A comprehensive statistical analysis of evaporation rates under climate change in Southern Iran using WEAP (Case study: Chahnimeh Reservoirs of Sistan Plain)

Bazzi, Hossein; Ebrahimi, Hossein; Aminnejad, Babak

doi:10.1016/j.asej.2020.08.030

Cited by 21 publications

(7 citation statements)

References 20 publications

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“…The results of this research have been compared with the results of Bazzi et al 62 and Kassem et al 25 Table 7 shows the comparison of the obtained results.…”

Section: Forecasting the River Flowmentioning

confidence: 87%

Forecasting hydropower generation byGFDL‐CM3climate model and hybrid hydrological‐Elman neural network model based on Improved Sparrow Search Algorithm (ISSA)

Wang

Gholinia

2021

Concurrency and Computation

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One of the most sensitive factors affecting hydropower generation is climate change.The objective of this study is to forecast the hydropower generation under the influence of climate change for the next 50 years. For this purpose, the GFDL-CM3 model is used under three scenarios: RCP2.6, RCP4.5, and RCP8.5 to predict precipitation and temperature. Any change in the inlet flow to the turbine will cause changes in the hydropower output. Therefore, the more accurately the flow is estimated, the hydropower generation is forecasted more accurately. In this research, a hydrological-neural network hybrid model for flow prediction is presented in which the Improved Sparrow Search Algorithm (ISSA) has been used. The results forecasting climate parameters showed that the average annual rainfall, runoff, and evaporation have a downward trend compared to the control period. The minimum and maximum annual temperatures have an increasing trend compared to the control period. To evaluate the hydropower generation Aras dam, the HEC-Ressim reservoir model is utilized. By comparing the average annual hydropower with the control period, it is known that the power generation will decrease in future years. The average annual electricity generated by hydropower under the scenario RCP2.6 and RCP4.5 and RCP8.

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“…The results of this research have been compared with the results of Bazzi et al 62 and Kassem et al 25 Table 7 shows the comparison of the obtained results.…”

Section: Forecasting the River Flowmentioning

confidence: 87%

Forecasting hydropower generation byGFDL‐CM3climate model and hybrid hydrological‐Elman neural network model based on Improved Sparrow Search Algorithm (ISSA)

Wang

Gholinia

2021

Concurrency and Computation

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“…Shahnameh 2 begins from the border of Afghanistan and finishes in the middle of Chahnimeh 1. Shahnameh 3 is placed west of the second Chahnimeh (Bazzi et al 2021 ). Figure 1 shows the geographical places of the Chahnimeh reservoirs.…”

Section: Methodsmentioning

confidence: 99%

“…For this purpose, five stations (Fig. 2 ) were carefully selected for sampling after field visits according to available facilities, the area of reservoirs, surface zoning, and sources of pollutant production (Bazzi et al 2021 ). The number of samples was 60.…”

Section: Methodsmentioning

confidence: 99%

Evaluation of water quality of Chahnimeh as natural reservoirs from Sistan region in southwestern Iran: a Monte Carlo simulation and Sobol sensitivity assessment

Kamani

Hosseini

Mohebi

et al. 2023

Environ Sci Pollut Res

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Maintaining the water quality is essential because of the limitation of drinking water bodies and their significant effects on life. Recently, much scientific interest has been attracted to the ecological condition assessment of water resources. Because of numerous health issues connected to water quality, the present work aimed to define the water quality status of Chahnimeh reservoirs, Sistan and Baluchistan province, Iran via the Iran Water Quality Index (IRWQISC), the National Sanitation Foundation Water Quality Index (NSFWQI), and human risk assessment. This cross-sectional descriptive work was accomplished in 4 seasons in 2020. The samples were gathered from 5 various points of Chahnimeh reservoirs. This study led to the results that the NSFWQI index was between 29.4 to 49.32, which showed “bad” quality, and the IRWQI index was between 19.27 and 39.23, which indicated “bad” and “relatively bad” quality. The best water quality based on both indexes was observed in the spring, and the worst was in the fall and summer. The highest value of HQ related to nitrate in drinking water was 1.60 in the group of children. However, according to the Monte Carlo simulation, HQ95% was estimated as 1.29. The Sobol sensitivity analysis of the first-order effect showed that daily water’s daily ingestion rate (IR) was the most sensitive input. In addition, the value of the second-order effect indicated that the interaction effect of concentration—ingestion rate was the most sensitive input parameter for HQ. Therefore, regular monitoring is necessary to ensure water safety for human consumption.

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“…These features enable WEAP to answer the research question of this study adequately. WEAP has been used to conduct studies with reservoirs (Bazzi et al, 2021;Hatamkhani et al, 2021) and dams (Khalil et al, 2018), but these were often of higher volume and located in larger watersheds. In general, however, this study is an example that WEAP can be used to model small water infrastructures sufficiently.…”

Section: Weap Model Descriptionmentioning

confidence: 99%

The potential of unused small-scale water reservoirs for climate change adaptation: A model- and scenario based analysis of a local water reservoir system in Thuringia, Germany

2022

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The 6th Intergovernmental Panel on Climate Change (IPCC) report (2021) stated that hot extremes have become more frequent and intense across most land regions in the past decades. It is projected that the changing climatic conditions in Germany and Thuringia in particular will lead to a higher frequency of drought events. Thus, it is vital to develop local adaptation strategies to mitigate the effects of droughts on agriculture to ensure future crop production. Water resource infrastructure has a critical role in planning future climate change adaptation measures that are sustainable. As the construction of new dams and reservoirs is controversial, it is preferable to use existing infrastructures, if they are suitable. Small-scale water management reservoirs built in Thuringia during the GDR (German Democratic Republic) and decommissioned after the German reunification were examined in this study to determine whether their reuse could be considered as a potential adaptation strategy. For this purpose, three reservoirs in Thuringia were selected. The impact of climate change on soil moisture, water availability and crop production, and the use of water from the reservoirs to meet future irrigation needs were modeled using the Water Evaluation and Planning system (WEAP). The modeled climatic changes have direct effects on the soil moisture status, leading to a higher water demand of the local agriculture. The results show that the crop water needs could double between near future (2020–2040) and distant future (2071–2100). However, predicted declines in yields can be mitigated by irrigation; modeling results indicate that supplemental irrigation with reservoir water mitigates projected losses and even allows 6.2–13.5% more crop production. Hence, the reuse of the reservoirs is worth to be considered as an adaptation strategy by policymakers. In addition to a cost-benefit analysis for future evaluation of the reservoirs, local user interests and demands need to be included avoiding conflicts about water. In general, WEAP as a modeling tool and the findings of the study show, that this research approach could be used to investigate the potential adaptive capacity of other small-scale water infrastructures.

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A comprehensive statistical analysis of evaporation rates under climate change in Southern Iran using WEAP (Case study: Chahnimeh Reservoirs of Sistan Plain)

Cited by 21 publications

References 20 publications

Forecasting hydropower generation byGFDL‐CM3climate model and hybrid hydrological‐Elman neural network model based on Improved Sparrow Search Algorithm (ISSA)

Forecasting hydropower generation byGFDL‐CM3climate model and hybrid hydrological‐Elman neural network model based on Improved Sparrow Search Algorithm (ISSA)

Evaluation of water quality of Chahnimeh as natural reservoirs from Sistan region in southwestern Iran: a Monte Carlo simulation and Sobol sensitivity assessment

The potential of unused small-scale water reservoirs for climate change adaptation: A model- and scenario based analysis of a local water reservoir system in Thuringia, Germany

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