Scale Hydrology Research Articles

LID Implementation in an urban basin: a Brazilian case study

Problems related to urban drainage systems and the disorderly growth of large urban centers have led to the search for alternative drainage techniques. These techniques have been called Low Impact Development (LID), and generally influence the reduction of peak flow and runoff volume. In an urban sub-basin in the city of Recife, PE, the hypothesis of replacing existing roofs with a green roof (GR) was considered in three scenarios: (1) pre-urbanized, (2) current, (3.1) 30% of GR, (3.2) 50% of GR, (3.3) 75% of GR, (3.4) 100% of T.V. For this, simulations were carried out in PCSWMM based on the current urbanization situation. Linimetric readings were taken for calibration, obtaining 0.61 NSE and 0.903 R². Validation was carried out using images at two points within the basin. The reduction in peak flow values ranged from 0.74 to 2.10 m³/s, in addition to the time being delayed from 31 to 90 minutes. As for river level values, the variation was between 4 and 13 cm, while volume reductions recorded values between 67.42 and 190.81 m³. Overall, this proposed methodology can help stormwater managers better evaluate the performance of LID techniques at different hydrological scales, showing the importance of prioritizing urban adaptation and green infrastructure implementation.

Hydrometeorological controls of and social response to the 22 October 2019 catastrophic flash flood in Catalonia, north-eastern Spain

Abstract. On 22 October 2019, the Francolí River basin in Catalonia, north-eastern Spain, experienced a heavy precipitation event that resulted in a catastrophic flash flood, causing six fatalities. Few studies comprehensively address both the physical and human dimensions and their interrelations during extreme flash flooding. This research takes a step forward towards filling this gap in knowledge by examining the alignment among all these factors. The hydrometeorological factors are investigated using the new Triangle-based Regional Atmospheric Model, radar-derived precipitation estimates, post-flood field and gauge observations, and the Kinematic Local Excess Model. The social dimension is assessed by examining the relationship between catchment dynamics and warning response times and by quantifying human behaviour during the course of the flash flood through a post-event citizen science campaign. Results reveal that a persistent south-easterly airflow brought low-level moisture and established convective instability in the region, while local orography was instrumental to triggering deep moist convection. A convective train promoted intense, copious, and prolonged precipitation over the north-western catchment headwaters. Basin response was significantly modulated by the very dry initial soil moisture conditions. After the long-lasting rainfall, an acute burst of precipitation resulted in extreme flash flooding. Fast and abrupt increases in streamflow affect small spatial scales and leave limited time for the effective implementation of protective measures. The institutional organization–protection–prevention cycle unfolded at the spatial and temporal scales typically dominated by the meteorological rather than hydrological scales. Although the citizen science campaign reveals the effectiveness of the warnings in reaching the population living in the most affected areas, a significant proportion of the respondents expressed a lack of adequate information or were unfamiliar with the intended meaning. In addition, a majority of the interviewees did not perceive any significant threat to life or property. In view of these results, this study identifies potential areas for improving social preparedness for similar natural hazards in the future.

An Isotope Mass Balance Analysis of Evaporative Loss From Lake Turkana, Kenya Using δ18O and δD of Natural Waters

AbstractMeasurements of oxygen and hydrogen stable isotope ratios (δ18O and δD) in meteoric waters provide insight to overlapping effects of evaporation, precipitation, and mixing on basin scale hydrology. This study of waters collected between 2016 and 2021 in the Turkana Basin, northern Kenya, uses δ18O and δD to understand water balance in Lake Turkana, a large, low‐latitude, alkaline desert lake. The Omo River, a major river system in the Ethiopian Highlands, is historically understood to provide approximately 90% of the water input to Lake Turkana. Discharge of the Omo is prohibitively difficult to measure, but stable isotope ratios in the lake may provide a meaningful method for monitoring the lake's response to changes in input. Precipitation in the Turkana Basin is low (<200 mm/year) with negligible rainfall on the lake's surface, and all water loss from the lake is evaporative. We compare new measurements with previous data from the region and records of lake height and precipitation from the same time period. We show that a Bayesian approach to modeling evaporation using atmospheric conditions and river δ18O and δD yields results consistent with published water balance models. Continued sampling of lake and meteoric waters in the Turkana Basin will be a useful way to monitor the lake's response to regional and global climate change.

