A Methodological Framework to Combine Multiple Precipitation Datasets for Improving Streamflow Simulations: A test study in the Saskatchewan River basin, Canada

2020 ◽  
Author(s):  
Jefferson Wong ◽  
Fuad Yassin ◽  
James Famiglietti
Keyword(s):  
River Basin ◽  
Land Surface ◽  
Large River ◽  
Combination Method ◽  
Methodological Framework ◽  
Surface Hydrology ◽  
Test Study ◽  
Basin Scale ◽  
Precipitation Estimation

<p>Obtaining reliable precipitation measurements and accurate spatiotemporal distribution of precipitation remains as a challenging task for driving Hydrologic-Land Surface Models (H-LSMs) and better hydrological simulations and predictions. To further improve the accuracy of precipitation estimation for hydrological applications, the idea of generating a hybrid dataset by combining existing precipitation products has become a more appealing approach in recent years. The reliability of the hybrid dataset is evaluated against in-situ climate stations and error characteristics are calculated to compare to the existing products. However, the robustness of the hybrid dataset in representing spatial details could be problematic when evaluated only using a sparse network of in-situ observations at regional or basin scales. This study aims to develop a methodological framework that combines multiple precipitation products based on evaluation against not only climate stations but also streamflow stations that are spatially representative across large river basin. The framework is illustrated using a Canadian H-LSM named MESH (Modélisation Environmentale communautaire - Surface Hydrology) in the Saskatchewan River basin, Canada over the period of 2002 to 2012. Five existing precipitation datasets are considered as the candidates for generating the hybrid dataset. The framework consists of three components. The first component evaluates each precipitation candidate against the local gauge data for benchmarking, runs each candidate through MESH with 10 km spatial resolution and default parameterization, and calculates the overall streamflow performance in each sub-basins with equal weighting of three evaluation metrics. The second component generates the hybrid dataset by combining the best performing candidates (annual or seasonal) at sub-basin scale. The third component assesses the performance of the hybrid dataset at downstream gauge stations along the mainstream as a validation mechanism for comparison with the performance of the candidate datasets. Results shows that the hybrid dataset is able to perform equally well with the existing precipitation products in the headwater while improve the streamflow performance downstream. The successful application of the framework in this river basin could build the foundation and the confidence in applying the combination method to data-limited river basins in northern Canada.</p>

scholarly journals A combined use of in situ and satellite-derived observations to characterize surface hydrology and its variability in the Congo River Basin

2021 ◽  
Author(s):  
Benjamin Kitambo ◽  
Fabrice Papa ◽  
Adrien Paris ◽  
Raphael Tshimanga ◽  
Stephane Calmant ◽  
...  
Keyword(s):  
Surface Water ◽  
River Basin ◽  
Main Stream ◽  
Surface Hydrology ◽  
Radar Altimetry ◽  
Congo River ◽  
Basin Scale ◽  
Congo River Basin ◽  
In Situ Observations

Abstract. The Congo River Basin (CRB) is the second largest river system in the world, but its hydroclimatic characteristics remain relatively poorly known. Here, we jointly analyze a large record of in situ and satellite-derived observations, including long term time series of Surface Water Height (SWH) from radar altimetry (a total of 2,311 virtual stations) and surface water extent (SWE) from a multi-satellite technique to better characterize CRB surface hydrology and its variability. Firstly, we show that SWH from radar altimetry multi-missions agree well with in situ water stage at various locations, with root mean square deviation varying from 10 cm (with Sentinel-3A) to 75 cm (with European Remote Sensing-2). SWE from multi-satellite observations also shows a good behavior over a ~25-year period against in situ observations from sub-basin to basin scale. Both datasets help to better characterize the large spatial and temporal variability of hydrological patterns across the basin, with SWH exhibiting annual amplitude of more than 5 m in the northern sub-basins while Congo main-stream and Cuvette Centrale tributaries vary in smaller proportions (1.5 m to 4.5 m). Furthermore, SWH and SWE help better illustrate the spatial distribution and different timings of the CRB annual flood dynamic and how each sub-basin and tributary contribute to the hydrological regime at the outlet of the basin (the Brazzaville/Kinshasa station), including its peculiar bi-modal pattern. Across the basin, we jointly use SWH and SWE to estimate time lag and water travel time to reach the Brazzaville/Kinshasa station, ranging from 0–1 month in its vicinity downstream the basin up to 3 months in remote areas and small tributaries. Northern sub-basins and the central Congo region highly contribute to the large peak in December–January while the southern part of the basin supplies water to both hydrological peaks, in particular to the moderate one in April–May. The results are supported using in situ observations at various locations in the basin. Our results contribute to a better characterization of the hydrological variability in the CRB and represent an unprecedented source of information for hydrological modeling and to study hydrological processes over the region.

