Variations In Inflow Research Articles

Electrocoagulation for nickel, chromium, and iron removal from mine water using aluminum electrodes

High global demand for nickel metal has contributed significantly to the growth of the nickel mining industry in Indonesia. This growth has a positive multiplier effect on the economy, with the potential to affect aquatic life and humans owing to the high levels of chromium, nickel, and iron in mine water. Therefore, this study aims to develop an electrocoagulation (EC) reactor to remove nickel, chromium, and iron from mine water. This study used a continuous reactor and aluminum electrodes with variations in current density (3.378, 6.757, and 10.135 mA/cm2) and inflow (0.3, 0.5, and 1 L/min). The results showed that the operating scenario with a current strength of 6 A and an inflow of 0.3 L/min had a removal efficiency of 86.89 % nickel, 99.51 % chromium, and 80.61 % iron with a charge loading value of 11,194 F/ma3 and Reynolds number of 39. These results are expected to provide valuable information for the development of an effective EC technology, thereby demonstrating its potential for the removal of metals from nickel mine water.

Observed Pathways and Interannual Variability of the Warm Inflow Onto the Continental Shelf in the Southern Weddell Sea

AbstractModel projections suggest that the continental shelf in the southern Weddell Sea may experience a shift from today's near‐freezing temperature to a much warmer state, where warm water floods the shelf and basal melt rates beneath the Filchner Ronne Ice Shelf increase dramatically. Today, the Filchner Trough serves as a conduit for the southward flow of Warm Deep Water (WDW) during summer and, thus, requires continuous monitoring of its hydrographic conditions. An extensive network of moorings was installed at key sites along the inflow pathway from 2017 to 2021, to expand on existing mooring records starting in 2014. The moorings complemented with under‐ice profiling floats reveal two inflow pathways, where WDW enters along the eastern flank of the Filchner Trough as well as through a smaller trough east of there. Within the observed period, 2017 and 2018 feature anomalously warm inflows. The inflow is regulated by the heaving of isopycnals over the continental slope, and the southward propagation toward Filchner Ice Shelf is two times faster during these warm years. Furthermore, the warm years coincide with low summer sea ice concentration, which enhances surface stratification through increased freshwater input and modifies sea ice‐ocean stresses that both act to lift the warm water layer and increase the temperatures on the continental shelf. Finally, the recent record low sea ice conditions around the Antarctic emphasize the importance of our findings and raise concerns regarding a potentially increasing presence of WDW on the southern Weddell Sea shelf.

What drives the distinct evolution of the Aral Sea and Lake Balkhash? Insights from a novel CD-RF-FA method

Study RegionThe Aral Sea and Lake Balkhash. Study FocusThis study explores the impacts of climate change and human activities on the inflow of the Aral Sea and Lake Balkhash, revealing the different driving factors behind the evolution of inland lakes in arid environments. To achieve this, we propose a novel approach that combines classical seasonal decomposition with Random Forest and Factor Analysis (CD-RF-FA) to quantitatively assess the influences of climate change and human activities on lake inflow. New Hydrological Insights for the RegionDuring the period from 1960 to 1990, anthropogenic factors predominantly influenced the inflow to the lakes, contributing 89.9 %, 91.8 %, and 91.6 % to the Lake Balkhash Basin (BAK), the Syr Darya Basin (SYR), and the Amu Darya Basin (AMU), respectively. However, from 1991 to 2020, the influence of human activities diminished, and climate variables gradually dominated the changes in inflow, contributing 52.2 % and 47.2 % to BAK and SYR, respectively, with upstream inflow being the main driving factor. Additionally, reservoir construction and political factors also played significant roles in the variation of inflow, exerting direct or indirect effects. This study provides crucial insights into the complex interplay of factors affecting inland lakes in arid regions and informs strategies to mitigate the Aral Sea Syndrome.

