scholarly journals Uncertainty and Bias in Satellite-Based Precipitation Estimates over Indian Subcontinental Basins: Implications for Real-Time Streamflow Simulation and Flood Prediction*

2016 ◽  
Vol 17 (2) ◽  
pp. 615-636 ◽  
Author(s):  
Harsh L. Shah ◽  
Vimal Mishra
Keyword(s):  
Real Time ◽  
River Basin ◽  
Large Population ◽  
River Basins ◽  
The Other ◽  
Climate Data ◽  
Infiltration Capacity ◽  
Mahanadi River ◽  
Daily Streamflow ◽  
Better Than

Abstract Real-time streamflow monitoring is essential over the Indian subcontinental river basins, as a large population is affected by floods. Moreover, streamflow monitoring helps in managing water resources in the agriculture-dominated region. In this study, the authors systematically investigated the bias and uncertainty in satellite-based precipitation products [Climate Prediction Center morphing technique (CMORPH); Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN); PERSIANN Climate Data Record (PERSIANN-CDR); and Tropical Rainfall Measuring Mission (TRMM), version 7, real-time (3B42RTV7) and gauge-adjusted (3B42V7) products] over the Indian subcontinental river basins for the period of 2000–13. Moreover, the authors evaluated the influence of bias in the satellite precipitation on real-time streamflow monitoring and flood assessment over the Mahanadi river basin. Results showed that CMORPH and PERSIANN underestimated daily mean precipitation over the majority of the subcontinental river basins. On the other hand, TRMM-3B42RTV7 overestimated daily mean precipitation over most of the river basins in the subcontinent. While gauge-adjusted products of PERSIANN (PERSIANN-CDR) and TRMM (TRMM-3B42V7) performed better than their real-time products, large biases remain in their performance to capture extreme precipitation (both frequency and magnitudes) over the subcontinental basins. Among the real-time precipitation products, TRMM-3B42RTV7 performed better than CMORPH and PERSIANN over the majority of the Indian subcontinental basins. Daily streamflow simulations using the Variable Infiltration Capacity model (VIC) for the Mahanadi river basin showed a better performance by the TRMM-3B42RTV7 product than the other real-time datasets. Moreover, daily streamflow simulations over the Mahanadi river basin showed that bias in real-time precipitation products affects the initial condition and precipitation forcing, which in turn affects flood peak timing and magnitudes.

scholarly journals Assessing the Uncertainties of Four Precipitation Products for Swat Modeling in Mekong River Basin

2019 ◽  
Vol 11 (3) ◽  
pp. 304 ◽  
Author(s):  
Xiongpeng Tang ◽  
Jianyun Zhang ◽  
Chao Gao ◽  
Gebdang Ruben ◽  
Guoqing Wang
Keyword(s):  
River Basin ◽  
Assessment Tool ◽  
Model Performance ◽  
Mekong River ◽  
Distributed Hydrological Model ◽  
Parameter Uncertainties ◽  
Mekong River Basin ◽  
Daily Streamflow ◽  
Precipitation Estimates ◽  
Better Than

Using hydrological simulation to evaluate the accuracy of satellite-based and reanalysis precipitation products always suffer from a large uncertainty. This study evaluates four widely used global precipitation products with high spatial and temporal resolutions [i.e., AgMERRA (AgMIP modern-Era Retrospective Analysis for Research and Applications), MSWEP (Multi-Source Weighted-Ensemble Precipitation), PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record), and TMPA (Tropical Rainfall Measuring Mission 3B42 Version7)] against gauge observations with six statistical metrics over Mekong River Basin (MRB). Furthermore, the Soil and Water Assessment Tool (SWAT), a widely used semi-distributed hydrological model, is calibrated using different precipitation inputs. Both model performance and uncertainties of parameters and prediction have been quantified. The following findings were obtained: (1) The MSWEP and TMPA precipitation products have good accuracy with higher CC, POD, and lower ME and RMSE, and the AgMERRA precipitation estimates perform better than PERSIANN-CDR in this rank; and (2) out of the six different climate regions of MRB, all six metrics are worse than that in the whole MRB. The AgMERRA can better reproduce the occurrence and contributions at different precipitation densities, and the MSWEP has the best performance in Cwb, Cwa, Aw, and Am regions that belong to the low latitudes. (3) Daily streamflow predictions obtained using MSWEP precipitation estimates are better than those simulated by other three products in term of both the model performance and parameter uncertainties; and (4) although MSWEP better captures the precipitation at different intensities in different climatic regions, the performance can still be improved, especially in the regions with higher altitude.