scholarly journals A New Land Surface Hydrology within the Noah-WRF Land-Atmosphere Mesoscale Model Applied to Semiarid Environment: Evaluation over the Dantiandou Kori (Niger)

2009 ◽  
Vol 2009 ◽  
pp. 1-13 ◽  
Author(s):  
B. Decharme ◽  
C. Ottlé ◽  
S. Saux-Picart ◽  
N. Boulain ◽  
B. Cappelaere ◽  
...  
Keyword(s):  
Land Surface ◽  
Mesoscale Model ◽  
West African Monsoon ◽  
Radar Data ◽  
Rain Gauge ◽  
Surface Energy Budget ◽  
Surface Hydrology ◽  
Land Surface Hydrology ◽  
Rain Gauge Network

Land-atmosphere feedbacks, which are particularly important over the Sahel during the West African Monsoon (WAM), partly depend on a large range of processes linked to the land surface hydrology and the vegetation heterogeneities. This study focuses on the evaluation of a new land surface hydrology within the Noah-WRF land-atmosphere-coupled mesoscale model over the Sahel. This new hydrology explicitly takes account for the Dunne runoff using topographic information, the Horton runoff using a Green-Ampt approximation, and land surface heterogeneities. The previous and new versions of Noah-WRF are compared against a unique observation dataset located over the Dantiandou Kori (Niger). This dataset includes dense rain gauge network, surfaces temperatures estimated from MSG/SEVIRI data, surface soil moisture mapping based on ASAR/ENVISAT C-band radar data and in situ observations of surface atmospheric and land surface energy budget variables. Generally, the WAM is reasonably reproduced by Noah-WRF even if some limitations appear throughout the comparison between simulations and observations. An appreciable improvement of the model results is also found when the new hydrology is used. This fact seems to emphasize the relative importance of the representation of the land surface hydrological processes on the WAM simulated by Noah-WRF over the Sahel.

scholarly journals Reliability of Gridded Precipitation Products in the Yellow River Basin, China

2020 ◽  
Vol 12 (3) ◽  
pp. 374 ◽  
Author(s):  
Yanfen Yang ◽  
Jing Wu ◽  
Lei Bai ◽  
Bing Wang
Keyword(s):  
River Basin ◽  
Yellow River ◽  
Tropical Rainfall Measuring Mission ◽  
Yellow River Basin ◽  
Superior Performance ◽  
The Yellow River ◽  
Basin Scale ◽  
Precipitation Estimation ◽  
Precipitation Analysis ◽  
The Yellow River Basin

