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Theoretical and applied climatology
Springer
Theoretical and applied climatology

Springer

0177-798X

Theoretical and applied climatology/Journal Theoretical and applied climatologySCIISTPAHCI
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    Streamflow variability under SSP2-4.5 and SSP5-8.5 climate scenarios using QSWAT plus for Subansiri River Basin in Arunachal Pradesh, India

    Ghritartha GoswamiRam Kailash PrasadSameer Mandal
    1.1-1.23页
    查看更多>>摘要：Abstract The Subansiri River Basin faces hydrological challenges from climate and land use changes. Limited studies on future SSP2-4.5 and SSP5-8.5 scenarios hinder effective adaptation, requiring detailed hydrological assessments for sustainable management. Therefore, the present study is focused on the impact of land use, land cover, climate change on the water resources of the Subansiri River Basin, India. The study utilizes the Soil and Water Assessment Tool Plus (SWAT+) within the QGIS to analyze the variability of streamflow in the Basin. The study identified groundwater recharge as a key determinant, which contributes 69% to the hydrological mass balance. Moreover, the forest and vegetation cover influence water balance by 58.4% and 38%, respectively. Evapotranspiration contributes 23% while, surface runoff accounts for just 6%. Further, the study investigates the impact of climate change on streamflow in the Subansiri River Basin using SWAT+. It utilizes an ensemble of five Global Climate Models under SSP2-4.5 and SSP5-8.5 scenarios with CMIP6 dataset. The historical streamflow shows a peak discharge of 2,566 m³/sec in July 2008. Future projections of streamflow indicate increasing discharge, with peaks up to 2,724 m³/sec by 2072 under SSP2-4.5 and 3,680 m³/sec by 2100 under SSP5-8.5. The study also predicts significant monthly variability, with streamflow increases by over five times in the month of May in comparison to its historical observation under the SSP5-8.5 far-future scenario. In contrast, some months are likely to encounter decreased streamflow. Eventually leading to extreme hydrological events that could significantly impact flood management in the Subansiri River Basin.
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    South Indian agricultural crop yield prediction using deep learning and transfer learning models

    R. AnandavalliK. KarthigadeviG. Elizabeth Rani
    1.1-1.16页
    查看更多>>摘要：Abstract Agriculture is an essential part of the Indian economy, so crop yield (CY) prediction is vital to help farmers and their businesses understand when to plant a crop and when to harvest based on seasons for better CY. This study proposes a deep learning model called Mish Activation-based Bidirectional Gated Recurrent Unit (MABGRU) to forecast CYs primarily grown throughout India. The system comprises the following steps: preprocessing, deep feature extraction, feature selection, and CY prediction. Initially, the system performs preprocessing steps such as imputation and normalization to handle the missing values and standardize the dataset. Then, deep features are learned using the Deformable Attention-based Residual Network-50 (DARN50). Then, the best features are chosen from the extracted feature set using the Tent chaotic map and phasor operator, including the Sparrow search algorithm (TPSSA). Finally, MABGRU is employed for CY prediction. The result of the system is compared with the existing systems, and our model outperforms the previous techniques by achieving a maximum accuracy of 98.88% with less computational time (15.9 ms).
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    • NETL
    • NSTL
    • Springer Nature

    Evaluating streamflow and hydrological parameters in Oued Cherraa basin (Northeastern Morocco) through SWAT model

    Mohammed LaaboudiAbdelhamid MezrhabZahar Elkheir AliouaAli Achebour...
    1.1-1.16页
    查看更多>>摘要：Abstract The development of water resource management plans requires the use of streamflow modeling, especially in poorly monitored basins such as Oued Cherraa in eastern Morocco. Given the inherent challenges of direct monitoring in these areas, modeling serves as a crucial alternative for obtaining flow data. Comprehending the hydrological behavior of a basin is crucial for effectively addressing water-related challenges, such as floods, droughts, and the availability of water for hydropower, irrigation, and domestic needs. Additionally, it facilitates the creation of robust adaptation and preparedness strategies. This study modeled Oued Cherraa Basin using the Soil and Water Assessment Tool (SWAT) through the ArcSWAT interface, version 2012. The software, designated SWAT-CUP2012, which incorporates the SUFI- 2 algorithm for sensitivity analysis, calibration, and validation, was employed to refine the model. The model was calibrated over the 2014–2015 period and validated with 2016 data. The storage time constant for normal flow was most significantly influenced by the deep aquifer percolation (RCHRG_DP), the curve number (CN2), and the calibration coefficient. The outcomes of the calibration and validation processes yielded coefficient of determination (R2) values of 0.66 and 0.63, respectively. Nash–Sutcliffe efficiency (NSE) values of 0.58 and 0.60 were obtained. During the calibration period, the mean monthly flow recorded at the Tazarhine station was 2.077 m3/s. During the validation period, the velocity was 2.016 m3/s. A thorough methodology for calibration and validation was implemented to support the development of an improved model that accurately represents the hydrological processes within Oued Cherraa Basin. This data will be essential for designing effective water resource management and planning strategies in the region.
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    • NSTL
    • Springer Nature

