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Abstract: Quantifying evapotranspiration (ET) is critical to accurately predict vegetation health, groundwater recharge, and streamflow generation. Hillslope aspect, the direction a hillslope faces, results in variable incoming solar radiation and subsequent vegetation water use that drive ET. Previous work in watersheds with a single dominant vegetation type (e.g., trees) have shown that equator‐facing slopes (EFS) have higher ET compared to pole‐facing slopes (PFS) due to higher evaporative demand. However, it remains unclear how differences in vegetation type (i.e., grasses and trees) influence ET and water partitioning between hillslopes with opposing aspects. Here, we quantified ET and root‐zone water storage deficits between a PFS and EFS with contrasting vegetation types within central coastal California. Our results suggest that the cooler PFS with oak trees has higher ET than the warmer EFS with grasses, which is counter to previous work in landscapes with a singule dominant vegetation type. Our root‐zone water storage deficit calculations indicate that the PFS has a higher subsurface storage deficit and a larger seasonal dry down than the EFS. This aspect difference in subsurface water storage deficits may influence the subsequent replenishment of dynamic water storage, groundwater recharge and streamflow generation. In addition, larger subsurface water deficits on PFS may reduce their ability to serve as hydrologic refugia for oaks during multi‐year droughts. This research provides a novel integration of field‐based and remotely‐sensed estimates of ET required to properly quantify hillslope‐scale water balances. These findings emphasize the importance of resolving hillslope‐scale vegetation structure within Earth system models, especially in landscapes with diverse vegetation types.

Although Essential Climate Variables (ECVs) have been widely adopted as important metrics for guiding scientific and policy decisions, the Earth Observation (EO) and Land Surface and Hydrologic Model (LSM/HM) communities have yet to treat terrestrial ECVs in an integrated manner. To develop consistent terrestrial ECVs at regional and continental scales, greater collaboration between EO and LSM/HM communities is needed. An essential first step is assessing the LSM/HM simulation uncertainty. To that end, we introduce a new hydrological reference dataset that comprises a range of 19 existing LSM/HM simulations that represent the current state-of-the-art of our LSM/HMs. Simulations are provided on a daily time step, covering Europe, notably the Rhine and Po river basins, alongside the Tugela river basin in Africa, and are uniformly formatted to allow comparisons across simulations. Furthermore, simulations are comprehensively validated with discharge, evapotranspiration, soil moisture and total water storage anomaly observations. Our dataset provides valuable information to support policy development and serves as a benchmark for generating consistent terrestrial ECVs through the integration of EO products. [ABSTRACT FROM AUTHOR]

The Priestley–Taylor model of the Jet Propulsion Laboratory (PT-JPL) evapotranspiration (ET) model is relatively simple and has been widely used based on meteorological and satellite data. However, soil moisture (SM) constraints include a vapor pressure deficit (VPD) that causes large uncertainty. In this study, we proposed a PT-SinRH model by introducing a sine function of air relative humidity (RH) to replace RHVPD to characterize SM constraints, which can improve the accuracy of ET estimations. The PT-SinRH model is validated by eddy covariance (EC) data from 2000–2020. These data were collected by AmeriFlux at 28 sites on the conterminous United States (CONUS), and the land cover types of the sites vary from croplands to wetlands, grasslands, shrub lands and forests. The validation results from daily scale-based on-site and satellite data inputs showed that the PT-SinRH model estimates fit the observations with a coefficient of determination (R2) of 0.55, root-mean-square error (RMSE) of 17.5 W/m2, bias of −1.2 W/m2 and Kling–Gupta efficiency (KGE) of 0.70. Additionally, the PT-SinRH model based on reanalysis and satellite data inputs has an R2 of 0.49, an RMSE of 20.3 W/m2, a bias of −8.6 W/m2 and a KGE of 0.55. The PT-SinRH model showed better accuracy when using the site-measured meteorological data than when using reanalysis meteorological data as inputs. Additionally, compared with the PT-JPL model, the results demonstrate that our approach, i.e., PT-SinRH, improved ET estimates, increasing the R2 and KGE by 0.02 and decreasing the RMSE by about 0.6 W/m2. This simple but accurate method permits us to investigate the decadal variation in regional ET over the land. [ABSTRACT FROM AUTHOR]

The study gives an estimate of the effect of four methods most often used in hydrological models to calculate the potential evapotranspiration—Penman–Monteith, Priestley–Taylor, Oudin, and Hargreaves, which differ in complexity and meteorological data requirements—on the efficiency and the results of simulating the dynamics of water balance components. The methodological base of the hydrological simulation was the widely known HBV conceptual model, in which the actual evapotranspiration is associated with the current state of a storage, which simulates the dynamics of soil moisture content. The objects of the study were 18 catchments with areas from 2.4 to 755 km2, located within the former Primorskaya Water-Balance station, the data of which were used in calculations of potential evapotranspiration and simulations of runoff. The comparison of simulation results with observations showed that the model values of evapotranspiration at the use of physically sound methods are in better agreement with the Budyko's procedure of determination of potential evapotranspiration. The analysis of model sensitivity to the input potential evaportranspiration showed that the use of physically based methods to calculate the potential evapotranspiration has no general effect on the efficiency of runoff hydrograph simulation of the studied objects. At the same time, in the case when empirical models of evapotranspiration are used, the uncertainty in the results of calculation of potential evapotranspiration should be compensated for by model parameters that are less physically substantiated, which, in turn, can lead to distortion of the dynamics of water balance components and runoff genetic components. [ABSTRACT FROM AUTHOR]

Remotely sensed evapotranspiration (ETRS) shows promise for enhancing hydrological models, especially in regions lacking in situ streamflow observations. However, model calibration studies showed conflicting results regarding the ability of ETRS products to improve streamflow simulation. Rather than relying on model calibration, here we produce the first randomized experiment that explores the full streamflow–ET skill distribution, and also the first probabilistic assessment of the value of different global ETRS products for streamflow simulation. Using 280,000 randomized SWAT (Soil and Water Assessment Tool) model runs across seven catchments and four ETRS products, we show that the relationship between ET and streamflow skills is complex, and simultaneous improvement in both skills is only possible in a limited range. Parameter sensitivity analysis indicates that the most sensitive parameters can have opposite contributions to ET and streamflow skills, leading to skill trade-offs. Conditional probability assessment reveals that models with good ET skills are likely to produce good streamflow skills, but not vice versa. We suggest that randomized experiments such as ours should be performed before model calibration to determine whether using ETRS is worthwhile, and to help in interpreting the calibration results. [ABSTRACT FROM AUTHOR]

This study employs an event‐based approach to analyse drought propagation from meteorological to hydrological drought via agricultural drought in the semi‐arid Krishna River basin of India. The Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Soil Moisture Index (SSMI) and Standardized Streamflow Index (SSI) representing meteorological, agricultural and hydrological drought, respectively, were estimated. Two different cases of drought propagation are analysed: meteorological‐to‐agricultural (SPEI‐to‐SSMI) and agricultural‐to‐hydrological (SSMI‐to‐SSI). The drought propagation is analysed using three‐time matrices, namely the time difference between initiation (∆ti2i$$ \Delta {t}_{i2i} $$), peak (∆tp2p$$ \Delta {t}_{p2p} $$) and termination (∆tt2t$$ \Delta {t}_{t2t} $$) at multiple timescales of 1, 3, 6, 9 and 12 months using different drought threshold values 0, −0.5, −1 and − 1.5, respectively, to delineate shifts from mild to extreme drought conditions in detail. The results indicate that the propagation time from SPEI‐to‐SSMI drought decreased for most of the tributaries using multiple timescales at different threshold values, whereas it increased significantly for SSMI‐to‐SSI drought. The drought propagation changes with respect to time as well as magnitude (intensity and severity). The propagation factor (PF), defined as the ratio of the average value of succeeding drought to preceding drought characteristics, has also been studied. For SPEI‐to‐SSMI drought, the duration PF shrinks across all tributaries using multiple timescales at different threshold values, whereas it expands for SSMI‐to‐SSI drought. On the other hand, the severity and intensity PF magnify for SPEI‐to‐SSMI drought, whereas it experiences dampening effects for SSMI‐to‐SSI drought. Thus, the proposed study provides valuable insights into drought propagation dynamics, aiding in managing and mitigating droughts in the semi‐arid river basin and elsewhere. [ABSTRACT FROM AUTHOR]

