scholarly journals Satellite-based Precipitation Datasets Evaluation Using Gauge Observation and Hydrological Modeling in a Typical Arid Land Watershed of Central Asia

2021 ◽  
Vol 13 (2) ◽  
pp. 221
Author(s):  
Jiabin Peng ◽  
Tie Liu ◽  
Yue Huang ◽  
Yunan Ling ◽  
Zhengyang Li ◽  
...  
Keyword(s):  
Central Asia ◽  
Hydrological Modeling ◽  
Assessment Tool ◽  
Swat Model ◽  
Tropical Rainfall Measuring Mission ◽  
Northwest China ◽  
Lake Basin ◽  
Climate Data ◽  
Bosten Lake ◽  
Satellite Precipitation

Hydrological modeling has always been a challenge in the data-scarce watershed, especially in the areas with complex terrain conditions like the inland river basin in Central Asia. Taking Bosten Lake Basin in Northwest China as an example, the accuracy and the hydrological applicability of satellite-based precipitation datasets were evaluated. The gauge-adjusted version of six widely used datasets was adopted; namely, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (CDR), Climate Hazards Group Infrared Precipitation with Stations (CHIRPS), Global Precipitation Measurement Ground Validation National Oceanic and Atmospheric Administration Climate Prediction Center (NOAA CPC) Morphing Technique (CMORPH), Integrated Multi-Satellite Retrievals for GPM (GPM), Global Satellite Mapping of Precipitation (GSMaP), the Tropical Rainfall Measuring Mission (TRMM) and Multi-satellite Precipitation Analysis (TMPA). Seven evaluation indexes were used to compare the station data and satellite datasets, the soil and water assessment tool (SWAT) model, and four indexes were used to evaluate the hydrological performance. The main results were as follows: (1) The GPM and CDR were the best datasets for the daily scale and monthly scale rainfall accuracy evaluations, respectively. (2) The performance of CDR and GPM was more stable than others at different locations in a watershed, and all datasets tended to perform better in the humid regions. (3) All datasets tended to perform better in the summer of a year, while the CDR and CHIRPS performed well in winter compare to other datasets. (4) The raw data of CDR and CMORPH performed better than others in monthly runoff simulations, especially CDR. (5) Integrating the hydrological performance of the uncorrected and corrected data, all datasets have the potential to provide valuable input data in hydrological modeling. This study is expected to provide a reference for the hydrological and meteorological application of satellite precipitation datasets in Central Asia or even the whole temperate zone.

scholarly journals Assessment of TMPA 3B42V7 and PERSIANN-CDR in Driving Hydrological Modeling in a Semi-Humid Watershed in Northeastern China

2020 ◽  
Vol 12 (19) ◽  
pp. 3133
Author(s):  
Lu Zhang ◽  
Zhuohang Xin ◽  
Huicheng Zhou
Keyword(s):  
Hydrological Modeling ◽  
Assessment Tool ◽  
Surface Flow ◽  
Northeastern China ◽  
Base Flow ◽  
Hydrological Processes ◽  
Superior Performance ◽  
Climate Data ◽  
Satellite Precipitation ◽  
Precipitation Estimation

Recent developments of satellite precipitation products provide an unprecedented opportunity for better precipitation estimation, and thus broaden hydrological application. However, due to the errors and uncertainties of satellite products, a thorough validation is usually required before putting into the real hydrological application. As such, this study aims to provide a comprehensive evaluation on the performances of Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis (TMPA) 3B42V7 and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), as well as their adequacies in simulating hydrological processes in a semi-humid region in the northeastern China. It was found that TMPA 3B42V7 showed a superior performance at the daily and monthly time scales, and had a favorable capture of the rainfall-intensity distribution. Intra-annual comparisons indicated a better representation of TMPA 3B42V7 from January to September, whereas PERSIANN-CDR was more reliable from October to December. The Soil and Water Assessment Tool (SWAT) driven by gauge precipitation data performed excellently with NSE > 0.9, while the performances of TMPA 3B42V7- and PERSIANN-CDR-based models are satisfactory with NSE > 0.5. The performances varied under different flow levels and hydrological years. Water balance analysis indicated a better performance of TMPA 3B42V7 in simulating the hydrological processes, including evapotranspiration, groundwater recharge and total runoff. The runoff compositions (i.e., base flow, subsurface flow, and surface flow) driven by TMPA 3B42V7 were more accordant with the actual hydrological features. This study will not only help recognize the potential satellite precipitation products for local water resources management, but also be a reference for the poor-gauged regions with similar hydrologic and climatic conditions around the world, especially the northeastern China and western Russia.