    Effect of heat wave on physiological responses, body surface temperature, heat load, and panting behaviour in buffalo heifers

    Brijesh YadavPoonam YadavArun Kumar MadanMukul Anand...
    1.1-1.12页
    查看更多>>摘要：Abstract The present study was conducted to investigate the effect of heat wave on physiological responses and panting behaviour in buffalo heifers. The study was conducted in last fortnight of May when THI ranged between 78.42 and 88.84. The experiment was conducted on six apparently healthy buffalo heifers aged between 12 and 16 months that were maintained in well ventilated shed. The physiological parameters, body surface temperature (BST) (back, croup, neck, head, ear, eye and muzzle) and panting behaviour were recorded at 6 time points on day 1 and day 5 at 6 am, 10 am, 2 pm, 6 pm, 10 pm and next day 6 am and heat load (HL) was calculated. Respiratory rate (RR), rectal temperature (RT) and HL was significantly (p < 0.05) higher at 2 time points as compared to 6 am on day 1. However, RR increased significantly (p < 0.05) at 4 time points and RT and HL increased significantly (p < 0.05) at 3 times points on day 5 as compared to 6 am of the same day. RR, RT and HL were significantly (p < 0.05) higher at different time points on day 5 as compared to day 1. Both on day 1 and 5, BST at croup, neck and head were significantly (p < 0.05) higher at 4 time points whereas BST at back, ear and eye was higher (p < 0.05) only at 3 time points as compared to 6 am and next day 6 am. Except at 6 am and next day 6 am, BST was significantly (p < 0.05) higher at different time points on day 5 as compared to day 1, at different anatomical locations. Frequency and duration of panting were increased with progression of heat wave. The results indicated that physiological and behavioural heat loss mechanisms failed to maintain homeothermy, leading to substantial increase in heat load in buffalo heifers during heat wave.
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    Adaptive ensemble weighting for GCMs to enhance future drought characterization under various climate change scenarios

    Muhammad ShakeelHussnain AbbasAyesha WaseemZulfiqar Ali...
    1.1-1.20页
    查看更多>>摘要：Abstract Drought is one the most complex and catastrophic natural hazards. Global Climate Models (GCMs) have become increasingly popular for predicting future drought characteristics. However, errors and interdependence between the time series data of GCMs reduce the accuracy of drought characterization. This article introduces a new weighting scheme for multi-model ensemble to integrate the features of multiple GCM-based simulations of precipitation, called the Minimum Redundancy Maximum Relevance Adaptive Weighting Scheme (MRMRAWS). To evaluate the performance of MRMRAWS, this study uses simulations from 18 different GCMs, which represent monthly precipitation data from 1950 to 2014. Data were collected from 1817 uniformly distributed grid points on the Tibetan Plateau (TP). In addition, simulations from three future scenarios, covering monthly precipitation records from 2016 to 2100, are used to assess the temporal behavior of drought and its various classes. The results of this research have two main facets. First, the proposed MRMRAWS outperforms other widely used ensemble weighting schemes, advocating its use to improve the ensemble of GCMs. Second, the evaluation of future drought characteristics indicates that recurrent droughts are likely to persist in the TP region under longer time scales and higher-emission scenarios.
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    Cross-season influence of the Arctic oscillation on the Northeast China cold vortex during early summer

