Hydrological Community Research Articles

Development of runoff generation models in the former USSR and Russia: a historical overview

ABSTRACT The paper presents a historical overview of the development of hydrological models in the former USSR and Russia since the 1930s. An overwhelming number of hydrological papers were published in Russian, and they are not sufficiently well known to the world hydrological community. The purpose of the review is to fill the gap and present the main achievements, some of which were pioneering for their time. The period under consideration is divided into three sub-periods. Pre-computer, the 1930–1950s were associated, first of all, with the development of models of unsteady water flow in river channels and linear flood-routing models; in the 1960–1980s, many theoretical and practical foundations for modelling the processes of the hydrological cycle and the formation of river runoff were developed; and in the Russian era, following 1991, several notable advancements in the considered field were also made.

Reconstructing a georeferenced inventory of flooding hazards in Raoping, Guangdong province, China, from 1492 to 1985

ABSTRACT In ancient times, there is a scarcity of instrumental water flow data, which challenges the hydrological science community to understand the evolution of flood risk under the changing climate over the centennial scale. Based on the historical records of flood events, the first spatio-temporal database of flood risk occurrence was established in Raoping county, Guangdong, China from 1492 to 1985 (a 494-year period), with intensive human interpretation and local investigation. Specifically, the spatially explicit flood events of the river network were provided for each flood episode. A detailed analysis of the database shows a high frequency of flood risk in summer and early autumn. Specifically, a significant (p < 0.05) increase has been found in flood risks since 1960. However, flooding decreased significantly in recent decades due to meteorological and hydrological factors, as well as the population density and migration during the 500-year period. A spatial clustering of flood events in the northern and southern parts is also confirmed, which shows an impact of population dynamics on a centennial scale. Such methods can be a reference for establishing China's flooding database for ancient periods, promoting a better understanding of natural hazards and associated human behaviors under the context of long-term climate change.

Advancing SWAT Model Calibration: A U-NSGA-III-Based Framework for Multi-Objective Optimization

In recent years, remote sensing data have revealed considerable potential in unraveling crucial information regarding water balance dynamics due to their unique spatiotemporal distribution characteristics, thereby advancing multi-objective optimization algorithms in hydrological model parameter calibration. However, existing optimization frameworks based on the Soil and Water Assessment Tool (SWAT) primarily focus on single-objective or multiple-objective (i.e., two or three objective functions), lacking an open, efficient, and flexible framework to integrate many-objective (i.e., four or more objective functions) optimization algorithms to satisfy the growing demands of complex hydrological systems. This study addresses this gap by designing and implementing a multi-objective optimization framework, Py-SWAT-U-NSGA-III, which integrates the Unified Non-dominated Sorting Genetic Algorithm III (U-NSGA-III). Built on the SWAT model, this framework supports a broad range of optimization problems, from single- to many-objective. Developed within a Python environment, the SWAT model modules are integrated with the Pymoo library to construct a U-NSGA-III algorithm-based optimization framework. This framework accommodates various calibration schemes, including multi-site, multi-variable, and multi-objective functions. Additionally, it incorporates sensitivity analysis and post-processing modules to shed insights into model behavior and evaluate optimization results. The framework supports multi-core parallel processing to enhance efficiency. The framework was tested in the Meijiang River Basin in southern China, using daily streamflow data and Penman–Monteith–Leuning Version 2 (PML-V2(China)) remote sensing evapotranspiration (ET) data for sensitivity analysis and parallel efficiency evaluation. Three case studies demonstrated its effectiveness in optimizing complex hydrological models, with multi-core processing achieving a speedup of up to 8.95 despite I/O bottlenecks. Py-SWAT-U-NSGA-III provides an open, efficient, and flexible tool for the hydrological community that strives to facilitate the application and advancement of multi-objective optimization in hydrological modeling.

Energy‐Water Asynchrony Principally Determines Water Available for Runoff From Snowmelt in Continental Montane Forests

ABSTRACTChanges in the volume, rate, and timing of the snowmelt water pulse have profound implications for seasonal soil moisture, evapotranspiration (ET), groundwater recharge, and downstream water availability, especially in the context of climate change. Here, we present an empirical analysis of water available for runoff using five eddy covariance towers located in continental montane forests across a regional gradient of snow depth, precipitation seasonality, and aridity. We specifically investigated how energy‐water asynchrony (i.e., snowmelt timing relative to atmospheric demand), surface water input intensity (rain and snowmelt), and observed winter ET (winter AET) impact multiple water balance metrics that determine water available for runoff (WAfR). Overall, we found that WAfR had the strongest relationship with energy‐water asynchrony (adjusted r2 = 0.52) and that winter AET was correlated to total water year evapotranspiration but not to other water balance metrics. Stepwise regression analysis demonstrated that none of the tested mechanisms were strongly related to the Budyko‐type runoff anomaly (highest adjusted r2 = 0.21). We, therefore, conclude that WAfR from continental montane forests is most sensitive to the degree of energy‐water asynchrony that occurs. The results of this empirical study identify the physical mechanisms driving variability of WAfR in continental montane forests and are thus broadly relevant to the hydrologic management and modelling communities.

