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Web-based distributed volunteer computing enables scientists to constitute platforms that can be used for computational tasks by using potentially millions of computers connected to the internet. It is a widely used approach for many scientific projects, including the analysis of radio signals for signs of extraterrestrial intelligence and determining the mechanisms of protein folding. User adoption and clients' dependence on the desktop software present challenges in volunteer computing projects. This study presents a web-based volunteer computing framework for hydrological applications that requires only a web browser to participate in distributed computing projects. The framework provides distribution and scaling capabilities for projects with user bases of thousands of volunteers. As a case study, we tested and evaluated the proposed framework with a large-scale hydrological flood forecasting model.

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Different means of hydrological data collection have developed and used. However, they are constraint in one way or other. This paper therefore revisited the rainfall simulator as potential tool for hydrological research. The research disclosed that there are three different types of rainfall simulators; drop former simulator, pressure nozzle simulator and hybrid simulator. It can further be classified as indoor model and outdoor. The research also showed that precipitation is the driving force in hydrological studies. Consequently, in the design of rainfall simulator, the following should be taken into consideration: nozzle spacing, pump size, nozzle size, nozzle type, nozzle spacing, plot size and pressure. Meanwhile, intensity, distribution uniformity, kinetic energy, rainfall drop size and rainfall terminal velocity should be noted in its evaluation. Factoring-in the aforementioned design considerations, data collection is made easy without necessarily waiting for the natural rainfall. Since the rainfall can be controlled, the erratic and unpredictable changeability of natural rainfall is eliminated. Emanating from the findings, pressurized rainfall simulator produces rainfall characteristics similar to natural rainfall, which is therefore recommended for laboratory use if natural rainfall-like characteristics is the main target.

There is increasing recognition of the need to incorporate the complex and dynamic interactions between society and water in studies of water resource systems. The study of human-water dynamics requires the involvement of researchers from different disciplines, including hydrology and social science. This paper tracks recent trends in socio-hydrological research using quantitative and qualitative methods. Bibliographic metrics and network analysis are used to identify general trends and illustrate the internal connections in this small but growing interdisciplinary field. Results show that hydrologists dominate research in socio-hydrology as presently defined, with far less participation from social scientists. Research questions for socio-hydrology tend to focus on system dynamics and are often not framed in a way that engages the interests and expertise of social scientists. A qualitative analysis addresses key barriers to the interdisciplinary development of socio-hydrology and identifies research needs and directions for better integration of the human dimensions of water science. Attracting social scientists to this field requires a broader conceptualization of socio-hydrology to focus on sustainable development, risk assessment, hazard management, resilience, adaptation, and knowledge mobilization in addition to hydrology’s traditional focus on systems modeling and decision support. We propose three themes for thematic focus: systemic risk and natural hazards; sustainability science; and adaptive governance. This broader framing of socio-hydrology is inherently more interdisciplinary, brings new methods and viewpoints to the field, and ensures that place-based local values are included in studies of water system dynamics.

Global Satellite Mapping of Precipitation (GSMaP), Climate Hazards Group InfraRed Preconception with Station data (CHIRPS), Tropical Rain Measurement Mission Multisatellite Precipitation Analysis (TRMM 3B42 V7) and Rainfall Estimation from Soil Moisture Observations (SM2RAIN) are satellite precipitation products with high applicability, but their applicability in hydrological research in arid mountainous areas is not clear. Based on precipitation and runoff data, this study evaluated the applicability of each product to hydrological research in a typical mountainous basin (the Qaraqash River basin) in an arid region by using two methods: a statistical index and a hydrological model (Soil and Water Assessment Tool, SWAT). Simulation results were evaluated by Nash efficiency coefficient (NS), relative error (PBIAS) and determination coefficient (R2). The results show that: (1) The spatial distributions of precipitation estimated by these four products in the Qaraqash River basin are significantly different, and the multi-year average annual precipitation of GSMaP is 97.11 mm, which is the closest to the weather station interpolation results. (2) On the annual and monthly scales, GSMaP has the highest correlation (R ≥ 0.82) with the observed precipitation and the smallest relative error (BIAS < 6%). On the seasonal scale, the inversion accuracy of GSMaP in spring, summer and autumn is significantly higher than other products. In winter, all four sets of products perform poorly in estimating the actual precipitation. (3) Monthly runoff simulations based on SM2RAIN and GSMaP show good fitting (R2 > 0.6). In daily runoff simulation, GSMaP has the greatest ability to reproduce runoff changes. The study provides a reference for the optimization of precipitation image data and hydrological simulation in data-scarce areas.

