Waterflood Management Research Articles

ExtendinG SUb-DAily River Discharge data over INdia (GUARDIAN).

River discharge information is crucial for various applications, but the measurement process often remains impeded by factors that hinder near real-time (NRT) data availability in India. However, leveraging telemetry-based water surface elevation (WSE) data across the country provides an opportunity to convert it into river discharge. This conversion is made possible by utilizing rating curves (RCs) derived from historical collocated measurements of WSE and discharge. In this study, NRT WSE from the Central Water Commission (CWC) flood portal is obtained via the web-scraping tool. Through the application of RCs, discharge data is extended across 210 gauging stations in India from the year 2020 to the present, encompassing sub-daily discharge during the non-monsoon and hourly discharge series during monsoon (June-September) across the Indian rivers. Annually, the study generated over 800,000 discharge data points for Indian rivers, accounting for more than 4000 discharge measurements per station annually. These comprehensive datasets provide valuable insights for water resource and flood management research, offering NRT access to WSE, and discharge, along with the local RCs.

Parameter Estimation of the Inverted Kumaraswamy Distribution by Using L-Moments Method: An Application on Precipitation Data

Modeling precipitation data plays a critical role in water resource and flood management. Statistical distributions are frequently used in describing hydrological variables. Different distributions and estimation methods have been presented in previous studies for modeling precipitation data. In this study, the inverted Kumaraswamy distribution is considered for its advantageous properties, and the L-moments and maximum likelihood methods are employed in estimating the parameters of the inverted Kumaraswamy distribution. In the application part, the annual maximum monthly precipitations recorded in the Rize, Türkiye are modeled with the inverted Kumaraswamy distribution. To the best of the author’s knowledge, the L-moment method is considered for the first time to estimate the parameters of the inverted Kumaraswamy distribution. In addition, the efficiencies of the estimation methods are compared with a Monte-Carlo simulation study. For evaluating the performances of the estimation methods, the goodness of fit criteria including root mean square error, Kolmogorov Smirnov test, and coefficient of determination (R^2) are used in the application part of the study. The results show that for the data considered, the L-moments method yields more accurate results than the maximum likelihood method in estimating the parameters when the sample size is small. Accordingly, the corresponding distribution with L-moments estimations provides a better fit to precipitation data obtained from the Rize station.

REVIEW AND COMPARATIVE STUDY OF HYDROLOGICAL MODELS FOR RAINFALL-RUNOFF MODELLING

Water is considered as an important resources for human existence on the earth. In order to simulate or optimized hydrological data for various water resources management, several hydrological models are very useful to attain this aim for water resources management and as a decision support tools. A rainfall-runoff model is a quantitative prototype explaining the rainfall-runoff interactions at basin scale. The hydrological models have peculiarities in terms of capabilities for various water resources management. This paper tends to reviewed over fifty (50) papers that are peculiar to hydrological models as applicable to rainfall-runoff modeling. It involved evaluating and comparing different hydrological models used in simulating rainfall process converting into surface runoff for water use efficiency. Several runoff models such as Hydrologic Engineering Center - Hydrologic Modeling System (HEC-HMS), Soil and Water Assessment Tool (SWAT), Precipitation-Runoff Modeling System (PRMS), Variable Infiltration Capacity model (VIC), LISt-based Erosion Model (LISEM), MIKE Surface Water - Groundwater Hydrology (MIKE SHE) and Runoff Prophet were critically assessed. Rainfall-runoff models are globally utilized for different applications to enhance water use efficiency across different sectors. However, types of hydrological models by examining various hydrological models, model accuracy by evaluating the accuracy and reliability of each model in predicting runoff from rainfall data, scope of applications by determining the adequacy of the models for numerous geographical regions and climatic circumstances, complexity and usability by assessing the complexity of the models, their data requirements, ease of use and computational efficiency, also the models advantages and limitations in capturing the dynamics of the rainfall-runoff process were critically assessed. This was to aid modeling objectives. It was inferred that HEC-HMS is widely applied for modelling precipitation-runoff processes in watersheds of various sizes, aiding in flood forecasting, reservoir operation, and water management for agricultural and urban water use efficiency. SWAT is used for assessing the impact of land management practices (e.g., crop rotation, irrigation, land use changes) on water resources, including runoff generation and water quality, thus optimizing water use efficiency in agriculture. PRMS is applied to model the transport of water via complex hydrological systems, aiding in watershed management and water use efficiency assessments. In conclusion, this comparative review seeks to guide water scientists, the users of hydrological models and hydrological engineers in selecting the most suitable models for their specific modelling needs for sustainable water resources management.