scholarly journals Applicability and Hydrologic Substitutability of TMPA Satellite Precipitation Product in the Feilaixia Catchment, China

Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1803
Author(s):  
Xiaoli Chen ◽  
Guoru Huang
Keyword(s):  
Assessment Tool ◽  
Swat Model ◽  
Tropical Rainfall Measuring Mission ◽  
Climatic Conditions ◽  
High Latitudes ◽  
Climate Trends ◽  
Runoff Simulation ◽  
Satellite Precipitation ◽  
Precipitation Analysis ◽  
Water Assessment

The assessment of various precipitation products’ performances in extreme climatic conditions has become a topic of interest. However, little attention has been paid to the hydrological substitutability of these products. The objective of this study is to explore the performance of the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) product in the Feilaixia catchment, China. To assess its applicability in extreme consecutive climates, several statistical indices are adopted to evaluate the TMPA performance both qualitatively and quantitatively. The Cox–Stuart test is used to investigate extreme climate trends. The Soil and Water Assessment Tool (SWAT) model is used to test the TMPA hydrological substitutability via three scenarios of runoff simulation. The results demonstrate that the overall TMPA performance is acceptable, except at high-latitudes and locations where the terrain changes greatly. Moreover, the accuracy of the SWAT model is high both in the semi-substitution and full-substitution scenarios. Based on the results, the TMPA product is a useful substitute for the gauged precipitation in obtaining acceptable hydrologic process information in areas where gauged sites are sparse or non-existent. The TMPA product is satisfactory in predicting the runoff process. Overall, it must be used with caution, especially at high latitudes and altitudes.

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 Hydrological modeling of Upper Ribb watershed, Abbay Basin, Ethiopia.

2020 ◽  
Keyword(s):  
Surface Runoff ◽  
Hydrological Modeling ◽  
Assessment Tool ◽  
Swat Model ◽  
Simulated Data ◽  
Coefficient Of Determination ◽  
Climate Data ◽  
Water Balance Components ◽  
Discharge Data ◽  
Forested Areas

<p>Hydrological modeling of a watershed is necessary for water resources planning and management. The hydrology of upper Ribb watershed has been analyzed using spatially semi-distributed Soil and water assessment tool (SWAT) model. This study aimed to determine the water balance components and its relation with the rainfall which reaches to the surface of the earth. Different spatio-temporal (land use, soil, digital elevation model, climate data, river discharge) data were used for hydrological modelling of Upper Ribb watershed. The applicability of SWAT model in Upper Ribb watershed has been evaluated using coefficient of determination (R2) and Nash Sutcliff efficiency (NSE) parameters. The calibration results revealed the observed data showed a very good agreement with the simulated data with the R2 and NSE values of 0.90 and 0.84 respectively. Similarly, the validation results of streamflow were acceptable with the R2 and NSE values of 0.80 and 0.82 respectively. The monthly average streamflow from Upper Ribb watershed were found 13.39 m3/s. The major portion of the rainfall contributes to the surface runoff due to the major percentage of the watershed is covered with agricultural lands. The groundwater flow was high in forested areas, while evapotranspiration was found very high in water bodies (Ribb reservoir). In this study area the rainfall showed a direct relationship with the streamflow. The ratio of streamflow and evapotranspiration with rainfall was 0.61 and 0.36 respectively. Due to the presence of high amount of surface runoff and evapotranspiration the deep recharge which contributes to the ground water is not that much significant.</p>

scholarly journals Baseflow simulation using SWAT model in an inland river basin in Tianshan Mountains, Northwest China

2012 ◽  
Vol 16 (4) ◽  
pp. 1259-1267 ◽  
Author(s):  
Y. Luo ◽  
J. Arnold ◽  
P. Allen ◽  
X. Chen
Keyword(s):  
River Basin ◽  
Hydrological Modeling ◽  
Assessment Tool ◽  
Swat Model ◽  
Northwest China ◽  
Tianshan Mountains ◽  
Soil Freezing ◽  
Low Flow ◽  
Model Based ◽  
The One