Women play a central part in the provision, management and safeguarding of water. This pivotal role of women as providers and users of water and guardians of the living environment has seldom been reflected in institutional arrangements for the development and management of water resources. Acceptance and implementation of this principle requires positive policies to address women's specific needs and to equip and empower women to participate at all levels in water resources programmes, including decision-making and implementation. The objective of this paper is to highlight some of the recent contribution of women in the field of Hydrology.

Snow depth mirrors regional climate change and is a vital parameter for medium- and long-term numerical climate prediction, numerical simulation of land-surface hydrological process, and water resource assessment. However, the quality of the available snow depth products retrieved from remote sensing is inevitably affected by cloud and mountain shadow, and the spatiotemporal resolution of the snow depth data cannot meet the need of hydrological research and decision-making assistance. Therefore, a method to enhance the accuracy of snow depth data is urgently required. In the present study, three kinds of snow depth data which included the D-InSAR data retrieved from the remote sensing images of Sentinel-1 synthetic aperture radar, the automatically measured data using ultrasonic snow depth detectors, and the manually measured data were assimilated based on ensemble Kalman filter. The assimilated snow depth data were spatiotemporally consecutive and integrated. Under the constraint of the measured data, the accuracy of the assimilated snow depth data was higher and met the need of subsequent research. The development of ultrasonic snow depth detector and the application of D-InSAR technology in snow depth inversion had greatly alleviated the insufficiency of snow depth data in types and quantity. At the same time, the assimilation of multi-source snow depth data by ensemble Kalman filter also provides high-precision data to support remote sensing hydrological research, water resource assessment, and snow disaster prevention and control program.

Many small-scale water development initiatives are accompanied by hydrological research to study either the form of the intervention or its impacts. Humans influence both the development of intervention and research, and thus one needs to take human agency into account. This paper focuses on the effects of human actions in the development of the intervention and its associated hydrological research, as hydrological research is often designed without adequate consideration of how to account for human agency and that these effects have not yet been discussed explicitly in a systematic way. In this paper, we propose a systematic planning for hydrological research, based on evaluating three hydrological research efforts targeting small-scale water development initiatives in Vietnam, Kenya, and Indonesia. The main purpose of the three cases was to understand the functioning of interventions in their hydrological contexts. Aiming for better decision-making on hydrological research in small-scale water intervention initiatives, we propose two analysis steps, including (1) consideration of possible surprises and possible actions and (2) cost–benefit analysis. By performing the two analyses continuously throughout small-scale hydrological intervention-based initiatives, effective hydrological research can be achieved.

Hydrological investigations require the development of a geodatabase allowing for the calculation of physiographic catchment parameters, as well as the analysis of amounts of water resources and changes therein. Such a geodatabase usually consists of meteorological, hydrological and cartographic data. The present study offers a review of datasets that may be used for geodatabase development in the interests of hydrological research, in catchments located in the Polish-Ukrainian borderland. The catchment of the Wiar River – selected to serve as a case study – is in fact divided by the state border into two equal sub-catchments (395.5 km2 in Poland and 398.9 km2 in Ukraine).The results reveal disparities in the spatial distribution of stream and meteorological gauges. For the Polish part of the catchment datasets include many parameters (in accordance with EU Directive and Regulations) and the results from monitoring are available online as yearly reports. For the Ukrainian part, only chemical components are monitored, and these data are not made available publicly. Consistent data sets such as DEM can be obtained from globally available ASTER and SRTM models. Datasets, such as LiDAR, which are important for medium and large-scale analyses allowing for the development of high-resolution DEMs, do not exist. Use of TanDEM-X data is restricted for the Ukrainian territory. However, comparison between the SRTM and LiDAR models (for the Polish part) revealed that the SRTM model may be optimised to serve the whole area. Land-use and land-cover data (LULC) are important in many hydrological analyses. the authors propose using satellite images in the development of a comparable layer describing land cover of the whole catchment.

