PAVLIB4SWAT: a Python analysis and visualization tool and library based on Kepler.gl for SWAT models DOI Creative Commons
Qiaoying Lin, Dejian Zhang, Jiefeng Wu

и другие.

Journal of Hydroinformatics, Год журнала: 2023, Номер 26(1), С. 189 - 202

Опубликована: Дек. 30, 2023

Abstract The Soil and Water Assessment Tool (SWAT) has been widely applied to simulate the hydrological cycle, investigate cause-and-effect relationships, aid decision-making for better watershed management. However, software tools model dataset analysis visualization support informed in a web environment are not considered fully fledged technically intensive implement. This study focuses on addressing these issues by establishing tool library (named PAVLIB4SWAT) that can largely reduce technical expertise requirements developers adopt customize this work their own demands. Specifically, we created PAVLIB4SWAT based Kepler.gl widget visualize SWAT data, including shapefiles from delineation process, inputs, simulated results via dynamic interactive maps. We evaluated through Jinjiang use case demonstrate its utility ease of adoption. shows provide various geospatial mapping functionalities models flexibly distribute visualized as standalone offline pages servers. In addition, was designed an open-source project implemented purely Python programming language; thus, easily adapt it suit

Язык: Английский

Improved forest canopy evaporation leads to better predictions of ecohydrological processes DOI
Henrique Haas, Latif Kalin, Haw Yen

и другие.

Ecological Modelling, Год журнала: 2024, Номер 489, С. 110620 - 110620

Опубликована: Янв. 13, 2024

Язык: Английский

Процитировано

3

Advanced Soft Computing Techniques for Monthly Streamflow Prediction in Seasonal Rivers DOI Creative Commons
Mohammed Achite, Okan Mert Katipoğlu, Veysi Kartal

и другие.

Atmosphere, Год журнала: 2025, Номер 16(1), С. 106 - 106

Опубликована: Янв. 19, 2025

The rising incidence of droughts in specific global regions recent years, primarily attributed to warming, has markedly increased the demand for reliable and accurate streamflow estimation. Streamflow estimation is essential effective management utilization water resources, as well design hydraulic infrastructure. Furthermore, research on gained heightened importance because not only survival all living organisms but also determining quality life Earth. In this study, advanced soft computing techniques, including long short-term memory (LSTM), convolutional neural network–recurrent network (CNN-RNN), group method data handling (GMDH) algorithms, were employed forecast monthly time series at two different stations Wadi Mina basin. performance each technique was evaluated using statistical criteria such mean square error (MSE), bias (MBE), absolute (MAE), correlation coefficient (R). results study demonstrated that GMDH algorithm produced most forecasts Sidi AEK Djillali station, with metrics MSE: 0.132, MAE: 0.185, MBE: −0.008, R: 0.636. Similarly, CNN-RNN achieved best Kef Mehboula 0.298, 0.335, −0.018, 0.597.

Язык: Английский

Процитировано

0

Modeling the Nexus of Climate Change and Deforestation: Implications for the Blue Water Resources of the Jari River, Amazonia DOI Open Access
Paulo Ricardo Rufino, Björn Gücker, Martin Völk

и другие.

Water, Год журнала: 2025, Номер 17(5), С. 660 - 660

Опубликована: Фев. 24, 2025

Deforestation and agricultural practices, such as livestock farming, disrupt biogeochemical cycles, contribute to climate change, can lead serious environmental problems. Understanding the water cycle changes in discharge patterns at watershed scale is essential tracking how deforestation affects flow downstream bodies ocean. The Amazon basin, which provides about 15–20% of freshwater flowing into oceans, one most important river systems world. Despite this, it increasingly suffering from anthropogenic pressure, mainly converting rainforests areas, drive global warming ecosystem instability. In this study, we applied a calibrated Soil Water Assessment Tool (SWAT) model Jari River Watershed, part Brazilian Amazon, assess combined effects change on resources between 2020 2050. was validated using observed streamflow. results show an NS 0.85 0.89, PBIAS −9.5 −0.6, p-factor 0.84 0.93, r-factor 0.78, for periods calibration validation, respectively, indicating strong performance. We analyzed four scenarios that examined different levels change. Our suggest could increase surface runoff by 18 mm, while groundwater recharge vary declines −20 mm increases 120 mm. These amplify streamflow variability, affect its dynamics, intensify flood risks, reduce availability during dry periods, leading significant risks hydrology Amazonian watersheds human supply. This, turn, profoundly impact region’s megadiverse flora fauna, directly depend balanced watersheds.

Язык: Английский

Процитировано

0

Impacts of Land Use and Climate Changes on River Streamflow: The Case Study of the Piracicaba Basin - Brazil DOI
Ronalton Evandro Machado, Tárcio Rocha Lopes, Sérgio Nascimento Duarte

и другие.

