Comparison and evaluation of satellite derived precipitation products for hydrological modeling of the Zambezi River Basin

Abstract. In the framework of the African DAms ProjecT (ADAPT), an integrated water resource management study in the Zambezi Basin is currently under development. In view of the sparse gauging network for rainfall monitoring, the observations from spaceborne instrumentation currently produce the only available rainfall data for a large part of the basin. Three operational and acknowledged high resolution satellite derived estimates: the Tropical Rainfall Measuring Mission product 3B42 (TRMM 3B42), the Famine Early Warning System product 2.0 (FEWS RFE2.0) and the National Oceanic and Atmospheric Administration/Climate Prediction Centre (NOAA/CPC) morphing technique (CMORPH) are analyzed in terms of spatial and temporal repartition of the precipitations. They are compared to ground data for the wet seasons of the years 2003 to 2009 on a point to pixel basis at daily, 10-daily and monthly time steps and on a pixel to pixel basis for the wet seasons of the years 2003 to 2007 at monthly time steps. The general North-South gradient of precipitation is captured by all the analyzed products. Regarding the spatial heterogeneity, FEWS pixels are much more inter-correlated than TRMM and CMORPH pixels. For a rainfall homogeneity threshold criterion of 0.5 global mean correlation coefficient, the area of each sub-basin should not exceed a circle of 2.5° latitude/longitude radius for FEWS and a circle of 0.75° latitude/longitude radius for TRMM and CMORPH considering rectangular meshes. In terms of reliability, the correspondence of all estimates with ground data increases with the time step chosen for the analysis. The volume ratio computation indicates that CMORPH is overestimating the rainfall by nearly 50%. The statistics of TRMM and FEWS estimates show quite similar results. Due to its lower inter-correlation and longer data set, the TRMM 3B42 product is chosen as input for the hydraulic-hydrologic model of the basin. Further work will focus on the calibration of the hydraulic-hydrological model of the basin, including the major existing hydraulic structures with their operation rules.

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Comparison and evaluation of satellite derived precipitation products for hydrological modeling of the Zambezi River Basin

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-8-8173-2011 ◽

2011 ◽

Vol 8 (4) ◽

pp. 8173-8201 ◽

Cited By ~ 4

Author(s):

T. Cohen Liechti ◽

J. P. Matos ◽

J.-L. Boillat ◽

A. J. Schleiss

Keyword(s):

Water Resource Management ◽

Hydrological Modeling ◽

Volume Ratio ◽

Hydrologic Model ◽

Time Step ◽

Data Set ◽

Operation Rules ◽

Threshold Criterion ◽

Rectangular Mesh ◽

Trmm 3B42

Abstract. In the framework of the African Dams ProjecT (ADAPT), an integrated water resource management study in the Zambezi Basin is currently under development. In view of the sparse gauging network for rainfall monitoring, the observations from spaceborne instrumentation currently produce the only available rainfall data for a large part of the basin. Three operational and acknowledged high resolution satellite derived estimates: the Tropical Rainfall Measuring Mission product 3B42 (TRMM 3B42), the Famine Early Warning System product 2.0 (FEWS RFE2.0) and the National Oceanic and Atmospheric Administration/Climate Prediction Centre (NOAA/CPC) morphing technique (CMORPH) are analyzed in terms of spatial and temporal repartition of the precipitations. They are compared to ground data for the wet seasons of the years 2003 to 2009 on a point to pixel basis at daily, 10-daily and monthly time steps and on a pixel to pixel basis for the wet seasons of the years 2003 to 2007 at monthly time steps. The general North-South gradient of precipitation is captured by all the analyzed products. Regarding the spatial heterogeneity, FEWS pixels are much more inter-correlated than TRMM and CMORPH pixels. For a rainfall homogeneity threshold criterion of 0.5 global mean correlation coefficient, the area of each subbasin should not exceed a circle of 2.5° latitude/longitude radius for FEWS and a circle of 0.75° latitude/longitude radius for TRMM and CMORPH considering rectangular mesh. In terms of reliability, the correspondence of all estimates with ground data increases with the time step chosen for the analysis. The volume ratio computation indicates that CMORPH is overestimating by nearly 1.5 times the rainfall. The statistics of TRMM and FEWS estimates show quite similar results. Due to the its lower inter-correlation and longer data set, the TRMM 3B42 product is chosen as input for the hydraulic-hydrologic model of the basin. Further work will focus on the calibration of the hydraulic-hydrological model of the basin, including the major existing hydraulic structures with their operation rules.