Abstract. Baseflow is an important component in hydrological modeling. The complex streamflow recession process complicates the baseflow simulation. In order to simulate the snow and/or glacier melt dominated streamflow receding quickly during the high-flow period but very slowly during the low-flow period in rivers in arid and cold northwest China, the current one-reservoir baseflow approach in SWAT (Soil Water Assessment Tool) model was extended by adding a slow- reacting reservoir and applying it to the Manas River basin in the Tianshan Mountains. Meanwhile, a digital filter program was employed to separate baseflow from streamflow records for comparisons. Results indicated that the two-reservoir method yielded much better results than the one-reservoir one in reproducing streamflow processes, and the low-flow estimation was improved markedly. Nash-Sutcliff efficiency values at the calibration and validation stages are 0.68 and 0.62 for the one-reservoir case, and 0.76 and 0.69 for the two-reservoir case. The filter-based method estimated the baseflow index as 0.60, while the model-based as 0.45. The filter-based baseflow responded almost immediately to surface runoff occurrence at onset of rising limb, while the model-based responded with a delay. In consideration of watershed surface storage retention and soil freezing/thawing effects on infiltration and recharge during initial snowmelt season, a delay response is considered to be more reasonable. However, a more detailed description of freezing/thawing processes should be included in soil modules so as to determine recharge to aquifer during these processes, and thus an accurate onset point of rising limb of the simulated baseflow.

scholarly journals The China Meteorological Assimilation Driving Datasets for the SWAT Model (CMADS) Application in China: A Case Study in Heihe River Basin

2017 ◽  
Author(s):  
Xian-yong Meng ◽  
Hao Wang ◽  
Si-yu Cai ◽  
Xue-song Zhang ◽  
Guo-yong Leng ◽  
...  
Keyword(s):  
River Basin ◽  
Large Scale ◽  
Hydrologic Modeling ◽  
Hydrological Modeling ◽  
Assessment Tool ◽  
Swat Model ◽  
Heihe River Basin ◽  
Heihe River ◽  
Climate Data ◽  
Weather Stations

Large-scale hydrological modeling in China is challenging given the sparse meteorological stations and large uncertainties associated with atmospheric forcing data.Here we introduce the development and use of the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) in the Heihe River Basin(HRB) for improving hydrologic modeling, by leveraging the datasets from the China Meteorological Administration Land Data Assimilation System (CLDAS)(including climate data from nearly 40000 area encryption stations, 2700 national automatic weather stations, FengYun (FY) 2 satellite and radar stations). CMADS uses the Space Time Multiscale Analysis System (STMAS) to fuse data based on ECWMF ambient field and ensure data accuracy. In addition, compared with CLDAS, CMADS includes relative humidity and climate data of varied resolutions to drive hydrological models such as the Soil and Water Assessment Tool (SWAT) model. Here, we compared climate data from CMADS, Climate Forecast System Reanalysis (CFSR) and traditional weather station (TWS) climate forcing data and evaluatedtheir applicability for driving large scale hydrologic modeling with SWAT. In general, CMADS has higher accuracy than CFRS when evaluated against observations at TWS; CMADS also provides spatially continuous climate field to drive distributed hydrologic models, which is an important advantage over TWS climate data, particular in regions with sparse weather stations. Therefore, SWAT model simulations driven with CMADS and TWS achieved similar performances in terms of monthly and daily stream flow simulations, and both of them outperformed CFRS. For example, for the three hydrological stations (Ying Luoxia, Qilian Mountain, and ZhaMasheke) in the HRB at the monthly and daily Nash-Sutcliffe efficiency ranges of 0.75-0.95 and 0.58-0.78, respectively, which are much higher than corresponding efficiency statistics achieved with CFSR (monthly: 0.32-0.49 and daily: 0.26 &ndash; 0.45). The CMADS dataset is available free of charge and is expected to a valuable addition to the existing climate reanalysis datasets for deriving distributed hydrologic modeling in China and other countries in East Asia.

scholarly journals Evaluation of Satellite Precipitation Products for Hydrological Modeling in the Brazilian Cerrado Biome