Drought is a complex natural hazard that has been recurrently occurred in many regions across the globe. Therefore, precise drought characterization and its regional monitoring are key challenges for advanced water management and hydrological research. In this research, we provided a novel method to improve annual average time series data for the Standardized Drought Index (SDI)-type drought monitoring tools. We proposed multi-auxiliary information-based estimation strategy that improves annual moving average/total precipitation time series records. Therefore, we incorporated a minimum and maximum temperature as auxiliary variables under multi-auxiliary regression estimator. In summary, this study propagates a new drought index named: the Precision-Weighted Standardized Precipitation Index (PWSDI). We evaluated the performance of PWSDI for 10 meteorological stations in Pakistan. We found that improved estimates of temporal precipitation time series are good candidates for modelling and monitoring hydrological drought at the regional settings under SDI procedure.

Around one-third of the world’s population drinks water from groundwater resources. Of this, about 10 percent, approximately 300 million people, obtains water from groundwater resources. This study identify and mapping of groundwater potential zone for growing population, irrigation and industrial development, combining with remote sensing (RS), geographical information system (GIS) and field data for hydrological research in Kalmykia, Russia. Various thematic layers (i.e. land use/cove, soil, geomorphology, lithology, elevation, slope, rainfall, normalized difference vegetation index (NDVI), drainage density, lineament density, degraded land, forest, relief, vegetation, surface water body, land use, agriculture, flow accumulation, flow direction and base map) wear used along with existing maps to prepare groundwater potential zone (GWPZ) map. Weights were assigned to all above factors according to their effectiveness, sensitivity and relevance to ground water potentiality. Furthermore the resulting GWPZ map has been classified into five classes, named very high, high, moderate, low and very low based on hydro-geomorphological condition, covering 0.93, 11.65, 35.45, 43.20 and 8.77% area respectively. The results show that most part of areas with favorable lithology, soil texture, vegetation, slope, optimum rainfall condition has a high potential for groundwater. The results provide significant information and can be use by local authorities for groundwater exploitation and management.

The Marcell Experimental Forest (MEF) in northern Minnesota, USA, with hydrological research and monitoring of peatland catchments in a low-topographic relief landscape, contrasts with the mountainous terrain that typifies most research catchments. Six research catchments were instrumented and hydrological and meteorological monitoring was initiated during 1960. Paired-catchment studies, which started during 1969, have been used to assess land management and environmental change effects on forests, water availability, and biogeochemistry. Over the decades, the research and collaborations have proliferated to include new monitoring and ecosystem experiments. We provide an overview of available datasets and access information for hydrological and meteorological data. Data on streamflow, water table elevation, precipitation, snow, ground frost, air temperature, soil moisture, upland runoff, and water chemistry are discoverable with associated metadata and are archived through several Web-based, community repositories. The research programme is ongoing and we anticipate updates on an annual or more frequent basis. Additionally, we aim to release other physical, chemical, and isotopic measurements associated with long-term catchment monitoring and studies at the MEF.

Time series remote sensing data provide data support for agricultural monitoring, atmospheric and hydrological research, etc. As an effective method to reconstruct time series remote sensing images, remote sensing spatiotemporal information fusion technology can supply the shortage of high spatial resolution data. Aiming at the accuracy of time series remote sensing data generated by spatiotemporal fusion model, this paper proposes a time series assessment method based on Dynamic time warping (DTW), which uses GF-2 and Landsat-8 data to product 2015 year time series data by selected four typical spatiotemporal fusion models (STARFM, FSDAF, ESPFM, Single-pair SPSTFM), and compare synthesized data with reference data. The results show that the time series assessment method has a high consistency with the existing methods which based on spatial quality evaluation. And this method can be used as an effective method to evaluate the accuracy of synthesized time series data.