Design of Rain Water Harvesting System for Efficient Water Scarcity and Flood Management in India

Areas experiencing extensive floods during the rainy season and water scarcity in winter require efficient water resource management. Economical water-harvesting structures such as drystone masonry and upstream-wall cement masonry, with heights ranging from 1 to 2.5 meters, are constructed for catchments smaller than 10, 10 to 20, and 20 to 30 hectares, respectively, utilizing locally sourced materials. These constructions offer significant cost-effectiveness for the location, boasting a B:C ratio of 3.5:1. In certain areas of Assam, Garh structures are constructed, featuring large and lengthy embankments on both sides with an open central section for water flow. Within paddy fields, the entire area is partitioned into small square segments, creating small embankments known as "Dara." which store rainwater for cultivation. Across the entire Western Himalayan region, encompassing Jammu, Himachal Pradesh, and Northern Uttaranchal, Guhl serves as a standardized water harvesting technique. Notably, in Akola and Chittoor districts, the establishment of farm ponds has significantly boosted crop and livestock productivity, along with farm income. Additional irrigation has notably enhanced the yield of various rainfed crops such as pigeon pea, chickpea, groundnut, cotton, and vegetables, as well as mango and coconut plants, with improvements ranging from 5 to 72%. With the availability of harvested rainwater for supplemental irrigation, farmers have also planted additional fruit trees, resulting in increased productivity of existing fruit trees, such as mango (39%) in Chittoor district and coconut (51%) in Vellore district. Expanding the number of rainwater harvesting structures could potentially reduce runoff within the basin by up to 60%. The implementation of Doha Models, involving percolation tanks dug along the length of lower-order seasonal streams in Jalna district of Maharashtra, has increased cropping intensity from 129% to 132%. Remarkably, five out of seven crops have demonstrated a relatively higher percentage increase in yields. The optimal productivity of harvested water is achieved when efficient application methods such as micro-irrigation are employed, targeting high-value crops.

Assessment of CMIP6 GCMs for selecting a suitable climate model for precipitation projections in Southern Thailand

The selection of General Circulation Models (GCMs) is critical due to computational limitations and underlying uncertainties. This study provides a comprehensive assessment of three bias correction (BC) methods, namely the delta change method (DT), quantile mapping (QM), and empirical quantile mapping (EQM). Utilizing precipitation data from 30 observation stations across Southern Thailand, the evaluation encompasses five CMIP6 GCM models (CAMS-CSM1-0, CanESM5, CNRM-CM6-1, CNRM-ESM2-1, IPSL-CM6A-LR). Evaluation metrics, root mean square error (RMSE), mean absolute error (MAE), Pearson's correlation (r), index of agreement (d), and mean bias error (MBE) are employed to assess BC methods. Evaluation measures suggest that the DT method outperforms EQM and QM, with higher accuracy and lower errors (DT: RMSE = 3.61, MAE = 2.32; EQM: RMSE = 3.82, MAE = 3.70). Taylor diagrams show that CNRM-ESM2-1 has the highest correlation across sites (r = 0.36), albeit with a wider dispersion, while CanESM5 has a more balanced performance. Significant annual precipitation increases are projected for different spans 2021-30, 2061-70, and 2091–2100, particularly under SSP585, which will influence flood risk, water management, and climate adaptation. Future projections with SSP585 continuously projecting a larger probability of increased precipitation. The DT method is recommended for the downscaling of CMIP6 GCMs for precipitation projections in Southern Thailand, recognizing its superior performance. The study's findings provide a foundation for informed decision-making and adaptation planning in southern Thailand, urging policymakers to prioritize climate resilience and adaptation strategies while using a multi-model ensemble approach for robust climate forecasts.

