# data[].attributes.body
Name: Roberta Horton

Email: rhorton@riveru.edu

Career Stage: Graduate student

Affiliation: River University

Social Media: hydrohorton on BlueSky

DOI: https://doi.org/10.5194/essd-17-461-2025

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< 100 word blurb:

As a catchment hydrologist interested in sensitivity and uncertainty analysis of rainfall-runoff models, I was excited by this recent addition to CAMELS: CAMELS-IND. This paper includes data to analyze and model 472 catchments across India. I know the amount of time and effort that can go into making a large dataset, and that's why I find this work especially impressive. Considering that hydrological data are usually biased toward the US and Europe, this study is an important example of expanding data availability and access to areas in the Global South. I'm excited to explore this dataset further.

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Signiﬁcant Baseﬂow Reduction in the São Francisco River Basin  

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Signiﬁcant Baseﬂow Reduction in the São Francisco River Basin  

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Name: José Gescilam Uchôa Email: gescilam@usp.br Career Stage: Graduate student Affiliation: University of São Paulo Social Media: @GescilamUchoa on X, @gescilam.bsky.social on BlueSky DOI: https://doi.org/10.3390/w13010002 I consent to my post being shared on social media. < 100 word blurb: I like this paper because it highlights the need for integrated water resource management that considers both groundwater and surface water. Historically, in many countries—including Brazil—these resources have been managed separately. This study analyzes long-term (1980–2015) trends in streamflow and baseflow in the São Francisco River Basin, alongside precipitation, evapotranspiration, and changes in terrestrial water storage. The results indicate a decline in groundwater contributions (i.e., baseflow) to the river, suggesting that groundwater withdrawals are likely a key driver of the observed negative trend, particularly in the heavily irrigated Middle Basin region.

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Significant Baseflow Reduction in the Sao Francisco River Basin

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Water scarcity is a key challenge to global development. In Brazil, the Sao Francisco River Basin (SFB) has experienced water scarcity problems because of decreasing streamflow and increasing demands from multiple sectors. However, the drivers of decreased streamflow, particularly the potential role of the surface-groundwater interaction, have not yet been investigated. Here, we assess long-term trends in the streamflow and baseflow of the SFB during 1980–2015 and constrain the most likely drivers of observed decreases through a trend analysis of precipitation (P), evapotranspiration (ET), and terrestrial water storage change (TWS). We found that, on average, over 86% of the observed decrease in streamflow can be attributed to a significant decreasing baseflow trend along the SFR, with a spatial agreement between the decreased baseflow, increased ET, and irrigated agricultural land in the Middle SFB. We also noted a decreasing trend in TWS across the SFB exceeding –20 mm year−1. Overall, our findings indicate that decreasing groundwater contributions (i.e., baseflow) are providing the observed reduction in the total SFR flow. A lack of significant P trends and the strong TWS depletion indicate that a P variability only has likely not caused the observed baseflow reduction, in mainly the Middle and Sub-middle SFB. Therefore, groundwater and surface withdrawals may likely be a driver of baseflow reduction in some regions of the SFB.

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Name: Sididk Barbhuiya

Email: siddikbarbhuiya@gmail.com

Career Stage: PhD Scholar at IIT Mandi, INDIA

Affilitaion: IIT Mandi

Social Media: https://www.linkedin.com/in/barbhuiya12/

DOI: 10.22541/au.173801002.25089607/v2

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Short Summary of paper:

Predicting streamflow in ungauged or poorly gauged basins remains one of hydrology’s grand challenges—especially in countries like India, where climatic and physiographic diversity is extreme, and observational networks are sparse. This study introduces UBLSTM, a deep learning model that estimates river flow without relying on past discharge data, achieving near-parity with traditional models. It represents a major step toward solving the Prediction in Ungauged Basins (PUB) problem. Hydrologists working in data-limited regions or pursuing scalable, AI-driven solutions for water management should read this work—it offers a powerful, transferable approach for hydrological forecasting across the globe.

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Attribution of the 2015 drought in Marathwada, India from a multivariate perspective

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Debdut Sengupta

PhD Student, IIT Madras

In recent times, the increasing frequency and intensity of extreme events necessitates the application of event attribution analysis to assess the relative contributions of natural and anthropogenic factors.

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Indian Institute of Technology Roorkee, Roorkee, Uttarakhand

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Mapping Global Irrigation Quantities from Space!

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Mapping Global Irrigation Quantities from Space!

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Name: Mukund Narayanan

Email: mukundnarayanan1997@gmail.com

Affliation: Indian Institute of Technology Roorkee

Career Stage: Ph.D. Candidate

Social Media: LinkedIn , X

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Paper: Estimation of Global Irrigation Water Use by the Integration of Multiple Satellite Observations

DOI: https://doi.org/10.1029/2021WR030031

Brief Overview:

Agriculture consumes the most freshwater (70%) on Earth, making it critical to accurately measure irrigation water quantities for sustainable water management. However, imagine trying to track how much water every farm on earth uses for irrigation: a massive challenge, right? Traditionally, getting precise global data on irrigation has been a huge challenge.

But what if satellites could help? This exciting research presents a powerful new way to estimate global irrigation water use directly from space. By optimizing water balance models with satellite based observations of eight different soil moisture datasets and four precipitation datasets, scientists identify irrigation events and quantify water use more accurately than before at effectively every farm on earth. This study’s groundbreaking method helps us see where and how much water is being used, improving our ability to manage this precious resource sustainably. It's a big leap for hydrology and essential reading for anyone passionate about water!

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Indian Institute of Technology Roorkee, Roorkee, Uttarakhand

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Small reservoirs: Hidden hotspots of drought intensification

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Small reservoirs: Hidden hotspots of drought intensification

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Submitted by:
Name: Ankit Sharma

Email: a_sharma@wr.iitr.ac.in

Affiliation: Indian Institute of Technology, Roorkee, India
Career stage: Ph.D. Student
LinkedIn: linkedin.com/in/sharmasankit

Consent: I consent to the AGU Catchment Hydrology Technical Committee sharing my entry on social media and linking the study DOI to their Padlet board.

