Freshwater Availability Research Articles

Multi-Criteria Analysis for Geospatialization of Potential Areas for Water Reuse in Irrigated Agriculture in Hydrographic Regions

As the climate crisis progresses, droughts and the seasonal availability of fresh water are becoming increasingly common in different regions of the world. One solution to tackle this problem is the reuse of treated wastewater in agriculture. This study was carried out in two significant hydrographic regions located in the southeast of Brazil (Mogi Guaçu River Water Management Unit—UGRHI-09 and Piracicaba River Basin—PRB) that have notable differences in terms of land use and land cover. The aim of this study was to carry out a multi-criteria analysis of a set of environmental attributes in order to classify the areas under study according to their levels of soil suitability and runoff potential. The integrated analysis made it possible to geospatialize prospective regions for reuse, under two specified conditions. In the UGRHI-09, condition 1 corresponds to 3373.24 km2, while condition 2 comprises 286.07 km2, located mainly in the north-western and central-eastern portions of the unit. In the PRB, condition 1 was also more expressive in occupational terms, corresponding to 1447.83 km2; and condition 2 was perceptible in 53.11 km2, predominantly in the central region of the basin. The physical characteristics of the areas studied were decisive in delimiting the areas suitable for the reuse of treated wastewater.

Regional-scale seasonal forecast of surface water availability in a semi-arid environment: The case of Ceará State in Northeast of Brazil

Study region:Ceará (Brazil). Study focus:Considerable intra- and inter-annual variability of rainfall in this semi-arid region lead to strong temporal variations in water availability. To store and supply water in times of water scarcity, tens of thousands of freshwater reservoirs have been built over time, most of which are unmonitored. Here, we develop a hydrological forecasting system for the entire state of Ceará which integrates satellite-based monitoring of reservoir water storage, bias-corrected seasonal weather forecasts and hydrological modeling of freshwater availability. We test and demonstrate the applicability of this system by conducting experiments with historic data, hindcasts and forecasts. New hydrological insights for the region:The assimilation of in-situ and Sentinel-1 based observations of reservoir fillings into the hydrological model WASA-SED proved to be feasible and an important step in the modeling of available water resources dynamics. Hydrological simulations for January to June from 1990–2019 based on meteorological observations resulted in a median average NRMSE between observed and modeled reservoir fillings of strategic reservoirs of 29.51%. The comparison of observed and predicted precipitation from two different seasonal forecasting systems were in the same order of magnitude (i.e. 19.51% and 24.52%). Hindcast experiments suggested the superposition of uncertainties of different model components. Efforts are currently being made to further test and improve the developed integrated framework as part of the operational service.

Exploring the Interactions of Climate Change, Freshwater Supply, and Environmental Balance

Climate change has far-reaching implications for global freshwater availability and environmental balance. The increase in greenhouse gases from the burning of fossil fuels has triggered global climate change, affecting precipitation patterns, glacier melt and sea level rise. Parts of the United States are experiencing significant changes in precipitation patterns, with some areas experiencing frequent storms and others experiencing more prolonged droughts. Accelerated glacier melt is leading to fewer water sources during the dry season, and sea level rise is threatening coastal freshwater resources, triggering saltwater intrusion and a decline in freshwater quality. Wildfires in California are an important consequence of climate change, severely affecting freshwater resources and environmental balance. Wildfires lead to reduced water resources, impacting agricultural water use and irrigation infrastructure, and affecting water quality through increased sediment and pollutant loads. The 2018 Camp Hill Fire contaminated local water sources, and the rebuilding process has increased demand for water resources, exacerbating resource constraints. Global warming has lengthened wildfire seasons and increased fire intensity, leading to increased pressure on freshwater resources. By analyzing the impacts of climate change on freshwater resources, this paper hopes to draw public attention to environmental protection and provide a reference for gradually optimizing ecosystems and creating a healthy living environment.

Estimation of glacier-stored freshwater volume present in major tributaries of the Brahmaputra basin.

