Reservoir Level Research Articles

Effects of aeration on water quality in agricultural reservoirs in the northern Great Plains

Lerminiaux J, Norton B, Wilson RJ, Rimas R, Lavender TM, Finlay K. 2024. Effects of aeration on water quality in agricultural reservoirs in the northern Great Plains. Lake Reserv Manage. 40:264–284. Aeration of agricultural reservoirs is an encouraged practice in the northern Great Plains of Canada as it can improve water quality by reducing pathogenic bacteria and algal abundance. Cattle also prefer aerated water, resulting in greater weight gain. Despite its known benefits, agricultural reservoir aeration is still not uniformly adopted, largely given its cost of installation and maintenance. Wind powered aeration has been shown to be an eco-friendly and sustainable way to increase oxygen levels in agricultural reservoirs, but the mechanisms by which this aeration can improve water quality are not well documented. By comparing 5 aerated agricultural reservoirs to 5 unaerated agricultural reservoirs, we evaluated whether wind-powered aeration improves water quality. We measured dissolved oxygen, nitrogen, and phosphorus, algal biomass (as chlorophyll a), cyanobacteria abundance, and algal toxins (microcystin, anatoxin-a, and β-N-methylamino-L-alanine) in the aerated and unaerated agricultural reservoirs on a weekly basis over a 12-week period from mid June through August 2022. We found that the aerators were able to mix the water column and add oxygen to deeper regions of the agricultural reservoir, but this did not result in consistent improvements to any measured water quality parameter. The observed lack of a strong response to aeration suggests that this practice may provide only minimal water quality benefits, but aeration may still prove beneficial for deep (>2 m) and sheltered agricultural reservoirs that do not regularly mix from wind effects alone.

Applicability of seasonal forecasts from dynamical models for reservoir management practices

Despite the availability of reliable seasonal forecasts of Indian Summer Monsoon Rainfall (ISMR), the use of dynamical models driven by these forecasts for reservoir level management is limited. Reservoir water management can specially be useful if it can be done several months in advance, in view of an impending drought/flood scenario. The applicability of seasonal forecasts from the Monsoon Mission (MM) seasonal forecast model for seasonal and monthly inflow forecasts for tropical Indian reservoirs (Mula and Kangsabati) is studied using the Soil and Water Assessment Tool (SWAT) hydrological model, at a lead time of 3 months. Long-term observed inflow datasets are used for calibration and validation of SWAT-Calibration and Uncertainty Procedure (CUP) with Sequential Uncertainty Fitting (SUFI)-2 algorithm using insitumeteorological data. Observed inflows and inflow simulations are compared with simulated inflow using SWAT with same calibrated parameters, but with forcing derived from reforecasts from the MM model. The SWAT-CUP calibrated well with reasonable Nash Sutcliffe Efficiency (NSE) (Mula = 0.75, Kangsabati = 0.79) and Percentage Bias (PBIAS) (Mula = -28%, Kangsabati = 17%) for both reservoirs. The skill scores for streamflow predictions vary from 0.6-0.70 during the monsoon season, indicating reasonable accuracy for these predictions. The SWAT-MM model has a reasonable skill with 0.52-0.53 NSE and 26%-40% PBIAS. Therefore, SWAT-MM-based model has a good potential to forecast monthly and seasonal reservoir inflow for various agro-climatic zones of India. These forecasts when used in real-time, can serve as a guideline for managing the reservoir storage and release, and hence proving to be of great socio-economic importance.

Petrographical and petrophysical rock typing for flow unit identification and permeability prediction in lower cretaceous reservoir AEB_IIIG, Western Desert, Egypt

