Evaporation Data Research Articles

The influence of impurities on the evaporation behavior of Po from liquid Pb–Bi eutectic at high temperatures

AbstractThis study presents an in-depth analysis of the polonium evaporation from high-energy and high-intensity proton-irradiated liquid lead-bismuth eutectic. The applied experimental conditions closely mimic those encountered within an accelerator-driven nuclear reactor, particularly focusing on the interaction of other impurities with polonium. Utilizing proton-irradiated lead-bismuth eutectic with an impurity spectrum similar to that of a real reactor, this research establishes reliable data for the polonium evaporation in the presence of said impurities, employing the transpiration method. The results agree well with those of prior model experiments using pure lead-bismuth eutectic. This indicates that the other coexisting impurities have a negligible impact on the polonium evaporation. The good agreement of the experimental values with literature data emphasizes the reliability of the applied methods and the robustness of the current understanding. These findings have significant implications for the operation and safety assessment of heavy metal-cooled nuclear reactors and support the advancement of Generation IV accelerator-driven systems.

Does vegetation greening have a positive effect on global vegetation carbon and water use efficiency?

Terrestrial ecosystems have undergone significant changes as a result of climate change, profoundly affecting global carbon and water cycling processes. Notably, the synergistic changes in vegetation carbon use efficiency (CUE) and water use efficiency (WUE) and their response to patterns of climate change over the last 40 years are unknown. Therefore, in this study, global vegetation WUE and CUE were inverted using Gross primary productivity (GPP), Net primary productivity (NPP) and total evaporation (ET) data from 1981 to 2019 to reveal their temporal and spatial patterns of change through trend analysis and stability analysis. A stepwise regression algorithm was used to reveal the potential driving law of environmental factors on vegetation WUE and CUE. The results shows that (1) From 1981 to 2019, the global vegetation WUE and CUE showed in a relatively stable state, and the trends of WUE and CUE were -0.00004/year and 0.006 g C m−2 mm−1/year, respectively; (2) the greening of vegetation was the most important cause of the changes in WUE and CUE, and the driving force of rain and heat conditions on the CUE of vegetation was smaller than that of solar radiation and soil water, the regions where CO2 is the dominant factor affecting CUE and WUE are mainly in the north temperate zone; (3) the region of synergistic growth of WUE and CUE accounts for about 31.38 % of the global terrestrial area, and this pattern of change suggests that the global vegetation carbon sink potential is huge, and the popularization of vegetation planting patterns under the synergistic growth of CUE and WUE should be strengthened. The research has shown that vegetation greening is a key factor influencing changes in the WUE and CUE of vegetation, therefore, the implementation of ecological engineering will be an important step in combating climate change.

Characterizing and improving the performance of molten-salt-steam heat exchangers in concentrating solar power plants

Shell-and-tube heat exchangers (HXs) for steam generation from molten salts in concentrating solar power (CSP) plants experience thermal fatigue due to significant temperature gradients and inherent transient operation. Molten salt-steam HX design lifespans exceed actual lifespans, and, as a consequence, designers overpredict plant profitability and operators neglect appropriate prescriptions to optimize these lifetimes. This study refines HX lifespan estimates with data benchmarked against thermal-fluid mechanical modeling of stress and accumulated fatigue. Reduced-order thermal models of the molten salt-steam, shell-and-tube evaporator and superheater predict transient temperature profiles along the two HXs salt-steam flow paths. The modeled evaporator and superheater temperature profiles enable assessment of cyclic stresses within the HX tubesheets, where molten-salt HX failures are most common. Evaporator and superheater performance data from a current 110 MWelec commercial CSP plant provide a basis for validating the reduced-order HX models. HX life predictions derived from stochastic failure distributions serve as inputs for simulating and optimizing existing plant operations. The impact of the updated lifespans on overall plant revenue depends on operating scenarios. This study suggests that typical ramping rates for a CSP plant with a high-temperature Rankine cycle result in an evaporator and superheater life of approximately 10 and 25 years, respectively, compared to the design target of 30 years. Reduced HX lifespans decrease operational plant revenue on average by 4.6-5.1%. Furthermore, there may be as many as four HX replacements over the 30-year lifetime of the plant; and, purchase agreement loss due to failure to meet contractual production requirements can have ramifications that include the risk of bankruptcy.

