Surface Reservoirs Research Articles

Integration of geospatial technologies with multi-criteria decision analysis for aquaculture land suitability evaluation: The case of Fincha'a River Sub-basin, Western Ethiopia

Assessment of physical land suitability for aquaculture is a prerequisite for promoting fish farming and enhancing food security as increase in global population and fish demand is tremendously rising. In addition, our country is also riches in enough water resources and conducive environments. Despite these facts, the vast majority of the local communities in Ethiopia are not benefited from aquaculture due to limited information and infrastructures. This study intended to assess land suitability for aquaculture using geospatial techniques in Fincha'a river sub basin, western Ethiopia. In the present study, slope, river, road, market, land use land cover (LULC), soil types, land surface temperature (LST), rainfall, lakes and reservoirs were performed using multi criteria Evaluation (MCE) based Pairwise Comparison Matrix to evaluate land suitability for aquaculture. The results revealed that, about 51.4km 2 is highly suitable, while 843.5km 2 categorized under moderately suitable. About 1483.5km 2 were categorized under marginally suitable, while 56.5km 2 is not suitable for aquaculture. Based on the result, we recommend that, community awareness is required to utilize maximum potential of aquaculture farming, that may contribute towards poverty eradication and food security in Ethiopia. • Warm area and wetland areas were highly suitable for fish farming. • Analytical hierarchy process is a powerful method to generate land suitability for aquaculture. • Land suitability assessment can indicate the potential of particular land for different purposes. • Utilizing maximum potential of aquaculture farming, that may contribute towards poverty eradication and food security in Ethiopia is forwarded.

ASSESSMENT OF THE RESERVOIRSꞋ IMPACT ON THE RIVER FLOW

In this article, the influence of reservoirs and ponds on the hydrological regime in the Yesil River basin is studied. To assess the impact of existing reservoirs on the annual runoff of rivers in the study basin, a simplified methodology of the State Hydrological Institute was used. The change in the annual (seasonal) runoff under the influence of ponds and reservoirs was determined using two methods: by the volume of filling the reservoirs; due to additional evaporation from the water surface of reservoirs compared to evaporation from land before their creation. When assessing the impact of ponds in terms of filling volumes or taking into account in the direct form of water intakes for economic needs, the influence of not only ponds, as artificial elements of the landscape, but also other factors of economic activity, was revealed. When assessing the impact of economic activities on the elements of the hydrological regime of rivers, including the creation of reservoirs for long-term regulation, changes in the climatic background are taken into account. According to the analysis of the results of assessing the impact on the runoff of the volumes of filling reservoirs, economic activities from 1974 to 2018 led to a decrease in runoff in the alignment of the river. Yesil - Nur-Sultan in the middle years of water availability (50% supply) by 30%, and in the mouth section. Yesil - Petropavlovsk city decrease in runoff up to 7%.

Surface Dust Redistribution on Mars From Interannual Differences in Temperature and Albedo

AbstractThe present climate of Mars is punctuated by recurring dust storm events, where dust is lifted from the surface and is transported by the atmosphere. Dust addition or removal can brighten or darken the surface, as well as affect thermal insulating properties because of its low thermal conductivity. Of particular interest is the recurrence of global dust storms (GDSs) and whether their frequency is controlled by the replenishment or depletion of finite surface reservoirs between events. Global climate models predict changes in dust coverage before and after global storms, but output varies substantially regarding the amounts and locations of transported dust. The analysis of global, multiyear observations of surface temperature and albedo from orbit can constrain changes in dust coverage and/or thickness. We calculate and map interannual differences in surface temperature from Mars Year (MY) 24 through MY35 to identify regions of dust redistribution. Regional temperature changes across the MY25 GDS can be explained by changes in albedo and do not require changes in surface thermal properties, supporting extremely small dust thickness changes. Across the MY34 GDS, we find less extensive changes in surface temperature, indicating a reduced impact on dust redistribution compared to MY25. However, we identify a region between Acidalia and Arabia Terra that experienced substantial dust removal and positively correlates with visible high‐resolution orbital images. Our work supports minuscule changes in dust thickness from the observed GDSs and is consistent with effectively infinite dust reservoirs on timescales of at least 103 years.