A meso- to micro-scale coupled model under typhoon conditions considering vortex structure and coriolis effect for wind farms

Accurate simulations of typhoon-induced wind speeds on wind farms are crucial for the refined assessment of typhoon risks in wind turbines. Southeastern coastal area in China is rich in wind resources but is also severely threatened by typhoons. As an extremely destructive weather system with complex structures, the refined near-surface wind fields of typhoons are difficult to simulate by meso-scale models for risk assessment. Therefore, a coupled meso- and micro-scale model under typhoon conditions is proposed to simulate typhoon-induced winds on a wind farm. The Coriolis force is considered in the coupled model to reflect the rotating effect of typhoons caused by the vortex structure. A coupling algorithm based on objective analysis is proposed to construct boundary conditions at the coupling interface, to consider the variation of inflow variables in the vertical and cross-wind directions. Model constants of the two-equation turbulence model are calibrated based on typhoon field observations, to more reasonably simulate typhoons. A validation study is conducted, and the results show that the maximum wind speed on the wind farm simulated by the coupled model exhibits an increased accuracy compared with that of the meso-scale model, where the absolute error decreases by 34%.

The effects of foreign direct investment on human capital accumulation—Evidence from China

AbstractThis paper examines the effect of foreign direct investment (FDI) on human capital accumulation in China. The identification strategy exploits variations in FDI inflows across manufacturing sub‐sectors caused by China's FDI liberalisation and initial sectoral composition patterns across cities. Using a panel of city‐level data from 1990 to 2005, the paper shows that FDI liberalisation accelerated human capital accumulation. Cities with higher exposure to FDI liberalisation experienced higher growth in high school and college enrollment. FDI incentivizes individuals' investment in their human capital by paying a higher wage premium for skilled workers, pushing up the skill premium in the local labor market, and raising household income. Compared to export‐oriented FDI and FDI in less‐skilled industries, market‐seeking FDI and skill‐intensive FDI have a much larger effect on college enrollment.

Cross Country Study of Human Capital Formation and USFDI Inflows

Purpose: The neo-classical theory of economic growth features the positive impact of the human capital of an economy on its growth. The inflow of foreign direct investment is one of the main components to carry forward the growth effect, this study investigates the impact of country-specific institutional quality and human capital on the cross-country variations of US-Foreign Direct Investment (FDI) inflows. Our core hypothesis is that Countries with better Human capital will attract more FDI if they have good quality institutions in terms of less risk in investment opportunities. Method: Using a set of panel data of US-Foreign Direct Investment (FDI) inflows for both developed and developing countries over the period 1984-2021. Result: The country-specific quality of institutions reinforces the impact of human capital on the inflow of US foreign direct investment in this study. Using two-dimensional panel data we find strong support for our hypothesis using a two-way fixed effects model. Our results are robust to the alternative measures of institutional quality. Implications: The strength of our approach is that in contrast to the previous works (1) we have used the USFDI inflow across countries that have been widely neglected in the related literature and (2) emphasis has been given to the conditional or joint impact of human capital and country-specific institutional quality in determining the cross-country variations in USFDI inflows.

Impact of Ownership-Location-Internalization (OLI) Paradigm and Investment Development Path (IDP) on Gravity Model of Foreign Direct Investments in Eastern Europe and Central Asia (EECA) Region

This study investigates the impact of OLI paradigm and the IDP on the gravity model of FDI in EECA region. Using panel data from 1995 to 2017, the analysis employs POLS, Fixed Effects, and Random Effects estimation methods to examine the determinants of FDI inflows. The results highlight the significance of the receiving country's GDP and labour market quality as the most consistent and statistically significant factors influencing FDI inflows. The distance between source and receiving countries also exhibits a negative relationship with FDI flows. Other variables, such as the source country's GDP, tertiary education, institutional governance, taxation, infrastructure, foreign exchange rates, and labour costs, do not show consistent or statistically significant effects across the estimation methods. The Fixed Effects model demonstrates the highest explanatory power, suggesting its suitability for capturing the variation in FDI inflows. These findings contribute to understanding the determinants of FDI and provide insights for policymakers and investors. Countries aiming to attract FDI should focus on promoting economic growth, improving labour market conditions, and reducing perceived distances between source and receiving countries.