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2571
Author(s):  
Jhones da S. Amorim ◽  
Marcelo R. Viola ◽  
Rubens Junqueira ◽  
Vinicius A. de Oliveira ◽  
Carlos R. de Mello
Keyword(s):  
Hydrological Modeling ◽  
Assessment Tool ◽  
Hydrological Regime ◽  
Tropical Rainfall Measuring Mission ◽  
Brazilian Cerrado ◽  
Local Data ◽  
Satellite Precipitation ◽  
Cerrado Biome ◽  
Statistical Precision ◽  
P Factor

This study investigates the applicability of Satellite Precipitation Products (SPPs) in streamflow simulations performed in the Brazilian Cerrado biome, which is one of the world’s biodiversity hotspots. Local data from ground observations were used as a reference for evaluating the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) and Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG). The Soil and Water Assessment Tool (SWAT) was used to simulate the streamflow in a subbasin of the Tocantins river basin. Statistical precision metrics showed that both SPPs presented a satisfactory performance for precipitation monitoring on a monthly scale, in which IMERG performed better than TMPA. The Nash–Sutcliff coefficient and Kling–Gupta efficiency obtained for both calibration and validation period were greater than 0.82 and 0.79, respectively, demonstrating that both SPPs were able to simulate the hydrological regime adequately. However, the bias indicated that the SPPs overestimated the observed streamflow. The r-factor and p-factor values showed that both TMPA and IMERG presented low uncertainty in streamflow simulations. SPPs offer a great alternative for monitoring the precipitation and hydrological studies in the Brazilian Cerrado biome, and presented better simulation results than rain gauges.

scholarly journals Baseflow simulation of SWAT model in an inland river basin in Tianshan Mountains, Northwest China

2011 ◽  
Vol 8 (6) ◽  
pp. 10397-10424 ◽  
Author(s):  
Y. Luo ◽  
J. Arnold ◽  
P. Allen ◽  
X. Chen
Keyword(s):  
River Basin ◽  
Hydrological Modeling ◽  
Assessment Tool ◽  
Swat Model ◽  
Northwest China ◽  
Tianshan Mountains ◽  
Soil Freezing ◽  
Low Flow ◽  
Model Based ◽  
The One

Abstract. Baseflow is an important component in hydrological modeling. Complex streamflow recession process complicates the baseflow simulation. In order to simulate the snow and/or glacier melt dominated streamflow receding quickly during high-flow period but very slowly during the low-flow period in rivers in arid and cold Northwest China, the current one-reservoir baseflow approach in SWAT (Soil Water Assessment Tool) model was extended by adding a slow reacting reservoir and applied to the Manas River basin in Tianshan Mountains. Meanwhile, a digital filter program was employed to separate baseflow from streamflow records for comparisons. Results indicated that the two-reservoir method yielded much better results than the one-reservoir one in reproducing streamflow processes, and the low-flow estimation was improved markedly. Nash-Sutcliff efficiency values at the calibration and validation stages are 0.68 and 0.62 for the one-reservoir case, and 0.76 and 0.69 for the two-reservoir case, respectively. The filter-based method estimated the baseflow index as 0.60, while the model-based as o.45. The filter-based baseflow responds almost immediately to surface runoff occurrence at onset of rising limb, while the model-based with a delay. In consideration of watershed surface storage retention and soil freezing/thawing effects on infiltration and recharge during initial snowmelt season, a delay response is considered to be more reasonable. However, a more detailed description of freezing/thawing processes should be included in soil modules so as to determine recharge to aquifer during these processes, and thus an accurate onset point of rising limb of the simulated baseflow.

scholarly journals Hydrologic Assessment of TRMM and GPM-Based Precipitation Products in Transboundary River Catchment (Chenab River, Pakistan)

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1902 ◽  
Author(s):  
Ehtesham Ahmed ◽  
Firas Al Janabi ◽  
Jin Zhang ◽  
Wenyu Yang ◽  
Naeem Saddique ◽  
...  
Keyword(s):  
Hydrological Modeling ◽  
Assessment Tool ◽  
Tropical Rainfall Measuring Mission ◽  
Climatic Data ◽  
River Catchment ◽  
Satellite Precipitation ◽  
Taylor Diagram ◽  
Set Up ◽  
Promising Source ◽  
Chenab River

