Runoff Characteristics Research Articles

Contamination characteristics in runoff fractions from a nuclear facility in São Paulo, Brazil.

The stormwater runoff may act as a nonpoint pollutant source and contributes to aquatic ecosystem quality decay in urban environments. The aim of this work was to evaluate the runoff characteristics on the transport of total solids and total metals, as well as pH and conductivity responses during the rainfall evolution. During 2017 and 2018, 12 rain events were monitored in 4 sampling stations at a car parking lot located at Nuclear and Energy Research Institute (IPEN/CNEN) in São Paulo/Brazil. A 4-chamber integrated collector allowed the sequential/temporal runoff evolution assessment. The runoff composition, in decreasing order of quantities, was Ca > K > Mg > Si > Al > Fe > Na > Zn > Mn > Sr > Ti > Mo > V > Cu > B > Pb > Ni > Ce > Sb > Cr > La > U > Th > Cd. The amount of total solids, Al, and Fe exceeded the Brazilian water quality standards. Principal component analysis (PCA) identified the elemental clusters linked to the facility activity, soil, and traffic/atmospheric-related deposition. The results show that the runoff characteristics could be differentiated by pollutant source. Factors such as seasonal variation, rain event intensity, air mass from oceanic or continental origin, spatial distribution inside the monitoring area, and the intensity of the first flush must be considered in order to disentangle the elemental clusters and pollution source contributions. In winter, continental air masses were associated with higher concentrations of heavy metals in the surface runoff. Spatial changes with no seasonal variation were observed for U, Th, La, and Ce.

Runoff retention characteristics of forested and deforested catchments: an analysis using a spatially lumped model

ABSTRACT This study investigates the runoff characteristics of forested and deforested catchments using the Soil Conservation Services–curve number (SCS-CN) model from the perspective of the Kerala floods in 2018 and 2019. The forested and deforested catchments chosen for the study are the drainage area of the Kakkayam Dam and Punoor River respectively of Kozhikode District, Kerala. The study used input variables such as rainfall, land use/land cover (LU/LC) and soil data to estimate the runoff depth from these catchments during the floods in 2018 and 2019 using the SCS-CN model. Here, the hydrological response of these catchments is examined by different scenarios of rainfall and LU/LC change. It is found that the deforested catchment generates more runoff compared to the forested catchment under identical rainfall conditions. However, the study shows that, the runoff depth in the deforested catchment is expected to reduce if certain portion of plantations and barren land converts into the forest cover. The ability of runoff retention of the forested catchment is expected to lose if the forest-covered land is utilized for the plantation activities.

Striking a Balance between Conservation and Development: A Geospatial Approach to Watershed Prioritisation in the Himalayan Basin

This study was undertaken in the Himalayan basin, in the river Lohawati, Uttarakhand, to study its hydro-morphological characteristics and prioritise the watersheds using geospatial tools. Advanced Spaceborne Thermal Emission and Reflection (ASTER-30 m) data and the Survey of India’s topographic sheets were used to analyse the study area comprehensively. Nine watersheds were identified within the basin in order to calculate the hydro-morphological characteristics in terms of basic, shape, texture, and relief aspects. The basin was identified as being elongated, with a total drainage area of 337.48 km2. The interaction between the terrain, rock formations, and precipitation levels produced a branching structure in the areas drainage system that ranged from dendritic to sub-dendritic. The basin had been classified as a fifth-order basin, comprising a network of 500 stream segments spanning a total length of 492.41 km. In each of the watersheds, the primary streams are of the first order, followed by those of the second order, and so forth. The physiography and lithology of the basin have a significant influence on this pattern. The calculated elongation ratio, circulatory ratio, form factor, shape index, and shape factor ranged from 0.57 to 0.80, 0.35 to 0.64, 0.26 to 0.50, 1.98 to 3.89, and 0.57 to 1.77, respectively. These values indicate that watersheds are elongated, suggesting moderate lag times. The parameters, including drainage density (0.98 to 1.62), stream frequency (1.07 to 1.59), infiltration number (1.04 to 2.59), drainage texture (0.67 to 2.82), and drainage intensity (0.93 to 1.12), pointed towards the coarser drainage texture, higher infiltration, and minimal runoff characteristics of the basin. In light of the relief characteristics of the basin, a higher basin relief, relief ratio, and relative relief were observed for the watersheds, indicating the possibility of higher erosion and deforestation rates. Using the Weighted Sum Analysis (WSA) method, the computed factors were utilised to rank the watersheds based on their potential for erosion. Based on the WSA approach, watersheds were classified into high-, moderate-, and low-prioritisation zones. This further indicates that 36.14% (121.95 km2) of watersheds are in the high-priority zone, and that 48.84% (164.91 km2) and 15.00% (50.62 km2) of watersheds are in the moderate- and low-priority zones, respectively. The WSA is a practical strategy to prioritise watersheds when making appropriate decisions.

