Water Cycle Research Articles

Rising temperatures and sinking hopes: An in-depth analysis of the interplay between climate change, land use patterns, and the desiccation of a global biosphere reserve

Global ecosystems and communities are significantly impacted by climate change and extreme events. The rapid desiccation of massive wetlands, which are essential for controlling water cycles, and biodiversity, preventing floods, and supplying essential ecosystem services, is one of the most upsetting effects. The once-largest lake in the Middle East, Lake Urmia, had a significant impact on ecology, economy, and human life contributing to climate regulation, species preservation, habitat conservation, tourism and recreation, and a wide range of other ecosystem services. The Ramsar Convention classified the lake as a Wetland of International Importance, and UNESCO designated it as a Biosphere Reserve. The ecological, agricultural, and societal challenges caused by rising temperatures, improper water resource management and overuse, enhanced salinity, and declining water levels have made Lake Urmia an acute symbol of environmental vulnerability. Using Landsat imagery, this study begins a thorough analysis of changes in the Lake Urmia basin from 1990 to 2020. The endeavor aims to develop effective conservation and restoration strategies by identifying the multiple reasons that led to its vulnerable situation. The study attempts to identify the role of precipitation, temperature trends, agricultural development, population growth, water consumption, evapotranspiration, and atmospheric salt and aerosol concentrations in the desiccation of the lake. This study presents a comprehensive knowledge of the complex interplay between climate change, human activity, and water management and may have implications for the holistic recovery of the lake. The findings have the potential to improve prognostic models and inform targeted mitigation strategies for not only Lake Urmia but also for other globally threatened wetlands.

Triple oxygen isotope variability of precipitation in a tropical mountainous region

We present one year of δD, δ18O, d-excess, and Δʹ17O data from monthly precipitation at a Caribbean coastal site in Panama and from tap waters across the country to constrain geographic, climate, and moisture source controls on isotopic variability and better understand the sources and mechanisms of precipitation in Central America, a region facing significant modifications to the annual rainfall cycle due to climate change. Monthly precipitation δD ranged from –52.2 to +14.3 ‰, δ18O from –7.6 to +0.4 ‰, d-excess from +7.1 to +11.6 ‰, and Δ′17O from +11 to +29 per meg. Rainy season precipitation samples were found to have lower δD, δ18O, and d-excess due to Rayleigh distillation during the condensation and rainout of Pacific moisture over the central cordilleras, which results in decoupling between d-excess and Δ′17O. Outlier Δ′17O values during peak dry and rainy months may reflect seasonal changes in water vapor sourcing, from Caribbean to Pacific and/or locally recycled moisture, or may be a result of organic contamination. Tap water δD ranged from –82.3 to –14.3 ‰, δ18O from –11.6 to –2.4 ‰, d-excess from +4.3 to +12.2 ‰ and Δ′17O from –2 to +84 per meg. Tap water δD and δ18O values increase eastward due to lower orographic effects and Pacific and locally recycled moisture contributions to rainfall and greater secondary evaporation. Tap water d-excess and Δ′17O values are also de-coupled but lack clear spatial trends and controls. The results of this study indicate the promise of adding Δ′17O to the isotopic toolkit in tropical mountainous regions with complicated water cycling dynamics and provide a baseline for future triple oxygen isotope investigations.

A synthesis of research on the sequestration of carbon in forests and the conservation of water

Forests help solve environmental issues by sequestering carbon and conserving water. Forest management's ultimate goal is to optimize dual functions to reduce greenhouse gas emissions and maintain the water cycle. Increased forest production and ecosystem water balance have costs and benefits. This study reviews forest carbon sequestration and hydrological principles for future research. The interaction between forest carbon sequestration and water conservation revealed information gaps and research needs. Previous research has helped comprehend forest carbon fixing and hydrological regulation. Many equipment and methods can quantify and monitor forest carbon and hydrological issues at multiple geographical and temporal levels. Afforestation programs that improve carbon sequestration and water maintenance ecosystem services lack knowledge. Top-down scheduling of afforestation in locations with uncertain water supplies must address how much and where to plant assumed existing land, ecological implications, and local progress and income. Planting decisions dominate local management. Cooperative research is needed to build and manage planted forests for carbon sequestration, water management, and other societal purposes. This study's integrated paradigm for forest management considers carbon sequestration and water conservation can assist future research.

