Basin Water Research Articles

EFFECTS OF ORGANIC CORROSION INHIBITOR SPILLS ON ZOOPLANKTON LIFE IN FRESH WATER BASINS

The paper studies the effect of an organic corrosion inhibitor based on imidazoline in doses from 20 to 100 mg/l on the structural parameters of zooplankton from a freshwater basins. It is known that an increase in temperature can lead to a decrease in food absorption and filtration rate by adults, as well as to egg degeneration and even to their abortion. The flow rate also leads to a decrease in the vital activity process, and the release of cyanobacterial toxins (as well as other nitrogen-containing compounds) also reduces the feeding rate. Besides, these toxins getting into the area increase the weight of the host crustacean, hindering its movement and water filtration. Based on the results obtained, it is important to note that the greatest harm to zooplankton is caused by cyanobacteria and their varieties, the basis of which are nitrogen-containing organic compounds, which are widely used as corrosion inhibitors in oil production. At each stage of the oil production process, there may be (as a result of an accident, etc.) a release of harmful substances into the atmosphere, hydrosphere and lithosphere. When using corrosion inhibitors, there are risks associated with the ingress of inhibitors into fresh water basins. Based on the results of the work, it has been determined that the ingress of even a minimal amount of corrosion inhibitor has a negative effect on the vital activity of zooplankton, reducing the number and biomass. A probable spill of an organic corrosion inhibitor based on imidazoline will negatively affect the qualitative and quantitative characteristics of zooplankton. During the work, no changes were noted in relation to the final number and biomass, which indicates a detrimental effect for each of the dominant taxa presented in the work.

Environmental consequences of maintenance dredging in the port of Sabetta (Gulf of Ob) and compensation measures

In this work, we assess possible negative effects associated with regular maintenance dredging in the port of Sabetta on the marine biological resources and coastal environment of the Gulf of Ob. The costs of environmental protection measures and сountervailing payments are determined. As a restoration activity for fish fauna, it is proposed to implement the artificial reproduction of young fish of valuable species, such as peled, siberian sturgeon, or muksun, followed by their release into the natural environement of the lakes and rivers of the West-Siberian fishery water basin.

Analogs of Precambrian microbial communities formed de novo in Caucasian mineral water aquifers.

The microbiome of deep continental aquifers is considered the most slowly evolving part of the biosphere. The Yessentukskoye Mineral Water Basin (YMWB), located in the pre-Caucasus region, contains three closely spaced but distinct aquifers, the Upper Cretaceous, the Lower Cretaceous, and the Upper Jurassic, which represent unique objects for subsurface biosphere research due to gas-hydrogeochemical and thermal anomalies of the area. We analyzed the geological and hydrogeochemical parameters of the three aquifers and a recharge area of the YMWB and investigated their microbial communities using metagenomic and cultivation-based approaches within a long-term survey. Correlation analysis of the obtained data revealed stable and highly stratified microbial communities inhabiting four distinct ecosystems. Their structure and the metabolic traits of their prokaryotic populations were similar to those presumed to have dominated the Earth's biosphere during several critical periods of its evolutionary history, that is, the Early Archean, the period of banded iron formations accumulation, and the Great Oxidation Event. Among the YMWB strata, the Upper Jurassic aquifer, supersaturated with CO2, influenced by magmatic activity, and highly enriched with thermophilic autotrophic hydrogenotrophic acetogens, turned out to be the first described modern ecosystem based on the primary production by a process predicted to support the Last Universal Common Ancestor (LUCA). The characterization of the YMWB microbial communities reveals a contemporary model environment of the early stages of Earth's development and thus contributes to the understanding of the evolutionary traits in microbial populations that may have played a critical role in the formation of the modern biosphere.IMPORTANCEContinental subsurface environments are estimated to harbor up to one-fifth of the planet's total biomass, representing the most stable and slowly evolving part of the biosphere. Among the deep subsurface inhabitants, the microbial communities of drinking mineral waters remain the least studied. Our interdisciplinary study of the Yessentukskoye Mineral Water Basin shows how hydrochemical and hydrodynamic factors shape different subsurface ecosystems, whose microbial populations influence the composition of mineral waters. A comprehensive analysis reveals the similarity of these ecosystems to those predicted for the early Earth. The deepest of the studied aquifers is the first described modern ecosystem with the most probable primary producer performing hydrogenotrophic acetogenesis. Thus, our results contribute to the understanding of the genesis of modern drinking water resources and expand the knowledge of the evolutionary traits that may have played a critical role in the formation of the Earth's biosphere.

