P. Kumari, Rehana Shaik, Sharath Chandra Vannam, Shailesh Kumar Singh
{"title":"Drought evaluation using various evapotranspiration models over semi-arid river basins","authors":"P. Kumari, Rehana Shaik, Sharath Chandra Vannam, Shailesh Kumar Singh","doi":"10.2166/wcc.2024.699","DOIUrl":"https://doi.org/10.2166/wcc.2024.699","url":null,"abstract":"\u0000 \u0000 Multivariate drought indices including various hydrological processes into account can be more valuable under climatic and anthropogenic changes. Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized precipitation Actual Evapotranspiration Index (SPAEI) are the drought indices used to estimate drought index, considering precipitation, and evapotranspiration (ET) into account. Many studies used empirical, machine learning, and process-based model estimates of ET for the calculation of drought indices of SPEI and SPAEI. However, the sensitivity of ET estimates on drought characteristics at the catchment scale is highly complex. The present study aimed to include and analyze the sensitivity of various approaches of empirical (Budyko, Penman–Monteith, Hargreaves, and Turc), modeled (SWAT), and remote sensing (MODIS) in the drought characterization using SPEI and SPAEI. The present methodology was tested on a dry-sub-humid river catchment of India, the Tunga-Bhadra River catchment for the period of 2000–2012. The performance of statistical indicators (Nash–Sutcliffe Efficiency and R2) for SPEI values by various empirical methods of Potential Evapotranspiration (PET) (i) Penman–Monteith (ii) Hargreaves against remote sensing PET were 0.93 and 0.95, respectively, which are high in comparison with SWAT simulated PET-based SPEI values, which shows NSE values of 0.85 against remote sensing PET-based SPEI.","PeriodicalId":506949,"journal":{"name":"Journal of Water and Climate Change","volume":" 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141673644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Prediction of long-term changes of weak diurnal stratification in shallow lakes using artificial neural networks","authors":"Sebestyén Dániel Török, Péter Torma","doi":"10.2166/wcc.2024.032","DOIUrl":"https://doi.org/10.2166/wcc.2024.032","url":null,"abstract":"\u0000 \u0000 Thermal stratification plays a key role in lakes' ecosystems. In contrast to deep lakes, the thermal structure of shallow polymictic lakes is characterized by a weak stratification with an apparent diurnal cycle. Long-term changes in stratification are governed by climate change and anthropogenic effects such as water level regulation. We developed a simple and robust model system consisting of an energy balance model to estimate depth-averaged water temperatures and an artificial neural network (ANN) model to predict stratification with high temporal resolution. One novelty of our approach is that instead of directly estimating water temperatures at different depths, we simulated the potential energy anomaly index, the indicator of stratification's strength. The ANN-based model's performance was assessed against a physical-based one-dimensional model (General Ocean Turbulence Model) by modeling a 40-year-long period from 1981 to 2020. The new model accurately predicts a shallow lake's weak stratification and its diurnal cycle. Besides, the model proved reliable on longer time scales, capturing the effect of climate change, anthropogenic water level regulation, and their synergistic interaction on the change of stratification's intensity and duration.","PeriodicalId":506949,"journal":{"name":"Journal of Water and Climate Change","volume":" 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141675238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wenxian Guo, Zhiqian Yu, Ning He, Wenxiong Chen, Chaohui Sun, Jiaqi Lan, Yanhua Li, Bing Wang, Hongxiang Wang
{"title":"Quantitative assessment of runoff change and its drivers in a multi-scale framework","authors":"Wenxian Guo, Zhiqian Yu, Ning He, Wenxiong Chen, Chaohui Sun, Jiaqi Lan, Yanhua Li, Bing Wang, Hongxiang Wang","doi":"10.2166/wcc.2024.314","DOIUrl":"https://doi.org/10.2166/wcc.2024.314","url":null,"abstract":"\u0000 \u0000 Identifying runoff changes and quantifying the impacts of climate change and human activities are important for water resources planning and management in river basins. The impacts of climate change and human activities on runoff can be more accurately assessed through scientific hydrological modeling and data analysis methods. In this study, an integrated assessment framework was established to quantitatively separate the driving mechanisms of runoff at different time scales. The results show that the runoff of