Total Streamflow Research Articles

Changes in streamflow statistical structure across the United States due to recent climate change

Changes in statistical structure (spectral properties) of streamflow across the USA due to climate change were studied for water years 1980–2013. The Fractionally differenced Autoregressive Integrated Moving Average (FARIMA) model was fit to the deseasonalized streamflow time series to model its statistical structure. FARIMA allows the separation of streamflow into low- (slowly varying) and high-frequency (fast varying) components. In this study, the changes in the contribution of various components to the total streamflow variance were analyzed. Further, the variables affecting these changes were identified using random forest and linear regression. Results show that in the snow-dominated watersheds, the contribution of low-frequency components to total streamflow variance decreased over the study period, and the contribution of high-frequency components increased. The changes in the snow-dominated watersheds were primarily driven by changes in precipitation statistics and changes in snowpack but also by changes in seasonal temperature statistics. Among the rain-driven watersheds, the contribution of high-frequency components generally increased in arid regions but decreased in humid regions. In both humid and arid rain-driven watersheds, increasing winter temperature appears to be responsible for the change in streamflow statistical structure. These results have consequences for the predictability of streamflow in the presence of climate change. Further, the analysis carried out in this study allowed us to understand the plausible changes in watershed hydrologic processes that affect streamflow without using process-based or conceptual models.

A Multi-Temporal-Scale Modulation Mechanism for the Postprocessing of Precipitation Ensemble Forecasts: Benefits for Streamflow Forecasting

Abstract In the postprocessing of ensemble forecasts of weather variables, it is standard practice to first calibrate the forecasts in a univariate setting, before reconstructing multivariate ensembles that have a correct covariability in space, time, and across variables, via so-called “reordering” methods. Within this framework though, postprocessors cannot fully extract the skill of the raw forecast that may exist at larger scales. A multi-temporal-scale modulation mechanism for precipitation is here presented, which aims at improving the forecasts over different accumulation periods, and which can be coupled with any univariate calibration and multivariate reordering techniques. The idea, originally known under the term “canonical events,” has been implemented for more than a decade in the Meteorological Ensemble Forecast Processor (MEFP), a component of the U.S. National Weather Service’s (NWS) Hydrologic Ensemble Forecast Service (HEFS), although users were left with material in the gray literature. This paper proposes a formal description of the mechanism and studies its intrinsic connection with the multivariate reordering process. The verification of modulated and unmodulated forecasts, when coupled with two popular methods for reordering, the Schaake shuffle and ensemble copula coupling (ECC), is performed on 11 Californian basins, on both precipitation and streamflow. Results demonstrate the clear benefit of the multi-temporal-scale modulation, in particular on multiday total streamflow. However, the relative gain depends on the method used for reordering, with more benefits expected when this latter method is not able to reconstruct an adequate temporal structure on the calibrated precipitation forecasts.

Effects of landscape attributes and climate variables on catchment hydrology

Catchments characteristics, such as geomorphology, geology, soil, land use, and climatic variables, play an important role in total stream flow responses, a critical resource for people and the environment. Most of the previous literatures were applied a conventional statistical regression model to assess the relationship between landscape-climate descriptors, and streamflow and PET. However, a conventional statistical regression model didn’t consider dependence of explanatory variables that were collected or extracted across both space and time. This paper investigated the impacts of landscape attributes and climate variables on catchment scale temporal variation of total streamflow and spatio-temporal variation of potential evapotranspiration (PET) in the Mille catchment using multiple linear regression techniques, and the importance of this study was to test spatial autocorrelation in the spatial regression model which is required to properly assess and quantify the relationship between hydrological regime response components and Landscape-climate descriptors in a catchment with topographically complex, and high spatio-temporal climatic variation like in our case study area, the Mille catchment. Statistical regression analysis revealed significant relationships between streamflow and climate variables, especially with rainfall. Mean maximum temperature is the most dominant factor controlling temporal variation of potential evapotranspiration at a monthly scale, whereas NDVI is the most significant factor that controls the spatial variability of PET. The multiple regression model shows that 91.1% of temporal variation in streamflow was accounted for rainfall, whereas, 96.6% and 78.4% of temporal and spatial variation in potential evapotranspiration was accounted for in maximum temperature and NDVI, respectively. Methods also can be applied to catchments with similar landscape attributes and climate variables.

