Hydroclimatic Modeling and Monitoring under Climate Change

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water and Climate Change".

Deadline for manuscript submissions: 20 July 2024 | Viewed by 12547

Special Issue Editor

Special Issue Information

Dear Colleagues,

The impacts of global warming on the water cycle are accelerating. Floods and droughts are increasingly affecting many regions of our planet, some of which were thought to be safe before this century. Thus, it is necessary to assess these impacts on the water cycle and predict the changing effects in the context of the continuous and sustained rise in temperature. Nevertheless, these impacts are strongly influenced by human activities.

The objective of this Special Issue is to focus on the impact of global warming on the water cycle, placing particular emphasis on river flows and lake water levels. Thus, this Special Issue will include research papers which highlight the impacts of global warming on the water cycle in relation to anthropogenic activities. The topics of this Special Issue are as follows:

  • The analysis of the spatiotemporal variability of the components of the water cycle (rivers and lakes) in the current context of global warming.
  • The prediction of these components of the water cycle in the coming decades up to the year 2100 using hydrological and climatic models.
  • The impacts of human activities on the amplification or attenuation of global warming on the components of the water cycle.

Prof. Dr. Ali A. Assani
Guest Editor

Manuscript Submission Information

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Keywords

  • streamflow
  • lakes water levels
  • evapotranspiration
  • runoff
  • infiltration
  • agriculture
  • wetlands
  • deforestation–afforestation
  • urbanization
  • hydroclimatologic modeling and hydroclimatologic monitoring
  • climate change

Published Papers (8 papers)