    Dickson MbigiZiniu XiaoNan Zhang
    1.1-1.17页
    查看更多>>摘要：Abstract The Northeast China cold vortex (NCCV) exerts substantial impacts on the East Asian climate. While several studies have reported the NCCV formation and characteristics related to the local internal atmospheric variability and extrinsic forcing, limited studies have focused on the roles of Arctic Oscillation (AO) associated with the NCCV variability. This study investigated the modulation of the NCCV in early summer by the preceding winter AO. The results show that the NCCV is positively correlated with the AO, indicating that an enhancing (weakening) preceding winter-AO could lead to increases (decreases) of NCCV activity in early summer. A positive winter-AO leads to a concurrent cold sea surface temperature in the subpolar North Atlantic through dynamic and thermodynamic processes. This cooling tendency is essential in sustaining the influence of preceding winter AO in the subsequent early summer. Subsequently, it triggers the wave train from the subpolar North Atlantic via the western Europe-Mediterranean Sea and central China and eventually reaches Northeast China to cause negative height anomalies. This process results in enhancing significant cyclonic anomalies over Northeast China, which creates conducive conditions for the occurrence and maintenance of NCCV activities over there. Moreover, an empirical prediction model was formulated to predict the NCCV variations based on the joint SST and AO indices. The hindcast shows promising prediction skills when AO is incorporated into the model. These results could be useful for decision-makers to take action in dealing with NCCV events in the context of the AO.  
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    • NETL
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    • Springer Nature

    Rain-on-snow climatology and its impact on flood risk in snow-dominated regions of Türkiye

    Serhan YeşilköyÖzlem Baydaroğlu
    1.1-1.17页
    查看更多>>摘要：Abstract The rapid snowmelt that typically occurs after snow accumulates at low temperatures and precipitation develops at higher temperatures is a defining characteristic of rain-on-snow (ROS). During ROS events, the swift release of melted snow water can result in flash floods and a substantial surge in runoff, which in turn can lead to the overflow or elevation of rivers and consequently severe inundation and flooding. This study reveals the climatology of ROS events and examines the connections between ROS events and surface runoff quantities, aiming to contribute to flood projections and snow research for Türkiye, specifically focusing on the regions in the north and east of the country that receive substantial snowfall and have previously encountered serious flooding. The findings indicate a decline in ROS events in the Eastern and Southeastern Anatolia regions, particularly throughout the past three decades, while there has been an increase in the Central and Western Black Sea regions. The decline in the quantity of ROS (rainfall over snow) in the Southeastern Anatolia region, which serves as the primary water source for Türkiye, is a favorable outcome as it leads to a decrease in the risk of floods, a longer duration of snow cover, and the feeding of water resources. Given the rise in ROS events in the Central and Western Black Sea regions, it is imperative to formulate novel urbanization strategies to mitigate potential flood risks and minimize associated damages that consider the region’s topography, urbanization, and precipitation patterns. In addition, the results reveal a startling new trend: ROS events are shifting both spatially and temporally.
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    • NETL
    • NSTL
    • Springer Nature

    Trends and historical patterns of meteorological droughts in New Brunswick, Canada, using PDSI and SEDI indices

    Ali FaghfouriGuillaume FortinAlbin UllmannFlorian Raymond...
    1.1-1.23页
    查看更多>>摘要：Abstract Droughts are increasingly recognized as a significant global challenge, with severe impacts observed in Canada's Prairie provinces. While less frequent in Eastern Canada, prolonged precipitation deficits, particularly during summer, can lead to severe drought conditions. This study investigates the causes and consequences of droughts in New Brunswick (NB) by employing two drought indices: the Palmer Drought Severity Index (PDSI) and Standardized Evapotranspiration Deficit Index (SEDI)– at ten weather stations across NB from 1971 to 2020. Additionally, the Canadian Gridded Temperature and Precipitation Anomalies (CANGRD) dataset (1979–2014) was utilized to examine spatial and temporal drought variability and its alignment with station-based observations. Statistical analyses, including the Mann–Kendall test and Sen's slope estimator, were applied to assess trends in drought indices on annual and seasonal timescales using both station and gridded data. The results identified the most drought-vulnerable regions in NB and revealed significant spatial and temporal variability in drought severity over the 1971–2020 period. Trend analyses further highlighted the intensification of extreme drought events during specific years. Coastal areas in southern NB were found to be particularly susceptible to severe drought conditions compared to inland regions, consistent with observed declines in both the frequency of rainy days and daily precipitation amounts in these areas. These findings underscore the need for targeted drought mitigation strategies particularly in NB’s coastal zones, to address the region’s increasing vulnerability to extreme drought events.
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    Spatiotemporal rainfall concentration and erosivity in a tropical monsoon country