Land use transformations in the Brazilian Savanna: A decade of soil erosion and runoff measurements

Changes in land cover and land use (LULC) are one of the main drivers of erosion and runoff. How ever, most research has relied on short-term observations and only focused on one or two land cover types. We investigated the long-term trade-off between common agricultural land covers (sugarcane, pasture, and soybean), runoff, and soil loss rates. We compared these to native forest (wooded Cerrado) and bare soil. The field observations were done in 100 m2 experimental plots in Brazil maintained during the past 10 years. The paper provides three main contributions: (1) long-term runoff and soil loss rates of plots under different LULCs, (2) comparison of runoff, soil loss, and pedological characteristics between plots constructed 10 years apart, and (3) analysis of the trade-off between different LULCs. When ranking land covers based on runoff and soil loss rates, there is a shift in ranking positions, making it difficult to determine which one is more environmentally harmful. However, it is evident that whatever agricultural practice is used, there is a significant impact when compared to native forest. For example, the area converted to pasture resulted in almost 20 times higher runoff, while conversion to sugarcane resulted in 5 times higher soil loss. Not only land cover plays a major influencing factor, but also weathering exposing time. Areas under the same land cover and environmental conditions had different rates of soil loss and runoff due to long-term exposure effects such as soil crusting. Our findings have high relevance for the hydrological and agricultural community by demonstrating (i) the magnitude of trade-off in terms of soil loss and runoff due to land cover changes and (ii) that soil loss should not be assumed to be a linear process over time, as it is commonly assumed.

Characterizing multifarious hydroclimatic patterns using geodetic measurements in the Australian mainland

Benefiting from the tremendous advance of modern geodetic technologies, accurate measurements provide us with novel means to weigh terrestrial water storage (TWS) and shed critical light on hydroclimatic interaction mechanisms. In this study, GNSS and GRACE observations are jointly used to investigate spatiotemporal TWS fluctuations and their connections with large-scale climate patterns in the Australian mainland. A variational Bayesian principal component analysis-based inversion method is designed to handle random data missing in GNSS and long-term data gaps in GRACE. The jointly inferred TWS estimates manifest more spatial details compared to the GRACE Mascon solutions and good resistance to non-hydrological mechanisms in GNSS data. The joint inversion results are compared with other water-related storage/flux estimates (i.e., GLDAS, GRACE, and precipitation), which have considerable coherence with TWS at both temporal and spatial scales. The results indicate obvious annual variations in TWS changes in north Australia in contrast to inappreciable seasonal hydrological signatures in other vast arid zones. Hydrological wet/dry conditions are quantified with drought severity index (DSI) datasets derived from multiple means and the joint-based DSI datasets temporally agree with the other datasets and correspond well with precipitation anomalies in most watersheds. In addition, the jointly inverted TWS estimates are used to declassify multifarious hydroclimatic features, and multi-source hydrometeorological datasets are used to attribute interannual TWS changes. Our study contributes to better observing the water cycles for the hydrological community and illuminates more application prospects in the climate sciences.

Snow Depth Extraction From Time‐Lapse Imagery Using a Keypoint Deep Learning Model

AbstractSnow pole time‐lapse photography, in which a snow pole of a known height is installed in front of a camera and photographed repeatedly over the course of a snow season, allows a large network of sites to be established relatively quickly and affordably. However, current approaches for extracting snow depth from snow poles typically relies on time intensive manual photo processing. By integrating computer vision algorithms with snow pole photography, we present a method that uses a keypoint detection model to automatically observe snow height across a network of sites. At 20 snow pole locations from Grand Mesa, CO (n = 9,722 images), our model successfully predicts the top and bottom of the pole with a mean absolute error (MAE) of 1.30 cm. To assess model generalizability, we tested the model on 12 sites in Washington State (n = 1,770 images). When the Colorado trained model was fine‐tuned using a subset of Washington images, the model predicted snow depth with a MAE of 4.0 cm. Best performance was achieved when both data sets were included during training, with a MAE of 2.05 cm for Colorado images and a MAE of 1.14 cm for Washington images. We demonstrate that, especially when trained using a subset of site‐specific data, a keypoint detection model can accelerate snow pole automation. This algorithm brings the hydrology community one step closer to a generalized snow pole detection model, and we call for a future model that integrates across time‐lapse images from additional locations.

