Hydrological response of drought impacts across catchments worldwide

Drought will inevitably affect linkages between different water components, which have previously been investigated across different spatiotemporal scales. Elucidating drought-induced precipitation (P) partition effects remain uncertain because they involve drought propagation, even inducing streamflow (Q) non-stationarity. This study collected data on 1069 catchments worldwide to investigate Q and evapotranspiration (ET) impacts from P deficit-derived reductions in drought propagation. Results show that P deficits trigger soil moisture drought, subsequently inducing negative Q and ET anomalies that vary under different climate regimes. Generally, drought-induced hydrological legacies indicate that breaks in hydrological linkages cause a relatively rapid Q response (i.e., negative Q anomaly), amplified by drought strength and duration. Compared with the Q response, the ET response to drought stress involves a more complex, associative vegetation response and an associative evaporative state controlled by water and energy, which lags behind the Q response and can also intensify with increasing drought severity and duration. This is confirmed by the ET response under different climate regimes. Namely, in drier climates, a positive ET anomaly can be detected in its early stages, this is unusual in wetter climate. Additionally, Q and ET sensitivity to drought strength can be mechanistically explained by the water and energy status. This implies that ET is mainly controlled by water and energy, resulting in higher and lower drought sensitivity within water- and energy-limited regions, respectively. Understanding the impacts of drought on Q and ET response is essential for identifying key linkages in drought propagation across different climate regimes. Our findings will also be useful for developing early warning and adaptation systems that support both human and ecosystem requirements.

Integrating conceptual and machine learning models to enhance daily-Scale streamflow simulation and assessing climate change impact in the watersheds of the Godavari basin, India

This study examined and addressed climate change's effects on hydrological patterns, particularly in critical places like the Godavari River basin. This study used daily gridded rainfall and temperature datasets from the Indian Meteorological Department (IMD) for model training and testing, 70% and 30%, respectively. To anticipate future hydrological shifts, the study harnessed the EC-Earth3 data, presenting an innovative methodology tailored to the unique hydrological dynamics of the Godavari River basin. The Sacramento model provided initial streamflow estimates for Kanhargaon, Nowrangpur, and Wairagarh. This approach melded traditional hydrological modeling with advanced multi-layer perceptron (MLP) capabilities. When combined with parameters like lagged rainfall, lagged streamflow, potential evapotranspiration (PET), and temperature variations, these initial outputs were further refined using the Sac-MLP model. A comparison with Sacramento revealed the superior performance of the Sac-MLP model. For instance, during training, the Nash Sutcliffe efficiency (NSE) values for the Sac-MLP witnessed an improvement from 0.610 to 0.810 in Kanhargaon, 0.580 to 0.692 in Nowrangpur, and 0.675 to 0.849 in Wairagarh. The results of the testing further corroborated these findings, as evidenced by the increase in the NSE for Kanhargaon from 0.890 to 0.910. Additionally, Nowrangpur and Wairagarh experienced notable improvements, with their NSE values rising from 0.629 to 0.785 and 0.725 to 0.902, respectively. Projections based on EC-Earth3 data across various scenarios highlighted significant shifts in rainfall and temperature patterns, especially in the far future (2071-2100). Regarding the relative change in annual streamflow, Kanhargaon projections under SSP370 and SSP585 for the far future indicate increases of 584.38% and 662.74%. Similarly, Nowrangpur and Wairagarh are projected to see increases of 98.27% and 114.98%, and 81.68% and 108.08%, respectively. This study uses EC-Earth3 estimates to demonstrate the Sac-MLP model's accuracy and importance in climate change water resource planning. The unique method for region-specific hydrological analysis provides vital insights for sustainable water resource management. This research provides a deeper understanding of climate-induced hydrological changes and a robust modeling approach for accurate predictions in changing environmental conditions.

Assessment of land use/ land cover change derived catchment hydrologic response: An integrated parsimonious hydrological modeling and alteration analysis based approach

Land use/land cover (LULC) change, often a consequence of natural or anthropogenic drivers, plays a decisive role in governing global catchment dynamics, and subsequent impact on regional hydrology. Insight into the complex relationship between the drivers of LULC change and catchment hydrology is of utmost importance to decision makers. Contemplating the dynamic rainfall-runoff response of the Indian catchments, this study proposes an integrated modeling-based approach to identify the drivers and relative contribution to catchment hydrology. The proposed approach was evaluated in the tropical climate Nagavali River Basin (NRB) (9512 km2) of India. The Soil and Water Assessment Tool (SWAT) hydrological model, which uses daily-scale rainfall, temperature, wind speed, relative humidity, solar radiation, and streamflow information was integrated with the Indicators of Hydrologic Alteration (IHA) technique to characterize the plausible changes in the flow regime of the NRB. Subsequently, the Partial Least Squares Regression (PLSR) based modeling analysis was performed to quantify the relative contribution of individual LULC components on the catchment water balance. The outcomes of the study revealed that forest land has been significantly converted to agricultural land (45-59%) across the NRB resulting in mean annual streamflow increase of 3.57 m3/s during the monsoon season. The affinity between land use class and streamflow revealed that barren land (CN = 83-87) exhibits the maximum positive response to streamflow followed by the built-up land (CN = 89-91) and fallow land (CN = 88-93). The period 1985-1995 experienced an increased ET scenario (911-1050 mm), while the recent period (2005-2020) experienced reduced ET scenario owing to conversion of forest to agricultural land. Certainly, the study endorses adopting the developed methodology for understanding the complex land use and catchment-scale hydrologic interactions across global-scales for early watershed management planning.

Precipitation inequality exacerbates streamflow inequality, but dams moderate it

Access to clean water is a fundamental human right, yet millions worldwide face the dire consequences of water scarcity and inadequate sanitation. Water inequality, characterized by disparities in access and availability of water resources, has emerged as a critical global challenge with far-reaching social, economic, and environmental implications. Using a globally representative observational streamflow dataset and Gini coefficients, this study investigates how streamflow inequality, which has a large impact on inequality of water availability, varies spatially and temporally, and its relationship with different underlying catchment characteristics. This study finds that watersheds in arid climates exhibit a higher degree of streamflow inequality than polar and equatorial ones. Africa experiences the highest streamflow inequality, followed by Australia, while South America experiences relatively lower streamflow inequality. Around 19.6 % of the catchments in Australia display an increasing trend in streamflow inequality, pointing to worsening conditions. Conversely, South America experiences a decreasing trend in streamflow inequality in 18.3 % of its catchments during the same period. It is also found that a more evenly distributed precipitation within the catchment and higher dam storage capacity corresponds to more evenly distributed streamflow availability throughout the year. This study enhances our understanding of streamflow inequality worldwide, which will aid policy formulation to foster sustainable development.

A review of hydroclimate variability and changes in the Blue Nile Basin, Ethiopia

Understanding the factors that influence hydroclimate variability is crucial for developing sustainable water management strategies in dynamic environments. The Blue Nile Basin, a significant freshwater resource in Africa, is facing challenges related to hydroclimate changes that impact sustainable development. Since the 1970s, the hydroclimate patterns of the region have undergone notable changes, prompting the need for a review of the literature on hydroclimate variability of the basin. Therefore, this study aims to offer a brief overview of the latest literature on hydroclimate variability and changes in the Blue Nile Basin. Based on the review of hydroclimate studies in the basin, it is evident that there have been significant advancements in our understanding of this complex system. However, the review also highlights that there are still areas of research that require further development to provide more comprehensive knowledge of the basin's hydroclimate. The projected intensification of hydroclimate change throughout the 21st century underscores the urgency for continued research efforts. The observed warming trend in the temperature of the basin and the discrepancies amongst research outputs on precipitation changes are important areas that require further investigation. Additionally, the inconsistency in reported changes in the watershed's hydrology and streamflow across the basin emphasizes the need for continued research to understand the factors behind these changes. Overall, this review provides valuable insights into the current state of hydroclimate studies in the basin and highlights the key areas for future research efforts to enhance our understanding of this vital system.

Climate change impacts on groundwater discharge-dependent streamflow in an alpine headwater catchment

Climate change will have-and, in much of the world, is already having-a pronounced impact on alpine water resources. A deeper understanding of the future role of groundwater in alpine catchments, including quantification of climate change impacts on groundwater discharge, is vital for understanding the future of alpine water resources as a whole. Here, we develop and couple a geophysics-informed groundwater model with a net recharge model to investigate the impacts of climate change on a nival-regime alpine headwater catchment with significant unconfined Quaternary aquifer coverage. Flow in the groundwater-fed stream at the catchment outlet is analysed to determine changes in its annual dynamics. Comparing the periods 2020-2040 and 2080-2100 under ten RCP-8.5 climate models, we find a 35 % decrease in mean groundwater discharge and an increase in no-flow periods from ~0 % to 4.3 %. We also observe significant changes to the timing of monthly mean discharge maxima and minima, which shift ~1 month and ~5 months earlier, respectively. While groundwater has the potential to dampen the impacts of snow cover loss, currently perennial nival-regime alpine streams could be at risk of becoming intermittent by the end of the century. Our study underscores the increasingly critical role that groundwater will play in alpine catchments and emphasizes the need for quantitative understanding of the limits to its buffering capacity.