In light of climate change and limited water resources, optimizing water usage in agriculture is crucial. This study models water productivity to help regional planners address these challenges. We integrate CROPWAT-based reference evapotranspiration (ETo) with Sentinel 2 data to calculate daily evapotranspiration and water needs for maize using soil and climate data from 2021 to 2023. The HYDRUS model predicted volumetric soil moisture content, validated against observed data. A 2D hydrodynamic model within HYDRUS simulated temporal and spatial variations in soil water distribution for maize at a non-irrigated site in Hungary. The model used soil physical properties and crop evapotranspiration rates as inputs, covering crop development stages from planting to harvest. The model showed good performance, with R² values of 0.65 (10 cm) and 0.81 (60 cm) in 2021, 0.51 (10 cm) and 0.50 (60 cm) in 2022, and 0.38 (10 cm) and 0.72 (60 cm) in 2023. RMSE and NRMSE values indicated reliability. The model revealed water deficits and proposed optimal irrigation schedules to maintain soil moisture between 32.2 and 17.51 V/V%. This integrated approach offers a reliable tool for monitoring soil moisture and developing efficient irrigation systems, aiding maize production's adaptation to climate change. [ABSTRACT FROM AUTHOR]

The combination effect of straw mulching and supplemental irrigation on the soil water and heat, and the growth and productivity of mature apple trees on the Loess Plateau of China remains unclear. Field experiments were conducted in 2022 and 2023 to evaluate the combined effect of straw mulching and supplemental irrigation (two irrigation types, ring and double-row drip irrigation, and three irrigation levels: high, medium, and low irrigation level) on the soil water and temperature, growth, yield, and water productivity (WP) of a mature apple orchard. Local rainfed cultivation was used as the control (CK). The results showed that straw mulching increased soil moisture by 2.4–6.5% compared to the CK treatment. Supplemental irrigation significantly increased soil moisture in the 0–60 cm layer by 3.0–8.1%, and its effect increased with an increasing irrigation level. Straw mulching significantly reduced soil temperature by 7.8% compared to the CK treatment. Supplemental irrigation significantly increased the new shoot length and stem thickness of apple trees. Under straw mulching, a medium supplemental irrigation level significantly increased both apple yield and WP compared to the CK treatment. In this study area, it is recommended to choose a combination of straw mulching and a medium supplemental irrigation level. [ABSTRACT FROM AUTHOR]

Flash droughts are rapidly developing subseasonal climate extreme events that are manifested as suddenly decreased soil moisture, driven by increased evaporative demand and/or sustained precipitation deficits. Over each climate region in the contiguous United States (CONUS), we evaluated the forecast skill of weekly root-zone soil moisture (RZSM), evaporative demand (ETo), and relevant flash drought (FD) indices derived from two dynamic models [Goddard Earth Observing System model V2p1 (GEOS-V2p1) and Global Ensemble Forecast System version 12 (GEFSv12)] in the Subseasonal Experiment (SubX) project between years 2000 and 2019 against three reference datasets: Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2), North American Land Data Assimilation System, phase 2 (NLDAS-2), and GEFSv12 reanalysis. The ETo and its forcing variables at lead week 1 have moderate-to-high anomaly correlation coefficient (ACC) skill (∼0.70–0.95) except downwelling shortwave radiation, and by weeks 3–4, predictability was low for all forcing variables (ACC < 0.5). RZSM (0–100 cm) for model GEFSv12 showed high skill at lead week 1 (∼0.7–0.85 ACC) in the High Plains, West, Midwest, and South CONUS regions when evaluated against GEFSv12 reanalysis but lower skill against MERRA-2 and NLDAS-2 and ACC skill are still close to 0.5 for lead weeks 3–4, better than ETo forecasts. GEFSv12 analysis has not been evaluated against in situ observations and has substantial RZSM anomaly differences when compared to NLDAS-2, and our analysis identified GEFSv12 reforecast prediction limit, which can maximally achieve ACC ∼0.6 for RZSM forecasts between lead weeks 3 and 4. Analysis of major FD events reveals that GEFSv12 reforecast inconsistently captured the correct location of atmospheric and RZSM anomalies contributing to FD onset, suggesting the needs for improving the dynamic models' assimilation and initialization procedures to improve subseasonal FD predictability. Significance Statement: Flash droughts are rapidly developing climate extremes which reduce soil moisture through enhanced evaporative demand and precipitation deficits, and these events can have large impacts on the ecosystem and crop health. We evaluated the subseasonal forecast skill of soil moisture and evaporative demand against three reanalysis datasets and found that evaporative demand skill was similar between forecasts and reanalyses while soil moisture skill is dependent on the reference dataset. Skill of evaporative demand decreases rapidly after week 1, while soil moisture skill declines more slowly after week 1. Case studies for the 2012, 2017, and 2019 United States flash droughts identified that forecasts could capture rapid decreases in soil moisture in some regions but not consistently, implying that long-lead forecasts still need improvements before being used in early warning systems. Improvements in flash drought predictability at longer lead times will require less biased initial conditions, better model parameterizations, and improved representations of large-scale teleconnections. [ABSTRACT FROM AUTHOR]

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The hydrologic flows across the river–aquifer interface play an important role in groundwater dynamics and biogeochemical reactions within the subsurface; however, little is known about the effects of river–aquifer interactions on land surface processes. In this study, we developed a fully coupled three‐dimensional (3D) land surface and subsurface model at a high resolution (~1 km) that accounts for high‐frequency hydrologic exchange flow conditions to investigate how river–aquifer interactions modulate surface water budgets in the Upper Columbia‐Priest Rapids watershed, a typical semiarid watershed located in the northwestern United States where river stage fluctuates in response to reservoir releases changing. Our results show that the spatiotemporal dynamics of river–aquifer interactions are highly heterogeneous, driven mainly by river‐stage fluctuations. Adding 6.64 × 106 m3 year−1 of water over the watershed from the river to groundwater owing to the lateral flow, river–aquifer interactions led to an increase in soil evaporation and transpiration supplied by higher soil moisture content, particularly in deeper subsurface. In a hypothetic future scenarios where a 5‐m rise in river stage was assumed, the hydrologic flow exchange rates were intensified, resulting in higher surface water over the entire watershed. Overall, lateral flow induced by river–aquifer exchanges leads to an increase in evapotranspiration of ~75% in the historical period and of ~83% in the hypothetical future scenario. Our study demonstrates the potential of coupled model as an effective tool for understanding river–aquifer–land surface interactions, and indicates that river–aquifer interactions fundamentally alter the water balance of the riparian zone for the semiarid watershed and will likely become more frequent and intense in the future under the effects of climate change. [ABSTRACT FROM AUTHOR]

This study investigates the hazardous effect of salinity on plant growth and soil moisture dynamics in the root zone. Field irrigation experiments on paddy (Oryza sativa L.—basmati variety) with varying levels of salinity of irrigation water (0.5, 5, 10, 15, 20, and 25 dS/m) were performed for studying the effect of salt water stress on crop growth. Throughout the crop's growth period, measurements of leaf area index (LAI), root depth (RD), and soil moisture status in the root zone were recorded. For the analysis, a numerical model was developed to simulate root water uptake (RWU) and soil moisture movement in the root zone, accounting for osmotic pressure developed as a result of the salinity. Nonlinear parameters for the RWU model were estimated based on these observations for each salinity level. By incorporating meteorological data and soil–crop parameters, the model simulated RWU and root zone soil moisture. The results of the irrigation experiments revealed that increased salinity levels in the irrigation water significantly hindered crop development, leading to a decrease in LAI and root depth. The maximum LAI in the growth period decreased markedly, from 5.19 m2m−2 at 0.5 dS/m to 2.01 m2m−2 at 25 dS/m, a decline of approximately 61%. Root depth also exhibited a substantial reduction, declining by up to 36%, from 69.5 cm at 0.5 dS/m to 44.5 cm at 25 dS/m. The simulation outcomes further demonstrated that higher salt concentrations in the irrigation water resulted in reduced root water uptake and decreased soil moisture content in the root zone, ultimately affecting crop yield. The reduction in root water uptake becomes notably pronounced, exhibiting an approximate decrease of 81% when salinity level increases from 0.5 to 25 dS/m. These findings shed light on the hazards posed by salinity in agricultural practices and emphasize the importance of effective management strategies to ensure sustainable crop production in the presence of salinity-induced hazards. Practical Applications: The results of our research yield significant insights with practical applications for real-life conditions. We find that increasing salinity levels in irrigation water have a pronounced adverse effect on paddy crop growth and root water uptake. As salinity levels rise, there is a noticeable effect on crop growth i.e., decrease in leaf area index (LAI), root depth (RD), and root water uptake (RWU), which are crucial parameters for crop development. Furthermore, our findings reveal a clear correlation between increasing salinity and reduced soil moisture content, particularly at the critical depths of 20 and 40 cm below the surface. The practical implications of our research are twofold. First, it underscores the importance of carefully managing salinity levels in irrigation practices to mitigate the negative effects on crop growth and water uptake. Secondly, our study provides valuable insights for crop selection, suggesting that paddy crops may be less suitable under high salinity conditions. These results offer practical guidance for agricultural decision makers, highlighting the need for salinity control measures and informed crop selection to optimize agricultural productivity in regions with saline water environments. [ABSTRACT FROM AUTHOR]

Determination of actual crop evapotranspiration (ETc) is a crucial challenge for sustainable irrigation water management. In this sense, robust and accurate estimation models of crop water consumption along with spatial tools and processing platforms in the cloud are necessary to determine the timing and amount of irrigation needed as a first step toward proposing solutions and water use efficiency. The objective of this study was to determine maize crop evapotranspiration using the algorithms of the Mapping Evapotranspiration at High Resolution with Internalized Calibration (METRIC) model in the Google Earth Engine (GEE) platform. The crop was monitored with 14 Landsat images during its growth period. ETc values with METRIC were compared with ETc obtained with the FAO-56 methodology, and the cumulative ETc was compared with ETc derived from a soil moisture sensor. The evaluation between the METRIC model and FAO-56 displayed a determination coefficient (R2) of 0.87, mean squared error (MSE) of 0.8 mm/day, and bias percentage (PBIAS) of -14.5. According to the cumulative ETc, the difference was 16 mm for METRIC and 63 mm for FAO-56, compared with moisture sensor values. METRIC overestimated by 3.0% (PBIAS=-3.0), and FAO-56 underestimated by 11.9% (PBIAS=11.9). The results and the programmed algorithms in this work can be the basis for future calibrations and validations of the evapotranspiration of different crops.