Analyzing variation of water inflow to inland lakes under climate change: Integrating deep learning and time series data mining

The alarming depletion of global inland lakes in recent decades makes it essential to predict water inflow from rivers to lakes (WIRL) trend and unveil the dominant influencing driver, particularly in the context of climate change. The raw time series data contains multiple components (i.e., long-term trend, seasonal periodicity, and random noise), which makes it challenging for traditional machine/deep learning techniques to effectively capture long-term trend information. In this study, a novel FactorConvSTLnet (FCS) method is developed through integrating STL decomposition, convolutional neural networks (CNN), and factorial analysis into a general framework. FCS is more robust in long-term WIRL trend prediction through separating trend information as a modeling predictor, as well as unveiling predominant drivers. FCS is applied to typical inland lakes (the Aral Sea and the Lake Balkhash) in Central Asia, and results indicate that FCS (Nash-Sutcliffe efficiency = 0.88, root mean squared error = 67m³/s, mean relative error = 10%) outperforms the traditional CNN. Some main findings are: (i) during 1960–1990, reservoir water storage (WSR) was the dominant driver for the two lakes, respectively contributing to 71% and 49%; during 1991–2014 and 2015–2099, evaporation (EVAP) would be the dominant driver, with the contribution of 30% and 47%; (ii) climate change would shift the dominant driver from human activities to natural factors, where EVAP and surface snow amount (SNW) have an increasing influence on WIRL; (iii) compared to SSP1-2.6, the SNW contribution would decrease by 26% under SSP5-8.5, while the EVAP contribution would increase by 9%. The findings reveal the main drivers of shrinkage of the inland lakes and provide the scientific basis for promoting regional ecological sustainability.

Efficient river hydrodynamics modelling in realistic river systems using a Fourier neural operator-based network

Effective river management relies heavily on the accurate simulation of river flow dynamics to develop scenario-based strategies and inform decision making. Deep learning (DL) models, as alternatives to conventional simulation techniques, offer a compelling blend of precision and efficiency. This study introduces FNOCL (Fourier Neural Operator with ConvLSTM units), a novel DL neural network for modelling unsteady natural river flows. The network is adept at handling the complexities of spatial and temporal variations. FNOCL builds upon the Fourier neural operator (FNO) by incorporating convolutional long short-term memory (ConvLSTM) layers, combining robust performance with high proficiency in terms of capturing spatiotemporal patterns. Notably, FNOCL accommodates complex river cross-section profiles, thus enabling the accurate modelling of flow dynamics within intricate river morphologies. Our study applies FNOCL to two distinct river networks with varying morphology complexity levels. With reference to the HEC-RAS model, FNOCL showcases its ability to attain high accuracy in model prediction tasks and superior generalization with regard to addressing the uncertainty associated with inflow variations and cross-sectional changes. In comparative analyses with benchmark models (i.e., FNO and ConvLSTM), FNOCL performs most efficiently during the training process and obtains the most accurate water level and river flow predictions in the spatiotemporal domain. Furthermore, FNOCL exhibits a substantial speedup over HEC-RAS, notably reaching up to 50 times in a complex river network. These results highlight FNOCL as an efficient surrogate for conventional simulators, facilitating precise analyses across various scenarios. It provides efficient computations for system responses within complex river flow networks, thereby enhancing applications in river management, such as flood risk assessment, flood control, and the planning and design of hydraulic control structures.

Impact of harmonic inflow variations on the size and dynamics of the separated flow over a bump

The separated flow over a wall-mounted bump geometry under harmonic oscillations of the inflow stream is investigated with direct numerical simulations. The bump geometry gives rise to streamwise pressure gradients similar to those encountered on the suction side of low-pressure turbine (LPT) blades. Under steady inflow conditions, the separated-flow laminar-to-turbulent transition is initiated by self-sustained vortex shedding due to Kelvin-Helmholtz (KH) instability. In LPTs the dynamics are further complicated by the passage of the wakes shed by the previous stage of blades. The wake-passing effect is modeled here by introducing a harmonic variation of the inflow conditions. Three inflow oscillation frequencies and three amplitudes are considered. The frequencies are comparable to the wake-passing frequencies in practical LPTs. The amplitudes range from 1% to 10% of the inflow total pressure. The dynamics of the separated flow are studied by isolating the flow components that are respectively coherent with and uncorrelated to the inflow oscillation. Three scenarios are identified. The first one is analogous to the steady inflow case. In the second one, the KH vortex shedding is replaced during a part of the inflow period by the formation and release of a large vortex cluster. The third scenario consists solely of the periodic formation and release of the vortex cluster; it leads to a consistent reduction of the separated flow length over the entire period compared to the steady inflow case and would be the most desirable flow condition in a practical application. Published by the American Physical Society 2024