Impacts of longleaf pine (Pinus palustris Mill.) on long-term hydrology at the watershed scale

Threats from climate change and growing populations require innovative solutions for restoring streamflow in many regions. In the arid western U.S., attempts to increase streamflow (Q) through forest management have had mixed results, but these approaches may be more successful in the eastern U.S. where greater precipitation (P) and lower evapotranspiration (ET) offer greater potential to increase Q by reducing ET. Longleaf pine (Pinus palustris Mill.) (LLP) woodlands, once the dominant land cover in the southeastern United States, often have lower ET than other forest types but it is unclear how longleaf pine cover impacts watershed-scale hydrology. To address this question, we analyzed 21 gaged rural watersheds. We estimated annual water balance ET (ETwb) as the difference between precipitation (P) and streamflow (Q) between 1989 and 2021 and quantified low flow rates (7Q10) among watersheds with high and low LLP cover. To control for climate variability among watersheds, we compared variation in hydrology metrics with biotic and abiotic variables using the Budyko equation (ETBudyko) to understand the differences between the two ET estimates (∆ET). Watersheds with 15-72 % LLP cover had 17 % greater mean annual Q, 7 % lower annual ETwb, and 92 % greater 7Q10 low flow rates than watersheds with <3 % LLP. LLP cover decreased ET and increased Q by 2.4 mm or 0.15 % Q/P per 1 % of watershed area, but only when LLP was managed as open woodlands. Our results demonstrate that ecological forest restoration in these systems, which entails mechanical thinning and re-introduction of low-intensity prescribed fire to maintain open woodlands, and enhance understory diversity, can contribute to decreases in ET and increases in Q in eastern forests.

Impacts of LULC and climate changes on hydropower generation and development: A systematic review

There is a growing concern on a global scale that the world should transition towards the utilisation of energy-efficient technologies. Hydropower plays a very significant part in the fight against climate change, and as a result, it lessens the impact that climate changewill have on our ability to achieve the Sustainable Development Goals (SDGs). Both the effectiveness of hydropower generation and the amount of streamflow are impacted by climate change as well as land use and land cover (LULC). Accordingly, the purpose of this study is to conduct a literature review on the topic of the past and future effects of climate, land use, and land cover changes on hydropower generation. This review will be based on the entries found in a number of reliable databases. A systematic literature review was carried out to analyse how LULC and climate change will affect hydropower generation and development. The research was based on 158 pieces of relevant literature that had been reviewed by experts and indexed in Scopus, Google Scholar, and ScienceDirect. The review was carried out to determine three goals in mind: the impact of climate change on hydropower generation and development; the impact of climate change on streamflow; and the combined impact of changes in climate and changes in LULC on hydropower. The findings bring to light the primary factors contributing to climate change as well as shifts in LULC which are essential to the generation of hydropower on all scales. The study identifies factors such as precipitation, temperature, floods, and droughts as examples of climate change. Deforestation, afforestation, and urbanisation are identified as the primary causes of changes in LULC over the past several decades. These changes have a negative impact on the generation and development of hydropower.

Impacts of hydrometeorological factors on discharge simulation in the North West Himalayas: a SUFI-2 algorithm-driven investigation using the SWAT model

The Soil and Water Assessment Tool (SWAT) is a computational hydrological model extensively utilised for developing sustainable strategies and viable approaches for prudent management of water resources. The central emphasis of this study is on the utilisation of SWAT model along with SWAT-CUP (SWAT calibration toolbox) to simulate streamflow in the upper Jhelum basin, the North West Himalayas, for a period of 20 years from 2000 to 2019. The global sensitivity analysis algorithm, Sequential Uncertainty Fitting 2 (SUFI-2) of SWAT-CUP, is used for sensitivity and uncertainty analysis. The optimised parameter set estimated by SUFI-2 constitutes 11 parameters that are found to be sensitive with soil conservation service (SCS) curve number (CN) being the most influential parameter followed by snowmelt base temperature. Autocorrelation analysis using the autocorrelation function was conducted on the temperature and precipitation time series data, followed by a pre-whitening procedure to remove any autocorrelation effects. Subsequently, the modified Mann-Kendall (MMK) test was applied to examine trends in the annual temperature and precipitation data. The results indicated statistically significant positive trends in both datasets on an annual scale. The results for the calibration period (2003-2014) for monthly simulation displayed good model performance at three gauging stations, Rambiara, Sangam and Ram Munshi Bagh with R2 values of 0.83, 0.847, 0.829, P factor values of 0.73, 0.76, 0.75 and R factor values of 0.61, 0.58, 0.63, respectively. The validation results for monthly simulation for the 2015-2019 period showed good model agreement with R2 values of 0.817, 0.853, and 0.836, P factor values of 0.76, 0.8, and 0.75 and R factor values of 0.62, 0.53, and 0.65, respectively. The study concludes that the SWAT hydrological model can perform satisfactorily in high mountainous catchments and can be employed to analyse the impact of land use-land cover changes and the effect of climate variation on streamflow dynamics.

Microplastic distribution and characteristics across a large river basin: Insights from the Neuse River in North Carolina, USA

While microplastics (MP) have been found in aquatic ecosystems around the world, the understanding of drivers and controls of their occurrence and distribution have yet to be determined. In particular, their fate and transport in river catchments and networks are still poorly understood. We identified MP concentrations in water and streambed sediment at fifteen locations across the Neuse River Basin in North Carolina, USA. Water samples were collected with two different mesh sizes, a trawl net (>335 μm) and a 64 μm sieve used to filter bailing water samples. MPs >335 μm were found in all the water samples with concentrations ranging from 0.02 to 221 particles per m³ (p m^-3) with a median of 0.44 p m^-3. The highest concentrations were observed in urban streams and there was a significant correlation between streamflow and MP concentration in the most urbanized locations. Fourier Transform Infrared (FTIR) analysis indicated that for MPs >335 μm the three most common polymer types were polyethylene, polypropylene, and polystyrene. There were substantially more MP particles observed when samples were analyzed using a smaller mesh size (>64 μm), with concentrations ranging from 20 to 130 p m^-3 and the most common polymer type being polyethylene terephthalate as identified by Raman spectroscopy. The ratio of MP concentrations (64 μm to 335 μm) ranged from 35 to 375, indicating the 335 μm mesh substantially underestimates MPs relative to the 64 μm mesh. MPs were detected in 14/15 sediment samples. Sediment and water column concentrations were not correlated. We estimate MP (>64 μm) loading from the Neuse River watershed to be 230 billion particles per year. The findings of this study help to better understand how MPs are spatially distributed and transported through a river basin and how MP concentrations are impacted by land cover, hydrology, and sampling method.

The impacts of global atmospheric circulations on the water supply in select watersheds in the Indonesian Maritime Continent using SPI

Despite the diverse atmospheric circulations affecting the Indonesian Maritime Continent (IMC), i.e., El Nino Southern Oscillation-ENSO, Indian Ocean Dipole-IOD, Madden Julian Oscillation-MJO, Monsoon, there is a lack of research on their interaction with hydrological events in watersheds. This study fills this gap by providing insights into the dominant atmospheric events and their correlation with the water supply in three characteristic watersheds, i.e., Tondano (north/Pacific Ocean), Jangka (south/Indian Ocean), and Kapuas (equatorial/interior) in IMC. The research used the standardized precipitation index for the 1-monthly (SPI1), 3-monthly (SPI3), and 6-monthly (SPI3) scale generated from 23 years (2000-2022) of monthly historical satellite rainfall data. The analysis compared each location's SPI indices with the monthly Nino 3.4, Dipole Mode Index (DMI), MJO (100E and 120E), Monsoon index, and streamflow data. The result shows that the dominant atmospheric events for the Tondano watershed were ENSO, IOD, and MJO, with correlation values of -0.62, -0.26, and -0.35, respectively. The MJO event was dominant for the Kapuas watershed, with a correlation value of -0.28. ENSO and IOD were dominant for the Jangka watershed, with correlation values of -0.27 and -0.28, respectively. The monsoon correlated less with the SPI3 in all locations, while it modulates the wet and dry period pattern annually. Most intense dry periods in Tondano occur with the activation of El Nino, while the intense wet period occurs even in normal atmospheric conditions. Most intense wet periods in Jangka occur with the activation of La Nina, while the intense dry period occurs even in normal atmospheric conditions. The occurrence of MJO compensates for the intense wet and dry periods in Kapuas. The correlation among SPI3, atmospheric circulation, and streamflow in the diverse watershed characteristics in the IMC watersheds could give strategic information for watershed management and applies to other watersheds with similar atmospheric circulation characteristics.

Climate and landuse change enhance spatio-temporal variability of Dongjiang river flow and ammonia nitrogen

The adverse impacts of climate and landuse change are threatening the availability of water quantity and its quality, yet there are limited understandings in the response of water availability to changing environment at different spatio-temporal scales. Aimed at quantifying the individual and superimposed effects of climate and landuse change on streamflow and ammonia nitrogen (NH₃-N) load in the Dongjiang River Basin (DRB), we dynamically simulated the historical (1981-2010) and future (2030-2070) variation of runoff depth and NH₃-N load coupling multiple regional climate model and landuse data. The increase in runoff depth (avg. +233.9 mm) due to climate change was about 33 times greater than that caused by landuse change (avg. -7.2 mm). Especially in the downstream of DRB (Hong Kong, Shenzhen and Dongguan cities, etc.), the maximum rise of runoff depth under climate change was near twice compared with baseline period, indicating the dominant control of climate change on runoff. Also there existed higher coefficient of variation (C_v) value of runoff in the dry season of downstream DRB, contributing potential great fluctuation in runoff. Besides, the variation of NH₃-N load was jointly influenced by climate and landuse change, revealing an offset or amplification effect. Moreover, the variability of NH₃-N load (C_v value as the metric) increased from 2030, reached a maximum in 2050, following decreased to 2070. The spatial distribution of NH₃-N load, in general, presented a downward trend and concentrated near the water body, while the monthly average NH₃-N load showed distinct peaks in spring and late summer temporally. Overall, the results highlight the significance of investigating the water availability under changing environment and more adaptive strategies should be proposed for better basin water management.