Study Details:

Title: Drought Cycle Analysis to Evaluate the Influence of a Dense Network of Small Reservoirs on Drought Evolution

Authors: G. G. Ribeiro Neto, L. A. Melsen, E. S. P. R. Martins, D. W. Walker, P. R. van Oel

DOI: https://doi.org/10.1029/2021WR030799

This study unveils an intriguing paradox in drought management: small reservoirs, widely used as a coping mechanism against drought, can unintentionally prolong and intensify drought conditions. Through an innovative "Drought Cycle Analysis," which integrates satellite-derived reservoir volumes (Landsat imagery) with precipitation indices, this research demonstrates that dense networks of small reservoirs in Brazil’s semi-arid Riacho do Sangue watershed extend hydrological droughts by approximately 30%, and up to twice as long in specific cases. This compelling finding highlights the critical need for hydrologists globally to account for the impacts of unmonitored small reservoirs, guiding more resilient and sustainable drought management strategies.

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Name: Rachel Breunig

Email: rachel.breunig@wisc.edu

Career Stage: PhD student

Affiliation: University of Wisconsin- Madison

Social Media: @rebreunig.bsky.social

DOI: https://doi.org/10.1016/j.jsames.2025.105412

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Why is it important/ Why should other hydrologists read this paper?:

Rojas-Castillo et al. creatively use unconventional data to construct a conceptual framework explaining the sequence of events that led to a destructive river avulsion in Chaitén, Chile, despite a long-term paucity of monitoring data spanning the event. They navigate a complex sequence of volcanic eruption, extreme rainfall, lahars, and rapid knickpoint migration to present a compelling model that supports mitigation of future extreme rainfall events in the area. This study actively demonstrates that valuable scientific insights can emerge from data-scarce regions and reminds us that advancing hydrologic science requires valuing diverse data sources and broadening its geographic inclusivity.

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We developed a combined drought index to better monitor agricultural drought events. To develop the index, different combinations of the temperature condition index, precipitation condition index, vegetation condition index, soil moisture condition index, gross primary productivity, and normalized difference water index were used to obtain a single drought severity index. To obtain more effective results, a mesoscale hydrologic model was used to obtain soil moisture values. The SHapley Additive exPlanations (SHAP) algorithm was used to calculate the weights for the combined index. To provide input to the SHAP model, crop yield was predicted using a machine learning model, with the training set yielding a correlation coefficient (R) of 0.8, while the test set values were calculated to be 0.68. The representativeness of the new index in drought situations was compared with established indices, including the Standardized Precipitation-Evapotranspiration Index (SPEI) and the Self-Calibrated Palmer Drought Severity Index (scPDSI). The index showed the highest correlation with an R-value of 0.82, followed by the SPEI with 0.7 and scPDSI with 0.48. This study contributes a different perspective for effective detection of agricultural drought events. The integration of an increased volume of data from remote sensing systems with technological advances could facilitate the development of significantly more efficient agricultural drought monitoring systems.

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Name: Jan Kreibich

Email: j.kreibich@unsw.edu.au

Career stage: ECR

Affiliation: UNSW Sydney

Social media: https://www.linkedin.com/in/jan-philipp-kreibich/

DOI: https://doi.org/10.1016/j.jenvman.2024.122962

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< 100 word blub:

The Murrumbidgee River is one of Australia’s largest and most heavily regulated river systems, with climate change projected to increase existing pressures. We modeled ‘natural’ streamflow to evaluate the impacts of river regulation and climate change on flow and flood regimes. Our results show overbank flow duration could decline by up to 85%, threatening major floodplain wetlands. These semi-arid wetlands are among eastern Australia’s largest waterbird breeding sites and home to 50,000 years of rich Aboriginal cultural heritage. Our research informs environmental flow management aimed at restoring this ecologically and culturally important wetland ecosystem at a landscape scale.

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Why this study matters:

This study assesses the long-term performance and cost-effectiveness of rainwater harvesting systems (LID) in Barcelona using a “15-minute city” framework. Through hydrologic modeling (SWMM), LCA (SimaPro), and MCA, it evaluates Infiltration Trenches, Rain Gardens, and Rooftop Disconnects under climate change scenarios. Results show that Infiltration Trenches offer the best environmental and economic outcomes. This work advances sustainable urban water management outside the US/EU context and supports evidence-based adaptation planning.

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Name: Lahcen Goumghar

Email: lahcen.goumghar@gmail.com

Affiliation: University of Québec in Abitibi-Témiscamingue (UQAT) / Ibn Tofail University, Faculty of Sciences.

Career level: Graduate student (PhD M.Sc. in Engineering – Environmental Sciences)

LinkedIn: https://www.linkedin.com/in/lg3/

This study assessed flood susceptibility in Morocco’s Draa Oued Noun Basin using a decision-based modeling approach that integrates key hydrogeological and geomorphological factors. It highlights the importance of spatial analysis tailored to local conditions to support flood management and land-use planning. This work led to a follow-up study using artificial intelligence to enhance flood prediction and model interpretability. Ongoing hydraulic simulations aim to better understand flood dynamics. This research is especially relevant for hydrologists working in climate-sensitive and under-documented regions where flood risk is rising and data availability is limited.

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University of Calabria, Via Pietro Bucci, Arcavacata, CS

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University of Calabria, Via Pietro Bucci, Arcavacata, CS

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University of Calabria, Via Pietro Bucci, Arcavacata, CS

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Luca Furnari

luca.furnari@unical.it

University of Calabria

Research Assistant

We present HydroCAL, a next-generation, fully physically based integrated surface–subsurface hydrological model (ISSHM) designed to capture complex hydrological processes with high resolution. Built on the Cellular Automata paradigm and powered by the OpenCAL computational library, HydroCAL seamlessly harnesses the combined power of CPUs and GPUs, significantly reducing computation time without compromising accuracy. The model has been tested against established literature benchmarks and real-world catchments, consistently delivering outstanding results. HydroCAL not only ensures mass balance fidelity but also provides rich, spatially distributed insights into both surface and subsurface dynamics, making it a powerful tool for advancing hydrological research and applications.

