Integration of dynaMic water extents towards imProved lake wAter suRface Temperature (IMPART).

Lake water surface temperature (LWST) is a critical component in understanding the response of freshwater ecosystems to climate change. Traditional estimation of LWST estimation considers water surface bodies to be static. Our work proposes a novel open-source web application, IMPART, designed for estimating dynamic LWST using Landsat reflectance and MODIS temperature datasets from 2004 to 2022. Results presented globally for over 342 lakes reveal a root mean square deviation of 0.86 °C between static and dynamic LWST. Additionally, our results demonstrate that 57% of the lakes exhibit a statistically significant difference between the static and dynamic LWST values. Improved LWST will ultimately enhance our ability to comprehensively monitor and respond to the impacts of climate change on freshwater ecosystems worldwide. Furthermore, based on the Koppen-Geiger climate classification, our zonal analysis demonstrates the deviation between static and dynamic LWST. It identifies specific zones where considering waterbodies as dynamic entities is essential.

Dynamics of confined water inside carbon nanotubes based on studying tetrahedral order parameters.

Water dynamics inside hydrophobic confinement, such as carbon nanotubes (CNTs), has garnered significant attention, focusing on water diffusion. However, a crucial aspect remains unexplored - the influence of confinement size on water ordering and intrinsic hydrogen bond dynamics. To address this gap, we conducted extensive molecular dynamics simulations to investigate local ordering and intrinsic hydrogen bond dynamics of water molecules within CNTs of various sizes (length:20 nm, diameters: 1.0 nm to 5.0 nm) over a wide range of temperatures (260K, 280K, 300K, and 320K). A striking observation emerged: in smaller CNTs, water molecules adopt an icy structure near tube walls while maintaining liquid state towards the center. Notably, water behavior within a 2.0 nm CNT stands out as an anomaly, distinct from other CNT sizes considered in this study. This anomaly was explained through the formation of water layers inside CNTs. The hydrogen bond correlation function of water within CNTs decayed more slowly than bulk water, with an increasing rate as CNT diameter increased. In smaller CNTs, water molecules hold onto their hydrogen bond longer than larger ones. Interestingly, in larger CNTs, the innermost layer's hydrogen bond lasts a shorter time compared to the other layers, and this changes with temperature.

Exploring the Water-Soil-Crop Dynamic Process and Water Use Efficiency of Typical Irrigation Units in the Agro-Pastoral Ecotone of Northern China.

Groundwater resources serve as the primary source of water in the agro-pastoral ecotone of northern China, where scarcity of water resources constrains the development of agriculture and animal husbandry. As a typical rainfed agricultural area, the agro-pastoral ecotone in Inner Mongolia is entirely dependent on groundwater for agricultural irrigation. Due to the substantial groundwater consumption of irrigated farmland, groundwater levels have been progressively declining. To obtain a sustainable irrigation pattern that significantly conserves water, this study faces the challenge of unclear water transport relationships among water, soil, and crops, undefined water cycle mechanism in typical irrigation units, and water use efficiency, which was not assessed. Therefore, this paper, based on in situ experimental observations and daily meteorological data in 2022-2023, utilized the DSSAT model to explore the growth processes of potato, oat, alfalfa, and sunflower, the soil water dynamics, the water balance, and water use efficiency, analyzed over a typical irrigation area. The results indicated that the simulation accuracy of the DSSAT model was ARE < 10%, nRMSE/% < 10%, and R2 ≥ 0.85. The consumption of the soil moisture during the rapid growth stage for the potatoes, oats, alfalfa, and sunflower was 7-13% more than that during the other periods, and the yield was 67,170, 3345, 6529, and 4020 kg/ha, respectively. The soil evaporation of oat, potato, alfalfa, and sunflower accounted for 18-22%, 78-82%; 57-68%, and 32-43%, and transpiration accounted for 40-44%, 56-60%, 45-47%, and 53-55% of ETa (333.8 mm-369.2 mm, 375.2 mm-414.2 mm, 415.7 mm-453.7 mm, and 355.0 mm-385.6 mm), respectively. It was advised that irrigation water could be appropriately reduced to decrease ineffective water consumption. The water use efficiency and irrigation water use efficiency for potatoes was at the maximum amount, ranging from 16.22 to 16.62 kg/m3 and 8.61 to 10.81 kg/m3, respectively, followed by alfalfa, sunflowers, and oats. For the perspective of water productivity, it was recommended that potatoes could be extensively cultivated, alfalfa planted appropriately, and oats and sunflowers planted less. The findings of this study provided a theoretical basis for efficient water resource use in the agro-pastoral ecotone of Northern China.