Coupling SWAT and Bi-LSTM for improving daily-scale hydro-climatic simulation and climate change impact assessment in a tropical river basin

Global climate change has led to an increase in both the frequency and magnitude of extreme events around the world, the risk of which is especially imminent in tropical regions. Developing hydrological models with better capabilities to simulate streamflow, especially peak flow, is urgently needed to facilitate water resource planning and management as well as climate change mitigation efforts in the tropics. In view of the need, this paper explores the feasibility of improving streamflow simulation performance in the tropical Kelantan River Basin (KRB) of Peninsular Malaysia through coupling a conceptual process-based hydrological model - Soil and Water Assessment Tool (SWAT) with a deep learning model - Bidirectional Long Short-Term Memory (Bi-LSTM) in two ways. All SWAT parameters were set as their default values in one hybrid model (SWAT-D-LSTM), whereas three most sensitive SWAT parameters were calibrated in the other hybrid model (SWAT-T-LSTM). Comparison of daily streamflow simulation results have shown that SWAT-T-LSTM consistently performs better than SWAT-D-LSTM as well as the stand-alone SWAT and Bi-LSTM model throughout the simulation period. Particularly, SWAT-T-LSTM performs considerably better than the other three models in simulating daily peak flow. Based on the latest projection results of five GCMs from the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6) under three emission scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5), the best-performed SWAT-T-LSTM was run to assess the potential impacts of climate change on streamflow in the KRB. Ensemble assessment results have concluded that both average and extreme streamflow is much likely to increase considerably in the already wet northeast monsoon season from November to January, which has surely raised the alarm for more frequent flood occurrence in the KRB.

Assessment of future water demand and supply using WEAP model in Dhasan River Basin, Madhya Pradesh, India

Understanding the available resources and the needs of those who use them is necessary for the evaluation and allocation of water resources. The main sectors utilizing the basin water resources are agriculture, drinking water, animal husbandry, and industries, and the efficient and rational management of water resources to be distributed among those different sectors of activity is vital. This study attempts to develop an integrated water resource management system for the Dhasan River Basin (DRB) by employing a scenario analysis approach in conjunction with Water Evaluation and Planning Model (WEAP) to analyze trends in water use and anticipated demand between 2015 and 2050, simulating five possible scenarios (I, II, III, IV, and V) as for external driving factors. For the WEAP modeling framework, 2015 was chosen as a current (base) year for which all available information and input data were given to the model and the future demand situation was analyzed for the period 2016-2050 (forecasting period). From the findings, it was observed that for the forecasting period, total water demand, unmet demand, and streamflow were 185.29 Bm³, 117.35 Bm³, and 58.26 Bm³, respectively, in the case of scenario I; 232.34 Bm³, 162.17 Bm³, and 59.87 Bm³ in case of scenario II; 139.40 Bm³, 84.37 Bm³, and 58.15 Bm³ in case of scenario III; 186.15 Bm³, 118.76 Bm³, and 56.98 Bm³ in case of scenario IV; and 181.89 Bm³, 96.87 Bm³, and 53.11 Bm³ in case of scenario V. Results of the study indicated that by 2050, increasing population growth, industrial development, and an increase in the agricultural area will rise the water demand dramatically, posing threats to the environment and humans. Therefore, implementing improved irrigation technologies, advancing agricultural practices on farms, and constructing water conservation and retaining structures could significantly reduce the unmet demands and shortfalls in DRB. Overall findings reveal that the pressure on the Dhasan water resources would increase in the future, and thus several suggestions have been provided to assist decision-makers in sustainable planning and management of water resources to meet future demands.

Joint probability analysis of streamflow and sediment load based on hybrid copula

Statistical analysis of streamflow and sediment is very important for integrated watershed management and the design of water infrastructure, especially in silt-rich rivers. Here, we propose a bivariate joint distribution framework based on nonparametric kernel density estimation (KDE) and a hybrid copula function to describe the complex streamflow-sediment dependent structure. In this framework, the non-parametric KDE is used to fit the marginal distribution function of streamflow and sediment variables, and then the hybrid copula function is constructed by using the linear combination of Clayton, Frank, and Gumbel copulas, and compared with five commonly used single copulas (Clayton, Frank, Gumbel, Gaussian, and t). We use the Jinsha River Basin (JRB) in the Yangtze River's (JR) upper reaches to verify the proposed method. The results show the following: (1) Compared with the gamma distribution (Gamma) and generalized extreme value (GEV) distribution of parameters, the marginal distribution function of streamflow and sediment variables can be effectively obtained based on nonparametric KDE. (2) Compared with the single copula, the hybrid copula function more fully reflects the complex dependent structure of streamflow and sediment variables. (3) Compared with the best single copula, the precision of return period based on hybrid copula can be increased by 7.41%. In addition, the synchronous probability of streamflow and sediment in JRB is 0.553, and the asynchronous probability of streamflow and sediment is 0.447. This study can not only improve the accuracy of streamflow and sediment statistical analysis in JRB, but also provide a useful framework for other bivariate joint probability analysis.

Modelling climate change impacts at a drinking water reservoir in Turkey and implications for reservoir management in semi-arid regions

Climate change can have severe impacts on the water availability in semi-arid regions. In this study, we assessed the impact of climatic changes on water availability in the Altınapa Reservoir Watershed, located in the Konya province, south-central Turkey. Altınapa Reservoir supplies drinking water to Konya, a city of about 2 million population. We investigated possible changes in streamflow and reservoir storage over 2021-2098 under two representative concentration pathway scenarios (RCP4.5 and RCP8.5) developed based on GFDL-ESM2M, HadGEM2-ES, and MPI-ESM-MR global circulation models. We used a physically based model (SWAT-Soil and Water Assessment Tool) for understanding the hydrologic response of the basin to climatic changes. Results show that upward trends in air temperatures in the range of 0.01-0.04 °C/year and 0.005-0.06 °C/year are expected from 2021 to 2098 under the RCP4.5 and RCP8.5 scenarios, respectively. According to the HadGEM2-ES model, precipitation and streamflow would show a downward trend at a rate of 0.96 mm/year and 0.007 m³/s/year under the RCP4.5 scenario and at a rate of 1.62 mm/year and 0.01 m³/s/year under the RCP8.5 scenario, respectively. GFDL-ESM2M and MPI-ESM-MR models project upward trends in precipitation and streamflow under the RCP4.5 scenario (in the range of 0.64-1.28 mm/year and 0.0003-0.006 m³/s/year, respectively), and downward trends under the RCP8.5 scenario (in the range of 0.47-0.76 mm/year and 0.0015-0.003 m³/s/year, respectively). Reservoir storage is projected to increase slightly according to GFDL-ESM2M model and decrease according to the HadGEM2-ES, and MPI-ESM-MR models under both scenarios. Precipitation, streamflow, and reservoir storage predictions of GFDL-ESM2M and MPI-ESM-MR models are considerably lower than those observed in the basin in recent decades, showing that water resources will decrease in the future. The changes in water withdrawal patterns could cause further reductions in water availability. Good resilience to climate change can be achieved by a flexible water management system and by reducing water consumption and water losses in the watershed and from the reservoirs.

Long-term hydrological response emerges from forest self-thinning behaviour and tree sapwood allometry

Fires in forested catchments are of great concern to catchment managers due to their potential effect on water yield. Among other factors such as meteorological conditions and topography, dominant vegetation and its regeneration traits can play a key role in controlling the variability in the type and recovery-time of the hydrological response between forested catchments after stand-replacing fires. In temperate South-Eastern Australia, a long-term reduction in streamflow from catchments dominated by regenerating tall-wet Eucalyptus obligate seeder forests was observed, which has substantial implications for Melbourne's water supply. While the unusual hydrological response has been attributed to the higher water-use of the regrowth forests, the dominant underlying mechanism has not yet been identified. Here we show analytically and with a closed-form solution that this streamflow pattern can emerge from forest dynamics, namely the combination of growth and tree mortality as constrained by the self-thinning line (STL) and sapwood allometry of the dominant overstory tree species under non-limiting rainfall regimes. A sensitivity analysis shows that observed variations in the relative streamflow anomaly trend can be explained by parameters controlling: (i) the shape of the STL; (ii) regeneration success; (iii) radial tree growth rate; and (iv) fire severity. We conclude that the observed variation in long-term post-disturbance streamflow behaviour might have resulted from different trajectories of forest dynamics and suggest that to minimize uncertainty in future water-balance predictions, eco-hydrological models for even aged forests include a mechanistic representation of stand demography processes that are constrained by forest inventory data.

Impact of variation in climatic parameters on hydropower generation: A case of hydropower project in Nepal

Nepal has substantial potential to generate electricity through hydropower projects. Most of the hydropower projects in Nepal are Run-off-River (ROR) types. Significant seasonal variation can be pronounced on its river basins resulting in higher streamflow & higher hydropower generation during the wet/summer season and just reverse scenario in case of the dry/winter season. Thus, ROR-type hydropower in Nepal is more susceptible to Climate Change. This study assesses the impact of variation in climatic parameters on the hydropower generation by implementing WEAP model using the meteorological and hydrological data from 1976 to 2004 under Reference & Climatic Scenarios. The results reveal that the streamflow of Dordi River of Nepal is in increasing trends and can be more pronounced during April, May, June & July of the season under climatic scenarios. The generation of hydropower plant is likely to increase up to 15%, 1%-32% & 1%-51% over the study period under climatic scenario-1, 2 & 3, respectively, as compared to baseline scenario and the increments are observed to be more prominent during April & May of the season which is very crucial finding in current context of Nepal as there is power deficit during the dry season. Therefore, detailed technical and policy level planning can enhance the power generating capability of the future hydropower projects that will be developed in this corridor. This will significantly impacts the national energy planning and implementation.