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Name: Georgios Vagenas

Email: georgios.vagenas@mncn.csic.es

Career stage: PhD student

Social media: ‪@gvagenas.bsky.social‬

DOI: https://doi.org/10.1016/j.scitotenv.2024.176373

Location: Arid and Desert regions in the vicinity of the Sahara Desert (Morocco)

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I consider this study important because it pioneers ecohydrological models for aquatic biota in North Africa’s regulated rivers, addressing a critical gap in arid-desert climatic zones. By integrating a novel ecohydraulic modeling framework, we establish the first e-flow simulations for these systems, revealing hydraulic suitability in extreme arid systems. Hydrologists should read this work because it provides information for water-stressed regions, balancing dam operations with ecosystem needs under climate change. The alarming drought status of these rivers underscores the urgency of implementing science-based flows to sustain biodiversity and water security in one of the world’s most vulnerable hydrologic regions.

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Contact Information:

Name: Luis Eduardo Mier-Valderrama

University: Virginia Tech (graduate student)

Email: luismier@vt.edu

Cel: 361.522.8924

Explanation:

This study covers 25 headwater catchments in the tropical Andes (Ecuador, Peru, Bolivia), a region critical yet underrepresented in global hydrology. It addresses a major knowledge gap on how cultivation, afforestation, and grazing alter hydrological processes amid widespread ecosystem degradation. Hydrologists should read this work because it reveals consistent patterns of increased streamflow variability and reduced catchment regulation and water yield due to land use. Using the innovative iMHEA participatory monitoring network, the study offers rare, high-quality data from data-scarce, human-impacted regions, essential for improving water resource management beyond traditionally studied areas.

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Name: Jiangtao Liu

Email: liujiangtao3@gmail.com

Career Stage: Graduate student

Affiliation: The Pennsylvania State University

Social Media: https://www.linkedin.com/in/jiangtaoliud/

DOI: https://doi.org/10.5194/gmd-16-1553-2023

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< 100 word blurb:

This study introduces a multitask LSTM model combining satellite and in situ data to enhance global soil moisture predictions, particularly for poorly monitored regions like Africa and the Middle East. It outperforms existing products, offering critical insights for water resource management, crop threat mitigation, pest outbreaks, and climate adaptation. Hydrologists will benefit significantly in addressing water-related challenges in data-scarce areas.

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Jiangtao Liu, David Hughes, Farshid Rahmani, Kathryn Lawson, and Chaopeng Shen

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Evaluating a global soil moisture dataset from a multitask model (GSM3 v1.0) with potential applications for crop threats

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Abstract. Climate change threatens our ability to grow food for an ever-increasing population. There is a
need for high-quality soil moisture predictions in under-monitored regions
like Africa. However, it is unclear if soil moisture processes are globally
similar enough to allow our models trained on available in situ data to
maintain accuracy in unmonitored regions. We present a multitask long
short-term memory (LSTM) model that learns simultaneously from global
satellite-based data and in situ soil moisture data. This model is evaluated in
both random spatial holdout mode and continental holdout mode (trained on
some continents, tested on a different one). The model compared favorably to
current land surface models, satellite products, and a candidate machine
learning model, reaching a global median correlation of 0.792 for the random
spatial holdout test. It behaved surprisingly well in Africa and Australia,
showing high correlation even when we excluded their sites from the training
set, but it performed relatively poorly in Alaska where rapid changes are
occurring. In all but one continent (Asia), the multitask model in the
worst-case scenario test performed better than the soil moisture active
passive (SMAP) 9 km product. Factorial analysis has shown that the LSTM model’s
accuracy varies with terrain aspect, resulting in lower performance for dry
and south-facing slopes or wet and north-facing slopes. This knowledge
helps us apply the model while understanding its limitations. This model is
being integrated into an operational agricultural assistance application
which currently provides information to 13 million African farmers.

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Evaluating land use and climate change impacts on Ravi river flows using GIS and hydrological modeling approach

DOI: 10.1038/s41598-024-73355-2

Shanza Arshad

engineershanzaarshad@gmail.com

Forman Christian College University, Lahore, Pakistan

Graduate Student

www.linkedin.com/in/shanzaarshad

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Using GIS, remote sensing, and SWAT-model simulations, this study evaluates combined land-use and climate change influences on the Ravi River catchment (calibrated for 1999–2005, NSE > 0.85). It projects a 31.7% increase in built-up area by 2100 and rising precipitation (up to +14.9%) under SSP scenarios—leading to a 19–28% increase in river inflows. With observed groundwater declines (~0.8 m/year), this work is crucial for sustainable water planning in semi-arid South Asia. Hydrologists exploring urbanizing, data-scarce basins should read it to integrate future change scenarios into water-resource management.

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Evaluating land use and climate change impacts on Ravi river flows using GIS and hydrological modeling approach

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Helmholtz Centre for Environmental Research - UFZ, Permoserstraße, Leipzig-Ost

# data[].attributes.attachment_caption
Hengduan Mountains with the Irrawady, Salaween, Mekong, and Yangtze rivers running parallel to each other. Comparison of (a) the base map subgrid stream network against the stream network upscaled by the (b) D8, (c) FLOW, and (d) SCC schemes. (e) Zoom-in of the pixel E4 showing the multiple outflowing links using SCC.

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SCC - A Game changer for Streamflow Routing in Grid-based Hydrological Models

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SCC - A Game changer for Streamflow Routing in Grid-based Hydrological Models

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Name: Pallav Kumar Shrestha

Computational hydrologist and model developer

Contact: pallav-kumar.shrestha@ufz.de

DOI: https://doi.org/10.1029/2024WR038183

Why important?

A break thought paper that provides solution to modeling small catchments, unresolved since 2000s:

Accurately represents catchments as small as 1 km² using meso-scale grids for faster runtime, crucial for flood modeling.