Incorporating experimentally derived streamflow contributions into model parameterization to improve discharge prediction

Abstract. Environmental tracers have been used to separate streamflow components for many years. They allow us to quantify the contribution of water originating from different sources, such as direct runoff from precipitation, subsurface storm flow, or groundwater to total streamflow at variable flow conditions. Although previous studies have explored the value of incorporating experimentally derived fractions of event and pre-event water into hydrological models, a thorough analysis of the value of incorporating hydrograph-separation-derived information on multiple streamflow components at varying flow conditions into model parameter estimation has not yet been performed. This study explores the value of such information to achieve more realistic simulations of catchment discharge. We use a modified version of the process-oriented HBV model that simulates catchment discharge through the interplay of hillslope, riparian-zone discharge, and groundwater discharge at a small forested catchment which is located in the mountainous north of South Korea, subject to a monsoon season between June and August. Applying a Monte-Carlo-based parameter estimation scheme and the Kling–Gupta efficiency (KGE) to compare discharge observations and simulations across two seasons (2013 and 2014), we show that the model is able to provide accurate simulations of catchment discharge (KGE ≥ 0.8) but fails to provide robust predictions and realistic estimates of the contribution of the different streamflow components. Using a simple framework that compares simulated and observed contributions of hillslope, riparian zone, and groundwater to total discharge during two sub-periods, we show that the precision of simulated streamflow components can be increased, while remaining with accurate discharge simulations. We further show that the additional information increases the identifiability of all model parameters and results in more robust predictions. Our study shows how tracer-derived information on streamflow contributions can be used to improve the simulation and predictions of streamflow at the catchment scale without adding additional complexity to the model. The complementary use of temporally resolved observations of streamflow components and modeling provides a promising direction to improve discharge prediction by representing model internal dynamics more realistically.

Evaluating Methods of Streamflow Timing to Approximate Snowmelt Contribution in High-Elevation Mountain Watersheds

Current streamflow timing metrics, such as the center of volume, or COV, use flow days, which are days at which a specific total streamflow volume, such as 50% for COV, has passed a given point. These metrics have been used as indicators for changes in the timings of snowmelt contributions to streamflow, but they may not be indicating changes to snowmelt timings as they have a fixed volume. Using manually extracted start and end days for high-elevation, mountainous watersheds, which are regarded as true values, we developed a new method to estimate when snowmelt is entering streams. Based on RMSE and NSE values, this new method is a better model for snowmelt-driven streamflow than using flow days or the COV. In general, the trend analysis results from the different timing metrics indicate an earlier timing in the year. This method was suitable for 40 different-sized watersheds in Colorado, USA; these are all snow-dominated watersheds in a semi-arid climate. This method could be used to assess watersheds in different climates, including those that are not as snow-dominated.

Simulating glacier mass balance and its contribution to runoff in Northern Sweden

Glaciers are one of the main sources of freshwater in cold regions. The glacier melting process can significantly impact the glacier mass balance (GMB) and contribute a large amount of runoff in cold regions. This study applied the recently developed semi-distributed glacio-hydrological conceptual model (FLEXG) to understand the glacier melting process and the effect of topography on GMB in the Torne River basin, northern Sweden. The study simulated glacier and snow accumulation and ablation, as well as runoff from the glacier and non-glacier areas of the basin using the FLEXG model for the time period 1989–2018. The FLEXG model considers the influence of topography on runoff generation, and in this study the basin was classified into 143 zones depending on elevation and aspect. In order to gain a comprehensive view of the performance of the FLEXG model, the classical lumped hydrological model HBV was used and compared with the FLEXG model in simulating total streamflow and peak runoff at the outlet of the basin. Our results revealed that the FLEXG model performed well in reproducing the streamflow (also better than the HBV model) with metric Kling-Gupta Efficiency (KGE) of 0.80 and 0.71 for the calibration and validation periods, respectively. We also found that the FLEXG model performs better in peak runoff simulation than the HBV model. The FLEXG simulated snow cover area proportion agreed well with the MODIS satellite snow cover product (R2 = 0.60 and RMSE = 28%). The GMB in different elevation zones was simulated, and a downward trend was found for GMB changes during the study period because of climate change.

