Ramon J. Batalla

Water temperature is a key factor influencing physical, chemical, and biological processes in aquatic ecosystems. Accurate monitoring is crucial for understanding these dynamics, their variability, and their evolution, especially in the face of global change. In-situ measurements and satellite remote sensing methods have limitations ranging from high costs and logistical constraints to restricted spatial and temporal resolutions. This study introduces the MultiTEMP system, a cost-effective and customizable tool for high-frequency, spatially distributed water temperature monitoring. Leveraging open-source Arduino technology and digital sensors, MultiTEMP enables synchronized data collection across various locations (multiple submerged points), significantly advancing the study of thermal dynamics. The system has been tested in regulated rivers affected by hydropeaking events. Field deployments have demonstrated its capability to capture detailed spatiotemporal temperature variations, which are essential for understanding the ecological impacts of artificial changes in flow regime. Overall, MultiTEMP represents a simple but valuable monitoring system, offering an affordable, flexible, and scalable approach to water temperature monitoring. Its continued development and integration into broader monitoring networks could significantly improve the environmental management of flows and the conservation of fluvial ecosystems.

Water scarcity is an escalating environmental challenge, particularly in semi-arid regions like Spain, where balancing human and ecosystem needs is critical for sustainable development. Freshwater ecosystems are vital for biodiversity, water security, and economic systems, but often lose protection during droughts. Spain, largely under a Mediterranean climate, shows strong interdependence between ecological and socioeconomic systems, with agriculture, tourism, and energy sectors heavily reliant on scarce water resources. Spain’s economy has thrived on water-dependent activities yet increasing droughts and infrastructure limits are pushing ecosystems toward collapse, with severe biodiversity loss and irreversible damage. Furthermore, investments aimed at increasing water-use efficiency often backfire, leading to expanded irrigation without real water savings. Climate change, urbanization, and pollution exacerbate these tensions, posing risks to public health and economic stability. Transformative strategies are urgently needed: protecting and restoring ecosystems, promoting conservation agriculture, regulating water-intensive industries, and planning collective responses to illegal water use. Simply increasing supply or reacting to crises without systemic change of water demands will not ensure future water security. Spain’s experience highlights the urgent need for integrated management of natural and human systems to preserve freshwater resources, biodiversity, and economic resilience.

The determination of critical shear stresses is fundamental to bedload sediment transport prediction in gravel‐bed rivers. Due to the heterogeneous shape and arrangement of the individual clasts in a riverbed, critical shear stresses typically show a large spatial variability, which is not adequately captured by the reach‐averaged description followed in common studies. In this regard, there is a general paucity of field data on this spatial variability of the critical shear stress, largely due to the lack of a standardized measurement method. In an attempt to fill this gap, we propose a field‐based workflow to estimate the frequency distribution of dimensionless critical shear stress (also named critical Shields number), which is based on the measurement of a series of variables related to the position, orientation and resistance to motion of individual clasts in a gravel‐bed river, combined with a probabilistic approximation to drag and lift coefficients. Following this workflow, the patch‐scale variability of particle incipient‐motion conditions was determined in a gravel bar of the Upper Cinca River, Spain. The results are consistent with what is known about sediment entrainment in gravel‐bed rivers. We consider this method to have great potential to advance our understanding of particle initiation of motion in gravel‐bed rivers as it provides valuable systematic field information.

Understanding the effects of human disturbance on the bedload transport regime of anthropised rivers is a topic of growing importance, as such information is of interest for adequate river diagnosis, correct implementation of restoration measures and appropriate design of post‐action monitoring programs. However, such assessments are complex, especially in sites where multiple factors simultaneously influence the bedload transport regime, so that it is difficult to establish simple causal relationships between human disturbances and changes in the sediment transport regime, notably on bedload. To overcome this, there is a need for rigorous hypothesis‐driven approaches to assess the isolated effects of each driver. With this in mind, we have characterised the dynamics of bedload transport in the Upper Garonne (Central Pyrenees, Spain‐France), a river impacted by sediment retention, flow diversion and mining that influence its morphological conditions and transport regime. We assessed the effects of (1) surface grain size distribution, (2) river morphology, (3) sediment supply and (4) flow diversion on the bedload transport regime. Four sites with different degrees of river anthropisation were selected. After defining hypotheses on the most likely bedload transport conditions for each site, we proposed a set of discriminating criteria to test these hypotheses, based on temporal within‐site and spatial between‐site comparisons of coarse particle tracking measurements over four years. The results of this research showed that the hydrosedimentary regime of the Garonne is controlled by a complex combination of drivers such as valley physiography, which exerts a first‐order control on differences in reach‐scale bedforms and bedload dynamics; and human disturbances which contribute to a reduction in sediment supply through changes in land cover and hydropower dams, or to changes in hydrology (i.e., flow competence) due to water diversion and abstraction.