Gridded precipitation products are the potential alternatives in hydrological studies, and the evaluation of their accuracy and potential use is very important for reliable simulations. The objective of this study was to investigate the applicability of gridded precipitation products in the Yellow River Basin of China. Five gridded precipitation products, i.e., Multi-Source Weighted-Ensemble Precipitation (MSWEP), CPC Morphing Technique (CMORPH), Global Satellite Mapping of Precipitation (GSMaP), Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis 3B42, and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), were evaluated against observations made during 2001−2014 at daily, monthly, and annual scales. The results showed that MSWEP had a higher correlation and lower percent bias and root mean square error, while CMORPH and GSMaP made overestimations compared to the observations. All the datasets underestimated the frequency of dry days, and overestimated the frequency and the intensity of wet days (0–5 mm/day). MSWEP and TRMM showed consistent interannual variations and spatial patterns while CMORPH and GSMaP had larger discrepancies with the observations. At the sub-basin scale, all the datasets performed poorly in the Beiluo River and Qingjian River, whereas they were applicable in other sub-basins. Based on its superior performance, MSWEP was identified as more suitable for hydrological applications.

scholarly journals River Water Quality of the Selenga-Baikal Basin: Part II—Metal Partitioning under Different Hydroclimatic Conditions

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2392
Author(s):  
Nikolay Kasimov ◽  
Galina Shinkareva ◽  
Mikhail Lychagin ◽  
Sergey Chalov ◽  
Margarita Pashkina ◽  
...  
Keyword(s):  
River Basin ◽  
Large River ◽  
Metal Partitioning ◽  
River Systems ◽  
Catchment Scale ◽  
Selenga River Basin ◽  
Extensive Field ◽  
Basin Scale ◽  
Wide Range ◽  
Dissolved Form

The partitioning of metals and metalloids between their dissolved and suspended forms in river systems largely governs their mobility and bioavailability. However, most of the existing knowledge about catchment-scale metal partitioning in river systems is based on a limited number of observation points, which is not sufficient to characterize the complexity of large river systems. Here we present an extensive field-based dataset, composed of multi-year data from over 100 monitoring locations distributed over the large, transboundary Selenga River basin (of Russia and Mongolia), sampled during different hydrological seasons. The aim is to investigate on the basin scale, the influence of different hydroclimatic conditions on metal partitioning and transport. Our results showed that the investigated metals exhibited a wide range of different behaviors. Some metals were mostly found in the dissolved form (84–96% of Mo, U, B, and Sb on an average), whereas many others predominantly existed in suspension (66–87% of Al, Fe, Mn, Pb, Co, and Bi). Nevertheless, our results also showed a consistently increasing share of metals in dissolved form as the metals were transported to the downstream parts of the basin, closer to the Lake Baikal. Under high discharge conditions (including floods), metal transport by suspended particulate matter was significantly greater (about 2–6 times). However, since high and low water conditions could prevail simultaneously at a given point of time within the large river basin, e.g., as a result of on-going flood propagation, snap-shot observations of metal partitioning demonstrated contrasting patterns with domination of both particulate and dissolved phases in different parts of the basin. Such heterogeneity of metal partitioning is likely to be found in many large river systems. These results point out the importance of looking into different hydroclimatic conditions across space and time, both for management purposes and contaminant modeling efforts at the basin scale.

scholarly journals Characterization of Basin-Scale Dynamic Storage–Discharge Relationship Using Daily GRACE Based Storage Anomaly Data

Geosciences ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. 404
Author(s):  
Durga Sharma ◽  
Swagat Patnaik ◽  
Basudev Biswal ◽  
John T. Reager
Keyword(s):  
Land Surface ◽  
Drainage Basin ◽  
Land Surface Model ◽  
Large River ◽  
Surface Model ◽  
Satellite Mission ◽  
Basin Scale ◽  
Potential Applications ◽  
Gravity Recovery

Despite the fact that streamflow occurs mainly due to depletion of storage, our knowledge on how a drainage basin stores and releases water is very limited due to measurement limitations. A window of opportunity, however, is provided to us by GRACE (Gravity Recovery and Climate Experiment) satellite mission that provides storage anomaly (San) data. Many studies have explored a range of potential applications of San data such as flood forecasting. Here we argue that the capability of GRACE satellite mission has not been fully explored as most of the studies in the past have performed analysis using monthly San data for large river basins. In this study, we use daily San data for several mid-sized catchments to perform storage–discharge analysis. Our results support the earlier notion that storage–discharge relationship is highly dynamic. Furthermore, we demonstrate that San data can be exploited for prediction of k of the Brutsaet–Nieber equation −dQ/dt=kQα (Q is discharge at time t). For comparison we also use storage information provided by Catchment Land Surface Model (CLSM) as well as past discharge information to predict k. Our results suggest that GRACE based storage information can be used to predict k reasonably well in gauged as well as ungauged basins.

