scholarly journals The potential of global reanalysis datasets in identifying flood events in Southern Africa

2018 ◽  
Vol 22 (9) ◽  
pp. 4667-4683 ◽  
Author(s):  
Gaby J. Gründemann ◽  
Micha Werner ◽  
Ted I. E. Veldkamp
Keyword(s):  
Water Resources ◽  
River Basin ◽  
Southern Africa ◽  
Large Scale ◽  
Meteorological Data ◽  
Climatic Variability ◽  
Added Value ◽  
Flood Events ◽  
Global Models ◽  
Global Reanalysis

Abstract. Sufficient and accurate hydro-meteorological data are essential to manage water resources. Recently developed global reanalysis datasets have significant potential in providing these data, especially in regions such as Southern Africa that are both vulnerable and data poor. These global reanalysis datasets have, however, not yet been exhaustively validated and it is thus unclear to what extent these are able to adequately capture the climatic variability of water resources, in particular for extreme events such as floods. This article critically assesses the potential of a recently developed global Water Resources Reanalysis (WRR) dataset developed in the European Union's Seventh Framework Programme (EU-FP7) eartH2Observe (E2O) project for identifying floods, focussing on the occurrence of floods in the Limpopo River basin in Southern Africa. The discharge outputs of seven global models and ensemble mean of those models as available in the WRR dataset are analysed and compared against two benchmarks of flood events in the Limpopo River basin. The first benchmark is based on observations from the available stations, while the second is developed based on flood events that have led to damages as reported in global databases of damaging flood events. Results show that, while the WRR dataset provides useful data for detecting the occurrence of flood events in the Limpopo River basin, variation exists amongst the global models regarding their capability to identify the magnitude of those events. The study also reveals that the models are better able to capture flood events at stations with a large upstream catchment area. Improved performance for most models is found for the 0.25° resolution global model, when compared to the lower-resolution 0.5° models, thus underlining the added value of increased-resolution global models. The skill of the global hydrological models (GHMs) in identifying the severity of flood events in poorly gauged basins such as the Limpopo can be used to estimate the impacts of those events using the benchmark of reported damaging flood events developed at the basin level, though this could be improved if further details on location and impacts are included in disaster databases. Large-scale models such as those included in the WRR dataset are used by both global and continental forecasting systems, and this study sheds light on the potential these have in providing information useful for local-scale flood risk management. In conclusion, this study offers valuable insights in the applicability of global reanalysis data for identifying impacting flood events in data-sparse regions.

scholarly journals The potential of global re-analysis datasets in identifying flood events in Southern Africa

2018 ◽  
Author(s):  
Gaby J. Gründemann ◽  
Micha Werner ◽  
Ted I. E. Veldkamp
Keyword(s):  
Water Resources ◽  
River Basin ◽  
Southern Africa ◽  
Large Scale ◽  
Meteorological Data ◽  
Climatic Variability ◽  
Analysis Data ◽  
Added Value ◽  
Flood Events ◽  
Global Models

Abstract. Sufficient and accurate hydro-meteorological data are essential to manage water resources. Recently developed global re-analysis datasets have significant potential in providing these data, especially in regions such as Southern Africa that are both vulnerable and data poor. These global re-analysis datasets have, however, not yet been exhaustively validated and it is thus unclear to what extent these are able to adequately capture the climatic variability of water resources, in particular for extreme events such as floods. This article critically assesses the potential of a recently developed global Water Resource Re-analysis (WRR) dataset developed in the EU FP7 eartH2Observe project for identifying floods, focussing on the occurrence of floods in the Limpopo River basin in Southern Africa. The discharge outputs of seven global models and ensemble mean of those models as available in the WRR dataset are analysed and compared against two benchmarks of flood events in the Limpopo River basin. The first benchmark is based on observations from the available stations, while the second is developed based on flood events that have led to damages as reported in global databases of damaging flood events. Results show that while the WRR dataset provides useful data for detecting the occurrence of flood events in the Limpopo River basin, variation exists amongst the global models regarding their capability to identify the magnitude of those events. The study also reveals that the models are better able to capture flood events at stations with a large upstream catchment area. Improved performance for most models is found for the 0.25 degrees resolution global model, when compared to the lower resolution 0.5 degrees models, thus underlining the added value of increased resolution global models. The skill of the global hydrological models in identifying the severity of flood events in poorly gauged basins such as the Limpopo can be used to estimate the impacts of those events using the benchmark of reported damaging flood events developed at the basin level, though could be improved if further detail on location and impacts are included in disaster databases. Large-scale models such as those included in the WRR dataset are used by both global and continental forecasting systems, and this study sheds light on the potential these have in providing information useful for local scale flood risk management. In conclusion, this study offers valuable insights in the applicability of global re-analysis data for identifying impacting flood events in data sparse regions.