Regional Climate Change and Drought Dynamics in Tunceli, Turkey: Insights from Drought Indices

Global warming and climate change are causing temperatures to rise, which is having a negative impact on water resources. Climate change is a worldwide problem that affects and will continue to affect the frequency and intensity of natural disasters in many regions of the world. Tunceli region in Turkey, which until 10 years ago was known as an environmentally friendly city with abundant water resources and frequent rainfall, is experiencing a decrease in precipitation during the snowy winter season. This situation has made the investigation of climate change impacts an important issue in the region. Therefore, effective climate change adaptation strategies need to be developed. To determine these strategies, in this study, we assessed long-term drought conditions using multiple drought indices such as Standardized Precipitation Index (SPI), Reconnaissance Drought Index (RDI), Normal Precipitation Index (PNI), and Aridity Index (AI). The SPI and RDI analyses were performed in annual reference periods on a time scale of 3, 6, 9, and 12 months using temperature, precipitation, and evaporation data. Consequently, the SPI and RDI results were compared, and both indices show similar behavior in dry, wet, and normal seasons. Nevertheless, RDI shows less variation between different time scales, which is an advantage over SPI and is probably due to the inclusion of potential evapotranspiration in RDI. The variations in PNI between humid and dry sub-humid categorizations throughout the years, combined with the AI results, indicate that the Tunceli region predominantly experiences a climate ranging from dry sub-humid to semi-arid. This study could help decision-makers take effective measures to become more resilient to climate change in temperate climate regions and take important steps toward sustainable water resources management.

Estimation of Actual Evapotranspiration and Water Stress in Typical Irrigation Areas in Xinjiang, Northwest China

The increasing water demand and the disparities in the spatiotemporal distribution of water resources will lead to increasingly severe water shortages in arid areas. Accurate evapotranspiration estimation is the basis for evaluating water stress and informing sustainable water resource management. In this study, we constructed a surface energy balance algorithm for land (SEBAL) model based on the Google Earth Engine platform to invert the actual evapotranspiration (ETa) in typical irrigation areas in Xinjiang, northwest China, during the growing season from 2005 to 2021. The inversion results were evaluated using the observed evaporation data and crop evapotranspiration estimated by the FAO Penman–Monteith method. The water stress index (WSI) was then calculated based on the simulated ETa. The impacts of climatic factors, hydrological conditions, land-use change, and irrigation patterns on ETa and WSI were analyzed. The results indicated the following: (1) The ETa simulated by the SEBAL model matched well with the observed data and the evapotranspiration estimated using the FAO Penman–Monteith approach, with correlation coefficients greater than 0.7. (2) The average ETa was 704 mm during the growing season, showing an increasing trend in the irrigation area of the Yanqi Basin (IAY), whereas for the irrigation area of Burqin (IAB) the average ETa was 677 mm during the growing season, showing an increasing trend. The land cover type mainly influenced the spatial distribution of ETa in the two study areas. (3) The WSI in both irrigation areas exhibited a decreasing trend, with the WSI in the IAY lower than that in the IAB. (4) Climate warming, increases in irrigation areas, and changes in cropping patterns led to increased ETa in the IAY and IAB; the overall decreasing trend in the WSI derived from the popularization of agricultural water-saving irrigation patterns in both regions, which reduces ineffective evapotranspiration and contributes positively to solving the water shortage problem in the basins. This study provides insight into water resource management in the Xinjiang irrigation areas.

Analysis of the Relationship between Extreme Precipitation Pattern and Maximum Runoff in Hongze County From the Perspective of Urban Underlying Surface Production and Confluence

Based on the hourly precipitation data and evaporation data of the meteorological in Hongze County from 1959 to 2020, we studied the relationship between extreme precipitation and annual runoff control rate from the perspective of the underlying surface of the Hongze County watershed. We conducted a literature review and statistical analysis using SPSS in this study. From 1959 to 2020, precipitation in the Hongze region varied greatly annually, with the maximum and minimum annual precipitation of 1473.8 and 349.6 mm. The precipitation fluctuated but increased, and the extreme precipitation was concentrated in July to August. The annual average evapotranspiration from 1959 to 2020 was 1165.8 mm with an inter-annual fluctuation and decrease due to the urbanization process. The process affected the local evapotranspiration condition. More evaporation was observed from May to August than from December to January with a difference of 50 mm. The evaporation data coincided with seasonal variation in Hongze County. In determining the control rate of annual total runoff, we considered the inter-annual and annual differences in precipitation. The natural runoff condition and economic cost before urbanization were explored, too. The greater the rain intensity, the earlier the runoff generation time, the shorter the confluence time, and the greater the possibility of floods. In short-duration extreme precipitation, it is necessary to pay attention to its middle period, while for long-duration extreme precipitation, it is necessary to focus on its late period.