Total Streamflow Variation for the Upper Catchment of Bosten Lake Basin in China Inferred from Tree-Ring Width Records

Bosten Lake Basin not only is a major source of drinking water for the residents of the surrounding area, but also maintains the ecological balance of the region. However, with the influence of climate change and human activities, the water level of Bosten Lake fluctuates sharply and has a great impact on the surrounding ecological environment. Therefore, the study of its historical water flow changes as a reference has become a focus of research. In this study, the radial growth of Schrenk spruces (Picea schrenkiana Fisch. et Mey.) significantly correlated with the tributary streamflow coming from the mountainous region near Bosten Lake Basin. On the basis of this good coherence, the tree-ring chronologies were used to reconstruct the streamflow for Huangshuigou River from the previous August to the present July (r = 0.766, p < 0.0001, n = 50). The reconstructed streamflow series matched observations well, explaining 63.3% of the variation in the observed streamflow of 1956–2005. Then, the sum of the streamflow reconstruction of Huangshuigou River and another two tree-ring-based streamflow reconstructions (Kaidu River and Qingshui River) was used to represent the hydrological variation of the upper catchment of Bosten Lake Basin, and the reconstruction sequence was 306 years. The 10.7, 5.5, and 2.1 year cycles of the power spectrum and wavelet analysis revealed that the runoff series reconstructed from tree-ring hydrometeorology was related to solar activity. Some dry and wet years in the reconstructed streamflow series of the upper catchment of Bosten Lake Basin corresponded to the historical record. During the wet years, the Indian Ocean was probably the main source of precipitation.

Comparison of the SCS-CN and Hydrograph Separation Method for Runoff Estimation in an Ungauged Basin: The Izmit Basin, Turkey

The separation of surface runoff and base flow is a very specific problem in water balance calculations, particularly if there is not enough measured flow data. In this study, the SCS-CN method is used to estimate the surface runoff in the ungauged Izmit Basin. The CNs are estimated using the Hydrologic Soil Groups map, based on soil data of the General Directorate of Rural Services of Turkey and land use obtained from the CORINE-2006 database for different AMCs. The surface runoff was computed using the SCS-CN method for the ungauged Izmit Basin that corresponds to 17% and 21% of the rainfall, i.e. 134 mm (for Kocaeli Meteorological Station; rainfall=804 mm) and 171 mm (for Sakarya Meteorological Station; rainfall=820 mm). According to SCS-CN method estimates, approximately 41-42% of the annual rainfall in the Izmit Basin directly contributes to the total streamflow, and 21-25% of it contributes to base flow and unmeasured infiltration. To compare the results of the SCS-CN method along with hydrograph separation method, the gauged Yuvacık Dam Sub-Basin, which is hydro-meteorologically similar to the Izmit Basin, was selected. The results showed that 16% of the rainfall in the Yuvacık Dam Sub-Basin became surface runoff. Also, it was found that about 42% of the annual rainfall in the Yuvacık Dam Sub-Basin directly contributes to the total streamflow and 23% of it contributes to the base flow and unmeasured infiltration. These results confirm that the ratio of surface runoff obtained by the hydrograph separation method in the Yuvacık Dam Sub-Basin matches with the ratio of surface runoff calculated using the SCS-CN method for the entire Izmit Basin.

Glacier contribution to lowland streamflow: A multi-year, daily geochemical hydrograph separation study in subarctic Alaska

