Hydrological Research Articles

The hydrological system as a living organism

Abstract. Hydrology is the bloodstream of the terrestrial system. The terrestrial system is alive, with the ecosystem as its active agent. The ecosystem optimises its survival within the constraints of energy, water, climate and nutrients. The key variables that the ecosystem can modify are the controls on fluxes and storages in the hydrological system, such as: the capacities of preferential flow paths (preferential infiltration, recharge and subsurface drainage); and the storage capacities in the root zone, wetlands, canopy and ground surface. It can also, through evolution, adjust the efficiency of carbon sequestration and moisture uptake. Some of these adjustments can be made fast, particularly rootzone storage capacity, infiltration capacity, vegetation density and species composition. These system components are important controls on hydrological processes that in hydrological models are generally considered static and are determined by calibration on climatic drivers of the past. This leads to hydrological models that are dead and incapable to react to change, whereas the hydrological system is alive and will adjust. The physical law driving this evolutionary process is the second law of thermodynamics with the Carnot limit as its constraint. This physical limit allows optimisation techniques to explore the reaction of the hydrological system and its components to change in climatic drivers. This implies a new direction in the theory of hydrology, required to deal with change and addressing the Unsolved Problems in Hydrology.

Simulating block-scale flood inundation and streamflow using the WRF-Hydro model in the New York City metropolitan area

This study assesses the performance of the Weather Research and Forecasting-Hydrological modeling system (WRF-Hydro) in the simulation of street-scale flood inundation. The case study is the Hackensack River Watershed in New Jersey, US, which is part of the operational Stevens Flood Advisory System (SFAS), a one-way coupled hydrodynamic-hydrologic system that currently uses the Hydrologic Engineering Center's Hydrologic Modeling System (HEC-HMS) to simulate streamflow. The performance of the 50-m gridded WRF-Hydro model was assessed for potential integration into the operational SFAS system. The model was calibrated with the dynamically dimensioned search algorithm using streamflow observations. The model performance was assessed using (i) streamflow observations, (ii) USGS HWMs, and (iii) crowdsourced data on street inundation. Results show that WRF-Hydro outperformed the HEC-HMS model. WRF-Hydro over and underestimated flood inundation extent due to the inaccuracy of the synthetic rating curves and the modeling structure errors. An agreement was noticed between WRF-Hydro and crowdsourced data on flood extent.

The last remnants of the Italian Apennine glaciers: 3-D modeling of the Lower Calderone Glacieret by the IDW spatial interpolation of GPR data

Abstract We present a quantitative ground-penetrating radar (GPR) analysis of the Lower Calderone Glacieret to highlight the recent evolution of one of the southernmost glacial systems in Europe. The Upper and Lower Calderone Glacierets are the last two perennial ice bodies in the Apennine Mountains (Italy), and their continuous monitoring is important for glaciology, hydrology and climate science. We applied a proprietary auto-picking algorithm to track reflections accurately and objectively within three pseudo-3-D GPR data sets that were acquired over the Lower Glacieret in different years. After the time-to-depth conversion, the basal reflections were projected onto the normal versors of a 3-D topographic model of the survey area, at the different GPR trace positions. We then applied an Adjusted Inverse-Distance Weighted Spatial Interpolation method to extrapolate the ice-bedrock interface within the areas not directly covered by the GPR profiles and compare it with the topographic surface to recover the glacieret volume. In this paper, we critically examine the accuracy of the reconstructed models, including possible issues related to the challenging survey areas, such as local artifacts in the interpolated interface caused by irregular GPR coverage. We further discuss the various advantages of the implemented procedure with respect to more traditional glacier monitoring techniques.