Reporting guidelines for terrestrial respirometry: Building openness, transparency of metabolic rate and evaporative water loss data

Respirometry is an important tool for understanding whole-animal energy and water balance in relation to the environment. Consequently, the growing number of studies using respirometry over the last decade warrants reliable reporting and data sharing for effective dissemination and research synthesis. We provide a checklist guideline on five key sections to facilitate the transparency, reproducibility, and replicability of respirometry studies: 1) materials, set up, plumbing, 2) subject conditions/maintenance, 3) measurement conditions, 4) data processing, and 5) data reporting and statistics, each with explanations and example studies. Transparency in reporting and data availability has benefits on multiple fronts. Authors can use this checklist to design and report on their study, and reviewers and editors can use the checklist to assess the reporting quality of the manuscripts they review. Improved standards for reporting will enhance the value of primary studies and will greatly facilitate the ability to carry out higher quality research syntheses to address ecological and evolutionary theories.

Effect of oil concentration, viscosity, and surface tension on tube temperature and heat transfer coefficients of R1234ze(E)/oil spray evaporation on an enhanced tube bundle

Shell-and-tube evaporators are widely used in desalination, refrigeration, and petrochemical industries. The heat transfer process in spray-type evaporators combines the droplets impingement at the top rows of the bundles and falling film evaporation for the bottom rows, with a transitional region in the center of the bundle. Spray evaporators are a promising alternative to flooded-type shell and tube heat exchangers because they run with significantly lower refrigerant charge amounts.This study presents new data for the spray evaporation of low-GWP refrigerant/oil mixtures on an enhanced tube bundle. The experiments involved R134a (HFC) and R1234ze(E) (HFO) paired with synthetic Polyolester (POE68 and POE220) lubricants. The tests utilized a boiling enhanced tube (re-entrant cavity tube) and were conducted at saturation temperatures of −6.7 °C, 2.2 °C and 10 °C (20°F, 36°F and 50°F), with heat flux varying from 3 to 35 kW/m2 and oil circulation ratio (OCR) ranging from 0.4 % to 2 %. With the addition of oil, the bundle heat transfer coefficient (HTC) of refrigerant/oil mixtures decreased by 20–50 % at an OCR of 1.2 % and a heat flux of 13.5 kW/m2, across the tested saturation temperatures. The average wall superheat across the bundle exhibited at least a 48 % increase for all the refrigerant/oil mixtures tested at an OCR of 1.2 %. The viscosity of the refrigerant/oil mixture showed a limited influence on heat transfer compared to surface tension, mainly because the oil concentrations were quite small. Oil promoted a partial dry-out of the tubes, especially at the bottom of the bundle. Foaming was observed and increased with heat flux and oil concentration. Foam sheets on the tube bundle created an additional barrier for the liquid refrigerant to reach the tube heat transfer surfaces and thus decreased the overall bundle heat transfer coefficient.

Generating a monthly variability of sea surface salinity based on source tracing of salt concentration and the estimated SEBAL-evaporation

Abstract The variation and spatial distribution of sea surface salinity (SSS) depend on the geographic condition of the water surfaces and the temporal variation of atmospheric conditions. The SSS might differ in a local coastal area compared to similar situations in global and regional oceans. The SSS values have been estimated based on spatial regression of extracted water-salt concentration as a source tracing of salt against corrected Landsat 8 satellite data during the drought season of April 2023. Here, the electrical conductivity (EC) from the Cimanuk River can be used as primary data. This result, paired with the evaporation-derived surface energy balance algorithm for land (SEBAL) algorithm, explains a monthly SSS variability after the validation using pre-defined resampled regional SSS and evaporation data. The result shows variations in estimated SSS values along with fluctuated SEBAL evaporation ranging from 1.64 to 1.62 dS/m and 1.04 to 0.41 W/m2, respectively. It describes monthly variability and their relationship in a local coastal area limited to the condition of a drought season. However, the validation shows that the root means square error (RMSE) of 1.00 from the SSS map, produced by the regression model involving band 7 of Landsat 8 and 9, has satisfied the reasonable SSS value ranges besides the best accuracy.