Spatial and Temporal Patterns of Vegetation Water Use Efficiency and Its Response to Climatic and Environmental Factors in Gansu Province

Vegetation water use efficiency (WUE) is a crucial indicator for elucidating the interconnections between the carbon and water cycles of ecosystems and for discerning the response of vegetation ecosystems to climate change. Gansu Province in northwestern China is facing significant ecological water-related challenges. However, the response of vegetation WUE to climate environmental factors in this region remains unclear. In this study, the MODIS vegetation gross primary productivity (GPP) and evapotranspiration (ET) datasets were used to calculate the vegetation WUE in Gansu Province and, combined with meteorological data, Theil–Sen median trend analysis and partial correlation analysis were used to determine the spatial and temporal characteristics of vegetation WUE in this region and its response to climate environmental factors. Finally, the random forest model was used to rank the importance of climate environmental factors. The results indicate the following: (1) The average values of vegetation WUE, GPP, and ET in Gansu Province from 2000 to 2020 were 1.46 gC·mm−1·m−2, 510.22 gC·m−2, and 343.68 mm, respectively, and their spatial distribution was high in the southeast and low in the northwest, which was closely related to the distribution of vegetation in the region. (2) Over the past 20 years, the vegetation WUE in this region showed a slowly decreasing trend in general, with a decrease rate of 16.57%. There were significant differences in the WUE of different vegetation types, among which forest WUE was the highest and grassland WUE the lowest. (3) The trend prediction of WUE in Gansu Province was performed by using the rescaled extreme difference method, and the Hurst index was 0.45, which means that the vegetation WUE in this region is expected to increase in the future. (4) In general, precipitation was the main factor influencing the change in vegetation WUE in Gansu Province, followed by vapor pressure deficit (VPD), temperature, and soil moisture. This study provides strategy support for the coupling process of vegetation ecosystems and the sustainable development of agriculture and animal husbandry in Gansu Province and has scientific reference value for promoting and planning the sustainable development of vegetation in arid and semi-arid areas.

How have atmospheric components of the local water cycle changed around the abrupt climatic shift over France?

The significant increase in surface air temperature experienced by Western Europe over the last few decades has resulted in an abrupt warming in France, around 1987/1988 years. This climatic shift impacted hydrological cycle, particularly by reducing runoff in spring and summer. Evapotranspiration and precipitation have been identified as the main drivers of climatic water balance. But the impact of the 1987/1988 climatic shift on local water cycle over France has not been quantified yet. This study tries to assess the consequences of this rapid warming on the main climatic components of local water cycle. Climate variables linked to the water cycle extracted from a reanalysed observed climate database are analysed using robust Bayesian change points detection and mean comparison techniques. After the abrupt rise in surface air temperature and surface solar radiation, water demand increases significantly on almost the entire French territory in spring, summer and autumn. Our results show that, from March to May, the vegetation cover is able to respond to this increase by drawing from the soil water reservoirs. But in summer, most of the territory is facing a significant rise in water constraint (i.e. difference between potential and actual evapotranspiration), extending on the last decade over autumn. In spring and summer, the increase in potential evapotranspiration is the main driver of the intensification of water constraint. In the beginning of autumn, longer dry spell also plays a major role in the lengthening of periods of water constraint. This innovative study highlights the specific impact of a climatic shift on the main components of the atmospheric water balance at regional and local scale. As the observed changes in climate hazard linked to water cycle affect growth cycle of the majority of the vegetation covers and crops, this could lead to a worsening of hydric stress events. As such climatic shifts are expected to happen again in the future, their impacts on the local water cycle represent a major issue for natural terrestrial ecosystems as well as for agriculture.

