scholarly journals Hydrological recurrence as a measure for large river basin classification and process understanding

2015 ◽  
Vol 19 (4) ◽  
pp. 1919-1942 ◽  
Author(s):  
R. Fernandez ◽  
T. Sayama
Keyword(s):  
River Basin ◽  
River Basins ◽  
Global Scale ◽  
Hydrologic Model ◽  
Surface Model ◽  
Data Set ◽  
Arctic Regions ◽  
Monthly Scale ◽  
Monsoon Area ◽  
Hydrological Variable

Abstract. Hydrological functions of river basins are summarized as collection, storage and discharge, which can be characterized by the dynamics of hydrological variables including precipitation, evaporation, storage and runoff. The temporal patterns of each variable can be indicators of the functionality of a basin. In this paper we introduce a measure to quantify the degree of similarity in intra-annual variations at monthly scale at different years for the four main variables. We introduce this measure under the term of recurrence and define it as the degree to which a monthly hydrological variable returns to the same state in subsequent years. The degree of recurrence in runoff is important not only for the management of water resources but also for the understanding of hydrologic processes, especially in terms of how the other three variables determine the recurrence in runoff. The main objective of this paper is to propose a simple hydrologic classification framework applicable to large basins at global scale based on the combinations of recurrence in the four variables using a monthly scale time series. We evaluate it with lagged autocorrelation (AC), fast Fourier transforms (FFT) and Colwell's indices of variables obtained from the EU-WATCH data set, which is composed of eight global hydrologic model (GHM) and land surface model (LSM) outputs. By setting a threshold to define high or low recurrence in the four variables, we classify each river basin into 16 possible classes. The overview of recurrence patterns at global scale suggested that precipitation is recurrent mainly in the humid tropics, Asian monsoon area and part of higher latitudes with an oceanic influence. Recurrence in evaporation was mainly dependent on the seasonality of energy availability, typically high in the tropics, temperate and sub-arctic regions. Recurrence in storage at higher latitudes depends on energy/water balances and snow, while that in runoff is mostly affected by the different combinations of these three variables. According to the river basin classification, 10 out of the 16 possible classes were present in the 35 largest river basins in the world. In the humid tropic region, the basins belong to a class with high recurrence in all the variables, while in the subtropical region many of the river basins have low recurrence. In the temperate region, the energy limited or water limited in summer characterizes the recurrence in storage, but runoff exhibits generally low recurrence due to the low recurrence in precipitation. In the sub-arctic and arctic regions, the amount of snow also influences the classes; more snow yields higher recurrence in storage and runoff. Our proposed framework follows a simple methodology that can aid in grouping river basins with similar characteristics of water, energy and storage cycles. The framework is applicable at different scales with different data sets to provide useful insights into the understanding of hydrologic regimes based on the classification.

scholarly journals Hydrological recurrence as a measure for large river basin classification and process understanding

2014 ◽  
Vol 11 (7) ◽  
pp. 8191-8238 ◽  
Author(s):  
R. Fernandez ◽  
T. Sayama
Keyword(s):  
River Basin ◽  
Land Surface ◽  
Fourier Transforms ◽  
Land Surface Model ◽  
Arctic Region ◽  
River Basins ◽  
Large River ◽  
Global Scale ◽  
Surface Model ◽  
Monsoon Area

Abstract. Hydrologic functions of river basins are summarized as water collection, storage and discharge, which can be characterized by the dynamics of hydrological variables including precipitation, evaporation, storage and runoff. In some situations these four variables behave more in a recurrent manner by repeating in a similar range year after year or in other situations they exhibit more randomness with higher variations year by year. The degree of recurrence in runoff is important not only for water resources management but also for hydrologic process understandings, especially in terms of how the other three variables determine the degree of recurrence in runoff. The main objective of this paper is to propose a simple hydrologic classification framework applicable to global scale and large basins based on the combinations of recurrence in the four variables. We evaluate it by Lagged Autocorrelation, Fast Fourier Transforms and Colwell's Indices of variables obtained from EU-WATCH dataset composed by eight hydrologic and land surface model outputs. By setting a threshold to define high or low recurrence in the four variables, we classify each river basin into 16 possible classes. The overview of recurrence patterns at global scale suggested that precipitation is recurrent mainly in the humid tropics, Asian Monsoon area and part of higher latitudes with oceanic influence. Recurrence in evaporation was mainly dependent on the seasonality of energy availability, typically high in the tropics, temperate and subarctic regions. Recurrence in storage at higher latitudes depends on energy/water balances and snow, while that in runoff is mostly affected by the different combinations of these three variables. According to the river basin classification 10 out of the 16 possible classes were present in the 35 largest river basins in the world. In humid tropic region, the basins belong to a class with high recurrence in all the variables, while in subtropical region many of the river basins have low recurrence. In temperate region, the energy limited or water limited in summer characterizes the recurrence in storage, but runoff exhibits generally low recurrence due to the low recurrence in precipitation. In the subarctic and arctic region, the amount of snow also influences the classes; more snow yields higher recurrence in storage and runoff. Our proposed framework follows a simple methodology that can aid in grouping river basins with similar characteristics of water, energy and storage cycles. The framework is applicable at different scales with different datasets to provide useful insights into the understanding of hydrologic regimes based on the classification.