The primary objective of this study is to identify and analyze the petrophysical properties of the newly investigated AEB_IIIG member reservoir in Meleiha West Deep (MWD) Field and to classify it into different rock types. Additionally, this research intends to develop mathematical equations that may be utilized to estimate permeability in uncored sections of the same well or in other wells where core samples are unavailable. The analysis focused on the pore hole records of ten wells that were drilled in MWD Field. The reservoir levels were identified, and their petrophysical parameters were evaluated using well logs and core data. We were able to recognize seven different types of rocks (petrophysical static rock type 1 (PSRT1) to PSRT7) using petrography data, the reservoir quality index (RQI), the flow zone index (FZI), R35, hydraulic flow units (HFUs), and stratigraphy modified Lorenz (SML) plots. The analysis of the petrophysical data shows that AEB_IIIG has unsteady net pay thicknesses over the area. It has a range of 8–25% shale volume, 12–17% effective porosity, and 72–92% hydrocarbon saturation. The RQI results show that psrt1, psrt2 and psrt3 have a good reservoir quality as indicated by high R35 and helium porosity, respectively. They contribute with more than 75% of the reservoir production. The equation derived for each rock type of AEB_IIIG reservoir can be employed to forecast the permeability value distribution inside the reservoir.

A novel approach for quantifying upper reservoir leakage

During the operational phases of the upper reservoir in a pumped storage power station, the water level, leakage area, and hydraulic gradient of the upper reservoir alter dynamically due to the cyclic pumping and draining activities. The rising groundwater level during storage introduces distinct leakage conditions within the reservoir basin, characterized by unsaturated, partially saturated, and saturated states. Consequently, reservoir basin leakage exhibits variability across these states. To address this issue, this study formulated rational assumptions corresponding to the three leakage states in a reservoir basin and derived analytical expressions for seepage calculation based on Darcy's law and the principles governing groundwater flow refraction. A case study was conducted to investigate the relationship between various factors and leakage. The results showed that leakage primarily depended on the permeability of the impermeable layer in the reservoir basin. The upper reservoir leakage was estimated, and the calculated leakage generally agreed with the measurements, offering insights into the leakage mechanism of the Liyang pumped storage power station. In addition, the reasons for disparities between measured and calculated leakage were analyzed, and the reliability of the developed method was validated. The findings of this study provide a foundation for the seepage control design of upstream reservoirs in similar projects.

An improved transfer coefficient method considering the combined effect of reservoir level variation and rainfall and its application in the stability evaluation of multistage sliding ancient landslides

Abstract In this paper, by considering the dynamic water pressure and particle migration effect caused by reservoir level variation, the weakening effect of slip zone soil influenced by rainfall infiltration, and the interaction force between multistage sliding bodies, an improved transfer coefficient method for multistage sliding ancient landslide is proposed under the combined action of reservoir level variation and rainfall. The results show that (1) the combined action of reservoir level variation and rainfall has a significant influence on the stability of multistage sliding ancient landslides. (2) The sliding force calculated by the improved transfer coefficient method is smaller than the calculation result by the traditional transfer coefficient method, and the residual sliding force is larger. The different sliding body stability coefficient is reduced by about 28.84, 18.13, 19.26, and 21.01%, respectively. (3) The stability results calculated by the traditional transfer coefficient are higher than the improved transfer coefficient method, which may lead to deviation in the multistage sliding ancient landslide stable state judgment. (4) This improved transfer coefficient method can provide a reference for the multistage sliding ancient landslides stability accurate evaluation in hydropower station reservoir area.

Estimating and Assessing Monthly Water Level Changes of Reservoirs and Lakes in Jiangsu Province Using Sentinel-3 Radar Altimetry Data

Generating accurate monthly estimations of water level fluctuations in reservoirs and lakes is crucial for supporting effective water resource management and protection. The dual-satellite configuration of Sentinel-3 makes it possible to monitor water level changes with great coverage and short time intervals. However, the potential of Sentinel-3’s Synthetic Aperture Radar Altimetry (SRAL) data to enable operational monitoring of water levels across Jiangsu Province on a monthly basis has not yet been fully explored. This study demonstrated and validated the use of Sentinel-3’s SRAL to generate accurate monthly water level estimations needed to inform water management strategies. The monthly water levels of lakes and reservoirs from 2017 to 2021 were produced using Sentinel-3 level-2 land products. Results showed that, compared with in situ data across eight studied lakes, all lakes presented R (Pearson correlation coefficient) values greater than 0.5 and Root Mean Square Error (RMSE) values less than 1 m. Notably, water level estimates for Tai Lake, Gaoyou Lake, and Luoma Lake were particularly accurate, with R above 0.9 and RMSE below 0.5 m. Furthermore, the monthly water level estimates derived from the Sentinel-3 data showed consistent seasonal trends over the multi-year study period. The annual water level of all lakes did not change significantly, except for Shijiu Lake, of which the difference between the highest and lowest water level was up to about 5 m. Our findings confirmed the water level observation ability of Sentinel-3. The accuracy of water level monitoring could be influenced by internal water level differences, terrain features, as well as the area and shape of the lake. Larger lakes with more altimetry sampling points tended to yield higher accuracy estimates of water level fluctuations. These results demonstrate that the frequent, wide-area coverage offered by this satellite platform provides valuable hydrological information, especially across remote regions lacking in situ data. Sentinel-3 has immense potential to support improved water security in data-scarce regions.