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Runoff Predicting and Variation Analysis in Upper Ganjiang Basin under Projected Climate Changes

Sustainability ◽

10.3390/su11215885 ◽

2019 ◽

Vol 11 (21) ◽

pp. 5885 ◽

Cited By ~ 3

Author(s):

Chao Deng ◽

Weiguang Wang

Keyword(s):

Resource Management ◽

Water Resource ◽

Water Resource Management ◽

Hydrological Modeling ◽

Hydrologic Model ◽

Global Climate Models ◽

Balance Model ◽

Model Parameters ◽

The Mean ◽

Parameter Approach

Catchment runoff is significantly affected by climate condition changes. Predicting the runoff and analyzing its variations under future climates play a vital role in water security, water resource management, and the sustainable development of the catchment. In traditional hydrological modeling, fixed model parameters are usually used to transfer the global climate models (GCMs) to runoff, while the hydrologic model parameters may be time-varying. It is more appropriate to use the time-variant parameter for runoff modeling. This is achieved by incorporating the time-variant parameter approach into a two-parameter water balance model (TWBM) through the construction of time-variant parameter functions based on the identified catchment climate indicators. Using the Ganjiang Basin with an outlet of the Dongbei Hydrological Station as the study area, we developed time-variant parameter scenarios of the TWBM model and selected the best-performed parameter functions to predict future runoff and analyze its variations under the climate model projection of the BCC-CSM1.1(m). To synthetically assess the model performance improvements using the time-variant parameter approach, an index Δ was developed by combining the Nash–Sutcliffe efficiency, the volume error, the Box–Cox transformed root-mean-square error, and the Kling–Gupta efficiency with equivalent weight. The results show that the TWBM model with time-variant C (evapotranspiration parameter) and SC (water storage capacity of catchment), where growing and non-growing seasons are considered for C, outperformed the model with constant parameters with a Δ value of approximately 5% and 10% for the calibration and validation periods, respectively. The mean annual values of runoff predictions under the four representative concentration pathways (RCPs) exhibited a decreasing trend over the future three decades (2021–2050) when compared to the runoff simulations in the baseline period (1982–2011), where the values were about −9.9%, −19.5%, −16.6%, and −11.4% for the RCP2.6, RCP4.5, RCP6.0, and RCP8.5, respectively. The decreasing trend of future precipitation exerts impacts on runoff decline. Generally, the mean monthly changes of runoff predictions showed a decreasing trend from January to August for almost all of the RCPs, while an increasing trend existed from September to November, along with fluctuations among different RCPs. This study can provide beneficial references to comprehensively understand the impacts of climate change on runoff prediction and thus improve the regional strategy for future water resource management.

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A Long–Term Response-Based Rainfall-Runoff Hydrologic Model: Case Study of The Upper Blue Nile

Hydrology ◽

10.3390/hydrology6030069 ◽

2019 ◽

Vol 6 (3) ◽

pp. 69 ◽

Cited By ~ 2

Author(s):

Eatemad Keshta ◽

Mohamed A. Gad ◽

Doaa Amin

Keyword(s):

River Flow ◽

Hydrologic Model ◽

Initial Assessment ◽

Rainfall Runoff ◽

Time Step ◽

Data Set ◽

Blue Nile ◽

Catchment Areas ◽

Surface And Groundwater

This study develops a response-based hydrologic model for long-term (continuous) rainfall-runoff simulations over the catchment areas of big rivers. The model overcomes the typical difficulties in estimating infiltration and evapotranspiration parameters using a modified version of the Soil Conservation Service curve number SCS-CN method. In addition, the model simulates the surface and groundwater hydrograph components using the response unit-hydrograph approach instead of using a linear reservoir routing approach for routing surface and groundwater to the basin outlet. The unit-responses are Geographic Information Systems (GIS)-pre-calculated on a semi-distributed short-term basis and applied in the simulation in every time step. The unit responses are based on the time-area technique that can better simulate the real routing behavior of the basin. The model is less sensitive to groundwater infiltration parameters since groundwater is actually controlled by the surface component and not the opposite. For that reason, the model is called the SCHydro model (Surface Controlled Hydrologic model). The model is tested on the upper Blue Nile catchment area using 28 years daily river flow data set for calibration and validation. The results show that SCHydro model can simulate the long-term transforming behavior of the upper Blue Nile basin. Our initial assessment of the model indicates that the model is a promising tool for long-term river flow simulations, especially for long-term forecasting purposes due to its stability in performing the water balance.