Water resources planning and management depend on the quality of climatic data, particularly rainfall data, for reliable hydrological modeling. This can be very problematic in transboundary rivers with limited disclosing of data among the riparian countries. Satellite precipitation products are recognized as a promising source to substitute the ground-based observations in these conditions. This research aims to assess the feasibility of using a satellite-based precipitation product for better hydrological modeling in an ungauged and riparian river in Pakistan, i.e., the Chenab River. A semidistributed hydrological model of The soil and water assessment tool (SWAT) was set up and two renowned satellite precipitation products, i.e., global precipitation mission (GPM) IMERG-F v6 and tropical rainfall measuring mission (TRMM) 3B42 v7, were selected to assess the runoff pattern in Chenab River. The calibration was done from 2001–2006 with two years of a warmup period. The validation (2007–2010) results exhibit higher correlation between observed and simulated discharges at monthly timescale simulations, IMERG-F (R2 = 0.89, NSE = 0.82), 3B42 (R2 = 0.85, NSE = 0.72), rather than daily timescale simulations, IMERG-F (R2 = 0.66, NSE = 0.61), 3B42 (R2 = 0.64, NSE = 0.54). Moreover, the comparison between IMERG-F and 3B42, shows that IMERG-F is superior to 3B42 by indicating higher R2, NSE and lower percent bias (PBIAS) at both monthly and daily timescale. The results are strengthened by Taylor diagram statistics, which represent a higher correlation (R) and less RMS error between observed and simulated values for IMERG-F. IMERG-F has great potential utility in the Chenab River catchment as it outperformed the 3B42 precipitation in this study. However, its poor skill of capturing peaks at daily timescale remains, leaving a room for IMERG-F to improve its algorithm in the upcoming release.

scholarly journals Evaluation and Hydrological Application of a Data Fusing Method of Multi-Source Precipitation Products-A Case Study Over Tuojiang River Basin

2021 ◽  
Vol 13 (13) ◽  
pp. 2630
Author(s):  
Yao Li ◽  
Wensheng Wang ◽  
Guoqing Wang ◽  
Siyi Yu
Keyword(s):  
River Basin ◽  
Hydrological Modeling ◽  
Assessment Tool ◽  
Swat Model ◽  
Weighted Average ◽  
Probability Of Detection ◽  
Coefficient Of Determination ◽  
Maximum Probability ◽  
Satellite Precipitation

Precipitation is an essential driving factor of hydrological models. Its temporal and spatial resolution and reliability directly affect the accuracy of hydrological modeling. Acquiring accurate areal precipitation needs substantial ground rainfall stations in space. In many basins, ground rainfall stations are sparse and uneven, so real-time satellite precipitation products (SPPs) have become an important supplement to ground-gauged precipitation (GGP). A multi-source precipitation fusion method suitable for the Soil and Water Assessment Tool (SWAT) model has been proposed in this paper. First, the multivariate inverse distance similarity method (MIDSM) was proposed to search for the optimal representative precipitation points of GGP and SPPs in sub-basins. Subsequently, the correlation-coefficient-based weighted average method (CCBWA) was presented and applied to calculate the fused multi-source precipitation product (FMSPP), which combined GGP and multiple satellite precipitation products. The effectiveness of the FMSPP was proven over the Tuojiang River Basin. In the case study, three SPPs were chosen as the satellite precipitation sources, namely the Climate Forecast System Reanalysis (CFSR), Tropical Rainfall Measuring Mission Project (TRMM), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network Climate Data Record (PERSIANN-CDR). The evaluation indicators illustrated that FMSPP could capture the occurrence of rainfall events very well, with a maximum Probability of Detection (POD) and Critical Success Index (CSI) of 0.92 and 0.83, respectively. Furthermore, its correlation with GGP, changing in the range of 0.84–0.96, was higher in most sub-basins on the monthly scale than the other three SPPs. These results demonstrated that the performance of FMSPP was the best compared with the original SPPs. Finally, FMSPP was applied in the SWAT model and was found to effectively drive the SWAT model in contrast with a single precipitation source. The FMSPP manifested the highest accuracy in hydrological modeling, with the Coefficient of Determination (R2) of 0.84, Nash Sutcliff (NS) of 0.83, and Percent Bias (PBIAS) of only −1.9%.

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