Stochastic Generation of Plausible Hydroclimate Futures Using Climate Teleconnections for Southeastern Australia

Abstract Generating plausible future climate time series is needed for bottom-up climate impact modeling, as well as downscaling climate model output for hydrological applications. A novel method for generating multisite daily stochastic climate series is developed based on 1) linear regression between climate teleconnection time series (e.g., IPO/SOI) and annual rainfall, 2) clustered method of fragments for subannual disaggregation, and 3) a regression-based approach to daily potential evapotranspiration (PET) for hydrological modeling. We demonstrate that bias (i.e., oversampling) occurs with the standard method of fragments disaggregation in the multisite context and show that selection of an analog year from clustered rainfall amounts provides better sampling properties than the standard method of fragments. Using hydrological data for southeastern Australia, we model runoff from observed and simulated rainfall and PET using the GR4J (Génie Rural à 4 paramètres Journalier) model. Simulated annual and daily rainfall and runoff characteristics from the new method are similar to existing methods, with improvements demonstrated in wet–wet transition probabilities and spatial (between-site) correlations. Significance Statement In this paper we develop a novel method for generating multisite daily stochastic climate series regressing climate teleconnections (e.g., ENSO, IPO) to annual site rainfall, and disaggregation using a clustered version of the method of fragments. The modular nature of the method also allows for the possibility of the generation of replicates from GCM output of climate teleconnections, as well as perturbed climate futures for scenario-neutral modeling. Results demonstrate that rainfall and runoff metrics of interest for water resource modeling are reproduced well using the model.

Lithologic Controls on Parameters of Conceptual Rainfall–Runoff Model and Runoff Characteristics: A Case Study of the Xinanjiang Model

Lithologic Controls on Parameters of Conceptual Rainfall–Runoff Model and Runoff Characteristics: A Case Study of the Xinanjiang Model

Runoff and sediment characteristics of a typical watershed after continuous soil erosion control in the red soil region of Southern China

To investigate the runoff and sediment characteristics of the watershed after continuous soil erosion control in the red soil region of southern China, hydrological data were collected from 2013 to 2020 in the Zhuxi watershed, which is located in the southeast of the red soil region. The results showed that the monthly suspended sediment concentration and annual sediment yield have significantly decreased since 2017. At the event scale, 180 floods were classified into four flood patterns (A, B, C and D) by the K-medoids clustering method based on the flood duration, runoff depth and peak discharge. Each flood pattern resulted in differing levels of the event sediment yield (D > C > B > A), and Pattern C contributed the most to runoff and sediment yield. The study period was divided into two stages according to the annual sediment yield. Compared with 2013–2016, the total runoff and sediment yield of the 3 major flood patterns (A, B and C) in 2017–2020 decreased by 17.88%∼25.12% and 78.92%∼90.34%, respectively. These flood patterns decreased not only in frequency but also in suspended sediment concentration, which was caused by the changes in the runoff-sediment relationships of flood events. Six types of suspended sediment concentration and discharge (SSC-Q) relations appeared in the flood events, indicating that the sediment sources and sediment transport processes were complex and dynamic. In 2017–2020, the single-valued relation became the dominant type of SSC-Q relations for all flood patterns, which suggests that the sediment supply was inhibited. The results provide a more comprehensive understanding of the runoff and sediment processes of a watershed after continuous soil erosion control, which is beneficial for revealing the development of soil erosion in the red soil region of southern China.