Optimal selection of inversion method for gas-adsorption pore characterization of shales in Wufeng and Longmaxi Formation, Sichuan Basin

The pore space in gas shale spans multiple scales, ranging from nanometers to micrometers with an extremely complex structure and strong microscopic heterogeneity. Existing low-temperature gas adsorption (LTGA) pore size distribution (PSD) analysis models are based on the assumption of a one-dimensional tubular model and there is a lack of sufficient basis for selecting the most appropriate inversion model among the various types available. In this study, a comprehensive characterization of numerous samples from the Wufeng and Longmaxi Formation in the southern Sichuan Basin was conducted using different methods and inversion models. Based on multiple dimensions, such as fitting errors, the correlation between different methods including low-temperature CO2 adsorption (LTCA), nitrogen adsorption (LTNA), and large-scale mosaic Scanning Electron Microscopy (LAM-SEM), the most suitable one-dimensional models for LTCA and LTNA PSD analysis for the studied shale samples are determined. The simulation of gas condensation processes on LAM-SEM images yielded pore volume (PV) in the range of 32–48 nm comparable to the PV characterized by LTNA. Furthermore, the differences observed in PSDs between the gas condensation simulation procedure and the equivalent circular area diameter method indicate that irregular corner regions within larger pores are attributed to the volume of smaller-sized pores during gas adsorption characterization. It is revealed that the correlation between stitched surface area (SA) and maximum methane adsorption is stronger than individual characterizations, indicating that both micropores and mesopores contribute significantly to adsorption, and both characterization methods need to be employed to obtain SSA that influences methane adsorption. The research findings are helpful to the improvement of the multi-scale pore characterization level and evaluation of shale reservoirs.

It's not all about drought: What “drought impacts” monitoring can reveal

Drought impacts monitoring has been called the missing piece in drought assessment. The potential to improve drought management is high but uncertain due to rare analyses of impacts datasets, predominantly because there are few impacts monitoring programmes to generate the datasets. Drought impacts monitoring is conducted on the ground in much of Brazil by local observers at monthly and municipality scale to support the Brazilian Drought Monitor. In Ceará state, within drought-prone semiarid northeast Brazil, over 3600 drought impacts reports were completed by agricultural extension officers from 2019 to 2022. We investigated, through manual coding and observer interviews, the reported drought impacts and impact drivers. Analysis provided a catalogue of the experienced impacts and showed that impacts still occur, and are often normalised, during non-drought periods, sometimes as lingering effects of previous droughts. The impact drivers were predominantly non-extreme hydrometeorological conditions or a result of socio-technical vulnerabilities such as insufficient water infrastructure. The normalisation of “impacts” included, in particular: a generally accepted high level of crop losses and consistently low reservoir levels around which the agricultural and domestic systems are adapted. Conventional drought indices often did not align with experienced impact severity, highlighting the limitations of relying solely on these indices for emergency response. Continual impacts monitoring could be extremely valuable anywhere in the world for identifying vulnerabilities and informing proactive measures to reduce drought and other hazard risk, in addition to guiding targeted mitigation efforts.