A method for detecting the non-stationarity during high flows under global change

The sustainability of existing water resources is influenced by extreme streamflow, and climate variability and human activities are generally the major factors controlling these dynamics. However, most of previously proposed methods to determine the effects of these factors have only been developed under the assumption of stationarity. Therefore, to overcome the existing research gap, an innovative method was proposed in this study to analyze and distinguish the effects of climate variability and human activities on extreme streamflow based on the non-stationarity theory. Accordingly, a rainfall-runoff model was developed using long-term hydrological data in the watersheds of Southeast China, which cover >75,000 km². The model proposed in this study showed an acceptable performance, as indicated by the Nash-Sutcliffe efficiency coefficient (NSE), the Kling-Gupta efficiency (KGE), and percent bias (PBIAS). The NSE, KGE, and |PBIAS| were 0.67-0.75, 0.57-0.74, and 1.22-16.79 during the calibration periods, respectively. And the NSE, KGE, and |PBIAS| were 0.69-0.77, 0.65-0.76, and 0.98-17.51 during the calibration periods, respectively. The trends of the extreme streamflow were analyzed for these watersheds at different time scales. The streamflow extremes at short time scales were found to be more sensitive to changing environment than those at longer time scales. The major factor controlling streamflow extremes at short time scales was human activities and climate change may be the dominant factor influencing streamflow extremes at long time scales. The findings of this study could provide useful insights into water management under global change conditions.

Integrated remote sensing and machine learning tools for estimating ecological flow regimes in tropical river reaches

With the gradual declining streamflow gauging stations in many world-rivers, emphasis is given nowadays to develop remote sensing (RS)-based approaches as the next-generation hydrometry for estimating riverine ecological flow regimes (EFR). For constructing EFR based on daily-streamflow data in scantily-gauged reaches, use of RS techniques in narrow flow-width tropical rain-fed rivers is constrained with the non-availability of finer spatial satellite data at daily scale. To address these limitations, this study proposes a novel framework that integrates the enhanced spatiotemporal adaptive reflectance fusion (FUS) of the 250 m × 1-day resolution Aqua-MODIS and 30 m × 1-day resolution Landsat satellite-based remote sensing images in the near-infrared region with the machine learning algorithms. These developed frameworks are named as Artificial Neural Network-based ANNFUS, Random Forest Regression-based RFRFUS, and Support Vector Regression-based SVRFUS models, which were tested for daily-scale streamflow estimation in a typical Brahmani River Basin, India. The results reveal that by addressing the linear and nonlinear dynamism between the streamflow and satellite signals, all the developed models could simulate the streamflow very well with the Nash-Sutcliffe efficiency>0.8, Kling-Gupta efficiency>0.8, relative root mean square error (rRMSE) of 0.051-0.12, and normalized RMSE of 0.23-0.36. However, for reproducing the high, median, and low streamflow regimes, the SVRFUS model was found to be the best with the NSE>0.85 and KGE>0.8. Conclusively, the proposed approach is found to have the potential to be replicated in other world-river basins to estimate ecological flow regimes at defunct gauging stations facilitating the basin-scale aquatic environmental management.

Multi-decadal analysis of water resources and agricultural change in a Mediterranean semiarid irrigated piedmont under water scarcity and human interaction

Mediterranean piedmonts are an important hydro-agricultural systems. They constitute the junction between the mountains, where the streamflow is generated, and the surrounding plains, where the water is used. In Morocco, these traditional systems extend largely along the High Atlas Mountains. Yet, changing conditions in the Mediterranean basin as well as recurrent droughts in recent decades remain poorly understood in terms of hydrological and agricultural impacts, particularly in traditional hydro-agro-systems. The combined effects of climate variability and ineffective management of water resource dynamics may lead to increased water scarcity in these regions. The present work aims to assess the effects of climate variability and associated agricultural changes on water resources in a traditional irrigated piedmont of the Moroccan High Atlas. To that end, a trend analysis, together with change points detection, was carried out on annual and monthly precipitation, and streamflow from 1965 to 2018. Then, the standardized precipitation index (SPI) was employed to identify meteorological droughts. Also, groundwater, and spring discharge data were analyzed and discussed from 1973 to 2021. SPI outcomes revealed three major droughts, in 1981-1988, 1999-2008, and 2013-2018. Although the precipitation data showed no significant trend, except for Tahannaout station, the average annual precipitation over the piedmont area decreased by 28%. Similarly, streamflow decreased significantly by almost 40% for all stations, as did the Abainou spring's discharge. Consistent with that, groundwater level has declined dramatically over the past decades in the downstream piedmont. These decreases in water cycle components were tightly aligned with droughts. Yet, irrigation diversions were maintained in both dry and wet periods. Paradoxically, this decrease in water resources was associated with an agricultural transition from seasonal crops (cereals) to perennial crops (olive trees). This conversion is likely to amplify the water shortage, leading to groundwater resources overexploitation to satisfy the growing agricultural demand.

Water availability drives instream conditions and life-history of an imperiled desert fish: A case study to inform water management

In arid ecosystems, available water is a critical, yet limited resource for human consumption, agricultural use, and ecosystem processes-highlighting the importance of developing management strategies to meet the needs of multiple users. Here, we evaluated how water availability influences stream thermal regimes and life-history expressions of Lahontan cutthroat trout (Oncorhynchus clarkii henshawi) in the arid Truckee River basin in the western United States. We integrated air temperature and stream discharge data to quantify how water availability drives stream temperature during annual spawning and rearing of Lahontan cutthroat trout. We then determined how in situ stream discharge and temperature affected adult spawning migrations, juvenile growth opportunities, and duration of suitable thermal conditions. Air temperatures had significant, large effects (+) on stream temperature across months; the effects of discharge varied across months, with significant effects (-) during May through August, suggesting increased discharge can help mitigate temperatures during seasonally warm months. Two models explained adult Lahontan cutthroat trout migration, and both models indicated that adult Lahontan cutthroat trout avoid migration when temperatures are warmer (~ > 12 °C) and discharge is higher (~ > 50 m³*s^-1). Juvenile size was best explained by a quadratic relationship with cumulative degree days (CDD; days>4 °C) as size increased with increasing CDDs but decreased at higher CDDs. We also found an interaction between CDDs and discharge explaining juvenile size: when CDDs were low, higher discharge was associated with larger size, but when CDDs were high, higher discharge was associated with smaller size. Stream temperatures also determined the duration of juvenile rearing, as all juvenile emigration ceased at temperatures >24.4 °C. Together, our results illustrated how stream discharge and temperature shape the life-history of Lahontan cutthroat trout at multiple stages and can inform management actions to offset warming temperatures and facilitate life-history diversity and population resilience.

Connecting microbial, nutrient, physiochemical, and land use variables for the evaluation of water quality within mixed use watersheds

As non-point sources of pollution begin to overtake point sources in watersheds, source identification and complicating variables such as rainfall are growing in importance. Microbial source tracking (MST) allows for identification of fecal contamination sources in watersheds; when combined with data on land use and co-occuring variables (e.g., nutrients, sediment runoff) MST can provide a basis for understanding how to effectively remediate water quality. To determine spatial and temporal trends in microbial contamination and correlations between MST and nutrients, water samples (n = 136) were collected between April 2017 and May of 2018 during eight sampling events from 17 sites in 5 mixed-use watersheds. These samples were analyzed for three MST markers (human - B. theta; bovine - CowM2; porcine - Pig2Bac) along with E. coli, nutrients (nitrogen and phosphorus species), and physiochemical paramaters. These water quality variables were then paired with data on land use, streamflow, precipitation and management practices (e.g., tile drainage, septic tank density, tillage practices) to determine if any significant relationships existed between the observed microbial contamination and these variables. The porcine marker was the only marker that was highly correlated (p value <0.05) with nitrogen and phosphorus species in multiple clustering schemes. Significant relationships were also identified between MST markers and variables that demonstrated temporal trends driven by precipitation and spatial trends driven by septic tanks and management practices (tillage and drainage) when spatial clustering was employed.

Impact of climate change on future precipitation amounts, seasonal distribution, and streamflow in the Omo-Gibe basin, Ethiopia

This study projected the impact of climate change on the amount of precipitation, seasonal distribution, and streamflow of the Omo-gibe basin, Ethiopia. Projections of climate change using the results of high-resolution multimodal ensembles from fifteen regional climate models (RCMs) of the Coordinated Regional Climate Reduction Experiment (CORDEX)-Africa were statistically downscaled and bias-adjusted using a quantile mapping approach. Precipitation and temperature were projected under RCP 8.5 and RCP 4.5 emission scenarios. Climate and streamflow projections from a mean ensemble of RCMs in the near future (2025–2050), medium future (2051–2075), and far future (2076–2100) were compared to the reference (1989–2019). Mann-Kendall (MK) trend testing was used to determine if a change is statistically significant and to detect trends in temperature, precipitation, and streamflow. The Soil and Water Assessment Tool (SWAT) hydrological model was used to project the impact of climate change on the streamflow. According to RCP4.5 and RCP8.5, the emission scenarios predicted significant positive (rising) temperature, but significant negative (decreasing) precipitation and streamflow. The average temperature projected increases range from 2.40-3.34 °C under the RCP 4.5 emission scenarios and 2.6–4.54 °C under the RCP 8.5 emission scenarios. Annual average precipitation projected decreases range between 10.77-13.11% under the RCP 4.5 emission scenario, while the RCP 8.5 emission scenarios decrease range between 11.10-13.86% in the rainy summer season (June–August) and the irregular rain season (March–May). Projected annual average streamflow decrease range between 7.08-10.99% under the RCP 4.5 emission scenarios and 10.98–12.88% under the RCP 8.5 emission scenarios. Results on projected temperature increases and reductions in precipitation and streamflow will help to develop effective adaptation measures to reduce the ongoing impacts of climate change and draw up long-term water resource management plans in the river basin. Both the results and the multidisciplinary approach will be vital to irrigation and hydropower project planners.