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Advances and challenges of the French operational flash flood warning system, Vigicrues Flash

10.5194/egusphere-egu21-16063 ◽

2021 ◽

Author(s):

Julie Demargne ◽

Catherine Fouchier ◽

Didier Organde ◽

Olivier Piotte ◽

Anne Belleudy

Keyword(s):

Hydrological Model ◽

Flash Flood ◽

Warning System ◽

Hydrologic Model ◽

Parameters Estimation ◽

Flood Events ◽

Time Step ◽

Flood Warning ◽

Flood Warning System ◽

High Flood

Since March 2017, the French flash flood warning system, Vigicrues Flash, provides warnings for small-to-medium ungauged basins for about 10,000 municipalities to help emergency services better mitigate potential impacts of ongoing and upcoming flash flood events. Set up by the Ministry in charge of Environment, this system complements flood warnings produced by the Vigicrues procedure for French monitored rivers. Based on a discharge-threshold flood warning method called AIGA, Vigicrues Flash currently ingests radar-gauge rainfall grids at a 1-km resolution into a conceptual distributed rainfall-runoff model. Real-time peak discharge estimated on any river cell are then compared to regionalized flood quantiles (estimated with the same hydrological model). Automated warnings are issued for rivers exceeding the high flood and very high flood thresholds (defined as years of return periods) and for the associated municipalities that might be impacted. This service shares a web platform for the dissemination and communication of early warnings and hazard map displays with the APIC heavy rainfall warning service from M&#233;t&#233;o-France. To better anticipate flash flood events and extend the coverage of the Vigicrues Flash service, the hydrological modeling is being enhanced within the SMASH (Spatially-distributed Modelling and ASsimilation for Hydrology) platform developed by INRAE (formerly Irstea). For the upcoming operational update of Vigicrues Flash, a simplified distributed hydrologic model is continuously run at a 15-minute time step and a 1-km resolution. It includes only 2 parameters per cell, controlling respectively a production reservoir and a transfer reservoir from the G&#233;nie Rural (GR) conceptual models. Cross-validation and regionalization of these two parameters have been improved to better account for basins spatial heterogeneities while optimizing flash flood warning performance. Evaluation results for 921 French basins on the 2007-2019 period show improvements in terms of flash flood event detection and effective warning lead time. Current developments aim to integrate a cell-to-cell routing component and improve parameters estimation at the national scale with the variational calibration schemes recently developed on the SMASH platform by Jay-Allemand et al. (2020). Challenges of including high-resolution precipitation nowcasts and accounting for the hydrometeorological uncertainties via data assimilation and ensemble forecasting are also discussed based on ongoing SMASH research.&#160;Jay-Allemand, M., Javelle, P., Gejadze, I., Arnaud, P., Malaterre, P.-O., Fine, J.-A., and Organde, D.: On the potential of variational calibration for a fully distributed hydrological model: application on a Mediterranean catchment, Hydrol. Earth Syst. Sci., 24, 5519&#8211;5538, https://doi.org/10.5194/hess-24-5519-2020, 2020.

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Evaluating the Performance of Secondary Precipitation Products through Statistical and Hydrological Modeling in a Mountainous Tropical Basin of India

Advances in Meteorology ◽

10.1155/2020/8859185 ◽

2020 ◽

Vol 2020 ◽

pp. 1-23

Author(s):

Kolluru Venkatesh ◽

N. Y. Krakauer ◽

E. Sharifi ◽

H. Ramesh

Keyword(s):