A novel score system to evaluate carbonate reservoir combining microscale and macroscale parameters

The central Sichuan Basin, located in western China, holds great significance in terms of hydrocarbon production, especially in relation to complex carbonate reservoirs, notably the Qixia Formation of the Middle Permian epoch. However, the comprehensive evaluation of this geological formation presents considerable challenges due to complex lithology, limited availability of reservoir property data at various scales, inadequacies in data integration, and the absence of a reliable reservoir ranking system for development decision making. Previous studies primarily relying on conventional data at the reservoir level, such as well logs and geological information, have proven insufficient in accurately characterizing the reservoir. This is especially evident without precise lithological information and detailed knowledge of microscale properties, which are crucial for effective reservoir evaluation. To address these challenges, this study integrates advanced technologies like X-ray diffraction, micro-CT and scanning electron microscope (SEM) techniques in digital drill cutting analysis at the microscale. A novel scoring system has been developed using a prominent component analysis (PCA) approach and an expert scoring system, which incorporates existing conventional well log data and digital cutting analysis. This scoring system has been validated using actual production data, thus establishing a robust evaluation methodology for assessing the exploration potential and optimizing development strategies for carbonate gas reservoirs in the Qixia Formation. The innovative approach, which incorporates parameters at both micro- and macroscales, holds promising potential in facilitating future exploration and development efforts.

Creep deformation monitoring of landslides in a reservoir area

Effective utilization of reservoirs facilitates the distribution of water resources in both time and space, providing strong support for the sustainable growth of the economy and society. However, the periodic water level fluctuations of a reservoir during its operation may lead to geological hazards such as landslides. Here, we conducted a comparative analysis of the deformation processes of reservoir and non-reservoir landslides in the Jilintai area between 2017 and 2022 using Interferometric Synthetic Aperture Radar (InSAR) technology and wavelet analysis. Results show that more unstable locations were found on shaded slopes with a soil moisture of 6–10% than on sunny ones with a soil moisture of 15–19%. Both reservoir and non-reservoir landslides showed continuous and prolonged creep displacement over time. The deformation curve of the reservoir landslides displayed a step-like trend, whereas it was a linear trend without the discernible acceleration period for the non-reservoir landslides. Furthermore, the wavelet analysis revealed that the deformation of reservoir landslides follows a one-year period, almost synchrony with reservoir level changes. The results from this work deepen our understanding of kinematic processes of reservoir and non-reservoir landslides, which is crucial for reasonable and effective landslide monitoring and prevention.

Dam Breakdown and Response of Protection Dam, Case Scenarios of Mosul-Badush Dams, Northern Iraq

In this study, a program was built to simulate the sudden and complete collapse of the Mosul and Badush Dams behavior towards this collapse and predict the level at which the water will balance in the two dams after the collapse, compared to different levels at the Mosul Dam before the collapse. Two mathematical models were built as inputs to this program. The first predicted the water level in the Mosul Dam reservoir in terms of its storage volume before the collapse, and the second predicted the water level in the Badush reservoir after the collapse, according to the level in the Mosul reservoir before the collapse. For each collapse scenario, the program was organized according to sequential steps summarized assuming the water level in the Badush Dam reservoir when the level stabilizes, and from it determining the water volume in Badush reservoir based on the geometric analysis of the reservoir, then the volume of water transferred from Mosul reservoir to Badush reservoir, and thus the volume of water inside Mosul reservoir before the collapse. From the first mathematical model, the level of the Mosul Dam reservoir was determined before the collapse. The second mathematical model determined the level of the Badush Dam reservoir after the collapse. The results showed that the program has high flexibility in predicting what will happen in the Badush Dam reservoir after the collapse based on the water level in the Mosul Dam reservoir before it collapses and that the limits of the program's work extend from the minimum to the maximum level in Mosul Dam at which the failure can occur. Also, the storage volume in Mosul Dam will be distributed to the two reservoirs after the failure until the level stabilizes. Badush Dam, at a level of 330.4 m (a.s.l), can expand the maximum flood wave resulting from the total and sudden collapse of Mosul Dam at its maximum level of 333 m (a.s.l).

