Submit to Special Issue Submit Abstract to Special Issue Review for Hydrology Propose a Special Issue

Journal Menu

Journal Browser

Trends and Variations in Hydroclimatic Variables: 2nd Edition

Print Special Issue Flyer
Editors
Special Issue Information
Keywords
Benefits of Publishing in a Special Issue
Related Special Issue
Published Papers

A special issue of Hydrology (ISSN 2306-5338). This special issue belongs to the section "Hydrology–Climate Interactions".

Deadline for manuscript submissions: 31 December 2026 | Viewed by 9794

Share This Special Issue

Editors

Dr. Adilson Pacheco De Souza

E-Mail Website
Guest Editor

Institute of Agrarian and Environmental Sciences, Federal University of Mato Grosso, Sinop 78557-287, Brazil
Interests: hydrometeorology; hydroclimatology; agrometeorology; water and soil conservation engineering; environmental sciences
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Frederico Terra De Almeida

E-Mail Website
Guest Editor

Institute of Agrarian and Environmental Sciences, Federal University of Mato Grosso, Sinop 78557-287, Brazil
Interests: hydrology; sedimentology; water and soil conservation; engineering
Special Issues, Collections and Topics in MDPI journals

Dr. Daniela Roberta Borella

E-Mail Website
Guest Editor

Institute of Natural, Human and Social Sciences, Cuiabá University Campus, Federal University of Mato Grosso, Av. Alexandre Ferronato, 1200, Industrial Sector, Sinop 78557-267, Brazil
Interests: climatology; agrometeorology; water resources; water and soil conservation; geoprocessing

Special Issue Information

Dear Colleagues,

This Special Issue invites studies that investigate the seasonality, trends, and variations in space and time in the main hydroclimatic variables that, interrelated with precipitation, affect evapotranspiration (drought/aridity) and water availability through other components of the hydrological cycle, such as flow/floods, water levels in reservoirs (lakes and dams), and groundwater. These variables play a crucial role in understanding and managing water resources, predicting climate impacts, and in addressing various environmental, ecological, productive, economic, social and public health issues. The integration of hydroclimatic variable data into decision-making processes is crucial to deal with the multifaceted impacts of climate change and ensure sustainable development.

Although hydroclimatic variables are indispensable for several applications, their complexity and variability present challenges in analysis and prediction. The influence of geographic and astronomical factors, mesoscale atmospheric phenomena, and climate change on these variables indicates the need for continuous monitoring and advanced modeling techniques to improve our understanding of the management of water resources and related systems.

The methods used to analyze trends and variations in hydroclimatic variables in space and time can be grouped into three categories: (a) statistical, (b) machine learning, and (c) deterministic/physics-based. The objective of this Special Issue is to group together a collection of articles that present a range of methodological approaches for understanding hydroclimatic variations. The topics covered in this Special Issue include the following, among others:

Studies aimed at monitoring systems and direct measurements of hydroclimatic variables;
Studies aimed at statistical hydrology, with the aim to define the patterns, probability distribution functions, and return time of hydroclimatic variables;
Analysis of trends and variations in time series of hydroclimatic variables;
Analysis of extreme events (droughts, floods);
Detection of spatial variations and trends in hydroclimatic variables;
Future effects of climate change on hydroclimatic variables;
Geostatistical methods in remote sensing and GIS for assessing the impact of climate change;
Assessment of the impact of climate change using hydrological modeling of surface and groundwater at the scale of river basins or aquifers;
Impact of climate change/disturbances on water use for agriculture (including irrigation and drainage);
Impact of climate change/disturbances on natural ecosystems and ecosystem services.

We look forward to receiving your original research articles and reviews.