Impact of changing climate on bryophyte contributions to terrestrial water, carbon, and nitrogen cycles.

Bryophytes, including the lineages of mosses, liverworts, and hornworts, are the second-largest photoautotroph group on Earth. Recent work across terrestrial ecosystems has highlighted how bryophytes retain and control water, fix substantial amounts of carbon (C), and contribute to nitrogen (N) cycles in forests (boreal, temperate, and tropical), tundra, peatlands, grasslands, and deserts. Understanding how changing climate affects bryophyte contributions to global cycles in different ecosystems is of primary importance. However, because of their small physical size, bryophytes have been largely ignored in research on water, C, and N cycles at global scales. Here, we review the literature on how bryophytes influence global biogeochemical cycles, and we highlight that while some aspects of global change represent critical tipping points for survival, bryophytes may also buffer many ecosystems from change due to their capacity for water, C, and N uptake and storage. However, as the thresholds of resistance of bryophytes to temperature and precipitation regime changes are mostly unknown, it is challenging to predict how long this buffering capacity will remain functional. Furthermore, as ecosystems shift their global distribution in response to changing climate, the size of different bryophyte-influenced biomes will change, resulting in shifts in the magnitude of bryophyte impacts on global ecosystem functions.

Soil water dynamics and deep percolation in an agricultural experimental area of the North China Plain over the past 50 years: Based on field monitoring and numerical modeling.

The unregulated irrigation systems used in the late 20th century have led to increasingly severe deep percolation (DP) in the agricultural irrigation areas of the North China Plain. This has become an important factor limiting the efficient utilization of water resources and sustainable environmental development in these irrigation areas. However, the thick vadose zone is hydrodynamically exceptionally complex. The soil hydrological cycle is constantly changing under the influence of major climate change and human activity, thereby causing changes in DP that are difficult to quantify accurately. Here, the Luancheng Agricultural Irrigation District in North China was selected for a continuous 20-year in situ experiment. Soil-water dynamics were monitored using neutron probes and tensiometers, to determine the complete annual soil-water cycle and the hydrodynamic properties of the thick vadose zone irrigation district. For 1971-2021, DP was simulated using the HYDRUS-1D model and was verified by fitting observed values. Soil water content (SWC) exhibited similar trends in years that differed in terms of the amounts of irrigation and precipitation. The 0-100 cm soil layer was significantly affected by precipitation and other factors, and recharge >60 mm/d caused percolation. DP occurred mostly after irrigation or during the period of intensive precipitation in July-October. The maximum percolation rate was 16.9 mm/d under the present irrigation method. The main factors leading to DP were soil water storage capacity (R2 = 0.86) and precipitation (R2 = 0.54). Under the evolution of irrigation measures in the last 50 years, the average DP has gradually decreased from 574.2 mm (1971-1990) to 435.5 mm (2005-2021). However, a substantial amount of precipitation and irrigation water infiltrated the soil and percolated into the deep soil layer without being utilized by the crop. Therefore, there is an urgent need to consider measures to reduce DP to improve water-use efficiency in agriculture.

Improving on mapping long-term surface water with a novel framework based on the Landsat imagery series.