Hydrochemical Characteristics and Formation Causes of Ground Karst Water Systems in Gudui Spring Catchment

As one of the famous karst springs in Shanxi Province, the Gudui spring is the only medium-low temperature hot spring, with a long history of development and a rich cultural accumulation. The karst groundwater in the Gudui spring catchment was taken as the research object. Through systematic sample collection and isotope analysis, hydrochemistry (Durov map, ion ratio, Gibbs map, and hydrogen and oxygen isotope) methods were comprehensively used to analyze groundwater hydrochemistry and groundwater system runoff characteristics. The87Sr/86Sr value of karst groundwater in the Gudui spring catchment was 0.709 to 0.717, and the Mg/(Mg+Ca) value was 0.27 to 0.74. By analyzing the Sr isotope composition and Mg/(Mg+Ca) and 1/Sr variation characteristics, it was concluded that the karst groundwater in the Gudui spring catchment was a mixture of deep hot water and shallow cold water. The karst water subsystem of Nanliang spring presented the characteristics of carbonate stratum runoff. The karst water subsystem of Fuling Mountain Gaoxian Haitou spring and the deep circulation subsystem of Houma Basin exhibited the runoff characteristics of carbonate rock and igneous rock strata. The karst water subsystem of Taiershan Jiuyuanshan Gudui spring presented the runoff characteristics of carbonate rock and ancient silicoaluminate strata. The δ18O value in karst groundwater of Guodui spring area ranged from -11.46‰ to -7.81‰, and the average value was -10.08‰. The range of the δD value was -83.7‰ to -60.8‰, and the average value was -73.6‰. This showed that karst groundwater in the spring area was the result of mixing of various types of water. Through comparative analysis of hydrogen and oxygen isotopes of 2014 and 2021 sampling points at the same location, it was concluded that the change in water samples at the Guduiquan resulted from the gradual accumulation of water supplied by Sanquan Reservoir. The change in Sanquan Reservoir was due to the influence of Yellow River diversion. The karst groundwater in the spring area were characterized by large calcium ion, magnesium ion, and sodium ion values; a small potassium ion value; a large sulfate value; and a small chloride value. The hydrochemical types of karst groundwater in Gudui spring catchment could be divided into SO4-Na, SO4-Ca, HCO3-Na, HCO3-Mg, HCO3-Ca, and Cl-Na. The hydrochemical types of karst groundwater showed evident hydrochemical composition zoning from HCO3-Ca·Mg→HCO3·SO4-Ca·Mg→SO4·HCO3-Na·Ca→SO4·Cl-Na·Ca. According to the comprehensive analysis of hydrochemical isotope and hydrogeological conditions, the karst water subsystem of Nanliang spring was primarily recharged by rainfall infiltration in the exposed limestone area and river infiltration, and its karst groundwater was recharged by runoff from south to north to the karst water subsystem of Fuling Mountain Gaoxian Haitou spring and the deep circulation subsystem of Houma Basin. The karst water subsystem of Taier Jiuyuan Mountain Gudui spring received rainfall infiltration supplement and upstream runoff supplement from the exposed limestone area. Its karst groundwater flowed from north to south and received the supply of Sanquan Reservoir from Yellow River water in the natural discharge area of Gudui spring.

Monthly runoff prediction using the VMD-LSTM-Transformer hybrid model: a case study of the Miyun Reservoir in Beijing

Abstract Accurate runoff prediction is of great significance for flood prevention and mitigation, agricultural irrigation, and reservoir scheduling in watersheds. To address the strong non-linear and non-stationary characteristics of runoff series, a hybrid model of monthly runoff prediction, variational mode decomposition (VMD)–long short-term memory (LSTM)–Transformer, is proposed. Firstly, VMD is used to decompose the runoff series into multiple modal components, and the sample entropy of each modal component is calculated and divided into high-frequency and low-frequency components. The LSTM model is then used to predict the high-frequency components and the transformer to predict the low-frequency components. Finally, the prediction results are summed to obtain the final prediction results. The Mann–Kendall trend test method is used to analyze the runoff characteristics of the Miyun Reservoir, and the constructed VMD–LSTM–Transformer model is used to forecast the runoff of the Miyun Reservoir. The prediction results are compared and evaluated with those of VMD–LSTM, VMD–Transformer, empirical mode decomposition (EMD)–LSTM–Transformer, and empirical mode decomposition (EMD)–LSTM models. The results show that the Nash–Sutcliffe efficiency coefficient (NSE) value of this model is 0.976, mean absolute error (MAE) is 0.206 × 107 m3, mean absolute percentage error (MAPE) is 0.381%, and root mean squared error (RMSE) is 0.411 × 107 m3, all of which are better than other models, indicating that the VMD–LSTM–Transformer model has higher prediction accuracy and can be applied to runoff prediction in the actual study area.

Study on hydrological response of runoff to land use change in the Jing River Basin, China.