Climate change effects on rainfall extreme value distribution: the role of skewness

Quantifying the potential effects of Climate Change (CC) on hydrological scales is a topic with a more and more increasing interest for the scientific community, given the CC impact on agriculture, industry, economy, human health, ecosystems, among the others. In this context, the paper focuses on the sub-daily Annual Maxima (AM) of rainfall height time series, and specifically on the crucial role played by initial skewness, i.e. the skewness of the observed rainfall series used to evaluate potential parametric trends. Here a quick and user-friendly methodology is proposed, that is aimed at quantifying plausible future changes in terms of probability distributions assumed at rain gauge scale, from projections of any climatic model. In detail, the Generalized Extreme Value (GEV) and the Two-Component Extreme Value (TCEV) distributions are adopted as probability functions suitable for modelling observed rainfall AM series, which could increase their frequency and magnitude into future horizons under CC. EURO-CORDEX projections for Europe are considered, under the hypothesis that the values of the change factor, i.e. the ratio between the values of a specific quantile at two specific time horizons, are invariant when moving from an areally-averaged scale (typical for any climate model) to a point rain gauge scale, which induces that future changes are provided (in terms of frequency and magnitude of extreme events) without the need of any spatial downscaling from the assumed projections. The proposed methodology can contribute to hazard quantification associated to potential climate changes, and thus it can play a crucial role in the assessment of hydraulic structures resilience; the obtained results, specific for the study area of Italy, but easily extendable on a global scale, showed that larger increases in frequency of future heavy events are expected for time series with “EV1 alike” values of initial skewness.

Machine learning assessment of hydrological model performance under localized water storage changes through downscaling

The coarse spatial resolution of the Gravity Recovery and Climate Experiment (GRACE) data has limited its application in the management of local-scale water resources. To address this limitation, we developed a new downscaling approach using predictors from regional and global hydrological models for a 15-year period (2002–2017) and tested it in the northern Great Artesian Basin, Australia. We used four different machine learning algorithms (support vector machine, partial least squares, gaussian process and random forest) to downscale the original GRACE estimate of 0.5° to a spatial grain size of 0.1° (global) and 0.05° (regional). This was based on precipitation, evapotranspiration and runoff estimates from the Famine Early Warning Systems Network Land Data Assimilation System (FLDAS) and Australian Water Outlook (AWO) hydrological models, respectively. The downscaled products were validated using 42 in-situ precipitation observations spread across the test region. We further evaluated which of the downscaled products best mimicked local-scale hydrology using a range of statistical metrics. Our results showed that regional hydrological models best characterized the dynamics of local scale hydrology (rainfall v. downscaled product), and the gaussian process regression algorithm made the best predictions for both models. The correlation coefficients for the raw values varied from 0.45 to 0.49 while that of the standardized values varied from 0.46 to 0.52 with the random forest model providing the best fitting for the regional-based products. The regional downscaling approach employed in this study may be readily integrated into local water resources planning programs.

Hydrobiogeochemical Controls on the Delivery of Dissolved Organic Matter to Boreal Headwater Streams

AbstractUnderstanding controls on the delivery of dissolved organic matter (DOM) from terrestrial to aquatic systems is key for constraining carbon balances and fluxes in boreal headwater catchments. The largest export of DOM generally occurs during intense periods of water delivery to the landscape (e.g., rain events); however, the timing and magnitude of DOM is complicated by geomorphological, hydrometeorological, and biogeochemical variability. To better assess mechanisms controlling the delivery of DOM to boreal streams, DOM was investigated in two morphologically distinct catchments of an experimental forest watershed in western Newfoundland, one dominated by low relief wetlands and the other by steep hillslopes. The DOM was compared during two fall storms of similar magnitude but contrasting moisture conditions during the autumn transition. Variable concentrations and optical character highlighted antecedent conditions are important for the delivery of DOM to boreal streams. Concentration‐discharge relationships with stream hydrograph separation analysis suggest preferential flowpaths through shallow mineral horizons as a key pathway for delivery of DOM in the hillslope dominated catchment compared to rapid input from near‐stream wetlands in the low relief catchment. Loss of DOM via preferential pathways suggests an additional mechanism for surface soil carbon loss not directly informed by lateral flow and soil hydrology, which has important implications for our conceptualization and modeling of carbon fluxes in boreal systems. These results suggest watershed scale responses of DOM in boreal headwater catchments are complex, and better linkages between catchment scale hydrology and landscape hydrobiogeochemistry are required to constrain terrestrial to aquatic carbon fluxes in boreal landscapes.