Surface water plays a crucial role in the ecological environment and societal development. Remote sensing detection serves as a significant approach to understand the temporal and spatial change in surface water series (SWS) and to directly construct long-term SWS. Limited by various factors such as cloud, cloud shadow, and problematic satellite sensor monitoring, the existent surface water mapping datasets might be short and incomplete due to losing raw information on certain dates. Improved algorithms are desired to increase the completeness and quality of SWS datasets. The present study proposes an automated framework to detect SWS, based on the Google Earth Engine and Landsat satellite imagery. This framework incorporates implementing a raw image filtering algorithm to increase available images, thereby expanding the completeness. It improves OTSU thresholding by replacing anomaly thresholds with the median value, thus enhancing the accuracy of SWS datasets. Gaps caused by Landsat7 ETM + SLC-off are respired with the random forest algorithm and morphological operations. The results show that this novel framework effectively expands the long-term series of SWS for three surface water bodies with distinct geomorphological patterns. The evaluation of confusion matrices suggests the good performance of extracting surface water, with the overall accuracy ranging from 0.96 to 0.97, and user's accuracy between 0.96 and 0.98, producer's accuracy ranging from 0.83 to 0.89, and Matthews correlation coefficient ranging from 0.87 to 0.9 for several spectral water indices (NDWI, MNDWI, ANNDWI, and AWEI). Compared with the Global Reservoirs Surface Area Dynamics (GRSAD) dataset, our constructed datasets promote greater completeness of SWS datasets by 27.01%-91.89% for the selected water bodies. The proposed framework for detecting SWS shows good potential in enlarging and completing long-term global-scale SWS datasets, capable of supporting assessments of surface-water-related environmental management and disaster prevention.

Combining PSII photochemistry and hydraulics improves predictions of photosynthesis and water use from mild to lethal drought.

Rising temperatures and increases in drought negatively impact the efficiency and sustainability of both agricultural and forest ecosystems. Although hydraulic limitations on photosynthesis have been extensively studied, a solid understanding of the links between whole plant hydraulics and photosynthetic processes at the cellular level under changing environmental conditions is still missing, hampering our predictive power for plant mortality. Here, we examined plant hydraulic traits and CO2 assimilation rate under progressive water limitation by implementing Photosystem II (PSII) dynamics with a whole plant process model (TREES). The photosynthetic responses to plant water status were parameterized based on measurements of chlorophyll a fluorescence, gas exchange and water potential for Brassica rapa (R500) grown in a greenhouse under fully watered to lethal drought conditions. The updated model significantly improved predictions of photosynthesis, stomatal conductance and leaf water potential. TREES with PSII knowledge predicted a larger hydraulic safety margin and a decrease in percent loss of conductivity. TREES predicted a slower decrease in leaf water potential, which agreed with measurements. Our results highlight the pressing need for incorporating PSII drought photochemistry into current process models to capture cross-scale plant water dynamics from cell to whole plant level.

Nanoconfined Water in Pillared Zeolites Probed by 1H Nuclear Magnetic Resonance.

Here, we report the results of our 1H nuclear magnetic resonance study of the dynamics of water molecules confined in zeolites (mordenite and ZSM-5 structures) with hierarchical porosity (micropores in zeolite lamella and mesopores formed by amorphous SiO2 in the inter-lamellar space). 1H nuclear magnetic resonance (NMR) spectra show that water experiences complex behavior within the temperature range from 173 to 298 K. The temperature dependence of 1H spin-lattice relaxation evidences the presence of three processes with different activation energies: freezing (about 30 kJ/mol), fast rotation (about 10 kJ/mol), and translational motion of water molecules (23.6 and 26.0 kJ/mol for pillared mordenite and ZSM-5, respectively). For translational motion, the activation energy is markedly lower than for water in mesoporous silica or zeolites with similar mesopore size but with disordered secondary porosity. This indicates that the process of water diffusion in zeolites with hierarchical porosity is governed not only by the presence of mesopores, but also by the mutual arrangement of meso- and micropores. The translational motion of water molecules is determined mainly by zeolite micropores.

Soil water repellency in the Brazilian neotropical savanna: first detection, seasonal effect, and influence on infiltrability.