scholarly journals Microwave Snow-Water Equivalent Mapping of the Upper Colorado River Basin, U.S.A. (Abstract)

1987 ◽  
Vol 9 ◽  
pp. 244-245
Author(s):  
W.J. Campbell ◽  
E.G. Josberger ◽  
P. Gloersen ◽  
A.T.C. Chang
Keyword(s):  
Real Time ◽  
River Basin ◽  
Crystal Size ◽  
Colorado River ◽  
Snow Water Equivalent ◽  
The Other ◽  
Colorado River Basin ◽  
Snow Pack ◽  
Upper Colorado River Basin ◽  
Snow Water

During spring 1984, a joint agency research effort was made to explore the use of satellite passive microwave techniques to measure snow-water equivalents in the upper Colorado River basin. This study involved the near real-time acquisition of microwave radiances from the Scanning Multichannel Microwave Radiometer (SMMR) aboard the Nimbus-7 satellite, coupled with quasi-simultaneous surface measurements of snow-pack depth and profiles of temperature, density, and crystal size within the basin. A key idea in this study was to compare, for the same space and time-scales, the SMMR synoptic physics data taken in the basin. Such a snow-measurement program was logistically difficult, but two field teams took detailed snow-pit measurements at 18 sites in Colorado, Utah, and Wyoming during the last 2 weeks of March, when the snow-pack is normally at its maximum extent and depth. These observations were coupled with snow-water-equivalent measurements from Soil Conservation Service SNOTEL sites. Microwave- gradient ratio, Gr (Gr is the difference of the vertically polarized radiances at 8 mm and 17 mm divided by the sum), maps of the basin were derived in a near real-time mode every 6 days from SMMR observations. The sequential Gr maps showed anomalously low values in the Wyoming snow-pack when compared to the other states. This near real-time information then directed the field teams to Wyoming to carry out an extensive survey, which showed that these values were due to the presence of depth hoar; the average crystal sizes were more than twice as large as in the other areas. SMMR can be used to monitor the spatial distribution and temporal evolution of crystal size in snow-packs. Also, scatter diagrams of snow-water equivalents from the combined snow-pit and SNOTEL observations versus Gr from the Wyoming part, and the Colorado and Utah part, of the basin can be used to estimate snow-water equivalents for various parts of the basin.

scholarly journals Fish fauna of headwater streams that cross the Atlantic Forest of south São Paulo state

Check List ◽  
2012 ◽  
Vol 8 (3) ◽  
pp. 421 ◽  
Author(s):  
Mauricio Cetra ◽  
Walter Barrella ◽  
Francisco Langeani Neto ◽  
Abílio G. Martins ◽  
Bruno J. Mello ◽  
...  
Keyword(s):  
Endangered Species ◽  
Exotic Species ◽  
River Basin ◽  
Headwater Streams ◽  
Fish Fauna ◽  
River Basins ◽  
The Other ◽  
Misgurnus Anguillicaudatus ◽  
Dry Period ◽  
Paulo State

The fishes of the present study were collected in the headwater streams of the Sorocaba, Paranapanema and Ribeira de Iguape river basins during the dry period in 2010. A total of 2892 fishes, grouped in 53 species, were captured. The composition of the ichthyofauna captured in the streams of Sorocaba and Paranapanema river basin was greatly similar. On the other hand, the fish fauna of the streams of Ribeira de Iguape river basin were quite different from the ones captured in the others basins, with the occurrence of endangered species (Isbrueckerichthys epakmos and I. duseni) and exotic species (Misgurnus anguillicaudatus). The previous list of fish for the Sorocaba river basin increased with the addition of seven species of Characiformes, one Gymnotiformes and four Siluriformes.

scholarly journals Evaluation and Hydrological Application of CMADS against TRMM 3B42V7, PERSIANN-CDR, NCEP-CFSR, and Gauge-Based Datasets in Xiang River Basin of China

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1225 ◽  
Author(s):  
Xichao Gao ◽  
Qian Zhu ◽  
Zhiyong Yang ◽  
Hao Wang
Keyword(s):  
River Basin ◽  
Bayesian Model Averaging ◽  
Assessment Tool ◽  
Swat Model ◽  
Model Averaging ◽  
Tropical Rainfall Measuring Mission ◽  
Probability Of Detection ◽  
Climate Data ◽  
Xiang River ◽  
Better Than