Assessment of total evaporation rates and its surface distribution by tridimensional modelling and remote sensing

In arid and semiarid environments, evaporation is responsible for significant water losses from reservoirs. This condition is of special concern in the Brazilian Northeast region, as this is one of the most populous semiarid areas in the planet. The present study aims to assess the spatio-temporal variability of evaporation rates on the water surface of Pentecoste reservoir, located in the Brazilian semiarid region, by using both the hydrodynamic model Delft3D and a remote sensing technique (RS). While RS has already been used to evaluate the spatial distribution of evaporation rates in lakes, Delft3D was innovatively tested and applied for this purpose for the first time in this study. The calibration results showed an accurate reproduction of the water level variability (r2 of 0.997), along with a satisfactory calibration of the reservoir's thermal structure for the full water column (MAE of 0.539 °C, RMSE of 0.572 °C, and NMAE of 0.008). Curves relating monthly evaporation rates with air temperature and wind speed showed strong correlation between those variables (r2 of 0.817 for air temperature and 0.849 for wind speed). Also, the averaged evaporation rates modeled by Delft3D differed by less than 5% compared to RS. Regarding the spatial distribution results, for the wet period the evaporation patterns were similar to those of RS, while in the dry period RS provided a more stable evaporation pattern when compared to Delft3D. The innovative approach proposed in the present study can be used to better understand the evaporation dynamics in surface waters and optimize the location of damping evaporation structures, namely air diffusers, shading systems, and floating solar panels, which are important for improving water availability, not only in drylands.

Water Management causes increment of reservoir silting and reduction of water yield in the semiarid State of Ceará, Brazil

The semiarid State of Ceará, Brazil, implemented its water management system in the early 1990s. The drought-prone State is densely populated and its supply strongly relies on surface reservoirs, whose yield reduces with silting. Using artificial neural networks and data from 141 monitored dams, we show that the silting ratio of the reservoirs significantly enhanced after the implementation of the water management system. An explanation for this fact is that, since the management started, water withdrawal increased, leading to lower reservoir levels at the beginning of the rainy season. This reduces the probability of spilling, which is the main mechanism of sediment outflow, thus causing excessive siltation. As a result, water availability is expected to reduce by 6% in 30 years, creating a clear contradiction with the management objectives. To tackle this problem, four actions are recommended: to include spilling in the operational rules, to reduce erosion in the basins, to execute sediment reuse policy, and to implement water-demand management.

The effect of reservoir expansion from underground karst cave to surface reservoir on water quality in southwestern China.

Due to the excessive exploitation of traditional energy sources, the attention paid to water energy has increased in recent years. As an important means to effectively utilize water energy, reservoirs play an important role in drinking water, irrigation, flood control, and drought resistance. However, utilizing reservoirs often led to water quality issues resulting from the interaction of nutrients and hydrological conditions, especially due to the special structure of karst areas. Because of the change of hydrological conditions by the effect of dam construction, the dynamic of water quality will be more obvious in karst areas with a fast exchange of water and contaminants between underground and surface streams. In the present study, the change in water quality of a karst reservoir, the Muzhu Reservoir in the Houzhai Catchment, was studied. Long-term monitored datasets (1981-2002) and water quality datasets of more recent years were used to assess the effect on the water quality of reservoir expansion from the underground reservoir to the surface reservoir in a karst area. Long-term series datasets had shown that the hydro-chemistry type had been changed from HCO3-·SO42--Ca2+·Mg2+ type to HCO3--Ca2+ type in the short term after the reservoir's expansion. The chemical components of water originating from a rock background reduced markedly after the reservoir's expansion, whereas the content of the anthropogenic contribution in the water decreased after the expansion, except in April and May. Isotopic characteristics showed that δ15N-NO3- and δ18O-NO3- values were positively correlated before and after the reservoir expansion, but the slope of the linear regression before the expansion was 0.34, while the slope of the linear regression before the expansion was close to 0.7. This indicated that although denitrification and assimilation may occur simultaneously after the reservoir's expansion, the role of denitrification on nitrate removal decreased, which resulted in nitrate accumulation in the karst reservoir. The results highlighted that nitrate accumulation in karst reservoirs should be monitored to decrease nitrate concentration in the future.

Hydroelectric operation for hybridization with a floating photovoltaic plant: A case of study

Hybrid renewable systems increase electricity production by reducing the randomness of sources without greenhouse gas emissions. Literature indicates that further research is still required for large systems connected to the grid. The energy storage capability of hydroelectric plants provides an opportunity to develop new renewable energy generation.This work presents the results of a hybrid preliminary design between an existing hydropower plant (HPP) in Brazil, Santa Branca, and a simulated floating photovoltaic plant (FPV), occupying only 2.8% of reservoir's surface. The study analyzed 20 years of HPP historical data, the methodology proposed the injection of the FPV full power into the system during daytime and the HPP adjusting the production. As this process changed the HPP generation profile, operational limits such as reservoir level needed to be verified.In the period, while HPP generated about 4 TWh, the FPV could add 2 TWh without significantly changing the daily generation of HPP. This increase of 50% in production was possible since there was space available in the reservoir to store water during the day and use it during the night, working as a free virtual battery for the FPV. A 50% increase of the grid connection capacity factor was also observed.