Climate Change ◽

Hydrological Modeling ◽

Assessment Tool ◽

Extreme Event ◽

Poor Performance ◽

Event Analysis ◽

Time Step ◽

Global Precipitation Climatology Centre ◽

Statistical Metrics ◽

Trmm 3B42

This paper investigates the performance of gridded rainfall datasets for precipitation detection and streamflow simulations in Indiaʼs Tungabhadra river basin. Sixteen precipitation datasets categorized under gauge-based, satellite-only, reanalysis, and gauge-adjusted datasets were compared statistically against the gridded Indian Meteorological Dataset (IMD) employing two categorical and three continuous statistical metrics. Further, the precipitation datasets’ performance in simulating streamflow was assessed by using the Soil and Water Assessment Tool (SWAT) hydrological model. Based on the statistical metrics, Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE) furnished very good results in terms of detecting rainfall, followed by Climate Hazards Group Infrared Precipitation (CHIRP), National Centres for Environmental Prediction-Climate Forecast System Reanalysis (NCEP CFSR), Tropical Rainfall Measurement Mission (TRMM) 3B42 v7, Global Satellite Mapping of Precipitation Gauge Reanalysis v6 (GSMaP_Gauge_RNL), and Multisource Weighted Ensemble Precipitation (MSWEP) datasets which had good-to-moderate performances at a monthly time step. From the hydrological simulations, TRMM 3B42 v7, CHIRP, CHIRPS 0.05°, and GSMaP_Gauge_RNL v6 produced very good results with a high degree of correlation to observed streamflow, while Soil Moisture 2 Rain-Climate Change Initiative (SM2RAIN-CCI) dataset exhibited poor performance. From the extreme flow event analysis, it was observed that CHIRP, TRMM 3B42 v7, Global Precipitation Climatology Centre v7 (GPCC), and APHRODITE datasets captured more peak flow events and hence can be further implemented for extreme event analysis. Overall, we found that TRMM 3B42 v7, CHIRP, and CHIRPS 0.05° datasets performed better than other datasets and can be used for hydrological modeling and climate change studies in similar topographic and climatic watersheds in India.

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Hydrological modeling with special reference to snow cover processes

Facta universitatis - series Architecture and Civil Engineering ◽

10.2298/fuace1302147s ◽

2013 ◽

Vol 11 (2) ◽

pp. 147-168 ◽

Cited By ~ 1

Author(s):

Milan Stojkovic ◽

Nikola Milivojevic

Keyword(s):

Hydrological Modeling ◽

Hydrologic Model ◽

Morphological Data ◽

Soil Composition ◽

Time Step ◽

Temperature Index ◽

Distributed Hydrologic Model ◽

Physically Based ◽

Thiessen Polygons ◽

Weather Stations

A physically-based distributed hydrologic model was applied in this research. The river basin, or watershed, was discretized with a square grid, where each square carried morphological data about a portion of the watershed, the vegetation, the soil composition, the hydrogeological layer, and the like. The effect of weather stations was defined by Thiessen polygons, including correction for altitude. The hydrological model was continuous, with a one-day time step. It was partitioned into three reservoirs: vegetation, snow and soil. The snow reservoir was defined using the degree-day and temperature index methods. The hydrologic model was applied to the basin of the Banjska River, which is a tributary of the Juzna Morava.

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The value of ASCAT soil moisture and MODIS snow cover data for calibrating a conceptual hydrologic model

Hydrology and Earth System Sciences ◽

10.5194/hess-25-1389-2021 ◽

2021 ◽

Vol 25 (3) ◽

pp. 1389-1410

Author(s):

Rui Tong ◽

Juraj Parajka ◽

Andreas Salentinig ◽

Isabella Pfeil ◽

Jürgen Komma ◽

...

Keyword(s):