EvalHyd v0.1.2: a polyglot tool for the evaluation of deterministic and probabilistic streamflow predictions

Abstract. The evaluation of streamflow predictions forms an essential part of most hydrological modelling studies published in the literature. The evaluation process typically involves the computation of some evaluation metrics, but it can also involve the preliminary processing of the predictions as well as the subsequent processing of the computed metrics. In order for published hydrological studies to be reproducible, these steps need to be carefully documented by the authors. The availability of a single tool performing all of these tasks would simplify not only the documentation by the authors but also the reproducibility by the readers. However, this requires such a tool to be polyglot (i.e. usable in a variety of programming languages) and openly accessible so that it can be used by everyone in the hydrological community. To this end, we developed a new tool named evalhyd that offers metrics and functionalities for the evaluation of deterministic and probabilistic streamflow predictions. It is open source, and it can be used in Python, in R, in C++, or as a command line tool. This article describes the tool and illustrates its functionalities using Global Flood Awareness System (GloFAS) reforecasts over France as an example data set.

Evaluation of Algal Control Measures in Eutrophic Reservoirs Based on Aquatic Ecosystem Models

The frequency of freshwater cyanobacterial blooms is increasing globally due to climate change and eutrophication, particularly in reservoirs. Reservoir ecosystems exhibit unique characteristics, and there is a complex relationship between factors such as light, temperature, nutrient salts, hydrology, and algal growth. The impact of the other factors on algal growth varies significantly among different reservoirs. Thus, it is crucial to assess the effectiveness of various algal control measures implemented in different reservoirs. This study conducted a comprehensive assessment by establishing a eutrophication model for the Shanzi Reservoir in Fuzhou City. The model incorporated meteorology, hydrology, carbon dynamics, nutrient cycling, and biological communities. The effectiveness of diverse management measures was systematically evaluated. The findings demonstrate that increasing the water level, reducing nutrient salts in sediments, and implementing ecological fish stocking effectively suppressed algal growth to varying degrees and improved nitrogen and phosphorus levels. Lower water levels and ecological fish stocking had a significant impact on algal reproduction, while sediment reduction had a minimal effect. Conversely, lower water levels and ecological fish stocking did not significantly improve nitrogen and phosphorus concentrations in the reservoir, whereas sediment reduction had a noticeable effect. Consequently, the management strategies for the Shanzi Reservoir should prioritize external control measures and the implementation of ecological fish stocking.

Long-term climate and hydrologic regimes shape stream invertebrate community responses to a hurricane disturbance.

Disturbances can produce a spectrum of short- and long-term ecological consequences that depend on complex interactions of the characteristics of the event, antecedent environmental conditions, and the intrinsic properties of resistance and resilience of the affected biological system. We used Hurricane Harvey's impact on coastal rivers of Texas to examine the roles of storm-related changes in hydrology and long-term precipitation regime on the response of stream invertebrate communities to hurricane disturbance. We detected declines in richness, diversity and total abundance following the storm, but responses were strongly tied to direct and indirect effects of long-term aridity and short-term changes in stream hydrology. The amount of rainfall a site received drove both flood duration and flood magnitude across sites, but lower annual rainfall amounts (i.e. aridity) increased flood magnitude and decreased flood duration. Across all sites, flood duration was positively related to the time it took for invertebrate communities to return to a long-term baseline and flood magnitude drove larger invertebrate community responses (i.e. changes in diversity and total abundance). However, invertebrate response per unit flood magnitude was lower in sub-humid sites, potentially because of differences in refuge availability or ecological-evolutionary interactions. Interestingly, sub-humid streams had temporary large peaks in invertebrate total abundance and diversity following recovery period that may be indicative of the larger organic matter pulses expected in these systems because of their comparatively well-developed riparian vegetation. Our findings show that hydrology and long-term precipitation regime predictably affected invertebrate community responses and, thus, our work underscores the important influence of local climate to ecosystem sensitivity to disturbances.

