Watershed environmental impact assessment for extreme climates based on shared socioeconomic pathway climate change scenarios DOI Creative Commons
Jung Min Ahn, Jungwook Kim, Hongtae Kim

и другие.

Ecological Indicators, Год журнала: 2023, Номер 154, С. 110685 - 110685

Опубликована: Июль 27, 2023

Abnormal climate phenomena that exceed conventional weather observations occur worldwide, such as severe floods, droughts, and environmental issues, have attracted increasing attention. To avoid indiscriminate industrialization achieve sustainable development, experts presented various opinions based on change scenario data. In this study, shared socioeconomic pathway (SSP) scenarios consider conditions were used to assess the impact of extreme watersheds. Using UK Earth System Modelling (UKESM1) SSP scenarios, we analyzed following: 1) Heat index for each using H-Index; 2) standardized precipitation (SPI); 3) non-point pollution event mean concentration (EMC); 4) flow caused by combining K-water Distributed RUnoff Model (K-DRUM) global calculator (GEFC) models. According heat analysis regarding SSPs heatwave will continue rise if high carbon emissions persist. Temperature serves an important indicator has most meaningful ecosystems. The SPI showed increase in "extremely dry" conditions, overall, more droughts are likely due emission-induced change. nonpoint source is also higher with emissions. drought assessment revealed a shift from "moist conditions" category grade C. Our assessments study conclusively indicate frequency along pollution. Furthermore, flows C, resulting disappearance some sensitive ecological species invasive species. These analyses determined leads significant alterations overall water circulation, thereby complicating resource management. identified watersheds highly vulnerable designated these "mid-watersheds" first require Here, aquatic ecosystem environment can be affected without any artificial influence. Various research-based methods modeling been beneficial establishing policies coping strategies preservation development.

Язык: Английский

Hydrological Modelling and Climate Adaptation under Changing Climate: A Review with a Focus in Sub-Saharan Africa DOI Open Access
Vincent Dzulani Banda, Bloodless Dzwairo, Sudhir Kumar Singh

и другие.

Water, Год журнала: 2022, Номер 14(24), С. 4031 - 4031

Опубликована: Дек. 10, 2022

Empirical evidence continues to show that climate change remains a threat the stability of hydrologic system. As system interacts with cycle, one significant repercussion global warming includes changes in water availability at both regional and local scales. Climate adaptation is intrinsically difficult attain due dynamic earth lack comprehensive understanding future its associated uncertainties. Mostly developing countries, hampered by scarcity good quality adequate hydro-meteorological data. This article provides synopsis modelling chain applied investigate response under changing climate, which choosing appropriate models, downscaling techniques, emission scenarios, approach be used modelling. The conventional criteria for suitable hydrological model are discussed. advancement scenarios including latest Shared Socioeconomic Pathways their role modelling, impact assessment, adaptation, also highlighted. paper discusses uncertainties impacts plausible approaches reducing such Among outcomes this review include highlights studies on commonly models assessing particularly sub-Saharan Africa region some specific reviews southern Africa. Further, as human systems keep dominating within several ways, effective should involve coupling these may truly represent bidirectional feedback experienced modern world. concludes data key having robust measures, hence poorly gauged basins use artificial neural networks satellite datasets have shown successful tools, calibration validation.

Язык: Английский

Процитировано

33
Identifying the impacts of land use landscape pattern and climate changes on streamflow from past to future DOI Creative Commons
Yingshuo Lyu, Hong Chen, Zhe Cheng

и другие.

Journal of Environmental Management, Год журнала: 2023, Номер 345, С. 118910 - 118910

Опубликована: Сен. 8, 2023

Identifying the individual and combined hydrological response of land use landscape pattern climate changes is key to effectively managing ecohydrological balance regions. However, their nonlinearity, effect size, multiple causalities limit causal investigations. Therefore, this study aimed establish a comprehensive methodological framework quantify in climate, evaluate trends streamflow response, analyze attribution events five basins Beijing from past future. Future projections were based on three general circulation models (GCMs) under two shared socioeconomic pathways (SSPs). Additionally, 2035 natural development scenario was simulated by patch-generating simulation (PLUS). The Soil Water Assessment Tool (SWAT) applied spatial temporal dynamics over period 2005-2035 with scenarios. A bootstrapping nonlinear regression analysis boosted tree (BRT) model used streamflow, respectively. results indicated that future, overall basin would decrease, slightly reduced peak most summer significant increase autumn winter. quadratic more explained impact streamflow. change depended where relationship curve relation threshold. In addition, impacts not isolated but joint. They presented nonlinear, non-uniform, coupled relationship. Except for YongDing River Basin, annual influenced pattern. dominant factors critical pair interactions varied basin. Our findings have implications city planners managers optimizing functions promoting sustainable development.

Язык: Английский

Процитировано

22
Spatiotemporal variations of water conservation and its influencing factors in the Qinghai Plateau, China DOI Creative Commons
Xin Yan,

Guangchao Cao,

Shengkui Cao

и другие.

