Does comprehensive evaluation of hydrological models influence projected changes of mean and high flows in the Godavari River basin?

2020 ◽  
Vol 163 (3) ◽  
pp. 1187-1205 ◽  
Author(s):  
Vimal Mishra ◽  
Harsh Shah ◽  
M. Rocío Rivas López ◽  
Anastasia Lobanova ◽  
Valentina Krysanova
Keyword(s):  
River Basin ◽  
Comprehensive Evaluation ◽  
Hydrological Models ◽  
Godavari River ◽  
High Flows ◽  
Projected Changes

Evidence of river flow regulation loss over time in the Magdalena river basin 

2021 ◽  
Author(s):  
Diver E. Marín ◽  
Juan F. Salazar ◽  
José A. Posada-Marín
Keyword(s):  
Climate Change ◽  
Environmental Change ◽  
River Basin ◽  
River Flow ◽  
Southern Oscillation ◽  
Scaling Theory ◽  
Scaling Properties ◽  
Low Flows ◽  
High Flows ◽  
Magdalena River

<p>Some of the main problems in hydrological sciences are related to how and why river flows change as a result of environmental change, and what are the corresponding implications for society. This has been described as the Panta Rhei context, which refers to the challenge of understanding and quantifying hydrological dynamics in a changing environment, i.e. under the influence of non-stationary effects. The river flow regime in a basin is the result of a complex aggregation process that has been studied by the scaling theory, which allows river basins to be classified as regulated or unregulated and to identify a critical threshold between these states. Regulation is defined here as the basin’s capacity to either dampen high flows or to enhance low flows. This capacity depends on how basins store and release water through time, which in turn depends on many processes that are highly dynamic and sensitive to environmental change. Here we focus on the Magdalena river basin in northwestern South America, which is the main basin for water and energy security in Colombia, and at the same time, it has been identified as one of the most vulnerable regions to be affected by climate change. Building upon some of our previous studies, here we use data analysis to study the evolution of regulation in the Magdalena basin for 1992-2015 based on the scaling theory for extreme flows. In contrast to most previous studies, here we focus on the scaling properties of events rather than on long term averages. We discuss possible relations between changes in the scaling properties and environmental factors such as climate variability, climate change, and land use/land cover change, as well as the potential implications for water security in the country. Our results show that, during the last few decades, the Magdalena river basin has maintained its capacity to regulate low flows (i.e. amplification) whereas it has been losing its capacity to regulate high flows (i.e. dampening), which could be associated with the occurrence of the extremes phases of  El Niño Southern Oscillation (ENSO) and anthropogenic effects, mainly deforestation. These results provide foundations for using the scaling laws as empirical tools for understanding temporal changes of hydrological regulation and simultaneously generate useful scientific evidence that allows stakeholders to take decisions related to water management in the Magdalena river basin in the context of environmental change.</p>

Chemical and sediment mass transfer in the Godavari River basin in India

1980 ◽  
Vol 46 (3-4) ◽  
pp. 331-342 ◽  
Author(s):  
G. Bikshamaiah ◽  
V. Subramanian
Keyword(s):  
Mass Transfer ◽  
River Basin ◽  
Godavari River ◽  
Sediment Mass

scholarly journals Aplicação do Tank Model como Ferramenta de Gestão na Bacia do Rio Perdizes – Cambará do Sul/RS

2021 ◽  
Vol 14 (2) ◽  
pp. 1143
Author(s):  
Karla Campagnolo ◽  
Sofia Melo Vasconcellos ◽  
Vinicius Santanna Castiglio ◽  
Marina Refatti Fagundes ◽  
Masato Kobiyama
Keyword(s):  
River Basin ◽  
National Park ◽  
Management Tool ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
Moisture Index ◽  
Tank Model ◽  
Calibration And Validation ◽  
Historical Series ◽  
Soil Moisture Index

