ABSTRACT India’s Dam Safety Act (2021) stipulates the objectives and functions of the organisational entities concerned with dam safety. A time-bound action by dam owners has been mandated only with respect to (i) comprehensive dam safety evaluation, (ii) emergency action plan, and (iii) risk assessment. Exigency for these actions stem from urgency to prioritise India′s ageing dams for a satisfactory level of dam safety assurance through structural rehabilitation and/or non-structural measures. Despite earnest efforts to meet the 5-year timeline for mandated actions, the dam owners are encountering serious challenges, especially regarding the risk assessment part. Since prevailing guidelines specify a complex methodology for assessing dam risks, a rapid risk assessment approach – involving an abstract exercise of risk indexing – is being attempted as a shortcut. However, compliance in this manner fails to prioritise India‘s ageing dams for expeditious safety assurance. Demystifying the risk assessment, the paper points out an alternative pathway, which the Act itself advocates as an integration of dam safety evaluation, risk assessment, and risk management. The Paper develops an integrated framework that leverages the overlapping nature of mandated actions, in which the outcome of one action serves as input to the other, substantially simplifying overall implementation of the Act.

ABSTRACT This study provides the first basin-wide application of the Integrated Watershed Health Framework (IWHF) in the Nan River Basin (NRB), Northern Thailand, assessing 17 sub-basins using 29 ecological, socio-cultural, economic, and policy indicators derived from SWAT simulations, land-use datasets, socio-economic statistics, and institutional assessments. Watershed Health Index (WHI) scores ranged from 2.77 to 3.64, indicating clear spatial variability. Upstream units, particularly Sub-basin 5 (WHI = 3.64), demonstrated stronger hydrological regulation, forest cover, and institutional capacity, whereas downstream sub-basins (11, 12, 16, 17; WHI < 3.00) exhibited lower health due to forest decline, agricultural expansion, weakened riparian zones, and limited socio-economic resources. Future vulnerability was examined using bias-corrected CMIP6 climate projections, Dyna-CLUE land-use simulations, and water demand forecasts under SSP2-4.5 and SSP5-8.5. Vulnerability intensifies from the Near to Far Future, with the greatest impacts under SSP5-8.5, particularly downstream. A resilience-based assessment integrating adaptive capacity and exposure identified key Restoration Priority sub-basins (11, 15, 17). Despite limitations related to categorical scoring, projection uncertainties, and data gaps, the IWHF provides a robust basis for targeted watershed management and is transferable to similar monsoon-driven, data-limited basins in Southeast Asia.

ABSTRACT Sediment flow should be accurately monitored in river systems to efficiently manage sediment-related problems. Error analysis can become helpful in improving the model performance by capturing and minimisation of the systemic error. Previous studies on error correction models have found to improve sediment forecasting performance. However, a concurrent error correction model for improving sediment flow forecast at river systems needs investigation. Therefore, the present study investigates the applicability of an error model based on a multiple-input multiple-output 2 (MIMO-2) model framework incorporating error analysis simultaneously at multiple sections of a river system. Artificial neural network (ANN)-based models were developed for the Mississippi River system. Comparison with the MIMO-2 model indicates an average SSE reduction of approximately 10% whereas, maximum SSE reduction of 23% was observed for the Thebes section. It was validated using normalised root mean square error (NRMSE) and Nash–Sutcliffe efficiency coefficient (CE) values. An NRMSE of <10% and a CE value of >0.45 for all gaging sections (except Eureka) suggest satisfactory model performance. Therefore, deep learning concepts have proven to be useful in capturing error characteristics, and thus, their subsequent reduction can be achieved for improved sediment forecasting at river systems.

ABSTRACT Riverine barriers impact longitudinal connectivity and hinder fish migration; remedial measures are urgently required. European eel (Anguilla anguilla) are critically endangered and legislation (EC 1100/2007) states safe downstream passage must be provided at hazardous intakes. Gravity sluices at pumping stations have the potential to provide a safe and low-cost downstream passage route for seaward migrating silver eels. Uniquely, this study surveyed pumping station managers to characterise the physical and operational features of gravity sluices pertinent to both upstream and downstream eel passage, whichvaried substantially between pumping stations. The gravity sluice was not operational at twenty-five (35.2%) pumping stations, eight (18.2%) rarely passed water downstream and three (6.8%) were not considered safe downstream passage routes. Operational changes to facilitate safe downstream eel passage, i.e. increase the frequency and duration of sluicing at night during the new moon, could be implemented at only 8.9% of pumping stations, and thus can only rarely be considered an effective downstream passage solution. Paradoxically, gravity sluices may inadvertently exacerbate eel entrainment risk by providing upstream passage into pumped catchments with traditional (i.e. not fish-friendly) pumps and thus should be considered a higher priority for eel protection than pumping stations without gravity sluices.

ABSTRACT The Educandos basin in Manaus, Amazonas is under threat with sources of metal contamination coming from homes and industry. The objective of this study was to identify the factors that decisively influence the concentration of metals in the Educandos basin. Were selected 14 points of the basin for the collection of water samples. The metal elements were analyzed using inductively coupled plasma optical emission spectrometry (ICP-OES). Pearson correlation, Principal Component (PCA), and Cluster (CA) Analyses were used. The results showed that seasonality has a strong influence on the presence of metals, presenting, for example, average Al values of 187.7 µg.L−1 in the rainy season to 984.3 µg.L−1, and 1,204.2 µg.L−1, behaviour also observed in other metals. PCA showed that, in the rainy season, the behaviour of the concentrations of metals is more homogeneous. In the CA, it was possible to establish the sampling points with possible sources of contamination. The results contribute to understanding of the seasonal processes of the presence and concentrations of metal elements in the waters of the basin.