scholarly journals Analysis of evapotranspiration and biomass in pastures with degradation indicatives in the Upper Tocantins River Basin, in Brazilian Savanna

Revista CERES ◽  
2016 ◽  
Vol 63 (6) ◽  
pp. 754-760 ◽  
Author(s):  
Ricardo Guimarães Andrade ◽  
Antônio Heriberto de Castro Teixeira ◽  
Janice Freitas Leivas ◽  
Sandra Furlan Nogueira
Keyword(s):  
River Basin ◽  
Large Scale ◽  
Meteorological Data ◽  
Simple Algorithm ◽  
Production Potential ◽  
Pasture Degradation ◽  
Ndvi Time Series ◽  
Tocantins River ◽  
Remote Sensing Techniques ◽  
Degraded Pastures

ABSTRACT The objective of this study was to apply the Simple Algorithm For Evapotranspiration Retrieving (SAFER) with MODIS images together with meteorological data to analyze evapotranspiration (ET) and biomass production (BIO) according to indicative classes of pasture degradation in Upper Tocantins River Basin. Indicative classes of degraded pastures were obtained from the NDVI time-series (2002-2012). To estimate ET and BIO in each class, MODIS images and data from meteorological stations of the year 2012 were used. The results show that compared to not-degraded pastures, ET and BIO were different in pastures with moderate to strong degradation, mainly during water stress period. Therefore, changes in energy balance partition may occur according to the degradation levels, considering that those indicatives of degradation processes were identified in 24% of the planted pasture areas. In this context, ET and BIO estimates using remote sensing techniques can be a reliable indicator of forage availability, and large-scale aspects related to the degradation of pastures. It is expected that this knowledge may contribute to initiatives of public policies aimed at controlling the loss of production potential of pasture areas in the Upper Tocantins River Basin in the state of Goiás, Brazil.

scholarly journals Comparing bias correction methods in downscaling meteorological variables for hydrologic impact study in an arid area in China

2014 ◽  
Vol 11 (11) ◽  
pp. 12659-12696 ◽  
Author(s):  
G. H. Fang ◽  
J. Yang ◽  
Y. N. Chen ◽  
C. Zammit
Keyword(s):  
Water Resources ◽  
River Basin ◽  
Bias Correction ◽  
Meteorological Data ◽  
Hydrologic Model ◽  
Temperature Correction ◽  
Arid Area ◽  
Tarim River ◽  
Tarim River Basin ◽  
Impact Study

Abstract. Water resources are essential to the ecosystem and social economy in the desert and oasis of the arid Tarim River Basin, Northwest China, and expected to be vulnerable to climate change. Regional Climate Models (RCM) have been proved to provide more reliable results for regional impact study of climate change (e.g. on water resources) than GCM models. However, it is still necessary to apply bias correction before they are used for water resources research due to often considerable biases. In this paper, after a sensitivity analysis on input meteorological variables based on Sobol' method, we compared five precipitation correction methods and three temperature correction methods to the output of a RCM model with its application to the Kaidu River Basin, one of the headwaters of the Tarim River Basin. Precipitation correction methods include Linear Scaling (LS), LOCal Intensity scaling (LOCI), Power Transformation (PT), Distribution Mapping (DM) and Quantile Mapping (QM); and temperature correction methods include LS, VARIance scaling (VARI) and DM. These corrected precipitation and temperature were compared to the observed meteorological data, and then their impacts on streamflow were also compared by driving a distributed hydrologic model. The results show: (1) precipitation, temperature, solar radiation are sensitivity to streamflow while relative humidity and wind speed are not, (2) raw RCM simulations are heavily biased from observed meteorological data, which results in biases in the simulated streamflows, and all bias correction methods effectively improved theses simulations, (3) for precipitation, PT and QM methods performed equally best in correcting the frequency-based indices (e.g. SD, percentile values) while LOCI method performed best in terms of the time series based indices (e.g. Nash–Sutcliffe coefficient, R2), (4) for temperature, all bias correction methods performed equally well in correcting raw temperature. (5) For simulated streamflow, precipitation correction methods have more significant influence than temperature correction methods and the performances of streamflow simulations are consistent with these of corrected precipitation, i.e. PT and QM methods performed equally best in correcting flow duration curve and peak flow while LOCI method performed best in terms of the time series based indices. The case study is for an arid area in China based on a specific RCM and hydrologic model, but the methodology and some results can be applied to other area and other models.