Optimizing Residential Construction Site Selection in Mountainous Regions Using Geospatial Data and eXplainable AI

The rapid urbanization of Abha and its surrounding cities in Saudi Arabia’s mountainous regions poses challenges for sustainable and secure development. This study aimed to identify suitable sites for eco-friendly and safe building complexes amidst complex geophysical, geoecological, and socio-economic factors, integrating natural hazards assessment and risk management. Employing the Fuzzy Analytic Hierarchy Process (Fuzzy-AHP), the study constructed a suitability model incorporating sixteen parameters. Additionally, a Deep Neural Network (DNN) based on eXplainable Artificial Intelligence (XAI) conducted sensitivity analyses to assess the parameters’ influence on optimal location decision making. The results reveal slope as the most crucial parameter (22.90%), followed by altitude and land use/land cover (13.24%), emphasizing topography and environmental considerations. Drainage density (11.36%) and rainfall patterns (9.15%) are also significant for flood defense and water management. Only 12.21% of the study area is deemed “highly suitable”, with “no-build zones” designated for safety and environmental protection. DNN-based XAI demonstrates the positive impact of variables like the NDVI and municipal solid waste generation on site selection, informing waste management and ecological preservation strategies. This integrated methodology provides actionable insights for sustainable and safe residential development in Abha, aiding informed decision making and balancing urban expansion with environmental conservation and hazard risk reduction.

Wave Loads On Hydraulic Structures

Hydraulic structures are essential for flood protection, water management and navigation in coastal, delta and lake regions. Their importance will continue to grow in the coming years and decades, because of two main factors. Firstly, because of the consequences of climate change and sea level rise. Secondly, because of the continuous development and urbanization of coastal, delta and lake regions, with an increase in the value of the assets and activities in those locations combined with more strict safety requirements. Those factors will lead to the construction of a series of new hydraulic structures and the renovation of several existing structures around the world. Wave loads acting on such hydraulic structures are crucial for their design and safety assessment. This study addresses two different types of wave loads acting on hydraulic structures: confined wave impact loads and bimodal wave loads. To this end, a series of laboratory experimental test campaigns were carried out in a wave flume.

Submerged flow over various shapes of piano key weir

The weir, an essential element of dams utilized for floodwater management, plays a crucial role in human life. Over the years, nonlinear weirs have advanced into Piano Key Weirs (PKWs). These PKWs provide enhanced discharge efficiency, a reduced structural footprint, and heightened cost-effectiveness. PKWs possess a sophisticated structure defined by numerous geometric parameters. The impact of these parameters on the discharge capacity is of paramount significance. This study aims to experimentally investigate the hydraulic of submerged PKWs with different plan shapes, including triangular, trapezoidal, and rectangular, with apex width to cycle width ratio of (A/w) of 0, 0.25, and 0.5, and magnification ratio (B/w) of 1, 2, and 3, respectively. The results indicate that submergence depends on the shape and size of the PKW. Furthermore, the efficiency of the PKW increases as the ratio of approach flow head to weir height (Ho⁄P) decreases and B⁄w increases. The influence of the shape of the PKW on the performance of the weir is more pronounced at higher values of B/w. Additionally, the order of the highest discharge coefficient values follows a pattern from the trapezoidal to triangular and rectangular PKWs. Specifically, for B⁄w = 2, the trapezoidal PKW exhibits an approximate improvement of 6 and 15 % in the discharge efficiency compared to the triangular and rectangular PKWs, respectively. A new equation was developed to predict the discharge coefficient for different shapes of PKWs under various hydraulic conditions. Based on the experimental data, this study offers valuable insights into the hydraulic behavior and discharge coefficient of PKWs. This research significantly contributes to enhancing our understanding and optimizing the performance of submerged PKWs in water management systems.

