scholarly journals Influences of Climate Change on Water Resources Availability in Jinjiang Basin, China

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Wenchao Sun ◽  
Jie Wang ◽  
Zhanjie Li ◽  
Xiaolei Yao ◽  
Jingshan Yu

The influences of climate change on water resources availability in Jinjiang Basin, China, were assessed using the Block-wise use of the TOPmodel with the Muskingum-Cunge routing method (BTOPMC) distributed hydrological model. The ensemble average of downscaled output from sixteen GCMs (General Circulation Models) for A1B emission scenario (medium CO2emission) in the 2050s was adopted to build regional climate change scenario. The projected precipitation and temperature data were used to drive BTOPMC for predicting hydrological changes in the 2050s. Results show that evapotranspiration will increase in most time of a year. Runoff in summer to early autumn exhibits an increasing trend, while in the rest period of a year it shows a decreasing trend, especially in spring season. From the viewpoint of water resource availability, it is indicated that it has the possibility that water resources may not be sufficient to fulfill irrigation water demand in the spring season and one possible solution is to store more water in the reservoir in previous summer.

Author(s):  
X. Yao ◽  
X. Cui ◽  
J. Yu ◽  
W. Sun

Abstract. According to the IPCC Fourth Assessment, the temperature and evapotranspiration will increase in the future. As a sensitive region to climate change, hydrological process in the middle reaches of the Yellow River will be significantly affected by climate change. In this study, water resources change in the future for a typical basin there: Lushi basin is assessed using the Soil and Water Assessment Tool (SWAT) hydrological model. Downscaled ensemble output from sixteen General Circulation Models (GCMs) for the A1B emission scenario in the 2050s was input to SWAT as the regional climate change scenario. The prediction shows that ET of this basin increases in winter and spring, and decreases in summer and autumn, and the streamflow increases throughout the year. The increased streamflow will probably improve the water demand guarantee and be conducive to crop growth in winter and spring, and may improve the flood risk in summer.


2016 ◽  
Vol 7 (3) ◽  
pp. 551-577 ◽  
Author(s):  
Azin Shahni Danesh ◽  
Mohammad Sadegh Ahadi ◽  
Hedayat Fahmi ◽  
Majid Habibi Nokhandan ◽  
Hadi Eshraghi

As a result of inappropriate management and rising levels of societal demand, in arid and semi-arid regions water resources are becoming increasingly stressed. Therefore, well-established insight into the effects of climate change on water resource components can be considered to be an essential strategy to reduce these effects. In this paper, Iran's climate change and variability, and the impact of climate change on water resources, were studied. Climate change was assessed by means of two Long Ashton Research Station-Weather Generator (LARS-WG) weather generators and all outputs from the available general circulation models in the Model for the Assessment of Greenhouse-gas Induced Climate Change-SCENario GENerator (MAGICC-SCENGEN) software, in combination with different emission scenarios at the regional scale, while the Providing Regional Climates for Impacts Studies (PRECIS) model has been used for projections at the local scale. A hydrological model, the Runoff Assessment Model (RAM), was first utilized to simulate water resources for Iran. Then, using the MAGICC-SCENGEN model and the downscaled results as input for the RAM model, a prediction was made for changes in 30 basins and runoffs. Modeling results indicate temperature and precipitation changes in the range of ±6 °C and ±60%, respectively. Temperature rise increases evaporation and decreases runoff, but has been found to cause an increased rate of runoff in winter and a decrease in spring.


2016 ◽  
Vol 55 (3) ◽  
pp. 773-789
Author(s):  
Soojun Kim ◽  
Jaewon Kwak ◽  
Hung Soo Kim ◽  
Younghun Jung ◽  
Gilho Kim

AbstractThe spatial and temporal resolution of readily available climate change projections from general circulation models (GCM) has limited applicability. Consequently, several downscaling methods have been developed. These methods predominantly focus on a single meteorological series at specific sites. Spatial and temporal correlation of the precipitation and temperature fields is important for hydrologic applications. This research uses a nearest neighbor–genetic algorithm (NN–GA) method to analyze the Namhan River basin in the Korean Peninsula. Using the simulation results of the CNRM-CM for the RCP 8.5 climate change scenario, archived in the fifth phase of the Coupled Model Intercomparison Project (CMIP5), the GCM projections are downscaled through the NN–GA. The NN–GA simulations reproduce the features of the observed series in terms of site statistics as well as across variables and sites.