Marine Aluminum Phosphate–Sulfate Authigenesis as a Phosphorus Sink During Mid‐Proterozoic Oxygenation

AbstractEnhanced continental phosphorus input into the ocean has been suggested as a potential trigger for the transient oxygenation events during the mid‐Proterozoic; however, the response of phosphorus cycling to these marine oxygenations remains unclear. Here, we report the changes in phosphorus cycling associated with a ∼1.7 Ga transient oxygenation. Abundant authigenic aluminum phosphate–sulfate mineral svanbergite (SrAl3(PO4) (SO4) (OH)6; 8.02 ± 4.92 wt%) is identified within the ∼1.7 Ga Yunmengshan ironstones from the Xiong'er Basin, North China and other contemporaneous basins. This observation provides new evidence to support the suggestion that early diagenetic aluminum phosphate‐sulfate minerals could have represented a critical sink of marine phosphorus during the Proterozoic. We suggest that atmospheric oxygenation and concomitant changes in porewater redox chemistry may have enhanced the formation of early diagenetic phosphates, leading to a negative feedback on the oceanic phosphorus reservoir and atmospheric oxygen levels.

WITHDRAWN: Comparative Analysis of Asphaltene Deposition Methods : Stability indices, Stability plots, and Equation of state

Asphaltene deposition is one of the major problems that hinder hydrocarbon production. It can occur anywhere between the reservoir and the surface. Therefore, it is imperative that there be a procedure for minimizing the deposition of asphaltene in the production flow lines. There are several screening criteria that can be considered to determine the asphaltene deposition. This research will conduct a comprehensive study on different methodologies to determine the stability of asphaltene: the first category is the stability criteria using indices such as: the colloidal instability index (CII), the colloidal stability index (CSI), the stability index (SI), and the asphaltene stability predicting model (ANJIS). These four methods are used to predict the stability of asphaltene using SARA analysis. The fifth one is called modified CII which uses the compositions analysis of reservoir fluids, instead of SARA analysis, to determine the stability of asphaltene. The second method uses SARA Analysis to predict the stability via plots such as: Stankiewics plot (SP), De Boer plot, Sepulveda stability criterion (SCP). The third method is using compositional analysis of reservoir fluids and the equation of state model to predict the asphaltene onset pressure (AOP). In the last method Soave Redlich Kwong (SRK) equation of state model was used to predict asphaltene precipitations.In this work, a dataset of 166 was created which includes reservoir information, depth, compositional analysis, and SARA analysis. These data are used to study the potential of asphaltene deposition at the reservoir level. It was found that the stability criteria using indices and plots shows discrepancy in the results. The only two methods that show all the datasets are stable are the modified CII and the EOS model. As far as predicting asphaltene stability is concerned, the EOS method, based on compositional analysis and the thermodynamic model, appears to be the most reliable and trustworthy method. The other methods presented are observational rather than thermodynamic. Using these criteria is intended as a quick and fast estimate of the stability potential of asphaltene, not for planning or management of asphaltene deposition issues.

WITHDRAWN: A novel step function approach for reservoir operation to balance water storage and flood control during extreme rainfall events

Reservoir operation is crucial during extreme rainfall events which impact flooding and water supply. Simple models with upgraded operating rules can accurately simulate reservoir operations and used as a tool to investigate operations during extreme rainfall events. In this study, a step function for reservoir operation, that can be upgraded based on historical flood events, was developed and embedded with a simple box model. This model simplifies the simulation of controlled reservoir operation and can be integrated with hydrologic and hydraulic models for the assessment of the impacts of controlled reservoir operation. Chembarambakkam, a large water supply reservoir in Chennai city, India, was used to assess the performance of the developed model. The parameters of the box model were calibrated and validated with an error estimation of 11 and 13 % for inflow, 21 and 22% for outflow, and 15 and 16% for water level, respectively. Furthermore, a massive flood event that occurred in Chennai in 2015 was evaluated with various combinations of reservoir operations using the developed approach. The sensitivity analysis of the parameters shows that the initial water level in the Chembarambakkam reservoir plays a substantial role in balancing water supply and flood mitigation. Restraining initial water levels from 50 to 75 % of storage helps to reduce the flood peaks from 14 to 38 % and inundation extents by 3.19 to 5.18 km2 besides the reliable storage of 81.50 % for water supply. Thus, the proposed box model was proven to be useful in controlled reservoir operation during extreme rainfall events.