Analyzing the Effects of Atmospheric Turbulent Fluctuations on the Wake Structure of Wind Turbines and Their Blade Vibrational Dynamics

In recent trends, a rising demand for renewable energy has driven wind turbines to larger proportions, where lighter blade designs are often adopted to reduce the costs associated with logistics and production. This causes modern utility-scale wind turbine blades to be inherently more flexible, and their amplified aeroelastic sensitivity results in complex multi-physics reactions to variant atmospheric conditions, including dynamic patterns of aerodynamic loading at the rotor and vortex structure evolutions within the wake. In this paper, we analyze the influence of inflow variance for wind turbines with large, flexible rotors through simulations of the National Rotor Testbed (NRT) turbine, located at Sandia National Labs’ Scaled Wind Farm Technology (SWiFT) facility in Lubbock, Texas. The Common Ordinary Differential Equation Framework (CODEF) modeling suite is used to simulate wind turbine aeroelastic oscillatory behavior and wind farm vortex wake interactions for a range of flexible NRT blade variations, operating in differing conditions of variant atmospheric flow. CODEF solutions of turbine operation in Steady-In-The-Average (SITA) wind conditions are compared to SITA wind conditions featuring a controlled gust-like pulse overimposed, to isolate the effects of typical wind fluctuations. Finally, simulations of realistic time-varying wind conditions from SWiFT meteorological tower measurements are compared to the solutions of SITA wind conditions. These increasingly complex atmospheric inflow variations are tested to show the differing effects evoked by various patterns of spatiotemporal atmospheric flow fluctuations. An analysis is presented for solutions of wind turbine aeroelastic response and vortex wake evolution, to elucidate the consequences of variant inflow, which pertain to wind turbine dynamics at an individual and farm-collective scale. The comparisons of simulated farm flow for SITA and measured fluctuating wind conditions show that certain regions of the wake contain up to a 12% difference in normalized axial velocity, due to the introduction of wind fluctuations. The findings of this study prove valuable for practical applications in wind farm control and optimization strategies, with particular significance for modern utility-scale wind power plants operating in variant atmospheric conditions.

Estimation of water inflows to reservoirs of irrigation dams in the Guinea Savannah ecological zone of Ghana

ABSTRACT The study was carried out in the northern Ghana to estimate water inflows to nine reservoirs of irrigation dams for a period of 20 years (1999–2018) using the USDA Natural Resources Conservation Service Curve Number model. The key input parameters of the model were hydrologic soil group, rainfall amount, landuse/landcover, weighted curve number, antecedent moisture condition, and potential maximum soil moisture retention. The annual rainfall within the reservoir catchments was found to vary between 617.20 and 1,382.30 mm. The estimated annual runoff depths ranged from 54.10 to 125.55 mm. A high degree of positive correlation was found between rainfall and runoff depths with a coefficient of determination (R2) ranging from 79.80 to 90.70%. Hydrologic soil groups accounted for about 67.2 and 62.5% of the variation in runoff depth and percentage runoff, respectively. The estimated annual water inflows to the reservoirs ranged from 145,206 ± 125,814 m3/y at Gambibgo to 47,074,634 ± 4,395,860 m3/y at Tono. The variation in the annual water inflows and annual storage capacity recharge among the various reservoirs was noted to be influenced by reservoir size, catchment size, rainfall, and soil characteristics in the reservoir catchments.

Diffusive wave model in a finite length channel with a concentrated lateral inflow subject to different types of boundary conditions

The diffusive wave model is one of the simplified forms of Saint-Venant equations, and it is often used instead of the full model. In this paper, we present an analytical solution for the linearized diffusive wave model represented by a simultaneous system of two first-order partial differential equations focused on spatial variation of a lateral inflow in a finite channel. A concentrated lateral inflow from a small-width tributary is considered through the Dirac delta function. We use the Laplace transform method to solve these equations analytically. Two types of upstream boundaries are considered here in the form of a flow-discharge hydrograph and a flow-depth hydrograph, while keeping a flow-depth hydrograph as the downstream boundary. Using unit-step responses of the lateral inflow, the effect of different boundaries on the flow-depth responses and the flow-discharge responses is studied for different values of the Peclet number (Pe). The flow depth is observed to be more sensitive to the downstream boundary and other parameters used in this work. Consideration of the flow depth as the upstream boundary reflects the effect of all the parameters on the unit-step responses presented. These responses are compared with the available semi-infinite channel responses, which are found to be an inappropriate substitute for the finite channel responses for Pe<5 which implies that the downstream boundary cannot be ignored for these cases. However, for the case Pe>5, although the semi-infinite channel responses are found to satisfactorily estimate the discharge along the entire channel, they can approximate the flow depth at the locations closer to the upstream boundary only.