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Research

28 pages, 8056 KiB  
Article
Projected Changes in Extreme Precipitation Patterns across Algerian Sub-Regions
by Yasmine Hamitouche, Ayoub Zeroual, Mohamed Meddi, Ali A. Assani, Ramdane Alkama, Zekâi Şen and Xinhua Zhang
Water 2024, 16(10), 1353; https://doi.org/10.3390/w16101353 - 10 May 2024
Viewed by 638
Abstract
Extreme precipitation events play a crucial role in shaping the vulnerability of regions like Algeria to the impacts of climate change. To delve deeper into this critical aspect, this study investigates the changing patterns of extreme precipitation across five sub-regions of Algeria using [...] Read more.
Extreme precipitation events play a crucial role in shaping the vulnerability of regions like Algeria to the impacts of climate change. To delve deeper into this critical aspect, this study investigates the changing patterns of extreme precipitation across five sub-regions of Algeria using data from 33 model simulations provided by the NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-GDDP-CMIP6). Our analysis reveals a projected decline in annual precipitation for four of these regions, contrasting with an expected increase in desert areas where annual precipitation levels remain low, typically not exceeding 120 mm. Furthermore, key precipitation indices such as maximum 1-day precipitation (Rx1day) and extremely wet-day precipitation (R99p) consistently show upward trends across all zones, under both SSP245 and SSP585 scenarios. However, the number of heavy precipitation days (R20mm) demonstrates varied trends among zones, exhibiting stable fluctuations. These findings provide valuable foresight into future precipitation patterns, offering essential insights for policymakers and stakeholders. By anticipating these changes, adaptive strategies can be devised to mitigate potential climate change impacts on crucial sectors such as agriculture, flooding, water resources, and drought. Full article
(This article belongs to the Special Issue Hydroclimatic Modeling and Monitoring under Climate Change)
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13 pages, 5462 KiB  
Article
Refined Assessment and Future Projections of Indian Summer Monsoon Rainfall Using CMIP6 Models
by Jiahao Li, Lingli Fan, Xuzhe Chen, Chunqiao Lin, Luchi Song and Jianjun Xu
Water 2023, 15(24), 4305; https://doi.org/10.3390/w15244305 - 18 Dec 2023
Viewed by 1116
Abstract
Analyzing and forecasting the Indian Summer Monsoon Rainfall (ISMR) is vital for South Asia’s socio-economic stability. Using 35 climate models from the latest generation of the Coupled Model Intercomparison Project (CMIP6) to simulate and project ISMR, we integrated statistical methods, such as Taylor [...] Read more.
Analyzing and forecasting the Indian Summer Monsoon Rainfall (ISMR) is vital for South Asia’s socio-economic stability. Using 35 climate models from the latest generation of the Coupled Model Intercomparison Project (CMIP6) to simulate and project ISMR, we integrated statistical methods, such as Taylor diagrams, comprehensive rating indicators, and interannual variability scores, to compare performance differences between various models and analyze influencing mechanisms. The results show that the majority of models effectively simulate the climatology of the ISMR. However, they exhibit limitations in accurately capturing its interannual variability. Importantly, we observed no significant correlation between a model’s ability to simulate ISMR’s general climatology and its accuracy in representing annual variability. After a comprehensive assessment, models, like BCC-ESM1, EC-Earth3-Veg, GFDL-CM4, INM-CM5-0, and SAM0-UNICON were identified as part of the prime model mean ensemble (pMME), demonstrating superior performance in spatiotemporal simulations. The pMME can accurately simulate the sea surface temperature changes in the North Indian Ocean and the atmospheric circulation characteristics of South Asia. This accuracy is pivotal for CMIP6’s prime models to precisely simulate ISMR climatic variations. CMIP6 projections suggest that, by the end of the 21st century, ISMR will increase under low, medium, and high emission scenarios, with a significant rise in rainfall under the high emission scenario, especially in the western and northern parts of India. Among the pMME, the projected increase in rainfall across India is more moderate, with an estimated increase of 30%. The findings of this study suggest that selecting the best models for regional climate downscaling research will project regional climate changes more accurately. This provides valuable recommendations for model improvements in the Indian region. Full article
(This article belongs to the Special Issue Hydroclimatic Modeling and Monitoring under Climate Change)
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17 pages, 1615 KiB  
Article
Determining the Changing Irrigation Demands of Maize Production in the Cukurova Plain under Climate Change Scenarios with the CROPWAT Model
by Burak Şen
Water 2023, 15(24), 4215; https://doi.org/10.3390/w15244215 - 7 Dec 2023
Cited by 2 | Viewed by 1351
Abstract
This study delves into the critical issue of climate change and its impact on maize cultivation, focusing on irrigation water requirements (IWR) and crop evapotranspiration (ETc) values over three distinct time periods: 1971–2000 (RF), 2025–2054 (P1), and 2069–2098 (P2), under the climate scenarios [...] Read more.
This study delves into the critical issue of climate change and its impact on maize cultivation, focusing on irrigation water requirements (IWR) and crop evapotranspiration (ETc) values over three distinct time periods: 1971–2000 (RF), 2025–2054 (P1), and 2069–2098 (P2), under the climate scenarios of RCP4.5 and RCP8.5 in the AR5 of the IPCC via the CROPWAT model. The research reveals significant increases in mean temperatures, particularly during summers, in both scenarios, signifying the substantial influence of climate change on the Cukurova Region’s climate. Daily average evapotranspiration (ETo) values for the study periods demonstrate noteworthy increases, with the most pronounced rise observed in July for P2 under RCP8.5, emphasizing the seasonality and magnitude of the change. Moreover, the study underscores a consistent escalation in irrigation water requirements from RF to P2 periods for both scenarios, highlighting the pressing need for water resource management