Development of a Non-Linear Integrated Drought Index (NDI) for Managing Drought and Water Resources Forecasting in the Upper Tana River Basin-Kenya

2020 ◽  
Vol 11 (1) ◽  
pp. 15-33
Author(s):  
Raphael Muli Wambua
Keyword(s):  
Water Resources ◽  
River Basin ◽  
Lead Time ◽  
Drought Index ◽  
Meteorological Data ◽  
Principal Component ◽  
Drought Forecasting ◽  
Tropical River ◽  
Tana River ◽  
Non Linear

This article uses the non-linear integrated drought index (NDI) for managing drought and water resources forecasting in a tropical river basin. The NDI was formulated using principal component analysis (PCA). The NDI used hydro-meteorological data and forecasted using recursive multi-step neural networks. In this article, drought forecasting and projection is adopted for planning ahead for mitigation and for the adaptation of adverse effects of droughts and food insecurity in the river basin. Results that forecasting ability of NDI model using ANNs decreased with increase in lead time. The formulated NDI as a tool for projecting into the future.

scholarly journals Evaluation of Global Water Resources Reanalysis Data for Estimating Flood Events in the Brahmaputra River Basin

2020 ◽  
Vol 34 (7) ◽  
pp. 2201-2220 ◽  
Author(s):  
Patricia López López ◽  
Tashrifa Sultana ◽  
Mohammed Abdulla Hel Kafi ◽  
Mohammed Shahadat Hossain ◽  
Abu Saleh Khan ◽  
...  
Keyword(s):  
Water Resources ◽  
River Basin ◽  
Reanalysis Data ◽  
Flood Events ◽  
Brahmaputra River ◽  
Global Water

An appraisal of flood events using IMD, CRU, and CCSM4-derived meteorological data sets over the Vaigai river basin, Tamil Nadu (India)

2019 ◽  
Vol 5 (4) ◽  
pp. 1731-1744 ◽  
Author(s):  
Satish Nagalapalli ◽  
Arnab Kundu ◽  
R. K. Mall ◽  
D. Thattai ◽  
S. Rangarajan
Keyword(s):  
River Basin ◽  
Tamil Nadu ◽  
Meteorological Data ◽  
Data Sets ◽  
Flood Events

scholarly journals Understanding Future Water Challenges in a Highly Regulated Indian River Basin—Modelling the Impact of Climate Change on the Hydrology of the Upper Narmada

Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1762 ◽  
Author(s):  
Nathan Rickards ◽  
Thomas Thomas ◽  
Alexandra Kaelin ◽  
Helen Houghton-Carr ◽  
Sharad K. Jain ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
River Basin ◽  
Large Scale ◽  
Monsoon Season ◽  
Future Climate Change ◽  
Impact Of Climate Change ◽  
Global Circulation Models ◽  
The Impact ◽  
Availability Assessment

The Narmada river basin is a highly regulated catchment in central India, supporting a population of over 16 million people. In such extensively modified hydrological systems, the influence of anthropogenic alterations is often underrepresented or excluded entirely by large-scale hydrological models. The Global Water Availability Assessment (GWAVA) model is applied to the Upper Narmada, with all major dams, water abstractions and irrigation command areas included, which allows for the development of a holistic methodology for the assessment of water resources in the basin. The model is driven with 17 Global Circulation Models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble to assess the impact of climate change on water resources in the basin for the period 2031–2060. The study finds that the hydrological regime within the basin is likely to intensify over the next half-century as a result of future climate change, causing long-term increases in monsoon season flow across the Upper Narmada. Climate is expected to have little impact on dry season flows, in comparison to water demand intensification over the same period, which may lead to increased water stress in parts of the basin.

