity-Quality-Environmental flow requirement (QQE) exist, they haven't been applied globally or comprehensively. This study introduces a 'clean-water scarcity' assessment, integrating both water quantity and quality aspects, building on previous works that individually assessed these factors. The study compares its findings to other assessments focusing solely on water quantity, highlighting the differences in identified hotspots and the underestimation of water scarcity in regions with high pollution levels but relatively high runoff. The study also acknowledges previous estimations of populations affected by water scarcity, noting that its inclusion of water quality significantly increases these estimates, aligning with findings that highlight the combined effects of quantity and quality challenges.

This study uses an integrated modeling framework combining land-system, hydrological, and water quality models (MAgPIE, VIC, and MARINA-Nutrients) to assess clean-water scarcity. The framework simulates land use, hydrological processes, and nitrogen pollution to calculate clean-water scarcity indicators for over 10,000 sub-basins globally for 2010 and 2050 under three Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs) scenarios representing different levels of climate change and socioeconomic activities. The quantity-based scarcity indicator (Squantity) utilizes VIC model simulations of river discharge and sector withdrawals. The quality-based indicator (Squality) uses the ratio of nitrogen pollution simulated by VIC, MAGPIE (nitrogen budgets), and MARINA-Nutrients (river exports of TDN from diffuse and point sources). Hotspots are identified based on thresholds for high quantity-based, quality-based, or both scarcity types. The MAGPIE model simulates land use, agriculture, and nitrogen budgets, while MARINA-Nutrients assesses riverine nitrogen pollution. The VIC model simulates water balance and water withdrawals. The study acknowledges uncertainties related to model inputs and approaches, comparing its nitrogen budget with other high-resolution data to build confidence in the results. Annual temporal and sub-basin spatial scales are used, acknowledging limitations regarding intra-annual variability and specific flow components. The analysis utilizes a threshold for TDN concentrations to avoid eutrophication, acknowledging potential biases. Three scenarios (SSP1-RCP2.6, SSP2-RCP2.6, SSP5-RCP8.5) are used to project future water scarcity under different socioeconomic and climate conditions. The scenarios include assumptions on sewage treatment, land use, agriculture, and water withdrawals.

The study reveals a dramatic increase in clean-water scarcity globally. The number of sub-basins experiencing severe scarcity doubles in 2010 and triples in 2050 when considering both water quantity and quality, compared to quantity-only assessments. South America, Central North America, and Africa emerge as severe clean-water scarcity hotspots due to high nitrogen pollution. The global area and population affected by severe scarcity more than double between 2010 and 2050 in all scenarios. In 2010, 2517 sub-basins (32% of global land area and 80% of the population) experienced severe clean-water scarcity, with quality-induced scarcity dominating in many regions. Quality-based scarcity hotspots are largely concentrated in Southern North America, Europe, the Middle East, Southeast Asia, China, India, and parts of Northern Africa. In 2050, under the worst-case scenario (SSP5-RCP8.5), hotspots are projected to cover 48% of the drainage area and 91% of the global population. These hotspots are predominantly associated with intensive agricultural activities, with projected increases in agricultural area, nitrogen inputs, and surpluses. Even considering the increase in water availability in many sub-basins, quantity-induced scarcity remains significant due to increased water demand and changes in hydrological cycles. The main drivers of quantity-induced scarcity are excessive withdrawals, with irrigation being the largest contributor globally. The main causes of quality-induced scarcity differ across regions, with agricultural production becoming dominant in most hotspots in 2050.

The findings underscore the critical role of water pollution in aggravating water scarcity. The study demonstrates that traditional quantity-based assessments significantly underestimate the extent of future water scarcity. By incorporating water quality, particularly nitrogen pollution, the research provides a more comprehensive and realistic picture of the challenge. The identified hotspots and the associated socioeconomic and climatic factors provide valuable insights for targeted water management strategies. The different causes of water scarcity across regions highlight the need for tailored solutions, considering factors like irrigation practices, industrial water use, and nitrogen use efficiency in agriculture. The results strongly suggest the need for integrated water resource management strategies that simultaneously address both water quantity and quality issues. Mitigation strategies focusing on pollution reduction, specifically nitrogen control, are crucial for addressing the rising clean-water scarcity. This necessitates improved agricultural practices, efficient sewage treatment, and a potential shift towards more plant-based diets.

This study provides a crucial global assessment of future clean-water scarcity, highlighting the severe impact of water pollution on exacerbating water scarcity. The findings strongly advocate for incorporating water quality considerations into water management policies and strategies. Future research should focus on expanding the assessment to include other pollutants, improving the understanding of their combined effects, and exploring the synergies and trade-offs between water management and other Sustainable Development Goals (SDGs). The developed framework and results provide a valuable tool for informing policy decisions and promoting sustainable water resource management.

The study focuses on nitrogen pollution as a primary indicator of water quality, potentially underestimating the impacts of other pollutants. The annual temporal resolution might not fully capture the intra-annual variability in water scarcity. Model uncertainties related to the inputs and approaches of the MAGPIE, VIC, and MARINA-Nutrients models can influence the results. The threshold used for defining severe clean-water scarcity based on nitrogen concentration prioritizes aquatic ecosystems' health and could be viewed as stringent in the context of human uses.