Establish an agricultural drought index that is independent of historical element probabilities

AbstractCurrently, there are three main shortcomings in meteorological drought indices: first, they rely on historical climate probability functions; second, the timescale used in calculations has a certain degree of subjectivity; third, the same index value may correspond to vastly different levels of actual drought in different climate types of regions. The purpose of this article is to establish a meteorological drought index that does not rely on historical meteorological element probability functions. Through theoretical derivation, four drought‐level maintenance lines are established on the cumulative precipitation‐cumulative water surface evaporation coordinate plane, and the coordinate quadrant is divided into five drought‐level areas. Through forward daily rolling accumulation, the maximum distance point is selected from the dynamically changing coordinate points to determine the corresponding cumulative precipitation and cumulative evaporation. The meteorological drought index is established by the distance from the selected coordinate point to each drought‐level maintenance line. Using daily precipitation and evaporation data from meteorological observation stations, the index is calculated based on the established meteorological drought index model, and compared with actual drought evolution and drought disaster records. The results show that the index can capture the development of drought well, and its changes are very consistent with drought disaster records. The index is of great significance for drought monitoring or assessment, and can provide guidance for water resource allocation, crop layout, and urban planning. Furthermore, it can also provide a way of thinking that does not rely on historical element probabilities for future drought research.

An approach for flood flow prediction utilizing new hybrids of ANFIS with several optimization techniques: a case study

ABSTRACT Using machine learning methods is efficient in predicting floods in areas where complete data is not available. Therefore, this study considers the Adaptive Neuro-Fuzzy Inference System (ANFIS) model combined with evolutionary algorithms, namely Harris Hawks Optimization (HHO) and Arithmetic Optimization Algorithm (AOA), to predict the flood of Shahrchay River in the northwest of Iran. The data used included the daily data of precipitation, evaporation, and runoff in the years 2016 and 2017, where 70% of the data were used for model training and the rest for testing the models. The results showed that although the ANFIS model provided values with high errors in several steps, especially in steps with maximum or minimum values, the use of HHO and AOA optimization algorithms resulted in a significant reduction in the error values. The ANFIS-AOA model utilizing an input scenario including the flow in the previous one to three days exerted the most promising results in the test data, with Nash Sutcliffe Efficiency (NSE) Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) of 0.93, 1.34, and 0.69, respectively. According to Taylor's diagram, the ANFIS-AOA hybrid algorithm predicts flood values with greater performance than the other models.

Revisiting the Thornthwaite Mather procedure for baseflow and groundwater storage predictions in sloping and mountainous regions

Hillslope aquifers regulate streamflow and are a critical potable and irrigation water source, especially in developing countries. Knowing recharge and baseflow is essential for managing these aquifers. Methods using available data to calculate recharge and baseflow from aquifers are not valid for uplands. This paper adapts the Thornthwaite and Mather (T-M) procedure from plains to sloping and mountainous regions by replacing the linear reservoir with a zero-order aquifer. The revised T-M procedure was tested over four years in two contrasting watersheds in the humid Ethiopian highlands: the 57 km2 Dangishta with a perennial stream and the nine km2 Robit Bata, where the flow ceased four months after the end of the rain phase. The monthly average groundwater tables were predicted with an accuracy ranging from satisfactory to good for both watersheds. Baseflow predictions were “very good” after considering the evaporation from shallow groundwater in the valley bottom during the dry phase in Dangishta. We conclude that the T-M procedure is ideally suited for calculating recharge, baseflow and groundwater storage in upland regions with sparse hydrological data since the procedure uses as input only rainfall and potential evaporation data that are readily available together with an estimate of the aquifer travel time.