Wu River has shown a decreasing trend since 2004, with a change degree of 56%, and the monthly average flow indexes of August and September have changed significantly, both of which have reached more than 90%. The NSE coefficient of the SWAT simulation effect is above 0.8, we validate the simulation results based on the LSTM model. It was found that climate change was the main factor affecting the runoff of Wu River, with the contribution rates reaching 60 and 57%, respectively. Pearson correlation analysis found that rainfall was the most important factor affecting the runoff. The results of this study are helpful to formulate effective water resources management policies and measures to ensure the sustainable utilization and management of water resources in the Wu River Basin.","PeriodicalId":506949,"journal":{"name":"Journal of Water and Climate Change","volume":" 20","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141673367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A systematic literature review on adoption and impact of micro-irrigation","authors":"Selva Ganapathi R., Shanthasheela M.","doi":"10.2166/wcc.2024.256","DOIUrl":"https://doi.org/10.2166/wcc.2024.256","url":null,"abstract":"\u0000 \u0000 Water is an indispensable resource, and it is crucial for sustaining human life and agriculture. Nowadays, the share of water for agriculture is also shrinking. In the agricultural sector, micro-irrigation (MI) has emerged as a prominent technology for the efficient utilization of available water. However, understanding the adoption and impact of this technology is essential for its success. While existing studies on MI technologies were often limited to specific locations, this study addressed this gap by analysing 160 documents from the Scopus database through a systematic literature review and bibliometric analysis with thematic clustering. The study examined influential authors and nations, keyword co-occurrences, co-citations, and collaborations among authors and institutions. VOSviewer was utilized for bibliometric analysis. The research trend showed a steady increase in MI studies, with Zaccaria D. being the most productive author and the United States being the most influential country with several publications. Agricultural Water Management emerged as the most impactful journal, with Coelho E.F. being the most cited author. Additionally, three thematic clusters, namely effects of irrigation water, weed growth and crop yield, and irrigation and organic cultivation, were identified and discussed.","PeriodicalId":506949,"journal":{"name":"Journal of Water and Climate Change","volume":" 20","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141675494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Laxmi Gangwani, Nikita Palod, S. Dongre, Rajesh Gupta
{"title":"Optimal pipe-sizing design of water distribution networks using modified Rao-II algorithm","authors":"Laxmi Gangwani, Nikita Palod, S. Dongre, Rajesh Gupta","doi":"10.2166/wcc.2024.055","DOIUrl":"https://doi.org/10.2166/wcc.2024.055","url":null,"abstract":"\u0000 \u0000 Several evolutionary algorithms (EAs) have been suggested in the last three decades for the least-cost design of water distribution networks (WDNs). EAs generally worked well to identify the global/near-global optimal solutions for small to moderate-size networks in a reasonable time and computational effort. However, their applications to large-size networks are still challenging due to large computational efforts. Recent developments in EAs are towards parameter-less techniques that avoid fine-tuning of case-specific parameters to reduce the computational efforts. Further, several self-adaptive penalties and search space reduction methodologies have been suggested to reduce the computational efforts. A fast, efficient, and parameter-less Rao-II algorithm is used earlier with the penalty-based approaches for the optimal design of WDNs. In this study, the application of a Rao-II algorithm is further explored with three self-adaptive penalty approaches to compare the convergence characteristics. The Rao-II algorithm is observed to converge at an infeasible solution in case the applied penalty to an infeasible solution is not substantial to make it inferior to the feasible solutions. Modifications are suggested to improve the Rao-II algorithm and named as modified Rao-II algorithm. The modified Rao-II algorithm with the self-adaptive penalty methods resulted in better solutions than those obtained earlier.","PeriodicalId":506949,"journal":{"name":"Journal of Water and Climate Change","volume":" 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141678392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Shafiq, Zahoor ul Islam, Abida Fayaz, Rashid Mahmood, Pervez Ahmed, A. P. Dimri