[Display omitted] Estimation of evapotranspiration (ET a) change on the Tibetan Plateau (TP) is essential to address the water requirement of billions of people surrounding the TP. Existing studies have shown that ET a estimations on the TP have a very large uncertainty. In this article, we discuss how to more accurately quantify ET a amount and explain its change on the TP. ET a change on the TP can be quantified and explained based on an ensemble mean product from climate model simulations, reanalysis, as well as ground-based and satellite observations. ET a on the TP experienced a significant increasing trend of around 8.4 ± 2.2 mm (10 a)−1 (mean ± one standard deviation) during 1982–2018, approximately twice the rate of the global land ET a (4.3 ± 2.1 mm (10 a)−1). Numerical attribution analysis revealed that a 53.8% TP area with the increased ET a was caused by increased temperature and 23.1% part was due to soil moisture rising, because of the warming, melting cryosphere, and increased precipitation. The projected future increase in ET a is expected to cause a continued acceleration of the water cycle until 2100. [ABSTRACT FROM AUTHOR]

Agriculture being an essential activity sector for the survival and prosperity of humanity, it is fundamental to use sustainable technologies in this field. With this in mind, some statistical data are analyzed regarding the food price rise and sustainable development indicators, with a special focus on the Portugal region. It is determined that one of the main factors that influences agriculture's success is the soil's characteristics, namely in terms of moisture and nutrients. In this regard, irrigation processes have become indispensable, and their technological management brings countless economic advantages. Like other branches of agriculture, the wine sector needs an adequate concentration of nutrients and moisture in the soil to provide the most efficient results, considering the appropriate and intelligent use of available water and energy resources. Given these facts, the use of renewable energies is a very important aspect of this study, which also synthesizes the main irrigation methods and examines the importance of evaluating the evapotranspiration of crops. Furthermore, the control of irrigation processes and the implementation of optimization and resource management models are of utmost importance to allow maximum efficiency and sustainability in this field. [ABSTRACT FROM AUTHOR]

This study addresses the impact of climate variability on latex yield. Field research was carried out in the Indonesian Rubber Research Institute Experimental Field, located in South Sumatra, Indonesia for 2020 to 2022. The study used mature IRR 118 clones of rubber (Hevea brasiliensis) planted in clay loam soil. Latex yields for dry and rainy seasons were compared to obtain the effects of climatic factors. A purposive sampling of latex clone IRR 118 was applied in the field. The results showed that declined rainfall and soil moisture content contributed to the low latex yield during dry season. A declined water availability acts as a limiting factor resulting in decreased latex yield. Latex yield consistently decreased when soil moisture content fell below 21.5%. Based on statistical analysis, the correlation between latex yield and climate factor was 0.36, 0.42, and 0.52 for rainfall, soil moisture content, and evapotranspiration, respectively. Our findings highlight the crucial influence of climatic factors, emphasizing the significance of optimal water availability for latex production. [ABSTRACT FROM AUTHOR]

The Brazilian Cerrado biome is known for its high biodiversity, and the role of groundwater recharge and climate regulation. Anthropogenic influence has harmed the biome, emphasizing the need for science to understand its response to climate and reconcile economic exploration with preservation. Our work aimed to evaluate the seasonal and interannual variability of the surface energy balance in a woodland savanna (Cerrado) ecosystem in southeastern Brazil over a period of 19 years, from 2001 to 2019. Using field micrometeorological measurements, we examined the variation in soil moisture and studied its impact on the temporal pattern of energy fluxes to distinguish the effects during rainy years compared to a severe drought spell. The soil moisture measures used two independent instruments, cosmic ray neutron sensor CRNS, and FDR at different depths. The measures were taken at the Pé de Gigante (PEG) site, in a region of well-defined seasonality with the dry season in winter and a hot/humid season in summer. We gap-filled the energy flux measurements with a calibrated biophysical model (SiB2). The long-term averages for air temperature and precipitation were 22.5 °C and 1309 mm/year, respectively. The net radiation (Rn) was 142 W/m2, the evapotranspiration (ET) and sensible heat flux (H) were 3.4 mm/d and 52 W/m2, respectively. Soil moisture was marked by a pronounced negative anomaly in the 2014 year, which caused an increase in the Bowen ratio and a decrease in Evaporative fraction, that lasted until the following year 2015 during the dry season, despite the severe meteorological drought of 2013/2014 already ending, which was corroborated by the two independent measurements. The results showed the remarkable influence of precipitation and soil moisture on the interannual variability of the energy balance in this Cerrado ecosystem, aiding in understanding how it responds to strong climate disturbances. [ABSTRACT FROM AUTHOR]

Satellite observations have shown widespread greening during the last few decades over the northern permafrost region, but the impact of vegetation greening on permafrost thermal dynamics remains poorly understood, hindering the understanding of permafrost‐vegetation‐climate feedbacks. Summer surface offset (SSO), defined as the difference between surface soil temperature and near‐surface air temperature in summer (June‐August), is often predicted as a function of surface thermal characteristics for permafrost modeling. Here we examined the impact of leaf area index (LAI), detected by satellite as a proxy to permafrost vegetation dynamics, on SSO variations from 2003 to 2021 across the northern permafrost region. We observed latitude‐ and biome‐dependent patterns of SSO changes, with a pronounced increase in Siberian shrublands and a decrease in Tibetan grasslands. Based on partial correlation and sensitivity analyses, we found a strong LAI signal (∼30% of climatic signal) on SSO with varying elevation‐ and canopy height‐dependent patterns. Positive correlations or sensitivities, that is, increases in LAI lead to higher SSO, were distributed in relatively cold and wet areas. Biophysical effects of permafrost greening on surface albedo, evapotranspiration, and soil moisture (SM) could link the connection between LAI and SSO. Increased LAI substantially reduced surface albedo and enhanced evapotranspiration, influenced energy redistribution, and further controlled interannual variability of SSO. We also found contrasting effects of LAI on surface SM, consequently leading to divergent impacts on SSO. The results offer a fresh perspective on how greening affects the thermal balance and dynamics of permafrost, which is enlightening for improved permafrost projections. Plain Language Summary: Climate change has caused substantial vegetation growth that was detected by satellite observations ("greening") over northern permafrost regions. However, the consequences or feedbacks of vegetation greening remain largely unknown, hindering the understanding of near‐surface thermal dynamics and bringing considerable uncertainty in model projections. Here we aimed to decipher the biophysical impact of permafrost greening on the summer surface offset (SSO), which is an indicator of permafrost degradation. We found latitude‐ and biome‐dependent patterns of SSO changes and divergent responses of SSO to greening. Increases in satellite‐observed leaf area index lead to higher SSO in relatively cold and wet areas but lower SSO in warm‐dry regions. Biophysical mechanisms associated with surface albedo, evapotranspiration, and SM can help explain various effects of greening on SSO. Our results highlight greening feedbacks on the thermal dynamics of permafrost with climate warming, calling for the improvement of current projections. Key Points: Vegetation greening impacts the thermal dynamics of permafrost surfaceBiophysical effects of greening on surface offset could be related to surface albedo, evapotranspiration, and soil moisture [ABSTRACT FROM AUTHOR]

Addressing impacts of flash droughts (FDs) on the water‐food nexus requires a understanding of FD mechanisms and drivers at the watershed level. Examining climatic drivers, dry and wet spell lengths from 1980 to 2019, we analyzed FD spatial and temporal characteristics, emphasizing areal extent, onset time, and duration. Our findings reveal substantial variations in FDs among different watersheds. Notably, watersheds in the Southern Hemisphere are witnessing expanding, faster‐developing, and longer‐lasting FDs, aligning with climate variations in precipitation and temperature. Additionally, at the watershed scale, the onset and duration of FDs are more influenced by the intensity (magnitude and variability) of climatic drivers than the average length of wet and dry periods. FD‐extents, however, correlate with both climatic conditions and wet and dry periods, underscoring watershed connectivity. Ultimately, our results underscore the necessity for research to comprehend the interplay between FDs and watershed characteristics and how it manifests in overall water resource management. Plain Language Summary: Flash droughts (FDs), which are sudden and severe dry periods, are causing problems for our water and food systems and making it harder to prepare for disasters. To address these challenges effectively, it is crucial to gain a thorough understanding of the underlying mechanisms and factors driving FDs at the watershed level. In this study, we looked at climatic patterns alongside the lengths of dry and wet periods spanning from 1980 to 2019. Our primary focus was on three key aspects: the extent of FDs, when they begin, and how long they persist. Our research findings demonstrate considerable variations in FDs occurrences across different regions. Notably, in the Southern Hemisphere, FDs are expanding rapidly, developing more swiftly, and enduring for extended periods, closely mirroring shifts in precipitation and temperature patterns. Interestingly, the onset and duration of FDs seem to depend more on the intensity of climatic factors than on how long it's been dry or wet. The expansion of FDs in a region is linked to both the climatic and dry/wet periods, emphasizing the geophysical connectivity within a watershed. Key Points: Watersheds in tropical, temperate climates, and with savanna and grassland land cover are more susceptible to flash droughts (FDs)FDs extents are affected by intraannual precipitation variability, but not by intraannual air temperature variabilityThe onset and duration of FD at the watershed scale are influenced more by climate variables, than average wet/dry spell periods [ABSTRACT FROM AUTHOR]

Evapotranspiration affects uncertain changes in volumetric soil moisture content (θ) of earth surface, which is considerably controlled by temporal variability of weather parameters like rainfall and ambient temperature. Accurate measurement of temporal variation and spatial distribution of θ in a particular land is very challenging. Numerical modelling with any suitable computer code might be useful in such cases. Thus, Hydrus 2D modelling of θ variation in the soil at Odisha University of Agriculture and Technology (OUAT) in Bhubaneswar is undertaken as main objective of present study to investigate soil moisture dynamics in top surface layer. For the study, the θ in OUAT land was measured daily by 5 TM water content sensor for the duration of two years spanning from January 2021 to December 2022. Meteorological data for these 2 years are collected from a nearby weather station at OUAT and used for calculating evapotranspiration (ET) based on five different well known ET models. Soil hydraulic parameters of OUAT land were also evaluated by laboratory investigation. The evapotranspiration so calculated along with precipitation and materials properties were then assigned as the inputs in Hydrus 2D simulations. The simulated results are found to be in good agreement with field observations. It is proven by Pearson's coefficient of determination (R2) and Nash-Sutcliffe efficiency (NSE) which are found to be 0.83 and 0.84 respectively. The soil moisture simulation was the most accurate only when measured soil parameters along with atmospheric boundary involving Penman-Monteith (PM) ET model were considered as model inputs. [ABSTRACT FROM AUTHOR]

Agricultural production across the African continent is subjected to various effects of climate variability. One of the main staple foods in Sub-Saharan Africa is maize. However, limited scientific research has recently focused on understanding the possible effects of hydro-climatic variability on maize production. The aim of the present work was to contribute to policy and climate adaptation, thus reducing the vulnerability of maize production to climate change over Equatorial Africa. This study firstly examined long-term trends of precipitation (PRE), soil moisture (SM), actual evapotranspiration (E), and potential evapotranspiration (Ep), as well as surface air temperatures, including the minimum (TMIN) and maximum (TMAX). Secondly, the relationship between maize production and these climate variables was quantified for 18 Equatorial African countries (EQCs) over 1980−2021. To assess the linear trends, Mann–Kendall and Sen's slope tests were used to quantify the magnitude of the hydro-climatic variable trends at the 5% significance level, and Pearson's correlation coefficient was used to evaluate the relation of these climate parameters with the maize production. The annual mean PRE declined at 0.03 mm day−110a−1. Other climate variables increased at different rates: SM at 0.02 mmday−110a−1, E at 0.03 mm day−110a−1, Ep at 0.02 mm day−1 10a−1, TMIN and TMAX at 0.01 °C day−110a−1. A regional analysis revealed heterogeneous significant wet–dry and warm–cool trends over the EQCs. While, spatially, dry and warm climates were observed in the central to eastern areas, wet and warm conditions dominated the western regions. Generally, the correlations of maize production with the E, Ep, TMAX, and TMIN were strong (r > 0.7) and positive, while moderate (r > 0.45) correlations of maize production with PRE and SM were obvious. These country-wide analyses highlight the significance of climate change policies and offer a scientific basis for designing tailored adaptation strategies in rainfed agricultural regions. [ABSTRACT FROM AUTHOR]

Accurate estimation of evapotranspiration (ET) is crucial for improving crop water-use efficiency and facilitating precision irrigation. The Penman–Monteith (P-M) model is a widely used approach for ET calculation, with canopy resistance (rc) acting as a critical determinant of accuracy that is greatly affected by meteorological, crop, and soil factors. This study focused on the calibration of two rc models: Jarvis (JA) and coupled resistance (CO), utilizing ant colony optimization (ACO) and the least square method (LSM). Data from an eddy covariance system and a meteorological station in the Huailai summer maize field (115°47'E, 40°20'N) for the year 2013 were employed for model parameterization. Performance evaluation of these models was conducted using ET measurements obtained through the eddy covariance system in 2014. Path analysis was conducted to elucidate the impact of net radiation (Rn), temperature (T), vapor pressure deficit (VPD), soil water content (θ) and leaf area index (LAI) on rc. Results revealed a decrease in rc during growing season, with influencing factors ordered as Rn, LAI, VPD, T, and θ. The CO model optimized by ACO exhibited superior accuracy, with R2 of 0.89. Integration of the ACO-optimized the CO model into P-M model for ET estimation also demonstrated the highest accuracy with R2 of 0.72. JA model optimized by ACO provided satisfactory results in both parameters calibration and ET estimation. Therefore, the ACO-optimized CO model was recommended as the optimal approach for rc calculation of summer maize in semi-arid area. Additionally, the JA model optimized by ACO was proposed as a credible alternative to the CO model. These findings contribute to the refinement of ET estimation methodologies, offering valuable insights for precision agricultural water management practices. [ABSTRACT FROM AUTHOR]

Quantifying terrestrial evapotranspiration (ET) and soil moisture dynamics accurately is crucial for understanding the global water cycle and surface energy balance. We present a novel, long-term dataset of global ET and soil moisture derived from the newly developed Simple Terrestrial Hydrosphere model, version 2 (SiTHv2). This ecohydrological model, driven by multi-source satellite observations and hydrometeorological variables from reanalysis data, provides daily global ET-related estimates (e.g., total ET, plant transpiration, soil evaporation, intercepted evaporation) and three-layer soil moisture dynamics at a 0.1° spatial resolution. Validation with in-situ measurements and comparisons with mainstream global ET and soil moisture products demonstrate robust performance of SiTHv2 in both magnitude and temporal dynamics of ET and soil moisture at multiple scales. The comprehensive water path characterization in the SiTHv2 model makes this seamless dataset particularly valuable for studies requiring synchronized water budget and vegetation response to water constraints. With its long-term coverage and high spatiotemporal resolution, the SiTHv2-derived ET and soil moisture product will be suitable to support analyses related to the hydrologic cycle, drought assessment, and ecosystem health. [ABSTRACT FROM AUTHOR]

While remote sensing has provided extensive insights into the global terrestrial water, carbon, and energy cycles, space‐based retrievals remain limited in observing the belowground influence of the full soil moisture (SM) profile on ecosystem function. We show that this gap can be addressed when coupling 70 m resolution ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station retrievals of land surface temperature (LST) with in‐situ SM profile measurements. These data sets together reveal that ecosystem water use decreases with depth with 93% of sites showing significant LST coupling with SM shallower than 20 cm while 34% of sites have interactions with SM deeper than 50 cm. Furthermore, the median depth of peak ecosystem water use is estimated to be 10 cm, though forests have more common peak interactions with deeper soil layers (50–100 cm) in 37% of cases. High spatial resolution remote sensing coupled with field‐level data can thus elucidate the role of belowground processes on land surface behavior. Plain Language Summary: Belowground processes, like how roots use soil water for transpiration and how soil water is used for soil evaporation, remain as large uncertainties in the Earth system. This is because these belowground processes are difficult to widely observe and thus tend to only be studied at sparsely located field sites. We address these limitations here by simultaneously using high resolution (70 m scale) remote sensing measurements of land surface temperature (LST), which integrates ecosystem soil and vegetation behavior and water use, and ground networks of soil moisture (SM) measurements between 5 and 100 cm. We find that the relationship between LST and SM at different soil depths shows how ecosystems use moisture across the soil profile. Across vegetation types, our analysis suggests most water use originates from upper soil layers where soil evaporation occurs and where roots presumably preferentially draw water under nominal climatic conditions. Grassland sites tend to have a greater preference for use of moisture in upper soil layers than for forested sites, which show an increase in deeper water use below 50 cm. We therefore demonstrate that such methods can reveal how ecosystems respond to SM across the rootzone and across a range of globally available sites. Key Points: High resolution satellite retrievals of land surface temperature can reveal ecosystem water use when coupled with soil moisture (SM) networksAcross vegetation types, evaporation tends to mainly use water from the upper soil layers with a decrease of SM use with depthGrassland sites tend to have more frequent ecosystem water use of upper layer SM than forested sites [ABSTRACT FROM AUTHOR]

Changes are projected for the boreal biome with complex and variable effects on forest vegetation including drought‐induced tree mortality and forest loss. With soil and atmospheric conditions governing drought intensity, specific drivers of trees water stress can be difficult to disentangle across temporal scales. We used wavelet analysis and causality detection to identify potential environmental controls (evapotranspiration, soil moisture, rainfall, vapor pressure deficit, air temperature and photosynthetically active radiation) on daily tree water deficit and on longer periods of tree dehydration in black spruce and tamarack. Daily tree water deficit was controlled by photosynthetically active radiation, vapor pressure deficit, and air temperature, causing greater stand evapotranspiration. Prolonged periods of tree water deficit (multi‐day) were regulated by photosynthetically active radiation and soil moisture. We provide empirical evidence that continued warming and drying will cause short‐term increases in black spruce and tamarack transpiration, but greater drought stress with reduced soil water availability. Plain Language Summary: This research explores how climate change could impact the water stress experienced by black spruce and tamarack trees in the western boreal forest of Canada. We focused on a key measure called "tree water deficit" to understand if the trees were under stress due to insufficient water. We examined how tree water deficit relates to environmental factors such as temperature, sunlight, and soil moisture. The findings revealed that, on a daily basis, factors like sunlight and temperature cause trees to release more water into the air. However, over longer periods (days to weeks), the amount of water in the soil becomes crucial, suggesting that trees might face water stress during dry spells. So, while trees could grow more on hotter, sunnier days, they could also experience water stress and reduced growth if the soil becomes too dry for an extended period. This study helps us grasp how various factors interact to influence tree water stress in the boreal forest, providing insights important for managing these ecosystems in a changing climate. Key Points: A novel approach to determine environmental controls of tree water deficit across time scales with wavelet analysis and Granger causalitySoil moisture emerges as a significant control of tree water deficit in boreal trees at longer scales (multi‐days)Daily productivity gains with warming will be mitigated by decreased soil water availability in longer periods of tree water deficit [ABSTRACT FROM AUTHOR]

In the past decades, the climatic conditions in the region have changed, showing extreme weather events and gradual changes in precipitation and evapotranspiration. The historical climatic data (1961-1999) are calculated to average, but the extreme dry (2000) and wet (2014) years are also taken into consideration. The sediment's hydraulic conductivity is calculated using the Hydrus 1D model and measured on-site to establish the assessment model for various crops that will be easily simulated. The calculated vs. experimental values showed good agreement for the selected location of Srbovac village. Other parameters, such as soil moisture field capacity, soil moisture at the wilting point, maximum infiltration flux, and maximum drainage flux to the saturated zone, were calculated, too. Finding the adequate crop water requirement for changed soil water balance is done by using the FAO CROPWAT program. Three different soil textures were used for calculations: loam, sandy loam, and silty loam. Soil moisture at field capacity is found to be 220 mm/m, the maximum infiltration flux per day was 250 mm, and the maximum drainage flux to the saturated zone was 5 mm. The soil water balance was calculated by CROPWAT and presented for each month. In the period from 1961-1999, historical data, the total average precipitation was 911 mm, reference evapotranspiration (ETo) was 879 mm, and actual evapotranspiration (ETa) was 375 mm, but crop evapotranspiration of winter wheat (ETc-Crop) for the same period was 400 mm, that proves good climatic conditions for the selected crop. In the period from 2000-2023, the average climatic conditions were used for Crop-Water balance calculation, and the total precipitation was 712 mm, whereas ETo was 924 mm, ETa was 477 mm, and ETc-Crop of winter wheat for the same period was 641 mm, with 166 mm crop deficit in April, May, and June. [ABSTRACT FROM AUTHOR]

This study analyzed the meteorological and hydrological droughts in a typical basin of the Brazilian semiarid region from 1994 to 2016. In recent decades, this region has faced prolonged and severe droughts, leading to marked reductions in agricultural productivity and significant challenges to food security and water availability. The datasets employed included a digital elevation model, land use and cover data, soil characteristics, climatic data (temperature, wind speed, solar radiation, humidity, and precipitation), runoff data, images from the MODIS/TERRA and AQUA sensors (MOD09A1 and MODY09A1 products), and soil water content. A variety of methods and products were used to study these droughts: the meteorological drought was analyzed using the Standardized Precipitation Index (SPI) derived from observed precipitation data, while the hydrological drought was assessed using the Standardized Soil Index (SSI), the Nonparametric Multivariate Standardized Drought Index (NMSDI), and the Parametric Multivariate Standardized Drought Index (PMSDI). These indices were determined using water balance components, including streamflow and soil water content, from the Soil Water Assessment Tool (SWAT) model, and evapotranspiration data from the Surface Energy Balance Algorithm for Land (SEBAL). The findings indicate that the methodology effectively identified variations in water dynamics and drought periods in a headwater basin within Brazil's semiarid region, suggesting potential applicability in other semiarid areas. This study provides essential insights for water resource management and resilience building in the face of adverse climatic events, offering a valuable guide for decision-making processes. [ABSTRACT FROM AUTHOR]

Emerald ash borer (EAB) (Agrilus planipennis Fairmaire), an invasive, phloem-feeding beetle native to Asia, has killed millions of ash (Fraxinus spp.) trees in North America since it was detected in southeast Michigan in 2002. Consistently high mortality of black ash (Fraxinus nigra) and green ash (F. pennsylvanica) which often occur in riparian forests is a concern given their role in regulating soil moisture and shallow groundwater levels. We monitored and compared hydrologic processes in a riparian forest impacted by EAB invasion and an adjacent unimpacted riparian forest site in southwest Michigan. From 2018 to 2022, we recorded soil moisture, depth to groundwater and meteorological variables at 15-min intervals throughout the growing season in a canopy gap following EAB-caused ash mortality and in adjacent, unaffected forest in the Augusta Creek riparian zone. Groundwater contributions to evapotranspiration (ETG) were estimated using a groundwater level fluctuation (WLF) method. Significant differences in volumetric soil moisture content (16%--26% higher in the gap than forest), average depth to water (10 cm in the gap vs. 70 cm below land surface in the forest) and mean daily ETG (0.6 in the gap vs. 3.0 mm per day in the forest) persisted across four growing seasons. Within the gap, prolonged saturation of the near surface may be contributing to a shift from a forested riparian ecosystem to herb and sedge-dominated wetland. These differences have implications for an array of riparian zone ecosystem services, a concern given the extent of ash mortality already sustained in much of eastern North America. [ABSTRACT FROM AUTHOR]

AbstractUnderstanding the roles of land surface conditions and atmospheric circulation on continental daily temperature variance is key to improving predictions of temperature extremes. Evaporative resistance (rs, hereafter), a function of the land cover type, reflects the ease with which water can be evaporated or transpired and is a strong control on land–atmosphere interactions. This study explores the effects of rs perturbations on summer daily temperature variance using the Simple Land Interface Model (SLIM) by mimicking, for rs only, a global land cover conversion from forest to crop/grassland. Decreasing rs causes a global cooling. The cooling is larger in wetter areas and weaker in drier areas, and primarily results from perturbations in shortwave radiation (SW) and latent heat flux (LH). Decreasing rs enhances cloud cover due to greater land surface evaporation and thus reduces incoming SW over most land areas. When rs decreases, wetter areas experience strong evaporative cooling, while drier areas become more moisture-limited and thus experience less cooling. Thermal advection further shapes the temperature response by damping the combined impacts of SW and LH. Temperature variance increases in drier areas and decreases in wetter areas as rs decreases. The temperature variance changes can be largely explained from changes in the combined variance of SW and LH, including an important contribution of changes in the covariance of SW and LH. In contrast, the effects of changes in thermal advection variance mainly affect the Northern Hemisphere midlatitudes.Significance StatementThis study aims to better understand processes governing daily near-surface air temperature variance over land. We use an idealized modeling framework to explore the effects of land surface evaporative resistance (a parameter that controls how hard it is to evaporate water from the surface) on summer daily temperature variance. We find that a uniform decrease of evaporative resistance across the global land surface causes changes in the temperature variance that can be predicted from changes in the combined variance of shortwave radiation and latent heat flux. The variance of horizontal advection is important in altering the temperature variance in the Northern Hemisphere midlatitudes. Our findings shed light on predicting the characteristics of temperature variability as a function of surface conditions.

