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Inter‐catchment groundwater flow (IGF) plays an essential role in streamflow generation and water quality in forested headwaters. Multiple factors are thought to contribute to IGF, including climate, topographical, and geological factors. However, studies have not clarified the relationships between IGF and catchment properties in the headwater catchments due to the lack of observational data at scales smaller than 100 ha. This study examined possible factors influencing IGF using random forest analysis based on annual water balance data from 152 forested catchments ranging from 0.09 to 9400 ha in Japan. The results showed that catchment scale had the greatest influence on IGF, and IGF tended to decrease with increasing catchment area at scales of less than 10 ha. The average IGF stabilized around zero in catchments greater than 10 ha. The averaged IGF trend with catchment scale indicated more outward groundwater flow in catchments smaller than 10 ha, but no relationship between IGF and catchment size in catchments larger than 10 ha. The variability in IGF decreased with catchment size and was lowest at 10–100 ha. The decrease in variability in catchments less than 100 ha was mainly due to river confluence and the increased variability in catchments larger than 100 ha indicated potential observation errors increase in catchments of this size. Plain Language Summary Inter‐catchment groundwater flow (IGF) refers to groundwater flux across surface topographic boundaries. Recent studies have clarified that IGF significantly affects streamflow generation and water quality. However, direct observation of IGF is difficult, and the mechanisms underlying IGF are not fully understood. This study examined the factors influencing IGF, as well as its scale dependence and variability based on water balance data from 152 forested catchments ranging from 0.09 to 9400 ha in Japan. This showed that catchment area had the greatest influence on IGF. Groundwater tended to flow out of catchments smaller than 10 ha, and stabilized in those larger than 10 ha. Variability in the IGF decreased with catchment size at less than 100 ha. These results suggest that on the scale of hillslope and headwater catchments, IGF has a great influence on streamflow generation. Key Points We examined the factors influencing inter‐catchment groundwater flow (IGF) using water balance data for 152 forest catchments in Japan Catchment scale was the factor with the greatest influence on the IGF Groundwater tends to flow out of catchments smaller than 10 ha and IGF approaches zero when the catchment area exceeds 10 ha

Stream gauging stations provide critical streamflow measurements for hydrological applications; however, they may not accurately capture total catchment discharge due to unmonitored regional groundwater flow. Here, we evaluate the effectiveness of streamflow data from gauging stations worldwide to represent total catchment discharge through a modified hydrological model that includes baseflow signatures to constrain groundwater flow processes. We find that approximately 70% of gauging stations present biased estimations of total catchment discharge (bias >10%). This result implies that hydrology‐related processes may not be fully understood, and misleading conclusions may be drawn owing to the low streamflow measurement effectiveness. By influencing subsurface hydrological processes, catchment factors, including catchment area, topography, climate, and geological features, are linked to the effectiveness of streamflow measurements. Our findings highlight the importance of accurate streamflow measurement effectiveness for obtaining a reliable understanding of catchment hydrological processes to support sustainable water resource management. Plain Language Summary The outflow of water from catchments plays a critical role in supporting downstream ecosystems and human society. This catchment outflow includes surface and subsurface discharge. However, a portion of the subsurface discharge may not directly flow into river networks and thus remains unaccounted for in streamflow records at gauging stations. The extent to which these unmonitored subsurface flows exist across catchments and their contribution to the total catchment discharge remains unknown. To address this knowledge gap, we have developed a novel method that simulates the movement of both surface and subsurface flows, enabling us to evaluate the representativeness of streamflow records in capturing the total catchment discharge. Our findings indicate that approximately 70% of gauging stations worldwide inadequately capture the total catchment discharge (bias >10%). This observation highlights the importance of unmonitored subsurface discharge as a significant component of catchment water yield. Such insights enhance our understanding of catchment hydrological processes, supporting the development of sustainable water resource management strategies. Key Points A modified hydrological model was developed by including baseflow signatures to constrain groundwater flow processes Approximately 70% of gauging stations presented biased estimations of total catchment discharge The catchment hydrological response based on gauging station measurements is highly likely to be overestimated or underestimated

Microplastic contamination of the oceans is one of the world’s most pressing environmental concerns. The terrestrial component of the global microplastic budget is not well understood because sources, stores and fluxes are poorly quantified. We report catchment-wide patterns of microplastic contamination, classified by type, size and density, in channel bed sediments at 40 sites across urban, suburban and rural river catchments in northwest England. Microplastic contamination was pervasive on all river channel beds. We found multiple urban contamination hotspots with a maximum microplastic concentration of approximately 517,000 particles m−2. After a period of severe flooding in winter 2015/16, all sites were resampled. Microplastic concentrations had fallen at 28 sites and 18 saw a decrease of one order of magnitude. The flooding exported approximately 70% of the microplastic load stored on these river beds (equivalent to 0.85 ± 0.27 tonnes or 43 ± 14 billion particles) and eradicated microbead contamination at 7 sites. We conclude that microplastic contamination is efficiently flushed from river catchments during flooding.