Ecological Indicators, Год журнала: 2023, Номер 155, С. 111047 - 111047

Опубликована: Окт. 7, 2023

Язык: Английский

Процитировано

18
Improving estimation capacity of a hybrid model of LSTM and SWAT by reducing parameter uncertainty DOI
Hyemin Jeong, Byeongwon Lee, Dongho Kim

и другие.

Journal of Hydrology, Год журнала: 2024, Номер 633, С. 130942 - 130942

Опубликована: Фев. 27, 2024

Язык: Английский

Процитировано

8
Hydrological Projections in the Third Pole Using Artificial Intelligence and an Observation‐Constrained Cryosphere‐Hydrology Model DOI Creative Commons
Junshui Long, Lei Wang, Deliang Chen

и другие.

Earth s Future, Год журнала: 2024, Номер 12(4)

Опубликована: Апрель 1, 2024

Abstract The water resources of the Third Pole (TP), highly sensitive to climate change and glacier melting, significantly impact food security millions in Asia. However, projecting future spatial‐temporal runoff changes for TP's mountainous basins remains a formidable challenge. Here, we've leveraged long short‐term memory model (LSTM) craft grid‐scale artificial intelligence (AI) named LSTM‐grid. This has enabled production hydrological projections seven major river TP. LSTM‐grid integrates monthly precipitation, air temperature, total mass (total_GMC) data at 0.25‐degree grid. Training employed gridded historical evapotranspiration sets generated by an observation‐constrained cryosphere‐hydrology headwaters TP during 2000–2017. Our results demonstrate LSTM grid's effectiveness usefulness, exhibiting Nash‐Sutcliffe Efficiency coefficient exceeding 0.92 verification periods (2013–2017). Moreover, monsoon region exhibited higher rate increase compared those westerlies region. Intra‐annual indicated notable increases spring runoff, especially where meltwater contributes runoff. Additionally, aptly captures before after turning points highlighting growing influence precipitation on reaching maximum total_GMC. Therefore, offers fresh perspective understanding spatiotemporal distribution high‐mountain glacial regions tapping into AI's potential drive scientific discovery provide reliable data.

Язык: Английский

Процитировано

8
Sensitivity analysis of SWAT streamflow and water quality to the uncertainty in soil properties generated by the SoLIM model DOI
Qiuliang Lei, Tianpeng Zhang, Miaoying An

и другие.

Journal of Hydrology, Год журнала: 2024, Номер 642, С. 131879 - 131879

Опубликована: Авг. 24, 2024

Язык: Английский

Процитировано

8
Deep learning algorithms and their fuzzy extensions for streamflow prediction in climate change framework DOI Creative Commons
Rishith Kumar Vogeti,

Rahul Jauhari,

Bhavesh Rahul Mishra

и другие.

Journal of Water and Climate Change, Год журнала: 2024, Номер 15(2), С. 832 - 848

Опубликована: Фев. 1, 2024

Abstract The present study analyzes the capability of convolutional neural network (CNN), long short-term memory (LSTM), CNN-LSTM, fuzzy CNN, LSTM, and CNN-LSTM to mimic streamflow for Lower Godavari Basin, India. Kling–Gupta efficiency (KGE) was used evaluate these algorithms. Fuzzy-based deep learning algorithms have shown significant improvement over classical ones, among which is best. Thus, it further considered projections in a climate change context four-time horizons using four shared socioeconomic pathways (SSPs). Average 2041–2060, 2061–2080, 2081–2090 are compared that 2021–2040 changed by +3.59, +7.90, +12.36% SSP126; +3.62, +8.28, +12.96% SSP245; +0.65, −0.01, −0.02% SSP370; +0.02, +0.71, +0.06% SSP585. In addition, two non-parametric tests, namely, Mann–Kendall Pettitt were conducted ascertain trend point projected streamflow. Results indicate provides more precise prediction than others. identified variations across different SSPs facilitate valuable insights policymakers relevant stakeholders. It also paves way adaptive decision-making.

Язык: Английский

Процитировано

7
Evaluation of optimal dam release to achieve agricultural economic-ecological development from stakeholders' perspectives in the Karkheh basin, Iran DOI Creative Commons
Javad Zahiri, Abbas Mirzaei

Journal of Hydrology Regional Studies, Год журнала: 2025, Номер 57, С. 102181 - 102181

Опубликована: Янв. 5, 2025

Язык: Английский

Процитировано

1
Dynamic classification and attention mechanism-based bidirectional long short-term memory network for daily runoff prediction in Aksu River basin, Northwest China DOI
Wei Qing, Ju Rui Yang, Fangbing Fu

и другие.

Journal of Environmental Management, Год журнала: 2025, Номер 374, С. 124121 - 124121

Опубликована: Янв. 15, 2025

Язык: Английский

Процитировано

1
Climate Change Impacts on Blue and Green Water of Meki River Sub-Basin DOI Open Access
Aster Tesfaye Hordofa, Olkeba Tolessa Leta, Tena Alamirew

и другие.

Water Resources Management, Год журнала: 2023, Номер 37(6-7), С. 2835 - 2851

Опубликована: Апрель 15, 2023

Язык: Английский

Процитировано

17