Model performance independent of pixel resolution, supporting flexible computational demands.

Resolves multiple gauges or dams per pixel, removing a key barrier in continental-scale streamflow modeling.

Why read?

Demonstrates a computationally agile alternative to be equally performant as hyper-resolution modeling.

Thumb rule: catchments should be >30 pixels for reliable results using "status quo" D8 method.

Comprehensive literature review on stream network upscaling to model resolution.

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Indian Institute of Technology Roorkee, Roorkee, Uttarakhand

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Indian Institute of Technology Roorkee, Roorkee, Uttarakhand

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Indian Institute of Technology Roorkee, Roorkee, Uttarakhand

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Submitted by

Name: Meena Sakthivel Pandian

Email: meena_s@wr.iitr.ac.in

Affiliation: Indian Institute of Technology Roorkee, India

Designation: PhD scholar

Linkeldn: linkedin.com/in/meena-sakthivel-pandian-033a72149

Consent: I consent to the AGU catchment hydrology Technical Committee sharing my entry on social media and linking the study DOI to their Padlet board.

Title of the study: Biogeochemical hotspots: Role of small water bodies in landscape nutrient processing

Authors: Frederick Y. Cheng, Nandita B. Basu

Year of Publication: 2017

Journal: Water Resources Research

DOI: https://doi.org/10.1002/2016WR020102

This study, for the first time, quantified the significant role small wetlands (SWs) play in nutrient (Nitrogen (N) and Phosphorus (P)) processing, and emphasized the need for their restoration, which are often globally overlooked. A mechanistic model of water-sediment interactions was developed to identify dominant controls on nutrient removal, highlighting differences in N and P dynamics and the influence of wetland size on nutrient removal. An interesting finding is that smaller wetlands have greater nutrient removal potential than larger wetlands for an equivalent amount of wetland area. Hydrologists should read this for insights into SWs’ role in water quality improvement.

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Name: Amirhossein Mirdarsoltany

Email: amirsoltanist@gmail.com

Affiliation: Leibniz University Hannover

Career Level: M.Sc. in Water Resources Engineering

LinkedIn: https://www.linkedin.com/in/amirhossein-mirdarsoltany-a4132816b?lipi=urn%3Ali%3Apage%3Ad_flagship3_profile_view_base_contact_details%3BYkckau7BQVeKSZ7VQTBR%2Bw%3D%3D

This research is crucial for improving drought monitoring using both parametric and non-parametric SPI methods, enhancing accuracy across varying climates and timescales. It introduces advanced techniques like GIS-based IDW and image processing for spatial analysis, vital under changing climate conditions.

Hydrologists should read it to understand how different SPI methods affect drought assessment, support water resource management, and improve regional planning. The study’s integration of climate models, interpolation methods, and drought metrics offers practical tools for forecasting and mitigating hydrological impacts, especially in arid and semi-arid regions like Iran.

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Name: Amirhossein Mirdarsoltany

Email: amirsoltanist@gmail.com

Affiliation: Leibniz University Hannover

Career Level: M.Sc. in Water Resources Engineering

LinkedIn: https://www.linkedin.com/in/amirhossein-mirdarsoltany-a4132816b?lipi=urn%3Ali%3Apage%3Ad_flagship3_profile_view_base_contact_details%3BYkckau7BQVeKSZ7VQTBR%2Bw%3D%3D

This article is important because it links agricultural land use changes to hydrological shifts that contributed to the decline of Urmia Lake. It introduces an innovative NDVI-DEM method to better differentiate land types and uses the SWAT model to simulate how increased irrigation and farming led to higher evapotranspiration and reduced streamflow. Hydrologists should read this to understand how integrated land use and water modeling can inform sustainable water management, especially in semi-arid regions facing similar environmental stresses.

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This study introduces an improved satellite precipitation merging method—Signal-to-Noise Ratio Optimization (SNR-opt)—which overcomes limitations of traditional triple collocation (TC), such as the need for three sources and assumptions of uncorrelated errors. Applied over the Himalayas, SNR-opt generated more accurate rainfall estimates using fewer inputs and better captured extremes, which are critical for hydrological modeling in data-scarce high-mountain regions. Hydrologists should read this work for its practical implications: improving precipitation inputs in challenging terrain where ground truth is sparse, and enhancing flood risk analysis, glacier melt studies, and water resources planning in vulnerable catchments.

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Advancing High-Mountain Precipitation Reconstruction Through Merging of Multiple Data Sources: Triple Collocation Versus Signal-to-Noise Ratio Optimization

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Merging multisource satellite precipitation data through triple collocation (TC) is an established method for enhancing precipitation estimates without ground observations. However, the effectiveness of TC is limited by three constraints: the need for three data sources, the sum of weights equalling one, and no error cross correlation (ECC) among datasets. These limitations restrict applications to areas with three distinct data sources, may result in suboptimal combinations, and can introduce biases. We explored a new framework, signal-to-noise ratio optimization (SNR-opt), which alleviates these restrictions. Applying TC and SNR-opt to datasets in the Himalayas, including three satellite-based (IMERG Final, CMORPH, and PERSIANN), one soil moisture-based (SM2RAIN-ASCAT), and one reanalysis dataset (ERA5), we assessed their performance. The flexibility of SNR-opt allowed for creating products suited to varying rainfall conditions and reconstructing extreme precipitation products for high-mountain Asia (HMA). The results show that: 1) the data triplet containing IMERG-final was the best performing among all merging products; 2) the merging method significantly enhanced dataset accuracy compared to the parent datasets, with SNR-opt proving superior to TC in all selected precipitation indices evaluated; and 3) SNR-opt had the flexibility of estimating both low and heavy rainfall, with a reduced bias for extreme precipitation, using fewer inputs (two) compared to TC. These advantages were found to be especially notable for the high-mountain region in focus, given the significant variability and limited observational data available.