Soil moisture is a key issue for eco-hydrological research in arid and semi-arid regions, and is primarily concerned with water availability for vegetation. Shallow and deep soil moisture occurs according to the maximum infiltration depth. Soil moisture has three-dimensional characteristics: inter-layer variability, horizontal heterogeneity and temporal variability. Soil moisture is affected by various factors including terrain, soil characteristics, climate and vegetation, and the effects of these change with time (e.g., rainfall patterns) and space (e.g., soil depth). In arid and semi-arid regions, deep soil moisture is of particular importance to vegetation restoration and the evaluation of vegetation sustainability; however, accurate prediction of the spatial distribution of deep soil moisture in the Loess Plateau of China still faces numerous challenges. Therefore, future research should focus on the mechanisms, models and scale effects of soil moisture, particularly for deep soil moisture.

Understanding potential evapotranspiration (PET) changes under climate change is of great importance for hydrological research. The trends of PET changes and their driving forces were investigated in the Lancang (LRB) and Yarlung Zangbo (YRB) river basins, southwest China, using diagnosis graphs and the Mann-Kendall test. Analysis of variance was applied to examine the contribution of different climatic variables to PET. The results show that: (i) there was a statistically significant increase in PET in the period of 1957–2015 in the LRB, while it showed a markedly decreasing trend in the YRB; (ii) PET in both basins is fairly sensitive to wind speed, relative humidity, solar radiation and maximum air temperature, and the interactions between wind speed and relative humidity are also important; and (iii) the increase in PET in the LRB is due mainly to the increase in maximum air temperature and decrease in relative humidity, while declines in wind speed and solar radiation are the main reasons for the decrease in PET in the YRB.

The aim of hydrological research has always been, and should still be to improve our understanding of hydrologic processes. Catchment hydrological response has the potential to enhance understanding of these processes. Regionalisation of hydrological response is important in identifying watersheds with similar catchment hydrological response, thus making predictions in ungauged and poorly gauged basins to be possible. This study establishes the hydrological response of 122 catchments in Swaziland's trans -boundary basins on the basis of validated WR90 hydro-meteorological time series data. The flow duration indices (FDIs: Q10, Q50, Q90) were determined and standardised by the mean monthly streamflow, and the runoff ratio was calculated as a method to determine how catchments respond to precipitation inputs. The runoff ratio and FDIs were then plotted against aridity indices, and the plot shows that the runoff ratio is consistent with the aridity index, except for a few suspected anomalies emanating from values of Q50 and Q90. The findings indicate that the hydrological response of the catchments is diverse and somewhat characterised by regions. The diversity and the regions are associated with climate regime and topography controls. It is anticipated that the potential of using hydrological response to gain more understanding of catchments behaviour will improve and further rigorous exploration may be required.

Air temperature is one of the most important meteorological factors that affect melting of glaciers, distribution of snowfall and rain at higher altitudes in the Himalaya. However, studies on spatio-temporal variability of air temperature in the central Himalaya are limited. In the present study, seasonal and annual characteristics (July 2011 to December 2015) of near-surface temperature and lapse rate in the Dokriani glacier catchment (DGC) of the central Himalaya are investigated using data from three automatic weather stations (AWSs). An attempt is also made to quantify 0 °C isotherm and temperate sustainability over the glacierized area. The results reveal that the average near-surface temperature lapse rate (NSTLR) of the catchment varies from 4.6 to 7.5 °C km−1 during all measurement seasons, suggesting that the standard environmental lapse rate (SELR, 6.5 °C km−1) is not a promising input for realistic glacio-hydrological modeling. The seasonal variability of the NSTLR indicates that the monsoon (warm and humid period) lowers the temperature lapse rate in this catchment due to the presence of high moisture content in the air. The steepest lapse rate is investigated during the pre-monsoon season due to clear and drier weather conditions. In addition to this, the results reveal strong variability in NSTLR at diurnal and sub-diurnal levels, with high variability in the day time and low in the night-time hours. A higher air temperature is examined in the ablation zone of the Dokriani Glacier during the monsoon season (i.e., JJAS: June, July, August, September), while other seasons (pre-monsoon, post-monsoon, winter) show both higher as well as lower temperatures. A large variation in 0 °C isotherm is also observed ranging from 5000 to 5500 m asl during 2012–2015. The present work emphasizes that the study of monthly, seasonal, and annual variability of the NSTLR are very important for glacio-hydrological research in the central Himalaya.