Effects of plantations on rainfall redistribution in a rocky mountain area of North China

AbstractRainfall redistribution plays a crucial role in the water cycle. However, the main factors affecting the redistribution of rainfall remain uncertain. We chose three different plantations—cork oak (Quercus variabilis Bl.), oriental arborvitae (Platycladus orientalis L.) and black locust (Robinia pseudoacacia L.)—to investigate the role of plantations in rainfall redistribution and to determine the main factors influencing rainfall redistribution. The results indicated that cork oak exhibited the highest stemflow (0.34%) and the lowest canopy interception (12.58%), whereas black locust had the lowest stemflow (0.21%), and oriental arborvitae displayed the greatest canopy interception (32.8%). Under different density conditions for cork oaks, the stemflow was highest (0.39%) in low‐density forests with 750 trees ha−2 and lowest (0.34%) in medium‐density forests with 1100 trees ha−2. Meanwhile, the highest canopy interception (17.68%) was observed in high‐density forests (1300 trees ha−2), while the lowest interception rate (9.22%) was found in low‐density forests. The main factors affecting rainfall redistribution and their contribution rates were as follows: bark roughness index (35%), wind speed (18.6%), tree species (14.2%), diameter at breast height (11.2%), stand density (9.6%) and rainfall amount (5.4%). Our findings suggested that structural characteristics of trees are the primary factors affecting rainfall redistribution. Planting cork oak in the rocky mountain regions of North China is recommended because of its substantial stemflow production, particularly under low‐density growth conditions. Therefore, this study has significant guiding implications for the selection of afforestation tree species in similar rocky mountain areas globally.

One Health, One Forest: Harnessing Reclaimed Wood as a Sustainable Solution

Deforestation is a multifaceted and wicked problem characterized by its complexity and resistance to straightforward solutions. The issue is driven by human activities and has severe ecological, socio-economic, and climatic consequences. Between 1990 and 2015, approximately 129 million hectares of forest were lost globally, a trend contributing to biodiversity loss, increased carbon dioxide emissions, and climate change. In Canada, deforestation due to logging significantly impacts the boreal forests, with consequences such as habitat fragmentation affecting species like the threatened boreal caribou. The Canadian logging industry aims to provide essential raw materials while fostering economic growth and employment, supplying critical resources for sawmills, planing mills, shingle mills, and pulp and paper industries. Despite economic benefits, logging, particularly clearcutting, disrupts natural forest regeneration, soil composition, and water cycles, leading to long-term ecological consequences. The One Health approach, integrating human, non-human animal, and environmental health, is proposed to address this issue sustainably. Actions like those by Forests Ontario and Evergreen focus on reforestation and urban greening, while companies like Consolidated Pallet Co. promote wood recycling. This action plan showcases the potential for community-driven solutions to reduce environmental footprints, enhance sustainability, and foster economic and social well-being.

Enhancing long-term vegetation monitoring in Australia: a new approach for harmonising the Advanced Very High Resolution Radiometer normalised-difference vegetation (NVDI) with MODIS NDVI

Abstract. Long-term, reliable datasets of satellite-based vegetation condition are essential for understanding terrestrial ecosystem responses to global environmental change, particularly in Australia, which is characterised by diverse ecosystems and strong interannual climate variability. We comprehensively evaluate several existing global Advanced Very High Resolution Radiometer (AVHRR) normalised-difference vegetation index (NDVI) products for their suitability for long-term vegetation monitoring in Australia. Comparisons with the MODIS NDVI highlight significant deficiencies, particularly over densely vegetated regions. Moreover, all the assessed products failed to adequately reproduce the interannual variability in the pre-MODIS era as indicated by Landsat NDVI anomalies. To address these limitations, we propose a new approach to calibrating and harmonising NOAA's Climate Data Record of AVHRR NDVI to the MODIS MCD43A4 NDVI for Australia using a gradient-boosting decision tree ensemble method. Two versions of the datasets are developed, one incorporating climate data in the predictors (“AusENDVI-clim”: Australian Empirical NDVI-climate) and another that is independent of climate data (“AusENDVI-noclim”). These datasets, spanning 1982–2013 at a spatial resolution of 0.05° and with a monthly time step, exhibit strong correlations (r2=0.89–0.94) and low mean errors compared with MODIS MCD43A4 NDVI (mean absolute error (MAE) = 0.014–0.028, RMSE = 0.021–0.046), accurately reproducing seasonal cycles over densely vegetated regions. Furthermore, they closely replicate the interannual variability in vegetation condition in the pre-MODIS era. A reliable method for gap-filling the AusENDVI record is also developed that leverages climate, atmospheric CO2 concentration, and woody-cover fraction predictors. The resulting synthetic NDVI dataset shows excellent agreement with the MODIS MCD43A4 NDVI and the recalibrated AVHRR NDVI time series (r2=0.82–0.95, MAE = 0.016–0.029, RMSE = 0.039–0.041). Finally, we provide a complete 41-year dataset where the gap-filled AusENDVI-clim from January 1982 to February 2000 is joined with the MODIS MCD43A4 NDVI from March 2000 to December 2022. Analysing 40-year per-pixel trends in Australia's annual maximum NDVI revealed increasing values, and shifts in the timing, of the annual peak NDVI across most of the continent, underscoring the dataset's potential to address crucial questions regarding the changing vegetation phenology and its drivers. The AusENDVI dataset can be used for studying Australia's changing vegetation dynamics and downstream impacts on the terrestrial carbon and water cycles, and it provides a reliable foundation for further research into the drivers of vegetation change. AusENDVI is open access and available at https://doi.org/10.5281/zenodo.10802703 (Burton et al., 2024).

