scholarly journals Evaluation of Various Precipitation Products Using Ground-Based Discharge Observation at the Nujiang River Basin, China

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2308
Author(s):  
Renjie Mao ◽  
Lei Wang ◽  
Jing Zhou ◽  
Xiuping Li ◽  
Jia Qi ◽  
...  
Keyword(s):  
River Basin ◽  
Hydrological Model ◽  
High Elevation ◽  
Frozen Soil ◽  
The Tibetan Plateau ◽  
Soil Physics ◽  
Correlation Relationship ◽  
Precipitation Product ◽  
Physically Based ◽  
Nujiang River

Precipitation observation and prediction is difficult in many high elevation regions due to the complex terrain and the lack of in situ observations for comparison. The Nujiang River (upper and middle Salween River) basin in the Tibetan Plateau is no exception. Because of this shortcoming, we propose the use of gauge-observed discharge time series at the basin outlet (e.g., Jiayuqiao hydrological station) to evaluate the performance of four different precipitation products (e.g., satellite-based products and reanalysis datasets). A physically-based distributed cryosphere hydrological model with coupled snow and frozen soil physics was adopted to transfer the basin-wide gridded precipitation into the basin-outlet discharges. First, we corrected and evaluated the four precipitation products. A correlation relationship was established between each precipitation product and the available (limited) gauge rainfall within different elevation zones, and then used to correct the four precipitation products in the study basin. Secondly, a distributed cryosphere hydrological model was used to simulate the basin-outlet runoff driven by each corrected precipitation product. The results indicated that modern-era retrospective analysis for Research and Applications, version 2 (MERRA2) precipitation has better performance in the upper Nujiang River basin relative to the other precipitation products based on comparisons of observed and simulated runoff.

scholarly journals Evaluation of global fine-resolution precipitation products and their uncertainty quantification in ensemble discharge simulations

2016 ◽  
Vol 20 (2) ◽  
pp. 903-920 ◽  
Author(s):  
W. Qi ◽  
C. Zhang ◽  
G. Fu ◽  
C. Sweetapple ◽  
H. Zhou
Keyword(s):  
Hydrological Model ◽  
Tropical Rainfall Measuring Mission ◽  
Heavy Precipitation ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Precipitation Product ◽  
Physically Based ◽  
Precipitation Estimation ◽  
Discharge Simulation ◽  
Fine Resolution

Abstract. The applicability of six fine-resolution precipitation products, including precipitation radar, infrared, microwave and gauge-based products, using different precipitation computation recipes, is evaluated using statistical and hydrological methods in northeastern China. In addition, a framework quantifying uncertainty contributions of precipitation products, hydrological models, and their interactions to uncertainties in ensemble discharges is proposed. The investigated precipitation products are Tropical Rainfall Measuring Mission (TRMM) products (TRMM3B42 and TRMM3B42RT), Global Land Data Assimilation System (GLDAS)/Noah, Asian Precipitation – Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and a Global Satellite Mapping of Precipitation (GSMAP-MVK+) product. Two hydrological models of different complexities, i.e. a water and energy budget-based distributed hydrological model and a physically based semi-distributed hydrological model, are employed to investigate the influence of hydrological models on simulated discharges. Results show APHRODITE has high accuracy at a monthly scale compared with other products, and GSMAP-MVK+ shows huge advantage and is better than TRMM3B42 in relative bias (RB), Nash–Sutcliffe coefficient of efficiency (NSE), root mean square error (RMSE), correlation coefficient (CC), false alarm ratio, and critical success index. These findings could be very useful for validation, refinement, and future development of satellite-based products (e.g. NASA Global Precipitation Measurement). Although large uncertainty exists in heavy precipitation, hydrological models contribute most of the uncertainty in extreme discharges. Interactions between precipitation products and hydrological models can have the similar magnitude of contribution to discharge uncertainty as the hydrological models. A better precipitation product does not guarantee a better discharge simulation because of interactions. It is also found that a good discharge simulation depends on a good coalition of a hydrological model and a precipitation product, suggesting that, although the satellite-based precipitation products are not as accurate as the gauge-based products, they could have better performance in discharge simulations when appropriately combined with hydrological models. This information is revealed for the first time and very beneficial for precipitation product applications.

Investigating of River-Aquifer Interactions using Sub-Surface Hydrological Model and Remote Sensing Inputs in an agriculturally Dominated Kosi River Basin, India.