{"title":"Spatio-temporal trends and variability in extreme temperature and precipitation indices in the Kashmir Valley, North Western Himalayas","authors":"M. Shafiq, Zahoor ul Islam, Abida Fayaz, Rashid Mahmood, Pervez Ahmed, A. P. Dimri","doi":"10.2166/wcc.2024.141","DOIUrl":"https://doi.org/10.2166/wcc.2024.141","url":null,"abstract":"\u0000 \u0000 Earth's average air temperature is warming at a substantial rate leading to an increase in the frequency and severity of extremes with major environmental and socio-economic impacts. The present study discusses temperature and precipitation extremes in Kashmir Valley using observational data from six meteorological stations. An Expert Team on Climate Change Detection and Indices (ETCCDI) (http://etccdi.pacificclimate.org/) provides 25 extreme climate indices (15 for temperature and 10 for precipitation) to be used. The absolute extreme temperature indices (TXx, TXn, TNx, and TNn) exhibit increasing tendencies, according to the findings. The number of changes witnessed in daily maximum temperature was greater than the daily minimum temperature which was manifested by increasing diurnal temperature range (DTR; 0.012 °C/year). These changes in extremes have impacts that pose a threat to agriculture, snow day and cover, glaciers, water resources, ecosystem services, etc. of the study region. The region is undergoing significant urban and land system changes making it further vulnerable to natural hazards. The findings are expected to further augment the hazard and risk analysis and the necessary disaster risk reduction measures for climate-related disasters in the region. These analyses will be helpful for the development of strategies for climate risk management in Kashmir.","PeriodicalId":506949,"journal":{"name":"Journal of Water and Climate Change","volume":" 40","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141679386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. A. Melo, L. A. Alvarenga, J. Tomasella, Ana Carolina N. Santos
{"title":"Uncertainty analysis on long-term runoff projection from the Budyko framework and a conceptual hydrological model","authors":"P. A. Melo, L. A. Alvarenga, J. Tomasella, Ana Carolina N. Santos","doi":"10.2166/wcc.2024.127","DOIUrl":"https://doi.org/10.2166/wcc.2024.127","url":null,"abstract":"\u0000 \u0000 Runoff projections are subject to uncertainties related to model structure and parameters. This study aims to analyze uncertainties in long-term runoff estimations from an empirical (Budyko framework) and a conceptual hydrological model (MHD-INPE). Results indicate that both MHD-INPE and Budyko estimations tend to overestimate long-term runoff during years of recurring droughts. Pareto front solutions in MHD-INPE exhibited small uncertainties in long-term runoff estimations regarding parameter calibration (bias between 5 and 7%); differences were observed in low (bellow 5% variation) and high (bellow 10% variation) daily runoff. Related to model structure uncertainties, both models follow similar patterns and performance for a qualitative analysis. Budyko's future projections tend to exceed MHD-INPE's during high precipitation estimates, where at 2000 mm yearly precipitation the estimated runoff from Budyko tends to be 100 mm greater than the hydrological model. As opposed, under arid conditions Budyko tends to estimate smaller runoff than MHD-INPE due to variations in soil moisture and water storage not properly represented in Budyko's parameter. Although uncertainties were identified related to model complexity and calibrated parameters, higher uncertainties were identified as related to the climate models. Therefore, the Budyko method is a viable alternative for first-order analysis of long-term impacts.","PeriodicalId":506949,"journal":{"name":"Journal of Water and Climate Change","volume":"228 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141681384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gilbert Chumo Maiyo, P. Ndiba, P. M. Odira, Ezekiel Nyangeri