A practical evaluation of micro-hydrokinetic power potential for the Continental United States

Study regionContinental United States (CONUS) Study focusMicro-hydrokinetic turbines are hydropower turbines that can utilize the current of the river to generate power without constructing a dam. Recent advances in micro-hydrokinetic turbine technology have made their use an attractive alternative to traditional hydropower systems that require the construction of a dam. In this paper, we introduce a novel and practical analysis of continental to global scale hydrology and hydraulics that we use to assess continental United States (CONUS) stream locations with optimum hydraulic characteristics for an example micro-hydrokinetic turbine (Volturnus). We then utilize the boundaries of CONUS military installations to determine installations possessing the greatest potential to utilize the Volturnus. New hydrological insights for the regionFor the Volturnus, our results indicate that although less than 1% of CONUS stream locations possess the hydraulic characteristics necessary for the Volturnus to function optimally, this translates into roughly 224–544 million kWh per week, considerably less than previous estimates of CONUS theoretical and recoverable power but substantial, nonetheless. Around 26–40 CONUS military installations possess streams that are sometimes capable of producing hydropower with the Volturnus and 12–20 of those military installations possess optimum hydraulic conditions for the Volturnus year round. In our analysis, reducing either the minimum velocity or minimum depth threshold of the Volturnus nearly double the proportion of CONUS locations with optimum Volturnus hydraulic characteristics.

X-band polarimetric radar QPE for urban hydrology: The increased contribution of high-resolution rainfall capturing

Increased population is exposed to urban flooding as a result of climate change. Flood early warning can largely reduce the loss of life and asset, while how detailed rainfall information is enough has always been a critical issue in achieving robust flood forecasting. Previous analysis has been limited by lacking high-resolution rainfall observation or a spatially-matched urban hydrological model. This study couples mature modeling technologies with comprehensive hydro-meteorological measurement, that is comprised of X-band polarimetric radar (75 m, 3 min), weather stations, and hydrometric stations, and this study further attempts to understand the rainfall spatial resolution effects and critical resolutions from a multi-scale perspective (e.g. block, district, and catchment scales). The results show that coarser resolutions always lead to underestimation of peak flows, even exceeding 40 % in the case of adopting 10 km rainfall data at the block scale. But such damping effects on discharge simulation can be largely attenuated with increased hydrological scale. In general, spatial resolutions of higher than 500 m, and 10 km are needed to obtain accurate simulation results (i.e. keep the relative bias within 20 %) at district and catchment scales, while at least 300 m for the block scale. In conclusion, refined rainfall forcing contributes to better simulation of peak flows in urban hydrological modeling, but the required rainfall spatial resolution changes with the scale of hydrological application. These findings help to better achieve the balance between rainfall observation cost and flood simulation accuracy.

The Performance of Natural Flood Management at the Large Catchment-Scale: A Case Study in the Warwickshire Stour Valley