Satellite-based and reanalysis precipitation products provide a practical way to overcome the shortage of gauge precipitation data because of their high spatial and temporal resolution. This study compared two reanalysis precipitation datasets (the China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS), the National Centers for Environment Prediction Climate Forecast System Reanalysis (NCEP-CFSR)) and two satellite-based datasets (the Tropical Rainfall Measuring Mission 3B42 Version 7 (3B42V7) and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR)) with observed precipitation in the Xiang River basin in China at two spatial (grids and the whole basin) and two temporal (daily and monthly) scales. These datasets were then used as inputs to a SWAT model to evaluate their usefulness in hydrological prediction. Bayesian model averaging was used to discriminate dataset performance. The results show that: (1) for daily timesteps, correlations between reanalysis datasets and gauge observations are >0.55, better than satellite-based datasets; The bias values of satellite-based datasets are <10% at most evaluated grid locations and for the whole baseline. PERSIANN-CDR cannot detect the spatial distribution of rainfall events; the probability of detection (POD) of PERSIANN-CDR at most evaluated grids is <0.50; (2) CMADS and 3B42V7 are better than PERSIANN-CDR and NCEP-CFSR in most situations in terms of correlation with gauge observations; satellite-based datasets are better than reanalysis datasets in terms of bias; and (3) CMADS and 3B42V7 simulate streamflow well for both daily (The Nash-Sutcliffe coefficient (NS) > 0.70) and monthly (NS > 0.80) timesteps; NCEP-CFSR is worst because it substantially overestimates streamflow; PERSIANN-CDR is not good because of its low NS (0.40) during the validation period.

scholarly journals Geospatial evaluation of drought resilience in sub-basins of Mahanadi river in India

2020 ◽  
Vol 20 (7) ◽  
pp. 2826-2844
Author(s):  
Preeti Rajput ◽  
Manish Kumar Sinha
Keyword(s):  
River Basin ◽  
Climatic Factors ◽  
Anthropogenic Activities ◽  
Central India ◽  
River Basins ◽  
Drought Vulnerability ◽  
High Coverage ◽  
Mahanadi River ◽  
Geospatial Database ◽  
Optimum Utilization

Abstract Development is said to be sustainable in respect of drought if the effect has been absorbed by the existing system. Occurrence of drought depends on physiographical, climatic factors and optimum utilization of available resources of the river basin. This study aims to evaluate the vulnerability and resilience of river basin systems for the identification of priority areas under drought susceptibility for three different river basins, namely Arpa, Kharun and Upper Seonath of Mahanadi river in central India, as a pilot area for this study. The study represents an approach to evaluate the drought susceptibility of river basins based on physiographical factors and anthropogenic activities. A model proposed for vulnerability assessment based on variables of exposure, sensitivity and adaptive capacity, and a geospatial database of basin characteristics contributing to vulnerability, was generated using remote sensing and a geographic information system. Multi-criteria decision analysis was done to evaluate the influence of river basin characteristics, population load and land-use/cover on drought susceptibility for assessing the drought vulnerability of the river basin and suggest the solution for the optimum utilization of natural resources according to the river basin characteristics. The result of this study demarcates the area in four categories of Extremely vulnerable, Moderately vulnerable, Vulnerable and Not vulnerable. On the analysis, only 3.86% of Upper Seonath is Not vulnerable, followed by Kharun basin having 15.59% as Not vulnerable area and 48.23% of the area of Arpa river basin identified as Not vulnerable. Arpa river basin is least affected by drought due to its lower population density and high coverage of forest and agriculture area.

scholarly journals Flood Forecasting in Large River Basins Using FOSS Tool and HPC

Water ◽  
2021 ◽  
Vol 13 (24) ◽  
pp. 3484
Author(s):  
Upasana Dutta ◽  
Yogesh Kumar Singh ◽  
T. S. Murugesh Prabhu ◽  
Girishchandra Yendargaye ◽  
Rohini Gopinath Kale ◽  
...  
Keyword(s):  
Open Source ◽  
River Basin ◽  
Indian Subcontinent ◽  
River Basins ◽  
Flood Forecasting ◽  
Economic Losses ◽  
Design Development ◽  
Irreversible Damage ◽  
Flood Prediction ◽  
Mahanadi River