2021 ◽  
Author(s):  
Naga Venkata Satish Laveti ◽  
Suresh A. Kartha ◽  
Subashisa Dutta
Keyword(s):  
Remote Sensing ◽  
Groundwater Recharge ◽  
River Basin ◽  
Hydrological Model ◽  
Temporal Variations ◽  
Interaction Process ◽  
Groundwater Levels ◽  
Physically Based ◽  
Spatio Temporal ◽  
Exchange Flux

<p>River-Aquifer Interaction is a natural and complex phenomenon for understanding its physical dynamic processes. These interactions highly vary with time and space and are to be investigated at river reach scale. The present study aims to understand and quantify the spatio-temporal variations of river-aquifer interaction process in Kosi river basin, India. This basin is majorly dominated with agricultural lands and irrigation requirement of the crops are mostly met by groundwater. In order to quantify the river-aquifer exchange flux at reach scale, a physically based sub-surface hydrological model has been carried for the study area. For this purpose, high resolution remotely sensed evapotranspiration data and groundwater recharge (estimated using soil water budget method method) along with other aquifer parameters were utilized for simulating the monthly groundwater levels as well as exchange flux between river and aquifer. The model results showed that simulated groundwater levels were well calibrated and validated with measured groundwater levels. Further, this calibrated groundwater flow model has been used to quantify the river-aquifer exchange flux. Based on the obtained exchange flux values, three different interaction zones were identified from upstream (Kosi barrage) to downstream (confluence point with Ganga river) in the study reach. It is observed that the river mostly loses water to the aquifer (as influent) in Zone I (80km from upstream) and the river mostly gains water from the aquifer (as effluent) in Zone III (40 km above downstream to confluence point). Whereas, the river has a combination of both losing and gaining natures in Zone II (between Zone I and III). From this study, it can be concluded that use of satellite remote sensing inputs (groundwater recharge and evapotranspiration) in the sub-surface hydrological model, facilitated to improve the assessment and understanding river-aquifer interaction process in an alluvial River basin.</p>

scholarly journals Modelling extreme discharge response to several geostatistically interpolated rainfall using very sparse raingage data

2016 ◽  
Author(s):  
Sarann Ly ◽  
Catherine Sohier ◽  
Catherine Charles ◽  
Aurore Degré
Keyword(s):  
Hydrological Model ◽  
Daily Rainfall ◽  
High Elevation ◽  
Multivariate Geostatistics ◽  
Rainfall Prediction ◽  
External Data ◽  
Thiessen Polygon ◽  
Physically Based ◽  
Key Factor

Abstract. This study presents modelling work of extreme discharge response to rainfall inputs interpolated by geostatistical approaches. Multivariate geostatistics are used by incorporating elevation as external data to improve the rainfall prediction. Thirty year daily rainfall in the Ourthe and Ambleve nested catchments, located in the Ardennes hilly landscape in the Walloon region, Belgium are interpolated and then used as inputs for a distributed physically-based hydrological model (EPIC-GRID). The effect of different raingage densities and particularly the effect of the raingage positions for very sparse raingage data used for rainfall interpolation, on extreme flow is analysed. We propose an index that can illustrate the quality of the raingage distribution with respect to the calculation of extreme discharge. In high elevation sub-catchment, we found that the multivariate geostatistics can significantly improve the rainfall prediction to produce very good simulated peak discharge. In the low elevation sub-catchment and the low raingage density, our results indicated that the Universal Kriging (UNK) is not appropriate. The IDW, Ordinary Kriging (ORK) and Ordinary Cokriging (OCK) methods provide generally good performance. The Thiessen polygon (THI) and Kriging with External Drift (KED) provide good performance for the whole catchment but less good for sub-catchments. The position of the raingages is the key factor for rainfall interpolation, particularly in the data-scarce region. UNK and KED methods are the most sensitive.

Spatial distribution of reference evapotranspiration considering topography in the Taoer river basin of Northeast China

2010 ◽  
Vol 41 (5) ◽  
pp. 424-437 ◽  
Author(s):  
LiQiao Liang ◽  
LiJuan Li ◽  
Qiang Liu
Keyword(s):  
Spatial Distribution ◽  
River Basin ◽  
Reference Evapotranspiration ◽  
Grid Cell ◽  
Spatial Modelling ◽  
High Elevation ◽  
Surface Radiation ◽  
Radiation Environment ◽  
Physically Based ◽  
Elevation Model