The limited understanding of Natural Flood Management (NFM) performance, especially at large hydrological scales, is considered a critical barrier for the further funding and implementation of these nature-based solutions to the increasing international problem of flooding. The publications of the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report and Environment Agency’s National Flood and Coastal Erosion Risk Management Strategy (NFCERMS) for England have shown that extreme weather, including increased likelihood of high magnitude flood events, will occur and will require more novel management methods. This study focused on the ability of co-designed NFM measures to ameliorate downstream fluvial flooding by attenuating catchment response through a highly spatially distributed network of attenuating and roughening measures. Performance was characterised by the ability of NFM to attenuate flood peaks at different spatial scales across a large (187 km2) dendritic catchment, including the lowering of flood peaks and delaying the time-to-peak. Using a coupled modelling methodology and applying it to the upper Stour Valley, Warwickshire-Avon, UK, a rural response to the application of a set of NFM interventions was developed using the hydrodynamic model Flood Modeller Pro and XPSWMM ©. The method demonstrated a means of incorporating local knowledge in a realistic set of NFM schemes, tested to multiple flood risk scenarios (including climate change). Under frequent, smaller design storm events (e.g., Index Flood (QMED) and 3.3% AEP), flood peaks were lowered across all hydrological scales tested (5.8 km2 to 187 km2). As the design flood event severity increases, impact from upstream NFM attenuation on downstream peak response diminished significantly, especially at the largest hydrological scales. However, even at the largest hydrological scale, delays in time-to-peak were noted, increasing the ability of downstream communities to respond and enact flood preparation activities, thus increasing resilience to potential flooding events. While the benefits were limited to large flood events, the modelling indicated that NFM has the potential to reduce downstream flood risk. However, greater integration of observed data to improve model confidence and reduce uncertainty in modelled events is needed, especially the uncertainty associated with using single peaked design storm events from the Flood Estimation Handbook (FEH). This paper proposes a future Before–After Control–Impact (BACI) monitoring programme that could be integrated with models and applied across non-tidally influenced catchments seeking to empirically test the hydrological performance of in-situ NFM.

Modeling water and nitrogen dynamics from processing tomatoes under different management scenarios in the San Joaquin Valley of California

Study regionThe Southern San Joaquin Valley (SSJV), California. Four representative soil types were evaluated. Study focusEvaluation of regional scale hydrology and nitrogen (N) fate and transport requires a robust modeling framework that considers critical local scale environmental conditions and crop root zone physical processes. Two widely used yet conceptually and mechanistically different models, HYDRUS(2D/3D) and SWAT (Soil and Water Assessment Tool), were used to investigate water and N dynamics in processing tomato fields across a range of soil types and management scenarios over a 30-year period in the SSJV. New hydrological insights for the regionThis study implements a framework to evaluate a regional scale model against a field scale model and provides a framework for assessing percolation and N transport results from regional scale simulations in the absence of extensive field observations. Field scale models developed in HYDRUS (2D/3D) produced similar results to a regional-scale SWAT model in four specific soils in terms of responses to percolation and N losses as a function of varying N fertilizer and irrigation management practices. This model-to-model agreement at the local scale provides confidence in region-scale hydrological and N fate and transport findings, particularly in the absence of extensive field observations. Both models suggest that promoting conservation practices targeting the optimization of irrigation and fertilizer-N management would have a large impact in protecting regional groundwater quality.

Evaluating SWOT water level information using a large scale hydrology simulator: A case study over India

An important goal of the Surface Water and Ocean Topography (SWOT) mission is to provide river width, height, slope to estimate global river discharges. To appraise the feasibility of SWOT data over India, the present study utilizes the SWOT simulator from Centre National D’Etudes Spatiales (CNES) to generate a long time-series (three years) of SWOT observations over the Mahanadi River basin in India. Two independent sources of river geometry are used in this study, namely satellite-based and hydrodynamic model-based estimates. Satellite-based river geometry is derived using a web-based User Interface (UI) developed in-house to generate time series of accurate river width shapefiles from Sentinel-1 satellite imagery. To compare these results, a 1D unsteady flow analysis is carried out over the Mahanadi River to simulate channel water depth and inundation extent using the Hydrologic Engineering Center's River Analysis System (HEC-RAS) model. The simulated observations are used in this study to assess the potential error in SWOT channel water depth measurements. Results indicate a good spatial correlation between the water surface area derived from Sentinel and HEC-RAS models with a correlation of 0.74. The simulated data shows a bias of 20 cm compared to gauge observations. This study is conducted as a proof of concept in demonstrating the ability of simulated SWOT data in capturing river water surface elevation with respect to the conventional HEC-RAS model. It also implements a new tool in google earth engine (GEE) to generate input to SWOT simulator.