Spatial Distribution, Source Analysis, and Risk Assessment of Multiple Antibiotics in Chaohu Lake Basin

Chaohu Lake is the fifth largest freshwater lake in China that meets the needs of surrounding industries for water, tourism, and flood storage, making it important for the socio-economic development and modernization of Anhui Province. As an important ecological wetland in the lower reaches of the Yangtze River, many rare bird habitats are present along the coast of Chaohu Lake. Therefore, it is eco-economically important to study antibiotic pollution in Chaohu Lake. To unveil antibiotic contamination in Chaohu Lake, surface water and sediment samples were collected from the main basin of Chaohu Lake by steamship in June 2022. Solid phase extraction and ultra-performance liquid chromatography-mass spectrometry （SPE-UPLC-MS） was used to determine the occurrence of 31 target antibiotics, including tetracyclines, sulfonamides, macrolides, and quinolones. The study focused on the spatial distribution, source analysis, and risk assessment of various antibiotics in the surface water and sediments of the main basin of Chaohu Lake. The occurrences of 20 different antibiotics were successively identified in the surface water and sediments of Chaohu Lake. These antibiotics included sulfonamides, quinolones, macrolides, tetracyclines, and others. Significant spatial differences in antibiotics were found between surface water and sediments. The horizontal spatial distribution results indicated differences in species and concentration of antibiotics in surface water and sediments. The vertical spatial distribution results showed that many types of antibiotics had consistent vertical distribution characteristics in surface water and sediments at the same point. The principal component analysis results indicated that the source of antibiotics in surface water was similar to that in sediment and considered with the actual distribution of existing industries around Chaohu Lake； the main sources were livestock and poultry breeding sewage, aquaculture sewage, and household sewage. The ecological risk quotient （RQ） results indicated that norfloxacin in the surface water of Chaohu Lake posed a high risk to algae （RQ > 1）, while sulfamethoxazole and doxycycline posed a medium risk to algae （0.1 ≤ RQ < 1）. The health risk quotient （HRQ） showed that the risk of exposure to antibiotics through drinking water was very low （HRQ < 0.01）. Our findings provide scientific support for decision makers to control antibiotic pollution and reduce the management costs of antibiotic watershed pollution.

Water Recovery of brine water treatment from a small-scale desalination system in Nakhon Ratchasima

This study aims to recover water from treating brine water of a small-scale desalination using a solar still. The design focuses on keeping temperatures inside at conditions suitable for water evaporation from the brine water basin. Water vapor rises and condenses into water droplets on the transparent glass cover, moving down the slope into a channel and collecting outside. The solar still is 1.0 m x 1.0 m x 0.5 m (width x depth x height) with a 25-degree slope for a transparent glass cover on top. This slope allows the water droplet to move down without reentering into the brine water basin below. The brine water was placed on top of the carbonized rice hull. The black residues can absorb heat energy by being a dark color, locally available, environmentally friendly, and stable. The test results during rainy and early winter months showed that the prototype solar still produced the average recovery water of 150 mL/day/set, with the hourly temperatures inside the chamber ranging from 30 to 70.1 Celsius. The highest inside temperature occurred at 2 PM, with an average of 70.1 Celsius. A correlation was observed between temperature and the amount of distilled water. Water recovery from the prototype ranged from 1,090 to 1,256 mL/day. Low recovery occurred in the rainy months. Estimation of water recovery rates in Nakhon Ratchasima ranged from 45 to 55 mL/m2/day. The solar still provides an alternative to recover water and mitigate the direct impact of brine water discharge from the small-scale desalination in Nakhon Ratchasima from possible effect of salinity water discharge. The method is economical, less burdensome to the caretaker, and low budget. The recovery water is freshwater; thus, it can be reused and has no long-term impact. The use of solar still is an auxiliary device that can be used with small-scale desalination in areas with saline water.