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Name: Ryoko Araki

Email: raraki8159 (at) sdsu.edu

Career stage: PhD candidate

Social Media: ‪@rarakihydro.bsky.social‬ or @rarakihydro on Twitter. I consent to my post to be shared on social media

DOI: https://doi-org.libproxy.sdsu.edu/10.1002/(SICI)1099-1085(20000215)14:2%3C215::AID-HYP921%3E3.0.CO;2-P

Location: Tropical rainforest steeplands in Brunei

Rainfall-runoff processes in humid tropics remain understudied due to financial and logistical constraints. A case study in Brunei by Dykes and Thornes presents strikingly flashy runoff generation behavior of humid tropical hillslope: runoff coefficient reach 0.4 with little time lag between precipitation, subsurface flow, and streamflow responses. The key is in particle aggregation of tropical clays (looks like lumps of flour), which creates macropores and preferential flow. This finding challanges the conventional use of soil texture-based estimates of hydraulic conductivity, suggesting it might underestimate floods magnitude in humid tropical watersheds. Check out Bonell (2009) book for a comrehensive overview of hydrology in tropical forest.

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Hydrological Processes - 2000 - Dykes - Hillslope hydrology in tropical rainforest steeplands in Brunei

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Name: Brittany Barreto Martinez

I consent to any social media posts

Email: bbarretomartinez@sdsu.edu

Affiliation: San Diego State University (Post-doc)

DOI Link: https://doi.org/10.1016/j.jsames.2022.104151

LinkedIn: https://www.linkedin.com/in/brittany-barreto

Entry: This study is important because it demonstrates the viability of using bias-corrected satellite precipitation data (IMERG) to model hydrological processes in data-scarce regions like the Peruvian Andes. It provides a valuable framework for assessing water resources in remote headwater basins where in-situ measurements are limited. Hydrologists working in similar contexts, whether in mountainous, tropical, or otherwise underserved regions, can benefit from the methodology, especially the use of SWAT modeling with satellite inputs. The results reinforce the importance of bias correction in remote sensing data and underscore the potential for reliable hydrological analysis and resource management even in observation-limited environments.

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Mohammad Hagiri
Ph.D student, Department of Earth and Environmental Science, University of Illinois Chicago, IL, USA.

Email: mhaghi2@uic.edu

Website: https://mhaghiri.github.io/

Linkedin: https://www.linkedin.com/in/mohammad-haghiri77/

CV: https://mhaghiri.github.io/images/Mohammad%20Haghiri_CV_public.pdf

DOI: https://doi.org/10.1007/s12665-024-11734-8

Why this study is important and why hydrologists should read it:

This study introduces a framework for rainwater harvesting in arid and semi-arid regions, integrating remote sensing, GIS, and field visit to identify small-scale rainwater harvesting sites for agriculture consumption.  It demonstrates how simple hydrological analyses and engineering  can collect 450,000 m³ of water per year, and cause decrease groundwater depletion and increase agricultural resilience. This approach is cost-effective, locally adaptable, and environmentally sustainable, offering insights for hydrologists working in water-scarce areas. It shows transferable methods for sustainable water management in other regions.

paper:

Haghiri, M., Asef, M.R. Remote sensing and field visit for small scale runoff harvesting for agricultural water consumption management, case study at Kariyan, Hormozgan, Iran. Environ Earth Sci 83, 416 (2024). https://doi.org/10.1007/s12665-024-11734-8

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Favorite hydrology papers 2025
The AGU TC Catchment Hydrology competition is open to undergraduates, graduate students, and postdocs interested in catchment hydrology. To be entered to win, we ask that you briefly (< 100 words) tell us about a modeling or field-based study with a focus outside of the US or Europe. Globally focused studies are welcome, too! 

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Name: Sohrab Salehi

Email: Sohrabshl@gmail.com

Career Stage: Graduate student

Affiliation: Tarbiat Modares University

Social Media: www.linkedin.com/in/sohrab-salehi-27ba536a

I consent to my post being shared on social media.

The global rain-on-snow (ROS) assessment by Maina & Kumar (2025, Nat. Commun.) impressed me, particularly because of their careful integration of the Noah-MP model with bias-corrected CMIP6 climate data. They effectively demonstrate that ROS events, key to floods and runoff responses, will significantly shift in location and timing by 2100. This study provides a robust modeling framework and critical insights into how snow hydrology is evolving, offering essential information that hydrologists working in cold and mountainous regions should definitely consider.

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Global patterns of rain-on-snow and its impacts on runoff from past to future projections - Nature Communications

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This study reveals that rain-on-snow is becoming more frequent in many mountain and northern regions, but its contribution to runoff is expected to decline due to shrinking snowpack and increasing rainfall.

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Name: Nisha Jindwal

Email: jindwalnisha@gmail.com

Career Stage: M.Tech. Research Scholar at IIT Mandi, INDIA

Affiliation: IIT Mandi

Social media: https:/www.linkedin.com/in/nishajindwal

DOI: 10.9734/jsrr/2025/v31i53060

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Short Summary of Paper:

This field study in the Himalayan region documents how severe forest fires lead to significant reductions in soil moisture and water storage, with some sites losing up to 60% of their capacity post-fire. By analyzing 42 burn sites, the research shows how vegetation loss and soil degradation disrupt runoff patterns and groundwater recharge, threatening water resources relied upon by millions. Understanding these fire-driven hydrological changes is essential for managing water security in fire-prone mountain landscapes, especially under changing climate conditions. This work offers valuable insights for hydrologists working on regional and global water challenges.

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View of Post-Fire Hydrological Impacts and Water Storage Changes in the Forests of Uttarakhand, India

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Name: Jack Boyle

Career Stage: PhD Student

Institution: University of Virginia

Contact: pzy5nd@virginia.edu

DOI: 10.1061/JHYEFF.