The Forecast of Streamflow through Göksu Stream Using Machine Learning and Statistical Methods

Forecasting streamflow in stream basin systems plays a crucial role in facilitating effective urban planning to mitigate floods. In addition to employing intricate hydrological modeling systems, machine learning and statistical techniques offer an alternative means for streamflow forecasts. Nonetheless, the precision and dependability of these methods are subjects of paramount importance. This study rigorously investigates the effectiveness of three distinct machine learning techniques and two statistical approaches when applied to streamflow data from the Göksu Stream in the Marmara Region of Turkey, spanning from 1984 to 2022. Through a comparative analysis of these methodologies, this examination aims to contribute innovative advancements to the existing methodologies used in the prediction of streamflow data. The methodologies employed include machine learning methods such as Extreme Gradient Boosting (XGBoost), Random Forest (RF), and Support Vector Machine (SVM) and statistical methods such as Simple Exponential Smoothing (SES) and Autoregressive Integrated Moving Average (ARIMA) model. In the study, 444 data points between 1984 and 2020 were used as training data, and the remaining data points for the period 2021–2022 were used for streamflow forecasting in the test validation period. The results were evaluated using various metrics, such as the correlation coefficient (r), mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), coefficient of determination (R2), and Nash–Sutcliffe efficiency (NSE). Upon analyzing the results, it was found that the model generated using the XGBoost algorithm outperformed other machine learning and statistical techniques. Consequently, the models implemented in this study demonstrate a high level of accuracy in predicting potential streamflow in the river basin system.

Response of Floods to the Underlying Surface Changes in the Taojiang River Basin Using the Hydrologic Engineering Center’s Hydrologic Modeling System

Due to underlying surface changes (USCs), the changes in the Taojiang River Basin’s flood generation conditions could impact the flooding process in the basin. However, most studies have typically focused on either land-use changes (LUCs) or soil and water conservation measures (SWCMs) to assess the impact of the USCs on floods, which may not provide a more comprehensive understanding of the response of floods to the USCs. To investigate how the USCs have altered the floods in the Taojiang River Basin, located upstream of Poyang Lake, China, the HEC-HMS model, which incorporates the influence of the USCs into the parameter calibration, is established in this study to investigate the flood processes on an hourly scale. The flood peak and the maximum 72 h flood volume are selected as two indexes and are applied to analyze the changes in floods caused by the USCs. The 1981–2020 period is divided into three sub-periods (i.e., 1981–1992, 1993–2007, and 2008–2020) based on the conditions of the USCs. It is found that the two indexes have exhibited decreasing trends, mainly due to the USCs during 1981–2020. Benchmarked against the baseline period of 1981–1992, the two indexes decreased by 3.06% (the flood peak) and 4.00% (the maximum 72 h flood volume) during 1993–2007 and by 5.92% and 7.58% during 2008–2020. Moreover, the impacts of the LUCs and SWCMs are separated through parameter adjustments in the model, revealing that the SWCMs played a dominant role in the USCs in the Taojiang River Basin. The quantification and assessment of the impact of the USCs on floods of different magnitudes revealed that the influence decreases with increasing flood magnitude. The results of this study improve our understanding of how USCs affect the flooding process and therefore provide support for flood control management under changing environments.

The Antarctic Subglacial Hydrological Environment and International Drilling Projects: A Review

Subglacial lakes and hydrological systems play crucial roles in Antarctic subglacial hydrology, water balance, subglacial geomorphology, and ice dynamics. Satellite altimetry has revealed that some recurrent water exchange occurs in subglacial lakes. They are referred to as ’active lakes’, which prominently influence a majority of subglacial hydrological processes. Our analysis indicates that active subglacial lakes are more likely to be situated in regions with higher surface ice flow velocities. Nevertheless, the origin of subglacial lakes still remains enigmatic and uncertain. They could have potential associations with geothermal heat, ice sheets melting, and ice flow dynamics. Subglacial lake drilling and water sampling have the potential to provide valuable insights into the origin of subglacial lakes and subglacial hydrological processes. Moreover, they could also offer unique opportunities for the exploration of subglacial microbiology, evolution of the Antarctic ice sheets, and various fundamental scientific inquiries. To date, successful drilling and sampling has been accomplished in Lake Vostok, Lake Mercer, and Lake Whillans. However, the use of drilling fluids caused the water sample contamination in Lake Vostok, and the drilling attempt at Lake Ellsworth failed due to technical issues. To explore more of the conditions of the Antarctic subglacial lakes, the Lake Centro de Estudios Científicos (Lake CECs) and Lake Snow Eagle (LSE) drilling projects are upcoming and in preparation. In this study, we aim to address the following: (1) introduce various aspects of Antarctic subglacial lakes, subglacial hydrological elements, subglacial hydrology, and the interactions between ice sheets and the ocean; and (2) provide an overview and outlook of subglacial lakes drilling projects.