Estimation of the glacier-stored freshwater is important to understand the water security in the Himalayan region. While previous work has studied the western and central Himalayan glaciers, the eastern counterpart received less and more scattered attention. In this study, an attempt is made to quantify the total glacier-stored freshwater in the Brahmaputra basin and later compared with previous global models. Using open-source tools such as COSI-Corr and the Himalayan Glacier Thickness Mapper (HIGTHIM), the surface velocity and thickness of 1075 glaciers (> 1 km2) in the Brahmaputra basin were estimated, resulting in a current ice-volume estimate of 283 × 109 m3. Based on the laminar flow model, the mean ice volume ranges from 8284 to 230,186 m3, with an average of 36,570 m3. Sub-basin-wise evaluations of the total glacier-stored freshwater availability in the basin were also conducted, revealing that the Siang (89.998 × 109 m3, 31.45%) and Lohit (84.371 × 109 m3, 29.49%) sub-basins have significantly larger ice volumes than others. The average mean ice volume for each sub-basin are as follows: Teesta (45,233 m3), Sankosh (45,552 m3), Manas (39,581.7 m3), Subansiri (40,922.4 m3), Kameng (41,241.2 m3), Siang (36,120.5 m3), Dibang (31,792.2 m3), and Lohit (30,340.6 m3). Teesta, Sankosh, and Manas exhibit relatively higher average mean ice volumes than others. In comparison with the global studies, the present study's findings are acceptable with ensemble ice-volume estimates considering an uncertainty of ± 17.35%. Therefore, these results serve as a primary input for assessing the future changes in water resources and hazards related to water in the Brahmaputra basin.

Climatology of Orographic Precipitation Gradients Over High Mountain Asia Derived From Dynamical Downscaling

AbstractWithin High Mountain Asia (HMA), the annual melting of glaciers and snowpack provides vital freshwater to populations living downstream. Precipitation over HMA can directly affect the freshwater availability in this region by altering the mass balance of glaciers and snowpack. However, available reanalyses and downscaling simulations lack the resolution required to understand important glacier‐scale variations in precipitation. This study aimed to determine the current characteristics of orographic precipitation gradients (OPG) by curve‐fitting daily precipitation as a function of elevation from a 15‐year, 4‐km grid spaced Weather Research and Forecasting (WRF) model simulation focused on the Himalayan, Karakoram, and Hindu‐Kush mountain ranges. To facilitate precipitation curve‐fitting, the WRF model grid points were separated into regions of similar orientation, referred to as facets. Akaike Information Criterion‐corrected values and an F‐test p‐value identified the need for a curvature term to account for a varying OPG with elevation. Regions with similar seasonal variability were found using ‐means clustering of the monthly mean OPG coefficients. The central Himalayan slope's intra‐seasonal variability of OPG depended on synoptic scale conditions, in which cyclonically‐forced heavy‐precipitation events produced strong sublinear increases in precipitation with elevation. Initial testing of precipitation estimates using monthly coefficients showed promising results in downscaling daily WRF precipitation; the daily mean absolute error at each grid point had a lower magnitude than the daily mean precipitation total, on average. Results provide a physically‐based context for machine learning algorithms being developed to predict OPG and downscale precipitation output from global climate models over HMA.

Innovations in Wastewater Treatment

The rapid growth of the world population and climate change are two key factors that immensely affect freshwater availability [...]

Effect of Heat Stress on the Expression of Circulating Cyto(chemo)kine and Inflammatory Markers in Broiler Chickens Selected for High- or Low-water Efficiency.

Water scarcity is a current, significant global concern that will only increase under the pressure of climate change. Improving water efficiency of poultry is a new and promising area to help temper agriculture's future impact on fresh water availability. Here, we explored the effects of acute heat stress (HS) on circulating stress and inflammatory markers in 2 lines of broilers divergently selected for water efficiency. Male chicks from low (LWE) and high water efficient (HWE) lines were raised in 12 environmental chambers (2 pens/chamber, 6 chambers/line, 20 birds/pen) under normal conditions until day 28. On day 29, birds were subjected to thermoneutral (TN, 25 °C) or HS (36 °C) conditions, resulting in four treatments (2 lines × 2 environmental conditions). After 3 h of HS, whole blood was collected (8 birds per line × environment) and analyzed for target gene expression and plasma cytokine levels. Data were analyzed by 2-way ANOVA, with line, environment, and their interaction as main factors, and means were compared using Tukey's multiple range test. Gene expression of heat shock protein (HSP) 27, HSP70, interleukin (IL)-6, IL-18, c-reactive protein (CRP), tumor necrosis factor-α (TNFα), C-C motif chemokine ligand 4 (CCL4), CCL20, nucleotide-binding domain, leucine-rich repeat (NLR) family pyrin domain containing 3 (NLRP3), NLR family CARD domain containing 5 (NLRC5), and NLR family member X1 (NLRX1) were increased by HS, with no differences between the lines. HSP70, IL-10, and NLRC3 were lower in the HWE as compared to the LWE lines. Additionally, there were interactive effects between line and environment for HSP90, IL-4, and CCL4, where HS induced HSP90 expression in the LWE only, and IL-4 and CCL4 in HWE only. Arginine vasopressin (AVP) gene expression was significantly lower in the whole blood of the HWE line; however, plasma protein levels were not different. Overall, most of the effects seen on cyto (chemokines) and inflammatory markers were due to acute HS, with only a few genes differentially regulated between the lines. This likely indicates that the divergent selection for water efficiency for four generations did not elicit changes in inflammation and stress molecular signatures.