Large sensory analysis of vegetables from conventional, organic and no-till practices

There is a growing interest in agriculture to address soil deterioration issues and achieve a sus-tainable agrosystem. Many producers introduce no-till techniques and show significant yields with better ecosystem functioning, as well as improved carbon and water cycles. However, sensory analysis to compare vegetables from these practices are scarce. In this paper, we conduct triangle and hedonic tests over 15 panels of consumers for a total of 915 consumers. Based on statistical hypothesis testing and maximum likelihood estimation, significant statistical differences (p < 0.05 and less) are produced for both triangle tests and hedonic ranking in some specific cases. These results show a trend for sensory preferences of no-till practices.

Challenges and Future Directions in Quantifying Terrestrial Evapotranspiration

AbstractTerrestrial evapotranspiration is the second‐largest component of the land water cycle, linking the water, energy, and carbon cycles and influencing the productivity and health of ecosystems. The dynamics of ET across a spectrum of spatiotemporal scales and their controls remain an active focus of research across different science disciplines. Here, we provide an overview of the current state of ET science across in situ measurements, partitioning of ET, and remote sensing, and discuss how different approaches complement one another based on their advantages and shortcomings. We aim to facilitate collaboration among a cross‐disciplinary group of ET scientists to overcome the challenges identified in this paper and ultimately advance our integrated understanding of ET.

Large Scale Oscillations in the Martian Tropical Cloud Belt

AbstractThe Tropical Cloud Oscillation (TCO) in the Martian atmosphere is a shift of clouds in the northern spring and summer tropical cloud belt between the eastern and western hemispheres on an intra‐seasonal timescale of about 10–40 sols. The TCO is a significant intraseasonal variation and may strongly affect the Martian general circulation, water cycle, and dust cycle. We examine TCOs using multiple data sets with a focus on the clouds observed in Mars Daily Global Maps during Mars Year (MY) 29–35. One or more TCO cycles are observed in each MY and the phenomenon is most prominent during Ls = 135°–185°. Space‐time spectral analysis shows a variety of waves which appear to follow the theoretical dispersion relationships of equatorial waves, such as Kelvin waves, Rossby waves, and Mixed Rossby Gravity waves. The TCO appears to be controlled by zonal wavenumber one traveling waves with Kelvin and Rossby wave characteristics and exhibits a fine‐scale latitudinal structure that requires modeling with sufficient resolution. Issues with current data assimilation products for use in studies of Martian equatorial waves due to this fine‐scale structure are discussed.

Seasonal dynamics in microbial trace metals transporters during phytoplankton blooms in the Southern Ocean.