Glacier melt water is a critical fresh water contribution of stream discharge for many regions and in high latitudes glacier extent is decreasing with climate warming. However, characteristics of glacierized contributions to subarctic watershed-scale geochemistry and runoff have attracted limited attention. Tracer studies of glacier dominated watersheds are also commonly limited to a few days. We conducted a six-year geochemical hydrograph separation study of melt season daily streamflow in a glacierized watershed in Interior Alaska to estimate glacier, rain, snow, and baseflow contributions. Bulk streamflow water samples were collected daily from the lowlands of Jarvis Creek (634 km2, 3.3% glacier cover) throughout the flow season (late April through September) during 2011–2016. Synoptic sampling of source waters included rain, snow, headwater late-winter streamflow and late-summer glacier terminus discharge. All 1227 source water and bulk streamflow samples were analyzed for stable water isotopes (δ18O and δD) and dissolved ion concentrations (SO42−:Cl− ratio). Bulk streamflow water samples exhibited large seasonal and inter-annual geochemical variation. Considerable inter-annual differences in stable water isotopes within each source water (δ18O values of −15.8 to −20.9‰ for rain, for example) emphasize the importance of informing the mixing model with source waters sampled during the same season as bulk streamflow collection. We estimated glacier discharge to be the largest seasonal contributor to total warm season lowland streamflow (average 35%, ranging from 20% in year 2016 to 44% in 2012) with daily variability from 2 (June 2, 2011) to 80% (September 10, 2013). If the glacier contribution were to cease completely, total warm season bulk stream discharge would be reduced by between 22 and 48% during an above or below average total seasonal rainfall, respectively, with up to an 80% reduction in peak flows. Results from this study suggest that high variability in source contribution of glacierized watersheds, extending across intra- and interannual timescales, challenge any generalization of hydrologic function derived from short-term studies.

SMAP soil moisture data assimilation impacts on water quality and crop yield predictions in watershed modeling

Model soil moisture predictions are routinely updated with independent observations using data assimilation techniques. While the impacts of these updates on modeled hydrology are well studied, impacts on predicted water quality and crop yield are unresolved. In this study, we evaluated data assimilation effects for a range of predictions in the Soil and Water Assessment Tool (SWAT). We used satellite surface soil moisture data products from the Soil Moisture Active/Passive (SMAP) mission to update SWAT soil moisture for two U.S. experimental watersheds. We addressed possible limitations to the vertical transfer of surface soil moisture updates to deeper layers in the model by additionally testing a modified soil percolation approach that relies on relative saturation rather than the original thresholding behavior of SWAT. Results at both watersheds demonstrated that data assimilation greatly impacted water quality and crop yield predictions. Modifying the soil percolation algorithm, however, did not improve assimilation results. Assimilation increased median soil moisture (+2% to +6 %) which in turn increased total streamflow (+0.43 to +1.70 m3/s daily). Critically, streamflow alone was not a sufficient predictor for the assimilation changes to water quality predictions as flow component contributions and seasonality differed between sites. A varied response in annual water quality predictions to soil moisture updates was identified (+1.70 to +123 kg/ha total nitrogen; −0.11 to −0.57 kg/ha total phosphorous; +8.1 to +50.0 kg/ha sediment) that was dependent upon the timing of the updates, site characteristics, and change to specific transport and transformation processes. Crop yield predictions were similarly impacted by data assimilation from changes to both water and nutrient availability that varied by crop type. The overall strong and diverse response of water quality and crop yield predictions to soil moisture updates provides evidence that assimilation can impact a range of model predictions. Efforts to improve soil moisture simulations, therefore, have potential for meaningful improvements in targeted, non-hydrologic predictions.

Gestão dos recursos hídricos em bacias tropicais complexas: uma abordagem customizada da modelagem eco-hidrológica SWAT para o Rio das Velhas, Brasil

ABSTRACT Hydrological modeling in decision-making is particularly challenging in tropical countries such as Brazil. There are numerous modeling tools; however, many applications have focused on watersheds with a total area of <20,000km2. Here we tailored a customized SWAT (Soil and Water Assessment Tool) ecohydrological model application using the SWAT CUP tool for calibration and validation of the Rio das Velhas, a relatively large, complex Brazilian basin (~28,000km2). The Rio das Velhas is the longest tributary of the São Francisco River and contains heterogeneous landforms, soils, vegetation, and land uses. A multisite calibration method obtained specific regionalized parameters for each sub-basin group for successfully simulating Rio das Velhas streamflows. Our results showed a suitable adjustment of the model. Nash-Sutcliff (NS) model performance values were 0.73-0.97 (calibration) and 0.51-0.98 (validation). The percent bias (PBIAS) was -11.3 to 19.4 (calibration) and -18.6 to 24.6 (validation), and the coefficient of determination values (R2) were >0.6 in all sub-basins on a monthly basis. We also explored how four contrasting land use scenarios affected four water-flow variables (surface runoff, base flow, percolation, and total streamflow). Our results show that by using multiple flow-monitoring stations and multisite calibration approaches, ecohydrological models can be useful for managing basin-extent water resources in countries of continental dimensions such as Brazil.