ABSTRACT This study presents a comprehensive longitudinal assessment of water poverty in Morocco, a severely water-stressed nation, using the multidimensional Water Poverty Index (WPI) for the period 2010–2022 at a national scale. Unlike previous cross-sectional analyses, a time-series approach has been employed to dynamically track changes, addressing a critical gap in WPI literature. Utilizing 16 variables across five WPI components, the analysis reveals significant fluctuations in overall water poverty, with the WPI notably ranging from a low of 43.90 in 2011 to a high of 57.91 in 2021. The Resource and Use components emerged as the primary drivers of these variations, highlighting the profound impact of increasing water scarcity due to climate change and escalating agricultural demand, which accounts for nearly 85% of total water consumption. Based on these findings, the study provides data-driven policy recommendations for enhanced governance, conservation strategies, and agricultural sector transformation. The implications underscore the urgent need for targeted interventions to improve water use efficiency and resilience in Morocco. This research demonstrates the WPI's utility as a robust, transparent, and dynamic monitoring tool, offering valuable, replicable insights for sustainable water management in other water-stressed developing economies globally.

ABSTRACT Pig farming significantly contributes to water pollution, particularly on tropical islands such as Okinawa Main Island in Japan and Bali Island in Indonesia. Historically, Okinawa faced severe river contamination due to untreated wastewater from pig farms. In response, the government enacted strict regulatory measures, Act No. 112 of 1999, which substantially improved water quality. The Mukue River, once considered one of Japan’s most polluted, saw a drastic reduction in livestock-related pollution, from 45% in the 1970s to just 9% by 2007. This study assesses the effectiveness of Okinawa’s wastewater regulations through field surveys, water quality tests, and DNA tracing to detect pig waste contamination. Results show BOD levels rising from 1.7 mg/L upstream to 150 mg/L downstream, confirming ongoing pollution from small-scale farms. In contrast, Bali lacks stringent enforcement; a survey of 79 farms reveals that 54.4% are family-owned, with 46.5% discharging waste directly, while only 20.3% utilise septic tanks. This research proposes dual strategies for Bali: enforce stricter regulations and provide subsidies for adequate waste treatment infrastructure. These recommendations aim to mitigate environmental degradation and align with Sustainable Development Goals (SDGs) 6 (Clean Water), 12 (Responsible Consumption), and 15 (Life on Land), promoting more sustainable pig farming practices.

ABSTRACT The use of Uncrewed Aerial Vehicles (UAVs), or drones, in monitoring sediments for the management of rivers and reservoirs has become increasingly prevalent around the world. This paper reviews recent case studies of UAVs showcasing practical applications in sediment management in Europe. As European watercourses face increasing challenges and pressure from human activities and climate change, innovative approaches like UAVs offer promising solutions for more effective monitoring and management of sediments and the fluvial environment in general. The current study aims to provide an evaluation of UAV deployment in this context, highlighting their potential applications, benefits, and challenges, as well as offering insights that can guide future research and practical applications in river sediment transport management. The findings summarized here indicate that UAVs offer significant advantages in monitoring sediment transport and deposition, providing high-resolution data and improving safety for researchers. However, challenges such as regulatory constraints, technical limitations, and data processing complexities persist. Future works should focus on enhancing UAV capabilities, developing standardized protocols, and improving data integration techniques, as well as considering applications beyond Europe.

ABSTRACT The river water quality greatly depends upon land use/land cover (LULC) in the vicinity. In this study, Sentinel-2 imagery is utilized for two purposes, viz., (1) to predict water quality parameters and, thereby, to determine the water quality index (WQI) for drinking purpose and 2) to monitor and map parameters of water quality. The water quality of 2025 was predicted by regression model analysis, taking landscape metrics as the independent variables, using hybrid classification and regression tree (CART) classifier-Cellular Automata Markov algorithm algorithms. The second method generates the time series from DO (dissolved oxygen) on Google Earth Engine (GEE) from the transformation of remote sensing data into DO distribution maps on one-dimensional hydraulic model and artificial neural network. The MAE for the GEE-derived DO and in-situ measurement was 0.92. Finally, the WQI was calculated using analytical hierarchy process-variable weight theory (AHP-VWT) which empowers assigning variable weights to water quality parameters for the closest correctness of WQI. The authors believe that the study will be of benefit to strategize and enforce necessary measures to avoid predicted future pollution scenarios, total coliform (TC), biological oxygen demand (BOD), Nitrate (N O 3 − ), electrical conductivity.

ABSTRACT Monitoring fish communities is essential for assessing the health and functioning of mountainous river basins, providing valuable insights for their effective management. Environmental DNA (eDNA) analysis has emerged as a powerful tool in surveying fish communities; however, its application in river health assessment is limited by uncertainties regarding eDNA decay characteristics. To address this, we conducted field experiments in the Heishui River using Homatula variegata as the target species to explore the relationships among its biomass, eDNA copy number, and habitat factors, employing Pearson correlation, generalized linear models (GLM), and generalized additive models (GAM) for quantitative analysis. The results revealed that the suspended sediments had the greatest impact on eDNA analysis accuracy. Further indoor experiments revealed that suspended sediment degrades eDNA through microbial degradation and physical damage, with the latter being dominant and the eDNA decay rate increased as suspended sediment concentration increased. Notably, when the concentration reached 1000 mg/L, microbial degradation became a significant contributor to eDNA decay. In conclusion, our study highlights the critical importance of considering suspended sediment concentrations when utilizing eDNA analysis for the health assessments of mountainous river basins. This understanding enhances the reliability and applicability of eDNA as a tool for river health management.