Trace metals are required as cofactors in metalloproteins that are essential in microbial metabolism and growth. The microbial requirements of diverse metals and the capabilities of prokaryotic taxa to acquire these metals remain poorly understood. We present here results from metagenomic observations over an entire productive season in the region off Kerguelen Island (Indian Sector of the Southern Ocean). We observed seasonal patterns in the abundance of prokaryotic transporters of seven trace elements (zinc [Zn], manganese [Mn], nickel [Ni], molybdenum [Mo], tungsten [W], copper [Cu] and cobalt [Co]) and the consecutive spring and summer phytoplankton blooms were strong drivers of these temporal trends. Taxonomic affiliation of the functional genes revealed that Rhodobacteraceae had a broad repertoire of trace metal transporters (Mn, Zn, Ni, W and Mo) and a more restricted set was observed for other prokaryotic groups, such as Flavobacteriaceae (Zn), Nitrincolaceae (Ni and W) and Thioglobaceae (Mo). The prevalence of trace metal transporters within a prokaryotic group, as determined on the family level, was overall confirmed in representative metagenome-assembled genomes. We discuss the potential involvement of prokaryotic groups in processes related to organic matter utilisation that require these metals and the consequences on carbon and trace metal cycling in surface waters of the Southern Ocean.

Evaluating Land Surface Temperature Variation and Its Responses to Climate Change and Human Activities on the Southeastern Tibetan Plateau

ABSTRACTThe Yarlung Zangbo River Basin (YZRB), situated within the Qinghai‐Tibetan Plateau, has experienced significant alterations due to global warming and vegetation greening. This region serves as a critical indicator of the interplay between vegetation growth and climatic fluctuations, as evidenced by substantial changes in spatiotemporal land surface temperature (LST) over recent decades. In this research, we assessed the components of the water and energy cycles from 1980 to 2015 utilising the variable infiltration capacity (VIC) model to generate a continuous daily LST data over a 35‐year period. Subsequently, we analysed the variations in LST and identified the influence of environmental factors on temperature changes. Notably, while greening was observed, LST exhibited an upward trend. By differentiating the effects of climatic and anthropogenic factors on LST, we found that climate was the predominant influence, accounting for a contribution rate of 70.36% from 1980 to 1995. In contrast, human activities became the primary driver of LST changes, contributing 55% after 1995. Grasslands with moderate coverage demonstrated potential cooling effects. Among the various environmental factors examined, albedo exhibited a negative and delayed impact on LST, while temperature, precipitation and evapotranspiration were positively correlated with LST, displaying relatively synchronous variations. Additionally, soil moisture and the normalised difference vegetation index (NDVI) were identified as leading contributors to positive changes in LST. This study enhances the understanding of the mechanisms influencing LST and provides essential insights for socio‐economic development in areas with sensitive ecosystem.

A critical assessment of geological weighing lysimeters: Part 2—Modelling field scale soil moisture storage and hydrological fluxes

AbstractLand surface models (LSMs) are used to simulate the terrestrial component of water, energy, and biogeochemical cycles. These simulations are useful for water resources management, drought and flood prediction, and numerical climate/weather prediction. However, the usefulness of LSMs are dependent by their ability to reproduce states and fluxes realistically. Accurate measurements of water storage are useful to calibrate and validate LSMs outputs. Geological weighing lysimeters (GWLs) are instruments that can provide field‐scale estimates of integrated total water storage within a soil profile. We use field estimates of total water storage and subsurface storage to critically evaluate two different land surface models: the Modélisation Environnementale communautaire—Surface Hydrology (MESH) which uses the Canadian Land Surface Scheme (CLASS), and the Structure for Unifying Multiple Modeling Alternatives: (SUMMA). These models have differences in how the processes and properties of the land surface are represented. We attempted to parameterize each model in an equivalent manner, to minimize model differences. Both models were able to reproduce observations of total water storage and subsurface storage reasonably well. However, there were inconsistencies in the simulated timing of snowmelt; depth of soil freezing; total evapotranspiration; partitioning of evaporation between soil evaporation and evaporation of intercepted water; and soil drainage. No one model emerged as better overall, though each model had specific strengths and weaknesses that we describe. Insights from this study can be used to improve model physics and performance.