2020 ◽  
Vol 9 (9) ◽  
pp. 506
Author(s):  
Liping Wang ◽  
Shufang Wang ◽  
Liudong Zhang ◽  
Mohamed Khaled Salahou ◽  
Xiyun Jiao ◽  
...  

Studying the pattern of agricultural water demand under climate change has great significance for the regional water resources management, especially in arid areas. In this study, the future pattern of the irrigation demand in Hotan Oasis in Xinjiang Uygur Autonomous Region in Northwest China, including Hotan City, Hotan County, Moyu County and Luopu County, was assessed based on the general circulation models (GCMs) and the Surface Energy Balance System model (SEBS). Six different scenarios were used based on the GCMs of BCC_CSM1.1, HadGEM2-ES and MIROC-ESM-CHEM under the Representative Concentration Pathway (RCP) 4.5 and RCP 8.5. The results showed that the method integrating the GCMs and SEBS to predict the spatial pattern was useful. The irrigation demand of Hotan Oasis will increase in 2021–2040. The annual irrigation demand of Hotan City is higher, with 923.2 and 936.2 mm/a in 2021–2030 and 2031–2040, respectively. The other three regions (Hotan County, Moyu County and Luopu County) are lower in the six scenarios. The annual irrigation demand showed a spatial pattern of high in the middle, low in the northwest and southeast under the six scenarios in 2021–2040. The study can provide useful suggestions on the water resources allocation in different regions to protect water resources security in arid areas.


2018 ◽  
Vol 99 (10) ◽  
pp. 2093-2106 ◽  
Author(s):  
Ambarish V. Karmalkar

AbstractTwo ensembles of dynamically downscaled climate simulations for North America—the North American Regional Climate Change Assessment Program (NARCCAP) and the Coordinated Regional Climate Downscaling Experiment (CORDEX) featuring simulations for North America (NA-CORDEX)—are analyzed to assess the impact of using a small set of global general circulation models (GCMs) and regional climate models (RCMs) on representing uncertainty in regional projections. Selecting GCMs for downscaling based on their equilibrium climate sensitivities is a reasonable strategy, but there are regions where the uncertainty is not fully captured. For instance, the six NA-CORDEX GCMs fail to span the full ranges produced by models in phase 5 of the Coupled Model Intercomparison Project (CMIP5) in summer temperature projections in the western and winter precipitation projections in the eastern United States. Similarly, the four NARCCAP GCMs are overall poor at spanning the full CMIP3 ranges in seasonal temperatures. For the Southeast, the NA-CORDEX GCMs capture the uncertainty in summer but not in winter projections, highlighting one consequence of downscaling a subset of GCMs. Ranges produced by the RCMs are often wider than their driving GCMs but are sensitive to the experimental design. For example, the downscaled projections of summer precipitation are of opposite polarity in two RCM ensembles in some regions. Additionally, the ability of the RCMs to simulate observed temperature trends is affected by the internal variability characteristics of both the RCMs and driving GCMs, and is not systematically related to their historical performance. This has implications for adequately sampling the impact of internal variability on regional trends and for using model performance to identify credible projections. These findings suggest that a multimodel perspective on uncertainties in regional projections is integral to the interpretation of RCM results.


Water ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 1715
Author(s):  
Soha M. Mostafa ◽  
Osama Wahed ◽  
Walaa Y. El-Nashar ◽  
Samia M. El-Marsafawy ◽  
Martina Zeleňáková ◽  
...  