strategies in agriculture. Under RCP4.5, the study found that average simulated ETc increased by 9.2% for P1 and 11.7% for P2 compared to the RF period. In the harsher RCP8.5 scenario, ETc values displayed a substantial 20.0% increase for P2 and exhibited a wide range of variation across the study periods. In the light of these escalating climate change impacts, this study underscores the imperative of understanding and addressing the challenges encountered in maize cultivation. The findings emphasize the consistent rise in temperature and irrigation demands, underscoring the necessity for proactive adaptive strategies to ensure the sustainability of agricultural practices and long-term food security. As climate change continues to exert its influence, this research serves as a call to action for policymakers, agricultural stakeholders, and researchers to prioritize adaptation efforts to safeguard the future of maize production and the global food supply. Full article
(This article belongs to the Special Issue Hydroclimatic Modeling and Monitoring under Climate Change)
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17 pages, 4575 KiB  
Article
Effects of Climate Change on Surface Runoff and Soil Moisture in the Source Region of the Yellow River
by Jianhua Si, Jianming Li, Sujin Lu, Xuejiao Qi, Xiuzhi Zhang, Wenjin Bao, Xiaoyan Zhang, Shipeng Zhou, Cheng Jin, Lijuan Qi, Yue Qi, Xiaojing Zheng, Yanhong Gong and Zhanqing Wang
Water 2023, 15(11), 2104; https://doi.org/10.3390/w15112104 - 1 Jun 2023
Cited by 3 | Viewed by 1858
Abstract
The impact of climate change on surface runoff and soil moisture in the source region of the Yellow River is analyzed, which will provide a scientific basis for the rational use and protection of water resources in the source area. In this paper, [...] Read more.
The impact of climate change on surface runoff and soil moisture in the source region of the Yellow River is analyzed, which will provide a scientific basis for the rational use and protection of water resources in the source area. In this paper, the SWAT hydrological model was coupled with the Coupled Model Intercomparison Project (CMIP) to predict future changes in surface runoff and soil moisture in the source region of the Yellow River. The prediction of surface runoff and soil moisture in the Yellow River Basin was analyzed by a linear regression model. The SWAT model rate had a calibration period R2 of 0.876 and a validation period R2 of 0.972. The trend of surface runoff and annual mean temperature in the source region of the Yellow River from 2011 to 2022 showed an overall increasing trend, and soil moisture showed a general decreasing trend. 2011–2022 trends between surface runoff and annual mean temperature in the source region of the Yellow River showed a highly significant difference, indicating that surface runoff flow was significantly influenced by temperature. The difference between the trends in soil moisture and the annual mean temperature was highly significant. The surface runoff fluctuated greatly in different years, and the surface runoff changed greatly in different scenarios of CMIP5 (RCP2.6, RCP4.5, and RCP8.5). For all three climate change scenarios, the surface runoff displayed a downward trend. The surface runoff showed a similar uneven distribution for all scenarios on a yearly cycle. Under the three climate scenarios, the runoff was highest between May and August, with a slowly increasing trend from January to April and a slightly decreasing trend from September to December. The interannual and interannual distribution of soil water was basically consistent with the distribution of surface runoff, and there was an overall trend in the length of all soil water reduction scenarios. Surface runoff and soil moisture are and will be greatly affected by climate change (mainly temperature and precipitation). Under the three climate scenarios, the precipitation increases to some extent, but the surface runoff and soil moisture will both decrease, which may be attributed to the greater evaporation than the precipitation. Full article
(This article belongs to the Special Issue Hydroclimatic Modeling and Monitoring under Climate Change)
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19 pages, 3207 KiB  
Article
Stakeholder-Informed Hydroclimate Scenario Modeling in the Lower Santa Cruz River Basin for Water Resource Management
by Neha Gupta, Lindsay Bearup, Katharine Jacobs, Eve Halper, Chris Castro, Hsin-I Chang and Julia Fonseca
Water 2023, 15(10), 1884; https://doi.org/10.3390/w15101884 - 16 May 2023
Cited by 2 | Viewed by 1366
Abstract
The Lower Santa Cruz River Basin Study (LSCRB Study) is a collaborative effort of regional and statewide water management stakeholders working with the US Bureau of Reclamation under the auspices of the 2009 SECURE Water Act. The impacts of climate change, land use, [...] Read more.
The Lower Santa Cruz River Basin Study (LSCRB Study) is a collaborative effort of regional and statewide water management stakeholders working with the US Bureau of Reclamation under the auspices of the 2009 SECURE Water Act. The impacts of climate change, land use, and population growth on projected water supply in the LSCRB were evaluated to (1) identify projected water supply and demand imbalances and (2) develop adaptation strategies to proactively respond over the next 40 years. A multi-step hydroclimate modeling and risk assessment process was conducted to assess a range of futures in terms of temperature, precipitation, runoff, soil moisture, and evapotranspiration, with a particular focus on implications for ecosystem health. Key hydroclimate modeling process decisions were informed by ongoing multi-stakeholder engagement. To incorporate the region’s highly variable precipitation pattern, the study used a numerical “weather generator” to develop ensembles of precipitation and temperature time series for input to surface hydrology modeling efforts. Hydroclimate modeling outcomes consistently included increasing temperatures, and generated information related to precipitation responses (season length and timing, precipitation amount) considered useful for evaluating potential ecosystem impacts. A range of risks was identified using the hydroclimate modeling outputs that allowed for development of potential adaptation strategies. Full article
(This article belongs to the Special Issue Hydroclimatic Modeling and Monitoring under Climate Change)