Nitrate stable isotopes: tools for determining nitrate sources among different land uses in the Mississippi River Basin

2002 ◽  
Vol 59 (12) ◽  
pp. 1874-1885 ◽  
Author(s):  
Cecily C.Y Chang ◽  
Carol Kendall ◽  
Steven R Silva ◽  
William A Battaglin ◽  
Donald H Campbell
Keyword(s):  
Land Use ◽  
Stable Isotopes ◽  
River Basin ◽  
Mississippi River ◽  
Large River ◽  
Mississippi River Basin ◽  
Land Uses ◽  
Nitrate Sources ◽  
Isotopic Signatures ◽  
Basin Scale

A study was conducted to determine whether NO3– stable isotopes (δ15N and δ18O), at natural abundance levels, could discriminate among NO3– sources from sites with different land uses at the basin scale. Water samples were collected from 24 sites in the Mississippi River Basin from five land-use categories: (1) large river basins (>34 590 km2) draining multiple land uses and smaller basins in which the predominant land use was (2) urban, (3) undeveloped, (4) crops, or (5) crops and livestock. Our data suggest that riverine nitrates from different land uses have overlapping but moderately distinct isotopic signatures. δ18O data were critical in showing abrupt changes in NO3– source with discharge. The isotopic values of large rivers resembled crop sites, sites with livestock tended to have δ15N values characteristic of manure, and urban sites tended to have high δ18O values characteristic of atmospheric nitrate.

Regional Parameter Estimation of the VIC Land Surface Model: Methodology and Application to River Basins in China

2007 ◽  
Vol 8 (3) ◽  
pp. 447-468 ◽  
Author(s):  
Zhenghui Xie ◽  
Fei Yuan ◽  
Qingyun Duan ◽  
Jing Zheng ◽  
Miaoling Liang ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
River Basin ◽  
Land Surface ◽  
Land Surface Model ◽  
River Basins ◽  
Large River ◽  
Surface Model ◽  
Parameter Estimates ◽  
Climatic Zones ◽  
Streamflow Simulation

Abstract This paper presents a methodology for regional parameter estimation of the three-layer Variable Infiltration Capacity (VIC-3L) land surface model with the goal of improving the streamflow simulation for river basins in China. This methodology is designed to obtain model parameter estimates from a limited number of calibrated basins and then regionalize them to uncalibrated basins based on climate characteristics and large river basin domains, and ultimately to continental China. Fourteen basins from different climatic zones and large river basins were chosen for model calibration. For each of these basins, seven runoff-related model parameters were calibrated using a systematic manual calibration approach. These calibrated parameters were then transferred within the climate and large river basin zones or climatic zones to the uncalibrated basins. To test the efficiency of the parameter regionalization method, a verification study was conducted on 19 independent river basins in China. Overall, the regionalized parameters, when evaluated against the a priori parameter estimates, were able to reduce the model bias by 0.4%–249.8% and relative root-mean-squared error by 0.2%–119.1% and increase the Nash–Sutcliffe efficiency of the streamflow simulation by 1.9%–31.7% for most of the tested basins. The transferred parameters were then used to perform a hydrological simulation over all of China so as to test the applicability of the regionalized parameters on a continental scale. The continental simulation results agree well with the observations at regional scales, indicating that the tested regionalization method is a promising scheme for parameter estimation for ungauged basins in China.