scholarly journals Are General Circulation Models Ready for Operational Streamflow Forecasting for Water Management in the Ganges and Brahmaputra River Basins?

2015 ◽  
Vol 17 (1) ◽  
pp. 195-210 ◽  
Author(s):  
Safat Sikder ◽  
Xiaodong Chen ◽  
Faisal Hossain ◽  
Jason B. Roberts ◽  
Franklin Robertson ◽  
...  
Keyword(s):  
Water Management ◽  
River Basins ◽  
Hydrologic Model ◽  
Streamflow Forecasting ◽  
Management Decisions ◽  
Brahmaputra River ◽  
Ganges Basin ◽  
Monthly Scale ◽  
Brahmaputra Basin ◽  
The Ganges

Abstract This study asks the question of whether GCMs are ready to be operationalized for streamflow forecasting in South Asian river basins, and if so, at what temporal scales and for which water management decisions are they likely to be relevant? The authors focused on the Ganges, Brahmaputra, and Meghna basins for which there is a gridded hydrologic model calibrated for the 2002–10 period. The North American Multimodel Ensemble (NMME) suite of eight GCM hindcasts was applied to generate precipitation forecasts for each month of the 1982–2012 (30 year) period at up to 6 months of lead time, which were then downscaled according to the bias-corrected statistical downscaling (BCSD) procedure to daily time steps. A global retrospective forcing dataset was used for this downscaling procedure. The study clearly revealed that a regionally consistent forcing for BCSD, which is currently unavailable for the region, is one of the primary conditions to realize reasonable skill in streamflow forecasting. In terms of relative RMSE (normalized by reference flow obtained from the global retrospective forcings used in downscaling), streamflow forecast uncertainty (RMSE) was found to be 38%–50% at monthly scale and 22%–35% at seasonal (3 monthly) scale. The Ganges River (regulated) experienced higher uncertainty than the Brahmaputra River (unregulated). In terms of anomaly correlation coefficient (ACC), the streamflow forecasting at seasonal (3 monthly) scale was found to have less uncertainty (>0.3) than at monthly scale (<0.25). The forecast skill in the Brahmaputra basin showed more improvement when the time horizon was aggregated from monthly to seasonal than the Ganges basin. Finally, the skill assessment for the individual seasons revealed that the flow forecasting using NMME data had less uncertainty during monsoon season (July–September) in the Brahmaputra basin and in postmonsoon season (October–December) in the Ganges basin. Overall, the study indicated that GCMs can have value for management decisions only at seasonal or annual water balance applications at best if appropriate historical forcings are used in downscaling. The take-home message of this study is that GCMs are not yet ready for prime-time operationalization for a wide variety of multiscale water management decisions for the Ganges and Brahmaputra River basins.

scholarly journals Climate change impact on streamflow in large-scale river basins: projections and their uncertainties sourced from GCMs and RCP scenarios

2018 ◽  
Vol 379 ◽  
pp. 139-144 ◽  
Author(s):  
Olga N. Nasonova ◽  
Yeugeniy M. Gusev ◽  
Evgeny E. Kovalev ◽  
Georgy V. Ayzel
Keyword(s):  
Climate Change ◽  
River Runoff ◽  
Climate Change Impact ◽  
Large Scale ◽  
River Basins ◽  
Surface Model ◽  
Second Phase ◽  
Rcp Scenarios ◽  
Data Set ◽  
Change Impact