A Distinct Role for Aerosol and GHG Forcing in Historical CMIP6 Evapotranspiration Trends

AbstractEvapotranspiration (ET) is crucial for the global water balance, plant growth, and freshwater availability. It connects the surface water balance with surface energy fluxes, making its accurate representation vital for climate projections. However, global climate models (GCMs) struggle with ET representation due to resolution limitations and simplified depictions of soil, plant, and atmosphere interactions. Simulated future changes in ET are uncertain, and the role of driving processes remain unclear. Here, we explore the utility of a simple and interpretable method to disentangle these varying drivers. We investigate the sensitivity of JJA ET to different atmospheric variables through simple linear models predicting ET from atmospheric variables only. The model consistently yields good results across GCMs or forcing scenarios. We find that GCMs have shown strong decreases and subsequent increases in ET over the historical period, related to changes in net surface radiation. For future climate projections, decreases in water availability compete with higher available surface radiation, making future projections uncertain. Single forcing GCM realizations show that historical ET trends in densely populated regions have been more influenced by aerosol emissions than greenhouse gases. Finally, we investigate which atmospheric variables explain most short‐term (year‐to‐year) and long‐term (decadal) changes. While water availability may be the most important driver of short‐term variability, for certain regions, radiation trends dominate long‐term forcing. This paper leverages a simple approach to provide a comprehensive and understandable view into recent and future changes in ET, reconciling the evidence provided by more complex case studies.

Use of Machine Learning and Indexing Techniques for Identifying Industrial Pollutant Sources: A Case Study of the Lower Kelani River Basin, Sri Lanka

With the recent acceleration in urbanisation and industrialisation, industrial pollution has severely impacted inland water bodies and ecosystem services globally, causing significant restrains to freshwater availability and myriad damages to benthic species. The Kelani River Basin in Sri Lanka, covering only ~3.6% of the land but hosting over a quarter of its population and many industrial zones, is identified as the most polluted watershed in the country. This study used unsupervised learning (UL) and an indexing approach to identify potential industrial pollutant sources along the Kelani River. The UL results were compared with those obtained from a novel Industrial Pollution Index (IPI). Three latent variables related to industrial pollution were identified via Factor Analysis of monthly water quality data from 17 monitoring stations from 2016 to 2020. The developed IPI was validated using a Long Short-Term Memory Artificial Neural Network model (NSE = 0.98, RMSE = 0.81), identifying Cd, Zn, and Fe as the primary parameters influencing river pollution status. The UL method identified five stations with elevated concentrations for the developed latent variables, and the IPI confirmed four of them. Based on the findings from both methods, the industrial zones along the Kelani River have emerged as a likely source of pollution in the river’s water. The results suggest that the proposed method effectively identifies industrial pollution sources, offering a scalable methodology for other river basins to ensure sustainable water resource management.

Effects of drinking saline water on carcass traits and meat quality of growing and mature Blackhead Ogaden sheep and Somali goats.