Location: Critical Watersheds around British Columbia, Canada

Why this study matters:

Hydrological conditions following wildfire can reshape landscapes, pollute water, and threaten human life. This Canadian study combines prefire hydrological modeling with “worst-burn” scenario simulations to estimate changes in peak flood flows after wildfire. Unburned vs. burned conditions are compared using flood frequency analysis to pinpoint high-risk watersheds. Conducting this research outside the US or Europe is important because it focuses on locations where wildfire data are limited, highlighting overlooked communities. This streamlined, transferable method enables hydrologists to screen flood hazards in data-scarce regions, allowing faster, more targeted mitigation in diverse landscapes facing increasing wildfire–flood risks.

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Tehran’s fast-responding urban catchments demand sub-hourly rainfall forecasts. Using 368 storms from Niavaran station (Tehran, Iran), we benchmark PSO-SVR, LSTM, and CNN at 5–15-min lead times and introduce two boosts: event-type models (duration/severity clusters) and “difference” + fine-scale (5-min) fluctuation features. LSTM excels at 5-min, PSO-SVR at 15-min; clustering/features raise skill and sharpen peaks. The recipe is data-light, compute-light, and transferable to data-sparse cities facing flash-flood risk(https://doi.org/10.1016/j.jhydrol.2022.128463)

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Most urban flood studies stop at prediction; we turn forecasts into action. In Tehran, we couple 5–15-minute rainfall forecasts (LSTM, PSO-SVR) with a SWMM-based optimizer that pre-emptively repositions storage and gate settings. Across city-scale tests, this forecast-driven operation reduced flood volume by up to 11.8% and peak discharge by ~39% compared to reactive control. Why it matters: it’s fast, affordable, and works where data and computing are limited. What’s different: a closed-loop, plug-and-play framework showing that short-lead forecasts, even imperfect ones, can measurably reduce risk in flash-flood-prone cities (https://doi.org/10.1016/j.jhydrol.2024.132118).

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Name: Fatemeh Saedi

Email: fsaedi@crimson.ua.edu

DOI: https://doi.org/10.2166/wcc.2021.219

LinkedIn: https://www.linkedin.com/in/fatemeh-saedi-278568172

Affiliation: The University of Alabama

The impact of climate change on water availability has become a major concern for reservoirs in arid and semi-arid regions. This study examines the effects of climate change on water supply and availability in the Zayandeh-Roud River Basin, Isfahan, Iran. To support better management, the Soil and Water Assessment Tool (SWAT) was applied to develop a hydrologic model of the basin. The model was calibrated and validated for two stream gauges. Results indicate that the highest annual water deficit could reach approximately 847 MCM. Furthermore, the lowest reservoir reliability and largest vulnerability were observed under the extreme RCP8.5 pathway.

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Name: Shima Kamali

Email: skamali@ccny.cuny.edu

Career Stage: PhD Student

Affiliation: The City College of New York

LinkedIn: http://linkedin.com/in/shima-kamali-335665224/

DOI: https://doi.org/10.1007/s11269-022-03268-0

As a hydrologist interested in groundwater–climate interactions, I studied the Najafabad aquifer in Isfahan, Iran, to understand how future droughts will affect water storage in this semi-arid region. Using a Support Vector Machine optimized with Particle Swarm Optimization, I combined drought indices and climate model projections to simulate aquifer response. Results show storage losses of nearly 9% by mid-century if current withdrawals continue. This study highlights the urgent need for adaptive groundwater management in drought-prone regions where water scarcity threatens long-term sustainability.

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A comprehensive analysis of the largest hydrological system in the world

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A comprehensive analysis of the largest hydrological system in the world

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Name: Aline Meyer Oliveira

Email: Aline.MeyerOliveira@glasgow.ac.uk

Career stage: Postdoc (funded by the Swiss National Science Foundation Postdoc Mobility program)

Affiliation: School of Geographical and Earth Sciences, University of Glasgow, UK

Social media: https://www.linkedin.com/in/aline-meyer-oliveira-1012aa295/

DOI: https://doi.org/10.1016/j.rse.2018.10.038

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This study mapped sediment dynamics of Amazon river-floodplain systems using remote sensing imagery. As the world's largest hydrological system, the Amazon is challenging to study comprehensively. This paper demonstrates how remote sensing enables large-scale hydrological analysis by processing extensive remotely sensed datasets that reveal connectivity between rivers and lakes. The findings have important implications for biogeochemical cycles and geomorphology. Hydrologists should consider reading this work to get a glimpse in the complexity of river-floodplain systems, and because of the beautiful maps and data visualizations.

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Contrasting impacts of irrigation and deforestation on Lancang-Mekong River Basin hydrology 

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Name: Jianning Ren

Email: jren[at]nus.edu.sg

Career stage: Postdoc

Social Media: @ren_will (at X)

DOI: https://www.nature.com/articles/s43247-025-02093-8

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Research paper summary:

The study couples surface–groundwater modeling with gauges and satellite data to disentangle irrigation and deforestation impacts across the Lancang–Mekong Basin. Irrigation increases soil moisture but depletes groundwater; it also raises evapotranspiration and baseflow, yielding mixed runoff changes. Deforestation lowers soil moisture; in steep terrain, enhanced lateral flow partly offsets groundwater losses. Interactions matter: deforestation-driven soil-moisture declines counter irrigation-driven evapotranspiration increases, producing broader areas of runoff gains than losses. Results highlight distinct, sometimes opposing hydrologic effects of coexisting land-use changes and provide a framework for assessing complex basin responses.

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Contrasting impacts of irrigation and deforestation on Lancang-Mekong River Basin hydrology - Communications Earth & Environment

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Impacts of irrigation and deforestation in the Lancang-Mekong River Basin are contrasting for soil moisture, groundwater, and other water variables causing complex runoff changes, according to analysis of modelling with river gauge and satellite data.

