Water balance model as a tool for building participation and joint water use promotion at the river basin level *

2020 ◽  
Author(s):  
Thanaporn Supriyasilp ◽  
Kobkiat Pongput
2019 ◽  
Vol 35 (9) ◽  
pp. 954-975
Author(s):  
Olutoyin Adeola Fashae ◽  
Rotimi Oluseyi Obateru ◽  
Adeyemi Oludapo Olusola

2015 ◽  
Vol 19 (9) ◽  
pp. 3829-3844 ◽  
Author(s):  
J. Hoogeveen ◽  
J.-M. Faurès ◽  
L. Peiser ◽  
J. Burke ◽  
N. van de Giesen

Abstract. GlobWat is a freely distributed, global soil water balance model that is used by the Food and Agriculture Organization (FAO) to assess water use in irrigated agriculture, the main factor behind scarcity of freshwater in an increasing number of regions. The model is based on spatially distributed high-resolution data sets that are consistent at global level and calibrated against values for internal renewable water resources, as published in AQUASTAT, the FAO's global information system on water and agriculture. Validation of the model is done against mean annual river basin outflows. The water balance is calculated in two steps: first a "vertical" water balance is calculated that includes evaporation from in situ rainfall ("green" water) and incremental evaporation from irrigated crops. In a second stage, a "horizontal" water balance is calculated to determine discharges from river (sub-)basins, taking into account incremental evaporation from irrigation, open water and wetlands ("blue" water). The paper describes the methodology, input and output data, calibration and validation of the model. The model results are finally compared with other global water balance models to assess levels of accuracy and validity.


2015 ◽  
Vol 12 (1) ◽  
pp. 801-838 ◽  
Author(s):  
J. Hoogeveen ◽  
J.-M. Faurès ◽  
L. Peiser ◽  
J. Burke ◽  
N. van de Giesen

Abstract. GlobWat is a freely distributed, global soil water balance model that is used by FAO to assess water use in irrigated agriculture; the main factor behind scarcity of freshwater in an increasing number of regions. The model is based on spatially distributed high resolution datasets that are consistent at global level and calibrated against values for Internal Renewable Water Resources, as published in AQUASTAT, FAO's global information system on water and agriculture. Validation of the model is done against mean annual river basin outflows. The water balance is calculated in two steps: first a "vertical" water balance is calculated that includes evaporation from in situ rainfall ("green" water) and incremental evaporation from irrigated crops. In a second stage, a "horizontal" water balance is calculated to determine discharges from river (sub-)basins, taking into account incremental evaporation from irrigation, open water and wetlands ("blue" water). The paper describes methodology, input and output data, calibration and validation of the model. The model results are finally compared with other global water balance models.


2021 ◽  
pp. 217-224
Author(s):  
A. Raviraj ◽  
Ramachandran J ◽  
Nitin Kaushal ◽  
Arjit Mishra

Reduction in agricultural water use and increasing the sustainability of water resources can be achieved by studying the water balance of the area and crop water demand. In this paper, by using a simple water balance model, Evapotranspiration, Rainfall, Runoff, Water Demand and Water Requirement different crops are estimated. The crop water requirement and crop water demand for different crops grown in the Periya Pallam Catchment of Upper Bhavani Basin, Tamilnadu, was estimated. Water balance estimation of the area reveals that out of the annual rainfall, runoff is estimated to be 129 mm, effective rainfall is 252 mm, and deep percolation is about 67 mm. The demand for water for agriculture in the study area is about 61 million cubic meters (MCM), but only 19 MCM of water is available through precipitation in the form of effective rainfall. Hence, the remaining 43 MCM of water is supplied through groundwater and other sources. The results will pave the way for sustainable crop water use planning and would achieve water security in the basin.


2010 ◽  
Vol 25 (3) ◽  
pp. 297-307 ◽  
Author(s):  
D. K. Karpouzos ◽  
E. A. Baltas ◽  
S. Kavalieratou ◽  
C. Babajimopoulos

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 800 ◽  
Author(s):  
Girma Berhe Adane ◽  
Birtukan Abebe Hirpa ◽  
Belay Manjur Gebru ◽  
Cholho Song ◽  
Woo-Kyun Lee

Hydrologic models play an indispensable role in managing the scarce water resources of a region, and in developing countries, the availability and distribution of data are challenging. This research aimed to integrate and compare the satellite rainfall products, namely, Tropical Rainfall Measuring Mission (TRMM 3B43v7) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), with a GR2M hydrological water balance model over a diversified terrain of the Awash River Basin in Ethiopia. Nash–Sutcliffe efficiency (NSE), percent bias (PBIAS), coefficient of determination (R2), and root mean square error (RMSE) and Pearson correlation coefficient (PCC) were used to evaluate the satellite rainfall products and hydrologic model performances of the basin. The satellite rainfall estimations of both products showed a higher PCC (above 0.86) with areal observed rainfall in the Uplands, the Western highlands, and the Lower sub-basins. However, it was weakly associated in the Upper valley and the Eastern catchments of the basin ranging from 0.45 to 0.65. The findings of the assimilated satellite rainfall products with the GR2M model exhibited that 80% of the calibrated and 60% of the validated watersheds in a basin had lower magnitude of PBIAS (<±10), which resulted in better accuracy in flow simulation. The poor performance with higher PBIAS (≥±25) of the GR2M model was observed only in the Melka Kuntire (TRMM 3B43v7 and PERSIANN-CDR), Mojo (PERSIANN-CDR), Metehara (in all rainfall data sets), and Kessem (TRMM 3B43v7) watersheds. Therefore, integrating these satellite rainfall data, particularly in the data-scarce basin, with hydrological data, generally appeared to be useful. However, validation with the ground observed data is required for effective water resources planning and management in a basin. Furthermore, it is recommended to make bias corrections for watersheds with poorlyww performing satellite rainfall products of higher PBIAS before assimilating with the hydrologic model.


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