Water salinity has a significant impact on water quality, posing challenges for livestock production and productivity, particularly in arid regions where climate change affects freshwater availability. This study aimed to determine the effect of drinking saline water on the carcass and meat quality traits of sheep and goats in Ethiopia. A total of 100 males with an average initial body weight of growing (18.17 ± 0.51) and mature (22.22 ± 0.52kg) Blackhead Ogaden sheep and growing (17.99 ± 0.50) and mature (21.99 ± 0.54) kg) Somali goats were used. The design of the experiment was a three-way factorial RCBD with three-factor combinations (5 treatment levels, 2 species, and 2 age groups).Water treatments were natural water (Lake Basaka water (control), low saline water (L-SW), moderate saline water (M-SW), high saline water (H-SW), and very high saline water (VH-SW); that is, NaCl was added to natural water at concentrations of 7.95, 11.93, 15.90, and 19.88g TDS/L, respectively. The finding showed that increasing salinity levels in drinking water reduced slaughter body weight (SBW), carcass weight (CW), dressing percentage (DP), rib eye area (RAE), total edible components (TEC), and increased total non-edible components (TNEC) (P < 0.05). Similarly, sheep and mature animals had higher (P < 0.001) SBW, CW, DP, RAE, and TEC than goats and growing animals. Sensory evaluation, shear force, and proximate analysis were affected by water salinity, species, and age groups (P < 0.05). Overall, the study revealed that consuming saline water above 11g TDS/L affected carcass traits and meat quality in Somali goats and Blackhead Ogaden sheep.

Controlled drainage with subirrigation systems: Reduce water supply by automatic control

Controlled drainage with subirrigation (CDSI) is a viable measure to supply, retain or discharge groundwater, thereby contributing to freshwater availability in agriculture under changing environmental conditions. Relatively simple CDSI systems can be controlled manually to set a few drainage levels. More advanced systems can be controlled remotely to set any drainage level (between a technical maximum and minimum). CDSI potentially improves hydrological conditions for crop growth, but the required external water supply can be large. Therefore, the objective of this paper is to investigate whether external water supply for subirrigation can be reduced by automatic control of CDSI systems in relation to crop water demand. Field measurements of a CDSI pilot in the Dutch sandy Pleistocene uplands were combined with weather forecasts to simulate the optimal drainage level and day by day water demand and supply using the agro-hydrological Soil, Water, Atmosphere, Plant model (SWAP). Firstly, model simulations showed that the water requirement reduced by 60 mm (dry growing season), 253 mm (average growing season) and 348 mm (wet growing season) using a dynamically managed crest level (CDSI-dyn) compared to using a fixed crest level (CDSI-fix), with minor effects on crop yield. Secondly, model simulations showed that a higher hydraulic resistance to downward seepage, a higher ditch water level or deeper roots reduced the water supply (up to 100 mm). Thirdly, accepting 10 % daily crop drought and oxygen stress for CDSI-dyn reduced the water supply requirement with 235–628 mm (dry vs wet growing season) compared to CDSI-fix. In conclusion, the required water volume for CDSI could be substantially reduced by automated control of the drainage level and water supply rate, while maintaining crop yield or accepting minor reductions, which increases the potential of implementation of CDSI systems.

Interface and mixing zone between soil waters arising from upward and downward seepage - Part II: Heterogeneous total density.

Freshwater lenses in otherwise saline environments contain an important source of fresh water for natural vegetation and agricultural crops. Such lenses are regularly found in areas where both upward seeping saline groundwater and downward infiltrating fresh recharge water occur simultaneously during part of the year, resulting in shallow freshwater lenses which are highly susceptible to changes in recharge or seepage. In a series of two papers, we consider the water – and solute transport in a 2D cross-section between two parallel outflow faces. In this second part of the series, we build upon expressions presented in the first part to consider a situation where the density of seepage water exceeds that of recharge water, as typical for many deltaic areas around the world. Analytical expressions and approximations are given to obtain the steady state position of the interface between the two types of water using a sharp interface approximation, with a focus on the position midway between two outflow faces. Results show that the effect of a heterogeneous density distribution is limited when the seepage flux exceeds the density difference induced flux, but increases rapidly for ratios of the seepage flux over the density flux falling below 1. The heterogeneous density distribution then results in a decrease in freshwater lens thickness and, correspondingly, a decrease in fresh water availability. We also consider time-variant, oscillatory boundary conditions, and show that for heterogeneous density distributions the interface approaches its equilibrium position faster than for a corresponding situation with a homogeneous density distribution, indicating a higher vulnerability for changing boundary conditions. We also demonstrate that heterogeneous density distributions have limited effect on the amplitude of the interface oscillations. Analytical results obtained with the simplified model are validated using the numerical code SUTRA, which solves the full model for a numerical grid.