How much evaporation occurs in Brazilian reservoirs? A multi-model perspective

Estimating evaporative losses from reservoirs is essential for water resource management. While remote sensing provides great opportunities for better constrain this process, there are still large uncertainties related to the behavior of evaporative losses across large domains. Here, we present a multi-model approach combined with remote sensing data to estimate evaporation losses at a national scale for dozens of reservoirs in Brazil. Open water evaporation (Ew) rates were obtained using two surface energy balance (SEB) models (the Google Earth Engine implementation of the Surface Energy Balance Algorithm for Land (geeSEBAL) and the Simplified Surface Energy Balance (SSEBop)). Due to the lack of in situ evaporation data, the estimations were cross-validated with results from the validated product Moderate-Resolution Imaging Spectroradiometer (MODIS) Water Reservoir Monthly Level 3 Global (MOD28C3) and the widely used open water evaporation equation described by Penman. Ew estimates were obtained for 74 large reservoirs, representing almost 70% of the area occupied by artificial water bodies in Brazil. Monthly estimates of Ew showed satisfactory agreement among the models, especially for geeSEBAL, SSEBop, and MOD28C3. Reservoirs with higher Ew were located in the semi-arid Caatinga Biome. The total annual evaporation and net evaporation (difference between lake Ew and surrounding evapotranspiration) for the assessed reservoirs were 46.6 ± 1.0 km³ and 16.4 ± 0.5 km³, respectively, for the period 2003–2021, based on an average of geeSEBAL and SSEBop. We also found that net evaporation is very high in dry climate zones and lower in tropical and humid subtropical climate zones. Our results show the advantage of integrating remote sensing datasets and evaporation models with cloud computing to obtain evaporation estimates in a tropical region and over a large domain. These multi-model evaporation estimates can improve our understanding of water resources in ungauged regions at a large spatial scale.

High Spatiotemporal Estimation of Reservoir Evaporation Water Loss by Integrating Remote-Sensing Data and the Generalized Complementary Relationship

Accurately estimating the reservoir evaporation loss is crucial for water resources management. The existing research on reservoir evaporation loss estimates primarily focuses on large spatiotemporal scales and neglects the rapid dynamic changes to reservoirs’ surface area. For reservoirs essential for frequent flood control and regular water supply, high spatiotemporal evaporation data are crucial. By integrating remote sensing and the evaporation model, this study proposes a new method for the high spatiotemporal estimation of the evaporation losses from reservoirs. The proposed method is applied to the largest artificial freshwater lake in Asia, i.e., Danjiangkou (DJK) Reservoir. The daily reservoir water surface area is extracted at a spatial resolution of 30 m during the period 2014–2018 based on the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM). The daily evaporation rate is estimated at a spatial resolution of 100 m using the generalized complementary relationship (GCR). The results show that the water surface area of the DJK Reservoir exhibits rapid and frequent fluctuations from 2015 to 2018, with a multi-year average area of 731.9 km2 and a maximum and minimum difference of 304 km2. Significant seasonal variations are observed in both the evaporation rate and volume, with a multi-year average evaporation rate of 806 mm and evaporation volume of 595 million m3. The estimated results align well with three other independent estimates, indicating that the GCR is capable of water surface evaporation estimation. Further analysis suggests that the data resolution has a great influence on the evaporative water loss from the reservoir. The estimated mean annual evaporation volume based on the 1000 m resolution water surface area data is 14% lower than that estimated using the 30 m resolution water surface area data. This study not only provides a new method for the high spatiotemporal estimation of reservoir evaporation by integrating remote-sensing data and the GCR method but also highlights that reservoir evaporation water loss should be quantified using the volume rather than the rate and that the estimated loss is noticeably affected by the estimation spatial resolution.

Drought Assessment of Yeşilırmak Basin Using Long-term Data

Drought is a prolonged period of inadequate rainfall, such as one season, one year or several years, on a statistical multi-year average for a region. Drought is a natural disaster effective on several socio-economic activities from agriculture to public health and leads to deterioration of the environment sustainability. The drought starts with meteorological drought, continues with agricultural and hydrological drought, and when it is in the socioeconomic dimension, the effects begin to be observed. Generally, drought studies are based on drought indices in the literature. This study applied long-term precipitation, temperature, and evaporation data from Samsun, Tokat, Merzifon, Çorum and Amasya meteorological stations from 1961 to 2022 to investigate the drought in the Yeşilırmak basin of Turkey. The present study applied Standardized Precipitation Index (SPI), and Effective Drought Index (EDI), China Z- Index (CZI) and Standardized Precipitation Evapotranspiration Index (SPEI) based on daily, monthly, seasonal, and annual time periods to evaluate drought. The Sen slope and Mann-Kendall test were employed for data analysis. The results revealed that the monthly drought indices for the study area were almost identical for the study area. Although dry and wet periods were observed.

Developing a General Daily Lake Evaporation Model and Demonstrating Its Application in the State of Texas

AbstractOpen water evaporation, which often consumes a large fraction of annual storage (especially in arid and semi‐arid regions), is a controlling variable for modern water resource management. Developing a daily reservoir evaporation data set is necessary for reservoir operations to consider the influence of evaporation in a timely manner. However, over the past few decades, the quantification of reservoir evaporation has primarily relied on monthly Class A pan evaporation observations, which might lead to largely biased estimations because they do not incorporate the effects of heat storage and fetch. In this study, we developed a general Daily Lake Evaporation Model (DLEM) based on Penman's equation combined with daily atmospheric reanalysis data sets, to improve the validity and frequency of reservoir evaporation monitoring. Compared with daily evaporation estimates from eddy covariance systems, the DLEM showed good quality and reliability, with R2 values ranging from 0.50 to 0.73 and RMSE values ranging from 1.13 to 1.97 mm day−1 in four different sites. By applying DLEM to all 188 major reservoirs in Texas, we generated a long‐term data set of (1 January 1981–31 December 2021) daily evaporation rates. The results reveal a clear geographic distribution and strong seasonality of evaporation throughout Texas, where the mean evaporation rate is highest during July, with 6.85 mm day−1. Trend analysis indicates that the annual average evaporation rate has significantly increased since 1981 at a rate of 0.076 mm day−1 decade−1. This study provides sufficient data support for water resource operations and management, and regional water planning.

Liquid evaporation from nanochannel in the presence of non-condensable gas by direct simulation Monte Carlo

Liquid-vapor phase change in the form of evaporation and with the confinement of nanostructures is of vast importance in many engineering applications. The direct simulation Monte Carlo (DSMC) approach was employed to simulate the liquid evaporation from two-dimensional nanochannels in the presence of non-condensable (NC) gases. The thermodynamic properties of vapor and NC gas flow fields as well as the evaporation rate of liquid were calculated. Factors such as channel opening ratio, meniscus receding depth and the NC gas density were examined to reveal their impacts on the liquid evaporation rates. The results showed that the gas mixture flow field transforms to one-dimensional away from the channel exit. The overall vapor pressure drop can be divided into that across the liquid–vapor interface, that within the channel, outside the channel, as well as that caused by the binary diffusion. The effect of NC gas on the evaporation rate was found to be the most outstanding with pinned meniscus and with a wide channel opening, in which case the normalized evaporation rate drops to 0.43. Moreover, the Maxwell-Stefan equation could capture the evaporation data with modified diffusion lengths. For receded meniscus (250 nm deep) and small opening ratio (0.417), the effective diffusion length was as large as 1.6 times that in the one-dimensional case.

Lake Tanganyika basin water storage variations from 2003–2021 for water balance and flood monitoring

Lake Tanganyika in East Africa contains 17% of the free freshwater on the Earth's surface and provides important ecosystem services to ∼13 million people in the region. It is one of the great lakes in East Africa for which a significant rise in water level between 2019 and 2020 led to flooding, with major environmental consequences and social impacts. This study focused on the Lake Tanganyika basin water balance between 2003 and 2021 to assess the influence of recent climate variability on lake water level variations (due in particular to the floods of 2020 and 2021) and to explore early warnings of flooding in the lake's surrounding lowlands. This process is performed using remote sensing data. For the computation of the basin's water balance, we compared variations in the watershed total water storage (TWS) with the basin water flux calculated using rainfall, evaporation (E), evapotranspiration (ET) and discharges data. The space–time variations in rainfall, E and ET were analyzed by decomposing their time series into trend and seasonal signals and applying (only for rainfall) multivariate statistical analysis to the decomposed signals. For flood mapping, we calculated the MNDWI spectral water index from Sentinel–2 images acquired between 2017 and 2022. Our study showed that the basin water balance is closed when rainfall from Era5 is combined with E and ET from GLEV and MOD16A2, respectively. During the 2003–2021 period, over the entire watershed, water losses of ∼70 km³ due to lake E were offset by an increase in water inflows of ∼100 km³ in the rest of the watershed. During the period from 2003 to 2021, the E rate from the lake was stable overall, while the ET and rainfall mainly in the Malagarasi basin increased significantly. The surface water storage (SWS), which represents the variation in lake water volume derived from altimetry measurements, corresponds to 41.8% of the TWS, groundwater storage corresponds to 57.7% of the TWS, and the soil moisture is less than 0.5%. The TWS strongly correlated with the SWS (∼91%), with a one-month lag in the SWS variations in response to the TWS fluctuations. Therefore, the SWS in May, when the flood risk is the highest, was estimated using TWS in February, March and April with accuracies of 85%, 94% and 95%, respectively. This valuable information could be integrated into flood management tools, particularly for areas such as Gatumba city and the Ruzizi Delta Nature Reserve, which were heavily affected by the May 2021 floods.