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The Drivers of Hydrologic Behavior in Brazil: Insights From a Catchment Classification

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The Drivers of Hydrologic Behavior in Brazil: Insights From a Catchment Classification

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Name: Adriane Hövel

Email: adriane.hoevel@boku.ac.at

Career stage: PhD student

Affiliation: BOKU University, Vienna, Austria

Social media: https://www.linkedin.com/in/adriane-h%C3%B6vel-42b12a211/

DOI: https://doi.org/10.1029/2024WR037212

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The study contributes to Brazilian large-sample hydrology, grouping catchments with similar hydrological functioning based on their streamflow signatures. The authors subsequently evaluate the influence of catchment attributes on the signatures in the respective groups derived. The catchment groups identified mainly follow climatic gradients related to aridity and seasonality across Brazil, with different drivers of streamflow signatures in the different catchment groups. Other hydrologists should read this work to learn about Brazilian catchment hydrology and to get insights into the varying drivers of streamflow signatures dependent on the associated catchment group across the country.

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Coevolution of volcanic catchments in Japan

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Coevolution of volcanic catchments in Japan

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Name: Amanda Donaldson

Email: amanda.donaldson@utexas.edu

Career Stage: Postdoc

Social media:amandaecohydro.bsky.social

DOI: https://doi.org/10.5194/hess-20-1133-2016

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Why is this study important?

Why should other hydrologists read this work?

Response:

Understanding and predicting how water flow paths vary spatial is one of the grand challenges of hydrology. Across catchments of different ages, this study uses relatively easy to calculate and accessible metrics show that hydrologic partitioning between shallow and deep flowpaths varied as a function of catchment age. This study is a fantastic example of integrating interdisciplinary data to develop a conceptual model for how these catchment co-evolved and drive present-day streamflow. I appreciate how this study presents multiple hypotheses and nicely lays out future work needed to disentangle the components of each that may dominant in volcanic catchments.

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Research article | Highlight paper | | 16 Mar 2016

Abstract. Present-day landscapes have evolved over time through interactions between the prevailing climates and geological settings. Understanding the linkage between spatial patterns of landforms, soils, and vegetation in landscapes and their hydrological response is critical to make quantitative predictions in ungaged basins. Catchment coevolution is a theoretical framework that seeks to formulate hypotheses about the mechanisms and conditions that determine the historical development of catchments and how such evolution affects their hydrological response. In this study, we selected 14 volcanic catchments of different ages (from 0.225 to 82.2 Ma) in Japan. We derived indices of landscape properties (drainage density and slope-area relationship) as well as hydrological response (annual water balance, baseflow index, and flow-duration curves) and examined their relation with catchment age and climate (through the aridity index). We found a significant correlation between drainage density and baseflow index with age, but not with climate. The intra-annual flow variability was also significantly related to catchments age. Younger catchments tended to have lower peak flows and higher low flows, while older catchments exhibited more flashy runoff. The decrease in baseflow with catchment age is consistent with the existing hypothesis that in volcanic landscapes the major flow pathways change over time from deep groundwater flow to shallow subsurface flow. The drainage density of our catchments decreased with age, contrary to previous findings in a set of similar, but younger volcanic catchments in the Oregon Cascades, in which drainage density increased with age. In that case, older catchments were thought to show more landscape incision due to increasing near-surface lateral flow paths. Our results suggests two competing hypotheses on the evolution of drainage density in mature catchments. One is that as catchments continue to age, the hydrologically active channels retreat because less recharge leads to lower average aquifer levels and less baseflow. The other hypothesis is that the active channels do not undergo much surface dissection after the catchments reach maturity.

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Coevolution of volcanic catchments in Japan

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Abstract. Present-day landscapes have evolved over time through interactions between the prevailing climates and geological settings. Understanding the linkage between spatial patterns of landforms, soils, and vegetation in landscapes and their hydrological response is critical to make quantitative predictions in ungaged basins.

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Information about myself:

Name: Anish Aryal

MS(R) Master of Science Research Student in Water Resource Engineering at IIT Delhi

Working under Prof. Rohith A.N

Currently Working in: Urban Flood Modelling

Contact Information: Mail: anisharyal35@gmail.com | Phone: +91- 9211270865

Paper Tile:

Large-scale hydrological modelling by using modified PUB recommendations: the India-HYPE case

Link/DOI:

https://doi.org/10.5194/hess-19-4559-2015, 2015

About the paper:

The India-HYPE study (2015) implemented a modified PUB-based hydrological model across 6,000 Indian subbasins, advancing large-scale multi-basin modeling. By integrating remote sensing, expert knowledge, and stepwise calibration, researchers improved model performance dramatically median Kling–Gupta efficiency rose from 0.14 to 0.64. This work remains foundational, influencing how hydrologists approach ungauged catchments and spatial variability in hydrologic processes across diverse Indian catchments.

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Name: Katelyn Mountjoy

Email: mountjok@mcmaster.ca

Career stage: Graduate Student

Affiliation: McMaster University

Doi: https://doi.org/10.1016/j.ocecoaman.2017.11.008

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blurb:

This study examined West Africa’s sediment system, which is experiencing widespread coastal erosion, in order to better understand the sediment budget. This study could be interesting for other hydrologists to read as it examines several countries along West Africa’s coast (including Benin, Togo, Ghana, and Côte d'Ivoire) in order to develop a large-scale sediment budget using a numerical modelling framework. The numerical modelling framework was then used to estimate the effects of dams, ports, and climate change (including sea level rise, wave conditions, and precipitation and temperature variations at river catchments) on sediment transport and changes to the shoreline.

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Name: Abinesh Ganapathy

Email: abinesh_g@hy.iitr.ac.in

Career Stage: PhD student

Affiliation: Indian Institute of Technology Roorkee

Social Media: Linkedin, X

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Paper: Climate-catchment-soil control on hydrological droughts in peninsular India

DOI: https://doi.org/10.1038/s41598-022-11293-7

Importance of the paper:

Does soil play a role in shaping hydrological drought characteristics? It is indeed an interesting research question for any hydrologist to work on. This study explores that question by assessing the influence of climate-catchment-and soil factors in tropical peninsular catchments. The findings reveal that terrain features primarily control drought growth, while soil properties (especially soil organic carbon) play a key role in drought duration. The research highlights the need to consider interactions among climate, soil, and topography for better drought modeling. With future conditions expected to become drier, these insights can be helpful for effective water management.