Hydrogeochemical characteristics and evolution of formation water in the continental sedimentary basin: A case study in the Qaidam Basin, China.

In deep formations, oil or gas reservoir rocks are generally accompanied by groundwater with high total dissolved solids (TDS), commonly referred to as "formation water". The enrichment of trace and/or metallic elements such as K, B, Li, Br, Sr in this type of groundwater holds significant industrial values and socioeconomic benefits. However, the processes involved in the burial and generation of formation water remain not fully understood. In this study, totally 468 sets of major ions and trace elements were collected from current study and literatures to investigate the hydrogeochemical characteristics and evolution mechanisms of formation water from different regional geological structure units in Qaidam Basin, China. The results indicated that TDS of formation water in Western (QW), Central (QC) and Northern (QN) units of Qaidam basin ranged from 173 to 290g/L, 101 to 152g/L and 32 to 73g/L, respectively, which were several to dozens of times higher than those of seawater, but lower than those of intercrystalline brine and salt lake water. The enrichment of Ca, Li, B, Br and depletion of Mg and SO42- were observed in the formation water in comparison to seawater and salt lake water. Formation water especially in QC and QW was identified as typical dissolved brine of terrestrial rock origin, experiencing prolonged water-rock interactions. However, the time and degree of water-rock interaction and metamorphism differed regionally due to the sedimentary history and patterns of Qaidam Paleolake. Overall, the large paleolake deposits under the control of multiple tectonic movements laid the material foundation for the burial and generation of the formation water, and a variety of fluids and deep faults became the sources and migration channels for formation water. It mainly experienced two stages, including the sedimentary process of saline strata and the transformation in the later period.

Bridging the gap: an interpretable coupled model (SWAT-ELM-SHAP) for blue-green water simulation in data-scarce basins

Blue water (BW) and green water (GW) are crucial components of the hydrological cycle, but their accurate simulation and interpretation remain challenging in data-scarce basins. We propose the SWAT-ELM-SHAP model, coupling the Soil and Water Assessment Tool (SWAT), Ensemble Learning Model (ELM), and Shapley Additive Explanations (SHAP) method. This novel approach bridges the gap between a physically-based hydrological model, a data-driven machine learning (ML) model, and a holistically-interpreted SHAP method, offering accurate blue-green water simulation and holistic result interpretation for improved water resources management in data-scarce basins. We took the transfer simulation of blue-green water from the Xiangjiang River Basin (source basin, 82,900km²) to the Zishui River Basin (target basin, 28,142km²) as a case study to test and evaluate the feasibility of the coupled model during 1991-2022. The model performance results indicate that the simulation accuracy of our new coupled model is improved in data-scarce basins. In combination with hydrological response features generated by SWAT and meteorological features as the ELM input, our model enhances the daily blue-green water simulation. The Nash-Sutcliffe Efficiency coefficient (NSE) for BW, Green water flow (GWF), and Green water storage (GWS) consistently exceeds 0.77 during the calibration period (1991-2010) and exceeds 0.8 during the testing period (2011-2022). The interpretation results of coupled model demonstrate that SHAP holistic interpretation provides good interpretability for blue-green water simulation results in data-scarce basins. In general, the SWAT-ELM-SHAP offers a referenced approach that can reliably and efficiently simulate blue-green water in data-scarce basins, but more importantly, can further our understanding of the potential causal relationships, influence mechanisms, and variation mechanisms of blue-green water under changing environmental conditions.

Construction and verification of distributed hydrothermal coupling model in the source area of the Yangtze River

Study regionThe source area of the Yangtze River, a typical catchment in the cryosphere on the Tibet Plateau, was used to develop and validate a distributed hydrothermal coupling model. Study focusClimate change has caused significant changes in hydrological processes in the cryosphere, and related research has become hot topic. The source area of the Yangtze River (SAYR) is a key catchment for studies of hydrological processes in the cryosphere, which contains widespread glacier, snow, and permafrost. However, the current hydrological modeling of the SAYR rarely depicts the process of glacier/snow and permafrost runoff from the perspective of coupled water and heat transfer, resulting in distortion of simulations of hydrological processes. Therefore, we developed a distributed hydrothermal coupling model, namely WEP-SAYR, based on the WEP-L (Water and energy transfer process in large river basins) model by introducing modules for glacier and snow melt and permafrost freezing and thawing. New hydrological insights for the regionIn the WEP-SAYR model, the soil hydrothermal transfer equations were improved, and a freezing point equation for permafrost was introduced. In addition, the glacier and snow meltwater processes were described using the temperature index model. Compared to previously applied models, the WEP-SAYR portrays in more detail glacier/snow melting, dynamic changes in permafrost water and heat coupling, and runoff dynamics, with physically meaningful and easily accessible model parameters. The model can describe the soil temperature and moisture changes in soil layers at different depths from 0 to 140cm. Moreover, the model has a good accuracy in simulating the daily/monthly runoff and evaporation. The Nash-Sutcliffe efficiency exceeded 0.75, and the relative error was controlled within ±20%. The results showed that the WEP-SAYR model balances the efficiency of hydrological simulation in large scale catchments and the accurate portrayal of the cryosphere elements, which provides a reference for hydrological analysis of other catchments in the cryosphere.

Analyzing solar still performance with PV electricity storage: Energy, exergy, exergoeconomic, and enviroeconomic perspectives

Population expansion and water shortages are driving up demand for freshwater worldwide. This study presents an in-depth 4E analysis (energy, exergy, exergoeconomic, and enviroeconomic) of a novel solar still (SS) design integrated with a photovoltaic (PV) module. In this configuration, the PV module is positioned on the backside of the SS, enabling electrical output to be stored during daylight hours and converted to thermal energy after sunset to heat saline water in the SS basin until midnight. Two solar still configurations are assessed: a conventional solar still (CSS) and an enhanced design featuring the PV module (CSS + PV). This integration not only optimizes land use by requiring no additional space but also enhances efficiency as the PV module acts as a reflector, transferring additional solar energy to the SS basin. Results demonstrate that the CSS + PV setup boosts the SS temperature by nearly 23 %, significantly increasing hourly freshwater production, particularly around midday, with a 52.3 % increase in daily freshwater yield over the CSS alone. Energy efficiency shows a steady increase until mid-afternoon, followed by a dip and subsequent rise into the evening, with CSS + PV consistently achieving higher efficiencies. The CSS + PV system also yields substantial gains in exergy, with day-to-day exergy efficiency improving by 20.12 % compared to conventional stills. This study underscores the potential of PV-integrated SS systems to enhance performance across multiple metrics, supporting their suitability for sustainable freshwater production and offering a viable solution for increased water and energy efficiency.

An agent-based socio-hydrological modeling to identify the feedbacks between agricultural irrigation and ecological water conveyance tradeoffs in Hotan River basin

Study regionHotan River basin in Northwest China Study focusThe conflict between agricultural irrigation and ecological water conveyance is particularly critical in arid inland river basins. Water resource systems involve multiple stakeholders and sectors, complicating the identification of dynamic feedback between agriculture and ecology. This study presents an agent-based socio-hydrological modeling (ABSHM) framework to address these interactions. New hydrological insights for the regionFeedback is quantified using dynamic state variable of oasis decision-making sensitivity in the Hotan River basin. When this sensitivity ranges from 0.03 to 0.06, water managers prioritize agricultural irrigation, increasing its usage from 8 to 47 million m3 at the expense of ecological water. Conversely, when sensitivity is from 0.015 to 0.03, ecological health requires increasing ecological water use from 27 to 66 million m³ by reducing irrigation. The ABSHM framework effectively captures these dynamic feedback processes, supporting basin water resources management and decision-making. The uniqueness of the ABSHM framework lies in its ability to capture the impact of individual decision-making behaviors on the overall water resource system. This offers new perspectives and approaches for addressing current and future water resource management challenges.