{"title":"Evaluation of sediment generation and transport: a case study of Thwake Dam in Kenya","authors":"Gilbert Chumo Maiyo, P. Ndiba, P. M. Odira, Ezekiel Nyangeri","doi":"10.2166/wcc.2024.040","DOIUrl":"https://doi.org/10.2166/wcc.2024.040","url":null,"abstract":"\u0000 The study aimed to evaluate sediment generation, transport, and deposition into the Thwake reservoir. This research sought to assess sediment transport patterns and their potential impact on the reservoir using regional and numerical techniques. The Thwake River basin constitutes 30% of the dam's catchment area and experiences high soil loss due to its semi-arid climate, steep slopes, and lack of vegetation. The river system in the sub-basin is ephemeral, with the riverbed remaining dry throughout most of the year and experiencing tidal flow only during storm events. Bed material samples were collected from selected reaches, and sediment properties were evaluated. The study involved analyzing datasets on the reservoir, catchment, and sand-bed channel. Numerical models assessed hydrological and sediment transport information by considering interacting variables and predicting deposition patterns and sediment yield estimates. The findings indicated that sufficient bed material from sub-basin 3E would be deposited into the reservoir, resulting in delta formation approximately 5 km downstream of the tail waters at minimum dam operating level. The mass cumulative sediment inflow from 3E into the reservoir was estimated between 14 and 26.3 metric tons per annum, representing reservoir loss and useful life under 50 years.","PeriodicalId":506949,"journal":{"name":"Journal of Water and Climate Change","volume":"14 s1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141688083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Impact of climate change on water scarcity in Pakistan. Implications for water management and policy","authors":"Baocheng He, Amir Jamil, Mihad Bellaoulah, Ayesha Mukhtar, Nouayou Kamdoum Clauvis","doi":"10.2166/wcc.2024.710","DOIUrl":"https://doi.org/10.2166/wcc.2024.710","url":null,"abstract":"\u0000 Water resources in Pakistan are under serious threat from climate change (CC), exacerbating water scarcity. The implications for water policy and management are far-reaching. Pakistan relies heavily on the Indus Basin Irrigation System (IBIS) for agricultural production and water supply, but the distribution and availability of water resources are threatened by changing climatic patterns, such as changing precipitation and melting glaciers. Water scarcity is heightened by faster glacial melt and erratic precipitation patterns, which affect the timing and quantity of water flow. Effective water management techniques, such as increased effectiveness, sustainable practices, and conservation measures, as well as robust infrastructure and governance are required to address these issues. Pakistan can benefit greatly from international cooperation and assistance to mitigate the impacts of CC and ensure water security for long-term development.","PeriodicalId":506949,"journal":{"name":"Journal of Water and Climate Change","volume":"23 3‐4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141686863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pacifique Batungwanayo, M. Vanclooster, Alice Alonso, Alan Koropitan
{"title":"Wavelet-based analysis of hydro-climatic and vegetation dynamics in heterogeneous agro-climatic zones (East Africa)","authors":"Pacifique Batungwanayo, M. Vanclooster, Alice Alonso, Alan Koropitan","doi":"10.2166/wcc.2024.257","DOIUrl":"https://doi.org/10.2166/wcc.2024.257","url":null,"abstract":"\u0000 \u0000 Natural and human-induced factors profoundly affect agricultural crop production in East Africa, sparking ongoing debates about their relative significance. This study investigates the impact of localized hydro-climatic variables like precipitation, temperature, vapor pressure deficit, and water deficit on crop production. Additionally, it examines climate oscillations such as ENSO, IOD, NAO, and PDO. Employing the NDVI metric, the analysis focuses on four climatic zones, ranging from arid to humid. Results indicate dominant annual (8–16 months) and intra-annual (4–8 months) periodicities for NDVI and hydro-climatic factors, contrasting with inter-annual and inter-decadal oscillations in circulation indices. Vegetation dynamics prove more sensitive to annual and intra-annual fluctuations in hydro-climatic factors than to circulation index oscillations. Bivariate wavelet coherence analysis highlights precipitation and ENSO as significant factors in vegetation variability. Incorporating additional variables enhances coherence strength, improving understanding of regional hydro-climatic processes affecting vegetation. This research underscores the importance of wavelet techniques in deciphering complex relationships between hydro-climatic factors and crop production, with implications for agricultural management and policy in East Africa.","PeriodicalId":506949,"journal":{"name":"Journal of Water and Climate Change","volume":"1977 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141707312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}