Mediterranean basins face significant water scarcity which demands examining long-term data to prospect their trends in water availability and quality. This study focuses on The Onyar River (Inner Catalan basins, NE Spain), to explore its historical streamflow changes, the influencing climatic and land-use factors, and the consequential impacts on water quality. We analyse key hydro-climatic variables—streamflow, precipitation, temperature, and evapotranspiration (both PET and AET)— across a 60-year span (1960 -2020) and their relationship with recent stream water chemistry data (2007-2020). We compare these patterns to the changes in land use, and to the variations in water demand according to urban use, livestock, and crop production estimates. Our findings highlight a consistent decline in streamflow, most pronounced over the last two decades, accompanied by an increase in PET, and a probable decrease in groundwater recharge. Notably, these changes co-occurred with higher concentrations of river water ammonium and nitrate. We attribute these patterns to changes in land use such as afforestation and intensive fertilization, as well as increased groundwater withdrawal, particularly during irrigation seasons. Additional factors include growing urban water demand and the discharges of treated wastewater back into the river system. This study offers a comprehensive overview of the declining water quantity and quality in the Onyar River, attributing these trends to an interplay of climatic and anthropogenic factors. The findings underscore the need for integrated water resource management strategies to mitigate the implications of these changes.

Bed mobility and stability are spatially and temporally variable, making it a complex phenomenon to study. This paper is the second of a pair, in which we present an automated image processing procedure for monitoring the mobility/stability of gravel river beds. The method is based on local comparison of the shape of the grains identified at the same coordinates between successive photos to identify coincident and new grains. From this categorisation in a given study area, several variables can be extracted, such as: the general proportion of mobile or immobile grains (number or area), the maximum mobile or immobile diameters, the proportion per grain fraction of grains that remained immobile (stable) and grains newly identified. Additionally, percentiles of the surface Grain Size Distribution (GSD) before and after a target hydrological event, as well as the immobile and mobilized GSD (which could be used as a proxy for bedload GSD) can be computed. In this part 2 paper, we present the entire GIS-based procedure for identifying the shape of each grain in digital images of bed patches to then classify their dynamic status (mobile/immobile), and derive a reliable result compatible with different forms of sampling (Area-by-number, Abn, and Grid-by-number, Gbn) and types of measurements (continuous and discrete square holes grain size reading). The performance of the GIS procedure is evaluated for the mentioned above variables over a control set composed of ten 1×1m paired before/after image samples representing different field conditions. The automatic classification applied on a perfect (manual) grain delineation yields Mean Absolute Errors (MAE) lower than 3% in both Abn and Gbn, while the automatic classification applied on an automated delineation with 10 min of manual boundary revision shows MAE around 8% and presents a larger MAE of 29% for only the estimation of the mobile percentile.

Particle entrainment intensity is spatially and temporally variable, making it a complex phenomenon to measure. This paper is the first of a pair, in which we present an automated image processing procedure (PhotoMOB) for monitoring the mobility/stability of gravel river beds. The method is based on local comparison of the shape of the grains identified at the same coordinates between successive photos to identify coincident and new grains. For each grain fraction, the proportion of grains that remained immobile and the proportion of grains newly identified in the study area can be calculated. In this part 1 paper, we present only the GIS-based procedure for identifying and characterising grain shapes in digital images of bed patches to derive a reliable surface Grain Size Distribution (GSD), and for subsequent analyses of bed mobility. The procedure is compatible with different forms of sampling (Area-by-Number i.e., AbN, and Grid-by-Number i.e., GbN) and types of measurements (continuous or real measures of the axes and discrete square holes measurements of the axes). The performance of the GIS procedure is evaluated by comparing estimated percentiles against manually delineated grains in ten 40x40cm image samples, as well as against the real bed grain sizes from the same patches measured with a Pebble-Box (continuous axis value) and two samples measured with a template (discrete axis value). Under optimal condition, the average root mean squared error (RMSE) of the manual procedure compared to the real measurement is 8.2% in AbN and 16.3% in GbN, while PhotoMOB performance is similar with RMSE of 9.5% in AbN and 16.6% in GbN. The paper also analyses how the tool performs when compared to discrete procedures such as measurement with templates. We found that in AbN, the under-estimation of the apparent size due to the imbrication effect is of the same order of magnitude as the under-estimation of the grain size measured by template. In GbN form, results emphasize the need of converting grain axis as a function of the average grain flatness for compatibility with discrete measurement, as coarse grains have more weight in the distribution and are often flatter in shape, hence are more often retained in inferior classes than smaller more spherical particles. A sufficiently large and appropriate sample area could reduce all the above mentioned RMSE by a third for AbN and by half in GbN.

An increase in the demand for renewable energy is driving hydropower development and its integration with variable renewable energy sources. When hydropower is produced flexibly from hydropower plants, it causes rapid and frequent artificial flow fluctuations in rivers, a phenomenon known as hydropeaking. Hydropeaking and associated hydrological alterations cause multiple impacts on riverine habitats with cascading effects on ecosystem functioning and structure. Given the significance of its ecological and socio‐economic implications, mitigation of hydropeaking requires an inter‐ and transdisciplinary approach. An interdisciplinary network called HyPeak has been conceived to enrich international research initiatives and support hydropower planning and policy. HyPeak has been founded based on exchange and networking activities linking scientists from several countries where hydropeaking has been widespread for decades and numerous studies dedicated to the topic have been carried out. HyPeak aims to integrate members from other countries and continents in which hydropower production plays a relevant role, and grow to be a reference group that provides expert advice on the topic to policy‐makers, as well as researchers, stakeholders, and practitioners in the field of hydropeaking.