Dense hydrous silica could carry water to Earth’s mantle

The deep water cycle may alter mantle properties and regulate surface reservoirs.

Water Storage Variation and Its Possible Causes Detected by GRACE in the Volta River Basin

This study applies Gravity Recovery and Climate Experiment (GRACE) data and the WaterGAP (Water Global Analysis and Prognosis) Global Hydrology Model (WGHM) to investigate the influence of the Bui reservoir operation on water storage variation within the Volta River Basin (VRB). Variation in groundwater storage anomalies (GWSA) was estimated by combining GRACE-derived terrestrial water storage anomalies (TWSA), radar altimetry records, imagery-derived reservoir (Lake Volta and Bui) surface water storage anomalies (SWSA), and Global Land Data Assimilation System (GLDAS)-simulated soil moisture storage anomalies (SMSA) from 2002 to 2016. Results showed that TWSA increased (1.30 ± 0.23 cm/year) and decreased (−0.82 ± 0.27 cm/year) during 2002–2011 and 2011–2016, respectively, within VRB, matching previous TWSA investigations in this area. It revealed that the multi-year averages of monthly GRACE-derived TWSA changes in 2011–2016 displayed an overall increasing trend, indicating storage increase in regional hydrology; while the Lake Volta water storage changes decreased. The GRACE-minus-WGHM residuals display an increasing trend in VRB water storage during the Bui reservoir impoundment during 2011–2016. The observed trend compares well with the estimated Bui reservoir SWSA, indicating that GRACE solutions can retrieve the true amplitude of large mass changes happening in a concentrated area, though Bui reservoir is much smaller than the resolution of GRACE global solutions. It also revealed that GWSA were almost stable from 2002 to 2006, before increasing and decreasing during 2006–2011 and 2012–2016 with rates of 2.67 ± 0.34 cm/year and −1.80 ± 0.32 cm/year, respectively. The observed trends in the GRACE-derived TWSA and GWSA changes are generally attributed to the hydro-meteorological conditions. This study shows that the effects of strong El-Niño Southern Oscillation events on the GWSA interannual variability within the VRB is short-term, with a lag of 6 months. This study specifically showed that the Bui reservoir operation significantly affects the TWSA changes and provides knowledge on groundwater storage changes within the VRB.

Use of Remote-Sensing-Based Global Products for Agricultural Drought Assessment in the Narmada Basin, India

Droughts exert severe impacts on the environment, economy, and society. The south Asian region is vulnerable to droughts and the Indian sub-continent is one of the most vulnerable in the region to frequent drought disasters. This study assesses the agricultural droughts in the Narmada River Basin (NRB), India, where more than 50% of the area is utilized for agriculture, through freely available local and global remote-sensing-based data focusing on long-term rainfall trends (1989–2018) and recently weakened monsoons in 2017 and 2018. In this study, some of the widely used indices to characterize droughts (viz., Standardized Precipitation Index (SPI), simplified Rainfall Index (RIs), Normalized Difference Vegetation Index (NDVI)), soil moisture content, and reservoir surface areas were used to assess the drought conditions in the Narmada River Basin over the study period. Our analysis shows that the NRB has experienced a decreasing trend in monsoon rainfall over the past three decades. The SPI captured most of the basin’s historical droughts. The weakened monsoons during 2017–2018 show that different parts of the NRB have experienced severe or moderate drought conditions. A clear difference does not show in the NDVI and in the soil moisture contents of the basin over three hydrological years (2015/16, 2016/17, and 2017/18), except for July to September 2017/18. The estimated water area depletion using the Normalized Difference Water Index (NDWI) follows the actual water levels in three selected reservoirs in the basin, of which, two show a decline in the maximum surface area, likely due to the weakened monsoons in 2017 and 2018. This research indicates that the freely available data can be beneficial for local authorities to monitor and understand the drought conditions to support water resources management and planning for agricultural activities.