Land use change greatly affects the runoff characteristics of the basin, which in turn affects the distribution of surface water and groundwater in the region. Quantitative analyses of the hydrological response of watershed runoff to land use change are conducive to the formulation of sustainable water resource strategies. In this paper, the impact of land use change on runoff characteristics in the Jing River Basin was evaluated using the SWAT model, the land use pattern of the Jing River Basin in 2040 was predicted using CA-Markov model, and five land use change scenarios were set up in combination with the trend of land use transfer, and the response relationship between land use change and runoff hydrological characteristics in the basin was studied. The results show that the land use changes reduce runoff and change the hydrological cycle process of the basin. The hydrological response of different land use types varies significantly, but only has a less impact on annual runoff. Farmland has a promoting effect on production flow; woodland and grassland are not conducive to the formation of surface runoff and will increase underground runoff and evapotranspiration in the basin. The increase in vegetation coverage after returning farmland to woodlands and grasslands has reduced surface runoff, increased the recharge of groundwater, and played a positive role in ecological restoration in the river basin. The research results are of great significance for understanding the hydrological consequences of land use change and the rational planning of land use patterns in river basins.

Analysis of the Source Tracing and Pollution Characteristics of Rainfall Runoff in Adjacent New and Old Urban Areas

This study aimed to examine the pollution characteristics of rainfall runoff as well as the runoff scouring effect and pollution traceability in adjacent new and old urban areas. The sampling and monitoring of rainfall runoff for different rainfall underlying surfaces were conducted for roads, green spaces, roofs, and a food market. The concentration of chemical oxygen demand (COD) and nutrients in the rainfall runoff of the market area was higher than that measured for roads, green spaces, and roofs. The initial scouring effect of each underlying surface was obvious during rainstorms, and 30% of the runoff transported nearly 50% of the pollutants. Further, 30% of the runoff transported about 30% of the pollutants under moderate and heavy rain conditions, and the overall initial scouring effect was not obvious. The results of this study showed that, as a considered underlying surface area, the market and possibly other similar service facilities had a significant impact on the calculation of runoff pollution load, and these should be included in the research scope of rainfall runoff and the impact of underlying surfaces. The purpose of this study was to provide reliable and practical information for water pollution prevention and control, especially for pollution prevention and control of rainfall runoff in areas where new and old urban parts of cities exist side by side.

Geomorphometric based catchment runoff characterization and assessment of temporal landuse change impact on runoff inflow to an ungauged reservoir under different climatic scenarios using geospatial techniques and SWAT model

Abstract A morphometric analysis was carried out to study runoff characteristics of the Saleran reservoir catchment. Further, the impact of catchment landuse change on runoff generation and inflow to the Saleran reservoir has been assessed using geospatial techniques and SWAT. The geomorphometric analysis shows that the catchment is less elongated in shape, having fourth-order stream network, high stream frequency (9.36 no./km2), drainage density (4.55 km/km2) and high relief (220 m), which indicates that catchment would generate a moderate amount of runoff. The SWAT (ArcSWAT) model was used for the simulation of runoff and the average annual runoff inflow was simulated to be 14.2 mm (1995–1999), 13.2 mm (2000–2009) and 11.8 mm (2010–2019) per 100 mm of rainfall under the landuse 1999, 2009 and 2019, respectively. The results indicated that the temporal change in catchment landuse has significantly increased the runoff generation and its inflow to the reservoir but there is a decrease in the volume of runoff inflow which may be due to the decreasing trend in monsoon rainfall. Hence, an appropriate conservation strategy needs to be developed and adopted in the Shivalik foot-hills for managing the catchment landuse for sustainable water supply through reservoirs.

The role of previously glaciated landscapes in spatiotemporal variability of streamflow in snow-dominated watersheds: British Columbia, Canada

Study regionTwenty-six glaciated basins on the Interior Plateau (56° N, 125° W) in British Columbia, Canada. Study focusLandscape and streamflow characteristics in glaciated basins show high spatiotemporal variability, while the linkages among runoff characteristics, landscapes, and glacial history remain unclear. We compiled a 10-year dataset of daily climate and streamflow observations, and 54 landscape attributes for 26 glaciated basins to explore the relationship between landscape, streamflow and glacial history. A Hierarchical Multiple Factor Analysis was performed to analyze landscapes. The hydrological signatures were selected to describe streamflow characteristics. A correlation analysis and machine learning models were used to explore the relationships between the glacial legacy and streamflow variation. New hydrological insights for the region(1)The landscape is well-structured. The principal components of PC1 and PC2 explain 44% of the total landscape variance, PC1 representing basins with steep, high-relief terrain and alpine glaciation and PC2 representing large, elongated basins with moraine and glacial lakes; (2) The landscape heterogeneity has a key role in accurate streamflow predictions. Most hydrological signatures are controlled by landscape components PC1 and PC2 and can be well predicted by Random Forest using landscape features as inputs. (3) Alpine glaciation results in rapid runoff generation and variable flow regime in mountains, while valley glaciation leads to smooth hydrographs with large baseflows and mild and infrequent extreme flow events in plateaus.