Key Aspects of a Good “Introduction to Water Resources Engineering” Course

This paper takes the elective course "Introduction to Hydraulic Engineering" set up by Agricultural University of Hebei as an example, and expounds the key links of a good elective course from several aspects, such as optimizing the teaching content, enriching the teaching means, preparing the lesson carefully and lecturing carefully.

An explainable multiscale LSTM model with wavelet transform and layer-wise relevance propagation for daily streamflow forecasting

Developing an accurate and reliable daily streamflow forecasting model is important for facilitating the efficient resource planning and management of hydrological systems. In this study, an explainable multiscale long short-term memory (XM-LSTM) model is proposed for effective daily streamflow forecasting by integrating the à trous wavelet transform (ATWT) for decomposing data, the Boruta algorithm for identifying model inputs, and the layer-wise relevance propagation (LRP) for explaining the prediction results. The proposed XM-LSTM is tested by performing multi-step-ahead forecasting of daily streamflow at four stations in the middle and lower reaches of the Yangtze River basin and compared with the X-LSTM. The X-LSTM is formed by coupling the long short-term memory (LSTM) with the LRP. For comparison, the inputs of these two models are identified by the Boruta selection algorithm. The results show that all models exhibit good ability to forecast daily streamflow, however, the prediction performance decreases as the lead time increases. The XM-LSTM provides a better forecasting performance than the X-LSTM, suggesting the ability of the ATWT to improve the LSTM for daily streamflow forecasting. Moreover, the correlation scores analysis by the LRP shows that the ATWT can extract useful information that influences the daily streamflow from the raw predictors, and the water level has the most significant contribution to streamflow prediction. Accordingly, the XM-LSTM model can be viewed as a potentially useful approach for increasing the accuracy and explainability of streamflow forecasting.

Contemporary movement of rock glaciers in the La Sal and Uinta Mountains, Utah, USA

Rock glaciers are common landforms in mountainous areas of the western US. The motion of active rock glaciers is a key indicator of ice content, offering connections to climate and hydrologic systems. Here, we quantified the movement of six rock glaciers in the La Sal and Uinta Mountains of Utah through repeat differential GPS surveying. Networks of 10–41 points on each rock glacier were surveyed in September 2021; July 2022; September 2022; and July 2023. We found that all features are moving with average annual rates of motion from 1.5 ± 0.8 to 18.5 ± 7.5 cm/yr. Rock glaciers move up to 3× faster in the summer than in the winter, and rates of motion were greater in 2023 after a winter with above-average snowfall, emphasizing the role of liquid water availability. Velocities of individual points in the winter of 2021–22 are positively correlated with velocities during the winter of 2022–23, suggesting that spatial variability of motion is not stochastic, but rather reflects internal properties of each rock glacier. Bottom temperature of snow measurements during winter, and the temperature of springs discharging water in summer, suggest that these rock glaciers contain modern permafrost. Radiocarbon data document advance of one rock glacier during the Little Ice Age. Our GPS dataset reveals complicated patterns of rock glacier movement, and the network of survey points we established will be a valuable baseline for detecting future cryosphere change in these mountains.

An Assessment of the Coupled Weather Research and Forecasting Hydrological Model on Streamflow Simulations over the Source Region of the Yellow River