scholarly journals Modeling for transboundary water resources planning and allocation

2008 ◽  
Vol 5 (1) ◽  
pp. 475-509 ◽  
Author(s):  
D. Juízo ◽  
R. Lidén
Keyword(s):  
South Africa ◽  
Water Resources ◽  
River Basin ◽  
Southern Africa ◽  
Degrees Of Freedom ◽  
System Analysis ◽  
Model Performance ◽  
Yield Model ◽  
Water Users ◽  
Development Scenarios

Abstract. International water resources agreements for transboundary rivers in southern Africa are based on system analysis models for water planning and allocation. The Water Resources Yield Model (WRYM) developed in South Africa has so far been the only model applied in official joint water resources studies aimed to form water-sharing agreements. The continuous discussion around the model performance and growing distress over it being South African, where it was originally developed, while South Africa is one of the interested parties in the process, results in an increased controversy over the system analysis results that are often only meant to guide in selecting the options for water resources management in a given set of scenarios. The objective of this study was therefore to assess the model performance of two other models; WAFLEX and WEAP21 in the Umbeluzi River Basin system where the WRYM was previously applied as part of a Joint River Basin Study. A set of basin development scenarios was equally tested in the three models and the results compared. The results show that the three models all are possible tools for system analysis of river basins in southern Africa, although the structure and complexity of the models are different. The obtained level of satisfaction for specific water users could, however, vary depending on which model was used, which causes uncertainties. The reason for the diverse results is the structurally different ways of describing allocation and prioritization of water in the three models. However, the large degrees of freedom in all system models cause even larger uncertainty in the results since the model user can, intentionally or unintentionally, direct the results to favor certain water users. The conclusion of this study is therefore that the choice of model does not per se affect the decision of best water allocation and infrastructure layout of a shared river basin. The chosen allocation and prioritization principles for the specific river basin and the model user's experience and integrity are more important factors to find the optimal and equitable allocation.

scholarly journals ESTIMATING CONTRIBUTION OF WATER FLOW COMPONENTS TO KAMENG RIVER BASIN USING HYDROLOGICAL MODELLING

2021 ◽  
Vol XLIII-B3-2021 ◽  
pp. 431-436
Author(s):  
S. Arora ◽  
A. V. Kulkarni ◽  
P. Ghosh ◽  
S. K. Satheesh
Keyword(s):  
Water Resources ◽  
River Basin ◽  
Water Resource Management ◽  
Hydrological Cycle ◽  
Meteorological Data ◽  
Clean Energy ◽  
Coefficient Of Determination ◽  
Melt Water ◽  
Resilient Infrastructure ◽  
Discharge Profile

Abstract. The Himalayas, also known as third pole of the Earth feed some of the major rivers of the world viz. Ganga, Indus, Brahmaputra etc. The accurate assessment of water resources in eastern Himalayas is very important for respective policy makers. The detailed assessment of water resources and hydrological cycle component are very critical for attaining United Nations sustainable development goals (SDGs) such as affordable and clean energy, clean water and sanitation and building resilient infrastructure This study focuses on Kameng river basin, estimating the melt water & its contribution to the total discharge of the river. A 3-layer VIC model coupled with energy balance algorithm is used to estimate the patterns of melt and discharge profile in the region. Net contribution of melt water to the river were estimated to be about 18% during peak melt season in upper catchments. With advancement in technology, acquiring meteorological data via remote sensing has become more accurate & of high resolution. This data is one of the major inputs of the model. With accurate forecasting of these parameters, multipurpose hydropower projects in these regions can plan well in advance thus playing a major role in Integrated Water Resource Management. In current study the coefficient of determination & Nash-Sutcliffe efficiency were calculated to be 0.82 & 0.71 respectively. With increasing population in the region, any substantial change in the streamflow will have consequences unknown as of now, thus making this study a necessity & need of hour.

Sign in / Sign up

Export Citation Format

Share Document