Using stable water isotopes to evaluate water flow and nonpoint source pollutant contributions in three southern Ontario agricultural headwater streams

AbstractImproved understanding of catchment‐scale hydrology and nutrient transport in agricultural catchments is needed. Here, the annual young water fraction is determined for three southern Ontario headwater catchments using the stable water isotope δ18O; the dominant event contributions for three streams were also determined using a two‐component isotopic hydrograph separation. On an annual average, Nissouri Creek (loamy soils, high tile drainage) sees the lowest amount of event water, followed by Big Creek (clay soils, high tile drainage) and then North Creek (clay soils, low tile drainage). Event hydrograph separations show Nissouri Creek has significantly higher median amounts of pre‐event water than Big and North Creek during events. These results in indicate soil type may be more influential than tile drainage presence with respect to the contribution of event contributions to total stream flow; specifically, higher contributions of event water occurred in the two clay soil catchments, despite differing tile presence. Antecedent moisture and event characteristics did not uniformly explain the observed pre‐event water contributions for events across all sites, with pre‐event contributions only weakly and positively correlated with discharge at event commencement and negatively with isotopic variability in stream water. The total contribution of pre‐event water during events was significantly correlated with mean event turbidity and the flow‐weighted mean concentrations of dissolved organic carbon, total phosphorus and total dissolved phosphorus, but not total nitrogen or nitrate. The correlations we observed between pre‐event water and water chemistry were stronger than between event size and water chemistry, suggesting isotopic information adds insight that simple hydrometrics are unable to provide. Our results show that event water is responsible for phosphorus loss at the watershed scale, indicating actions targeting fast pathways or targeting pools of phosphorus available to those fast pathways can aid in reducing phosphorus transported by event water.

Assessing characteristics and long-term trends in runoff and baseflow index in eastern Japan

Baseflow is the portion of streamflow derived from delayed subsurface pathways. The baseflow index (BFI) is a ratio of baseflow to total streamflow, and is an important hydrological variable when linking watershed characteristics to baseflow. The ‘smoothed minima’ procedure of baseflow separation was applied to streamflow data (29–67 years) from twenty-six gauges of watersheds in eastern Japan. The Mann-Kendall statistical test and Sen’s slope estimator were used to identify trends and estimate the rate of change in annual and seasonal runoff and BFI per decade at 0.01 and 0.05 significance levels. To the best of our knowledge, this is the first study to investigate long-term trends in runoff and BFI for watersheds in the large-scale region of eastern Japan. Results showed significant trends in annual runoff and BFI, with a concentration of significant seasonal trends occurring in winter with five gauges showing trends in runoff and nine gauges showing trends in BFI. The results suggest that the response of annual and seasonal runoff and BFI to climate change can already be seen, which implies that policymakers need more information on the impacts of climate change and human activities to manage water resources sustainably.

Grid-based calibration of the WRF-Hydro with Noah-MP model with improved groundwater and transpiration process equations