Cold Season Rain Event Has Impact on Greenland's Firn Layer Comparable to Entire Summer Melt Season

AbstractRainfall high on the Greenland Ice Sheet is an emerging phenomenon with consequences for the thermal and structural makeup of the surface layer. We document changes to Greenland's firn column due to a 4‐day cold‐season warm/rain event. Heavy precipitation occurred with a sudden 30°C increase in air temperature, reaching 0°C at 2,000 m elevation. Thermistor strings within the firn layer across a 35 km transect show rapid warming of 6°–23°C reaching depths of 2–10 m. Antecedent conditions governed the magnitude, duration, and depth‐distribution of sensible and latent heat added to the firn column. Heat fluxes from the firn layer required up to 8 weeks to recover to baseline, a significant fraction of the winter period. The amount of liquid water refrozen in the firn column was ∼20%–100% of the prior summer demonstrating the impact of extreme weather events on the ice sheet's evolution and runoff characteristics.

Evolution Characteristics of Rainfall and Runoff in the Upper Reaches of Zhang River Basin

It is of great significance to study and analyze the surface water resources and their change trend in the groundwater overexploitation area of the North China Plain, which is of great significance to solve the shortage of water resources in the groundwater overexploitation area of the North China Plain, promote the exploitation of groundwater, and realize the sustainable development of water resources. This paper takes Minyou Irrigation District of Handan City, a typical overexploitation area in the North China Plain, as an example. Based on the measured rainfall and runoff data from 1957 to 2020, the Mann–Kendall trend test, cumulative anomaly method, double cumulative curve method, and Morlet wavelet transform were used to analyze and predict the trend of water resources in the irrigation area and the individual contribution of climate change and human activities to runoff change. The results show that the annual rainfall and annual runoff in the irrigation area have a significant downward trend and significant cyclical changes throughout the study period. In 1977, the annual runoff showed a sudden change, and the average contribution rates of climate change and human activities to its change were 40.55% and 59.46%, respectively. In the future (2020–2035), runoff will remain stable and rainfall will show an increasing trend. The research results can provide scientific reference for the development, utilization, and rational allocation of surface water resources in the groundwater overexploitation area of the North China Plain.

Simulating Runoff Regime in a Glaciated High-Mountainous Basin: A Case Study of the Baksan River (Caucasus, Russia)

The water resources of the North Caucasus depend mostly on the state of glaciers, which have been intensely losing their mass in the recent decades against the background of climate changes. The deglaciation leads not only to a decrease in the glacier runoff of mountain rivers, but also to changes in the annual distribution of runoff. The focus of this study is the adaptation of ECOMAG software complex to simulating river runoff in the Baksan River basin based on data on the relief and underlying surface of the drainage basin (soil, vegetation) and daily data on the surface air temperature, air saturation deficit, and precipitation. The calibration and validation of the model and the statistical estimate of calculation efficiency were based on the data on water discharges in the Baksan River over 2000–2017. The developed model of runoff formation in the Baksan River basin was used to carry out numerical experiments for assessing the sensitivity of runoff characteristics to glacier area variations. Depending on the rate of deglaciation process, the runoff of the Baksan River can drop by 10–30% because of a decrease in its glacial component, and the maximal water discharges can drop by 10–15%.

River Runoff in European Russia under Global Warming by 1.5 and 2 Degrees

The ECOMAG hydrological model was used to evaluate runoff characteristics in the basins of the major rivers in European Russia: the Volga, Don, Northern Dvina, Pechora, and Kuban. The models of runoff formation for various hydrometric gauging stations in these basins were calibrated using data of weather station observations. Next, the input data were represented by the data of an ensemble of global climate models for assessing the regional hydrometeorological regime at the realization of a scenario of global warming by 1.5 and 2°C in the XXI century relative to the preindustrial values. The reproduction of the annual and seasonal runoff by data of climatic models was evaluated by comparison with observation data. According to the results of numerical experiments at global warming by 1.5 and 2°C, the values of the relative changes in river runoff in European Russia increase from N to S and from E to W, i.e., the hydrological systems under milder climate were found to be more sensitive to changes in the meteorological characteristics. The estimation of runoff anomalies in the European Russia showed the following common features: an increase in the winter runoff in the northern rivers and in the Volga basin, a decrease in the spring snowmelt runoff in the Northern Dvina, Volga, and Don, a decrease in the summer–autumn runoff of all studied rivers with various intensity. In this case, the annual runoff of the Pechora will show a positive trend, and that of the Northern Dvina, Volga, Don, and Kuban, a negative trend.