A stochastic approach for the assessment of suspended sediment concentration at the Upper Rhone River basin, Switzerland

This study addresses the link between suspended sediment concentration, precipitation, streamflow, and direct runoff components. This is important since suspended sediment concentration in the streamflow has invaluable importance in the management of the river basin. For this, the daily streamflow time series in five consecutive stations at Upper Rhone River Basin, a relatively large basin in the Alpine region of Switzerland, daily precipitation at one station, and the twice a week suspended sediment concentration records at the most downstream station between January 1981 and October 2020 are used. Initially, the base flow and the direct runoff associated with streamflow time series are obtained using the sliding interval method. Elasticity analyses between streamflow and suspended sediment concentration together with correlation, autocorrelation, partial autocorrelation, stationarity, and homogeneity are examined by the Augmented Dickey-Fuller and Pettitt's tests, respectively. Then, various stochastic scenarios are generated using the autoregressive moving average exogenous method (ARMAX). It is concluded that the precipitation and direct runoff have fewer effects on the suspended sediment concentration at downstream of the river. Hence, the cumulative effect of the glacier or snowmelt and channel erosion may exceed the effect of rain blown washouts on the suspended sediment concentration at the Port du Scex station. It is found that the ARMAX model results are satisfactory and can be suggested for further application.

Critical role of groundwater discharge in sustaining streamflow in a glaciated alpine watershed, northeastern Tibetan Plateau

As the hydrologic buffering capacity of glaciers diminishes on climate warming, groundwater stored in the glaciated alpine watersheds becomes an important source of streamflow, quantifying the groundwater contribution to this streamflow is significant for better predictions of the impact of rapidly disappearing glaciers on regional water resources. However, the role of groundwater in sustaining streams remains unclear. Here, we selected the upper Shule River Basin (USRB) on the northeast Tibetan Plateau (NETP) as a case to address this knowledge gap through a comprehensive study of geochemistry and stable isotopes data, the application of an end member mixing model and the baseflow hydrograph separation program (HYSEP). Our results indicate that even though the potential sources of streamflow exhibited distinct monthly differences during December 2012-December 2013, the groundwater was the dominant contributor to streamflow generation in the USRB. The groundwater contributed 45% to 100% of the monthly mean streamflow, and the annual mean value of 70%. By contrast, the glacier-snow meltwater and precipitation only contributed 12% and 18% of the annual discharge. The volume contributed by groundwater was calculated as 9.93 × 10⁸ m³, approximately six times higher than the input of the glacier-snow meltwater (i.e., 1.63 × 10⁸ m³). From 1954 to 2018, the volume of the groundwater discharge to the streamflow in the USRB continuously increased from 4.83 × 10⁸ m³/a (65% of total streamflow) in the 1950s to 10.34 × 10⁸ m³/a (71% of total streamflow) in the 2010s, an increase of 2.14 times. The retreating glacier, as well as increasing precipitation and temperature, were determined to be the main reasons for the increase in groundwater discharge to the streamflow. Our findings suggest that groundwater contribution is more important than was previously thought in the glaciated alpine watersheds on the NETP.

Carbon sequestration and water yield tradeoffs following restoration of abandoned agricultural lands in Mediterranean mountains

Abandoned cropland areas have the potential to contribute to climate change mitigation through natural revegetation and afforestation programs. These programs increase above and belowground carbon sequestration by expanding forest cover. However, this potential to mitigate climate change often involves tradeoffs between carbon sequestration and water availability. Particularly in a water limited environments such as the Mediterranean region, any loss of recharge to groundwater or streamflow can have critical societal consequences. In this study, we used an ecohydrologic model, Regional Hydro-Ecological Simulation System (RHESSys), to quantify these tradeoffs for land management plans in abandoned cropland areas in Mediterranean mountains. Changes to Net Ecosystem Production (NEP), water yield and Water-Use Efficiency (WUE) under different land management and climate scenarios were estimated for Arnás, a catchment with similar geology, vegetation and climate to many of the locations targeted for land abandonment restoration in the Spanish Pyrenees. Results showed significant changes to both carbon and water fluxes related to land management, while changes related to a warming scenario were not significant. Afforestation scenarios showed the highest average annual carbon sequestration rates (112 g C·m^-2·yr^-1) but were also associated with the lowest water yield (runoff coefficient of 26%) and water use efficiency (1.4 g C·mm^-1) compared to natural revegetation (-27 g C·m^-2·yr^-1, 50%, 1.7 g C·mm^-1 respectively). Under both restoration scenarios, results showed that the catchment ecosystem is a carbon sink during mid-February to July, coinciding with peak monthly transpiration and WUE, while during the rest of the year the catchment ecosystem is a carbon source. These results contribute to understanding carbon and water tradeoffs in Mediterranean mountains and can help adapt restoration plans to address both carbon sequestration and water management objectives.

Assessment of the changes in contributions from water sources to streamflow induced by urbanization in a small-sized catchment in Southeastern Brazil using the dual stable isotopes of water (18O and 2H)

Urban growth often results in changes in the urban hydrological cycle, causing impacts on water availability in densely populated regions. The water isotopologues can provide relevant information about the origin of water under different hydrogeological scenarios, aiding to implement better strategies for water conservation in coupled natural-urbanized environments. In this study, the isotopic compositions of multiple water sources were assessed in a pristine (Ipanema National Forest, FLONA) and an urbanized (Lavapés catchment, SOR) watershed located in the Sorocaba River basin (State of São Paulo, Southeastern Brazil), seeking to understand the causes of isotopic variability and to determine the relative contribution from different sources to streamflow, using the Bayesian mixing model approach. Differences in isotopic composition were observed, as FLONA yielded the most depleted water (ca. -7.5 ‰ [Formula: see text]¹⁸O for surface and groundwater and ca. + 11.0 ‰ d-excess), while SOR yielded the most enriched water (ca. -5.5‰ [Formula: see text]¹⁸O for surface and groundwater and -3.8‰ [Formula: see text]¹⁸O for the water supply system), with evidence of evaporation (ca. + 8.2 ‰ d-excess). The differences observed in isotopic compositions are related to a combination of different factors, such as geological framework, groundwater recharge, and evaporation associated with the Itupararanga water reservoir. Both in FLONA and SOR, groundwater discharge is the most important factor that regulates streamflow. However, in SOR, losses from the water supply system were almost constant along the year, representing an important contribution. The results presented here highlight the use of isotope hydrology techniques to solve problems related to urban hydrology.

Woodland's role in natural flood management: Evidence from catchment studies in Britain and Ireland

Despite the attention currently given to the potential environmental benefits of large-scale forest planting, there is a shortage of clear observational evidence regarding the effects on river flows, and what there is has often been contradictory or inconclusive. This paper presents three independently conducted paired-catchment forestry studies covering 66 station-years of flow measurements in the UK and Ireland. In each case coniferous evergreen trees were removed from one catchment with minimal soil disturbance while the adjoining control catchment was left unchanged. Trees were removed from 20% - 90% of the three experimental basins. Following woodland removal there was an increase in dry weather baseflow at all sites. Baseflows increased by about 8% after tree removal from a quarter of the Hore basin and by 41% for the near-total cut at Howan. But the changes were more complex for peak flows. Tree harvesting increased the smallest and most frequent peak storm flows, indicating that afforestation would lead to the suppression of such events. This was however restricted to events well below the mean annual flood, indicating that the impact of forests upon the largest and most damaging floods is likely to be limited. Whilst a forest cover can be effective in mitigating small and frequent stormflows it should never be assumed to provide protection against major flood events.

The re-greening of east coast Australian rivers: An unprecedented riparian transformation

Eastern Australia has a climate characterised by extreme variability and the occurrence of multiple years of drought conditions. Arguably one of the severest droughts on record - the Big Dry ended in many areas with the La Niña of 2009/2010. A succession of subsequent dry years brought a return to drought conditions across much of eastern Australia in 2018 and 2019, ending with the catastrophic fires of 2019/2020. An analysis of river gauges in eastern Australia demonstrates that unregulated rivers have been subject to reduced monthly and total annual flow for far longer than the recent multi-year droughts. A breakpoint regression model on the annual streamflow data shows statistically significant declines in total annual flow (by up to a factor of three) since 1992/93 on the far South coast of New South Wales (NSW). In the monthly data, fifteen of the nineteen gauges analysed exhibit modelled breakpoints, but with statistically significant differences in monthly mean discharge between consecutive periods only occurring in three of these gauges (occurring between 1972 and 1993 in both the North and South coast). The trend toward reduced flow over the last few decades has, for many rivers, coincided with land use and river management changes resulting in increases in woody riparian vegetation. To show this we use a remote sensing technique and estimate the magnitude of vegetation change along all major rivers and their tributaries on the eastern seaboard of NSW (28 catchments with total river length assessed of 19,750 km) using a normalized difference vegetation index (NDVI) analysis of woody vs non-woody riparian vegetation extent. Predicted vegetation change between 1987 and 2020 is spatially variable across catchments but the mean increase in woody riparian vegetation across all catchments is 9-51% (0.2 and 0.1 NDVI increases). Such increases are perhaps the largest biogeomorphic change the SE Australian drainage network has experienced since the initial clearance of vegetation associated with European colonisation in the late 18th and early 19th centuries.