The physically-based distributed WRF-Hydro modelling system, including the Noah land surface model with multiple parameterization options (Noah-MP) and the hydrological extension of the WRF atmospheric model (Weather Research and Forecasting model), has recently been widely used for water balance investigations, streamflow and coupled land–atmosphere simulations. Despite the multiple available physical parameterizations in the model, equations for simulating particular losses from the water balance are missing, and a grid-based calibration of distributed parameters across multiple watersheds has not been studied. To fill these gaps, this study aims: (i) to analyze the impact of soil, runoff, groundwater and vegetation parameters on water balance components; (ii) to improve baseflow and transpiration equations; and (iii) to test a grid-based calibration approach for distributed model parameters, using streamflow observations. The WRF-Hydro groundwater model was improved through the introduction of a groundwater loss factor and the Jarvis stomatal conductance model was modified to account for nocturnal transpiration. The grid-based calibration was performed for three parameters (infiltration, hydraulic conductivity and percolation) for 19 spatially-distributed classes, with the Parameter Estimation (PEST) software. The study area includes 31 small mountainous watersheds (5–115 km2) in Cyprus, in the Eastern Mediterranean. A two-year period (2011–2013) was used for calibration and a five-year period (2013–2018) for the evaluation. The baseline model set-up overestimated streamflow, on average, by 50 % in 2011–2012 and more than 100 % in 2012–2013. Overall, streamflow and evapotranspiration (ET) could vary by about ±30 % from the baseline simulation, using different model parameters and model options. The simulation of groundwater losses as a function of groundwater level reduced total streamflow, on average, by 30 %. The use of the proposed Jarvis equation for nocturnal transpiration increased the total ET, on average, by 25 %. The grid-based approach facilitated the calibration of the distributed parameters over the area of the 31 watersheds. The median Nash-Sutcliff Efficiency (NSE) was 0.49 during calibration, but 0.02 in the drier evaluation period. The calibrated WRF-Hydro model reproduced the annual variability of ET and the improved groundwater and transpiration equations reduced the substantial streamflow overestimation of WRF-Hydro. The model performance during dry years demonstrated the need for representation of more processes that occur in semi-arid environments with ephemeral streams and are not included in WRF-Hydro and Noah-MP. The grid-based WRF-Hydro parameterization can be applied to the full study area for fully-coupled atmospheric-hydrologic simulations.

Can annual streamflow volumes be characterised by flood events alone?

Can total annual streamflow in any given year be largely characterised by a relatively small number of high flow events? A comprehensive assessment of this is of high value as there is evidence to suggest that as flood events increase in rarity a more consistent response between streamflow extremes and temperatures increases can be established — providing greater reliability in projections of rare events. We propose here a novel methodology to characterise streamflow regimes in the context of total annual streamflow for water supply. Using the Australian Bureau of Meteorology’s Hydrologic Reference Station database, we developed annual event flow distributions that standardise the relationship between total annual streamflow and event flows. It was found that the annual event flow distributions are primarily a function of local climate and catchment size and were largely insensitive to interannual variability represented by the El Niño Southern Oscillation Index, mean annual temperature, or total annual rainfall volume. Statistically significant trends were found in the timeseries of annual event flow distribution values, signalling a move to a less even distribution in the southern latitudes and a more even distribution in the northern latitudes. Our results show that total annual streamflows can be characterised by a small number of high flow events. This suggests that for Australia’s most critical surface drinking water supply catchments the streamflow yields can be represented by changes in a few, high flow events, independent of interannual variability. As these relationships are non-stationary, they may provide a basis for understanding changes in water supply into the future.

1,100‐Year Reconstruction of Baseflow for the Santee River, South Carolina, USA Reveals Connection to the North Atlantic Subtropical High

AbstractSince 2013, extreme floods within the Santee River basin (North/South Carolina, USA) caused $1.5B in damage. The instrumental period, however, is too short to determine if recent extreme events are anomalous within a long‐term context. Here, we present reconstructions of storm‐, base‐, and total streamflow for the Santee River using a multi‐species tree‐ring network calibrated to flow data during the period 1923–2018. Tree‐ring data explained higher variance (r = 0.59; p < 0.01; 900–2018) of instrumental baseflow than total streamflow (r = 0.41; p < 0.01; 1500–2018) or stormflow (r = 0.26; p < 0.05; 1690–2018). Our reconstruction reveals a long‐term increase in baseflow over the past millennium. The North Atlantic subtropical high regulates baseflow in the Santee River (r = 0.45; p < 0.01). Recent high levels of baseflow may be connected to the position of the subtropical high, increasing the likelihood of flooding.