Activated carbon based TiO2 nanocomposites (TiO2@AC) used simultaneous adsorption and photocatalytic oxidation for the efficient removal of Rhodamine-B (Rh–B)

The availability of fresh water is limited compared to its huge consumption. Conversely, certain industries like dyes, textiles, paper, and tanning not only consume vast quantities of fresh water, but also generate significant amounts of wastewater that poses severe threats to living organisms. The present investigation focuses on the degradation of Rhodamine-B (Rh–B) as a model pollutant by using the nanocomposite based on waste scrap tire-derived activated carbon (AC) and titanium dioxide (TiO2). These nanostructures were fabricated using wet chemistry techniques. Analysis using scanning electron microscopy (SEM) revealed that the morphology of the structures remained largely unchanged even with a concentration of 6 mg of AC. X-ray diffraction (XRD) results confirmed the successful fabrication of rutile and anatase phases of TiO2@AC nanocomposite. The XPS results confirmed the presence of AC and TiO2 in the composite. Furthermore, the optical band gap of the nanocomposites decreased up to 17.17 % and 34.57 % through direct and indirect methods respectively, owing to the varying quantity of AC used. The narrowing of optical band gap and the increased surface oxygen vacancies were caused by the successive addition of AC during the synthesis of nanocomposites. This resulted in the efficient degradation of Rhodamine-B (Rh–B) using adsorption and photocatalytic oxidation. The findings demonstrate a significant influence of AC on the TiO2 catalyst in the removal of Rh–B dye. The maximum efficiency of dye removal, reaching up to 99.14 %, was achieved with the highest concentration of AC, thus demonstrating almost complete elimination of Rh–B dye. The findings suggest that the use of waste scrap tires can be effectively applied to design efficient photocatalysts for addressing the wastewater management issues.

Towards a gapless 1 km fractional snow cover via a data fusion framework

Accurate quantification of snow cover facilitates the prediction of snowmelt runoff, the assessment of freshwater availability, and the analysis of Earth’s energy balance. Existing fractional snow cover (FSC) data, however, often suffer from limitations such as spatial and temporal gaps, compromised accuracy, and coarse spatial resolution. These limitations significantly hinder the ability to monitor snow cover dynamics effectively. To address these formidable challenges, this study introduces a novel data fusion framework specifically designed to generate high-resolution (1 km) daily FSC estimation across vast regions like North America, regardless of weather conditions. It achieved this by effectively integrating the complementary spatiotemporal characteristics of both coarse- and fine-resolution FSC data through a multi-stage processing pipeline. This pipeline incorporates innovative strategies for bias correction, gap filling, and consideration of dynamic characteristics of snow cover, ultimately leading to high accuracy and high spatiotemporal completeness in the fused FSC data. The accuracy of the fused FSC data was thoroughly evaluated over the study period (September 2015 to May 2016), demonstrating excellent consistency with independent datasets, including Landsat-derived FSC (total 24 scenes; RMSE=6.8–18.9 %) and ground-based snow observations (14,350 stations). Notably, the fused data outperforms the widely used Interactive Multi-sensor Snow and Ice Mapping System (IMS) daily snow cover extent data in overall accuracy (0.92 vs. 0.91), F1_score (0.86 vs. 0.83), and Kappa coefficient (0.80 vs. 0.77). Furthermore, the fused FSC data exhibits superior performance in accurately capturing the intricate daily snow cover dynamics compared to IMS data, as confirmed by superior agreement with ground-based observations in four snow-cover phenology metrics. In conclusion, the proposed data fusion framework offers a significant advancement in snow cover monitoring by generating high-accuracy, spatiotemporally complete daily FSC maps that effectively capture the spatial and temporal variability of snow cover. These FSC datasets hold substantial value for climate projections, hydrological studies, and water management at both global and regional scales.

National-level resilience: Innovative framework for Energy-Water-Food nexus evaluation