scholarly journals Hydrological recurrence as a measure for large river basin classification and process understanding

2014 ◽  
Vol 11 (7) ◽  
pp. 8191-8238 ◽  
Author(s):  
R. Fernandez ◽  
T. Sayama
Keyword(s):  
River Basin ◽  
Land Surface ◽  
Fourier Transforms ◽  
Land Surface Model ◽  
Arctic Region ◽  
River Basins ◽  
Large River ◽  
Global Scale ◽  
Surface Model ◽  
Monsoon Area

Abstract. Hydrologic functions of river basins are summarized as water collection, storage and discharge, which can be characterized by the dynamics of hydrological variables including precipitation, evaporation, storage and runoff. In some situations these four variables behave more in a recurrent manner by repeating in a similar range year after year or in other situations they exhibit more randomness with higher variations year by year. The degree of recurrence in runoff is important not only for water resources management but also for hydrologic process understandings, especially in terms of how the other three variables determine the degree of recurrence in runoff. The main objective of this paper is to propose a simple hydrologic classification framework applicable to global scale and large basins based on the combinations of recurrence in the four variables. We evaluate it by Lagged Autocorrelation, Fast Fourier Transforms and Colwell's Indices of variables obtained from EU-WATCH dataset composed by eight hydrologic and land surface model outputs. By setting a threshold to define high or low recurrence in the four variables, we classify each river basin into 16 possible classes. The overview of recurrence patterns at global scale suggested that precipitation is recurrent mainly in the humid tropics, Asian Monsoon area and part of higher latitudes with oceanic influence. Recurrence in evaporation was mainly dependent on the seasonality of energy availability, typically high in the tropics, temperate and subarctic regions. Recurrence in storage at higher latitudes depends on energy/water balances and snow, while that in runoff is mostly affected by the different combinations of these three variables. According to the river basin classification 10 out of the 16 possible classes were present in the 35 largest river basins in the world. In humid tropic region, the basins belong to a class with high recurrence in all the variables, while in subtropical region many of the river basins have low recurrence. In temperate region, the energy limited or water limited in summer characterizes the recurrence in storage, but runoff exhibits generally low recurrence due to the low recurrence in precipitation. In the subarctic and arctic region, the amount of snow also influences the classes; more snow yields higher recurrence in storage and runoff. Our proposed framework follows a simple methodology that can aid in grouping river basins with similar characteristics of water, energy and storage cycles. The framework is applicable at different scales with different datasets to provide useful insights into the understanding of hydrologic regimes based on the classification.

Development of HydroClimatic Conceptual Streamflow (HCCS) model for tropical river basin

2013 ◽  
Vol 5 (1) ◽  
pp. 36-60 ◽  
Author(s):  
Parag P. Bhagwat ◽  
Rajib Maity
Keyword(s):  
Land Surface ◽  
Methodological Approach ◽  
Combined Processes ◽  
Time Varying ◽  
Surface Hydrology ◽  
Daily Streamflow ◽  
Proposed Model ◽  
Ground Water Recharge ◽  
Basin Scale ◽  
Water Recharge

Combined processes of land-surface hydrology and hydroclimatology influence the response of a watershed to different hydroclimatic variables. In this paper, streamflow response of a watershed to hydrometeorological variables is investigated over a part of two tropical Indian rivers – Narmada and Mahanadi. The proposed HydroClimatic Conceptual Streamflow (HCCS) model is able to consider the time-varying basin characteristics and major hydrologic processes to model basin-scale streamflow using climate inputs at a daily scale. In addition, the proposed model is able to provide additional overall estimates of ground water recharge component and evapotranspiration component from the entire basin. Moreover, ability to consider the time-varying watershed characteristics and hydroclimatic inputs renders the proposed model usable for assessment of future streamflow variation. This application is also investigated for both the study basins. In general, the methodological approach of the proposed model can be applied to other tropical basins for daily streamflow modelling as well as future streamflow assessment.

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