Spatial distribution of reference evapotranspiration (ET0) is essential in water resources planning and management, especially in semi-arid areas. In this paper, a digital elevation model is used in an ‘interpolate-then-calculate’ approach to calculating the spatially distributed ET0 using the physically based Penman–Monteith equation in the Taoer river basin in China. The results show the following. (1) Of 11 interpolation methods, the Inverse Distance Weighting (IDW) method was found to be best for interpolating wind speed and a tri-variate secondary trend surface method was found most suitable for interpolating mean air temperature and relative humidity. Spatial modelling of the radiation environment considered the effects of elevation, slope and aspect. (2) Monthly values in January for the three meteorological variables showed larger spatial variations than in July, and just the reverse of net surface radiation. (3) The resulting ET0 calculated at each grid cell with 200 m resolution and its spatial variation showed strong seasonal variation. Lower ET0 was found in high-elevation southern Great Xingan mountains in the northwest basin, while higher values were located in the plains adjacent to the lower reach. (4) The ET0 distribution by the ‘interpolate-then-calculate’ approach better reflected the effects of topography than that of the ‘calculate-then-interpolate’ approach.

scholarly journals An integration of gauge, satellite and reanalysis precipitation datasets for the largest river basin of the Tibetan Plateau

2020 ◽  
Author(s):  
Yuanwei Wang ◽  
Lei Wang ◽  
Xiuping Li ◽  
Jing Zhou ◽  
Zhidan Hu
Keyword(s):  
Tibetan Plateau ◽  
River Basin ◽  
Spatial Scales ◽  
Water Security ◽  
The Tibetan Plateau ◽  
Brahmaputra River ◽  
Hydrological Simulation ◽  
Precipitation Product ◽  
Basin Scale ◽  
Long Term Trends

Abstract. As the largest river basin of the Tibetan Plateau, the Upper Brahmaputra River Basin (also called “Yarlung Zangbo” in Chinese) has profound impacts on the water security of local and downstream inhabitants. Precipitation in the basin is mainly controlled by the Indian Summer Monsoon and Westerly, and is the key to understand the water resources available in the basin; however, due to sparse observational data constrained by a harsh environment and complex topography, there remains a lack of reliable information on basin-wide precipitation (there are only nine national meteorological stations with continuous observations). To improve the accuracy of basin-wide precipitation data, we integrate various gauge, satellite and reanalysis precipitation datasets, including GLDAS, ITP-Forcing, MERRA2, TRMM and CMA datasets, to develop a new precipitation product for the 1981–2016 period over the Upper Brahmaputra River Basin, at 3-hour and 5-km resolution. The new product has been rigorously validated at different temporal scales (e.g. extreme events, daily to monthly variability, and long-term trends) and spatial scales (point- and basin-scale) with gauge precipitation observations, showing much improved accuracies compared to previous products. An improved hydrological simulation has been achieved (low relative bias: −5.94 %; highest NSE: 0.643) with the new precipitation inputs, showing reliability and potential for multi-disciplinary studies. This new precipitation product is openly accessible at https://doi.org/10.5281/zenodo.3711155 (Wang et al., 2020) and, additionally at the National Tibetan Plateau Data Center (https://data.tpdc.ac.cn, login required).

scholarly journals The Role of Debris Cover in Catchment Runoff: A Case Study of the Hailuogou Catchment, South-Eastern Tibetan Plateau

Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2601 ◽  
Author(s):  
Yong Zhang ◽  
Shiyin Liu ◽  
Qiao Liu ◽  
Xin Wang ◽  
Zongli Jiang ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
High Elevation ◽  
The Tibetan Plateau ◽  
Eastern Tibetan Plateau ◽  
South Eastern ◽  
Lower Elevation ◽  
Debris Cover ◽  
Physically Based ◽  
Catchment Runoff

Runoff from high-elevation, debris-covered glaciers is a crucial water supply in the Tibetan Plateau (TP) and its surroundings, where insufficient debris thickness data make it difficult to analyze its influence. Here, we investigated the role of debris cover in runoff formation of the Hailuogou catchment in the south-eastern Tibetan Plateau for the 1988–2017 period, based on long-term observations combined with a physically based glacio-hydrological model. The catchment is characterized by extensive thin debris on the ablation zones of three debris-covered glaciers. An increasing trend in catchment runoff has been observed in the past three decades, more than 50% of which is attributed to glacier runoff in the last decade. With the exception of the influence of temperature rising and precipitation decreasing, our results underline the importance of debris cover and its spatial features in the glaciological and hydrological processes of the catchment, in which the acceleration effect of debris cover is dominant in the catchment. An experimental analysis indicated that the extraordinary excess meltwater in the catchment is generated from the debris-covered surface, especially the lower elevation region below 3600 m a.s.l.

scholarly journals Predicting floods in a large karst river basin by coupling PERSIANN-CCS QPEs with a physically based distributed hydrological model

2019 ◽  
Vol 23 (3) ◽  
pp. 1505-1532 ◽  
Author(s):  
Ji Li ◽  
Daoxian Yuan ◽  
Jiao Liu ◽  
Yongjun Jiang ◽  
Yangbo Chen ◽  
...  
Keyword(s):  
River Basin ◽  
Relative Error ◽  
Hydrological Model ◽  
Peak Flow ◽  
Coupled Model ◽  
Distributed Hydrological Model ◽  
Flood Simulation ◽  
Flood Prediction ◽  
Physically Based ◽  
Karst River