Computer System for Forecasting Water Quality Parameters Based on Machine Learning

The article presents research on environmental forecasting using machine learning methods for water quality analysis in the Southern Bug River. It focuses on the application of binary logistic regression and random forest regression to estimate the effects of various environmental parameters on key water quality indicators. The study involved data preparation by reading and processing CSV files with economic and environmental indicators and generating feature matrices and target vectors for model training. Both models were trained using nine years of data. The results can be used to develop water resource management strategies, predict the ecological state of water basins, and assess the influence of anthropogenic factors on the hydrochemical regime of rivers. In addition, the revealed relationships between the hydrochemical characteristics of water contribute to increasing the automation of water quality monitoring processes.

Method for Estimating the Diffuse Attenuation Coefficient from the Beam Attenuation Coefficient in the Waters of the Black Sea

The vertical attenuation coefficient of downward irradiance is one of the hydro-optical characteristics that determine the parameters of the light field in the sea. Information from the vertical attenuation coefficient of downward irradiance (or the diffuse attenuation coefficient) is necessary when determining an important biological and ecological parameter of water basin — the thickness of the euphotic layer. A possible method for estimating the vertical attenuation coefficient of downward irradiance (or the diffuse attenuation coefficient) from measurements of the beam attenuation coefficient at a wavelength of 525 nm for the Black Sea waters is described. The Black Sea waters are characterized by an increased content of dissolved organic matter and belong to type II waters (according to the Morel classification). Examples of the application of the method are given, which showed a quite high correlation (R = 0.85) between the values of the vertical attenuation coefficient of downward irradiance determined from in situ measurements of underwater irradiance with a photometer and calculated from in situ measurements of the beam attenuation coefficient with a transparency meter. The standard deviation of the calculated values from the measured ones is 0.008 m–1, the maximum deviation is 0.023 m–1.

Alkalothermophilic Iron-Reducing Bacteria of the Goryachinsk Thermal Water Basin

A study of iron-reducing prokaryotes that use the poorly crystalline mineral ferrihydrite as an electron acceptor revealed their widespread occurrence on the planet. However, the ability of iron reducers to develop under polyextreme conditions (at elevated values of pH and temperature) has not been previously demonstrated. To confirm the existence of alkalothermophilic iron reducers, we studied the water and sediment samples from the Goryachinsk nitrogen-rich thermal water basin. These springs are associated with young tectonic fractures in the Baikal rift zone; their water is characterized by low salinity, alkaline pH (8.8‒9.2) and temperature of 53‒55°C. Enrichment cultures reducing synthesized ferrihydrite were obtained by adding this mineral to the water and sediment samples from the Goryachinsk thermal springs, followed by anaerobic incubation at 50 and 55°C. The 16S rRNA gene profiling of the water and sediment samples and of the primary enrichment cultures revealed high taxonomic diversity, almost exclusively represented by bacterial taxa. Subsequent transfers with ferrihydrite and organic acids or hydrogen as electron donors resulted in stable enrichment cultures of organo- and lithotrophic alkalothermophilic iron reducers. Members of the genus Parvivirga, one of the first cultured representatives of the OPB41 group (now the order Anaerosomatales, phylum Actinomycetota), constituted 30 to 50% of the total abundance.