Soil water repellency (SWR) has been detected worldwide in various biomes and climates. However, this phenomenon has not been shown yet in the Brazilian neotropical savanna. The present study addressed the following questions: (a) Does SWR occur in the Brazilian neotropical savanna? If so, (b) does it exhibit seasonality? (c) Does it influence infiltration? To do that, we selected two similar study areas covered by similar soils (oxisol) and vegetation (netropical savanna). We performed water repellency and infiltration tests in both areas during the transition from dry to wet season. Our results indicate that SWR occurs in soils of the Brazilian neotropical savanna only during the dry season and influence water infiltration in the dry season. The likely cause of SWR might be related to the chemical composition of soil organic matter since neotropical savanna plants produce hydrophobic substances as a survival strategy, especially during the dry season.

Toward Optimal Irrigation Management at the Plot Level: Evaluation of Commercial Water Potential Sensors.

Proper irrigation practice consists of applying the optimum amount of water to the soil at the right time. The porous characteristics of the soil determine the capacity of the soil to absorb, infiltrate, and store water. In irrigation, it is not sufficient to only determine the water content of the soil; it is also necessary to determine the availability of water for plants: water potential. In this paper, a comprehensive laboratory evaluation-accuracy and variability-of the world's leading commercial water potential sensors is carried out. No such comprehensive and exhaustive comparative evaluation of these devices has been carried out to date. Ten pairs of representative commercial sensors from four different families were selected according to their principle of operation (tensiometers, capacitive sensors, heat dissipation sensors, and resistance blocks). The accuracy of the readings (0 kPa-200 kPa) was determined in two soils of contrasting textures. The variability in the recordings-repeatability and reproducibility-was carried out in a homogeneous and inert material (sand) in the same suction range. The response in terms of accuracy and value dispersion of the different sensor families was different according to the suction range considered. In the suction range of agronomic interest (0-100 kPa), the heat dissipation sensor and the capacitive sensors were the most accurate. In both families, registrations could be extended up to 150-200 kPa. The scatter in the readings across the different sensors was due to approximately 80% of the repeatability or intrinsic variability in the sensor unit and 20% of the reproducibility. Some sensors would significantly improve their performance with ad hoc calibrations.

Understanding the intricacy of protein in hydrated deep eutectic solvent: Solvation dynamics, conformational fluctuation dynamics, and stability.

Deep eutectic solvents (DESs) are potential biocatalytic media due to their easy preparation, fine-tuneability, biocompatibility, and most importantly, due to their ability to keep protein stable and active. However, there are many unanswered questions and gaps in our knowledge about how proteins behave in these alternate media. Herein, we investigated solvation dynamics, conformational fluctuation dynamics, and stability of human serum albumin (HSA) in 0.5 Acetamide/0.3 Urea/0.2 Sorbitol (0.5Ac/0.3Ur/0.2Sor) DES of varying concentrations to understand the intricacy of protein behaviour in DES. Our result revealed a gradual decrease in the side-chain flexibility and thermal stability of HSA beyond 30 % DES. On the other hand, the associated water dynamics around domain-I of HSA decelerate only marginally with increasing DES content, although viscosity rises considerably. We propose that even though macroscopic solvent properties are altered, a protein feels only an aqueous type of environment in the presence of DES. This is probably the first experimental study to delineate the role of the associated water structure of the enzyme for maintaining its stability inside DES. Although considerable effort is necessary to generalize such claims, it might serve as the basis for understanding why proteins remain stable and active in DES.

Design of Superhydrophobic Shape Memory Composites with Kirigami Structures and Uniform Wetting Property.

With the continuous increase in human demand to improve aircraft performance, intelligent aircraft technologies have become a popular research field in recent years. Among them, the deformable skin structure has become one of the key technologies to achieve excellent and reliable performance. However, during the service, deformable skin structures may encounter problems such as surface impact and adhesion of droplets in rainy weather or surface icing in low-temperature environments, which can seriously affect the flight safety of the aircraft. One way to overcome these issues is to use superhydrophobic shape memory materials in the structure. In this regard, first, shape memory composites were prepared with shape memory epoxy resin as the matrix and carbon fiber orthogonal woven fabric as the reinforcement material. Superhydrophobic shape memory composites (SSMCs) were then obtained by casting the kirigami composite with superhydrophobic carbon nanotube-polydimethylsiloxane (CNT@PDMS) mixture, and the surface was processed by laser micromachining. Shape memory performance and surface wetting performance were determined by material testing methods. The results showed that the shape memory recovery rate can reach 85.11%, the surface is superhydrophobic, the average water contact angle is 156.9 ± 4.4°, and the average rolling angle is 3 ± 0.5°. The three-point bending test of the specimens with different kirigami cell configurations showed that the shape memory composite based on the rectangular structure has the best deformability with an aspect ratio of 0.4. From the droplet impact test, it was found that the impact speed of water droplets and the curvature of the surface can greatly affect the dynamic performance of water. This work is expected to be of significant research value and importance for developing functional deformable skin materials.