Dr. Adilson Pacheco De Souza
Prof. Dr. Frederico Terra De Almeida
Dr. Daniela Roberta Borella
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Hydrology is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

time series analysis of hydroclimatic variables
analysis of extreme events
assessment and uncertainty of climate change
relationships between hydroclimatic and agrometeorological attributes
statistical, machine learning, and deterministic modeling approaches
effects of climate variations on agriculture
effects of climate variations on ecosystem services

Benefits of Publishing in a Special Issue

Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Related Special Issue

Trends and Variations in Hydroclimatic Variables in Hydrology (8 articles)

Published Papers (6 papers)

Download All Papers

Order results

Result details

Show export options Show export options

Select all

Export citation of selected articles as:

Research

24 pages, 25633 KB

Open AccessArticle

Trends and Future Projections of Extreme Precipitation Indices in Limpopo Province, South Africa

by Michael G. Mengistu, Andries C. Kruger, Sifiso M. S. Mbatha and Sandile B. Ngwenya

Hydrology 2026, 13(5), 121; https://doi.org/10.3390/hydrology13050121 - 30 Apr 2026

Cited by 1 | Viewed by 1023

Abstract

Climate-related extremes such as floods and droughts have been the main causes of natural disasters in southern Africa in recent years, with noticeable trends in climate extremes being observed. The Limpopo Province in South Africa has been especially prone to these extremes. The extreme precipitation in Limpopo is mainly caused by a mix of intense tropical weather systems and La Niña conditions, both exacerbated by climate change. Climate change exacerbates current water challenges across the province by affecting precipitation patterns, distribution, timing and intensity, leading to extreme climate events such as floods and drought. The historical and future trends of precipitation and relevant extreme indices using observed data from the South African Weather Service and CORDEX ensemble model simulations under the RCP4.5 and RCP8.5 scenarios were examined. An analysis of all precipitation data suitable for the study of long-term variability and trends indicates that most areas underwent drying to various degrees over the last century, especially the central and western parts. Drier conditions over the eastern parts have become more prevalent over the last 50 years. Also, more extremes on a sub-seasonal basis were experienced. Regarding future scenarios, three projected time periods compared to the baseline period (1976–2005) were examined: Current climatology (2006–2035), near-future (2036–2065), and far-future (2066–2095). Most areas will experience a further decrease in precipitation under both emission scenarios, especially in the south-east, central and extreme northern parts. In addition, these areas are expected to experience a decrease in the frequency of heavy precipitation days for all periods under both RCP scenarios, mainly due to drying. Consecutive dry days are expected to increase significantly. Transitioning to renewable energy and enhancing natural carbon sinks can reduce emissions, while prioritizing resilience through renewable energy, water management, and climate-smart agriculture will help address climate change challenges in the province. Full article

(This article belongs to the Special Issue Trends and Variations in Hydroclimatic Variables: 2nd Edition)

► Show Figures

Figure 1

21 pages, 3317 KB

Open AccessArticle

Assessing Nonstationary Hydroclimatic Impacts on Streamflow in the Soan River Basin, Pakistan, Using Mann–Kendall Test and Artificial Neural Network Technique

by Rafi Ul Din, Saddam Hussain, Adeel Ahmad Khan, Muhammad Naveed Anjum, A. T. M. Sakiur Rahman and Saif Ullah

Hydrology 2026, 13(4), 106; https://doi.org/10.3390/hydrology13040106 - 1 Apr 2026

