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

2011 ◽  
Vol 8 (4) ◽  
pp. 8173-8201 ◽  
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.

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

2012 ◽  
Vol 16 (2) ◽  
pp. 489-500 ◽  
Author(s):  
T. Cohen Liechti ◽  
J. P. Matos ◽  
J.-L. Boillat ◽  
A. J. Schleiss
Keyword(s):  
Water Resource Management ◽  
Hydrological Modeling ◽  
Warning System ◽  
Volume Ratio ◽  
Hydrologic Model ◽  
Time Step ◽  
Data Set ◽  
Operation Rules ◽  
Threshold Criterion ◽  
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 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.

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

2019 ◽  
Vol 11 (21) ◽  
pp. 5885 ◽  
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.

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

Hydrology ◽  
2019 ◽  
Vol 6 (3) ◽  
pp. 69 ◽  
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.

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

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.

scholarly journals Hydrological modeling with special reference to snow cover processes

2013 ◽  
Vol 11 (2) ◽  
pp. 147-168 ◽  
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.

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

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.

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

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.

New Transboundary Hydrographic Data Set for Advancing Regional Hydrological Modeling and Water Resources Management

2019 ◽  
Vol 145 (6) ◽  
pp. 06019004 ◽  
Author(s):  
Lacey A. Mason ◽  
Andrew D. Gronewold ◽  
Michael Laitta ◽  
David Gochis ◽  
Kevin Sampson ◽  
...  
Keyword(s):  
Water Resources ◽  
Water Resources Management ◽  
Hydrological Modeling ◽  
Hydrographic Data ◽  
Data Set ◽  
Resources Management

scholarly journals Spatial evapotranspiration, rainfall and land use data in water accounting – Part 1: Review of the accuracy of the remote sensing data

2015 ◽  
Vol 19 (1) ◽  
pp. 507-532 ◽  
Author(s):  
P. Karimi ◽  
W. G. M. Bastiaanssen
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Water Resource Management ◽  
Hydrological Modeling ◽  
Remote Sensing Data ◽  
Actual Evapotranspiration ◽  
Primary Concern ◽  
Suitable Alternative ◽  
Sensing Data ◽  
Water Accounting

Abstract. The scarcity of water encourages scientists to develop new analytical tools to enhance water resource management. Water accounting and distributed hydrological models are examples of such tools. Water accounting needs accurate input data for adequate descriptions of water distribution and water depletion in river basins. Ground-based observatories are decreasing, and not generally accessible. Remote sensing data is a suitable alternative to measure the required input variables. This paper reviews the reliability of remote sensing algorithms to accurately determine the spatial distribution of actual evapotranspiration, rainfall and land use. For our validation we used only those papers that covered study periods of seasonal to annual cycles because the accumulated water balance is the primary concern. Review papers covering shorter periods only (days, weeks) were not included in our review. Our review shows that by using remote sensing, the absolute values of evapotranspiration can be estimated with an overall accuracy of 95% (SD 5%) and rainfall with an overall absolute accuracy of 82% (SD 15%). Land use can be identified with an overall accuracy of 85% (SD 7%). Hence, more scientific work is needed to improve the spatial mapping of rainfall and land use using multiple space-borne sensors. While not always perfect at all spatial and temporal scales, seasonally accumulated actual evapotranspiration maps can be used with confidence in water accounting and hydrological modeling.

scholarly journals Modeling of Stage-Discharge Using Back Propagation ANN, ANFIS, and WANN-based Computing Technique

2021 ◽  
Author(s):  
Ravi Shukla ◽  
Pravendra Kumar ◽  
Dinesh Kumar Vishwakarma ◽  
Rawshan Ali ◽  
Rohitashw Kumar ◽  
...  
Keyword(s):  
Water Resource Management ◽  
Hydrological Modeling ◽  
Fuzzy Inference ◽  
Back Propagation ◽  
Activation Function ◽  
Neural System ◽  
Back Propagation Algorithm ◽  
Inference System ◽  
Computing Technique ◽  
Artificial Neural

Abstract The development of the stage-discharge relationship is a fundamental issue in hydrological modeling. Due to the complexity of the stage-discharge relationship, discharge prediction plays an essential role in planning and water resource management. The present study was conducted for modeling of discharge at the Gaula barrage site in Uttarakhand state of India. The study evaluated, Adaptive Neuro-Fuzzy Inference System (ANFIS), Artificial Neural Network (ANN) and Wavelet-Based Artificial Neural System (WANN) based models to estimate the discharge. The daily data of 12 years (2007-2018) were used to train and test the models. The Gamma test was used to identify the best model for discharge prediction. The input data having a stage with one-day lag and discharge with one and two-days lag and current-day discharge as output was used for discharge modeling. In the case of ANN models, the back-propagation algorithm and hyperbolic tangent sigmoid activation function was used. WANN used Haar, a trous based wavelet function. In ANFIS models, triangular, psig, generalized bell, and Gaussian membership functions were used to train and test the models. The models were evaluated qualitatively and quantitatively using correlation coefficient, root means square error, Willmott index, and coefficient of efficiency. It was found that ANFIS model performed better than ANN and WANN-based models for discharge prediction at the Gaula barrage.

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