The Source Region of the Yellow River (SRYR), renowned as the “Water Tower of the Yellow River”, serves as an important water conservation domain in the upper reaches of the Yellow River, significantly influencing water resources within the basin. Based on the Weather Research and Forecasting (WRF) Model Hydrological modeling system (WRF-Hydro), the key variables of the atmosphere–land–hydrology coupling processes over the SRYR during the 2013 rainy season are analyzed. The investigation involves a comparative analysis between the coupled WRF-Hydro and the standalone WRF simulations, focusing on the hydrological response to the atmosphere. The results reveal the WRF-Hydro model’s proficiency in depicting streamflow variations over the SRYR, yielding Nash Efficiency Coefficient (NSE) values of 0.44 and 0.61 during the calibration and validation periods, respectively. Compared to the standalone WRF simulations, the coupled WRF-Hydro model demonstrates enhanced performance in soil heat flux simulations, reducing the Root Mean Square Error (RMSE) of surface soil temperature by 0.96 K and of soil moisture by 0.01 m3/m3. Furthermore, the coupled model adeptly captures the streamflow variation characteristics with an NSE of 0.33. This underscores the significant potential of the coupled WRF-Hydro model for describing atmosphere–land–hydrology coupling processes in regions characterized by cold climates and intricate topography.

Analysis of sediment provenance using geochemical and isotopic data for a post-LGM sediment core from the western Great Rann of Kachchh, India: Implications for climate control on source regions

This study addresses the nature and causes of post-Last Glacial Maxima (LGM) sedimentation in the Western Great Rann of Kachchh, Gujarat, India. Specifically, we report geochemical and isotopic data (87Sr/86Sr and 143Nd/144Nd) for a 46.5 m sediment core from the Nara River bed. These data indicate that up to the beginning of the Holocene, sedimentation mostly comprised contributions from monsoon-dominated rivers of Western Himalaya. Later in the early Holocene, a shift towards Indus-derived sediments occurred, with a minor reversal at ∼7 ka, attributed to the rejuvenation of the Ghaggar-Hakra channel. A renewed contribution from the Indus River routed through the Nara River and through the Kori Creek (mouth of the Nara River) occurred during the mid- to late Holocene. Persistent availability of freshwater during the mid- to late Holocene helped sustain early Iron Age and medieval cultures in the region. However, significant decline in the hydrological system anchored in the shifting Indus River through the Nara channel after the medieval period, likely caused the gradual collapse of these cultures. Our study is important as it demonstrates that, if the sediment source is from regions of contrasting climatic domains (for example, monsoon-dominated western Himalaya rivers and the westerlies-dominated Indus River), temporal changes in precipitation intensities exert a first order control in modulating the sediment provenances.

Opportunities and challenges for precipitation forcing data in post‐wildfire hydrologic modeling applications

AbstractThe frequency and extent of wildfires have increased in recent decades with immediate and cascading effects on water availability in many regions of the world. Precipitation is used as primary input to hydrologic models and is a critical driver of post‐wildfire hydrologic hazards including debris flows, flash floods, water‐quality effects, and reservoir sedimentation. These models are valuable tools for understanding the hydrologic response to wildfire but require accurate precipitation data at suitable spatial and temporal resolutions. Wildfires often occur in data‐sparse, headwater catchments in complex terrain, and post‐wildfire hydrologic effects are particularly sensitive to high‐intensity, short‐duration precipitation events, which are highly variable and difficult to measure or estimate. Therefore, the assessment and prediction of wildfire‐induced changes to watershed hydrology, including the associated effects on ecosystems and communities, are complicated by uncertainty in precipitation data. When direct measurements of precipitation are not available, datasets of indirect measurements or estimates are often used. Choosing the most appropriate precipitation dataset can be difficult as different datasets have unique trade‐offs in terms of spatial and temporal accuracy, resolution, and completeness. Here, we outline the challenges and opportunities associated with different precipitation datasets as they apply to post‐wildfire hydrologic models and modeling objectives. We highlight the need for expanded precipitation gage deployment in wildfire‐prone areas and discuss potential opportunities for future research and the integration of precipitation data from disparate sources into a common hydrologic modeling framework.This article is categorized under: Science of Water > Hydrological Processes Science of Water > Methods Science of Water > Water and Environmental Change

The hydrology of the Jezero crater paleolake: Implications for the climate and limnology of the lake system from hydrological modeling