Viewed by 1704

Abstract

Analysis of the hydroclimatic variations in complex topographic and climatic regimes is important in determining the freshwater availability and its response. Although several previous studies have assessed the changing patterns of hydroclimatic variables in South Asian River basins, most of them have considered traditional statistical methods, which may inadequately reflect potential non-linear hydroclimatic trends. This study determines long-term variations in precipitation, temperature, and streamflow in the Soan River Basin of Pakistan, using three decades of in situ records (1991–2020). A non-parametric (Mann–Kendall) trend test along with an artificial neural network (ANN) approach was used to check the linear and non-linear trends. The results exhibited that the basin was getting warmer at a consistent rate, although the amount of precipitation varied significantly with location and season. The annual average amount of precipitation over the entire basin was decreasing at the rate of −7.33 mm/year. As compared to the westerly season, the trend of monsoon precipitation was less certain. Changes in streamflow patterns generally demonstrated the consequences of changing precipitation and rising temperature patterns. The annual average streamflow was decreasing at the rate of −0.47 (−1.30) m³/year, as per the results of MK (ANN). A moderate positive correlation between precipitation and streamflow indicates that precipitation mainly governed the flows in the basin. The results of the MK test and the machine-learning approach demonstrated the similar decreasing tendencies of hydroclimatic variables. However, the ANN approach more precisely demonstrates the non-linear behavior of hydroclimatic variables. It was concluded that the streamflow patterns were considerably responsive to the warming of the Soan River Basin, as well as to the changing behavior of precipitation. These findings emphasized the significance of integrating statistical and machine-learning approaches to enhance the comprehension of hydroclimatic trends. Results of this research could be applicable in sustainable management and planning of the water resources within the basin. Full article

(This article belongs to the Special Issue Trends and Variations in Hydroclimatic Variables: 2nd Edition)

► Show Figures

Figure 1

18 pages, 5453 KB

Open AccessArticle

Bivariate Characterization of Long-Term Hydrological Drought Risks Using SRI and Archimedean Copulas

by Mohammed Achite, Tolga Barış Terzi, Osman Üçüncü, Kusum Pandey and Tommaso Caloiero

Hydrology 2026, 13(4), 104; https://doi.org/10.3390/hydrology13040104 - 30 Mar 2026

Cited by 2 | Viewed by 1124

Abstract

Hydrological drought poses a major threat to water security-y in semi-arid regions, where prolonged runoff deficits can severely affect reservoir reliability and ecosystem sustainability. This study presents a bivariate probabilistic framework to characterize long-term hydrological drought risk in the Wadi Sahouat basin (northwestern Algeria) using the 12-month Standardized Runoff Index (SRI-12) for the period 1973/74–2014/15. Drought events were identified through run theory with a threshold level of SRI ≤ −1.0, and some drought characteristics, duration, and severity were extracted. Marginal distributions were fitted and evaluated using AIC, BIC, and Kolmogorov–Smirnov tests, leading to the selection of the Weibull distribution for both variables. The dependence structure between duration and severity was modeled using Archimedean copulas, and the Gumbel copula provided the best fit at both hydrometric stations, indicating significant upper-tail dependence. Univariate and bivariate return periods were estimated for target intervals from 10 to 200 years. Results demonstrate that multivariate return periods substantially differ from univariate estimates, particularly for extreme events, highlighting the compounded risk of prolonged and severe droughts. Full article

(This article belongs to the Special Issue Trends and Variations in Hydroclimatic Variables: 2nd Edition)

► Show Figures

Figure 1

21 pages, 4863 KB

Open AccessFeature PaperEditor’s ChoiceArticle

Revealing Emerging Hydroclimatic Shifts: Advanced Trend Analysis of Rainfall and Streamflow in the Navasota River Watershed

by Ali Fares, Ripendra Awal, Anwar Assefa Adem, Anoop Valiya Veettil, Taha B. M. J. Ouarda, Samuel Brody and Marouane Temimi

Hydrology 2026, 13(1), 12; https://doi.org/10.3390/hydrology13010012 - 25 Dec 2025

Cited by 1 | Viewed by 1434

Abstract

Rainfall and streamflow analyses have long been central to hydrological research, yet traditional approaches often overlook the complexity introduced by changing climate signals, land-use dynamics, and human infrastructure. This study applies an integrated, data-driven framework to explore emerging hydroclimatic shifts in the Navasota River Watershed of east-central Texas. By combining autocorrelation analysis, Mann–Kendall and modified Mann–Kendall trend tests, and Pettitt’s change-point detection, we examine more than a century of precipitation and streamflow records alongside post-1978 reservoir operations. Results reveal an accelerating wetting tendency, particularly evident in decadal rolling averages and early-summer precipitation, accompanied by a statistically significant increase in 10-year moving averages of annual peak streamflow. While abrupt regime shifts were not detected, subtle but persistent changes point to evolving watershed memory and heightened flood risk in the post-dam era. This study reframes rainfall and streamflow trend analysis as a dynamic tool for anticipating hydrologic regime shifts, highlighting the urgent need for adaptive water infrastructure and flood management strategies in rapidly urbanizing and climate-sensitive watersheds. Full article