Accurate monthly evapotranspiration (ET) estimation is essential for many forest, climate, and hydrological applications, as well as for some agricultural uses. In this study, the relationship between ET and relative evapotranspiration (F) using land surface, and atmospheric variables was assessed with 17 FLUXNET sites data in savanna, cropland, and forest land covers, distributed all over the world. A sigmoid (Fs) and a logarithmic (Fl) F expression were included in Walker et al.’s (2019a,b) equations to evaluate their impact on the accuracy of ET estimations. The new parameterizations of ET outperformed the original expression, showing root mean square errors lower than 24% of the mean observed ET. The results presented here suggest that atmospheric parameters, coupled with land explanatory variables included in F estimates, produce more precise ET estimations. In addition, Soil Moisture Active Passive (SMAP) products were used to obtain global maps of ET and compared with Global Landsurface Evaporation Amsterdam Methodology (GLEAM) and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) MOD16 products, displaying the flexibility of these new parametrizations with different sources of data.

Abstract The numerical modeling of the land surface can make up for the insufficient station data in terms of number, dispersion, and temporal continuity. In this research, to evaluate the Noah-MP land surface model, the water balance components were estimated in the Neyshaboor watershed in the monthly time step during 2000–2009. Model input data were obtained from the global land data assimilation system version 1 (GLDAS-1), and the SWAT (soil and water assessment tool, a semi-distributed for small watershed to river basin-scale model) model output was used for the evaluation of the Noah-MP model. In this study, the ability of the Noah-MP model in simulating vegetation dynamically was studied. The precipitation was corrected before running the model for a more reliable evaluation. The time between 2000 and 2001 was considered a spin-up period and 2002–2009 for calibration and validation. The model has the best simulation in the mountainous areas; the runoff simulated by the Noah-MP model is in good agreement with the modeled runoff by SWAT in these areas. (R 2 = 0.78, NSE = 0.62, RMSE = 1.98 m3/s). The R2 for simulated soil moisture for soil layers (0–10, 10–40 cm) was 0.62 and 0.57, and RMSE was 0.059 (m3/m3) and 0.052 (m3/m3), respectively, in Motamedieh field. The annual amount of evapotranspiration estimated by the two models is comparable to the average annual evapotranspiration in the watershed (about 300 mm). Based on the results from the research, the model has well simulated: the runoff in the mountainous areas, the moisture in the upper layer of the soil, and the average annual evapotranspiration in the study area.

The optimization of irrigation in arboriculture holds crucial importance for effectively managing water resources in arid regions. This work introduces the development and implementation of an innovative solution named 'Soqia', a responsive WEB-GIS web application designed for real-time monitoring of the water status in arboriculture. This solution integrates meteorological data, remote sensing data, and ground sensor-collected data for precise irrigation management at the agricultural plot level. A range of features has been considered in the development of this WEB -GIS solution, ranging from visualizing vegetation indices to accessing current weather data, thereby contributing to more efficient irrigation management. Compared to other existing applications, 'Soqia' provides users with the current amount of water to irrigate, as well as an estimated amount for the next 8 days. Additionally, it offers spatio-temporal tracking of vegetation indices provided as maps and graphs. The importance of the Soqia solution at the national level is justified by the scarcity of water resources due to increasingly frequent and intense drought seasons for the past years. Low rainfall is recorded in all national agricultural areas. The implemented prototype is a first step toward the development of future innovative tools aimed at improving water management in regions facing water challenges. This prototype illustrates the potential of Web-GIS-based precision irrigation systems for the rational use of water in agriculture in general and arboriculture in particular. [ABSTRACT FROM AUTHOR]

The article investigates the effects of different cropping rotations on soil moisture and economic benefit. Cabbage–maize–cabbage (CMC), beans–maize–cabbage (BMC), and cabbage–cabbage–cabbage (CCC) treatments were set up to study the effects of different crop rotation combinations on soil water storage, evapotranspiration (ET), water use efficiency (WUE), and economic benefit. The results showed that the average soil moisture content decreased initially and then increased with crop rotation, whereas it continued to decrease with continuous cabbage cropping as the crop grew. CMC reduced ET, whereas BMC increased ET from the nodulation to maturation stages of cabbage compared with CCC in the third experimental year. WUE of different crops showed that cabbage > maize > beans. The economic benefit of the CMC was higher than the other treatments in the third planting year. Therefore, the best crop rotation combination in this area is cabbage–maize–cabbage. [ABSTRACT FROM AUTHOR]

Most Penman-Monteith-Leuning (PML) evapotranspiration (ET) modeling studies are dominated by consideration of meteorological, energy, and land use information, etc., but the dynamic coupling of soil moisture content (SM), especially in terms of improving accuracy through assimilation, lacks sufficient attention. This paper proposes a research framework for the dynamic coupling simulation of PML model and SM based on data assimilation, i.e., the remote sensing monitored SM is combined with soil evaporation of PML to obtain high-precision time-continuous SM data through data assimilation; simultaneously, dynamical soil evaporation coefficients are generated based on the assimilated SM to improve the simulation accuracy of the PML model. The new scheme was validated at a typical irrigation zone in north China and showed obvious improvements in both SM and ET simulations. Moreover, the effect of the assimilation of SM on the simulation accuracy of ET for different crop growth periods is further analyzed. This research provides a new idea for the coupling simulation of the SM and PML models. [ABSTRACT FROM AUTHOR]

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Permafrost thawing as a result of climate change has major consequences locally and globally for the biosphere as well as for human activities. The quantification of its extent and dynamics under different climate scenarios is needed to design local adaptation and mitigation measures and to better understand permafrost climate feedbacks. To this end, numerical simulation can be used to explore the response of soil thermo-hydric regimes to changes in climatic conditions. Mechanistic approaches minimize modelling assumptions by relying on the numerical resolution of continuum mechanics equations, but involve significant computational effort. In this work, the permaFoam solver is used along with high-performance computing resources to assess the impact of four climate scenarios of the Coupled Model Intercomparison Project - Phase 6 (CMIP6) on permafrost dynamics within a pristine, forest-dominated watershed in the continuous permafrost zone. Using these century time-scale simulations, changes in soil temperature, soil moisture, active layer thickness and water fluxes are quantified, assuming no change in vegetation cover. The most severe scenario (SSP5-8.5) suggests a dramatic increase in both active layer thickness and annual evapotranspiration, with maximum values on the watershed reached in 2100 of +46% and +29% respectively. For the active layer thickness, in current climatic conditions it would correspond to a 560 km southward shift. Moreover, in this scenario thermal equilibrium of near-surface permafrost with the new climatic conditions would not be reached in 2100, suggesting a further thawing of permafrost even in case of halting the climate change. [ABSTRACT FROM AUTHOR]

The land surface model (LSM) is extensively utilized to simulate terrestrial processes between land surface and atmosphere in the Earth system. Hydrology simulation is the key component of the model, which can directly reflect the capability of LSM. In this study, three offline LSM simulations were conducted over China using the Community Land Model version 5.0 (CLM5) driven by different meteorological forcing datasets, namely China Meteorological Forcing Dataset (CMFD), Global Soil Wetness Project Phase 3 (GSWP3), and bias-adjusted ERA5 reanalysis (WFDE5), respectively. Both gridded and in situ reference data, including evapotranspiration (ET), soil moisture (SM), and runoff, were employed to evaluate the performance levels of three CLM5-based simulations across China and its ten basins. In general, all simulations realistically replicate the magnitudes, spatial patterns, and seasonal cycles of ET over China when compared with remote-sensing-based ET observations. Among ten basins, Yellow River Basin (YRB) is the basin where simulations are the best, supported by the higher KGE value of 0.79. However, substantial biases occur in Northwest Rivers Basin (NWRB) with significant overestimation for CMFD and WFDE5 and underestimation for GSWP3. In addition, both grid-based or site-based evaluations of SM indicate that systematic wet biases exist in all three CLM5 simulations for shallower soil layer over nine basins of China. Comparatively, the performance levels in simulating SM for deeper soil layer are slightly better. Moreover, all three types of CLM5 simulate reasonable runoff spatial patterns, among which CMFD can capture more detailed information, but GSWP3 presents more comparable change trends of runoff when compared to the reference data. In summary, this study explored the capacity of CLM5 driven by different meteorological forcing data, and the assessment results may provide important insights for the future developments and applications of LSM. [ABSTRACT FROM AUTHOR]