Abstract. In general, there are no long-term meteorological or hydrological data available for karst river basins. The lack of rainfall data is a great challenge that hinders the development of hydrological models. Quantitative precipitation estimates (QPEs) based on weather satellites offer a potential method by which rainfall data in karst areas could be obtained. Furthermore, coupling QPEs with a distributed hydrological model has the potential to improve the precision of flood predictions in large karst watersheds. Estimating precipitation from remotely sensed information using an artificial neural network-cloud classification system (PERSIANN-CCS) is a type of QPE technology based on satellites that has achieved broad research results worldwide. However, only a few studies on PERSIANN-CCS QPEs have occurred in large karst basins, and the accuracy is generally poor in terms of practical applications. This paper studied the feasibility of coupling a fully physically based distributed hydrological model, i.e., the Liuxihe model, with PERSIANN-CCS QPEs for predicting floods in a large river basin, i.e., the Liujiang karst river basin, which has a watershed area of 58 270 km2, in southern China. The model structure and function require further refinement to suit the karst basins. For instance, the sub-basins in this paper are divided into many karst hydrology response units (KHRUs) to ensure that the model structure is adequately refined for karst areas. In addition, the convergence of the underground runoff calculation method within the original Liuxihe model is changed to suit the karst water-bearing media, and the Muskingum routing method is used in the model to calculate the underground runoff in this study. Additionally, the epikarst zone, as a distinctive structure of the KHRU, is carefully considered in the model. The result of the QPEs shows that compared with the observed precipitation measured by a rain gauge, the distribution of precipitation predicted by the PERSIANN-CCS QPEs was very similar. However, the quantity of precipitation predicted by the PERSIANN-CCS QPEs was smaller. A post-processing method is proposed to revise the products of the PERSIANN-CCS QPEs. The karst flood simulation results show that coupling the post-processed PERSIANN-CCS QPEs with the Liuxihe model has a better performance relative to the result based on the initial PERSIANN-CCS QPEs. Moreover, the performance of the coupled model largely improves with parameter re-optimization via the post-processed PERSIANN-CCS QPEs. The average values of the six evaluation indices change as follows: the Nash–Sutcliffe coefficient increases by 14 %, the correlation coefficient increases by 15 %, the process relative error decreases by 8 %, the peak flow relative error decreases by 18 %, the water balance coefficient increases by 8 %, and the peak flow time error displays a 5 h decrease. Among these parameters, the peak flow relative error shows the greatest improvement; thus, these parameters are of the greatest concern for flood prediction. The rational flood simulation results from the coupled model provide a great practical application prospect for flood prediction in large karst river basins.

scholarly journals Evaluation of TRMM precipitation and its application to distributed hydrological model in Naqu River Basin of the Tibetan Plateau

2016 ◽  
Vol 48 (3) ◽  
pp. 822-839 ◽  
Author(s):  
Denghua Yan ◽  
Shaohua Liu ◽  
Tianling Qin ◽  
Baisha Weng ◽  
Chuanzhe Li ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Tibetan Plateau ◽  
River Basin ◽  
Process Model ◽  
Hydrological Model ◽  
Hydrological Processes ◽  
The Tibetan Plateau ◽  
Precipitation Data ◽  
Distributed Hydrological Model ◽  
Trmm Precipitation

The Tibetan Plateau (TP) is the roof of the world and water towers of Asia. However, research on hydrological processes is restricted by the sparse gauge network in the TP. The distributed hydrological model is an efficient tool to explore hydrological processes. Meanwhile, the spatial distribution of precipitation directly affects the precision of distributed hydrological modelling. The latest TRMM 3B42 (V7) precipitation was evaluated compared with gauge precipitation at station and basin scales in the Naqu River Basin of the TP. The results show that Tropical Rainfall Measuring Mission (TRMM) precipitation overestimated the precipitation with BIAS of 0.2; the intensity distributions of daily precipitation are consistent in the two precipitation data. TRMM precipitation was then corrected by the good linear relation between monthly areal TRMM precipitation and gauge precipitation, and applied into the Water and Energy Process model. The results indicate that the simulated streamflow using both precipitation data produce a good fit with observed streamflow, especially at monthly scale. Furthermore, the better relations between average slopes and runoff coefficients of sub-basins from the corrected TRMM precipitation-based model implies that the spatial distribution of TRMM precipitation is closer to the spatial distribution of actual precipitation, and has an advantage in driving distributed hydrological models.

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