Sun Glints and Underwater Caustics in Remote Sensing of Seas and Oceans

The Sun glints that are observed on the water surface have different radiances, shapes, and color shades, depending on the positions of the Sun and the observer, the water surface statement, and the transparency of the water and atmosphere. The texture, radiance, and color characteristics of Sun glints carry information about the state of the water and atmosphere. Therefore, Sun glints play an important role in remote sensing of seas and oceans, being a useful signal in some problems and noise in others. Bright stripes (underwater caustics) on the bottom of the water basin that are caused by the waves are also an indicator of the water surface shape. The application of the wave theory of light is used to study the intensity distribution in the vicinity of the caustic (i. e., where the geometric-optical approximation is inapplicable), which arises when light is refracted on a wavy water surface.A formula, which determines the parameters of the waves from the width of the caustic zone is obtained. The correctness of the method has been verified by experiments carried out in the pool. Also, here we give a brief overview of our investigations related to sun glints and underwater caustics.

Insights into the effects of river network topology on sudden pollution risks

The risk of sudden water pollution is one of the biggest obstacles to ensuring the safety of river basin water environments. While external pressure factors such as illegal discharge have been extensively studied with regard to their impact on the risk of sudden pollution, the influence of the river network topology has received limited attention. To fill this gap, extensive computational experiments were conducted in this study to investigate the effects of river network topology on the potential risk of sudden pollution. Based on the real-world characteristics of dendritic river networks, we used optimal channel networks to generate various river network topologies, represented by seven indicators that encompass morphology, connectivity, and structure. The water quality model simulated the spatial and temporal responses of the samples to a wide range of sudden pollution scenarios, and quantified the associated risk of sudden pollution using three proxy indicators: the maximum standard-exceeding multiple, proportion of standard-exceeding river length, and duration of exceedance. The results showed that among the seven indicators, the average outlet path (Do) and geometric fractal dimension (Dg) had a significant impact on risk. This is because network topology alters hydrological signatures such as discharge, velocity, and travel time. Moreover, multi-group analysis of structural equations revealed that the aspect ratio influences the impact of structural and connectivity indicators on risk by modulating pollution range and concentration. This study revealed the topological factors of the risk of sudden water pollution in dendritic river networks, emphasizing the regulatory role of topology in potential sudden water pollution risk and providing valuable insights for river management and planning.

Impacts of land use changes on water conservation in the Songhuajiang River basin in Northeast China using the SWAT model

The Songhuajiang River basin (SRB) in Northeast China underwent obvious changes in land use in recent years, which might lead to intense changes in basin hydrology and water conservation. Therefore, to evaluate the effects of land use changes on the hydrological cycle and associated water conservation in the SRB, a calibrated Soil and Water Assessment Tool (SWAT) model was used. The model auto-calibration was conducted using the SWAT-CUP (SWAT Calibration and Uncertainty Procedures) tool. Results revealed that calibration of three crop yields of corn (Zea mays L.), rice (Oryza sativa L.), and soybean (Glycine max L.) during the study period (2001–2018) had the Percent BIAS (PBIAS) values of −8.7 %∼3.0 %, 6.2 %∼19.7 %, and −8.7 %∼7.2 %, respectively in 15 zones. Good agreements were obtained for simulated results of streamflow in comparison with measured data from 12 hydrological stations, in which the overall Nash-Sutcliffe Efficiency (NSE) values for the calibration (2009–2012) and validation (2013–2015) periods were 0.60 and 0.64, respectively, and the overall PBIAS values were 7.7 % and 15.4 %. For the land use changes, the hydrological cycle of corn to rice (all hydrological variables change by more than 18 %) was more complex and intense than that of corn to soybean (all hydrological variables change not exceed 5 %). According to the simulation results of water conservation, this study found that the implementation of the policy-driven replacement of corn with soybean in the SRB was feasible. As for the economy-driven conversion from corn to rice, it is necessary to consider the substantial impacts on the hydrological cycle and the decline in water conservation. Based on simulation results, it is not recommended that producers in the Western SRB promote corn to rice conversion.