The Indian subcontinent is annually affected by floods that cause profound irreversible damage to crops and livelihoods. With increased incidences of floods and their related catastrophes, the design, development, and deployment of an Early Warning System for Flood Prediction (EWS-FP) for the river basins of India is needed, along with timely dissemination of flood-related information for mitigation of disaster impacts. Accurately drafted and disseminated early warnings/advisories may significantly reduce economic losses incurred due to floods. This study describes the design and development of an EWS-FP using advanced computational tools/methods, viz. HPC, remote sensing, GIS technologies, and open-source tools for the Mahanadi River Basin of India. The flood prediction is based on a robust 2D hydrodynamic model, which solves shallow water equations using the finite volume method. The model is open-source, supports geographic file formats, and is capable of simulating rainfall run-off, river routing, and tidal forcing, simultaneously. The model was tested for a part of the Mahanadi River Basin (Mahanadi Delta, 9225 sq km) with actual and predicted discharge, rainfall, and tide data. The simulated flood inundation spread and stage were compared with SAR data and CWC Observed Gauge data, respectively. The system shows good accuracy and better lead time suitable for flood forecasting in near-real-time.

scholarly journals Microwave Snow-Water Equivalent Mapping of the Upper Colorado River Basin, U.S.A. (Abstract)

1987 ◽  
Vol 9 ◽  
pp. 244-245
Author(s):  
W.J. Campbell ◽  
E.G. Josberger ◽  
P. Gloersen ◽  
A.T.C. Chang
Keyword(s):  
Real Time ◽  
River Basin ◽  
Crystal Size ◽  
Colorado River ◽  
Snow Water Equivalent ◽  
The Other ◽  
Colorado River Basin ◽  
Snow Pack ◽  
Upper Colorado River Basin ◽  
Snow Water

During spring 1984, a joint agency research effort was made to explore the use of satellite passive microwave techniques to measure snow-water equivalents in the upper Colorado River basin. This study involved the near real-time acquisition of microwave radiances from the Scanning Multichannel Microwave Radiometer (SMMR) aboard the Nimbus-7 satellite, coupled with quasi-simultaneous surface measurements of snow-pack depth and profiles of temperature, density, and crystal size within the basin. A key idea in this study was to compare, for the same space and time-scales, the SMMR synoptic physics data taken in the basin. Such a snow-measurement program was logistically difficult, but two field teams took detailed snow-pit measurements at 18 sites in Colorado, Utah, and Wyoming during the last 2 weeks of March, when the snow-pack is normally at its maximum extent and depth. These observations were coupled with snow-water-equivalent measurements from Soil Conservation Service SNOTEL sites. Microwave- gradient ratio, Gr (Gr is the difference of the vertically polarized radiances at 8 mm and 17 mm divided by the sum), maps of the basin were derived in a near real-time mode every 6 days from SMMR observations. The sequential Gr maps showed anomalously low values in the Wyoming snow-pack when compared to the other states. This near real-time information then directed the field teams to Wyoming to carry out an extensive survey, which showed that these values were due to the presence of depth hoar; the average crystal sizes were more than twice as large as in the other areas. SMMR can be used to monitor the spatial distribution and temporal evolution of crystal size in snow-packs. Also, scatter diagrams of snow-water equivalents from the combined snow-pit and SNOTEL observations versus Gr from the Wyoming part, and the Colorado and Utah part, of the basin can be used to estimate snow-water equivalents for various parts of the basin.

scholarly journals Accuracy evaluation of GPM multi-satellite precipitation products in the hydrological application over alpine and gorge regions with sparse rain gauge network

2019 ◽  
Vol 50 (6) ◽  
pp. 1710-1729 ◽  
Author(s):  
Jiachao Chen ◽  
Zhaoli Wang ◽  
Xushu Wu ◽  
Xiaohong Chen ◽  
Chengguang Lai ◽  
...  
Keyword(s):  
Real Time ◽  
River Basin ◽  
Rain Gauge ◽  
Accuracy Evaluation ◽  
Precipitation Data ◽  
Infiltration Capacity ◽  
Lancang River ◽  
Processed Products ◽  
Global Precipitation ◽  
The Lancang River Basin