Developing Rainfall Intensity- Frequency- Duration Curves for Three Selected Sites in the Kurdistan Region, Iraq

Developing Rainfall Intensity- Frequency- Duration Curves for Three Selected Sites in the Kurdistan Region, Iraq

Storm water management model to evaluate urban inundation in Lowokwaru and Blimbing sub-catchments in the city of Malang

In the city of Malang, which is a highland area, there are still floods, including Blimbing and Lowokwaru sub-districts. One of the causal factors is the change of undeveloped areas becoming relatively large built-up areas in the Upper Brantas sub-watershed, from initially 20.5% in 2000 to 69.6% 20 years later. This change also impacts the transformation of irrigation canals that once irrigated rice fields, causing them to shift their function into drainage channels that carry runoff water toward natural channels (natural drainage). Consequently, the existing canal conditions cannot accommodate the runoff water. The research employed an approach that involved analyzing floodwater management models using the Storm Water Management Model (SWMM 5.1) and surveying existing canal data. The analysis results revealed that, within the studied areas of Blimbing Village and the Blimbing Catchment Area, 10 out of the existing 170 drainage channels were incapable of handling the discharge associated with rainfall intensities designed for return periods of 5 years (112.48 mm/day) and ten years (117.09 mm/day). In the Lowokwaru Catchment Area, it was evident that 18 out of the 216 existing canals experienced overflow events with designed flood discharge for 5-year and 10-year periods.

Advancing real-time error correction of flood forecasting based on the hydrologic similarity theory and machine learning techniques

Real-time flood forecasting is one of the most pivotal measures for flood management, and real-time error correction is a critical step to guarantee the reliability of forecasting results. However, it is still challenging to develop a robust error correction technique due to the limited cognitions of catchment mechanisms and multi-source errors across hydrological modeling. In this study, we proposed a hydrologic similarity-based correction (HSBC) framework, which hybridizes hydrological modeling and multiple machine learning algorithms to advance the error correction of real-time flood forecasting. This framework can quickly and accurately retrieve similar historical simulation errors for different types of real-time floods by integrating clustering, supervised classification, and similarity retrieval methods. The simulation errors “carried” by similar historical floods are extracted to update the real-time forecasting results. Here, combining the Xin'anjiang model-based forecasting platform with k-means, K-nearest neighbor (KNN), and embedding based subsequences matching (EBSM) method, we constructed the HSBC framework and applied it to China's Dufengkeng Basin. Three schemes, including “non-corrected” (scheme 1), “auto-regressive (AR) corrected” (scheme 2), and “HSBC corrected” (scheme 3), were built for comparison purpose. The results indicated the following: 1) the proposed framework can successfully retrieval similar simulation errors with a considerable retrieval accuracy (2.79) and time consumption (228.18 s). 2) four evaluation metrics indicated that the HSBC-based scheme 3 performed much better than the AR-based scheme 2 in terms of both the whole flood process and the peak discharge; 3) the proposed framework overcame the shortcoming of the AR model that have poor correction for the flood peaks and can provide more significant correction for the floods with bad forecasting performance. Overall, the HSBC framework demonstrates the advancement of benefiting the real-time error correction from hydrologic similarity theory and provides a novel methodological alternative for flood control and water management in wider areas.

Long-term natural streamflow forecasting under drought scenarios using data-intelligence modeling

Long-term river streamflow prediction and modeling are essential for water resource management and decision-making related to water resources. This research paper considers the importance of these predictions and proposes a model to address scarcity scenarios to support decision-making in water allocation, flood management, and drought prediction scenarios. Machine learning (ML) techniques offer promising alternatives for improving long-term streamflow prediction. However, most existing studies on ML models for streamflow prediction have focused on shorter time horizons, limiting their broader applicability. Consequently, there is a need for dedicated research that addresses the use of ML models in long-term streamflow prediction. Considering this research gap, this paper presents an ML-based approach that learns and replicates the natural flow dynamics of a river, allowing for the simulation of reduced flow scenarios (25 % and 50 % reduction). This capability allows for simulating drought scenarios of varying severity, providing valuable insights for water service managers. This study significantly contributes to the progress of predicting long-term river streamflow through the application of machine learning models. Moreover, this study offers valuable insights and recommendations for hydrologists to improve future research efforts.