Jezero crater, the landing site of the Perseverance rover, hosts sedimentary fan deposits, aqueously altered sedimentary rock, and an outlet breach of the crater rim, all of which indicates that a long-lived lake (or lakes) once existed within the crater. The deltaic deposits in the crater may preserve evidence of habitable conditions within the past lake system, which would have been influenced by the climate and conditions of the past hydrological system within the watersheds and basin. However, the aqueously altered sedimentary deposits within Jezero are less extensive than those found in other crater lakes on Mars, like Gale with a crater filling mound of cemented sediment. In this work we use hydrological models of the past Jezero lake system to constrain the climatic and hydrological conditions by comparing model predictions to the proposed lake stands and mineralogy in the crater observed from orbit and by the Perseverance rover thus far. We then compare these results to Gale crater to understand the influence of basin hydrology on the depositional setting found within past crater lakes. We show that a lake forming at the outlet breach elevation or higher in Jezero requires a semiarid or wetter-arid climate, consistent with previous estimates. An integrated hydrologic system with seasonal variations similar to arid and semiarid climates on Earth results in a lake system at Jezero characterized by both surface and subsurface outflow from the lake. Outflow to the subsurface and through the outlet breach will remove dissolved solids from the lake system, mitigating large-scale evaporite cementation within the Jezero basin, which is in contrast to Gale crater, where subsurface inflow constituted a larger percentage of the total inflow to the lake and all loss was through evaporation due to the setting in a deeper impact crater. Furthermore, at hyperarid climatic and/or groundwater-driven hydrological conditions, lake formation within Jezero would have ceased while a lacustrine depositional environment would have continued at Gale. This highlights the importance of considering basin hydrology, in addition to climate, when interpreting lacustrine sedimentary deposits in craters on Mars.

Predicted evaporation in Basrah using artificial neural networks

Abstract Accurate evaporation estimation is crucial for managing hydrologic, hydraulic, and agricultural systems, among many other applications of water resources. Empirical formulae for estimating evaporation exist, but their performance is not always sufficient due to the intricacy of the process and its nonlinear connection with other elements of the hydrological cycle. For this reason, a model of artificial neural networks was developed to estimate the daily potential evaporation in the southern Iraqi city of Basrah. A feedforward backpropagation (BP) network with a single hidden layer has been used to construct the mode. Different networks with various neuron counts were assessed. The developed models have been trained, tested, and validated using daily observations of the average rainfall, wind speed, average temperature, average relative humidity, and evaporation. The final evaporation was predicted using an artificial neural network (ANN) model. The proposed model was found to be more suitable to describe evaporation in any region of the world based on the values of the error analysis and the coefficient of determination, according to the ANN model. The Levenberg–Marquardt algorithm (LMA) was determined to have the lowest mean-squared error (MSE) and highest value of the coefficient of correlation (R) of the six proposed BP algorithms. The LMA’s hidden layer’s ideal neuron count was 30 neurons, with an MSE of 0.00288 and R 2 = 99. As a result, ANN displayed excellent performance in terms of evaporation prediction value. The study’s findings highlight the significance of predicting evaporation as the main metric for evaluating the effects of climate change on water resources.

Assessment of the influence of DTM quality on dam rupture simulation processes

Computer programs applied to disaster simulation are widely used and widespread today, taking as input various data types, from specific to the application area to DTMs (Digital Terrain Models). This need for data input and, in particular, data related to relief is very relevant in prediction procedures for forecasting catastrophes, such as the failure of tailings mining deposit dams. Therefore, it is of fundamental importance to know and quantify the quality of this input data in question, in order to effectively serve this application. To this end, in this research, several tests were carried out, using as a reference for best results those obtained with the introduction of DTM from a LIDAR (Light Detection and Ranging) flight survey, this data being used as one of the primary and input into HEC-RAS (Hydrologic Engineering Center-River Analysis System). Subsequently, these same data had their spatial resolution degraded, that is, the pixel size increased, generating models with worse quality for new inputs and obtaining new simulation results of mining dam failures. The test area of the B1 Dam, located in Brumadinho-MG, Brazil, was used as a laboratory, where one of the biggest mining disasters in the world recently occurred and, for which, there are real data from the area affected by the dam collapse. The results obtained demonstrated that the use of an DTM with a spatial resolution of at least 2.5 meters or better, with DTM class A cartographic quality compatible with the most recent Brazilian standard, would guarantee reliable results.