Dynamic assessment of slope stability based on multi‐source monitoring data and ensemble learning approaches: A case study of Jiuxianping landslide

Accurate assessment of slope stability is the most important task in geological disaster prevention and control. This study developed an ensemble learning approach based on stacking strategy and eight commonly used machine learning (ML) models, for exploring the feasibility of the factor of safety (FS) prediction using dynamic multi‐source monitoring data of slopes and landslides. Based on long‐term and dynamic field monitoring and numerical calculation, a dataset for constructing the FS prediction model for the Jiuxianping landslide was established. The dataset includes five types of monitoring data namely rainfall, reservoir water level, groundwater level, surface displacement and deep displacement for a total of nine features, and one label FS. Four regularized regression models, kernel ridge regression (KRR), lasso, elastic net and support vector regression (SVR), as well as four ensemble learning models, random forest (RF), gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost) and light gradient boosting machine (LightGBM), were adopted to obtain the nonlinear association between the nine features and the label FS, respectively. Based on five repeated 5‐fold cross‐validation (CV) and successive halving (SH) hyperparameter searching method, the hyperparameters of each model were determined, and the prediction effects of each optimal model were compared. The results show that the ensemble learning models outperform the common regression models. Furthermore, with the help of the stacking ensemble learning thinking, four excellent ensemble models were combined, and the final stacking ensemble learning model was used to predict the FS of the Jiuxianping landslide. The results indicate that the stacking model has better robustness and generalization performance. Besides, the feature relative importance of four ensemble learning models was analysed, for enhancing the interpretability of ML models and pointing out the research direction of feature engineering in the future.

Impacts of Climate Change on Water Resources, Agricultural Production and Food Security: Evidence from Turkiye

Since agricultural production depends mainly on nature and uses surface and groundwater reservoirs, changes in existing water resources significantly affect this sector. Again, changes in global climate bring changes in water levels, consequently affecting agriculture, food supply, and income sources of households in different areas. However, to date, no such research has investigated the farmers who are the producers and the most vulnerable group to the impacts of climate change. Therefore, this paper explores climate change impacts on the water resources of Sarayonu, which in turn affects the agricultural food production and food security of the producers' households and the country's market. This qualitative study conducted in-depth interviews with the farmers from the Sarayonu district of Konya province in Turkiye. The study results show that ground and surface water resources are negatively affected by climate change. Consequently, the study area observed a decrease in water level over the last 15 years. Thus, these changes in water resources have been significantly affecting the agriculture sector, which alters the food supply for the market in general and the producers in particular. When people have less water, they have low quality and quantity crop yields, resulting in food crises and economic difficulties.

Deep learning-accelerated 3D carbon storage reservoir pressure forecasting based on data assimilation using surface displacement from InSAR

• Developed a 3D data assimilation workflow for reservoir pressure forecasting in GCS. • InSAR data are used to infer reservoir pressure build up. • A 3D-to-2D residual U-Net structure is applied to accelerate the workflow. • The workflow can achieve a 1500-time speedup compared to a traditional approach. Fast forecasting of the reservoir pressure distribution during geologic carbon storage (GCS) by assimilating monitoring data is a challenging problem. Due to high drilling cost, GCS projects usually have spatially sparse measurements from few wells, leading to high uncertainties in reservoir pressure prediction. To address this challenge, we use low-cost Interferometric Synthetic-Aperture Radar (InSAR) data as monitoring data to infer reservoir pressure build up. We develop a deep learning-accelerated workflow to assimilate surface displacement maps interpreted from InSAR and to forecast dynamic reservoir pressure. Employing an Ensemble Smoother Multiple Data Assimilation (ES-MDA) framework, the workflow updates three-dimensional (3D) geologic properties and predicts reservoir pressure with quantified uncertainties. We use a synthetic commercial-scale GCS model with bimodally distributed permeability and porosity to demonstrate the efficacy of the workflow. A two-step CNN-PCA approach is employed to parameterize the bimodal fields. The computational efficiency of the workflow is boosted by two residual U-Net based surrogate models for surface displacement and reservoir pressure predictions, respectively. The workflow can complete data assimilation and reservoir pressure forecasting in half an hour on a personal computer.