    Gongbo WangHaibo HuAbu Reza Md Towfiqul IslamMst. Yeasmin Akter...
    1.1-1.16页
    查看更多>>摘要：Abstract Tropical monsoon countries like Bangladesh have experienced erratic spatiotemporal rainfall distribution, heavy rainfall, and extensive erosion in recent decades. The erosive nature of the soil in the country poses a serious ecological problem. However, there is a lack of studies on the spatiotemporal distribution of rainfall erosivity and precipitation concentration trends in Bangladesh. This study intends to investigate the Rainfall erosivity over the past three decades in Bangladesh. Using the Precipitation Concentration Index (PCI) and the Modified Fournier Index (MFI), this study attempted to demonstrate precipitation concentration and erosivity distribution during 1991–2020. The PCI and MFI indices were calculated using monthly precipitation records from 30 observatories nationwide. PCI values ranged between 15.43% and 21.04%, indicating substantial irregularity in rainfall across Bangladesh, while the MFI value higher than 98 shows a very high erosion capacity of rainfall in a shorter period. The mean annual rainfall erosivity factor (R-factor) found 865 MJ mm ha− 1 hr− 1 y− 1 with a range of 711.89–1019.97 MJ mm ha− 1 hr− 1 y− 1, suggesting moderate to higher erosivity potential in annual rainfall. All the stations exhibited higher erosivity values in monsoon (597.673–902.893 MJ mm ha− 1 hr− 1 y− 1), followed by pre-monsoon (325.779–436.599 MJ mm ha− 1 hr− 1 y− 1) and post-monsoon (166.67–241.52 MJ mm ha− 1 hr− 1 y− 1). Higher rainfall erosivity is concentrated in Bangladesh’s mid-central to northeastern region, while the southwest, northeast, and southeastern areas are at higher risk of monsoon rainfall erosivity. Though decreasing trends in annual rainfall erosivity were observed in 26 stations, monsoon and post-monsoon rainfall erosivity showed an increasing trend in 19 and 8 stations, respectively. The outcome of the current study is expected to help address the challenges of climate change and sustainable development issues in Bangladesh and similar climate-vulnerable countries around the world.
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    Long-term relationship between soil moisture and precipitation over India: An analysis using event coincidence analysis and PCMCI method

    Vibin JoseAnantharaman Chandrasekar
    1.1-1.21页
    查看更多>>摘要：Abstract The land-atmosphere interaction processes are crucial for the atmospheric modelling studies as it influences the interchange of energy and matter between the land surface and atmosphere and can impact climate and weather patterns on regional and global scales. The feedback between the soil moisture (SM) and precipitation (PR) is the key factor for land surface and atmosphere interactions; however the above feedback is not well understood. The present study employs Event Coincidence Analysis (ECA) method for investigating the influence of SM on extreme PR over the Indian domain. In this study, 21 years (2000-2020) of Global Land Evaporation Amsterdam Model (GLEAM) surface SM data and root zone (Rz\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_z$$\end{document}) SM data together with India Meteorological Department PR data are considered. The findings indicate that West central India (WCI) region has a higher long term relationship between SM and PR over the surface as well as Rz\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_z$$\end{document}, than the rest of the Indian regions. The higher long term relationship between SM and PR over WCI region is associated since the WCI region is a transition region, where the land-atmosphere interaction is more pronounced as compared to either the wet or the dry regions. The results of the ECA method also shows that the number of grid points having higher trigger coincidence rate (TCR) for the highest time lag (30 days), is lower for Rz\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_z$$\end{document} SM as compared to the surface SM. Additionally, seasonal TCR analyses are performed, using the 21 years (2000-2020) data. The results of the seasonal TCR analysis indicate that the monsoon season (June to September) shows reduced TCR magnitudes as compared to annual analyses; however the TCR results during monsoon provides similar spatial distributions as to the results of the annual analysis. The results of TCR monsoon season shows higher TCR values over in Northwest and WCI regions. Furthermore, the study employed the PCMCI causality test to examine the dynamic causal relationships between surface SM and PR over different time lags. The results of the PCMCI test shows strong short-term causal links between SM and PR in South Peninsular India, especially for lags of 1 and 2 days, while showing weaker long-term relationship between SM and PR over Northeast region. The strongest long-term causal relationship between SM and PR is observed in the Northwest India (NWI) region, with a time lag of 24 days. The above is attributed to the fact that the NWI region experiences very little impact from synoptic level weather systems that form over India. Furthermore, additionally, the PCMCI analysis reveals that the long-term causal relationships between SM and PR are significant over WCI and Central Northeast India. The results of this study demonstrate that both the ECA and PCMCI methods are effective in capturing the complex relationships between extreme SM and PR events across the Indian domain, and hence provide for deeper insights into land-atmosphere feedback mechanisms.
      原文链接:
    • NETL
    • NSTL
    • Springer Nature