Detection of lunar water, hydroxyl ion and their diurnal changes from CHACE-2 orbiter observation

This work reports the spatial and diurnal variations of the number densities of lunar molecular water (H2O), atomic mass unit (amu) 18 and hydroxyl (OH), amu 17 over low (0° to 30°), middle (31° to 60°) and high (61° to 80°) latitudinal regions of the lunar exosphere during the pre-sunrise, noon, sunset and midnight periods using the mass spectrometric data of CHandra's Atmospheric Composition Explorer-2 (CHACE-2) on board Chandrayaan-2, the second lunar mission developed in India. Both H2O and OH exhibit, particularly in the low latitude regions, a trend of increasing number density after the sunrise and up to noon, followed by a decrease till sunset. An overall higher density of H2O is obtained compared to the previous reports. The findings are justified in terms of the polar orbital height of the instrument and the duration of data procurement. The maximum number density for the low, middle and high latitudes reaches 5225 cm−3, 5135 cm−3 and 3747 cm−3, respectively. The corresponding OH abundances are found to be 5079 cm−3, 5565 cm−3 and 5720 cm−3. The diurnal variations of H2O and OH and their comparisons, similar to those of the present report may provide suitable means for tracing the lunar water cycle. The CHACE-2 observations imply that the influence of magnetotail passage on volatiles like water is to be further quantified in future missions with other sensors.

Subsurface influences on watershed nutrient concentrations and loading in a clay dominated agricultural system

Water quality issues in the Great Lakes Basin persist despite management and monitoring efforts. With changing land use and climatic conditions, the need for improved understanding of nutrient loss from agricultural field to surface water is imperative to reduce consequences on human and aquatic life, such as perpetual algal blooms and contaminated drinking water. There remains a gap in holistic rural water management studies that investigate the understanding of the water cycle in rural settings and the interconnections between different components of the water cycle, including artificial drainage. In the current study, a year-round paired investigation of subsurface and nutrient dynamics was conducted in a small, intensively managed agricultural watershed within southwestern Ontario, Canada. Nutrients (Nitrate and Phosphorus) and stable isotopes of water (δ2H and δ18O) were sampled at varying scales (i.e., field and watershed), from multiple hydrologic components (e.g., groundwater, surface water, tile flow, and soil water), from 2020 to 2022. Results indicate that nutrient concentrations in surface water were elevated during the growing season, while nutrient loading was greater during the non-growing season in surface water. Monthly nitrate loads were found to be significantly (p < 0.01) related to groundwater elevation, soil moisture and tile flow, whereas total phosphorus loading was found to be significantly (p < 0.01) related to soil moisture and tile flow. δ2H and δ18O signatures revealed that during the growing season nutrient movement was predominantly through interflow pathways (including tile drainage) comprised of event-water. In the non-growing season, there was an increased subsurface influence on nutrient transport. This study highlights the importance of including subsurface characterization in nutrient management studies. A comprehensive understanding of varying seasonal hydrologic mechanisms that control nutrient movement within an agricultural watershed is essential to sustain growing rural communities.

Groundwaterscapes: A Global Classification and Mapping of Groundwater's Large‐Scale Socioeconomic, Ecological, and Earth System Functions

AbstractGroundwater is a dynamic component of the global water cycle with important social, economic, ecological, and Earth system functions. We present a new global classification and mapping of groundwater systems, which we call groundwaterscapes, that represent predominant configurations of large‐scale groundwater system functions. We identify and map 15 groundwaterscapes which offer a new lens to conceptualize, study, model, and manage groundwater. Groundwaterscapes are derived using a novel application of sequenced self‐organizing maps that capture patterns in groundwater system functions at the grid cell level (∼10 km), including groundwater‐dependent ecosystem type and density, storage capacity, irrigation, safe drinking water access, and national governance. All large aquifer systems of the world are characterized by multiple groundwaterscapes, highlighting the pitfalls of treating these groundwater bodies as lumped systems in global assessments. We evaluate the distribution of Global Groundwater Monitoring Network wells across groundwaterscapes and find that industrial agricultural regions are disproportionately monitored, while several groundwaterscapes have next to no monitoring wells. This disparity undermines the ability to understand system dynamics across the full range of settings that characterize groundwater systems globally. We argue that groundwaterscapes offer a conceptual and spatial tool to guide model development, hypothesis testing, and future data collection initiatives to better understand groundwater's embeddedness within social‐ecological systems at the global scale.