Performance Evaluation of Water Treatment Plant of Kekri, Rajasthan, India

Drinking water is a sole element of human life. The rapidly growing population is adding to the excessive demand for water. Increasing demand for drinking water is rising the over-exploitation of water. Raw water sources require water treatment with a high production capacity of treatment. Present research provides a case study of the water treatment plant of Kekri, Rajasthan, India. In these two water treatment plants water purification efficiency is good as compared to conventional water treatment plants. Adding poly aluminum Chloride as a coagulant increases water treatment efficiency. Many parts of the water treatment plant add coagulation-flocculation, filtration, and disinfection by using poly aluminum chloride. Two water treatment plants with the capacity of 142 MLD and 132 MLD are having the net purifying capacity to remove the turbidity and Color. In this research, it has been found that turbidity removal of 142 MLD and 132 MLD WTP was found about 83.4 and 74.1% respectively. Total dissolved solid of surface reservoir Bisalpur dam found within acceptable limits. Total dissolved solids in Bisalpur dam surface water such as Chloride, Fluoride, and Nitrates were found of 60 mg/l, 0.3 mg/l, and 2 mg/l respectively. The pH value of surface water was found of 7.90 and remains almost constant with the seasonal variation impact. Turbidity and color reduction were found within the acceptable limit according to Indian standard 10500-2012.

Contamination Assessment and Temporal Evolution of Nitrates in the Shallow Aquifer of the Metauro River Plain (Adriatic Sea, Italy) after Remediation Actions.

Over the last decades, groundwater resources at global level have suffered a significant deterioration due to nitrate pollution, mainly related to the input of agricultural fertilizers, manure, sewage, and untreated urban and industrial effluents. The most impacted waters are those forming surface and shallow reservoirs, which usually play a key role in supplying waters to civil, agricultural, and industrial activities. The terminal portion of the Metauro River plain, located in central Italy along the Adriatic Sea coastline, hosts a strategic phreatic aquifer that, along with the surface water of the Metauro River, supplies water to the local population (i.e., about 60,000 people). This shallow coastal aquifer experiences a long-lasting story of nitrate contamination since the 1970s when the increase in the use of agricultural fertilizers contributed to very high levels of pollution (NO3− > 100 mg/L). This fact prompted the local authorities to carry out remediation actions that involve a pumping system to inject the NO3−-poor waters from the Metauro River course directly into the shallow aquifer. The present work was aimed at defining the contamination of nitrates in this important water resource. The main geochemical characteristics and the temporal evolution of NO3− concentrations (between 2009 and 2020), in the shallow coastal aquifer of the Metauro River plain, were analyzed by means of classical geochemical analyses and multivariate methods accounting for the compositional nature of the data, to assess the efficiency of the in-situ remediation over time.

USE OF UNMANNED AERIAL VEHICLES FOR WATER SAMPLING IN HARD-TO-REACH WATER RESERVOIRS

Collecting water samples for laboratory analysis from hard-to-reach surface areas such as post-industrial reservoirs (for example, tailings depositories) or overgrown lakes and ponds poses several difficulties, and it is potentially dangerous for the persons carrying out such activity. This can be improved by the use of unmanned aerial vehicles (UAVs) while ensuring an adequate level of safety and full compliance with the requirements of PN-ISO standards. This article presents the possibility of using the BSP in the option of autonomous (automatic) operation, allowing for the collection of water samples intended for physico-chemical tests, from hard-to-reach surface reservoirs, following the provisions of the relevant PN-ISO standards.

Improved maps of surface water bodies, large dams, reservoirs, and lakes in China

Abstract. Data and knowledge of surface water bodies (SWB), including large lakes and reservoirs (surface water areas > 1 km2), are critical for the management and sustainability of water resources. However, the existing global or national dam datasets have large georeferenced coordinate offsets for many reservoirs, and some datasets have not reported reservoirs and lakes separately. In this study, we generated China's surface water bodies, Large Dams, Reservoirs, and Lakes (China-LDRL) dataset by analyzing all available Landsat imagery in 2019 (19 338 images) in Google Earth Engine and very-high spatial resolution imagery in Google Earth Pro. There were ∼ 3.52 × 106 yearlong SWB polygons in China for 2019, only 0.01 × 106 of them (0.43 %) were of large size (> 1 km2). The areas of these large SWB polygons accounted for 83.54 % of the total 214.92 × 103 km2 yearlong surface water area (SWA) in China. We identified 2418 large dams, including 624 off-stream dams and 1794 on-stream dams, 2194 large reservoirs (16.35 × 103 km2), and 3051 large lakes (73.38 × 103 km2). In general, most of the dams and reservoirs in China were distributed in South China, East China, and Northeast China, whereas most of lakes were located in West China, the lower Yangtze River basin, and Northeast China. The provision of the reliable, accurate China-LDRL dataset on large reservoirs/dams and lakes will enhance our understanding of water resources management and water security in China. The China-LDRL dataset is publicly available at https://doi.org/10.6084/m9.figshare.16964656.v3 (Wang et al., 2021b).