Withdrawn: A novel step function approach for reservoir operation to balance water storage and flood control during extreme rainfall events

Reservoir operation is crucial during extreme rainfall events which impact flooding and water supply. Simple models with upgraded operating rules can accurately simulate reservoir operations and used as a tool to investigate operations during extreme rainfall events. In this study, a step function for reservoir operation, that can be upgraded based on historical flood events, was developed and embedded with a simple box model. This model simplifies the simulation of controlled reservoir operation and can be integrated with hydrologic and hydraulic models for the assessment of the impacts of controlled reservoir operation. Chembarambakkam, a large water supply reservoir in Chennai city, India, was used to assess the performance of the developed model. The parameters of the box model were calibrated and validated with an error estimation of 11 and 13 % for inflow, 21 and 22% for outflow, and 15 and 16% for water level, respectively. Furthermore, a massive flood event that occurred in Chennai in 2015 was evaluated with various combinations of reservoir operations using the developed approach. The sensitivity analysis of the parameters shows that the initial water level in the Chembarambakkam reservoir plays a substantial role in balancing water supply and flood mitigation. Restraining initial water levels from 50 to 75 % of storage helps to reduce the flood peaks from 14 to 38 % and inundation extents by 3.19 to 5.18 km2 besides the reliable storage of 81.50 % for water supply. Thus, the proposed box model was proven to be useful in controlled reservoir operation during extreme rainfall events.

Water quality assessment, possible origins and health risks of toxic metal(loid)s in five cascade reservoirs in the upper Mekong

The Mekong River holds significant importance as a transnational water system within the Asian region. This study investigated the pollution characteristics, origins, and health risks associated with eighteen toxic metal (loid)s (TMs) across various depths in five cascade reservoirs located in the upper Mekong. The findings revealed that naturally sourced TMs (As, Cd, Li, Mo, Sb, and Sr) exhibited elevated levels in upstream reservoirs due to the interception effects of cascade dams. Anthropogenically sourced TMs (Co, Cu, Ni, Pb, and Zn) showed heightened concentrations in downstream reservoirs, linked to increased human activities in the downstream region. In deep-water reservoirs, the vertical distribution of redox-sensitive elements was influenced by thermal stratification, with concentrations of As, Cs, Li, Mo, Rb, Sr, and U notably higher in the hypolimnion than the epilimnion. Importantly, the concentrations of all elements in these cascade reservoirs meet Chinese and WHO drinking water standards. Water quality index (WQI: 9.2–19.1), heavy metal evaluation index (HEI: 0.96–1.37), and Nemerow index (NI: 0.35–0.56) confirmed the commendable quality of the cascade reservoir waters. The health risk assessment identified As, Sb, U, and Tl as primary contributors to non-carcinogenic risks in the cascade reservoirs. In the context of a series of cascade dams along this substantial river, this research establishes a solid foundation for preventing TM pollution and ensuring the long-term sustainability of water resources.

Structural inheritance through 3D reservoir modeling and ant-tracking attribute implications for structural configuration of Upper Cretaceous Pab Sandstone, Kirthar Fold Belt, Pakistan

This research presents a comprehensive investigation to enhance understanding of subsurface structural complexities within the Upper Cretaceous Pab Sandstone reservoir level in a gas-producing field within the Kirthar Fold Belt of the Southern Indus Basin, Pakistan. The seismic interpretation for accurate structural delineation and characterization of intricate fault systems is often challenging in Fold and Thrust Belt settings. The 3D structural maps of Upper Cretaceous Pab Sandstone at the reservoir level and the application of the ant-tracking attribute for fault extraction improve the structural understanding of the gas-producing field in the Kirthar Fold Belt in the Southern Indus Basin, Pakistan. Attribute-assisted 3D seismic interpretation has revealed several subsurface structure elements, including a large thrusted anticline extended towards the north-south, the pattern of north-south oblique ramp thrusts on the southeastern flank, and a combination of easterly vergent thrusts with a counter-back thrust creating a local pop-up structure in the area. A 3D structural model at the reservoir level was generated using horizon and fault framework volume-based modeling approach, serving as a structural model for Pab sandstone. The structural smoothing, variance and ant-tracking attribute were applied iteratively to get the best results and correlated with manual interpretation. 3D seismic interpretation and application of ant-tracking for fault extraction identifies discrete structural styles and revealed that all thrusting occurred due to compressional tectonics of the Plio-Pleistocene period. The apparent different styles result from the reactivation of earlier extensional fault systems and probably during phased periods of compression. The resulting 3D reservoir model can be used as an input to populate petrophysical properties and results can be extended for future field development plans. Integration of well and 3D seismic data interpretation and the application of automatic fault extraction techniques are highly recommended in structurally complex areas and have an equal implication for worldwide basins with similar conditions for reliable structural interpretation in Fold and Thrust Belts with structural complexity.