Discharge variations of qanat near an ephemeral stream

Ephemeral streams are the most important sources of groundwater recharge in arid and semi-arid regions of the world. To extract this replenishable water, most of the time, qanats are constructed parallel to the ephemeral streams. Analytical modeling of a stream-qanat system can provide an effective tool for managing such a system in a timely fashion and, thus, is commonly applied in the hydrological communities. However, the available analytical solutions of discharge variation of qanat only consider the distributed recharge from rainfall and cannot be used to investigate the effects of geometric parameters of stream and hydraulic parameters of aquifer on the discharge of qanat near an ephemeral stream. Thus, the goal of this work is to obtain a semi-analytical solution of qanat discharge due to recharge from an ephemeral stream of an arbitrary shape in a three-dimensional anisotropic homogeneous unconfined aquifer. The solution is obtained via Laplace and Fourier transformations along with the principle of superposition. The results of this study are presented in the form of qanat discharge-time curves. The influences of the qanat length, shape, and recharge distribution along the ephemeral stream are explored in great detail. The effects of the hydraulic parameters of the aquifer on the discharge of qanat are also investigated. The results of this study can be used to predict the discharge of qanat due to recharge from an ephemeral stream, to calculate the optimum length of a qanat for maximum extraction of the replenished water, to estimate the adequate recharge from the ephemeral stream and the hydraulic parameters of aquifer using the discharge data of qanat, among other applications.

Temporal Fusion Transformers for streamflow Prediction: Value of combining attention with recurrence

Over the past few decades, the hydrology community has witnessed notable advancements in streamflow prediction, particularly with the introduction of cutting-edge machine-learning algorithms. Recurrent neural networks, especially Long Short-Term Memory (LSTM) networks, have become popular due to their capacity to create precise forecasts and realistically mimic the system dynamics. Attention-based models, such as Transformers, can learn from the entire data sequence concurrently, a feature that LSTM does not have. This work tests the hypothesis that combining recurrence with attention can improve streamflow prediction. We set up the Temporal Fusion Transformer (TFT) architecture, a model that combines both of these aspects and has never been applied in hydrology before. We compare the performance of LSTM, Transformers, and TFT over 2,610 globally distributed catchments from the recently available Caravan dataset. Our results demonstrate that TFT indeed exceeds the performance benchmark set by the LSTM and Transformers for streamflow prediction, when models are trained individually for each basin. Additionally, being an explainable AI method, TFT helps in gaining insights into the streamflow generation processes.

Overstaying our welcome: On the rise of women's seniority in the academy

AbstractIssues surrounding gender equality are—and should be—front and centre in the water resources community, and other science, technology, engineering and mathematics (STEM) fields. Very necessarily, the focus tends to be on recruitment, offering support for students and early career academics. The leaky pipeline concept used to describe the incremental loss of women from STEM fields with career duration describes a disproportionate loss of senior women, creating a parallel problem where highly qualified, top tier academics are lost from the system after significant financial and personnel investment by institutions. Ultimately, the leaky pipeline undermines the extensive investment of the hydrology and other STEM communities in equity, diversity, inclusion and accessibility (EDIA) recruitment and retention programmes by cutting short career ambitions and the trajectories of diverse top performing individuals, resulting in no net benefit of EDIA policy investments and a lack of diversity with seniority. Addressing this critical gender gap requires the attention and support of the hydrology community of practice with specific focus on generating opportunities for advancement, confronting systemic and structural biases and improving education around allyship. Institutions and professional organizations need to consciously grow diversity in leadership and recognize and outwardly manage the perception of academic excellence around slow research and education that attracts increased diversity. Supporting allyship, reducing competitiveness among community members and reinforcing collaboration will not only attract, but retain, a higher proportion of diversity in the hydrology community, academia and STEM professions in general. It is time for the water resources (and other STEM) communities to demand broader accountability and recognition of the barriers to women, implement and reward more diverse definitions of research excellence, and offer allyship training to the community of practice at large.

Assessing Extreme Drought Events and Their Temporal Impact: Before and after the Operation of a Hydropower Plant

The probabilistic analysis of streamflow and drought event durations plays a crucial role in the efficient and sustainable management of existing water resources in the region. This approach involves the collection of historical hydrological data from river gauging stations, the use of statistical and probabilistic models, and the assessment of hydrological projections at different return periods to provide valuable information for society to understand the potential impacts of extreme events. The analysis is carried out on the Sinú River in Colombia, with consideration given to both the presence and absence of the Hydropower Plant Urrá I. The results reveal that, under natural conditions, a higher number of return periods correspond to less extreme drought flows and longer temporal durations. However, when the hydropower plant is operational, the occurrence and duration of drought are influenced by the regulations implemented during energy generation. The results of this analysis can guide water resource management policies, considering the operation of the hydroelectric plant, thereby enabling decisions that enhance the resilience and sustainability of the river’s hydrological conditions and communities that depend on it.