Remote Sensing ◽

Soil Moisture ◽

Snow Cover ◽

Hydrological Modeling ◽

Hydrologic Model ◽

Catchment Scale ◽

Data Set ◽

Water Index ◽

Soil Moisture Data ◽

Moderate Resolution Imaging Spectroradiometer

Abstract. Recent advances in soil moisture remote sensing have produced satellite data sets with improved soil moisture mapping under vegetation and with higher spatial and temporal resolutions. In this study, we evaluate the potential of a new, experimental version of the Advanced Scatterometer (ASCAT) soil water index data set for multiple objective calibrations of a conceptual hydrologic model. The analysis is performed in 213 catchments in Austria for the period 2000–2014. An HBV (Hydrologiska Byråns Vattenbalansavdelning)-type hydrologic model is calibrated based on runoff data, ASCAT soil moisture data, and Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover data for various calibration variants. Results show that the inclusion of soil moisture data in the calibration mainly improves the soil moisture simulations, the inclusion of snow data mainly improves the snow simulations, and the inclusion of both of them improves both soil moisture and snow simulations to almost the same extent. The snow data are more efficient at improving snow simulations than the soil moisture data are at improving soil moisture simulations. The improvements of both runoff and soil moisture model efficiencies are larger in low elevation and agricultural catchments than in others. The calibrated snow-related parameters are strongly affected by including snow data and, to a lesser extent, by soil moisture data. In contrast, the soil-related parameters are only affected by the inclusion of soil moisture data. The results indicate that the use of multiple remote sensing products in hydrological modeling can improve the representation of hydrological fluxes and prediction of runoff hydrographs at the catchment scale.

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A driver drowsiness and distraction warning system based on raspberry Pi 3 Kit

Transport and Communication Science Journal ◽

10.25073/tcsj.70.3.4 ◽

2019 ◽

Vol 70 (3) ◽

pp. 184-192

Author(s):

Toan Dao Thanh ◽

Vo Thien Linh

Keyword(s):

Processing System ◽

Warning System ◽

Raspberry Pi ◽

Data Set ◽

Lower Lip ◽

Driver Drowsiness ◽

Image Sensing ◽

The Face ◽

The Common ◽

University Laboratory

In this article, a system to detect driver drowsiness and distraction based on image sensing technique is created. With a camera used to observe the face of driver, the image processing system embedded in the Raspberry Pi 3 Kit will generate a warning sound when the driver shows drowsiness based on the eye-closed state or a yawn. To detect the closed eye state, we use the ratio of the distance between the eyelids and the ratio of the distance between the upper lip and the lower lip when yawning. A trained data set to extract 68 facial features and “frontal face detectors” in Dlib are utilized to determine the eyes and mouth positions needed to carry out identification. Experimental data from the tests of the system on Vietnamese volunteers in our University laboratory show that the system can detect at realtime the common driver states of “Normal”, “Close eyes”, “Yawn” or “Distraction”

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A NEW TECHNIQUE ESTIMATING LOCATION OF MEAN JOINT CENTERS OF ROTATION WITH ASSOCIATED DISPERSIONS AND ASSESSING TO FUNCTIONAL COORDINATE SYSTEM OF MOVING LIMB SEGMENTS

Journal of Mechanics in Medicine and Biology ◽

10.1142/s0219519406001996 ◽

2006 ◽

Vol 06 (04) ◽

pp. 373-384

Author(s):

ERIC BERTHONNAUD ◽

JOANNÈS DIMNET

Keyword(s):

Numerical Technique ◽

New Technique ◽

Helical Axis ◽

Joint Movement ◽

Time Step ◽

Data Set ◽

Minimization Procedure ◽

A New Technique ◽

Joint Center

Joint centers are obtained from data treatment of a set of markers placed on the skin of moving limb segments. Finite helical axis (FHA) parameters are calculated between time step increments. Artifacts associated with nonrigid body movements of markers entail ill-determination of FHA parameters. Mean centers of rotation may be calculated over the whole movement, when human articulations are likened to spherical joints. They are obtained using numerical technique, defining point with minimal amplitude, during joint movement. A new technique is presented. Hip, knee, and ankle mean centers of rotation are calculated. Their locations depend on the application of two constraints. The joint center must be located next to the estimated geometric joint center. The geometric joint center may migrate inside a cube of possible location. This cube of error is located with respect to the marker coordinate systems of the two limb segments adjacent to the joint. Its position depends on the joint and the patient height, and is obtained from a stereoradiographic study with specimen. The mean position of joint center and corresponding dispersion are obtained through a minimization procedure. The location of mean joint center is compared with the position of FHA calculated between different sequential steps: time sequential step, and rotation sequential step where a minimal rotation amplitude is imposed between two joint positions. Sticks are drawn connecting adjacent mean centers. The animation of stick diagrams allows clinical users to estimate the displacements of long bones (femur and tibia) from the whole data set.

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