In 2018, 70 years have passed since the beginning of observations at the Kolyma Water-Balance Station (KWBS), a unique scientific research hydrological and permafrost catchment. The volume and duration (50 continuous years) of hydrometeorological standard and experimental data, characterizing the natural conditions and processes occurring in mountainous permafrost conditions, significantly exceed any counterparts elsewhere in the world. The data are representative of mountainous territory of the North-East of Russia. In 1997, the station was terminated, thereby leaving Russia without operating research watersheds in the permafrost zone. This paper describes the dataset containing the series of daily runoff from 10 watersheds with an area from 0.27 to 21.3 km2, precipitation, meteorological observations, evaporation from soil and snow, snow surveys, soil thaw and freeze depths, and soil temperature for the period 1948–1997. It also highlights the main historical stages of the station's existence, its work and scientific significance, and outlines the prospects for its future, where the Kolyma Water-Balance Station could be restored to the status of a scientific research watershed and become a valuable international centre for hydrological research in permafrost. The data are available at https://doi.org/10.1594/PANGAEA.881731.

Long-term persistence (LTP) of annual river runoff is a topic of ongoing hydrological research, due to its implications to water resources management. Here, we estimate its strength, measured by the Hurst coefficient H, in 696 annual, globally distributed, streamflow records with at least 80 years of data. We use three estimation methods (maximum likelihood estimator, Whittle estimator and least squares variance) resulting in similar mean values of H close to 0.65. Subsequently, we explore potential factors influencing H by two linear (Spearman's rank correlation, multiple linear regression) and two non-linear (self-organizing maps, random forests) techniques. Catchment area is found to be crucial for medium to larger watersheds, while climatic controls, such as aridity index, have higher impact to smaller ones. Our findings indicate that long-term persistence is weaker than found in other studies, suggesting that enhanced LTP is encountered in large-catchment rivers, were the effect of spatial aggregation is more intense. However, we also show that the estimated values of H can be reproduced by a short-term persistence stochastic model such as an auto-regressive AR(1) process. A direct consequence is that some of the most common methods for the estimation of H coefficient, might not be suitable for discriminating short- and long-term persistence even in long observational records.

Understanding cryospheric hydrology and the effects of cryospheric changes on river runoff is critical for sustainable water management especially in arid inland river basins such as those in northwest China where water resources mainly come from alpine areas. A cryospheric hydrometeorology observation system (CHOICE) has been established since 2008 in the Hulu catchment, which is a well-instrumented experimental and representative catchment in the upper reaches of the inland Hei River, Qilian Mountains, northwest China. The CHOICE includes dense meteorological measurements from 2980 to 4800 m asl (e.g. glacier, snow, and permafrost hydrology) and water and heat balance in the vertical landscape zones including alpine grassland, meadow, shrub, coniferous forest, marshy meadow, and moraine-talus zones. The comprehensive long-term observations available for the CHOICE provide the basis for model development and application in cryospheric hydrological research. We focus on cryospheric hydrometeorological process of precipitation, freeze–thaw cycle, energy balance, soil–vegetation–atmosphere transfer (SVAT), runoff, groundwater reservoir, and hydrological resiliency within vertical elevation in CHIOCE. Data from CHOICE, an open cryospheric hydrology observation and research system, is accessed through a website (/) and the WestDC database (/).