Transboundary river basins: Scenarios of hydropower development and operation under extreme climate conditions

Transboundary river basins across developing countries, such as the Lower Mekong River Basin (LMB), are challenging to manage given frequent divergences on development and conservation priorities. Driven by needs to sustain economic performance and reduce poverty, the LMB countries are embarking on significant land use changes in the form of more hydropower dams, to satisfy growing energy demands. This pathway could lead to irreversible changes to the ecosystem of the Mekong River, if not properly managed. Given the uncertain environmental externalities and trade-offs associated with further hydropower development and operation in the LMB, this research develops four plausible scenarios of future hydropower operation, and assesses their likely impact on streamflow and instream total suspended solids and nitrate loads of the Mekong River. The findings suggest that further hydropower operations on either tributary or mainstream could result in annual and wet season flow reduction between 11 and 25% while increase dry season flows by 1 to 15%, when compared to a business-as-usual scenario. Conversely, hydropower operation on both tributary and mainstream could result in dry season flow reduction between 10 and 15%. Both instream TSS and nitrate loads are forecasted to reduce under all three scenarios by as much as 78 and 20%, respectively, compared to the business-as-usual one. These effects are predicted to magnify under extreme climate conditions with dry season flow, TSS, and nitrate levels reduced by as much as 44, 81 and 35%, respectively, during a projected extreme dry climate condition, but less severe under improved operational alternatives. With further hydropower development in the LMB being highly unavoidable, these findings can inform effective transboundary management pathways for balancing electricity generation and protection of riverine ecology, water and food security, and people livelihoods.

The effects of climate variability and land-use change on streamflow and nutrient loadings in the Sesan, Sekong, and Srepok (3S) River Basin of the Lower Mekong Basin

This paper aimed at examining the climate variability and land-use change effects on streamflow and pollutant loadings, namely total suspended sediment (TSS), total nitrogen (T-N), and total phosphorus (T-P), in the Sesan, Sekong, and Srepok (3S) River Basin in the period 1981-2010. The well-calibrated and validated Soil and Water Assessment Tool (SWAT) was used for this purpose. Compared to the reference period, climate variability was found to be responsible to a 1.00% increase in streamflow, 2.91% increase in TSS loading, 11.35% increase in T-N loading, and 19.12% reduction in T-P loading for the whole basin. With regard to the effect of land-use change (LUC), streamflow, TSS, T-N, and T-P loadings increased by 0.01%, 3.70%, 10.12%, and 10.94%, respectively. Therefore, the combination of climate variability and LUC showed amplified increases in streamflow (1.03%), TSS loading (7.09%), and T-N loading (25.05%), and a net effect of decreased T-P loading (10.35%). Regarding the Sekong and Srepok River Basins, the streamflow, TSS, T-N and T-P showed stronger responses to climate variability compared to LUC. In case of the Sesan River Basin, LUC had an effect on water quantity and quality more strongly than the climate variability. In general, the findings of this work play an essential role in providing scientific information to effectively support decision makers in developing sustainable water resources management strategies in the study area.

Streamflow and sediment yield estimation, and area prioritization for better conservation planning in the Dawe River watershed of the Wabi Shebelle River Basin, Ethiopia

Estimating sediment yield and streamflow, as well as identifying soil erosion processes, are necessary for properly designing superior management techniques, monitoring and evaluating various management scenarios, and prioritizing better conservation planning. Therefore, this study estimates streamflow and sediment yield and prioritizes the catchment sub-watersheds for conservation planning in the Dawe River watershed. In the continuous-time step, sediment load data is generated by developing a sediment rating curve. Statistical measures were used to weigh the SWAT's performance in estimating streamflow and sediment output over the calibration (2000-2008) and validation (2009-2013) periods. The model's performance in estimating the monthly streamflow was 0.73, 0.55, and 0.79 for NSE, R-factor, and R², respectively, according to the calibration results. For sediment yield, the Nash Sutcliffe efficiency (NSE), R-factor, and R² were 0.77, 0.47, and 0.82, respectively. Estimated sediment output rates were higher in agricultural lands with eutric and rendzic leptosols soil types and gradients in the study watershed. For the indicated sub-watersheds in the catchment, the three best sediment management scenarios (BMPs) were considered: S1 (filter strip), S2 (terrace/bund), and S3 (reforestation). With the implementation of S1, S2, and S3, the sediment yield was reduced by 15.7 percent, 21.3 percent, and 24.9 percent, respectively, based on the chosen BMPs. As a result, adopting S3 for the Dawe River watershed for productive sediment reductions should be encouraged. As a result, our findings point to the best strategy for negotiating a stronger conservation plan.

Dynamics of streamflow and sediment load in Peninsular Indian rivers (1965-2015)

The streamflow and sediment load in natural rivers around the world are undergoing significant changes due to the present climate change and anthropogenic activities. Therefore, for the management of water resources, soil conservation practices, and regulating coastal erosion; it is crucial to identify spatio-temporal variability and dynamics of streamflow and sediment load in natural rivers. The inherent characters of the tropical rivers in Peninsular India are not extensively studied. This paper examines temporal variation in streamflow, sediment load, and sensitivity of landscape complexity in varying sediment yield in 12 major tropical rivers in Peninsular India. About half-century of daily time-series records have been assessed to compute annual variabilities, trends, and abrupt changes through Mann-Kendall and Pettitt tests. Partial least squares regression has been employed to determine dominant drivers of sediment yield from a large number of topographic and climatic variables. The results indicate that concerning the global river runoff and sediment flux, 12 major Peninsular Indian rivers contribute less than 1% water and little more than 1% sediment to the world oceans. During the past five decades, a significant decrease in streamflow is found in Krishna, Cauvery and Narmada rivers and the changes are associated with variation in precipitation. After 2000, sediment load in almost all rivers has declined more than 40%. Construction of numerous high capacity reservoirs and dams have a significant influence on the reduction of sediment load. Profile curvature, plan curvature, relief, average elevation, circularity ratio and average annual rainfall explain the most among numerous other topographic and climatic variables with relation to the sediment yield in Peninsular India. The present study is intended to elucidate the dynamics of streamflow and sediment load during the past five decades and bridge knowledge gaps of the dynamic nature of Peninsular rivers in India.

Improvement of simulating sub-daily hydrological impacts of rainwater harvesting for landscape irrigation with rain barrels/cisterns in the SWAT model

Rain barrels/cisterns, a popular type of low impact development (LID) practice, can restore urban hydrological processes and decrease municipal water use by harvesting roof runoff for later use, such as landscape irrigation. However, tools to assist decision makers in creating efficient rainwater harvesting and reuse strategies are limited. This study improved the Soil and Water Assessment Tool (SWAT) in simulating the subdaily hydrological impacts of rainwater harvesting for landscape irrigation with rain barrels/cisterns, including the simulation of rainwater harvesting with rain barrels/cisterns, rainwater reuse for auto landscape irrigation, evapotranspiration, initial abstraction, impervious area, soil profile, and lawn management operation. The improved SWAT was applied in the urbanized Brentwood watershed (Austin, TX) to evaluate its applicability and investigate the impacts of rainwater harvesting and reuse strategies on the reductions and reduction efficiencies (reductions per volume of rain barrels/cisterns implemented) of field scale runoff (peak and depth) and watershed scale streamflow (peak and volume) for two storm events. Scenarios explored included different sizes of rain barrels/cisterns, percentages of rooftop areas with rain barrels/cisterns implemented, auto landscape irrigation rates, and landscape irrigation starting times. The performance of rainwater harvesting and reuse strategies, which is determined by features of fields, watersheds, and storm events, varied for different reduction goals (streamflow or runoff, and peak or depth/volume). For instance, the scenario with rain barrel/cistern sizes of 7.5 mm (design runoff depth from treated roof area) and the scenario with 10% of suitable area implemented with rain barrels/cisterns provided the highest peak streamflow reduction efficiency and total streamflow volume reduction efficiency at the watershed scale, respectively for the smaller storm event. To achieve sustainable urban stormwater management, the improved SWAT model has enhanced capability to help stakeholders create efficient rainwater harvesting and reuse strategies to reduce field scale runoff and watershed scale streamflow.

Hydrological modelling of a snow/glacier-fed western Himalayan basin to simulate the current and future streamflows under changing climate scenarios

Himalayan rivers are the paramount source of water supply to millions of people in northern India for drinking, irrigation and hydropower generation. Several researches reported that the hydrological regime of these Himalayan rivers is vulnerable to climate change. In order to understand the hydrologic response of their headwaters and examine the climate change impacts on streamflow, a hydrological modelling study is carried out in the upper part of the Satluj river basin in western Himalaya by using a temperature index based SWAT (Soil Water Assessment Tool) model. The model performed well for both calibration (years 1986-2000) and validation (2001-2005) periods against the observed daily streamflow at Rampur (R² ≈ 0.9 and NSE ≥ 0.85). The study reveals that having a larger snow covered area, the snowmelt runoff is the major contributor to the Satluj river discharge at Rampur that comes out to be about 68-71% of the average annual water yield of about 600 mm. The actual evapotranspiration comes out to be about 14% of precipitation. The water yield of the basin is about 50% of the precipitation, for which the major part is generated in early summer. Further, to study the climate change impact on future streamflow, the downscaled data of CORDEX CCSM4 under two Representative Concentration Pathways (RCP4.5 and RCP8.5) scenarios are used. The bias correction is applied at point level to remove biases from future time series of downscaled data and subsequently loaded into the SWAT model to simulate the future streamflows at the end of the century. The future climate variability in terms of precipitation and temperature exhibited that the climate in the region would become wetter and warmer. A 14% to 21% of increase in annual precipitation is predicted towards the end of the century from the current average annual precipitation of about 420 mm under RCP4.5 and RCP8.5, respectively. Similar to precipitation, the temperature will also be increased by 2.18 °C to 5.71 °C (in both the RCPs) than the current temperature values. The changed climate conditions in future are transformed into the possible range of stream flows using the SWAT model and found that the future climate would increase the streamflow by over 11%-19% at the end of the century under RCP4.5 and RCP8.5 scenarios, respectively. The outcome of this study can be used to develop the suitable strategies for sustainable water management in the region.