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Name: Nithila Devi. N

Email: nallasam@gfz.de

Career Stage: Post-Doc

Affiliation: Helmholtz Centre for Geosciences

Social Media: www.linkedin.com/in/dr-nithila-devi-nallasamy-79a2676b

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Paper: Lost water bodies and a flooded city – Counterfactual scenarios of the extreme Chennai flood highlight the potential of nature-based solutions

DOI: https://doi.org/10.1016/j.uclim.2025.102454

Importance and relevance of the paper:

What happens when the waterbodies in a low-lying flood-prone metropolitan city are lost? This study answers this important question by quantifying the impact of the waterbodies in moderating extreme floods from multi-dimensional perspectives such as hazard, exposure, damages, and fatalities. Also, such a multi-dimensional analysis by hydrologists would help people from administrative institutions to better understand the immediacy of preserving the waterbodies. This can aid in a shift in the policy perspectives towards conservation of the existing waterbodies from the impending city expansion. This may, in turn, pave the way for proactive, sustainable, and resilient city development.

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A historical overview of experimental hydrology in China

Name: Zhaozhe Chen

Email: zhaozhe.chen@wisc.edu

Affiliation: University of Wisconsin – Madison

Career Stage: Postdoctoral Research Associate

LinkedIn: linkedin.com/in/zhaozhe-chen-3115b7191

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DOI: https://doi.org/10.1002/hyp.15233

This paper fills a huge gap by pulling together decades of experimental hydrology research in China that was scattered, hard to access, or only available in Chinese. I like that it makes this history visible and usable for the global community, setting the stage for future comparisons and new studies. Reading it reminded me how important it is to bring overlooked knowledge into view, and it has inspired me to think about documenting and connecting work across regions in my own research.

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Name: Pouya Moghaddasi

Email: pmoghaddasi@crimson.ua.edu

Affiliation: The University of Alabama

This research addresses critical groundwater depletion in Iran's Rafsanjan Plain, where overexploitation causes severe land subsidence (up to 20 cm/year). The study develops an innovative integrated framework combining stakeholder analysis using rough set theory, system dynamics modeling, and resilience assessment based on seven generic principles. Using Electoral College Voting for social choice, researchers identified that modern irrigation systems with water transfer can reduce consumption by 40% while improving groundwater resilience by 50%. This methodology provides a replicable template for sustainable groundwater management in water-stressed regions globally, demonstrating how technical solutions must integrate social dynamics for successful implementation.

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Total phosphorus-precipitation and Chlorophyll a-phosphorus relationships of lakes and reservoirs mediated by soil iron at regional scale

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Total phosphorus-precipitation and Chlorophyll a-phosphorus relationships of lakes and reservoirs mediated by soil iron at regional scale

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Name: Mumtahina Rahnuma

Career stage: MSc Student

Institution: Auburn University

Contact: mur0003@auburn.edu

DOI: https://doi.org/10.1016/j.watres.2019.01.038

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This study evaluates the TP-precipitation relationship and Chl a-TP relationship as a function of watershed soil iron for natural lakes and reservoirs. It detects that Soil irons are a critical variable mediating the impact of precipitation on TP concentration; however, their response is completely different for natural lakes and reservoirs.

This study links climate drivers (precipitation), watershed characteristics (soil iron), and waterbody type (lakes vs reservoirs) to understand phosphorus dynamics and trophic status. It will enable stakeholders to revise and differentiate the management practices for lakes and reservoirs by recognizing the different responses of the systems to climate variables.

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Name: Pankaj Verma

Email: d24164@students.iitmandi.ac.in

Affiliation: Indian Institute of Technology Mandi, India

Career Stage: PhD Scholar

Social Media: www.linkedin.com/in/pankaj-thakur-732bb3189

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Title of the Study:

Sap flux and stand scale transpiration measurements of a Chir pine forest in the west central Himalayas of India – radial and seasonal variations and comparison with co-located hydrometeorological and evapotranspiration measurements.

DOI: https://dx.doi.org/10.2139/ssrn.5377276

Why this Study Matters?

Conducted first multi-year sap flux and transpiration measurements in a natural Chir pine forest in the west-central Himalayas, filling a critical knowledge gap.

Used low-cost, lab-fabricated sap flux sensors for detailed radial and seasonal water use analysis across tree age classes.

Identified strong seasonal and age-related variations in transpiration, with the forest showing both energy and water limitations depending on the season.

Demonstrated that forest transpiration significantly exceeds streamflow except during the monsoon, indicating high groundwater use and implications for watershed hydrology and climate impact assessments.

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Sap Flux and Stand Scale Transpiration Measurements of a Chir Pine Forest in the West-Central Himalayas of India – Radial and Seasonal Variations and Comparison with Co-Located Hydrometeorological and Evapotranspiration Measurements

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Biomes in west-central Himalayas are witnessing a large scale transition from biodiverse broadleaved forests to monoculture forests of Chir pine (Pinus roxburgh

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Name: Marina Steiner

Email: stei0696@vandals.uidaho.edu

Career Stage: PhD student

Affiliation: University of Idaho

Social Media: https://www.linkedin.com/in/marina-steiner/

DOI: https://doi.org/10.1051/e3sconf/202338602004

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Hydrological modeling is critical for sustainable irrigation management. Incorporating real-time spatial data to obtain diverse landscape metrics strengthens site-specific models for regions of critical water resource management, such as in the Aral Sea basin. Developing and implementing these methodologies for a small agricultural district in Karakalpakstan enables opportunities to improve models for larger application in the Republic and similar water-stressed irrigated agriculture regions around the world. As the demand for crops, impacts of climate change, and demand for water all increase on a global scale, leveraging open-source GIS data offers an efficient way to improve hydrological models.

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S. Abdurakhmonov1*, K. Bekanov2, N. Embergenov3 and D. Eshnazarov4

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Hydrological modeling of agricultural lands on the basis of GIS technologies (On the example of the Chimbay district of the Republic of Karakalpakstan) | E3S Web of Conferences

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E3S Web of Conferences, open access proceedings in environment, energy and earth sciences