Modeling Water Quantity and Quality Nonlinearities for Watershed Adaptability to Hydroclimate Extremes in Agricultural Landscapes

Changing water supplies and demands, inherent to climate fluctuations and human activities, are pushing for a paradigm shift in water management worldwide. The occurrence of extreme hydrometeorological and climate events such as extended wet periods and droughts, compounded with contaminants, impair the access to water resources, demanding novel designs, construction, and management across multiple hydrologic scales and biogeochemical processes. A constraint to studying hydrologic and biogeochemical disturbances and improving best management practices for water quantity and quality at the watershed scale resides in the suitable monitoring, data availability, and the creation of frameworks. We hypothesize that streamflow and contaminants, simulated by the hydrologic model Soil and Water Assessment Tool (SWAT) and evaluated during drought and extended wet periods, capture the nonlinearities of contaminants of multiple biogeochemical complexities, indicating the adaptive abilities of watersheds. Our objectives are to (1) use rain gauge and radar data and linear regression to consolidate long-term precipitation data to simulate streamflow and water quality using the SWAT model in the Shell Creek (SC) watershed, Nebraska, U.S.; (2) use drought and extended wet events analytics on observed and simulated hydroclimate and water quality variables to identify SWAT’s performance; and (3) identify the temporal attributions of streamflow and water quality to complex biogeochemical patterns of variability. We implement a watershed modeling approach using the SWAT model forced with rain gauge and radar to simulate the intraseasonal and interannual variability streamflow, sediments, nutrients, and atrazine loads in the SC watershed. SWAT performance uses a calibration period between 2000 and 2005 and a validation period between 2005 and 2007. We examine the model’s ability to simulate hydrologic and biogeochemical variables in response to dry and extended wet flow regimes. The hydrologic model forced by either radar or rain gages performs similarly in the calibration (NSE = 0.6) and validation (NSE = 0.92) periods. It reproduces medium flows closer to the observations, although it overestimates low–flows up to 0.1 m3/s while underestimates high flows by 1 m3/s. The water quality model shows higher NSE for streamflow and sediments followed by nutrients, whereas it poorly reproduces atrazine. We conclude that seasonal changes and hydroclimate conditions led to the emergence of patterns of variability associated to the nonlinearities and coupling between processes of natural and human-origin sources. As climate change propels the occurrence of hydroclimate extremes, the simulation of water quantity and quality nonlinearities—as properties of complex adaptive hydrologic systems—can contribute to improve the predictability of climate-resilient water resources.

Multi-scale flow structure of a strike-slip tectonic setting: A self-similar model for the Liquiñe-Ofqui Fault System and the Andean Transverse Faults, Southern Andes (39–40°S)

The flow structure of a brittle crustal volume is defined by the multi-scale geometric and hydraulic properties of its fracture meshes. The length density distribution n(L,l) and the transmissivity distribution K(L,l) control the hydrologic scaling, where l is fracture length and L is the system size. The flow structure might display at most three key hydrologic scales: the connection scale, above which flow is focused in few critical paths; the channeling scale, above which flow is distributed in several paths; and the homogenization scale, above which permeability approaches a constant value. According to these scales, the hydrological structure could be distributed or clustered, thus having a clear impact in geothermal exploration campaigns and reservoir modeling. In this work, we determine the multi-scale flow structure for the Liquiñe-Ofqui Fault System (LOFS) and the Andean Transverse Faults (ATF) in the Southern Andes, by establishing the hydrologic scaling they follow. Using fractal statistics, we integrated geological data at the regional, meso‑ and micro-scale, including image analysis from X-ray microtomography. Our results suggest a self-similar, dense network with n(L,l)∼l−a and a = 2.6–2.9, from the regional scale where the LOFS and ATF interact to the meso‑ and micro-scale within highly fractured areas of the LOFS. Scaling models are constrained by the length distribution, and other power-law functions reflecting the geometric arrangement of fractures, as well as the spatial distribution of superficial geothermal occurrences. Thus, we expect the hydrologic scaling to depend on the transmissivity distribution. Lognormal transmissivity distribution yields a permeability increase with scale, from the connection to the homogenization scales; whereas power-law transmissivity distribution yields a permeability increase from the connection scale without a limiting value. Approximations of the connection scale are around 10−3–100 m; the channeling scale, around 100–104 m; and if the homogenization scale exists, it should be equal or greater than 103–104 m. Finally, the results presented here could to define the internal architecture of fracture meshes in fault-controlled fluid flow, and be used to select an appropriate hydrologic model according to the analyzed scale. Therefore, these findings must be taken into consideration in future geothermal prospecting, modeling and exploitation.