Hydrological monitoring and real-time access to data are valuable for hydrological research and water resources management. In the recent decades, rapid developments in digital technology, micro-electromechanical systems, low power micro-sensing technologies and improved industrial manufacturing processes have resulted in retrieving real-time data through Wireless Sensor Networks (WSNs) systems. In this study, a remotely operated low-cost and robust WSN system was developed to monitor and collect real-time hydrologic data from a small agricultural watershed in harsh weather conditions and upland rolling topography of Southern Ontario, Canada. The WSN system was assembled using off-the-shelf hardware components, and an open source operating system was used to minimize the cost. The developed system was rigorously tested in the laboratory and the field and found to be accurate and reliable for monitoring climatic and hydrologic parameters. The soil moisture and runoff data for 7 springs, 19 summer, and 19 fall season rainfall events over the period of more than two years were successfully collected in a small experimental agricultural watershed situated near Elora, Ontario, Canada. The developed WSN system can be readily extended for the purpose of most hydrological monitoring applications, although it was explicitly tailored for a project focused on mapping the Variable Source Areas (VSAs) in a small agricultural watershed.

Reconstruction of missing runoff data is of important significance to solve contradictions between the common situation of gaps and the fundamental necessity of complete time series for reliable hydrological research. The conventional empirical orthogonal functions (EOF) approach has been documented to be useful for interpolating hydrological series based upon spatiotemporal decomposition of runoff variation patterns, without additional measurements (e.g., precipitation, land cover). This study develops a new EOF-based approach (abbreviated as CEOF) that conditions EOF expansion on the oscillations at outlet (or any other reference station) of a target basin and creates a set of residual series by removing the dependence on this reference series, in order to redefine the amplitude functions (components). This development allows a transparent hydrological interpretation of the dimensionless components and thereby strengthens their capacities to explain various runoff regimes in a basin. The two approaches are demonstrated on an application of discharge observations from the Ganjiang basin, China. Two alternatives for determining amplitude functions based on centred and standardised series, respectively, are tested. The convergence in the reconstruction of observations at different sites as a function of the number of components and its relation to the characteristics of the site are analysed. Results indicate that the CEOF approach offers an efficient way to restore runoff records with only one to four components; it shows more superiority in nested large basins than at headwater sites and often performs better than the EOF approach when using standardised series, especially in improving infilling accuracy for low flows. Comparisons against other interpolation methods (i.e., nearest neighbour, linear regression, inverse distance weighting) further confirm the advantage of the EOF-based approaches in avoiding spatial and temporal inconsistencies in estimated series.

Soil moisture data assimilation (SMDA) has found growing application in the hydrological research community because of readily available satellite-based soil moisture (SM) data. Several past studies have explored the capability to assimilate observed SM in hydrological model to enhance streamflow prediction. However, the impact of the conceptual hydrological model (CHM) structure on the SMDA in streamflow prediction has not been investigated yet. In this study, to understand the CHM structure's role, we used three different CHMs for the SMDA: dynamic Budyko (DB), Genie Rural a 4 parametres Journalier (GR4J), and Probability Distributed Model (PDM) model. The SM obtained from Global Land Data Assimilation System (GLDAS) was assimilated using Ensemble Kalman Filter (EnKF) for 43 Model Parameter Estimation Experiment (MOPEX) basins. The GR4J model was found to be performed best from calibration and validation results, and the DB model was found to be performed least. The results show that the performance of the DB model improved during assimilation compared to its open-loop version for all the 43 basins. However, deterioration in model performance was observed for the GR4J and PDM model during assimilation for all basins except a few. The assimilated model performance was evaluated in respect of Assimilation Efficiency (AE) and ranged from 2.56 to 81.24%, −70.9 to 17.65%, and −71.38 to 24.86%, respectively, for the DB, GR4J, and PDM model. Further, we hypothesized that if the GLDAS SM is better than the model-simulated SM, then improvement in the model performance is observed due to the SMDA. The coefficient of determination (r2) between the SM simulated by all the three models without assimilation and the GLDAS SM was found for all the basins. Results indicated that the GR4J and PDM model captured SM better than the DB model. Moreover, to strengthen this hypothesis, we run the GR4J and PDM model deterministically, considering the daily GLDAS SM as the initial condition for streamflow simulation instead of the SM simulated by these models for the basins where deterioration in model performance was observed. For all the basins, it is found that the GR4J and PDM model performance deteriorated. Even though the GLDAS SM is used as every day's initial condition to simulate the streamflow, no improvement of model performance is observed. In general, our study underlines the significance of the CHM structure in the SMDA exercise.