The hydraulic network of the pre-Hispanic city of Tiwanaku (Bolivia): New insights from the integration of canal morphology, hydrogeological and palaeoenvironmental data

Water management enabled the development of ancient societies allowing them to ensure agropastoral production and manufacturing activities. In the Andes, near the shore of Lake Titicaca, the city of Tiwanaku (Bolivia) is one of the largest pre-Hispanic urban centres in South America. Abrupt climate changes in the high-altitude Altiplano during the late Holocene likely forced the population to develop water management strategies. So far, knowledge concerning the existence of a water network around the city of Tiwanaku is limited to hypotheses derived from surface and aerial observations. In this study, geoscience techniques (morphology, geophysics, sedimentology and chronostratigraphy) helped to reconstruct the canals' morphology and their flow dynamics, along with their chronology of operation in a context of hydroclimatic change. Two ca. 30 m large canals bypassing the monumental core and supplied by a shallow water table and multiple tributaries, connected the agricultural and the urban areas. The structure and organization of the network testify to an elaborate knowledge of the local hydrology by the former builders of the city. It ensured water supply and flood management in relation to the extreme intra- and inter-annual variability of precipitations in the central Andes. The palaeogeographical and landscape reconstruction demonstrates that canals were set from natural features during the early Late Formative period (200 BCE to 200 CE) during a wet period likely for water resource management needs. During the Tiwanaku state (before 800 CE), the filling of the canal network with soil and sediment suggests a major change in its use, and possibly its partial abandonment, during a major restructuration of the site, in a period of increased regional precipitation.

Slurry walls in flood mitigation and water management

Slurry walls in flood mitigation and water management

WATERFLOOD EFFICIENCY ASSESSMENT USING REGRESSION ANALYSIS

For quick waterflood efficiency assessment at oil fields, methods of visual analysis of the operating indicators of production and injection wells without calculating its quantitative characteristics are widely used. Thus, the development of analytical methods for calculating the effectiveness of measures taken on the injection wells is an urgent task.
 The aim of the work is to improve the quality of the waterflood management process by developing an algorithm for quick assessing the additional oil production from geological and technical activities at injection wells.
 To achieve this aim, regression analysis methods, genetic optimization methods, and methods of mathematical modeling of operating indicators using decline curves and displacement characteristics were used.
 The authors proposed an algorithm for quick assessing the effectiveness of injection sites, which allows, using Data Science methods, to quantify additional oil production after carrying out geological and technical measures at injection wells.

Co-production of nature’s contributions to people in dry rivers: a case study in Murcia, Spain

ABSTRACT Dry rivers are non-perennial rivers with no surface water in their channels except after heavy rainfall or snowmelt. The lack of water flow is often associated with a low provision of Nature’s Contributions to People (NCP) and a poor quality of life. However, recent review studies have found evidence of human communities thriving in dry rivers through the co-production of multiple NCP, although no case studies have yet confirmed this evidence. We assessed the capacity of dry rivers and their associated social systems to provide NCP. We selected three dry rivers with high natural, cultural and landscape values in the most arid part of Murcia (Spain). We interviewed 37 representatives of the most influential social groups in the study area to explore the NCP of dry rivers, their synergies and trade-offs. Four material, three non-material and eight regulating NCP were identified, as well as one unique NCP: access to villages and fields through dry riverbeds. Fifty-two synergies were identified, especially between material and non-material NCP, and eight trade-offs. This wide range of NCP and synergies is a consequence of the co-production processes between dry rivers and the social system. NCP co-production seems to be underpinned by the indigenous and local knowledge acquired by the social system over generations about the management of floodwaters, biodiversity and geodiversity. Incorporating this knowledge into research and governance can help raise awareness of the NCP provided by dry rivers and help develop strategies for mitigating and adapting to global change.

