scholarly journals Estimation of the Surface Water Budget of the La Plata Basin

2009 ◽  
Vol 10 (4) ◽  
pp. 981-998 ◽  
Author(s):  
Fengge Su ◽  
Dennis P. Lettenmaier

Abstract The Variable Infiltration Capacity (VIC) land surface hydrology model forced by gridded observed precipitation and temperature for the period 1979–99 is used to simulate the land surface water balance of the La Plata basin (LPB). The modeled water balance is evaluated with streamflow observations from the major tributaries of the LPB. The spatiotemporal variability of the water balance terms of the LPB are then evaluated using offline VIC model simulations, the 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40), and inferences obtained from a combination of these two. The seasonality and interannual variability of the water balance terms vary across the basin. Over the Uruguay River basin and the entire LPB, precipitation (P) exceeds evapotranspiration (E) and the basins act as a moisture sink. However, the Paraguay River basin acts as a net source of moisture in dry seasons (strong negative P − E). The annual means and monthly time series of ERA-40 P are in good agreement with gauge observations over the entire LPB and its subbasins, except for the Uruguay basin. The E estimates from VIC and inferred from the ERA-40 atmospheric moisture budget are consistent in both seasonal and interannual variations over the entire LPB, but large discrepancies exist between the two E estimates over the subbasins. The long-term mean of atmospheric moisture convergence P − E agrees well with observed runoff R for the upper Paraná River basin, whereas the imbalance is large (28%) for the Uruguay basin—possibly because of its small size. Major problems appear over the Paraguay basin with negative long-term mean of atmospheric moisture convergence P − E, which is not physically realistic. The computed precipitation recycling in the LPB (for L = 500 km) exhibits strong seasonal and spatial variations with ratios of 0%–3% during the cold season and 5%–7% during the warm season.

Water ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 1884 ◽  
Author(s):  
Guojie Wang ◽  
Jian Pan ◽  
Chengcheng Shen ◽  
Shijie Li ◽  
Jiao Lu ◽  
...  

Evapotranspiration (ET), a critical process in global climate change, is very difficult to estimate at regional and basin scales. In this study, we evaluated five ET products: the Global Land Surface Evaporation with the Amsterdam Methodology (GLEAM, the EartH2Observe ensemble (E2O)), the Global Land Data Assimilation System with Noah Land Surface Model-2 (GLDAS), a global ET product at 8 km resolution from Zhang (ZHANG) and a supplemental land surface product of the Modern-ERA Retrospective analysis for Research and Applications (MERRA_land), using the water balance method in the Yellow River Basin, China, including twelve catchments, during the period of 1982–2000. The results showed that these ET products have obvious different performances, in terms of either their magnitude or temporal variations. From the viewpoint of multiple-year averages, the MERRA_land product shows a fairly similar magnitude to the ETw derived from the water balance method, while the E2O product shows significant underestimations. The GLEAM product shows the highest correlation coefficient. From the viewpoint of interannual variations, the ZHANG product performs best in terms of magnitude, while the E2O still shows significant underestimations. However, the E2O product best describes the interannual variations among the five ET products. Further study has indicated that the discrepancies between the ET products in the Yellow River Basin are mainly due to the quality of precipitation forcing data. In addition, most ET products seem to not be sensitive to the downward shortwave radiation.


2008 ◽  
Vol 9 (3) ◽  
pp. 521-534 ◽  
Author(s):  
Clara Draper ◽  
Graham Mills

Abstract The atmospheric water balance over the semiarid Murray–Darling River basin in southeast Australia is analyzed based on a consecutive series of 3- to 24-h NWP forecasts from the Australian Bureau of Meteorology’s Limited Area Prediction System (LAPS). Investigation of the LAPS atmospheric water balance, including comparison of the forecast precipitation to analyzed rain gauge observations, indicates that the LAPS forecasts capture the general qualitative features of the water balance. The key features of the atmospheric water balance over the Murray–Darling Basin are small atmospheric moisture flux divergence (at daily to annual time scales) and extended periods during which the atmospheric water balance terms are largely inactive, with the exception of evaporation, which is consistent and very large in summer. These features present unique challenges for NWP modeling. For example, the small moisture fluxes in the basin can easily be obscured by the systematic errors inherent in all NWP models. For the LAPS model forecasts, there is an unrealistically large evaporation excess over precipitation (associated with a positive bias in evaporation) and unexpected behavior in the moisture flux divergence. Two global reanalysis products (the NCEP Reanalysis I and the 40-yr ECMWF Re-Analysis) also both describe (physically unrealistic) long-term negative surface water budgets over the Murray–Darling Basin, suggesting that the surface water budget cannot be sensibly diagnosed based on output from current NWP models. Despite this shortcoming, numerical models are in general the most appropriate tool for examining the atmospheric water balance over the Murray–Darling Basin, as the atmospheric sounding network in Australia has extremely low coverage.