Disorientations: The Political Ecology of “Displacing” Floating Communities from Cambodia's Tonle Sap Lake

AbstractIn this article, we extend a theory of disorientations to reveal how attempts to fix and control both water and people are disrupting once‐fluid relationships between the Tonle Sap Lake and communities who have lived with‐on the lake for generations. Using ethnographic and participatory mapping methods, we examine the socio‐ecological dynamics that preceded and succeeded in the forced relocation of three floating communities in 2018. We argue that communities’ experiences challenge land‐centric and event‐centric understandings of displacement that pathologise fluid lifeways and fail to account for the materiality of water that has shaped floating villages’ multi‐generational relationships with their wetland ecology. We develop the concept of disorientations to illuminate villagers’ experiences of relocation within a collapsing aquatic ecosystem—a collapse catalysed by state efforts to impose fixity on both hydrological flow and community mobility. The lens of disorientations invites displacement debates to consider materialities of place—whether pulsing water or living, shifting soils.

Salinity-induced succession of phototrophic communities in a southwestern Siberian soda lake during the solar activity cycle

A variety of lakes located in the dry steppe area of southwestern Siberia are exposed to rapid climatic changes, including intra-century cycles with alternating dry and wet phases driven by solar activity. As a result, the salt lakes of that region experience significant fluctuations in water level and salinity, which have an essential impact on the indigenous microbial communities. But there are few microbiological studies that have analyzed this impact, despite its importance for understanding the functioning of regional water ecosystems. This work is a retrospective study aimed at analyzing how solar activity-related changes in hydrological regime affect phototrophic microbial communities using the example of the shallow soda lake Tanatar VI, located in the Kulunda steppe (Altai Region, Russia, southwestern Siberia). The main approach used in this study was the comparison of hydrochemical and microscopic data obtained during annual field work with satellite and solar activity data for the 12-year observation period (2011–2022). The occurrence of 33 morphotypes of cyanobacteria, two key morphotypes of chlorophytes, and four morphotypes of anoxygenic phototrophic bacteria was analyzed due to their easily recognizable morphology. During the study period, the lake surface changed threefold and the salinity changed by more than an order of magnitude, which strongly correlated with the phases of the solar activity cycles. The periods of high (2011–2014; 100–250 g/L), medium (2015–2016; 60 g/L), extremely low (2017–2020; 13–16 g/L), and low (2021–2022; 23–34 g/L) salinity with unique biodiversity of phototrophic communities were distinguished. This study shows that solar activity cycles determine the dynamics of the total salinity of a southwestern Siberian soda lake, which in turn determines the communities and microorganisms that will occur in the lake, ultimately leading to cyclical changes in alternative states of the ecosystem (dynamic stability).

Scope and Direction of the Journal of Hydrologic Engineering : Serving the Hydrology Community and Beyond

Scope and Direction of the <i>Journal of Hydrologic Engineering</i> : Serving the Hydrology Community and Beyond

Watershed Management for Sustainable Livelihoods: Integrating Local Pond Ecosystems in Malda, West Bengal

This research article explores the intricate relationship between watershed management, local pond ecosystems, and sustainable livelihoods in the Malda district of West Bengal. The study investigates the potential of integrating local pond ecosystems into watershed management strategies as a means to enhance economic prosperity, ecological resilience, and community well-being. Through a multidisciplinary approach, combining ecological assessments, socioeconomic surveys, and participatory engagement, the research aims to provide insights into the synergies that exist between watershed management practices and the sustainable livelihoods of the local villagers. The research methodology involves field studies encompassing hydrological analysis, biodiversity assessments, and community consultations, aimed at understanding the dynamics of local pond ecosystems and their interconnectedness with the broader watershed. Special attention is given to the diverse ecosystem services provided by these ponds, such as water provisioning, nutrient cycling, and supporting aquatic biodiversity, and how they contribute to the overall resilience of the watershed. The findings of this study are expected to contribute valuable information for policymakers, environmental practitioners, and local communities in Malda district, offering a comprehensive understanding of how the integration of local pond ecosystems into watershed management plans can foster sustainable livelihoods. The article discusses potential strategies for optimizing the co-management of these resources, balancing the ecological health of the ponds with the socioeconomic needs of the local population. Ultimately, this research aims to provide a blueprint for sustainable watershed management practices that prioritize the conservation and utilization of local pond ecosystems, fostering a harmonious balance between ecological integrity and the livelihood aspirations of the communities in Malda, West Bengal.