Revealing Decadal Glacial Changes and Lake Evolution in the Cordillera Real, Bolivia: A Semi-Automated Landsat Imagery Analysis

The impact of global climate change on glaciers has drawn significant attention; however, limited research has been conducted to comprehend the consequences of glacier melting on the associated formation and evolution of glacial lakes. This study presents a semi-automated methodology developed on the cloud platforms Google Earth Engine and Google Colab to effectively detect dynamic changes in the glaciers as well as glacial and non-glacial lakes of the Cordillera Real, Bolivia, using over 200 Landsat images from 1984 to 2021. We found that the study area experienced a rise in temperature and precipitation, resulting in a substantial decline in glacier coverage and a simultaneous increase in both the total number and total area of lakes. A strong correlation between glacier area and the extent of natural glacier-fed lakes highlights the significant downstream impact of glacier recession on water bodies. Over the study period, glaciers reduced their total area by 42%, with recent years showing a deceleration in glacier recession, aligning with the recent stabilization observed in the area of natural glacier-fed lakes. Despite these overall trends, many smaller lakes, especially non-glacier-fed ones, decreased in size, attributed to seasonal and inter-annual variations in lake inflow caused by climate variability. These findings suggest the potential decline of natural lakes amid ongoing climate changes, prompting alterations in natural landscapes and local water resources. The study reveals the response of glaciers and lakes to climate variations, including the contribution of human-constructed water reservoirs, providing valuable insights into crucial aspects of future water resources in the Cordillera Real.

The effects of reservoir storage and water use on the upstream–downstream drought propagation

Temporal aspects (e.g., response time and propagation rate) of drought propagation have been explored extensively by many studies, yet much less is revealed about the spatial characteristics of drought propagation. In our case study region the Shaying River basin with two major reservoirs, the effects of reservoir storage and water use on drought propagation, especially the upstream–downstream drought propagation, are closely investigated. It is found that meteorological droughts propagate to reservoir droughts in the river basin with drought pooling and lengthening. How hydrological droughts propagate from upstream to downstream is closely related to drought severity. Mild and moderate upstream reservoir droughts usually did not propagate to the downstream reservoir, but severe upstream reservoir droughts could propagate to the downstream reservoirs with delayed occurrence, prolonged duration, and increased severity. Severe reservoir droughts could lead to severe streamflow droughts, even after the end of reservoir droughts as an aftermath. During the period of drought propagation from upstream to downstream, the downstreamness of stored volume (Dsv) typically keeps going down from above the downstreamness of storage capacity (Dsc) at the beginning of drought occurrence, indicating relatively more water is stored in the downstream reservoir, to below Dsc at the end of drought, indicating relatively more water stored in the upstream reservoir. Although the increase of water uses aggravated hydrological drought in the long-term, the typical exacerbating effect of water use on hydrological droughts is not observed during 2013–2018 because most human water use was industrial and domestic which was generally stable over time. In the 2013–2018 period, upstream reservoir’s drought was driven by inflow variability, while downstream reservoir's drought conditions were predominantly shaped by mainly the variation of the outflow from the upstream reservoir. These findings offer crucial implications for policymakers, aiding in the formulation of robust drought and water management strategies that consider upstream–downstream dynamics, providing essential insights for river-basin scale water resource management and drought mitigation.