Glass transition phenomena and dielectric relaxations in supercooled d-lyxose aqueous solutions.

Differential scanning calorimeter and broadband dielectric spectroscopy in a broad range of temperatures (150-300 K) were employed to study the d-lyxose aqueous mixture at different hydration levels. Two relaxation processes were observed in all investigated d-lyxose aqueous mixtures. A relaxation process (process-I) usually known as the primary relaxation mode which is accountable for the collective motion of d-lyxose aqueous solution, was observed above the glass transition temperature (Tg). Below Tg, another process designated as process-II was found which is mainly related to the water molecule relaxation inside the d-lyxose matrix. The average relaxation times as a function of temperature and dielectric strengths of both observed relaxation processes (I & II) were analyzed for all hydration levels in d-lyxose. It was identified that the relaxation amplitude of process-II in the d-lyxose aqueous mixture was increased drastically and their activation energies were found to be approximately independent of the content of water above critical concentration, xc = 0.28. This suggests that the dynamical process observed above xc was dominated by the presence of water clusters. In the current aqueous mixture, the critical content of water (xc) is slightly higher as compared to previously reported aqueous mixtures, indicating a more cooperative nature of water molecules with a d-lyxose matrix. Additionally, the Tg of pure water was estimated at 128 ± 5.8 K from the extrapolation of DSC Tg data of the d-lyxose aqueous solution by using the well-known Gordon-Taylor equation. Our current result gives further support to the well-accepted glass transition (Tg) of pure water.

Voltage-Mediated Water Dynamics Enables On-Demand Transport of Sugar Molecules in Two-Dimensional Channels.

The constructing of artificial channels with gating functions is an important undertaking for gaining insight into biological process and achieving efficient bionic functions. Typically, controllable transport within such channels relies on either electrostatic or specific interactions between the transporting species and the channel. However, for molecules with weak interactions with the channel, achieving precise gating of the transport remains a significant challenge. In this regard, this study proposes a voltage gating membrane of two-dimensional channels that selectively transport of neutral molecules glucose with a dimension of 0.60 nm. The permeation of glucose is switched on/off by electrochemically manipulating the water dynamics in the nanochannel. Voltage driven-intercalation of ion into the two-dimensional channel causes water to stratify and move closer to the channel walls, thereby resulting in the channel center being emptier for glucose diffusion. Due to the sub-nanometer size dimension of the channel, selective permeation of glucose over sucrose is also achieved in this approach.

Advanced insight on the water dynamics of anisotropic hydrogels by field-cycling nuclear magnetic resonance: Application of 3-Tau model.

Fast field cycling (FFC) nuclear magnetic resonance (NMR) relaxometry is used to investigate an anisotropic polygalacturonate hydrogel formed by the diffusion of calcium ions from an external reservoir (external gelation). Such a hydrogel has a gradient of polymer density accompanied by a gradient of the mesh size of its 3D network. The NMR relaxation process is dominated by the interaction of proton spins between water molecules located at polymer interfaces and in nanoporous spaces. The FFC NMR experiment provides the spin-lattice relaxation rate R1ω as a function of Larmor frequency ω producing dispersion (NMRD) curves that are highly sensitive to the dynamics of the protons at the surfaces. The hydrogel is sliced into three parts and the NMR profile for each hydrogel slice is measured. The NMRD data for each slice is interpreted using the 3-Tau Model with the aid of user-friendly fitting software called 3TM. The key fit parameters include three nano-dynamical time constants and the average "mesh size" which collectively determine the bulk water and water surface layer contribution to the total relaxation rate. The results are consistent with independent studies where comparison is possible.