A simplified modelling framework for real-time assessment of conservative pollutants in ungauged rivers during cloudy periods

Recently, the optical remote sensing technique is effectively applied to monitor real-time water quality parameters at finer spatiotemporal scales that are mostly based on the surface reflectance of satellite images. However, during the rainy season due to cloudy or hazy satellite images, it is a great challenge to obtain the surface reflectances and to estimate the pollutant concentration. This study is specially focused on developing a novel approach to estimate the daily-scale pollutant concentrations in ungauged rivers during cloudy days. The developed approach integrates the simplified physically-based VPMM-AD(ΨD_c) solute transport model with the remote sensing (RS)-based approach for assessing the non-reactive river pollutants in real-time. This integrated VPMM-AD(ΨD_c)-RS approach is tested for simulating the in-situ heavy metal (Fe, Zn, Cu, Cr, Pb, and Cd) and total suspended solid (TSS) concentrations in the Brahmani River during the tropical monsoon (rainy) seasons of the typical years 2010-2013. The study results reveal that the proposed integrated approach performed reasonably well with acceptable accuracy for real-time estimation of pollutant concentrations in the considered ungauged river reach during the cloudy period.

Applicability of modified SWAT model (SWAT-Twn) on simulation of watershed sediment yields under different land use/cover scenarios in Taiwan

Climate change leads to increasing intensity and frequency of extreme rainfalls, especially in Taiwan with steep slopes and rapid currents. Heavy rainfalls trigger serious erosion and landslides on hillslopes, which increase sand concentration in rivers, and thus affect the water quality of reservoirs and the ecohydrological functions of rivers. We take the Zhuoshui River basin as an example and applied the modified Soil Water Assessment Tool (SWAT) model, SWAT-Twn, to simulate sediment in the basin. In SWAT-Twn, estimation of sediment yield is carried out by integrating the Taiwan Universal Soil Loss Equation (TUSLE) and the landslide simulation. Results of daily streamflow simulation showed that the model performances were above the satisfactory level, while simulations of daily sediment loads showed that the SWAT-Twn model performed better than the official SWAT (SWAT664), in terms of PBIAS of - 46.6 to 16.0% (SWAT-Twn) and - 1.2 to - 107.0% (SWAT664). Two scenarios of land use/cover, scenario 1 with fixed land use/cover and scenario 2 with updated land use/cover in each year, were applied to simulate annual sediment in the river basin for investigating the effects of landslide area variation on sediments. Results of sediment simulation under the two scenarios showed that although updating landslide area may facilitate sediment yield simulation at the subbasin level, the sediment transport equation, Bagnold equation, does not reflect the variation in sediment loads in the watershed. With further modifications, SWAT-Twn is expected to be an effective tool for simulating the impacts of landslide on sediment loads in the watersheds with rainfall-induced landslide.

Impacts of climate variations on non-stationarity of streamflow over Canada

With climate change, understanding and assessing the impact of climate variations on non-stationary changes of streamflow is of importance in the hydrologic and atmospheric sciences. In this study, tempo-spatial and scaling effects in the impacts of 18 climate variations on nonstationary streamflow for 279 watersheds across Canada are explored. Specifically, the change point and trends of streamflow are examined through Pettitt's test and Mann-Kendall test. Spatial patterns of correlations between the climate variations and flow rates over Canada, especially their non-stationarity, are investigated at seasonal and decadal scales. The patterns are also quantified by seven spatial classification algorithms under method uncertainty. A series of findings regarding the impacts are revealed. For instance, nonstationary changes of streamflow exist for approximately 9% of Canadian watersheds and most of them are located in Prairie Provinces and the eastern coast. The Atlantic Multidecadal Oscillation, Niño 12, Niño 3, Niño 4, and Niño 3.4 pose significant impacts on Canadian streamflow, which vary with watersheds and seasons. The impacts are closely associated with human activities, e.g., significant impacts of climate variations on populated-area streamflow over Canada. Different climatic variations have different time-varying effects on streamflow. All watersheds have obvious clustering characteristics and four spatial patterns are identified, which is insensitive with classification algorithm. These findings are conducive to understanding the hydrological impacts of atmospheric circulation and enhancing the reliability of hydrological prediction.

The prediction of longitudinal dispersion coefficient in natural streams using LS-SVM and ANFIS optimized by Harris hawk optimization algorithm

Accurate calculation of the longitudinal dispersion coefficient (K_x) of pollution is essential in modeling river pollution status. Various equations are presented to calculate the K_x using experimental, analytical, and mathematical methods. Although machine learning models are more reliable than experimental equations in the presence of uncertainties missing data, they have not been widely used in predicting K_x. In this study, the K_x of the river was predicted using machine learning methods, including least square-support vector machine (LS-SVM), adaptive neuro-fuzzy inference system (ANFIS), and ANFIS optimized by Harris hawk optimization (ANFIS-HHO), and the results were compared with that of the experimental methods. Several scenarios were designed by different combinations of input variables, such as the average depth of the flow (H), average flow velocity (U), and shear velocity (u_⁎). The results showed that machine learning models had a more efficient performance to predict K_x than experimental equations. The ANFIS-HHO, with a scenario containing all the input variables, performed better than the other two models, with root mean square error, mean absolute percentage error, and coefficient of determination of 17.0, 0.22, and 0.97, respectively. Furthermore, the HHO algorithm slightly increased the prediction performance of the ANFIS. The discrepancy ratio (DR) evaluation criteria showed that experimental equations overestimated the values of K_x, while the machine learning models resulted in higher precision. Also, the results of Taylor's diagram showed the acceptable performance of the ANFIS-HHO model compared to other models. Given the promising results of the present study, it is expected that the proposed approach can be efficiently used for similar environmental modeling problems.

Dataset of 18O and 2H in streamflow across Canada: A national resource for tracing water sources, water balance and predictive modelling

Oxygen-18 and deuterium were measured in streamflow samples collected from 331 gauging stations across Canada during 2013 to 2019. This dataset includes 9206 isotopic analyses made on 4603 individual water samples, and an additional 1259 analysis repeats for quality assurance/quality control. We also include arithmetic and flow-weighted averages, and other basic statistics for stations where adequate data were available. Station data are provided including station code, name, province, latitude, longitude and drainage area. Flow data were extracted from the historical database of the Water Survey of Canada. Details on the preliminary application of these data are provided in "18O and 2H in streamflow across Canada" [1]. Overall, these data are expected to be useful when combined with precipitation datasets and analytical or numerical models for water resource management and planning, including tracing streamflow source, water balance, evapotranspiration partitioning, residence time analysis, and early detection of climate and land use changes in Canada.

Co-designed Land-use Scenarios and their Implications for Storm Runoff and Streamflow in New England

Landscape and climate changes have the potential to create or exacerbate problems with stormwater management, high flows, and flooding. In New England, four plausible land-use scenarios were co-developed with stakeholders to give insight to the effects on ecosystem services of different trajectories of socio-economic connectedness and natural resource innovation. With respect to water, the service of greatest interest to New England stakeholders is the reduction of stormwater and flooding. To assess the effects of these land-use scenarios, we applied the Soil and Water Assessment Tool to two watersheds under two climates. Differences in land use had minimal effects on the water balance but did affect high flows and the contribution of storm runoff to streamflow. For most scenarios, the effect on high flows was small. For one scenario-envisioned to have global socio-economic connectedness and low levels of natural resource innovation-growth in impervious areas increased the annual maximum daily flow by 10%, similar to the 5-15% increase attributable to climate change. Under modest population growth, land-use decisions have little effect on storm runoff and high flows; however, for the two scenarios characterized by global socio-economic connectedness, differences in choices regarding land use and impervious area have a large impact on the potential for flooding. Results also indicate a potential interaction between climate and land use with a shift to more high flows resulting from heavy rains than from snowmelt. These results can help inform land use and development, especially when combined with assessments of effects on other ecosystem services.

Evaluation of the impacts of climate change on streamflow through hydrological simulation and under downscaling scenarios: case study in a watershed in southeastern Brazil

Among the problems related to water security, the effects of climate change on water availability stand out. Researchers have used hydrological models integrated with climate models in order to predict the streamflow behaviour in different hydrographic basins. This work aimed to analyse future climate scenarios for the Ribeirão do Lobo River Basin, located in the state of São Paulo, Brazil. The stochastic generator PGECLIMA_R was used in the simulation of climate data, which were used as input data in the hydrological model SMAP, after it was calibrated and validated for the study site. In all, five future scenarios were generated, with scenarios A, B, C and D projected based on the 5th report of the IPCC and scenario E based on the trend of climate data in the region. Among the scenarios generated, scenario D, which considers an increase of 4.8 °C in air temperature and a reduction of 10% in rainfall, is responsible for the worst water condition in the basin and can reduce up to 72.41% of the average flow and up to 55.50%, 54.18% and 38.17% of the low flow parameters Q90%, Q95% and Q7,10, respectively, until the end of the twenty-first century. However, the E scenario also becomes a matter of concern, since it was responsible for greater increases in temperature and greater reductions in rainfall and, consequently, more drastic monthly reductions in streamflow, which may negatively impact water resources and affect the various uses of water in the Ribeirão do Lobo River Basin.