Wastewater treatment plants circular performance models evaluation: Portugal case-study

Population growth, economic growth, and changes in societal habits have led to significant changes in resource consumption. Therefore, it's crucial to accelerate the “reduce, reuse, recycle, and recover” of resources to ensure the balance of ecosystems, and water is surely one of the most fundamental resources. The acceleration of this approach in the water cycle makes sense only if we combine a circular economy (CE) transition with a sustainable perspective. In this context, more rational usage of water resources (which are under pressure) and more sustainable wastewater practices are expected to be a way towards the CE in the water and wastewater sector. This study provides a description and evaluation of existing frameworks that can be used to measure and assess the level of circularity of the wastewater treatment plant (WWTP). The treatment of urban wastewater requires new concepts of management and operation for the adaptation of existing plants, which lack robustness and flexibility, to face these new challenges and requirements because we can no longer continue to look at the WWTP only as treatment units, but as wastewater resource recovery facilities. This transformation must be transposed according to a matrix that allows the assessment to describe the current situation, analyse the problem, identify vulnerabilities and opportunities, identify, and evaluate measures, and identify and evaluate strategies. Considering that decision-makers face profound uncertainties such as climate change, population growth, population needs, innovative technologies, economic developments, ecosystem preservation and the impacts of human and natural activities.

Stability and physical properties of brucite at high pressures and temperatures: Implication for Earth’s deep water cycle

Brucite is a common hydrous mineral on Earth and may contribute to the deep water cycle of the Earth, but its stability and structure under mantle conditions remain uncertain. In this study, we investigated the stability of brucite up to 60 GPa at 800 K and 45 GPa at 1850 K. Within the experiment P-T conditions, no theoretically predicted new phase was observed, and brucite remained in the P3¯m1 structure. With the determined thermal EoS of brucite and the elastic parameters of mantle minerals, we modeled the velocity and density profile of subducted hydrous harzburgite in the top lower mantle, assuming that the water was stored in brucite and phase D. Based on the modelling, 1 wt% water will reduce the velocity and density of harzburgite by ∼ 5 % and ∼ 2 %, respectively, yet whether the water is stored in brucite or phase D has weak influence on both density and velocity. With a water content up to 2.4 wt%, the density of hydrous harzburgite could be reduced to 2.2(2)%–2.8(2)% lower than the surrounding mantle, while the VP and VS of hydrous harzburgite are still 0.3(1)%–0.7(1)% and 0.7(2)%–1.8(2)% higher than that of the normal mantle. Thus, the low-density hydrous harzburgite may slow down the subducting of slab, despite being a high-velocity body in seismic observations.

Machine‐Learning Based Multi‐Layer Soil Moisture Forecasts—An Application Case Study of the Montana 2017 Flash Drought

AbstractSoil moisture (SM) is an essential climate variable, governing land‐atmosphere interactions, runoff generation, and vegetation growth and productivity. Timely forecasts of SM spatial distribution and vertical profiles are needed for early detection and prediction of potential droughts. However, previous studies have primarily concentrated on historical or near real‐time soil moisture mapping, with less effort devoted to the development and integration of soil moisture forecast components within drought assessment systems. A satellite‐driven machine‐learning approach was developed in this study to build complex relationships between diversified predictor data sets and in situ multi‐layer SM measurements from the Montana Mesonet, a regionally dense environmental station network in the US upper Missouri and Columbia basins. The resulting 30‐m daily SM predictions showed strong performance against in situ SM measurements from 4‐, 8‐ and 20‐inch soil layers, and with 1‐ to 2‐week forecast lead times (R &gt; 0.91; RMSE ≤ 0.047 cm3/cm3). The machine‐learning model was subsequently applied to the entire Montana region, and the SM deficit forecasts with both 1‐ and 2‐week lead times successfully depicted onset, progression, and termination phases of the 2017 Montana flash drought, which was not effectively identified from prevailing operational systems. The resulting system is capable of delineating local scale SM heterogeneity, and could be extended to predict other critical water cycle variables, potentially enhancing future drought forecasts through multivariate assessments and benefiting water resource management, agricultural practices, and the provision of ecosystem services.