Robust waterflood optimization under geological uncertainties using streamline-based well pair efficiencies and assimilated models

Effective management of waterflooding requires optimization of injection and production rates. However, nominal optimization methods based on a single realization can result in suboptimal hydrocarbon recovery and sweep efficiency due to reservoir heterogeneity. To account for geological uncertainties, this paper proposes a streamline-based robust rate optimization that iteratively adjusts well rates of each realization using a joint well pair rate multiplier calculated from optimal interpolation method. This optimization process is applied over time intervals until the end of field life. The effective and robustness of this approach are validated using a 2D synthetic case and then applied to Brugge benchmark case. For each application, we generate 100 history-matched geological realizations, evenly split into 50 for training and 50 for testing purposes. Robust optimization is employed on the complete training dataset to derive an optimal schedule that maximizes the expected oil across all realizations. Simultaneously, nominal optimization is individually applied to each training realization to establish an optimal schedule specific to each instance. Subsequently, both the robust optimization schedule and the nominal optimization schedules are applied to the testing dataset to assess and compare their effectiveness. Results indicate that the streamline-based rate allocation optimization effectively adjusts well rates based on well-pair efficiency. The robust optimized schedule takes into account geological uncertainties and enhances cumulative oil production, even if it doesn't consistently outperform the nominal optimized schedules. Overall, this approach provides an effective way to optimize waterflooding management under geological uncertainties.

Climate stress impacts on the reservoir inflows: a decision-scaling and IHACRES modeling approach in South Korean basins

Abstract This study employed the Decision-Scaling (DS) approach and the IHACRES (Identification of unit Hydrographs And Component flows from Rainfall) long-term runoff model to investigate the impact of composite changes in rainfall and temperature on dam inflows at Chungju dam, Yongdam dam, Hapcheon dam, and Seomjingang dam basins. By analyzing flow regimes, rainfall scenarios, and temperature scenarios, the study revealed crucial insights into dam inflow and its response to climate stressors. The findings demonstrated that the rate of inflow increase in the study basins exceeded the rate of rainfall increase, indicating the significance of basin storage effects in contributing to runoff generation. The analysis of rainfall changes by quantile highlighted the dominant influence of the upper-high (UH) rainfall quantile, which led to higher flood inflow compared to other quantiles. Furthermore, scenarios with different rainfall patterns were compared, showcasing the predominant impact of UH quartile rainfall on the total inflow variation. The study also analyzed the runoff ratio, finding that changes in precipitation proportionally affected the runoff ratio. Overall, these insights contribute to understanding the sensitivity of dams to changes in rainfall and temperature, facilitating the development of strategies for sustainable water supply and flood management in dam systems.

Advances in Monitoring and Understanding the Dynamics of Suspended-Sediment Transport in the River Drava, Slovenia: An Analysis More than a Decade-Long

Managing sediment transport in streams is crucial to the surface water resource development strategy and has several implications for flood risk and water management, hydropower use, and balancing river morphology. This paper summarises the movement and behaviour of suspended sediment within the Slovenian portion of the River Drava, covering a span of thirteen years from 2005 to 2018. An analysis of relevant data collected during this period is also presented. Suspended-sediment dynamics strongly depend on flow velocity, seasonal variations in sediment sources, and human interventions in the riverbed. The transportation of material in the River Drava results in the accumulation of sediments in reservoirs and riverbeds, consequently impeding the natural hydrological cycle by reducing the outflow into aquifers. The 2018 high-water event is analysed in terms of the dependence of concentration of suspended sediments on discharge, where counterclockwise hysteresis was observed, providing an essential clue to the origin of sediment. Sediments from the River Drava in Slovenia are managed with some conventional processes and are mainly deposited or reintegrated into rivers and aquatic ecosystems. Some additional sediment management strategies with long-term solutions for efficient and comprehensive water management, hydropower, and ecological problems are proposed.

Green Infrastructure: Flood Control and Water Management

Water scarcity is a pressing issue in many parts of the world. One innovative solution to this problem is rainwater harvesting, which involves collecting and storing rainwater for later use. The study aims to install a rainwater harvesting and treatment system to :1. Reduce water loss by its running-off.2 Meeting the demands of increasing water. 3. Reducing groundwater contamination.4. Increase available water during dry season.5. Reduce flooding and potentially prevent flooding of roads. This is a descriptive research method and is purely qualitative. It used Focus Group Discussion (FGD), Interview, and secondary data to get the necessary information from three Consultants, three Executives, and four Professors who are experts in the field. The study found that the rainwater harvesting and treatment facility would be a feasible project. It would minimize water consumption costs and reduce flooding in the city, with potential for replication by other universities, governments, and private entities.