2021 ◽  
Author(s):  
Tobias Stacke ◽  
Stefan Hagemann

Abstract. Global hydrological models (GHMs) are a useful tool in the assessment of the land surface water balance. They are used to further the understanding of interactions between water balance components as well as their past evolution and potential future development under various scenarios. While GHMs are a part of the Hydrologist's toolbox since several decades, the models are continuously developed. In our study, we present the HydroPy model, a revised version of an established GHM, the Max-Planck Institute for Meteorology's Hydrology Model (MPI-HM). Being rewritten in Python, the new model requires much less effort in maintenance and due to its flexible infrastructure, new processes can be easily implemented. Besides providing a thorough documentation of the processes currently implemented in HydroPy, we demonstrate the skill of the model in simulating the land surface water balance. We find that evapotranspiration is reproduced realistically for the majority of the land surface but is underestimated in the tropics. The simulated river discharge correlates well with observations. Biases are evident for the annual accumulated discharge, however they can – at least to some part – be attributed to discrepancies between the meteorological model forcing data and the observations. Finally, we show that HydroPy performs very similar to MPI-HM and, thus, conclude the successful transition from MPI-HM to HydroPy.


2012 ◽  
Vol 43 (1-2) ◽  
pp. 73-90 ◽  
Author(s):  
Fei Yuan ◽  
Liliang Ren ◽  
Zhongbo Yu ◽  
Yonghua Zhu ◽  
Jing Xu ◽  
...  

Vegetation and land-surface hydrology are intrinsically linked under long-term climate change. This paper aims to evaluate the dynamics of potential natural vegetation arising from 21st century climate change and its possible impact on the water budget of the Hanjiang River basin in China. Based on predictions of the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC-SRES) A1 scenario from the PRECIS (Providing Regional Climates for Impact Studies) regional climate model, changes in plant functional types (PFTs) and leaf area index (LAI) were simulated via the Lund-Potsdam-Jena dynamic global vegetation model. Subsequently, predicted PFTs and LAIs were employed in the Xinanjiang vegetation-hydrology model for rainfall–runoff simulations. Results reveal that future long-term changes in precipitation, air temperature and atmospheric CO2 concentration would remarkably affect the spatiotemporal distribution of PFTs and LAIs. These climate-driven vegetation changes would further influence regional water balance. With the decrease in forest cover in the 21st century, plant transpiration and evaporative loss of intercepted canopy water will tend to fall while soil evaporation may rise considerably. As a result, total evapotranspiration may increase moderately with a slight increase in annual runoff depth. This indicates that, for long-term hydrological prediction, climate-induced changes in terrestrial vegetation cannot be neglected as the terrestrial biosphere plays an important role in land-surface hydrological responses.


1994 ◽  
Vol 29 (3) ◽  
pp. 347-349
Author(s):  
P. Soldán ◽  
J. Švrcula ◽  
H. O. Ibrekk ◽  
T. Källqvist

The Odra (Oder) River flows from the Czech Republic through Poland to the Baltic Sea. Surface water as well as groundwater in the Odra River Basin is heavily polluted, especially in the Ostrava industrial region and its surroundings. The high level of pollution causes considerable impacts on human health and ecology. There is a definite need to develop sound abatement strategies to achieve long term objectives of reducing the deterioration of the environment and to restore the ecological balance in the surface water. This poster presents several related studies and focuses on the Czech-Norwegian one - “Abatement Strategies in the Odra River Basin”.


2018 ◽  
Vol 12 (1) ◽  
pp. 227-245 ◽  
Author(s):  
Xinyue Zhong ◽  
Tingjun Zhang ◽  
Shichang Kang ◽  
Kang Wang ◽  
Lei Zheng ◽  
...  

Abstract. Snow depth is one of the key physical parameters for understanding land surface energy balance, soil thermal regime, water cycle, and assessing water resources from local community to regional industrial water supply. Previous studies by using in situ data are mostly site specific; data from satellite remote sensing may cover a large area or global scale, but uncertainties remain large. The primary objective of this study is to investigate spatial variability and temporal change in snow depth across the Eurasian continent. Data used include long-term (1966–2012) ground-based measurements from 1814 stations. Spatially, long-term (1971–2000) mean annual snow depths of >20 cm were recorded in northeastern European Russia, the Yenisei River basin, Kamchatka Peninsula, and Sakhalin. Annual mean and maximum snow depth increased by 0.2 and 0.6 cm decade−1 from 1966 through 2012. Seasonally, monthly mean snow depth decreased in autumn and increased in winter and spring over the study period. Regionally, snow depth significantly increased in areas north of 50° N. Compared with air temperature, snowfall had greater influence on snow depth during November through March across the former Soviet Union. This study provides a baseline for snow depth climatology and changes across the Eurasian continent, which would significantly help to better understanding climate system and climate changes on regional, hemispheric, or even global scales.


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