Abstract. Climate change impact on river runoff was investigated within the framework of the second phase of the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP2) using a physically-based land surface model Soil Water – Atmosphere – Plants (SWAP) (developed in the Institute of Water Problems of the Russian Academy of Sciences) and meteorological projections (for 2006–2099) simulated by five General Circulation Models (GCMs) (including GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, and NorESM1-M) for each of four Representative Concentration Pathway (RCP) scenarios (RCP2.6, RCP4.5, RCP6.0, and RCP8.5). Eleven large-scale river basins were used in this study. First of all, SWAP was calibrated and validated against monthly values of measured river runoff with making use of forcing data from the WATCH data set and all GCMs' projections were bias-corrected to the WATCH. Then, for each basin, 20 projections of possible changes in river runoff during the 21st century were simulated by SWAP. Analysis of the obtained hydrological projections allowed us to estimate their uncertainties resulted from application of different GCMs and RCP scenarios. On the average, the contribution of different GCMs to the uncertainty of the projected river runoff is nearly twice larger than the contribution of RCP scenarios. At the same time the contribution of GCMs slightly decreases with time.

Langat River Basin Hydrologic Model Using Integrated GIS and ArcSWAT Interface

2014 ◽  
Vol 567 ◽  
pp. 86-91 ◽  
Author(s):  
Mohd Fozi Ali ◽  
Nor Faiza Abd Rahman ◽  
Khairi Khalid ◽  
Nguyen Duy Liem
Keyword(s):  
River Basin ◽  
Stream Flow ◽  
Historical Data ◽  
River Basins ◽  
Hydrologic Model ◽  
Economic Activities ◽  
Gis Technology ◽  
Current State ◽  
Langat River ◽  
Gis Interface

Increase of socio-economic activities in the urban area has led to many water scarcity problems. Thus, the need to investigate the current state of Langat river is increasing. An integrative computational model, ArcSWAT with GIS interface was being used to predict daily stream flow of the study area. Historical data from years 1999 to 2010 was used for modeling purposes. The results reviewed that the calibrated model is able to simulate the flow for the river basin successfully with the R2 = 0.64 and Nash-Sutcliffe Index, NSI= 0.64. The results proved that GIS technology and ArcSWAT model is capable for simulating the stream flow in the Langat river basin and can be applied for other river basins. This shows that SWAT can be a tool for a hydrologic modeling in Malaysia in the future.

Regional Parameter Estimation of the VIC Land Surface Model: Methodology and Application to River Basins in China

2007 ◽  
Vol 8 (3) ◽  
pp. 447-468 ◽  
Author(s):  
Zhenghui Xie ◽  
Fei Yuan ◽  
Qingyun Duan ◽  
Jing Zheng ◽  
Miaoling Liang ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
River Basin ◽  
Land Surface ◽  
Land Surface Model ◽  
River Basins ◽  
Large River ◽  
Surface Model ◽  
Parameter Estimates ◽  
Climatic Zones ◽  
Streamflow Simulation

Abstract This paper presents a methodology for regional parameter estimation of the three-layer Variable Infiltration Capacity (VIC-3L) land surface model with the goal of improving the streamflow simulation for river basins in China. This methodology is designed to obtain model parameter estimates from a limited number of calibrated basins and then regionalize them to uncalibrated basins based on climate characteristics and large river basin domains, and ultimately to continental China. Fourteen basins from different climatic zones and large river basins were chosen for model calibration. For each of these basins, seven runoff-related model parameters were calibrated using a systematic manual calibration approach. These calibrated parameters were then transferred within the climate and large river basin zones or climatic zones to the uncalibrated basins. To test the efficiency of the parameter regionalization method, a verification study was conducted on 19 independent river basins in China. Overall, the regionalized parameters, when evaluated against the a priori parameter estimates, were able to reduce the model bias by 0.4%–249.8% and relative root-mean-squared error by 0.2%–119.1% and increase the Nash–Sutcliffe efficiency of the streamflow simulation by 1.9%–31.7% for most of the tested basins. The transferred parameters were then used to perform a hydrological simulation over all of China so as to test the applicability of the regionalized parameters on a continental scale. The continental simulation results agree well with the observations at regional scales, indicating that the tested regionalization method is a promising scheme for parameter estimation for ungauged basins in China.

scholarly journals Evaluating the streamflow simulation capability of PERSIANN-CDR daily rainfall products in two river basins on the Tibetan Plateau