SOL40: Forty Years of Simulations under Climate and Land Use Change

Nowadays, a major issue is land-use change by urban development that alters the catchment response to meteorological events. Urban basins have less storage capacity and more rapid runoff, so urban rivers rise more quickly during storms and have higher peak discharge rates than rural catchments. An exemplary case of this situation is the city of Milan (northern Italy) and its whole territory that extends towards the north collecting meteoric precipitation through the Seveso, Olona and Lambro (SOL) rivers. To assess the impact of anthropogenic development on urban catchment scale hydrology, a reanalysis of 40 years of simulations was carried out with the Curve Number (CN) map based on current land use and compared to simulations using the CN maps based on past land use. A coupled hydro-meteorological system was built that combined a physically based rainfall-runoff hydrological model FEST-WB, developed by the Politecnico di Milano, with the ERA5-Land hourly dataset for the period 1981 to 2020, that was provided by the ECMWF under the framework of the Copernicus Climate Change Service Programme. The study (named SOL40) analyses 40 year trends in the main meteorological (air temperature, precipitation) and hydrological variables (runoff) over the SOL area and tried to quantify and separate the impact of land use change from that of climate change.

The edge of the petri dish for a nation: Water resources carrying capacity assessment for Iran

Different methods have been proposed in population dynamics to estimate carrying capacity (K). This study estimates K for Iran, using three novel methods by integrating land and water limits into assessments based on Human Appropriated Net Primary Production (HANPP). The first method uses land suitability as the limiting resource. It gives theoretical estimates for K. The second method which is based on the first method, uses land suitability and water resources availability as limiting resources assuming highly efficient agriculture, also resulting in theoretical estimates for K. The third method is based on the second method assuming a lower, more realistic agricultural efficiency. The third therefore results in more realistic estimates. Four spatial hydrological scale levels were considered to estimate food production. Also, nine scenarios were defined: a reference one reflecting the current situation, five others for the first method, two for the second method, and finally, one scenario for the third method. Results show severe limitations on food production by the availability of suitable land, water availability, and crop productivity for agriculture. We estimated theoretical values for K using land and water limiting resources separately. Two realistic scenarios considering realistic agricultural productivity and water use at national and local levels were assessed, resulting in 35.5 and 20 million people, respectively. These are alarming values compared to the current population of Iran (84 million). Moreover, our conservative estimations are still higher than any assessment when considering social, economic, or political barriers. This research provides a systematic analysis of carrying capacity in Iran, showing the importance of food import on Iranians' lives, relevant to land, water, and food policies.

Are drought indices and climate data good indicators of ecologically relevant soil moisture dynamics in drylands?

Droughts are disproportionately impacting global dryland regions where ecosystem health and function are tightly coupled to moisture availability. Drought severity is commonly estimated using algorithms such as the standardized precipitation-evapotranspiration index (SPEI), which can estimate climatic water balance impacts at various hydrologic scales by varying computational length. However, the performance of these metrics as indicators of soil moisture dynamics at ecologically relevant scales, across soil depths, and in consideration of broader scale ecohydrological processes, requires more attention. In this study, we tested components of climatic water balance, including SPEI and SPEI computation lengths, to recreate multi-decadal and periodic soil-moisture patterns across soil profiles at 866 sites in the western United States. Modeling results show that SPEI calculated over the prior 12-months was the most predictive computation length and could recreate changes in moisture availability within the soil profile over longer periods of time and for annual recharge of deeper soil moisture stores. SPEI was slightly less successful with recreating spring surface-soil moisture availability, which is key to dryland ecosystems dominated by winter precipitation. Meteorological drought indices like SPEI are intended to be convenient and generalized indicators of meteorological water deficit. However, the inconsistent ability of SPEI to recreate ecologically relevant patterns of soil moisture at regional scales suggests that process-based models, and the larger data requirements they involve, remain an important tool for dryland ecohydrology