Energy partitioning and evapotranspiration (ET) of alpine meadows in permafrost areas are crucial for water cycle on the Qinghai-Tibet Plateau. However, seasonal (freeze–thaw cycle) variations in energy partitioning and ET and their driving factors must be clarified. Therefore, 4-year energy fluxes [i.e. latent heat (LE) and sensible heat (H)] were observed, and bulk parameters [i.e. surface conductance, decoupling coefficient (Ω), and Priestley–Taylor coefficient (α)] were estimated in an alpine meadow in the Qinghai-Tibet Plateau. Mean daily LE (27.45 ± 23.89 W/m2) and H (32.51 ± 16.72 W/m2) accounted for 31.71% and 50.14% of available energy, respectively. More available energy was allocated to LE during the rainfall period, while 67.54 ± 28.44% was allocated to H during the frozen period. H was half the LE during rainfall period and seven times the LE during frozen period due to low soil water content and vegetation coverage during the frozen season. Mean annual ET was 347.34 ± 8.39 mm/year, close to mean annual precipitation. Low mean daily Ω (0.45 ± 0.23) and α (0.60 ± 0.29) throughout the year suggested that ET in the alpine meadow was limited by water availability. However, ET was constrained by available energy because of sufficient water supply from precipitation during rainfall season. In contrast, large differences between ET and precipitation indicated that soil water was supplied via lateral flow from melting upstream glaciers and snow during the transition season. The results suggest that seasonal variations in bulk parameters should be considered when simulating water and energy fluxes in permafrost regions. [ABSTRACT FROM AUTHOR]

The numerical modeling of the land surface can make up for the insufficient station data in terms of number, dispersion, and temporal continuity. In this research, to evaluate the Noah-MP land surface model, the water balance components were estimated in the Neyshaboor watershed in the monthly time step during 2000–2009. Model input data were obtained from the global land data assimilation system version 1 (GLDAS-1), and the SWAT (soil and water assessment tool, a semi-distributed for small watershed to river basin-scale model) model output was used for the evaluation of the Noah-MP model. In this study, the ability of the Noah-MP model in simulating vegetation dynamically was studied. The precipitation was corrected before running the model for a more reliable evaluation. The time between 2000 and 2001 was considered a spin-up period and 2002–2009 for calibration and validation. The model has the best simulation in the mountainous areas; the runoff simulated by the Noah-MP model is in good agreement with the modeled runoff by SWAT in these areas. (R2 = 0.78, NSE = 0.62, RMSE = 1.98 m3/s). The R2 for simulated soil moisture for soil layers (0–10, 10–40 cm) was 0.62 and 0.57, and RMSE was 0.059 (m3/m3) and 0.052 (m3/m3), respectively, in Motamedieh field. The annual amount of evapotranspiration estimated by the two models is comparable to the average annual evapotranspiration in the watershed (about 300 mm). Based on the results from the research, the model has well simulated: the runoff in the mountainous areas, the moisture in the upper layer of the soil, and the average annual evapotranspiration in the study area. [ABSTRACT FROM AUTHOR]

Water resource modeling is an important means of studying the distribution, change, utilization, and management of water resources. By establishing various models, water resources can be quantitatively described and predicted, providing a scientific basis for water resource management, protection, and planning. Traditional hydrological observation methods, often reliant on experience and statistical methods, are time-consuming and labor-intensive, frequently resulting in predictions of limited accuracy. However, machine learning technologies enhance the efficiency and sustainability of water resource modeling by analyzing extensive hydrogeological data, thereby improving predictions and optimizing water resource utilization and allocation. This review investigates the application of machine learning for predicting various aspects, including precipitation, flood, runoff, soil moisture, evapotranspiration, groundwater level, and water quality. It provides a detailed summary of various algorithms, examines their technical strengths and weaknesses, and discusses their potential applications in water resource modeling. Finally, this paper anticipates future development trends in the application of machine learning to water resource modeling. [ABSTRACT FROM AUTHOR]

Enhancing our understanding of the intricate interplay among hydro‐climatic processes is crucial for a comprehensive assessment of water availability and climate extremes across global land regions. Here, we propose an integrated framework to investigate networks of the global fields of multiple hydrological variables (Precipitation, Evapotranspiration, Soil Moisture). We apply a two‐layer complex network concept to formulate the independent networks of each hydrological variable and their interactions. Intra‐ (Single‐layer) and cross‐ (two‐layer) network coefficients are derived from the formulated hydrological network to quantify the linkage, spatial connection density, and scale for the independent hydrological fields (or variables) and their interactions. The joint distribution of the intra‐network coefficients reveals multiple spatial scales of connectivity for a moderately well‐connected location in case of evapotranspiration and soil moisture. With increasing global mean temperature, spatially synchronized evapotranspiration over such a large scale may lead to multi‐continental droughts and heatwaves. Furthermore, the (cross‐) network coefficients have identified regions acting as "bottlenecks" for moisture flow and the water‐dominated areas with less evaporative actions. The contrasting features of two‐layer network coefficients have provided a qualitative picture of moisture circulation and recirculation over many hydrological hotspot regions, such as the Amazonian basin, Indian subcontinents, and the Sahel region. The derived results can be employed to gain insights into the global water cycle's multiple interacting processes (e.g., land‐atmosphere interactions). Key Points: The bottleneck regions of the precipitation network act like conduits for moisture flowDrought and heatwaves can coevolve on multiple continents through spatially synchronized evapotranspiration and dryingTransitional areas are important hydrologically interactive regions affirming the influence of soil moisture on distant precipitation events [ABSTRACT FROM AUTHOR]

Monitoring agricultural drought across a large area is challenging, especially in regions with limited data availability, like the Peshawar Valley, which holds great agricultural significance in Pakistan. Although remote sensing provides biophysical variables such as precipitation (P), land surface temperature (LST), normalized difference vegetation index (NDVI), and relative soil moisture (RSM) to assess drought conditions at various spatiotemporal scales, these variables have limited capacity to capture the complex nature of agricultural drought and associated crop responses. Here, we developed a composite drought index named "Temperature Vegetation ET Dryness Index" (TVEDI) by modifying the Temperature Vegetation Precipitation Dryness Index (TVPDI) and integrating NDVI, LST, and remotely sensed evapotranspiration (ET) using 3D space and Euclidean distance. Several statistical techniques were employed to examine TVPDI and TVEDI trends and relationships with other commonly used drought indices such as the standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI), and standardized soil moisture index (SSI), as well as crop yield, to better understand how these indices captured the spatial and temporal distribution of agricultural drought in the Peshawar valley between 1986 and 2018. Results indicated that while the temporal patterns of the 3-month SPI, SPEI, and SSI generally align with those of TVEDI and TVPDI, TVEDI was more strongly correlated with these indices (e.g., correlation coefficient, r = 0.78–0.84 from TVEDI and r = 0.73–0.79 from TVPDI). Moreover, the crop yield, a measure of crop response to agricultural drought, demonstrated a significant positive correlation with TVEDI (r = 0.60–0.80), much higher than its correlation with TVPDI (r = 0.30–0.48). These outcomes indicate that the inclusion of ET in TVEDI effectively captured changes in soil moisture, crop water status, and their impact on crop yield. Overall, TVEDI exhibited enhanced capability to identify drought impacts compared to TVPDI, showing its potential for characterizing agricultural drought in regions with limited data availability. [ABSTRACT FROM AUTHOR]

In forest ecosystems, transpiration (T) patterns are important for quantifying water and carbon fluxes and are major factors in predicting ecosystem change. Seasonal changes in rainfall and soil water content can alter the sensitivity of sap flux density to daily variations in vapor pressure deficit (VPD). This sensitivity is species-specific and is thought to be related to hydraulic strategies. The aim of this work is to better understand how the sap flux density of species with low versus high wood density differ in their sensitivity to VPD and soil water content and how potentially opposing water-use strategies influence T dynamics, and ultimately, correlations to evapotranspiration (ET). We use hysteresis area analysis to quantify the sensitivity of species-specific sap flux density to changes in the VPD, breakpoint-based models to determine the soil water content threshold instigating a T response and multiscalar wavelet coherency to correlate T to ET. We found that low wood density Commiphora leptophloeos (Mart.) Gillett had a more dynamic T pattern, a greater sensitivity to VPD at high soil water content, required a higher soil water content threshold for this sensitivity to be apparent, and had a significant coherency correlation with ET at daily to monthly timescales. This behavior is consistent with a drought avoidance strategy. High wood density Cenostigma pyramidale   (Tul.)   E. Gagnon & G. P. Lewis , conversely, had a more stable T pattern, responded to VPD across a range of soil water content, tolerated a lower soil water content threshold to T, and had a significant coherency correlation with ET at weekly timescales. This behavior is consistent with a drought-tolerant strategy. We build on previous research to show that these species have contrasting water-use strategies that should be considered in large-scale modeling efforts. [ABSTRACT FROM AUTHOR]