2017 ◽  
Vol 21 (1) ◽  
pp. 169-181 ◽  
Author(s):  
Xiaomang Liu ◽  
Tiantian Yang ◽  
Koulin Hsu ◽  
Changming Liu ◽  
Soroosh Sorooshian
Keyword(s):  
Tibetan Plateau ◽  
River Basin ◽  
Yangtze River ◽  
Yellow River ◽  
Yangtze River Basin ◽  
Information Source ◽  
River Basins ◽  
Hydrologic Model ◽  
The Tibetan Plateau ◽  
Streamflow Simulation

Abstract. On the Tibetan Plateau, the limited ground-based rainfall information owing to a harsh environment has brought great challenges to hydrological studies. Satellite-based rainfall products, which allow for a better coverage than both radar network and rain gauges on the Tibetan Plateau, can be suitable alternatives for studies on investigating the hydrological processes and climate change. In this study, a newly developed daily satellite-based precipitation product, termed Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks – Climate Data Record (PERSIANN-CDR), is used as input for a hydrologic model to simulate streamflow in the upper Yellow and Yangtze River basins on the Tibetan Plateau. The results show that the simulated streamflows using PERSIANN-CDR precipitation and the Global Land Data Assimilation System (GLDAS) precipitation are closer to observation than that using limited gauge-based precipitation interpolation in the upper Yangtze River basin. The simulated streamflow using gauge-based precipitation are higher than the streamflow observation during the wet season. In the upper Yellow River basin, gauge-based precipitation, GLDAS precipitation, and PERSIANN-CDR precipitation have similar good performance in simulating streamflow. The evaluation of streamflow simulation capability in this study partly indicates that the PERSIANN-CDR rainfall product has good potential to be a reliable dataset and an alternative information source of a limited gauge network for conducting long-term hydrological and climate studies on the Tibetan Plateau.

scholarly journals Application of a technique for scenario prediction of climate change impact on the water balance components of northern river basins

2014 ◽  
Vol 62 (3) ◽  
pp. 197-208 ◽  
Author(s):  
Yeugeniy M. Gusev ◽  
Olga N. Nasonova
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Water Balance ◽  
River Basin ◽  
General Circulation ◽  
General Circulation Models ◽  
River Basins ◽  
Surface Model ◽  
Water Balance Components ◽  
Northern River

Abstract The scenario forecasting technique for assessing changes of water balance components of the northern river basins due to possible climate change was developed. Three IPCC global emission scenarios corresponding to different possible scenarios for economic, technological, political and demographic development of the human civilization in the 21st century were chosen for generating climate change projections by an ensemble of 16 General Circulation Models with a high spatial resolution. The projections representing increments of monthly values of meteorological characteristics were used for creating 3-hour meteorological time series up to 2063 for the Northern Dvina River basin, which belongs to the pan-Arctic basin and locates at the north of the European part of Russia. The obtained time series were applied as forcing data to drive the land surface model SWAP to simulate possible changes in the water balance components due to different scenarios of climate change for the Northern Dvina River basin

scholarly journals Satellite-Based Evapotranspiration in Hydrological Model Calibration

2020 ◽  
Vol 12 (3) ◽  
pp. 428 ◽  
Author(s):  
Lulu Jiang ◽  
Huan Wu ◽  
Jing Tao ◽  
John S. Kimball ◽  
Lorenzo Alfieri ◽  
...  
Keyword(s):  
Land Surface ◽  
Model Calibration ◽  
Hydrological Model ◽  
Land Surface Model ◽  
River Basins ◽  
Global Scale ◽  
Surface Model ◽  
Model Parameters ◽  
Spatially Distributed ◽  
Streamflow Simulation

Hydrological models are usually calibrated against observed streamflow (Qobs), which is not applicable for ungauged river basins. A few studies have exploited remotely sensed evapotranspiration (ETRS) for model calibration but their effectiveness on streamflow simulation remains uncertain. This paper investigates the use of ETRS in the hydrological calibration of a widely used land surface model coupled with a source–sink routing scheme and global optimization algorithm for 28 natural river basins. A baseline simulation is a setup based on the latest model developments and inputs. Sensitive parameters are determined for Qobs and ETRS-based model calibrations, respectively, through comprehensive sensitivity tests. The ETRS-based model calibration results in a mean Kling–Gupta Efficiency (KGE) value of 0.54 for streamflow simulation; 61% of the river basins have KGE > 0.5 in the validation period, which is consistent with the calibration period and provides a significant improvement over the baseline. Compared to Qobs, the ETRS calibration produces better or similar streamflow simulations in 29% of the basins, while further significant improvements are achieved when either better ET or precipitation observations are used. Furthermore, the model results show better or similar performance in 68% of the basins and outperform the baseline simulations in 90% of the river basins using model parameters from the best ETRS calibration runs. This study confirms that with reasonable precipitation input, the ETRS-based spatially distributed calibration can efficiently tune parameters for better ET and streamflow simulations. The application of ETRS for global scale hydrological model calibration promises even better streamflow accuracy as the satellite-based ETRS observations continue to improve.