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16 pages, 2572 KiB  
Article
Projection of Future Meteorological Droughts in Lake Urmia Basin, Iran
by Babak Ghazi, Sanjana Dutt and Ali Torabi Haghighi
Water 2023, 15(8), 1558; https://doi.org/10.3390/w15081558 - 16 Apr 2023
Cited by 11 | Viewed by 2081
Abstract
Future changes (2015–2100) in precipitation and meteorological droughts in Lake Urmia Basin were investigated using an average mean ensemble of eight general circulation models (GCMs) with high-resolution datasets in socioeconomic pathway scenarios (SSPs) from the Coupled Model Intercomparison Project (CMIP6). In order to [...] Read more.
Future changes (2015–2100) in precipitation and meteorological droughts in Lake Urmia Basin were investigated using an average mean ensemble of eight general circulation models (GCMs) with high-resolution datasets in socioeconomic pathway scenarios (SSPs) from the Coupled Model Intercomparison Project (CMIP6). In order to project the drought, the standardized precipitation index (SPI) was calculated. Overall, the results revealed that precipitation in Lake Urmia Basin will decrease by 3.21% and 7.18% in the SSP1-2.6 and SSP5-8.5 scenarios, respectively. The results based on 6-month-timescale SPI indices projected more “Extremely dry” events in SSP5-8.5 scenarios. The frequency of “Extremely dry” months in SSP5-8.5 compared to SSP1-2.6 is expected to increase by 14, 7, 14, 10, 5, 14, and 7 months for the Mahabad, Maragheh, Saqez, Sarab, Tabriz, Takab, and Urmia stations, respectively. In contrast, the frequency of “Extremely wet” months will decline for all stations in Lake Urmia Basin. The results of this study provide useful insight for considering drought prevention measures to be implemented in advance for Lake Urmia Basin, which is currently experiencing various environmental issues. Full article
(This article belongs to the Special Issue Hydroclimatic Modeling and Monitoring under Climate Change)
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20 pages, 7451 KiB  
Article
Research on the Application of CEEMD-LSTM-LSSVM Coupled Model in Regional Precipitation Prediction
by Jian Chen, Zhikai Guo, Changhui Zhang, Yangyang Tian and Yaowei Li
Water 2023, 15(8), 1465; https://doi.org/10.3390/w15081465 - 9 Apr 2023
Cited by 3 | Viewed by 1459
Abstract
Precipitation is a vital component of the regional water resource circulation system. Accurate and efficient precipitation prediction is especially important in the context of global warming, as it can help explore the regional precipitation pattern and promote comprehensive water resource utilization. However, due [...] Read more.
Precipitation is a vital component of the regional water resource circulation system. Accurate and efficient precipitation prediction is especially important in the context of global warming, as it can help explore the regional precipitation pattern and promote comprehensive water resource utilization. However, due to the influence of many factors, the precipitation process exhibits significant stochasticity, uncertainty, and nonlinearity despite having some regularity. In this article, monthly precipitation in Zhoukou City is predicted using a complementary ensemble empirical modal decomposition (CEEMD) method combined with a long short-term memory neural network (LSTM) model and a least squares support vector machine (LSSVM) model. The results demonstrate that the CEEMD-LSTM-LSSVM model exhibits a root mean square error of 15.01 and a mean absolute error of 11.31 in predicting monthly precipitation in Zhoukou City. The model effectively overcomes the problems of modal confounding present in empirical modal decomposition (EMD), the existence of reconstruction errors in ensemble empirical modal decomposition (EEMD), and the lack of accuracy of a single LSTM model in predicting modal components with different frequencies obtained by EEMD decomposition. The model provides an effective approach for predicting future precipitation in the Zhoukou area and predicts monthly precipitation in the study area from 2023 to 2025. The study provides a reference for relevant departments to take effective measures against natural disasters and rationally plan urban water resources. Full article
(This article belongs to the Special Issue Hydroclimatic Modeling and Monitoring under Climate Change)
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16 pages, 12560 KiB  
Article
Water Balance of the Regulated Arid Lake as an Indicator of Climate Change and Anthropogenic Impact: The North (Small) Aral Sea Case Study
by Alexander Izhitskiy and Georgy Ayzel
Water 2023, 15(8), 1464; https://doi.org/10.3390/w15081464 - 9 Apr 2023
Cited by 3 | Viewed by 1665
Abstract
Inland waters in the endorheic basins of the arid zone are especially vulnerable to both climate-induced changes and anthropogenic influence. The North Aral Sea, which previously suffered a drastic shrinkage and partially recovered with the launch of the human-made Kokaral dam, is currently [...] Read more.
Inland waters in the endorheic basins of the arid zone are especially vulnerable to both climate-induced changes and anthropogenic influence. The North Aral Sea, which previously suffered a drastic shrinkage and partially recovered with the launch of the human-made Kokaral dam, is currently subject to significant inter-annual variability of its water volume. This study aimed to obtain insight into the modern water balance condition of the lake and to project the possible changes in it. A series of model simulation experiments were implemented based on three representative concentration pathway (RCP) scenarios with varying maximum lake surface levels, determined by the dam. Present-day dam conditions showed the possibility to retain the lake volume above 26 km3 under the RCP 2.6 and 6.0 scenarios. Simulations under the RCP 8.5 scenario revealed significant instability of the lake volume and a well-shown decrease in the outflow amount. A possible human-made increase in terms of the lake surface level up to 48.5 m.a.s.l. may allow for the retention of the volume in the range of 48–50 km3 in the RCP 2.6 case. The RCP 6.0 and 8.5 scenarios revealed a lake volume decrease and almost full cessation of the Kokaral outflow toward the end of the 21st century. Full article
(This article belongs to the Special Issue Hydroclimatic Modeling and Monitoring under Climate Change)
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