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Evaluating soil erosion zones in the Kangsabati River basin using a stacking framework and SHAP model: a comparative study of machine learning approaches DOI Creative Commons
Javed Mallick, Saeed Alqadhi, Swapan Talukdar

и другие.

Environmental Sciences Europe, Год журнала: 2025, Номер 37(1)

Опубликована: Март 7, 2025

Язык: Английский

Процитировано

0

Multi-Model Assessment to Analyze Flow Alteration Under the Changing Climate in a Medium-Sized River Basin in Nepal: A Case Study of the Kankai River Basin DOI Open Access
Manan Sharma, Rajendra Prasad Singh, Sanjay Sharma

и другие.

Water, Год журнала: 2025, Номер 17(7), С. 940 - 940

Опубликована: Март 24, 2025

The medium river basins (MRBs) in Nepal originate from mid-hills. These medium-range rivers are typically non-snow-fed, relying on rain and other water sources. small, the sizes of vary between 500 5000 km2. MRBs often used for irrigation agricultural purposes. In this analysis, we first set up, calibrated, validated three hydrological models (i.e., HBV, HEC HMS, SWAT) at Kankai River Basin (one MRB eastern Nepal). Then, best-performing SWAT model was forced with cutting-edge climate (CMs) using thirteen CMIP6 under four shared socioeconomic pathways (SSPs). We employed ten bias correction (BC) methods to capture local spatial variability precipitation temperature. Finally, likely streamflow alteration during two future periods, i.e., near-term timeframe (NF), spanning 2031 2060, long-term (FF), covering years 2071 2100, were evaluated against historical period (baseline: 1986–2014), considering uncertainties associated choice CMs, BC methods, or/and SSPs. study results confirm that there will not be any noticeable shifts seasonal variations future. However, magnitude is projected alter substantially. Overall, estimated upsurge upcoming periods. observed less deviation expected April, around +5 +7% more than baseline period. Notably, a higher percentage increment monsoon season (June–August). During NF (FF) period, flow +20% (+40%) lower SSPs, whereas +30% (+60%) SSPs high season. Thus, likelihoods flooding, inundation, discharge quite coming years.

Язык: Английский

Процитировано

0

Assessing the impact of climate change on snowmelt runoff and monthly streamflow in an Upper Himalayan River Basin using the SWAT model DOI
Soumyadip Biswas, Sujata Biswas

Theoretical and Applied Climatology, Год журнала: 2025, Номер 156(5)

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0

Watershed hydrological response in developing climate change resilience and adaptation strategies, case of Gilgal Gibe watershed, Ethiopia DOI
Wana Geyisa Namara,

Zeinu Ahimed Rabba,

Sewmehon Sisay Fanta

и другие.

Environmental Monitoring and Assessment, Год журнала: 2025, Номер 197(6)

Опубликована: Май 7, 2025

Язык: Английский

Процитировано

0

Estimation of monthly snowmelt contribution to runoff using gridded meteorological data in SWAT model for Upper Alaknanda River Basin, India DOI
Soumyadip Biswas, Sujata Biswas

Environmental Monitoring and Assessment, Год журнала: 2023, Номер 196(1)

Опубликована: Дек. 26, 2023

Язык: Английский

Процитировано

6

The Effects of Climate Change on Streamflow, Nitrogen Loads, and Crop Yields in the Gordes Dam Basin, Turkey DOI Open Access
Ayfer Özdemir, Martin Völk, Michael Strauch

и другие.

Water, Год журнала: 2024, Номер 16(10), С. 1371 - 1371

Опубликована: Май 11, 2024

The Mediterranean region is highly vulnerable to climate change. Longer and more intense heatwaves droughts are expected. Gordes Dam in Turkey provides drinking water for Izmir city irrigation a wide range of crops grown the basin. Using Soil Water Assessment Tool (SWAT), this study examined effects projected change (RCP 4.5 RCP 8.5) on simulated streamflow, nitrogen loads, crop yields basin period 2031–2060. A hierarchical approach define hydrological response units (HRUs) SWAT Fast Automatic Calibration (FACT) were used reduce computational time improve model performance. simulations showed that average annual discharge into reservoir increase by between 0.7 m3/s 4 under 8.5 scenarios. steep slopes changes precipitation area may lead higher streamflow. In addition, rising temperatures predicted projections could earlier spring snowmelt. This also increased Projected loads 8.8 25.1 t/year. results agricultural production variable. While poppy, tobacco, winter barley, wheat will some extent because change, maize, cucumbers, potatoes all be negatively affected. Non-continuous limited data quality uncertainties, so accuracy affected these limitations inconsistencies. However, provide basis developing sustainable land management practices at catchment scale quantity ecological balance resulting from use patterns economic benefit not fully demonstrated study. To explore most appropriate strategies production, developed should further multi-criteria optimization analysis considers only but targets.

Язык: Английский

Процитировано

2