The transboundary effects of climate change and global adaptation: the case of the Euphrates–Tigris water basin in Turkey and Iraq

The transboundary effects of climate change and global adaptation: the case of the Euphrates–Tigris water basin in Turkey and Iraq

Deep Reinforcement Learning for Multi-Objective Real-Time Pump Operation in Rainwater Pumping Stations

Rainwater pumping stations located near urban centers or agricultural areas help prevent flooding by activating an appropriate number of pumps with varying capacities based on real-time rainwater inflow. However, relying solely on rule-based pump operations that monitor only basin water levels is often insufficient for effective control. In addition to maintaining a low maximum water level to prevent flooding, pump operation at rainwater stations also requires minimizing the number of pump on/off switches. Reducing pump switch frequency lowers the likelihood of mechanical failure and thus decreases maintenance costs. This paper proposes a real-time pump operation method for rainwater pumping stations using Deep Reinforcement Learning (DRL) to meet these operational requirements simultaneously, based only on currently observable information such as rainfall, inflow, storage volume, basin water level, and outflow. Simulated rainfall data with various return periods and durations were generated using the Huff method to train the model. The Storm Water Management Model (SWMM), configured to simulate the Gasan rainwater pumping station located in Geumcheon-gu, Seoul, South Korea, was used to conduct experiments. The performance of the proposed DRL model was then compared with that of the rule-based pump operation currently used at the station.

An Extensive Review of Leaching Models for the Forecasting and Integrated Management of Surface and Groundwater Quality

The present study reviews leachate models useful for proactive and rehab actions to safeguard surface and subsurface soft water, which have become even more scarce. Integrated management plans of water basins are of crucial importance since intensively cultivated areas are adding huge quantities of fertilizers to the soil, affecting surface water basins and groundwater. Aquifers are progressively being nitrified on account of the nitrogen-based fertilizer surplus, rendering water for human consumption not potable. Well-tested solute leaching models, standalone or part of a model package, provide rapid site-specific estimates of the leaching potential of chemical agents, mostly nitrates, below the root zone of crops and the impact of leaching toward groundwater. Most of the models examined were process-based or conceptual approaches. Nonetheless, empirical prediction models, though rather simplistic and therefore not preferrable, demonstrate certain advantages, such as less demanding extensive calibration database information requirements, which in many cases are unavailable, not to mention a stochastic approach and the involvement of artificial intelligence (AI). Models were categorized according to the porous medium and agents to be monitored. Integrated packages of nutrient models are irreplaceable elements for extensive catchments to monitor the terrestrial nitrogen-balanced cycle and to contribute to policy making as regards soft water management.

Predicting Monthly Runoff: A BO-CNN-LSTM Approach for Enhanced Water Resource Management

Monthly runoff prediction is critical for sustainable water resource management, flood control, and drought preparedness. Accurate forecasts assist decision-making and management of water resources, which are critical for human and environmental demands. Previous prediction algorithms frequently lack accuracy due to human-defined hyperparameters. Autonomous hyperparameter tuning is required for improved predictions. Objectives: To improve the accuracy of monthly runoff predictions, this research proposes a BO-CNN-LSTM model that integrates Bayesian optimization (BO) with a convolutional neural network-long short-term memory neural network (CNN-LSTM). Methods/Analysis: The BO algorithm is utilized to enhance the CNN-LSTM model's hyperparameters, which helps to overcome the limits of human-set parameters. Model training and validation were carried out using monthly runoff data from 1956 to 2019 from Lanxi Station in the Hulan River Basin. The model's prediction performance was assessed using root mean square error (RMSE), mean absolute error (MAE), fitting coefficient (R²), and mean relative error (MAPE), and compared with other previous models. Findings: The results show that the BO-CNN-LSTM model outperforms conventional models in prediction accuracy and reduction of errors. The BO method efficiently enhances hyperparameters, resulting in higher performance metrics. This model gives more precise and dependable monthly runoff forecasts, which are critical for handling the Hulan River Basin's water resources. Novelty/Improvement: By combining BO and CNN-LSTM, the proposed model solves the constraints of previous models, improving prediction accuracy and reducing errors. This innovative technique presents a promising novel approach for monthly runoff prediction, with possible applications in larger hydrological prediction.