The escalating demand for energy, water, and food (EWF) resources, alongside external stressors such as climate change, is placing significant strain on national systems. Therefore, this study introduces a novel framework for assessing the resilience of interconnected EWF systems at a national level. The framework utilizes a hybrid approach of network systems modeling and optimization models, integrating sectoral and dependency impacts to offer a comprehensive perspective on the interconnected resilience of EWF components. Applied to Qatar's EWF nexus, the framework revealed significant interdependencies, particularly between water and energy components, that led to cascading failures and challenged nexus resilience. Under single failure scenarios, unmet demands for energy and water ranged from 9 to 59 GWh and 97,000 to 359,000 m3, respectively, with resilience indices from 0.86 to 0.99. In double failure scenarios, significantly higher unmet demands caused the resilience index to drop to 0.43. Due to limited freshwater availability, the food sector is highly vulnerable to groundwater supply disruptions, resulting in an 85.6 % reduction in total crop production under extreme scenarios. Furthermore, the study highlighted resilience-enhancement strategies, such as utilizing treated wastewater for agricultural, industrial, and commercial activities and diversifying energy sources to reduce the risk of cascading failures, which increased the nexus's resilience by 17 %. The proposed framework serves as an essential tool for identifying critical components within the EWF nexus and planning strategies to enhance both operational and structural resilience.

Multi-scale assessment of rainwater harvesting availability across the continental U.S.

Addressing resilience, sustainability, and water resource conservation has become increasingly important in the modern world. Challenges arise due to periodic droughts, climate change, and seasonal variability in areas with limited freshwater availability. Therefore, implementing and promoting water reuse is essential. Rainwater harvesting (RWH) is one such alternative, offering benefits in conserving water resources and mitigating droughts while reducing urban flooding and costs by generating alternative lower-cost water sources. Providing users with knowledge of available volumes for harvesting, including homeowners and governmental entities, is key to encouraging this practice. Hydrological data and geographic information systems are fundamental for managing, designing, and projecting rainwater harvesting practices. However, no tools currently integrate this information at multiple scales with current and future climate scenarios. This research aimed to develop a multi-scale assessment tool named H2O HARVEST, for evaluating the availability and potential of rainwater harvesting. Additional benefits of the H2O HARVEST app include aiding decision-making by national governmental entities and analyzing potential future scenarios for homeowner users. The app also provides regulatory policy information at the state level. We offer an app with the necessary capabilities to bridge the technology gap and promote rainwater harvesting practices. Our research demonstrated that RWH has the potential to be a sustainable water reuse practice. For more than 50% of the states, the RWH could supply at least 50% of the water demand. The regions of the US with the greatest potential are the Central and East.

Pleistocene archaeology and environments of the Free State, South Africa

ABSTRACT Pleistocene climate variability is often seen as a major cause of much of the evidence observed in the archaeological and palaeontological record of Africa. While continent-wide climate systems play an important role when testing pan-African human evolutionary processes, a more focused perspective centred on specific ecosystems at a regional level allows a detailed assessment of the different spatiotemporal scales of the proxies used to reconstruct past environments and the ways humans adapted to their change over time. Recent research in the arid interior of South Africa has provided insights into the availability of freshwater in the open landscape, which is a fundamental factor for human survival and the spatiotemporal distribution of which may have had a major influence on adaptive strategies. This article reviews the Pleistocene archaeological and environmental evidence of the Free State province of South Africa, which has produced major localities such as Cornelia-Uitzoek, Florisbad and Rose Cottage Cave, with the aim of providing a starting point for the discussion over freshwater availability with regard to southern Africa’s Grassland Biome. Particular emphasis is given to the description of multi-proxy approaches including the analysis of sediments, faunal remains, enamel stable isotopes, pollens and phytoliths and absolute dating based on trapped-charge methods. The picture that emerges highlights the paucity of Pleistocene datasets in the Free State and the necessity to expand research at open-air sites and improve the chronological resolution of human occupations and palaeoenvironmental proxies.

Can climate change signals be detected from the terrestrial water storage at daily timescale?

The global terrestrial water storage (TWS), the most accessible component in the hydrological cycle, is a general indicator of freshwater availability on Earth. The global TWS trend caused by climate change is harder to detect than global mean temperature due to the highly uneven hydrological responses across the globe, the brevity of global freshwater observations, and large noises of internal climate variability. To overcome the climate noise and small sample size of observations, we leverage the vast amount of observed and simulated meteorological fields at daily scales to project global TWS through its fingerprints in weather patterns. The novel method identifies the relationship between annual global mean TWS and daily surface air temperature and humidity fields using multi-model hydrological simulations. We found that globally, approximately 50% of days for most years since 2016 have climate change signals emerged above the noise of internal variability. Climate change signals in global mean TWS have been consistently increasing over the last few decades, and in the future, are expected to emerge from the natural climate variability. Our research indicates the urgency to limit carbon emission to not only avoid risks associated with warming but also sustain water security in the future.