During hydrological research in a Chilean swamp forest, we noted a pattern of higher streamflows close to midday and lower ones close to midnight, the opposite of an evapotranspiration (Et)-driven cycle. We analyzed this diurnal streamflow signal (DSS), which appeared mid-spring (in the growing season). The end of this DSS coincided with a sustained rain event in autumn, which deeply affected stream and meteorological variables. A survey along the stream revealed that the DSS maximum and minimum values appeared 6 and 4 hours earlier, respectively, at headwaters located in the mountain forests/ plantations than at the control point in the swamp forest. Et in the swamp forest was higher in the morning and in the late afternoon, but this process could not influence the groundwater stage. Trees in the mountain headwaters reached their maximum Ets in the early morning and/or close to midday. Our results suggest that the DSS is a wave that moves from forests high in the mountains towards lowland areas, where Et is decoupled from the DSS. This signal delay seems to convert the link between streamflow and Et in an apparent, but spurious positive relationship. It also highlights the role of landscape heterogeneity in shaping hydrological processes.

The integration of interdisciplinary scientific and societal knowledge plays an increasing role in sustainability science and more generally, in global change research. In the field of water resources, interdisciplinarity has long been recognized as crucial. Recently, new concepts and ideas about how to approach water resources management more holistically have been discussed. The emergence of concepts such as socio-hydrology indicates the growing relevance of connections between social and hydrological disciplines. In this paper, we determine how well social sciences are integrated with hydrological research by using two approaches. First, we conducted a questionnaire survey with a sample of hydrology researchers and professionals (N = 353) to explore current opinions and developments related to interdisciplinary collaboration between hydrologists and social scientists. Second, we analyzed the disciplinary composition of author teams and the reference lists of articles pertaining to the socio-hydrology concept. We conclude that interdisciplinarity in water resources research is on a promising track but may need to mature further in terms of its aims and methods of integration. We find that current literature pays little attention to the following questions: What kind of interdisciplinarity do different scholars want? What are social scientists’ preferred roles and knowledge from a hydrology perspective?

Mixing calculations (i.e., the calculation of the proportions in which end-members are mixed in a sample) are essential for hydrological research and water management. However, they typically require the use of conservative species, a condition that may be difficult to meet due to chemical reactions. Mixing calculation also require identifying end-member waters, which is usually achieved through End Member Mixing Analysis (EMMA). We present a methodology to help in the identification of both end-members and such reactions, so as to improve mixing ratio calculations. The proposed approach consists of: (1) identifying the potential chemical reactions with the help of EMMA; (2) defining decoupled conservative chemical components consistent with those reactions; (3) repeat EMMA with the decoupled (i.e., conservative) components, so as to identify end-members waters; and (4) computing mixing ratios using the new set of components and end-members. The approach is illustrated by application to two synthetic mixing examples involving mineral dissolution and cation exchange reactions. Results confirm that the methodology can be successfully used to identify geochemical processes affecting the mixtures, thus improving the accuracy of mixing ratios calculations and relaxing the need for conservative species. Fil: Pelizardi, Flavia Paola. Universidad Nacional del Centro de la Provincia de Buenos Aires. Rectorado. Instituto de Hidrología de Llanuras - Sede Azul. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto de Hidrología de Llanuras - Sede Azul; Argentina Fil: Bea, Sergio Andrés. Universidad Nacional del Centro de la Provincia de Buenos Aires. Rectorado. Instituto de Hidrología de Llanuras - Sede Azul. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto de Hidrología de Llanuras - Sede Azul; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Carrera, Jesús. Consejo Superior de Investigaciones Científicas; España. Universidad Politécnica de Catalunya; España Fil: Vives, Luis Sebastián. Universidad Nacional del Centro de la Provincia de Buenos Aires. Rectorado. Instituto de Hidrología de Llanuras - Sede Azul. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto de Hidrología de Llanuras - Sede Azul; Argentina