Assessing the impacts of historical and future land use and climate change on the streamflow and sediment yield of a tropical mountainous river basin in South India

In this study, the impacts of land use/land cover (LULC) and climate change on the streamflow and sediment yield were investigated for the Payaswani River Basin, Western Ghats, India. The LULC was determined using Landsat images, and climate data were procured from five general circulation models for representative concentration pathway (RCP) 4.5 (moderate emission) and 8.5 (high emission). The land change modeler was used to derive the future LULC and its changes from 1988 (historical) to 2030 (future) by using the transition matrix method. The SWAT model was used to assess the impacts of LULC and climate change for the streamflow and sediment yield. The results showed that decrease in forests and grasslands and increase in plantation, agricultural, and urban areas from 1988 to 2030 would lead to an increase in the mean streamflow (11.23%) and sediment yield (17.41%). Under RCP 4.5, climate change would decrease the streamflow by 2.38% in 2030. However, under RCP 8.5, climate change would increase the streamflow by 0.12% in 2030. The sediment yield under RCP 4.5 and 8.5 would increase by 1.23% and 3.33%, respectively. In comparison with the baseline condition, by 2030 future changes in the LULC and climate would increase the streamflow by 7.05% and 11.71% under RCP 4.5 and 8.5, respectively. The sediment yield would increase by 7.92% and 27.11% under RCP 4.5 and 8.5, respectively. The streamflow and sediment yield were predicted to increase in the summer and winter but decrease in the monsoon season.

Recent advances in understanding and measurement of mercury in the environment: Terrestrial Hg cycling

This review documents recent advances in terrestrial mercury cycling. Terrestrial mercury (Hg) research has matured in some areas, and is developing rapidly in others. We summarize the state of the science circa 2010 as a starting point, and then present the advances during the last decade in three areas: land use, sulfate deposition, and climate change. The advances are presented in the framework of three Hg "gateways" to the terrestrial environment: inputs from the atmosphere, uptake in food, and runoff with surface water. Among the most notable advances: These and other advances reported here are of value in evaluating the effectiveness of the Minamata Convention on reducing environmental Hg exposure to humans and wildlife.

Effects of active and passive land use management after cropland abandonment on water and vegetation dynamics in the Central Spanish Pyrenees

The Mediterranean mountains have been subject to significant land abandonment process during the second half of the 20th century. The subsequent natural revegetation following abandonment in rural areas has been widely documented to have substantial implications on the hydrological cycle and the vegetation. The Spanish Pyrenees are one of the most affected areas by these land transformations which could threaten their importance for water supply and agricultural activities in the downstream lowland areas. Land managers as well as scientists around the world have taken different positions on how to deal with these land use changes. Some are in favor of active management (AM) (i.e. density reduction) while others are supporting passive management (PM) (letting the process of revegetation continue). This study aims to investigate the implication of AM and PM on hydrological and vegetation dynamics under different climate trajectories in a representative abandoned cropland catchment in the Central Spanish Pyrenees. A coupled ecohydrologic model is used to estimate the post management response of streamflow (STR), evapotranspiration (ET), soil saturation deficit (SD) and plant carbon (PC) following shrub clearing. Clearing increased annual STR by 16%, while ET and SD decreased by around -9% and -6% respectively during the first year after management with changes to monthly flows. These changes to water regimes may be even higher in wetter years. Over a 10-years period of vegetation recovery annual STR increased between 7.1% and 24.2%, while annual ET and SD decreased between -2.6% to -8.7% and -2.7% to -6% respectively due to shrub clearing, with the highest changes occurring in the first three years of AM. On the effect of climate change, our results show that a 2 °C increase in temperature could reduce AM effects on water regimes and accelerate the recovery of PC given averaged rainfall conditions.

Assessment of the impact of climate change and mining activities on streamflow and selected metal's loading in the Chindwin River, Myanmar

The rapid expansion in mining activities is deteriorating the water quality in the Chindwin River of Myanmar. In addition, climate change may also aggravate this situation in future. Therefore, the aim of this study was to establish a connection between hydrology, mining area, heavy metal loading, and climate change in the Chindwin River. The hydrology of the upper Chindwin basin was modelled using SHETRAN hydrological model. Geochemical model PHREEQC was utilised to conduct speciation and saturation indexes modelling along the river in order to quantify the precipitated minerals along the river. Thereafter a regression relationship along with LOADEST model was used to quantify the heavy metal loads. Future climate was projected using four RCM's namely ACCESS1-CSIRO-CCAM, CCSM4-CSIRO-CCAM, CNRM-CM5-CSIRO-CCAM and MPI-ESM-LR-CSIRO-CCAM. Future discharges at water quality monitoring stations were simulated using the averaged ensembles. Finally, the heavy metal loading under future climate scenarios were analysed. Results indicate that climate change is likely to reduce future discharges by 3.4%-36.5% in all stations except in the Mokekalae station which shows 1.3%-9.4% increase in the near future discharges. Also, the projected metal loading under future climate conditions shows a decreasing pattern which is similar to the projected discharge pattern. In both baseline and future climate conditions, the area between stations Naung Po Aung and Uru downstream show the highest load effluent for both arsenic and mercury while the area between stations Uru downstream and Mokekalae show the highest load of iron effluent. Although future heavy metal loadings are expected to decrease, mining activities should be carefully monitored, since they discharge a large amount of toxic heavy metal loadings into the Chindwin River which is also expected to suffer a decrease streamflow in future.

Ensemble streamflow projections for a small watershed with HSPF model

A watershed modeling tool, Hydrological Simulation Program-FORTRAN (HSPF), was utilized to model the hydrological processes in the agricultural Sarısu watershed in western Turkey. The meteorological input data were statistically downscaled time series from General Circulation Model simulations. The input data were constructed as an ensemble of 400 individual time series of temperature, precipitation, dewpoint temperature, solar radiation, potential evapotranspiration, cloudiness, and wind velocity, as required by HSPF. The ensemble was divided into four subsets, each comprising of 100 time series, of different Special Report on Emissions Scenarios. Yearly and monthly total streamflow time series were obtained from the calibrated and validated HSPF model spanning a period of 116 years between the water years of 1984 and 2099. The projections in the watershed showed a median increase of 3 °C in yearly average temperatures between the beginning and end 30-year periods of the 116-year simulation periods based on 400 ensemble members while the corresponding change in total yearly precipitation was - 71 mm. These changes led to a decrease in yearly streamflows by 40% which reflected itself to varying degrees in monthly flows. Correlations were established between the principal drivers of the watershed hydrological cycle, namely temperature and precipitation, and streamflow. The results showed that the changes in the climatic conditions will greatly affect water-related issues in the watershed and emphasize the necessity of preparing carefully to adapt to a warmer and drier climate.

Climate change will pose challenges to water quality management in the st. Croix River basin

Responses of streamflow and nutrient export to changing climate conditions should be investigated for effective water quality management and pollution control. Using downscaled climate projections and the Soil and Water Assessment Tool (SWAT), we projected future streamflow, sediment export, and riverine nutrient export in the St. Croix River Basin (SCRB) during 2020-2099. Results show substantial increases in riverine water, sediment, and nutrient load under future climate conditions, particularly under the high greenhouse gas emission scenario. Intensified water cycling and enhanced nutrient export will pose challenges to water quality management and affect multiple Best Management Practices (BMPs) efforts, which are aimed at reducing nutrient loads in SCRB. In addition to the physical impacts of climate change on terrestrial hydrology, our analyses demonstrate significant reductions in ET under elevated atmospheric CO₂ concentrations. Changes in plant physiology induced by climate change may markedly affect water cycling and associated sediment and nutrient export. Results of this study highlight the importance of examining climate change impacts on water and nutrient delivery for effective watershed management.

Assessment of freshwater discharge into a coastal bay through multi-basin ensemble hydrological modelling

Coastal basins of the Brittany peninsula (France) are hydrological hot spots. A high level of nutrient pollution affects many of these basins and causes algal blooms in several coastal bays; nine have been a specific focus of the European Commission since 2007. The flux of each contributing basin flowing into these bays must be examined to assess the conditions and explore mitigation options. However, this task encounters a large lack of data since most of the basins are ungauged. In this context, this study developed a method which facilitates transposition of hydrographs from gauged basins to ungauged neighbouring basins of interest. Inverting a simple geomorphology-based transfer function of the gauged basin which describes travel time through channels enables the net rainfall time-series to be estimated from the discharge time-series of donor basins. To estimate the net rainfall of a given ungauged catchment, several net rainfall time series of gauged catchments are averaged. The resulting net rainfall is then transposed onto the ungauged target basin and convoluted by its own transfer function to estimate the hydrograph. This allows the transposition of as many hydrographs as there are different donor basins. This ensemble prediction enables the proportion of prediction uncertainty that is due to the heterogeneity in hydrological behaviour to be estimated. Moreover, the time-series of the donor basins are combined to estimate the ungauged net rainfall time-series. This provides a discharge prediction which values all available measurements. The method was applied to the highly controversial Saint Brieuc Bay, where it was possible to quantify the contribution of each coastal basin, even those influenced by dams, and ultimately the entire volume of fresh water entering the bay at an hourly time step. This work opens perspectives to additionally refine estimation of the associated nutrient fluxes.