(This article belongs to the Special Issue Trends and Variations in Hydroclimatic Variables: 2nd Edition)

► Show Figures

Figure 1

26 pages, 2546 KB

Open AccessArticle

Characterization of Hyetograms and Rainfall Patterns in Southern Amazonia

by Brenda Buose, Daniela Roberta Borella, Frederico Terra de Almeida and Adilson Pacheco de Souza

Hydrology 2025, 12(11), 302; https://doi.org/10.3390/hydrology12110302 - 14 Nov 2025

Viewed by 1492

Abstract

The variability of rainfall, mainly convective, in the southern Amazon remains poorly understood due to the limited number of studies examining the relationships between the intensities and durations of rainfall events in this region. This study aimed to characterize the intensity patterns—hyetograms (advanced, intermediate, delayed, and constant, as well as observations of new patterns)—in the northern state of Mato Grosso (southern Amazon). Generally, most research in Brazil on this topic has focused on other regions of the country or used simulations or data disaggregation processes, limiting the representation of the regional reality. Historical data series from five conventional stations (with pluviograms) and ten automatic stations with data obtained by tipping rain gauges were analyzed. The analysis involved classifying 6187 events into four main patterns: Advanced (53.52%), Intermediate (31.74%), Delayed (14.58%), and Constant (less than 1%), with 93 events unclassified. The hourly distribution of rainfall revealed greater occurrence in the afternoon and evening periods, suggesting a predominance of thermal convection in regional dynamics. The results offer valuable insights for water planning, agricultural security, and adaptive infrastructure, in addition to promoting integration between science, engineering, and public policies aimed at environmental management and risk prevention. Full article

(This article belongs to the Special Issue Trends and Variations in Hydroclimatic Variables: 2nd Edition)

► Show Figures

Figure 1

26 pages, 5202 KB

Open AccessArticle

Time-Varying Bivariate Modeling for Predicting Hydrometeorological Trends in Jakarta Using Rainfall and Air Temperature Data

by Suci Nur Setyawati, Sri Nurdiati, I Wayan Mangku, Ionel Haidu and Mohamad Khoirun Najib

Hydrology 2025, 12(10), 252; https://doi.org/10.3390/hydrology12100252 - 26 Sep 2025

Cited by 1 | Viewed by 2210

Abstract

Changes in rainfall patterns and irregular air temperature have become essential issues in analyzing hydrometeorological trends in Jakarta. This study aims to select the best copula of the stationary and non-stationary copula models and visualize and explore the relationship between rainfall and air temperature to predict hydrometeorological trends. The methods used include combining univariate Lognormal and Generalized Extreme Value (GEV) distributions with Clayton, Gumbel, and Frank copulas, as well as parameter estimation using the fminsearch algorithm, Markov Chain Monte Carlo (MCMC) simulation, and a combination of both. The results show that the best model is the non-stationary Clayton copula estimated using MCMC simulation, which has the lowest Akaike Information Criterion (AIC) value. This model effectively captures extreme dependence in the lower tail of the distribution, indicating a potential increase in extreme low events such as cold droughts. Visualization of the best model through contour plots shows a shifting center of the distribution over time. This study contributes to developing dynamic hydrometeorological models for adaptation planning of changing hydrometeorological trends in Indonesia. Full article

(This article belongs to the Special Issue Trends and Variations in Hydroclimatic Variables: 2nd Edition)

► Show Figures

Journal Menu

Journal Browser

Trends and Variations in Hydroclimatic Variables: 2nd Edition

Share This Special Issue

Editors

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Related Special Issue

Published Papers (6 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI