Climate Change Impact Assessment on Blue and Green Water by Coupling of Representative CMIP5 Climate Models with Physical Based Hydrological Model

Pandey, Brij Kishor; Khare, Deepak; Kawasaki, Akiyuki; Mishra, P. K.

doi:10.1007/s11269-018-2093-3

Cited by 59 publications

(41 citation statements)

References 39 publications

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“…4d) and BW (Fig. 4c) were higher in the upstream than those in the downstream for this time period due to the differences in precipitation patterns (Pandey et al, 2019;Fazeli Farsani et al, 2019;Zuo et al, 2015). Fig.…”

Section: Spatial and Temporal Changes Of Water Resources Componentsmentioning

confidence: 82%

“…7a, f). It should be noted that the surface runoff is a major part of BW (Pandey et al, 2019;Fazeli Farsani et al, 2019). BW is a renewable resource and potentially necessary for the agriculture sector in this area.…”

Section: Spatial and Temporal Changes Of Water Resources Componentsmentioning

confidence: 99%

“…Thus, paying attention to BW and GW is very important in the management of watershed basins. In the past few years, many studies in the world have concentrated on BW and GW in the field of hydrology and water resources under climate change (Pandey et al, 2019;Afshar et al, 2018;Badou et al, 2018;Shrestha et al, 2017;Zang et al, 2012; and on the importance of these components in different watershed basins for strategic decision-making (Schyns et al, 2019;Veettil and Mishra, 2016;Zang et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

“…Various physically-based integrated distribution models have extended for analysis and management of catchment, including: Hydrologic Simulation Program-Fortran (HSPF), Agricultural Non-Productive Source (AGNPS) model, Erosion Productivity Impact Calculator (EPIC), Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM), Water Erosion Prediction Project (WEPP), Chemical Runoff Erosion from Agricultural Management System (CREAMS), and Soil and Water Assessment Tools (SWAT). SWAT was developed and employed in most studies in order to determine the effects of climate change in the quantity and spatiotemporal distribution of BW and GW, and also the impacts of human activity on agricultural yield, chemical, and stream flow in a large scale basin (Pandey et al, 2019;Dadfar et al, 2019;Fazeli Farsani et al, 2019;Masud et al, 2018;Afshar and Hassanzadeh, 2017;Veettil and Mishra, 2016;Besharat et al, 2015;Faramarzi et al, 2009Faramarzi et al, , 2013). The Calibration and Uncertainty Procedures (SWAT-CUP) computer program, which connects to SWAT model, is applied in order to investigate the sensitivity analysis, the model parameters, and the calibration and validation processes (Hassanzadeh et al, 2019;Shivhare et al, 2018;Afshar et al, 2018;Uniyal et al, 2015;Abbaspour et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

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A hydrological toolkit to delineate patterns of blue and green water in a regional semi-arid climate in Iran via CMIP5 models

Afshar¹,

Hassanzadeh²

2021

Időjárás

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Water scarcity and the climate change impacts on water components will drastically alter everybody's life. The Soil and Water Assessment Tool (SWAT) has been utilized in this study in combination with Sequential Uncertainty Fitting Program (SUFI-2) to simulate precipitation (P), temperature (T), blue water (BW), green water flow (GWF), and green water storage (GWS) in Kashafrood River Basin, Iran. The outputs of two Coupled Model Intercomparison Project Phase 5 (CMIP5) models (MIROC-ESM and GFDL-ESM2G) are selected for hydrological modeling under Representative Concentration Pathways (RCPs) of 4.5 and 8.5 and for the near future (2014-2042) and far future (2043-2100( periods compared to historical period (1995-2011). The results of RCPs, in comparison with the historical period, show that P and BW are increased and in GFDL-ESM2G are better than MIROC-ESM, while T tends to increase, and MIROC-ESM is better than GFDL-ESM2G. GWF, in all future periods (except in MIROC-ESM in near future and under RCP4.5 and 8.5) and in all RCPs tend to decrease, and the results of MIROC-ESM are better than those of GFDL-ESM2G in near future and are vice versa in far future. It is anticipated that GWS continues its historical trend in the future.

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Section: Spatial and Temporal Changes Of Water Resources Componentsmentioning

confidence: 82%

Section: Spatial and Temporal Changes Of Water Resources Componentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A hydrological toolkit to delineate patterns of blue and green water in a regional semi-arid climate in Iran via CMIP5 models

Afshar¹,

Hassanzadeh²

2021

Időjárás

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“…While the many applications and tools available through the DIAS platform support research in a variety of fields Moiz et al 2018;Pandey et al 2018), this article focuses on one field: water resources management and water-related disaster risk reduction. We have selected three cases for study: -Case I: Real-time flood predictions and flood-control dam operation optimization system in Japan.…”

Section: Objectivesmentioning

confidence: 99%

Data Integration and Analysis System (DIAS) as a Platform for Data and Model Integration: Cases in the Field of Water Resources Management and Disaster Risk Reduction

Kawasaki

Koudelova

Tamakawa

et al. 2018

Data Science Journal

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Perspectives of human–water co‐evolution of blue–green water resources in subtropical areas

Pan

Yang

Lou

et al. 2023

Hydrological Processes

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Blue–green water resources and their transformation play a vital role in crop production and ecosystem services regulation, and their distribution and utilization are affected by human activity, such as policy‐driven green water resources development projects. However, it is unclear how policy‐driven green water resources development projects, such as the Grain for Green Project (GGP) in China, affect eco‐environmental quality and socio‐economic development, that is, human–water co‐evolution. Therefore, considering the GGP in a subtropical ungauged basin in southern China as an example, based on remote sensing hydrological station (RSHS) technology and multisource remote sensing data, this study analyzed the impact of the GGP on human–water co‐evolution from the perspective of blue–green water resources. The results show that: (1) From 2001 to 2020 the GGP transformed more blue water resources into green water resources, resulting in an increase in green water resources of 282.29% compared to that of blue water resources. (2) Due to the initial success of the GGP in 2005, there was a distinct positive correlation between the green water coefficient (GWC) and basin development index (BDI) from 2005 to 2020 (R2 = 0.70, p < 0.05), indicating that the GGP did not cause conflict between the sustainability of socio‐economic development and the health of the ecological environment. (3) In the GGP scenario, in which the cultivated land area maintained 50% of the current decreasing rate, the overall efficiency index maintain a continuously increasing trend at an average rate of 0.001 year−1 from 2021 to 2050, which not only improved the eco‐environmental quality but also met cultivated land demand. This research reveals the role of GGP in promoting the transformation from blue to green water resources, and proves the feasibility of the simultaneous promotion of GGP and socio‐economic development, providing significant insights for the promotion of policy‐driven green water resources development projects and long‐term blue–green water resources planning and management in other countries or regions.

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Climate Change Impact Assessment on Blue and Green Water by Coupling of Representative CMIP5 Climate Models with Physical Based Hydrological Model

Cited by 59 publications

References 39 publications

A hydrological toolkit to delineate patterns of blue and green water in a regional semi-arid climate in Iran via CMIP5 models

A hydrological toolkit to delineate patterns of blue and green water in a regional semi-arid climate in Iran via CMIP5 models

Data Integration and Analysis System (DIAS) as a Platform for Data and Model Integration: Cases in the Field of Water Resources Management and Disaster Risk Reduction

Perspectives of human–water co‐evolution of blue–green water resources in subtropical areas

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