Effects of the maximum flow ramping rates on the long-term operation decisions of a hydropower plant

This paper presents a study on the influence of maximum ramping rates (MRR) on the annual operation of a real hydropower plant. For this purpose, an annual optimization model based on incremental dynamic programming (IDP) with weekly steps is used, each step being evaluated by mixed integer linear programming (MILP) on an hourly basis. The model considers hourly water inflows and energy prices, limits on reservoir level and water discharge, power generation dependence on the available head, wear and tear costs of hydro units caused by power variations, start-up and shut-down costs of hydro units, and minimum environmental flows and maximum ramping rates. The main contribution of the proposed model is the consideration of the released flow as a second state variable to define the state diagram of the problem, with the aim of guaranteeing the continuity of flow between consecutive weeks and thus the fulfilment of MRR. The results obtained in a case study with a real plant are discussed. The inclusion of the released flow as state variable does not show a significant impact in the estimated annual revenue, but certain differences observed in some periods of the year might justify its consideration in shorter time horizons.

Phreatic Line Calculation of Reservoir Landslide under Complex Hydraulic Conditions—A Case Study

A seepage field, influenced by rainfall and reservoir water level fluctuation, is closely associated with the stability of the reservoir landslide. Understanding the phreatic line variation inside the landslide is of significant importance for the analysis and evaluation of slope stability. Currently, most of the boundaries of phreatic line analytical models and the hydrological conditions are simplified, resulting in discrepancies between the outcomes derived from these models and the actual situation. Given this, the newly proposed analytical model is refined by addressing the following two issues. Firstly, the consideration of variable-speed reservoir level fluctuations is incorporated, and secondly, the reservoir bank within the water-level fluctuation zone is treated as non-vertical. Under the combined effect of reservoir water level fluctuation and rainfall, the Boussinesq Differential Equation of unsteady seepage is established and applied to the Majiagou landslide in Three Gorges reservoir area. The results of the analytical solution are basically consistent with the measured groundwater level results, which has demonstrated the accuracy of the proposed model. Consequently, the proposed model can quickly and accurately calculate the groundwater level of landslides, which provides an effective means for the prediction and early warning of reservoir landslides.

Spatiotemporal deformation characteristics of Outang landslide and identification of triggering factors using data mining

Since the impoundment of Three Gorges Reservoir (TGR) in 2003, numerous slopes have experienced noticeable movement or destabilization owing to reservoir level changes and seasonal rainfall. One case is the Outang landslide, a large-scale and active landslide, on the south bank of the Yangtze River. The latest monitoring data and site investigations available are analyzed to establish spatial and temporal landslide deformation characteristics. Data mining technology, including the two-step clustering and Apriori algorithm, is then used to identify the dominant triggers of landslide movement. In the data mining process, the two-step clustering method clusters the candidate triggers and displacement rate into several groups, and the Apriori algorithm generates correlation criteria for the cause-and-effect. The analysis considers multiple locations of the landslide and incorporates two types of time scales: long-term deformation on a monthly basis and short-term deformation on a daily basis. This analysis shows that the deformations of the Outang landslide are driven by both rainfall and reservoir water while its deformation varies spatiotemporally mainly due to the difference in local responses to hydrological factors. The data mining results reveal different dominant triggering factors depending on the monitoring frequency: the monthly and bi-monthly cumulative rainfall control the monthly deformation, and the 10-d cumulative rainfall and the 5-d cumulative drop of water level in the reservoir dominate the daily deformation of the landslide. It is concluded that the spatiotemporal deformation pattern and data mining rules associated with precipitation and reservoir water level have the potential to be broadly implemented for improving landslide prevention and control in the dam reservoirs and other landslide-prone areas.