The Future Sustainability of the São Francisco River Basin in Brazil: A Case Study

The viewpoint and reaction of a country towards climate change are shaped by its political, cultural, and scientific backgrounds, in addition to the distinct characteristics of its evolving climate and the anticipated and actual consequences of the phenomenon in the times ahead. A region’s climate has a significant impact on how water is managed and used, mostly in the primary sector, and both the distribution of ecosystem types and the amount and spreading of species on Earth. As a result, the environment and agricultural practices are affected by climate, so evaluating both distribution and evolution is extremely pertinent. Towards this aim, the climate distribution and evolution in the São Francisco River basin (SFRB) is assessed in three periods (1970–2000, 1981–2022) in the past and 2041–2060 in the future from an ensemble of GCMs under two SSPs (Shared Socioeconomic Pathways), SSP2-4.5 and SSP5-8.5. The Köppen-Geiger (KG) climate classification system is analyzed, and climate change impacts are inferred for this watershed located in central-eastern Brazil, covering an area equivalent to 8% of the country. Results predict the disappearance of the hot summer (Csa) and warm summer (Csb) Mediterranean climates, and a reduction/increase in the tropical savanna with dry winter (Aw)/dry summer (As). A striking increase in the semi-arid hot (BSh-steppe) climate is predicted with a higher percentage (10%) under SSP5-8.5. The source and the mouth of SFRB are projected to endure the major impacts of climate change that are followed by a predicted increase/decrease in temperature/precipitation. Future freshwater resource availability and quality for human use will all be impacted. Consequences on ecosystems, agricultural, and socioeconomic sectors within the SFRB might deepen the current contrasts between regions, urban and rural areas, and even between population groups, thus translating, to a greater extent, the inequality that still characterizes Brazilian society. Maps depicting land use and cover changes in SFRB from 1985 to 2022 highlight tendencies such as urbanization, agricultural expansion, deforestation, and changes in shrubland and water bodies. Urban areas fluctuated slightly, while cropland significantly increased from 33.57% to 45.45% and forest areas decreased from 3.88% to 3.50%. Socioeconomic data reveals disparities among municipalities: 74.46% with medium Human Development Index (HDI), 0.59% with very high HDI, and 9.11% with low HDI. Most municipalities have a Gross Domestic Product (GDP) per capita below US$6000. Population distribution maps show a predominance of small to medium-sized urban and rural communities, reflecting the basin’s dispersed demographic and economic profile. To achieve sustainable adaptation and mitigation of climate change impacts in SFRB, it is imperative that integrated measures be conducted with the cooperation of stakeholders, the local population, and decision-makers.

Cross-Sectional Analysis of Water Access and Health Conditions in Salinity and Cyclone Prone Areas: A Case Study of Nishanbaria Village in Southern Bangladesh

The present study was conducted in Nishanbaria, a remote coastal village of Barguna district, Bangladesh where access to fresh water is the biggest problem due to salinity and cyclones along with poverty. The study applied several research methods (household survey, Key Informant Interviews, Focus Group Discussion, and observation) to conduct a cross-sectional analysis in order to identify the severity of the water problems and their impacts on people's health in this village. The study reveals that drinking and using saline and dirty water for a long time have direct impacts on health; 87.9% of the families had sick members during the field survey in 2022. The major health problems are skin diseases (according to 30.65 % of the respondents), gastric problems (25.39%), and waterborne diseases (19.35%). According to 90.3% of residents, the salinity of water has a direct impact on pregnancy and children's health and well-being. As the majority of the people collect drinking water from tube wells (80.43%), the number of people using tube wells goes down to only 24.4% after cyclones. Women are the main water collectors in this village; drinking water is collected by female members in 86.86% of the families, domestic water in 98.19%, and water for cleaning purposes in 93.56% of the families. Women are at risk of health problems; different types of pains (according to 49.36% of the residents), accidents (34.33%), and gender-based violence stem from carrying water from distant sources. Poverty (97.84% of the residents live below the poverty line) creates disparity among the residents in accessing proper treatments for all these health problems as well as collecting fresh water from distant sources. A comprehensive and context-based hazard and disaster management plan is required to help this disaster-prone village in improving freshwater availability, and their health and well-being. The Dhaka University Journal of Earth and Environmental Sciences, Vol. 12(2), 2023, P 15-26