Differences in Water Dynamics between the Hydrated Chitin and Hydrated Chitosan Determined by Quasi-Elastic Neutron Scattering.

Recently, it was reported that chitin and chitosan exhibited high-proton conductivity and function as an electrolyte in fuel cells. In particular, it is noteworthy that proton conductivity in the hydrated chitin becomes 30 times higher than that in the hydrated chitosan. Since higher proton conductivity is necessary for the fuel cell electrolyte, it is significantly important to clarify the key factor for the realization of higher proton conduction from a microscopic viewpoint for the future development of fuel cells. Therefore, we have measured proton dynamics in the hydrated chitin using quasi-elastic neutron scattering (QENS) from the microscopic viewpoint and compared the proton conduction mechanism between hydrated chitin and chitosan. QENS results exhibited that a part of hydrogen atoms and hydration water in chitin are mobile even at 238 K, and the mobile hydrogen atoms and their diffusion increase with increasing temperature. It was found that the diffusion constant of mobile protons is two times larger and that the residence time is two times faster in chitin than that in chitosan. In addition, it is revealed from the experimental results that the transition process of dissociable hydrogen atoms between chitin and chitosan is different. To realize proton conduction in the hydrated chitosan, the hydrogen atoms of the hydronium ions (H3O+) should be transferred to another hydration water. By contrast, in hydrated chitin, the hydrogen atoms can transfer directly to the proton acceptors of neighboring chitin. It is deduced that higher proton conductivity in the hydrated chitin compared with that in the hydrated chitosan is yielded by the difference of diffusion constant and the residence time by hydrogen-atom dynamics and the location and number of proton acceptors.

Effect of osmolytes on the EcoRI endonuclease: Insights into hydration and protein dynamics from molecular dynamics simulations.

Osmolytes play an important role in cellular physiology by modulating the properties of proteins, including their molecular specificity. EcoRI is a model restriction enzyme whose specificity to DNA is altered in the presence of osmolytes. Here, we investigate the effect of two different osmolytes, glycerol and DMSO, on the dynamics and hydration of the EcoRI enzyme using molecular dynamics simulations. Our results show that the osmolytes, alter the essential dynamics of EcoRI. Particularly, we observe that the dynamics of the arm region of EcoRI which is involved in DNA binding is significantly altered. In addition, conformational free energy analyses reveals that the osmolytes bring about a change in the landscape similar to that of EcoRI bound to cognate DNA. We further observe that the hydration of the enzyme for each of the osmolyte is different, indicating that the mechanism of action of each of these osmolytes could be different. Further analyses of interfacial water dynamics using rotational autocorrelation function reveals that while the protein surface contributes to a slower tumbling motion of water, osmolytes, additionally contribute to the slowing of the angular motion of the water molecules. Entropy analysis also corroborates with this finding. We also find that the slowed rotational motion of interfacial waters in the presence of osmolytes contributes to a slowed relaxation of the hydrogen bonds between the interfacial waters and the functionally important residues in the protein. Taken together, our results show that osmolytes alter the dynamics of the protein by altering the dynamics of water. This altered dynamics, mediated by the changes in the water dynamics and hydrogen bonds with functionally important residues, may contribute to the altered specificity of EcoRI in the presence of osmolytes.

Mutagenic analysis of actin reveals the mechanism of His161 flipping that triggers ATP hydrolysis.