Protection of drinking water resources from agricultural pressures: Effectiveness of EU regulations in the context of local realities

Over the last decades, nutrients and pesticides have proved to be a major source of the pollution of drinking water resources in Europe. Extensive legislation has been developed by the EU to protect drinking water resources from agricultural pollution, but the achievement of water quality objectives is still an ongoing challenge throughout Europe.The study aims to identify lessons that can be learnt about the coherence and consistency of the application of EU regulations, and their effects at the local level, using qualitative expert data for 13 local to regional governance arrangements in 11 different European countries.The results show that the complexities and inconsistencies of European legislation drawn up to protect drinking water resources from agricultural pollution come forward most explicitly at local level where cross-sectoral measures have to be taken and effects monitored. At this local level, rather than facilitate, they hamper efforts to achieve water quality objectives. The upcoming revision of the Water Framework Directive (WFD) should strengthen the links between the different directives and how they could be applied at local level.In addition, a more facilitated cross-sectoral approach should be adopted to improve stakeholder networks, between institutional levels and hydrological scales, to attain policy objectives at local level.

Simulating internal watershed processes using multiple SWAT models

The need for effective water quality models to help guide management and policy, and extend monitoring information, is at the forefront of recent discussions related to watershed management. These models are often calibrated and validated at the basin outlet, which ensures that models are capable of evaluating basin scale hydrology and water quality. However, there is a need to understand where these models succeed or fail with respect to internal process representation, as these watershed-scale models are used to inform management practices and mitigation strategies upstream. We evaluated an ensemble of models—each calibrated to in-stream observations at the basin outlet—against discharge and nutrient observations at the farm field scale to determine the extent to which these models capture field-scale dynamics. While all models performed well at the watershed outlet, upstream performance varied. Models tended to over-predict discharge through surface runoff and subsurface drainage, while under-predicting phosphorus loading through subsurface drainage and nitrogen loading through surface runoff. Our study suggests that while models may be applied to predict impacts of management at the basin scale, care should be taken in applying the models to evaluate field-scale management and processes in the absence of data that can be incorporated at that scale, even with the use of multiple models.

A Transient Stochastic Rainfall Generator for Climate Changes Analysis at Hydrological Scales in Central Italy

In this work, a comprehensive methodology for trend investigation in rainfall time series, in a climate-change context, is proposed. The crucial role played by a Stochastic Rainfall Generator (SRG) is highlighted. Indeed, SRG application is particularly suitable to obtain rainfall series that are representative of future rainfall series at hydrological scales. Moreover, the methodology investigates the climate change effects on several timescales, considering the well-known Mann–Kendall test and analyzing the variation of probability distributions of extremes and hazard. The hypothesis is that the effects of climate changes could be more evident only for specific time resolutions, and only for some considered aspects. Applications regarded the rainfall time series of the Viterbo rain gauge in Central Italy.

A combined mixing model for high-frequency concentration–discharge relationships

Streamflow is the major factor influencing the evolution of solute concentration in river water and different modelling approaches exist to characterize the dependency of ion concentration to discharge: the simplest are based on measurable quantities (stream discharge and stream ion concentration) but do not allow for an explicit, physical, flow-path interpretation; the more complex are based on mixing assumptions with different end-members sources, but require the knowledge of (unmeasurable) flow components. We present here a new concentration–discharge model, which associates a classical concentration–discharge relationship with a classical two-component mixing equation. The originality of our approach lies in the fact that we do not proceed in the usual way to perform the hydrograph separation: we use an a priori assumption of the baseflow-quickflow separation to infer the source concentration values, contrarily to the usual (inverse) approach. The other notable originality is that all the parameters of this model depend on the temporal variation of the stream discharge. This combined model was tested on high-frequency ion concentration series from the ORACLE-Orgeval observatory (France). This work demonstrates that high temporal resolution data allows for explicit testing of model performance across different hydrologic scales. Results show that the combined mixing model allows a better estimation of streamflow solute concentration series for most ions tested at inter-annual scale, except for nitrate (which do not exhibit a clear C-Q relationship). Our results also confirm the advantage of coupling a time dynamic hydrological model with static C-Q relations for each of the flow components.