Conceptual models often suffer from the over-parameterization problem due to limited available data for the calibration. This leads to the problem of parameter nonuniqueness and equifinality, which may bring much uncertainty of the simulation result. How to find out the appropriate model structure supported by the available data to simulate the catchment is still a big challenge in the hydrological research. In this paper, we adopt a multi-model framework to identify the dominant hydrological process and appropriate model structure of a karst spring, located in Guilin city, China. For this catchment, the spring discharge is the only available data for the model calibration. This framework starts with a relative complex conceptual model according to the perception of the catchment and then this complex is simplified into several different models by gradually removing the model component. The multi-objective approach is used to compare the performance of these different models and the regional sensitivity analysis (RSA) is used to investigate the parameter identifiability. The results show this karst spring is mainly controlled by two different hydrological processes and one of the processes is threshold-driven which is consistent with the fieldwork investigation. However, the appropriate model structure to simulate the discharge of this spring is much simpler than the actual aquifer structure and hydrological processes understanding from the fieldwork investigation. A simple linear reservoir with two different outlets is enough to simulate this spring discharge. The detail runoff process in the catchment is not needed in the conceptual model to simulate the spring discharge. More complex model should need more other additional data to avoid serious deterioration of model predictions.

Lateral flow separation occurs in rivers where banks exhibit strong curvature. In canyon bound rivers, lateral recirculation zones are the principal storage of fine sediment deposits. A parallelized, three-dimensional, turbulence-resolving model was developed to study the flow structures along lateral separation zones located in two pools along the Colorado River in Marble Canyon. The model employs the detached eddy simulation (DES) technique, which resolves turbulence structures larger than the grid spacing in the interior of the flow. The DES-3D model is validated using ADCP flow measurements taken during the 2008 controlled flood release from Glen Canyon Dam. A point-to-point validation using a number of skill metrics, often employed in hydrological research, is proposed here for fluvial modeling. The validation results show predictive capabilities of the DES model. The model reproduces the pattern and magnitude of the velocity in the lateral recirculation zone, including the size and position of the primary and secondary eddy cells, and return current. The lateral recirculation zone is open, having continuous import of fluid upstream of the point of reattachment and export by the recirculation return current downstream of the point of separation. Differences in magnitude and direction of near-bed and near-surface velocity vectors are found, resulting in an inward vertical spiral. Interaction between the recirculation return current and the main flow is dynamic, with large temporal changes in flow direction and magnitude. Turbulence structures with a predominately vertical axis of vorticity are observed in the shear layer becoming three-dimensional without preferred orientation downstream.

Changes in hydrological processes due to rising temperatures and related effects on the socio-economy and people’s livelihood are major concerns in Bangladesh. A study has been performed to assess the effects of increasing temperature on the groundwater levels and consequent changes in irrigation costs for groundwater-dependent irrigated agriculture in Northwest Bangladesh. A support vector machine (SVM) was used to model the temporal variations in groundwater level from rainfall, evapotranspiration, groundwater abstraction, and agricultural return flow. A multiple linear regression (MLR) model was developed to define the functional relationship between irrigation costs and groundwater levels. The model showed that average groundwater level during the major irrigation period (January-April) decreased by 0.15-2.01 m due to an increase in temperature of 1-5°C, which increased irrigation costs by 0.05-0.54 thousand Bangladesh Taka (BDT) per hector.