The dynamic assembly of actin is controlled by the hydrolysis of ATP, bound to the center of the molecule. Upon polymerization, actin undergoes a conformational change from the monomeric G-form to the fibrous F-form, which is associated with the flipping of the side chain of His161 toward ATP. His161 flipping from the gauche-minus to gauche-plus conformation leads to a rearrangement of the active site water molecules, including ATP attacking water (W1), into an orientation capable of hydrolysis. We previously showed that by using a human cardiac muscle α-actin expression system, mutations in the Pro-rich loop residues (A108G and P109A) and in a residue that was hydrogen-bonded to W1 (Q137A) affect the rate of polymerization and ATP hydrolysis. Here, we report the crystal structures of the three mutant actins bound to AMPPNP or ADP-Pi determined at a resolution of 1.35-1.55 Å, which are stabilized in the F-form conformation with the aid of the fragmin F1 domain. In A108G, His161 remained non-flipped despite the global actin conformation adopting the F-form, demonstrating that the side chain of His161 is flipped to avoid a steric clash with the methyl group of A108. Because of the non-flipped His161, W1 was located away from ATP, similar to G-actin, which was accompanied by incomplete hydrolysis. In P109A, the absence of the bulky proline ring allowed His161 to be positioned near the Pro-rich loop, with a minor influence on ATPase activity. In Q137A, two water molecules replaced the side-chain oxygen and nitrogen of Gln137 almost exactly at their positions; consequently, the active site structure, including the W1 position, is essentially conserved. This seemingly contradictory observation to the reported low ATPase activity of the Q137A filament could be attributed to a high fluctuation of the active site water. Together, our results suggest that the elaborate structural design of the active site residues ensures the precise control of the ATPase activity of actin.

Long-run forecasting surface and groundwater dynamics from intermittent observation data: An evaluation for 50 years.

The accurate prediction of water dynamics is critical for operational water resource management. In this study, we propose a novel approach to perform long-term forecasts of daily water dynamics, including river levels, river discharges, and groundwater levels, with a lead time of 7-30 days. The approach is based on the state-of-the-art neural network, bidirectional long short-term memory (BiLSTM), to enhance the accuracy and consistency of dynamic predictions. The operation of this forecasting system relies on an in-situ database observed for over 50 years with records gauging in 19 rivers, the karst aquifer, the English Channel, and the meteorological network in Normandy, France. To address the problem of missing measurements and gauge installations over time, we developed an adaptive scheme in which the neural network is regularly adjusted and re-trained in response to changing inputs during a long operation. Advances in BiLSTM with extensive learning past-to-future and future-to-past further help to avoid time-lag calibration that simplifies data processing. The proposed approach provides high accuracy and consistent prediction for the three water dynamics within a similar accuracy range as an on-site observation, with approximately 3 % error in the measurement range for the 7 day-ahead predictions and 6 % error for the 30 d-ahead predictions. The system also effectively fills the gap in actual measurements and detects anomalies at gauges that can last for years. Working with multiple dynamics not only proves that the data-driven model is a unified approach but also reveals the impact of the physical background of the dynamics on the performance of their predictions. Groundwater undergoes a slow filtration process following a low-frequency fluctuation, favoring long-term prediction, which differs from other higher-frequency river dynamics. The physical nature drives the predictive performance even when using a data-driven model.

Incoherent Neutron Scattering and Terahertz Time-Domain Spectroscopy on Protein and Hydration Water.

Incoherent inelastic and quasi-elastic neutron scattering (INS) and terahertz time-domain spectroscopy (THz-TDS) are spectroscopy methods that directly detect molecular dynamics, with an overlap in the measured energy regions of each method. Due to the different characteristics of their probes (i.e., neutron and light), the information obtained and the sample conditions suitable for each method differ. In this review, we introduce the differences in the quantum beam properties of the two methods and their associated advantages and disadvantages in molecular spectroscopy. Neutrons are scattered via interaction with nuclei; one characteristic of neutron scattering is a large incoherent scattering cross-section of a hydrogen atom. INS records the auto-correlation functions of atomic positions. By using the difference in neutron scattering cross-sections of isotopes in multi-component systems, some molecules can be selectively observed. In contrast, THz-TDS observes the cross-correlation function of dipole moments. In water-containing biomolecular samples, the absorption of water molecules is particularly large. While INS requires large-scale experimental facilities, such as accelerators and nuclear reactors, THz-TDS can be performed at the laboratory level. In the analysis of water molecule dynamics, INS is primarily sensitive to translational diffusion motion, while THz-TDS observes rotational motion in the spectrum. The two techniques are complementary in many respects, and a combination of the two is very useful in analyzing the dynamics of biomolecules and hydration water.