AltiMaP: altimetry mapping procedure for hydrography data

Abstract. Satellite altimetry data are useful for monitoring water surface dynamics, evaluating and calibrating hydrodynamic models, and enhancing river-related variables through optimization or assimilation approaches. However, comparing simulated water surface elevations (WSEs) using satellite altimetry data is challenging due to the difficulty of correctly matching the representative locations of satellite altimetry virtual stations (VSs) to the discrete river grids used in hydrodynamic models. In this study, we introduce an automated altimetry mapping procedure (AltiMaP) that allocates VS locations listed in the HydroWeb database to the Multi-Error Removed Improved Terrain Hydrography (MERIT Hydro) river network. Each VS was flagged according to the land cover of the initial pixel allocation, with 10, 20, 30 and 40 representing river channel, land with the nearest single-channel river, land with the nearest multi-channel river and ocean pixels, respectively. Then, each VS was assigned to the nearest MERIT Hydro river reach according to geometric distance. Among the approximately 12 000 allocated VSs, most were categorized as flag 10 (71.7 %). Flags 10 and 20 were mainly located in upstream and midstream reaches, whereas flags 30 and 40 were mainly located downstream. Approximately 0.8 % of VSs showed bias, with considerable elevation differences (≥|15| m) between the mean observed WSE and MERIT digital elevation model. These biased VSs were predominantly observed in narrow rivers at high altitudes. Following VS allocation using AltiMaP, the median root mean square error of simulated WSEs compared to satellite altimetry was 7.86 m. The error rate was improved meaningfully (10.6 %) compared to that obtained using a traditional approach, partly due to bias reduction. Thus, allocating VSs to a river network using the proposed AltiMaP framework improved our comparison of WSEs simulated by the global hydrodynamic model to those obtained by satellite altimetry. The AltiMaP source code (https://doi.org/10.5281/zenodo.7597310, Revel et al., 2023a) and data (https://doi.org/10.4211/hs.632e550deaea46b080bdae986fd19156, Revel et al., 2022) are freely accessible online, and we anticipate that they will be beneficial to the international hydrological community.

Impact of land use/land cover changes on evapotranspiration and model accuracy using Google Earth engine and classification and regression tree modeling

This research uses a Classification and Regression Tree (CART) model with Google Earth Engine (GEE) to assess the winter season’s land cover and change detection mapping impact on the evapotranspiration (crop water requirement) parameters. Winter seasons, crucial for agricultural planning, and irrigation water requirement challenges in accurately mapping land cover and detecting changes due to the dynamic nature of farming practices during this period. In this study, Landsat-8 OLI images have been combined to map Land use and Land cover (LULC) and other change detection mapping in Akola Block, Maharashtra, India, during the 2018–2022 winter season. As an discoverer researcher that found detailed information of LULC classes during last 2018 to 2022 winter seasons, the use of the CART model in combination with a cloud-computing GEE demonstrates to be a practical approach for accurate land cover classification and change detection maps to create a pixel-based winter seasons information of study area. The novelty of this study lies in its innovative use of GEE, a powerful platform for remote sensing and geospatial analysis, to create LULC maps with remarkable accuracy. Achieving a 100% training accuracy across the four years under consideration is an exceptional feat, highlighting the reliability and stability of the methodology. Furthermore, the validation accuracy values, ranging from 89 to 94% for the winter seasons of 2018 to 2022, underscore the robustness of this approach. Such consistently high accuracy in mapping LULC over time is a groundbreaking achievement and offers a new dimension to the field of hydrology. For the hydrological community, the implications of this study are profound. Accurate LULC mapping and change detection provide critical data for modeling and analyzing the effects of land use changes on water resources, watershed management, and water quality. The User, Kappa, and Producer accuracy metrics used in this research highlight the model’s performance and its suitability for hydrological applications. These accurate LULC maps can aid in the development of hydrological models, forecasting, and decision-making processes, ultimately contributing to more effective water resource management and environmental conservation. In summary, this study’s innovative use of GEE, its remarkable accuracy in LULC mapping, and its relevance to the hydrological community demonstrate the potential for advanced remote sensing and geospatial tools to significantly improve our understanding of land use changes and their implications for water resources and environmental management.