A representação do processo precipitação-vazão por meio de modelos hidrológicos conceituais visa quantificar o volume escoado em uma bacia como consequência de uma determinada precipitação. Aliados a eles, os índices têm sido uma ferramenta útil para quantificar eventos extremos, como o Soil Moisture Index (TMI) que foi formulado a partir do modelo hidrológico Tank Model. Desta forma, o objetivo deste trabalho foi aplicar o Tank Model para a bacia do rio Perdizes, em Cambará do Sul (RS), e avaliar o desempenho do TMI para prever a ocorrência de cheias, limiar este utilizado para o fechamento da Trilha do rio do Boi, no Parque Nacional de Aparados da Serra (PNAS). Os dados utilizados na simulação foram obtidos pelas estações meteorológica e fluviométrica instaladas na bacia. Após a calibração e validação de três séries históricas no Tank Model, os valores obtidos do TMI foram comparados com os dias que a Trilha foi fechada, a partir de altos níveis registrados no rio Perdizes. O TMI demonstrou que o nível utilizado para fechar a Trilha do rio do Boi correspondeu a cheias em 72% das vezes. Portanto, o TMI mostrou bom desempenho ao indicar a ocorrência de cheias na área estudada, sendo uma ferramenta útil para a tomada de decisões na gestão do PNAS.  Application of the Tank Model as a Management Tool in the Perdizes River Basin - Cambará do Sul/RS.ABSTRACTThe representation of the rainfall-runoff process by means of conceptual hydrological models aims to quantify the volume drained in a basin as result of a specific precipitation. Allied to them, the indices have been a useful tool to quantify extreme events, such as the Tank Moisture Index (TMI) which was formulated from the Tank Model. Thus, the objective of this work was to apply the Tank Model to the Perdizes river basin, in Cambará do Sul (RS), and to evaluate the performance of the TMI to predict the occurrence of floods, the threshold used for the closure of the Rio do Boi trail, in the Aparados da Serra National Park (PNAS). The data used in the simulation were obtained at the meteorological and fluviometric stations installed in the basin. After the calibration and validation of three historical series in the Tank Model, the values obtained in the TMI were compared with the days when the Trail was closed, from high levels recorded in the Perdizes river. The average TMI values demonstrated that the level used to close the Rio do Boi Trail corresponded to floods 72% of the time, and the median, 75%. Therefore, the TMI showed good performance in indicating the occurrence of floods in the study area, being a useful tool for decision making in the PNAS management.Keywords: Tank Moisture Index, trail closure, Aparados da Serra National Park.

scholarly journals The bias in GRACE estimates of continental water storage variations

2006 ◽  
Vol 3 (6) ◽  
pp. 3557-3594 ◽  
Author(s):  
R. Klees ◽  
E. A. Zapreeva ◽  
H. C. Winsemius ◽  
H. H. G. Savenije
Keyword(s):  
River Basin ◽  
Southern Africa ◽  
A Priori ◽  
Water Storage ◽  
Target Area ◽  
Hydrological Models ◽  
A Priori Information ◽  
Basin Scale ◽  
Priori Information ◽  
Gravity Field Models

Abstract. The estimation of terrestrial water storage variations at river basin scale is among the best documented applications of the GRACE (Gravity and Climate Experiment) satellite gravity mission. In particular, it is expected that GRACE closes the water balance at river basin scale and allows the verification, improvement and modeling of the related hydrological processes by combining GRACE amplitude estimates with hydrological models' output and in-situ data. When computing monthly mean storage variations from GRACE gravity field models, spatial filtering is mandatory to reduce GRACE errors, but at the same time yields biased amplitude estimates. The objective of this paper is three-fold. Firstly, we want to compute and analyze amplitude and time behaviour of the bias in GRACE estimates of monthly mean water storage variations for several target areas in Southern Africa. In particular, we want to know the relation between bias and the choice of the filter correlation length, the size of the target area, and the amplitude of mass variations inside and outside the target area. Secondly, we want to know to what extent the bias can be corrected for using a priori information about mass variations. Thirdly, we want to quantify errors in the estimated bias due to uncertainties in the a priori information about mass variations that are used to compute the bias. The target areas are located in Southern Africa around the Zambezi river basin. The latest release of monthly GRACE gravity field models have been used for the period from January 2003 until March 2006. An accurate and properly calibrated regional hydrological model has been developed for this area and its surroundings and provides the necessary a priori information about mass variations inside and outside the target areas. The main conclusion of the study is that spatial smoothing significantly biases GRACE estimates of the amplitude of annual and monthly mean water storage variations. For most of the practical applications, the bias will be positive, which implies that GRACE underestimates the amplitudes. The bias is mainly determined by the filter correlation length; in the case of 1000 km smoothing, which is shown to be an appropriate choice for the target areas, the annual bias attains values up to 50% of the annual storage; the monthly bias is even larger with a maximum value of 75% of the monthly storage. A priori information about mass variations can provide reasonably accurate estimates of the bias, which significantly improves the quality of GRACE water storage amplitudes. For the target areas in Southern Africa, we show that after bias correction, GRACE annual amplitudes differ between 0 and 30 mm from the output of a regional hydrological model, which is between 0% and 25% of the storage. Annual phase shifts are small, not exceeding 0.25 months, i.e. 7.5 deg. Our analysis suggests that bias correction of GRACE water storage amplitudes is indispensable if GRACE is used to calibrate hydrological models.

Application and comparison of different grid-based hydrological models in the Laoha River basin

2009 ◽  
Author(s):  
Xingze Wang ◽  
Xiumin Song ◽  
Yunhong Xue ◽  
Peng Li ◽  
Linlong Bai ◽  
...  
Keyword(s):  
River Basin ◽  
Hydrological Models ◽  
Grid Based
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