Recognition and Prediction of Collaborative Response Characteristics of Runoff and Permafrost to Climate Changes in the Headwaters of the Yellow River

As a response to climate changes, permafrost has deteriorated and the hydrologic process has undergone significant alterations in high-cold regions. The response mechanism still remains unknown. The characteristic contribution was calculated using the random forest (RF) algorithm, AdaBoost algorithm, and gradient-boosted decision tree (GBDT) algorithm. A comprehensive evaluation model was constructed to evaluate the contribution of climate changes to the headwaters of the Yellow River and the influence of permafrost degradation as well as climate-permafrost cooperation on runoff changes. The selected characteristic vectors were chosen as datasets for the support vector machine (SVM) and RF algorithms. A model was constructed for the prediction of permafrost degradation and runoff changes based on climate data. Results demonstrated that climate variables influencing the mean depth-to-permafrost table (DPT) were ranked according to their contributions: air temperature > evapotranspiration > wind speed > relative humidity (RHU) > sunshine duration > precipitation. The descending rank of climate and permafrost variables according to their contributions to runoff was the following: precipitation > sunshine duration > permafrost coverage > evapotranspiration > relative humidity (RHU) > mean DPT > wind speed > maximum DPT > air temperature. The model demonstrated good prediction results. The outputs can provide scientific references in applications related to water resources and the protection of ecologically vulnerable areas in high-cold regions.

Key influence of hydrogeological, geochemical, and geological structure factors on runoff characteristics in karst catchments

Lithology, dissolution degree, and other geological factors are essential factors affecting karst environments. However, the complex effects of multiple geologic factors on runoff characteristics have not been well quantified in karst catchments. Thus, 30 catchments and four runoff characteristics (runoff coefficient, runoff modulus, annual runoff extremes ratio, and annual runoff variation coefficient) were selected in this study to evaluate the influence of geological factors on runoff characteristics in karst catchments. The linear mixed effect model was used to quantitatively evaluate the contribution rate of each factor to the runoff characteristics, and the structural equation model was used to analyze the quantitative relationship between each factor and the runoff characteristics. The results show that among the three aspects of geological factors, hydrogeological factors have the greatest influence on runoff characteristic values. In turn, the density of sinkhole is the most influential factor among the hydrogeological factors. Geological structure factors had both direct and indirect effects on runoff characteristics (path coefficient is 0.27). Among them, the density of faults is the most influential factor. Geochemical factors affected runoff characteristics more by influencing hydrogeological factors (path coefficient −0.51) or geological structure factors (path coefficient −0.43). In conclusion, data from several watersheds directly confirm that in karst watersheds, these geological factors such as hydrogeology, geochemistry, and geological structure have a very fundamental influence on karst watershed runoff characteristics. Our results can help us further understand karst hydrological processes and improve the accuracy of karst hydrological modeling.

Estimation of Surface-Subsurface Water Balance in Lower Tapi River Basin Using Gridded Data and Station-Based Observed Data

ABSTRACT Water is an essential resource. An understanding of catchment water balance is crucial to ensure water availability in the region. Hydrological models are credible tools for water balance assessment of a region. These models are data intensive. The traditional hydrological modeling approach relies on station-based observed data. The availability of sufficient long-term consistent observed data is often limited. On the other hand, climate reanalysis data for a long timeperiod is available from multiple data sources. This study estimates runoff characteristics for Lower Tapi River Basin in western India, with the help of a Soil Conservation Service Curve Number method. The catchment water balance in terms of runoff, baseflow, and recharge at sub-basin scale is worked out with the help of station-based and climate reanalysis datasets. The model output are calibrated against observed river gauging data. A reasonable fit between model-simulated and observed runoff is obtained in terms of duration and magnitude of runoff peak. Tested model is applied to future climate scenarios. The simulations show an increase in surface runoff, recharge, baseflow and total runoff for future time period. Results reveal that climate changes have significant impact on hydrology of the basin.

Multivariate analysis of rainfall–runoff characteristics using copulas

Multivariate analysis of rainfall–runoff characteristics using copulas