In low-lying coastal regions, flooding arises from oceanographic (storm surges plus tides and/or waves), fluvial (increased river discharge), and/or pluvial (direct surface run-off) sources. The adverse consequences of a flood can be disproportionately large when these different sources occur concurrently or in close succession, a phenomenon that is known as “compound flooding”. In this paper, we assess the potential for compound flooding arising from the joint occurrence of high storm surge and high river discharge around the coast of the UK. We hypothesise that there will be spatial variation in compound flood frequency, with some coastal regions experiencing a greater dependency between the two flooding sources than others. We map the dependence between high skew surges and high river discharge, considering 326 river stations linked to 33 tide gauge sites. We find that the joint occurrence of high skew surges and high river discharge occurs more frequently during the study period (15–50 years) at sites on the south-western and western coasts of the UK (between three and six joint events per decade) compared to sites along the eastern coast (between zero and one joint events per decade). Second, we investigate the meteorological conditions that drive compound and non-compound events across the UK. We show, for the first time, that spatial variability in the dependence and number of joint occurrences of high skew surges and high river discharge is driven by meteorological differences in storm characteristics. On the western coast of the UK, the storms that generate high skew surges and high river discharge are typically similar in characteristics and track across the UK on comparable pathways. In contrast, on the eastern coast, the storms that typically generate high skew surges are mostly distinct from the types of storms that tend to generate high river discharge. Third, we briefly examine how the phase and strength of dependence between high skew surge and high river discharge is influenced by the characteristics (i.e. flashiness, size, and elevation gradient) of the corresponding river catchments. We find that high skew surges tend to occur more frequently with high river discharge at catchments with a lower base flow index, smaller catchment area, and steeper elevation gradient. In catchments with a high base flow index, large catchment area, and shallow elevation gradient, the peak river flow tends to occur several days after the high skew surge. The previous lack of consideration of compound flooding means that flood risk has likely been underestimated around UK coasts, particularly along the south-western and western coasts. It is crucial that this be addressed in future assessments of flood risk and flood management approaches.

This paper provides a summary of the assessment report of the World Meteorological Organization (WMO) Expert Team on Weather Modification that discusses recent progress on precipitation enhancement research. The progress has been underpinned by advances in our understanding of cloud processes and interactions between clouds and their environment, which, in turn, have been enabled by substantial developments in technical capabilities to both observe and simulate clouds from the microphysical to the mesoscale. We focus on the two cloud types most commonly seeded in the past: winter orographic cloud systems and convective cloud systems. A key issue for cloud seeding is the extension from cloud-scale research to water catchment–scale impacts on precipitation on the ground. Consequently, the requirements for the design, implementation, and evaluation of a catchment-scale precipitation enhancement campaign are discussed. The paper concludes by indicating the most important gaps in our knowledge. Some recommendations regarding the most urgent research topics are given to stimulate further research.

The quality of surface water in Czechia continues to be an ecological problem, also in rural areas. The Šlapanka River catchment belongs to one of these areas, and this study aims to determine what changes occurred between 1977 and 2020, with particular attention paid to the years 2002 and 2014. Due to the agricultural character, an emphasis was placed on nutrient monitoring. Several water quality parameters were monitored: water temperature, dissolved oxygen, conductivity, pH, nitrate and ammoniacal nitrogen, phosphate phosphorus, and organic substances. The average and characteristic values of concentrations were used to evaluate the time series of water quality parameters, and Mann–Kendall statistical tests were used to examine trends. Data were analyzed using multivariate statistical methods. In 2002, the water quality in the river basin was marked as heavily polluted, but by 2014, the water quality had improved in most monitored locations. Nitrates and organic substances concentrations differed significantly in the headwater catchments between 2002 and 2014. Nitrate concentrations were lower and organic substances were higher. Similar results were encountered in the longitudinal profile. Between 2002 and 2014, nitrate concentration levels dropped, mainly in the upper part of the river, while ammonium concentrations declined in the lower part. Over the same period, the number of organic substances increased in the middle part of the river. In contrast, phosphate phosphorus concentrations increased, though primarily downstream. Nonpoint sources slightly predominate, especially in the upper parts of the basin. Therefore, changes in agricultural praxis are the key to improving water quality.

Benchmarking model performance across large samples of catchments is useful to guide model selection and future model development. Given uncertainties in the observational data we use to drive and evaluate hydrological models, and uncertainties in the structure and parameterisation of models we use to produce hydrological simulations and predictions, it is essential that model evaluation is undertaken within an uncertainty analysis framework. Here, we benchmark the capability of several lumped hydrological models across Great Britain by focusing on daily flow and peak flow simulation. Four hydrological model structures from the Framework for Understanding Structural Errors (FUSE) were applied to over 1000 catchments in England, Wales and Scotland. Model performance was then evaluated using standard performance metrics for daily flows and novel performance metrics for peak flows considering parameter uncertainty. Our results show that lumped hydrological models were able to produce adequate simulations across most of Great Britain, with each model producing simulations exceeding a 0.5 Nash–Sutcliffe efficiency for at least 80 % of catchments. All four models showed a similar spatial pattern of performance, producing better simulations in the wetter catchments to the west and poor model performance in central Scotland and south-eastern England. Poor model performance was often linked to the catchment water balance, with models unable to capture the catchment hydrology where the water balance did not close. Overall, performance was similar between model structures, but different models performed better for different catchment characteristics and metrics, as well as for assessing daily or peak flows, leading to the ensemble of model structures outperforming any single structure, thus demonstrating the value of using multi-model structures across a large sample of different catchment behaviours. This research evaluates what conceptual lumped models can achieve as a performance benchmark and provides interesting insights into where and why these simple models may fail. The large number of river catchments included in this study makes it an appropriate benchmark for any future developments of a national model of Great Britain.