scholarly journals The Variable Infiltration Capacity Model, Version 5 (VIC-5): Infrastructure improvements for new applications and reproducibility

2018 ◽  
Author(s):  
Joseph J. Hamman ◽  
Bart Nijssen ◽  
Theodore J. Bohn ◽  
Diana R. Gergel ◽  
Yixin Mao
Keyword(s):  
Climate Modeling ◽  
Source Code ◽  
Model Development ◽  
Global Scale ◽  
Hydrologic Model ◽  
Variable Infiltration Capacity ◽  
Infiltration Capacity ◽  
Data Set ◽  
Vic Model ◽  
Macro Scale

Abstract. The Variable Infiltration Capacity (VIC) model is a macro-scale semi-distributed hydrologic model. VIC development began in the early 1990s and the model has since been used extensively for basin- to global-scale applications that include hydrologic data set construction, trend analysis of hydrologic fluxes and states, data evaluation and assimilation, forecasting, coupled climate modeling, and climate change impact assessment. Ongoing operational applications of the VIC model include the University of Washington's drought monitoring and forecasting systems and NASA's Land Data Assimilation System. This paper documents the development of VIC version 5 (VIC-5), which includes a major reconfiguration of the legacy VIC source code to support a wider range of modern hydrologic modeling applications. The VIC source code has been moved to a public GitHub repository to encourage participation by the broader user and developer communities. The reconfiguration has separated the core physics of the model from the driver source code, where the latter is responsible for memory allocation, pre- and post-processing and input/output (I/O). VIC-5 includes four drivers that use the same core physics modules, but which allow for different methods for accessing this core to enable different model applications. Finally, VIC-5 is distributed with robust test infrastructure, components of which routinely run during development using cloud-hosted continuous integration. The work described here provides an example to the model development community for extending the life of a legacy model that is being used extensively. The development and release of VIC-5 represents a significant step forward for the VIC user community in terms of support for existing and new model applications, reproducibility, and scientific robustness.

Identification of sibling species in the genus Eucyclops from water-bodies of Ukraine and Russia using crossbreeding studies

2014 ◽  
Vol 25 (1-2) ◽  
pp. 61-68 ◽  
Author(s):  
V. I. Monchenko ◽  
L. P. Gaponova ◽  
V. R. Alekseev
Keyword(s):  
Cryptic Species ◽  
River Basin ◽  
Black Sea ◽  
Species Complex ◽  
River Basins ◽  
Water Bodies ◽  
Similar Species ◽  
Basin Water ◽  
Different Populations ◽  
Baltic Sea Basin

Crossbreeding experiments were used to estimate cryptic species in water bodies of Ukraine and Russia because the most useful criterion in species independence is reproductive isolation. The problem of cryptic species in the genus Eucyclops was examined using interpopulation crosses of populations collected from Baltic Sea basin (pond of Strelka river basin) and Black Sea basin (water-reservoires of Dnieper, Dniester and Danube rivers basins). The results of reciprocal crosses in Eucyclops serrulatus-group are shown that E. serrulatus from different populations but from water bodies belonging to the same river basin crossed each others successfully. The interpopulation crosses of E. serrulatus populations collected from different river basins (Dnipro, Danube and Dniester river basins) were sterile. In this group of experiments we assigned evidence of sterility to four categories: 1) incomplete copulation or absence of copulation; 2) nonviable eggs; 3) absence of egg membranes or egg sacs 4) empty egg membranes. These crossbreeding studies suggest the presence of cryptic species in the E. serrulatus inhabiting ecologically different populations in many parts of its range. The same crossbreeding experiments were carries out between Eucyclops serrulatus and morphological similar species – Eucyclops macruroides from Baltic and Black Sea basins. The reciprocal crossings between these two species were sterile. Thus taxonomic heterogeneity among species of genus Eucyclops lower in E. macruroides than in E. serrulatus. The interpopulation crosses of E. macruroides populations collected from distant part of range were fertile. These crossbreeding studies suggest that E. macruroides species complex was evaluated as more stable than E. serrulatus species complex.

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