Abstract With the release of Global Precipitation Measurement Integrated Multi-satellitE Retrievals for GPM products, hydrologists can obtain precipitation data with higher resolution and wider coverage. However, great uncertainties still exist in the accuracy and hydrological utility of these data in alpine and gorge regions with sparse gauge stations. In this study, the Lancang River Basin in China was used as an example, and near real-time products (IMERG-E and IMERG-L) and post-processed products (IMERG-F and TMPA 3B42-V7) were evaluated. Different indexes and methods were applied to evaluate the accuracy of these products. The variable infiltration capacity hydrological model was adopted to evaluate their hydrological utility. The following findings were obtained. (1) Compared with observed precipitation data, the near real-time products tend to underestimate, while the post-processed products tend to overestimate precipitation. The performance of the four products in winter is poor. (2) IMERG products offer improvements in two aspects: first, the near real-time products achieve good accuracy and second, the detectability and the accuracy in gorge areas have been greatly improved. (3) The near real-time products have the potential for hydrological applications. The best simulation result was obtained based on IMERG-F, followed by 3B42-V7, IMERG-E, and IMERG-L. (4) The four products can provide reliable precipitation data for the hydrological application over the Lancang River Basin.

scholarly journals Study on Runoff Simulation of the Source Region of the Yellow River and the Inland Arid Source Region Based on the Variable Infiltration Capacity Model

2020 ◽  
Vol 12 (17) ◽  
pp. 7041
Author(s):  
Yuan Wang ◽  
Wengang Zheng ◽  
Hongwei Xie ◽  
Qi Liu ◽  
Jiahua Wei
Keyword(s):  
River Basin ◽  
Yellow River ◽  
Source Region ◽  
Source Area ◽  
River Basins ◽  
The Yellow River ◽  
Hydrological Process ◽  
Variable Infiltration Capacity ◽  
Infiltration Capacity ◽  
Runoff Simulation

Hydrological process simulation and rainfall–runoff analysis are important foundations for reasonably evaluating changes in water resources. In this paper, the VIC (Variable Infiltration Capacity) hydrological model was used to simulate runoff without observed data for exploring the applicability of the model in the Kequ, Dari, and Jimai river basins in the source region of the Yellow River, and the Balegen River basin in the inland arid source region. The results show that, from 2015 to 2018, the VIC model had a good simulation effect. The Nash efficiency coefficients (NSE) of the four basins were all above 0.7, and the NSE of the Dari River basin reached 0.93. The relative error (RE) of the three river basins was about 5%, on average, and the RE of the Balegen basin was 6.50%, indicating that the model has good applicability in the study area. Climate perturbation experiments were performed to quantitatively analyze the relationship between rainfall and runoff. The results show that, in the source area of the Yellow River, rainfall and runoff are roughly linearly related. However, in the inland arid source area, temperature has a slightly greater impact on runoff than rainfall.

scholarly journals Evaluation of Remotely Sensed Precipitation and Its Performance for Streamflow Simulations in Basins of the Southeast Tibetan Plateau

2015 ◽  
Vol 16 (6) ◽  
pp. 2577-2594 ◽  
Author(s):  
Sheng Wang ◽  
Suxia Liu ◽  
Xingguo Mo ◽  
Bin Peng ◽  
Jianxiu Qiu ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Real Time ◽  
Climate Prediction ◽  
Model Parameters ◽  
Station Network ◽  
Daily Streamflow ◽  
Areal Precipitation ◽  
Climate Prediction Center ◽  
Southeast Tibetan Plateau ◽  
Better Than

Abstract Four satellite-based precipitation products [TMPA real time (T-rt), its gauge-adjusted version (T-adj), Climate Prediction Center (CPC) morphing technique (CMORPH) real time (C-rt), and its gauge-adjusted version (C-adj)] were evaluated by a gauge-based synthesis dataset. Further, these products along with the CMORPH gauge–satellite blended version (C-ga), which is virtually C-adj in precipitation ungauged regions and is controlled by gauge analysis over regions of a dense station network, were intercompared with daily streamflow predicted by the distributed vegetation interface processes (VIP) model in the Lhasa and Gongbo basins of the southeast Tibetan Plateau. Results show these satellite-based products perform better in summer than in other seasons. Relative to the gauge-based synthesis dataset, for areal precipitation of the Lhasa basin from 2007 to 2010, biases of C-rt and T-rt are −10.49% and 157.88%, respectively. Biases of C-adj and T-adj are 3.42% and 24.12%, respectively. The C-rt bias is underestimation of the volume of observed rainfall correctly detected and overestimation of the volume of falsely alarmed rainfall, while T-rt bias comes from overestimation of the volume of observed rainfall correctly detected. Simulation efficiencies of stream discharges driven by T-adj and C-adj are better than those by T-rt and C-rt, which are consistent with the accuracies of these products. With benchmarked model parameters using the gauge-based dataset, C-adj presents well for simulation, while T-adj needs parameter recalibration to achieve good skills. Compared to T-adj and C-adj, better simulation could be obtained by C-ga in precipitation-gauged regions.

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