Application of CO2 miscible flooding in ultra-low permeability beach-bar sand reservoir

The beach-bar sand reservoir of the Sha 4 Member of the Shahejie Formation in the Dongying Sag is the main oil-bearing formation in this area. In recent years, its proven reserves have been getting lower and lower, and the poor petrophysical properties of the reservoir have made water injection development difficult. In turn, it results in a rapid decline in elastic development productivity and low oil recovery. In this study, the experimental evaluation and numerical simulation research on the adaptability of CO2 flooding in beach-bar sand reservoirs are carried out on the basis of fully investigating the successful examples of CO2 flooding conducted by the previous. According to the geological characteristics of the reservoir in the CL area of the Dongying Sag, the reasonable reservoir engineering parameters and surface injection procedures for the CO2 flooding have been formulated. Experiments show that after the completion of water flooding, the recovery factor of the CO2 continuous flooding is 85.64%. It proves that the recovery factor of the CO2 flooding is higher than that of the water flooding. Field tests have shown that CO2 molecules in beach-bar sand reservoirs behave in a supercritical state underground, which is easier to being injected into the reservoir than water. In addition, the displacement distance of the CO2 is obviously larger than that of the water injection development. The gas-oil ratio variation of different flooding types is different, and CO2 flooding can effectively increase the formation energy, and improve the oil recovery and economic benefits of this type of reservoir.

Rapid Synthesis of Multifunctional Apatite via the Laser-Induced Hydrothermal Process.

Synthetic biomaterials are used to overcome the limited quantity of human-derived biomaterials and to impart additional biofunctionality. Although numerous synthetic processes have been developed using various phases and methods, currently commonly used processes have some issues, such as a long process time and difficulties with extensive size control and high-concentration metal ion substitution to achieve additional functionality. Herein, we introduce a rapid synthesis method using a laser-induced hydrothermal process. Based on the thermal interaction between the laser pulses and titanium, which was used as a thermal reservoir, hydroxyapatite particles ranging from nanometer to micrometer scale could be synthesized in seconds. Further, this method enabled selective metal ion substitution into the apatite matrix with a controllable concentration. We calculated the maximum temperature achieved by laser irradiation at the surface of the thermal reservoir based on the validation of three simplification assumptions. Subsequent linear regression analysis showed that laser-induced hydrothermal synthesis follows an Arrhenius chemical reaction. Hydroxyapatite and Mg2+-, Sr2+-, and Zn2+-substituted apatite powders promoted bone cell attachment and proliferation ability due to ion release from the hydroxyapatite and the selective ion-substituted apatite powders, which had a low crystallinity and relatively high solubility. Laser-induced hydrothermal synthesis is expected to become a powerful ceramic material synthesis technology.

Investigation of the Different Regimes Associated with the Growth of an Interface at the Exit of a Capillary Tube into a Reservoir: Analytical Solutions and CFD Validation.

The emergence of a droplet from a capillary tube opening into a reservoir is an important phenomenon in several applications. In this work, we are particularly interested in this phenomenon in an attempt to highlight the physics behind droplet appearance. The emergence of a droplet from a tube opening into a reservoir under quasi-static conditions passes through three stages. The first stage starts when the meniscus in the tube reaches the exit. At this moment, the meniscus intersects the wall of the tube at the equilibrium contact angle. The interface then develops until its radius of curvature becomes equal to the tube radius. During this stage, the capillary pressure increases. In the second stage, the interface continues to evolve with its radius of curvature increasing until the static contact angle with respect to the surface of the reservoir is achieved. This marks the end of the second stage and the start of the third in which the contact line (CL) starts to depart the tube opening along the reservoir surface and the contact angle remains constant. Analytical models for the three stages have been derived based on the law of conservation of linear momentum. The models account for pressure, gravitational, capillary, and viscous forces, while inertia force is ignored. The model can predict the profiles of the mean velocity in the tube, the capillary pressure, and the evolution of the contact angle. In addition, a computational fluid dynamics (CFD) simulation has been conducted to provide a framework for validation and verification of the developed model. The CFD simulation shows qualitative behavior in terms of snapshots of the emerging droplet with time similar to that speculated by the analytical model. In addition, quantitative comparisons with respect to velocity, pressure, and volume profiles of the droplet show very good agreement, which builds confidence in the modeling approach.