Analysis of Variation in Foreign Inflows by Different Categories of Foreign Portfolio Investors

The liberalisation of Indian financial markets has smoothened the capital flows of international institutional investors, resulting in rising foreign investor participation in the domestic equity and debt markets. Since the reforms of the 1990s, India has become one of the favourite investment hubs of foreign institutional investors (FIIs) across the globe. The research aims to analyse the variation in contribution to foreign inflows by the three different categories of foreign portfolio investments (FPIs) and the determinants of inflows of the categories of FPIs. The study is based on the use of secondary data collected from the National Securities Depository Limited and the Securities Exchange Board of India. One-way ANOVA has been employed to examine the variation in inflows by different categories of FIIs. Autor regressive distributed lag model has been used to understand the factors determining the inflows of FPIs. The results of the study revealed that there exists variation in the inflows of investments among the different categories of FIIs. The variation in inflows by different categories into equity instruments was significant, while the inflows into debt instruments were not significant. Furthermore, the highest inflows were seen from the second category of FIIs. JEL Codes: C32, G2

Walking back from the edge: thresholds of change reveal options for adaptation to water scarcity under climate change in the Murray–Darling Basin, Australia

Climate change has increased the variability of river inflows in the Murray–Darling Basin, threatening the viability of irrigated agriculture, food processing industries and ecological condition of wetlands. With increasing water scarcity, decision-makers and communities face heightened contestation over scarce water resources and trade-offs and adaptation have become increasingly necessary. We used a social-ecological systems approach to identify thresholds of change in the Goulburn–Broken Catchment, a major food-producing region, to reveal options for adaptation to climate change. We developed systems models whereby feedbacks are identified between sub-systems of cultural paradigms, policies, human well-being and environmental condition. Models were constructed using data from semi-structured interviews with managers and decision-makers, industry reports and the scientific literature. We found environmental thresholds are fixed, but whether they are exceeded is socially determined. Environmental condition can be maintained by relaxing constraints on volumes of water released into the highly regulated river system and easing rules on the distribution of water among users in the dairy and horticulture industries. Socio-economic thresholds were more flexible. Industries have adapted to water scarcity through irrigation efficiency measures, inter-industry relationships for water-sharing and feed substitutes in dairy production. However, industry interdependence indicates potential for maladaption, whereas investment in adaptation and diversification offers more sustainable options. Current policy and management disconnects between water for the environment and water for food production reveal opportunities for co-benefits between environmental and socio-economic domains. Realising these benefits requires a systemic, inclusive adaptation pathways approach to design and implement options for change.

METHOD OF PREDICTING SEASONAL VARIATIONS IN WATER INFLOW TO UNDERGROUND MINE WORKINGS USING THE WATER CATCHMENT MODEL WITH CONCENTRATED PARAMETERS

The authors suggest using the water catchment model with concentrated parameters for prediction of seasonal variation in water inflow to mines. The efficiency of the slope runoff model application was previously shown on the base of three test subjects operating apatite-nepheline ore deposits in the Khibiny massif. The article provides a simple methodology for water inflow prediction which doesn’t require any specific software. The example is provided of using this methodology for monthly water inflow prediction based on an underground mine in Kuzbass.

Nutrient retention in a small reservoir under changed variability of inflow nutrient concentration

ABSTRACT Within freshwater networks, lakes and reservoirs are reactors that modify nutrient dynamics. Their functioning is based on an interplay of hydrological and biogeochemical processes, rendering them vulnerable to climate change. Future changes in catchment characteristics are likely to alter the timing and magnitude of nutrient concentrations in discharge. This study investigated the impact of changing variability of nutrient concentrations on lake and reservoir dynamics. We examined intraannual nutrient retention and analyzed the role of reservoirs in reconfiguring the variability of nutrients. Utilizing the 1D lake model GOTM-WET, we simulated nutrient processing in a mesotrophic reservoir. Further, we performed scenario simulations by modifying the variability of inflow nitrogen and phosphorus concentrations. Our findings indicate that the reservoir removed ∼4% and ∼12% of total nitrogen (TN) and total phosphorus (TP), respectively. Particulate fractions were retained efficiently, but there was a net export of dissolved organic fractions. Regarding mixing and stratification periods, however, we observed net nitrogen export during stratification in certain years. During stratification, outflow concentration variability remained relatively unchanged for TN and TP compared to inflow concentrations. Conversely, phosphate and nitrate concentration variability increased in the outflow because of in-lake assimilation and the influence of hydrological events. With increasing inflow concentration variability during stratification, there was decreased removal of TN and TP by the reservoir, but increased variability of concentration. By evaluating the lake's capacity to attenuate variability of nutrient inflows under altered conditions, there are opportunities to improve monitoring of nutrient export and evaluate the potential impact of nutrient peaks on downstream drinking water resources and ecosystems.

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.