Exacerbating water shortage induced by continuous expansion of surface artificial water bodies in the Yellow River Basin

Aggravated water shortage limits high-quality and sustainable development in the Yellow River Basin (YRB), an important strategic region with a dense population in China. Surface water area (SWA) and terrestrial water storage (TWS) are two crucial indicators of the overall status of water resources in the region, so monitoring their dynamics and drivers is extremely important for sustainable water management under a changing climate and anthropogenic disturbances. Here, we examined the interannual variabilities and trends of SWA and TWS in the YRB during 1990–2021 utilizing all Landsat-5/7/8 surface reflectance observations, Gravity Recovery and Climate Experiment mascon data, a robust water mapping algorithm based on spectral indices and thresholds, and the Google Earth Engine (GEE) cloud computing platform. We found that SWA continuously and substantially expanded (49.67 ± 9.73 km2/yr) in the YRB. The most rapid expansion of SWA occurred in Shandong Province (20.24 ± 1.00 km2/yr), next in the provinces of Henan (15.09 ± 1.16 km2/yr), Shanxi (13.21 ± 1.11 km2/yr), and Shaanxi (4.11 ± 1.07 km2/yr). Quantitative attribution analysis showed that anthropogenic factors, including constructing and extending artificial reservoirs/lakes (42.4 %) and aquaculture ponds (26.5 %), were the major contributors to increased SWA. However, TWS had a significant downward trend (-6.82 ± 0.99 mm/yr) across the entire YRB. Using water evaporation data, we found that evaporation consistently increased (0.07 ± 0.01 km3/yr or 0.16 ± 0.02 mm/yr), which was mainly caused by SWA expansion in Shandong, Henan, Shanxi, Shannxi, Inner Mongolia. We also identified the hotspots with the most rapid increases in evaporative loss, which were in the provinces of Shandong (0.026 ± 0.002 km3/yr) and Henan (0.018 ± 0.001 km3/yr). These losses resulted in a decline of TWS by 1.37 ± 0.11 mm/yr and 0.5 ± 0.05 mm/yr, respectively. Our findings warn that the expanding surface water bodies were not only an illusion of increased freshwater resources in the YRB but also exacerbated the water crisis by accelerating TWS loss through evaporation.

Hydraulic Characterization of Green Roof Substrates by Evaporation Experiments

Green roofs can be a valid solution for stormwater management in urban environments. The objective of this study was to develop a laboratory procedure for the hydraulic characterization of artificial substrates, used in the realization of green roofs, based on transient evaporation and steady-state unit hydraulic gradient (UHG) experiments. The retention, θ(h), and hydraulic conductivity, K(h), curves of two commercial substrates Terra Mediterranea® (TMT) and AgriTERRAM® (ATV) and a specifically developed substrate made by mixing peat, compost and sandy loam soil (MIX) were investigated. The unimodal van Genuchten–Mualem (VGM) hydraulic functions obtained by the direct evaporation method with different choices of the fitting parameters were compared with UHG measurements of K(h) conducted close to saturation. A numerical inversion of the transient evaporation experiments performed by Hydrus-1D software was also conducted, assuming that the hydraulic properties could be expressed either by unimodal or bimodal VGM models. The results indicated that an appropriate a priori choice of the residual water content parameter improved the estimation of the water retention curve. Moreover, the water retention data estimated from the direct evaporation method were not statistically different from those obtained with the inverse Hydrus-1D. The unsaturated hydraulic conductivity estimations obtained by the direct and inverse methods were highly correlated and the use of the bimodal VGM model improved the estimation of K(h) in the wet range. The numerical inversion of laboratory evaporation data with the hydraulic characteristics expressed by the bimodal VGM model proved to be a reliable and effective procedure for hydraulic characterization of artificial substrates, thus improving the reliability of simulated water fluxes in green roofs.