A guideline for spatio‐temporal consistency in water quality modelling in rural areas

A guideline for spatio‐temporal consistency in water quality modelling in rural areas

Baseflow Index Analysis for Bengawan Solo River, Indonesia

Hydrological investigation for major Java rivers remains research challenge todays, particularly in identification of runoff characteristics situated in monsoonal climate. This study aims to investigate the value of baseflow index for Bengawan Solo river. We employed daily streamflow data for period 1980-2010 to derive baseflow index (BFI) based on the smoothed minima. We utilized different approaches comprising the non-overlapping 3 days (BFI3), 5 days (BFI5), and 7 days (BFI7) of streamflow to compute the index. We found the average BFI3, BFI5, and BFI7 for this study period are 0.67, 0.56, and 0.49, respectively. It revealed that higher number of non-overlapping days would produce lower BFI, which could be an indication of less baseflow contribution to total streamflow. Additionally, our findings show there is an increasing trend of BFI in the last decade that may be associated with decreasing forest cover in the catchment area. Furthermore, the BFI value will provide a valuable information for key leader in water sector in particular during dry season, and further research is needed to integrate this BFI into sustainable water management index.

Hybrid global gridded snow products and conceptual simulations of distributed snow budget: evaluation of different scenarios in a mountainous watershed.

Considering snowmelt in mountainous areas as the important source of streamflow, the snow accumulation/melting processes are vital for accurate simulation of the hydrological regimes. The lack of snow-related data and its uncertainties/conceptual ambiguity in snowpack modeling are the different challenges of developing hydroclimatological models. To tackle these challenges, Global Gridded Snow Products (GGSPs) are introduced, which effectively simplify the identification of the spatial characteristics of snow hydrological variables. This research aims to investigate the performance of multi-source GGSPs using multi-stage calibration strategies in hydrological modeling. The used GGSPs were Snow-Covered Area (SCA) and Snow Water Equivalent (SWE), implemented individually or jointly to calibrate an appropriate water balance model. The study area was a mountainous watershed located in Western Iran with a considerable contribution of snowmelt to the generated streamflow. The results showed that using GGSPs as complementary information in the calibration process, besides streamflow time series, could improve the modeling accuracy compared to the conventional calibration, which is only based on streamflow data. The SCA with NSE, KGE, and RMSE values varying within the ranges of 0.47–0.57, 0.54–0.65, and 4–6.88, respectively, outperformed the SWE with the corresponding metrics of 0.36–0.59, 0.47–0.60, and 5.22–7.46, respectively, in simulating the total streamflow of the watershed. In addition to the superiority of the SCA over SWE, the two-stage calibration strategy reduced the number of optimized parameters in each stage and the dependency of internal processes on the streamflow and improved the accuracy of the results compared with the conventional calibration strategy. On the other hand, the consistent contribution of snowmelt to the total generated streamflow (ranging from 0.9 to 1.47) and the ratio of snow melting to snowfall (ranging from 0.925 to 1.041) in different calibration strategies and models resulted in a reliable simulation of the model.

Stable isotope modeling of the groundwater discharge in complex watersheds of the state of São Paulo, Brazil

The increasing pressure on water resources demands integrated and multidisciplinary approaches to address environmental, scientific, and social issues related to water availability in watersheds. In large watersheds, many factors control hydrologic processes, requiring the application of a methodology able to describe water dynamics in complex situations. This study uses stable isotope (2H and 18O) modeling to characterize the groundwater contribution in an area of heterogeneous hydrogeological framework and advanced anthropization, located in the Piracicaba-Capivari-Jundiaí (PCJ) and Tietê-Jacaré (TJ) water management units – central-eastern portion of the state of São Paulo, Brazil. Groundwater dynamics are controlled by the direct interaction of the rainfall regime with hydrogeological domains. The modeling in this study indicates that some 60–80% of the total streamflow volume comes from groundwater. However, in the crystalline domain, the aquifer capacity for surplus water storage is smaller, increasing the importance of rainfall for generating direct runoff and maintaining the streamflow. For this characteristic, the PCJ unit is more dependent on surface water and vulnerable to prolonged droughts. On the other hand, in the sedimentary areas, the contribution of groundwater discharge is around 80%, showing that the aquifer storage capacity guarantees homogenization of the discharge throughout the year, and ensures water security in drought periods. It is concluded that the successful application of stable isotope modeling in large basins. The method, combined with others already established, can add a more dynamic and sensitive set of information for understanding hydrological processes in complex hydrographic basins, with heterogeneous hydrogeological structures and the effects of anthropic action.