Increased attention directed at frozen soil hydrology has been prompted by climate change. In spite of an increasing number of field measurements and modeling studies, the impact of frozen soil on hydrological processes at the catchment scale is still unclear. However, frozen soil hydrology models have mostly been developed based on a bottom-up approach, i.e., by aggregating prior knowledge at the pixel scale, which is an approach notoriously suffering from equifinality and data scarcity. Therefore, in this study, we explore the impact of frozen soil at the catchment scale, following a top-down approach, implying the following sequence: expert-driven data analysis → qualitative perceptual model → quantitative conceptual model → testing of model realism. The complex mountainous Hulu catchment, northeast of the Qinghai–Tibet Plateau (QTP), was selected as the study site. First, we diagnosed the impact of frozen soil on catchment hydrology, based on multi-source field observations, model discrepancy, and our expert knowledge. The following two new typical hydrograph properties were identified: the low runoff in the early thawing season (LRET) and the discontinuous baseflow recession (DBR). Second, we developed a perceptual frozen soil hydrological model to explain the LRET and DBR properties. Third, based on the perceptual model and a landscape-based modeling framework (FLEX-Topo), a semi-distributed conceptual frozen soil hydrological model (FLEX-Topo-FS) was developed. The results demonstrate that the FLEX-Topo-FS model can represent the effect of soil freeze–thaw processes on hydrologic connectivity and groundwater discharge and significantly improve hydrograph simulation, including the LRET and DBR events. Furthermore, its realism was confirmed by alternative multi-source and multi-scale observations, particularly the freezing and thawing front in the soil, the lower limit of permafrost, and the trends in groundwater level variation. To the best of our knowledge, this study is the first report of LRET and DBR processes in a mountainous frozen soil catchment. The FLEX-Topo-FS model is a novel conceptual frozen soil hydrological model which represents these complex processes and has the potential for wider use in the vast QTP and other cold mountainous regions.

Recent studies have revealed evidence of trends in the median or mean flood discharge in Europe over the last 5 decades, with clear and coherent regional patterns. The aim of this study is to assess whether trends in flood discharges also occurred for larger return periods, accounting for the effect of catchment scale. We analyse 2370 flood discharge records, selected from a newly available pan-European flood database, with record length of at least 40 years over the period 1960–2010 and with contributing catchment area ranging from 5 to 100 000 km2. To estimate regional flood trends, we use a non-stationary regional flood frequency approach consisting of a regional Gumbel distribution, whose median and growth factor can vary in time with different strengths for different catchment sizes. A Bayesian Markov chain Monte Carlo (MCMC) approach is used for parameter estimation. We quantify regional trends (and the related sample uncertainties), for floods of selected return periods and for selected catchment areas, across Europe and for three regions where coherent flood trends have been identified in previous studies. Results show that in northwestern Europe the trends in flood magnitude are generally positive. In small catchments (up to 100 km2), the 100-year flood increases more than the median flood, while the opposite is observed in medium and large catchments, where even some negative trends appear, especially in northwestern France. In southern Europe flood trends are generally negative. The 100-year flood decreases less than the median flood, and, in the small catchments, the median flood decreases less compared to the large catchments. In eastern Europe the regional trends are negative and do not depend on the return period, but catchment area plays a substantial role: the larger the catchment, the more negative the trend.

Topographically delineated catchments are the common spatial unit to connect human activities and climate change with their consequences for water availability as a prerequisite for sustainable water management. However, inter-catchment groundwater flow and limited connectivity within the catchment results in effective catchment areas different from those suggested by surface topography. Here, we introduce the notion of effective catchment area quantified through an effective catchment index (ECI), derived from observed streamflow, precipitation and actual evapotranspiration estimates, to understand the prevalence and significance of substantial differences between topographic and effective catchment areas in a global dataset. We evaluate our ECI analysis by comparing it to hydraulic head simulations of a global groundwater flow model and to the Budyko framework. We find that one in three studied catchments exhibit an effective catchment area either larger than double or smaller than half of their topographic area. These catchments will likely be affected by management activities such as groundwater pumping or land use change outside their topographic boundaries. Or alternatively, they affect water resources beyond their topographic boundaries. We find that the magnitude of the observed differences is strongly linked to aridity, mean slope, distance to coast, and topographic area. Our study provides a first-order identification of catchments where additional in-depth analysis of subsurface connectivity is needed to support sustainable water management.