Assessing potential barriers to migratory Walleye in the Sandusky River, Ohio

AbstractObjectiveThe Sandusky River, Ohio, is one of the major Lake Erie tributaries that supports migratory Walleye Sander vitreus reproduction. Following the construction of the Ballville Dam in 1913, Walleye spawning was limited to an area downstream near Fremont, Ohio. After the removal of the dam in 2018, several natural and human‐made features were identified that may impede Walleye passage by collecting woody debris and altering flow conditions. In this study, we use hydrologic modeling and migratory sampling to understand the spatial and temporal dynamic nature of the blockages caused by the remaining anthropogenic and natural barriers.MethodsWe created a fine‐scale Hydrologic Engineering Center's River Analysis System (HEC‐RAS) model to examine these potential natural and human‐made barriers to Walleye passage during spawning. Using our model, we compared swim speeds (10 min maintained and burst) of small, medium, and large Walleye under three flow scenarios with five levels of blockage to assess whether the area was passable. Further, we conducted electrofishing surveys during annual spawning runs from 2020 to 2021 to assess Walleye presence upstream and downstream after dam removal.ResultOur model predicted that Walleye were able to pass the barriers under most of the scenarios by maintaining burst swim speed. Additionally, we captured Walleye above the former dam site in 2021, suggesting that Walleye can access newly available spawning habitat during certain river conditions.ConclusionRemoving the Ballville Dam restored fish passage, increased access to spawning habitat, and could improve Walleye production in the Sandusky River.

Harnessing climate services to support community resilience planning: lessons learned from a community-engaged approach to assessing NOAA’s National Water Model

IntroductionInland and coastal flooding and other water-based natural disasters are projected to increase in severity, frequency, and intensity as global temperatures rise, placing a growing number of US communities at risk. Governments at the local, state, and federal levels have been embracing resilience planning to better predict, mitigate, and adapt to such shocks and hazards. A growing number of climate services have been developed to aid communities engaged in these efforts to access, interpret, and make decisions with climate-related data and information. An important tool for potentially supporting this planning is the National Water Model (NWM), created by the National Oceanic and Atmospheric Administration’s (NOAA) National Water Center (NWC). The NWM is a river and streamflow model that can forecast conditions for the continental United States.MethodsHowever, community end-users were not being effectively engaged in ways that result in widespread tool use and adoption. From 2021 to 2023, seven geographically diverse US communities agreed to participate in a study to understand how the NWM might be applied in resilience planning. Interviews and collaborative sessions were conducted with NWC/NOAA staff and community resilience stakeholders in Burlington, VT; Cincinnati, OH; Portland, OR; Charlotte, NC; Boulder, CO; Minneapolis; MN; and Houston, TXResults and DiscussionResults provide an improved understanding of potential applications of the National Water Model and have identified actions to overcome the barriers to its use among municipal and regional resilience planners. This research yielded a set of recommendations, co-developed between the seven communities and NWC/ NOAA staff, for how these barriers could be overcome to facilitate wider use of the NWM and its data and visualization services in resilience planning. This study highlights the NWM’s applicability at shorter timescales in resilience planning and points to a more general need for climate services to accommodate near-, medium-, and longterm time frames. The study also found many community stakeholders who use water science and information in resilience planning have diverse disciplinarily backgrounds. Importantly, the majority were not trained hydrologists or water scientists, pointing to the critical need for climate service developers, including the NWC, to embrace co-development efforts that involve a wider range of end-users, including community resilience planners.

Characterizing sub-glacial hydrology using radar simulations

Abstract. The structure and distribution of sub-glacial water directly influences Antarctic ice mass loss by reducing or enhancing basal shear stress and accelerating grounding line retreat. A common technique for detecting sub-glacial water involves analyzing the spatial variation in reflectivity from an airborne radar echo sounding (RES) survey. Basic RES analysis exploits the high dielectric contrast between water and most other substrate materials, where a reflectivity increase ≥ 15 dB is frequently correlated with the presence of sub-glacial water. There are surprisingly few additional tools to further characterize the size, shape, or extent of hydrological systems beneath large ice masses. We adapted an existing radar backscattering simulator to model RES reflections from sub-glacial water structures using the University of Texas Institute for Geophysics (UTIG) Multifrequency Airborne Radar Sounder with Full-phase Assessment (MARFA) instrument. Our series of hypothetical simulation cases modeled water structures from 5 to 50 m wide, surrounded by bed materials of varying roughness. We compared the relative reflectivity from rounded Röthlisberger channels and specular flat canals, showing both types of channels exhibit a positive correlation between size and reflectivity. Large (> 20 m), flat canals can increase reflectivity by more than 20 dB, while equivalent Röthlisberger channels show only modest reflectivity gains of 8–13 dB. Changes in substrate roughness may also alter observed reflectivity by 3–6 dB. All of these results indicate that a sophisticated approach to RES interpretation can be useful in constraining the size and shape of sub-glacial water features. However, a highly nuanced treatment of the geometric context is necessary. Finally, we compared simulated outputs to actual reflectivity from a single RES flight line collected over Thwaites Glacier in 2022. The flight line crosses a previously proposed Röthlisberger channel route, with an obvious bright bed reflection in the radargram. Through multiple simulations comparing various water system geometries, such as canals and sub-glacial lakes, we demonstrated the important role that topography and water geometry can play in observed RES reflectivity. From the scenarios that we tested, we concluded the bright reflector from our RES flight line cannot be a Röthlisberger channel but could be consistent with a series of flat canals or a sub-glacial lake. However, we note our simulations were not exhaustive of all possible sub-glacial water configurations. The approach outlined here has broad applicability for studying the basal environment of large glaciers. We expect to apply this technique when constraining the geometry and extent of many sub-glacial hydrologic structures in the future. Further research may also include comprehensive investigations of the impact of sub-glacial roughness, substrate heterogeneity, and computational efficiencies enabling more complex and complete simulations.

Editorial: Emerging talents in water science: water and critical zone 2021/22

Editorial: Emerging talents in water science: water and critical zone 2021/22

Advanced floodplain mapping: HEC-RAS and ArcGIS pro application on Swat River

AbstractFloods stand out as one of the most devastating environmental threats worldwide resulting in the tragic loss of human lives and significant damage to our essential infrastructure. This study focuses on creating floodplain maps for the two important reaches of Swat River in the Khyber Pakhtunkhwa Province of Pakistan, namely, Kalam–Khwazakhela and Khwazakhela–Chakdara reaches. The Advanced Land Observing Satellite Phased Array Type L-band Synthetic Aperture Radar (ALOS PALSAR) 12.5 m Digital Elevation Model (DEM) data has been used for this purpose. Furthermore, the sensitivity of the flood model was assessed for the Flood 2022 event, considering simulated flood depth, extent, and velocity in relation to various terrains derived from the 12.5-m ALOS PALSAR data. To estimate extreme flows for different return periods (2, 5, 10, 25, 50, and 100 years), the Log Normal (LN), Log Pearson III (LP3), and Generalized Extreme Value (GEV) distributions were employed for the frequency analysis. The GEV distribution turned out to be the best fit for modeling the Swat River for both the Chakdara and Khwazakhela gauge stations. To predict flood levels for the peak floods identified through frequency analysis and for the specific return periods the Hydrologic Engineering Center's River Analysis System (HEC-RAS) 2D simulations were performed. Subsequently the outcomes of this model were used to create floodplain maps using Geographic Information System Professional (ArcGIS Pro) software customized for various return periods. The analysis revealed a linear increase in flood inundation area with longer return periods. The floodplain maps developed hold significant importance for the governing authorities of the Swat region. These maps serve as essential tools for implementing proactive measures against potential infrastructure damage, thereby protecting against economic losses and enhancing public safety. This research effectively combines hydrological modeling and geospatial technology offering practical solutions for managing flood risks. It serves as a valuable guide for making well-informed decisions and promoting sustainable development in flood-prone areas.