This paper presents a comprehensive study to assess the impact of climate change on Egypt’s water resources, focusing on irrigation water for agricultural crops, considering that the agriculture sector is the largest consumer of water in Egypt. The study aims to estimate future climate conditions using general circulation models (GCMs), to assess the impact of climate change and temperature increase on water demands for irrigation using the CROPWAT 8 model, and to determine the suitable irrigation type to adapt with future climate change. A case study was selected in the Middle part of Egypt. The study area includes Giza, Bani-Sweif, Al-Fayoum, and Minya governorates. The irrigation water requirements for major crops under current weather conditions and future climatic changes were estimated. Under the conditions of the four selected models CCSM-30, GFDLCM20, GFDLCM21, and GISS-EH, as well as the chosen scenario of A1BAIM, climate model (MAGICC/ScenGen) was applied in 2050 and 2100 to estimate the potential rise in the annual mean temperature in Middle Egypt. The results of the MAGICC/SceGen model indicated that the potential rise in temperature in the study area will be 2.12 °C in 2050, and 3.96 °C in 2100. The percentage of increase in irrigation water demands for winter crops under study ranged from 6.1 to 7.3% in 2050, and from 11.7 to 13.2% in 2100. At the same time, the increase in irrigation water demands for summer crops ranged from 4.9 to 5.8% in 2050, and from 9.3 to 10.9% in 2100. For Nili crops, the increase ranged from 5.0 to 5.1% in 2050, and from 9.6 to 9.9% in 2100. The increase in water demands due to climate change will affect the water security in Egypt, as the available water resources are limited, and population growth is another challenge which requires a proper management of water resources.


2021 ◽  
Author(s):  
Mohammad Reza Khazaei ◽  
Mehraveh Hasirchian ◽  
Bagher Zahabiyoun

Abstract Weather Generators (WGs) are one of the major downscaling tools for assessing regional climate change impacts. However, some deficiencies in the performance of WGs have limited their usage. This paper presents a method for correcting the low-frequency variability (LFV) of precipitation in the Improved Weather Generator (IWG) model. The method is based on bias correction in the monthly precipitation distribution of the generated daily series. The performance of the modified model was tested directly by comparing the statistics of generated and observed weather data for 14 stations, and also indirectly by comparing the characteristics of simulated stream-flows of a basin from the simulations run based on generated and observed weather data. The results showed that the method not only corrected the LFV of precipitation but also improved the reproduction of many other statistics. The provided IWG2 model can serve as a useful tool for the downscaling of General Circulation Models (GCMs) scenarios to assess regional climate change impacts, especially hydrological effects.


2021 ◽  
Author(s):  
James Ciarlo ◽  
Erika Coppola ◽  
Emanuela Pichelli ◽  
Jose Abraham Torres Alavez ◽  

<p>Downscaling data from General Circulation Models (GCMs) with Regional Climate Models (RCMs) is a computationally expensive process, even more so running at the convection permitting scale (CP). Despite the high-resolution products of these simulations, the Added Value (AV) of these runs compared to their driving models is an important factor for consideration. A new method was recently developed to quantify the AV of historical simulations as well as the Climate Change Downscaling Signal (CCDS) of forecast runs. This method presents these quantities spatially and thus the specific regions with the most AV can be identified and understood.</p><p>An analysis of daily precipitation from a 55-model EURO-CORDEX ensemble (at 12 km resolution) was assessed using this method. It revealed positive AV throughout the domain with greater emphasis in regions of complex topography, coast-lines, and the tropics. Similar CCDS was obtained when assessing the RCP 8.5 far future runs in these domains. This paper looks more closely at the CCDS obtained with this method and compares it to other climate change signals described in other studies.</p><p>The same method is now being applied to assess the AV and CCDS of daily precipitation from an ensemble of models at the CP scale (~3 km) over different domains within Europe. The current stage of the analysis is also looking into the AV of using hourly precipitation instead of daily.</p>


Sign in / Sign up

Export Citation Format

Share Document