Due to recent advances in the development of land data assimilation systems (LDAS) and the availability of high-quality, satellite-based surface soil moisture (SSM) retrieval products, we now have unambiguous evidence that the assimilation of SSM retrievals, or their proxy, can improve the precision (i.e., correlation versus truth) of surface state estimates provided by a land surface model (LSM). However, this clarity does not yet extend to the estimation of LSM surface water fluxes that are key to hydrologic and numerical weather forecasting applications. Here, we hypothesize that a key obstacle to extrapolating realized improvements in water state precision into comparable improvements in water flux accuracy (i.e., mean absolute error) is the presence of water state–water flux coupling strength biases existing in LSMs. To test this hypothesis, we conduct a series of synthetic fraternal twin data assimilation experiments where realistic levels of state–flux coupling strength bias—involving both evapotranspiration and runoff—are systematically introduced into an assimilation LSM. Results show that the accuracy of the resulting water flux analysis is sharply reduced by the presence of such bias, even in cases where the precision of soil moisture state estimates (e.g., SSM) is improved. The rescaling of SSM observations prior to their assimilation (i.e., the most common approach for addressing systematic differences between LSMs and assimilated observations) is not always a robust strategy for addressing these errors and can, in certain circumstances, degrade water flux accuracy. Overall, results underscore the critical need to assess, and correct for, LSM water state–water flux coupling strength biases during the operation of an LDAS. Significance Statement: Land data assimilation is the process by which land surface model estimates of water states (e.g., soil moisture) and water fluxes (e.g., runoff and evapotranspiration) are improved via the incorporation of observations. Over the past decade, substantial improvements have been made in the precision of land surface model states via the assimilation of satellite-based soil moisture information. However, to date, these improvements have not yet been extended into water flux estimates like runoff and evapotranspiration. This is a critical shortcoming since advances in important weather and hydrologic forecasting applications are dependent on the improved estimation of such fluxes. We demonstrate that this shortcoming is linked to the inability of existing land surface models to accurately describe the impact of variations in water states on water fluxes and propose strategies for overcoming this issue in future land data assimilation systems. [ABSTRACT FROM AUTHOR]

In Romania, evapotranspiration at bare soil or covered by crops is monitored within the experimental evapotranspiration stations: Căldărușani, Voinești and Poiana Brașov. Many experimental researches are carried out, in order to analysed the variation of crop evapotranspiration, in relation to the climatic parameters and soil moisture. The experiments carried out in recent years, have shown that starting from 2021 until 2023, at the level of G1 lysimeters, no more infiltrated water quantities were recorded, so all the amount of water was evaporated. It was also observed that in the year 2022 the sunflower and maize crops did not reach the stage of maturity. In 2023, an experiment was carried out that aimed to compare the maize evapotranspiration in a natural regime and exposed to additional watering (Căldărușani station). The water addition rate was established based on specialized literature and by applying CropWat model. Additional waterings generated different evapotranspiration values. The waterings changed the values of soil moisture and helped the plant not to reach the wilting point before ripening. [ABSTRACT FROM AUTHOR]

Hydrogeophysical methods have been increasingly used to study subsurface soil–water dynamics, yet their application beyond the soil compartment or the quantitative link to soil hydraulic properties remains limited. To examine how these methods can inform model‐based evapotranspiration (ET) calculation under varying soil water conditions, we conducted a pilot‐scale field study at an experimental maize plot with manipulated irrigation treatments. Our goal was to develop a workflow for (1) acquiring and inverting field electrical resistivity tomography (ERT) data, (2) correlating ERT to soil hydraulic properties, (3) spatially characterizing soil water stress that feeds into ET modeling (the FAO‐56 model), and (4) evaluating the performance of ERT‐based ET computation. Our results showed that ERT was able to capture decimeter‐scale soil water content (SWC) dynamics from root water uptake and irrigation manipulation and the contrast of soil water stress between deficiently and fully irrigated maize. We also demonstrated the flexibility of using ERT to spatially integrate soil water stress in the soil volume of interest, which could be adjusted based on different crops and plot layouts. The integration of the ERT datasets into ET modeling provided insights into the spatial heterogeneity of the subsurface that has been challenging for point‐based sensing, which can further our understanding of the hydraulic dynamics in the soil‐plant‐atmosphere continuum. Core Ideas: Electrical resistivity tomography (ERT) captured soil water dynamics induced by root water uptake and irrigation manipulation.ERT enabled spatial analysis and quantification of soil water stress, a key input to the evapotranspiration (ET) model.A workflow from field ERT data acquisition to ET computation was demonstrated. [ABSTRACT FROM AUTHOR]

Cosmic‐ray neutron sensors (CRNS) fill the gap between locally measured in‐situ soil moisture (SM) and remotely sensed SM by providing accurate SM estimation at the field scale. This is promising for improving hydrologic model predictions, as CRNS can provide valuable information on SM in the root zone at the typical scale of a model grid cell. In this study, SM measurements from a network of 12 CRNS in the Rur catchment (Germany) were assimilated into the Terrestrial System Modeling Platform (TSMP) to investigate its potential for improving SM, evapotranspiration (ET) and river discharge characterization and estimating soil hydraulic parameters at the larger catchment scale. The data assimilation (DA) experiments (with and without parameter estimation) were conducted in both a wet year (2016) and a dry year (2018) with the ensemble Kalman filter (EnKF), and later verified with an independent year (2017) without DA. The results show that SM characterization was significantly improved at measurement locations (with up to 60% root mean square error (RMSE) reduction), and that joint state‐parameter estimation improved SM simulation more than state estimation alone (more than 15% additional RMSE reduction). Jackknife experiments showed that SM at verification locations had lower and different improvements in the wet and dry years (an RMSE reduction of 40% in 2016 and 16% in 2018). In addition, SM assimilation was found to improve ET characterization to a much lesser extent, with a 15% RMSE reduction of monthly ET in the wet year and 9% in the dry year. Key Points: Assimilation of soil moisture from a network of cosmic‐ray neutron sensors improves soil moisture characterization at the catchment scaleSoil moisture characterization improved more in a wet year than in a very dry yearEvapotranspiration and river discharge simulation are only slightly improved, despite better estimations of soil moisture [ABSTRACT FROM AUTHOR]

Abstract Satellite observations have shown widespread greening during the last few decades over the northern permafrost region, but the impact of vegetation greening on permafrost thermal dynamics remains poorly understood, hindering the understanding of permafrost‐vegetation‐climate feedbacks. Summer surface offset (SSO), defined as the difference between surface soil temperature and near‐surface air temperature in summer (June‐August), is often predicted as a function of surface thermal characteristics for permafrost modeling. Here we examined the impact of leaf area index (LAI), detected by satellite as a proxy to permafrost vegetation dynamics, on SSO variations from 2003 to 2021 across the northern permafrost region. We observed latitude‐ and biome‐dependent patterns of SSO changes, with a pronounced increase in Siberian shrublands and a decrease in Tibetan grasslands. Based on partial correlation and sensitivity analyses, we found a strong LAI signal (∼30% of climatic signal) on SSO with varying elevation‐ and canopy height‐dependent patterns. Positive correlations or sensitivities, that is, increases in LAI lead to higher SSO, were distributed in relatively cold and wet areas. Biophysical effects of permafrost greening on surface albedo, evapotranspiration, and soil moisture (SM) could link the connection between LAI and SSO. Increased LAI substantially reduced surface albedo and enhanced evapotranspiration, influenced energy redistribution, and further controlled interannual variability of SSO. We also found contrasting effects of LAI on surface SM, consequently leading to divergent impacts on SSO. The results offer a fresh perspective on how greening affects the thermal balance and dynamics of permafrost, which is enlightening for improved permafrost projections.

Abstract Addressing impacts of flash droughts (FDs) on the water‐food nexus requires a understanding of FD mechanisms and drivers at the watershed level. Examining climatic drivers, dry and wet spell lengths from 1980 to 2019, we analyzed FD spatial and temporal characteristics, emphasizing areal extent, onset time, and duration. Our findings reveal substantial variations in FDs among different watersheds. Notably, watersheds in the Southern Hemisphere are witnessing expanding, faster‐developing, and longer‐lasting FDs, aligning with climate variations in precipitation and temperature. Additionally, at the watershed scale, the onset and duration of FDs are more influenced by the intensity (magnitude and variability) of climatic drivers than the average length of wet and dry periods. FD‐extents, however, correlate with both climatic conditions and wet and dry periods, underscoring watershed connectivity. Ultimately, our results underscore the necessity for research to comprehend the interplay between FDs and watershed characteristics and how it manifests in overall water resource management.

Abstract Changes are projected for the boreal biome with complex and variable effects on forest vegetation including drought‐induced tree mortality and forest loss. With soil and atmospheric conditions governing drought intensity, specific drivers of trees water stress can be difficult to disentangle across temporal scales. We used wavelet analysis and causality detection to identify potential environmental controls (evapotranspiration, soil moisture, rainfall, vapor pressure deficit, air temperature and photosynthetically active radiation) on daily tree water deficit and on longer periods of tree dehydration in black spruce and tamarack. Daily tree water deficit was controlled by photosynthetically active radiation, vapor pressure deficit, and air temperature, causing greater stand evapotranspiration. Prolonged periods of tree water deficit (multi‐day) were regulated by photosynthetically active radiation and soil moisture. We provide empirical evidence that continued warming and drying will cause short‐term increases in black spruce and tamarack transpiration, but greater drought stress with reduced soil water availability.