The unpredictability of crop yield due to severe weather events such as drought and extreme heat continue to be a key worry. The present study evaluated six meteorological and three Landsat satellite-based vegetation drought indices from 1986 to 2019 in the drought-prone-semi-arid Saurashtra region of Gujarat (India). Cotton and groundnut crop yield prediction models were developed using multiple linear regression (multilayer perception (MLP)), artificial neural network with MLP, and random forest (RF). The models performed crop yield estimation at two timescales, i.e., 75 days after sowing and 105 days after sowing. The standardized precipitation evapotranspiration index/reconnaissance drought index among meteorological drought indices, normalized difference vegetation anomaly index/vegetation condition index, and normalized difference water index anomaly were chosen as best highest correlations with crop yields. The RF-based models were found most efficient in predicting the cotton and groundnut yield of Saurashtra with R2 ranging from 0.77 to 0.92, Nash–Sutcliffe efficiency ranging from 71 to 90%, and root-mean-square error ranging from 80 to 133 kg/ha for cotton and 299 to 453 kg/ha for groundnut. This study demonstrated the method for making several decisions based on early crop yield prediction including timely drought mitigation measures.
{"title":"Early crop yield prediction for agricultural drought monitoring using drought indices, remote sensing, and machine learning techniques","authors":"Parthsarthi Pandya, Narendra Kumar Gontia","doi":"10.2166/wcc.2023.386","DOIUrl":"https://doi.org/10.2166/wcc.2023.386","url":null,"abstract":"\u0000 \u0000 The unpredictability of crop yield due to severe weather events such as drought and extreme heat continue to be a key worry. The present study evaluated six meteorological and three Landsat satellite-based vegetation drought indices from 1986 to 2019 in the drought-prone-semi-arid Saurashtra region of Gujarat (India). Cotton and groundnut crop yield prediction models were developed using multiple linear regression (multilayer perception (MLP)), artificial neural network with MLP, and random forest (RF). The models performed crop yield estimation at two timescales, i.e., 75 days after sowing and 105 days after sowing. The standardized precipitation evapotranspiration index/reconnaissance drought index among meteorological drought indices, normalized difference vegetation anomaly index/vegetation condition index, and normalized difference water index anomaly were chosen as best highest correlations with crop yields. The RF-based models were found most efficient in predicting the cotton and groundnut yield of Saurashtra with R2 ranging from 0.77 to 0.92, Nash–Sutcliffe efficiency ranging from 71 to 90%, and root-mean-square error ranging from 80 to 133 kg/ha for cotton and 299 to 453 kg/ha for groundnut. This study demonstrated the method for making several decisions based on early crop yield prediction including timely drought mitigation measures.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":" 15","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138611502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study presents a sediment rating curve (SRC), multiple regression (MR), and long short-term memory (LSTM) model for estimating daily suspended sediment concentration (SSC). The data of daily SSC at Yen Thuong and daily flow at five locations in the Ca River Basin, Vietnam are used to demonstrate multiple approaches. Using the daily flow and SSC data in the period from 2009 to 2019, appropriate coefficients in each method are identified carefully using five popular criteria. The results showed that SRC and MR approaches reproduced acceptably the observed values, with the values of RMSE, MAE, and ME of daily SSC being less than 5% of daily SSC magnitude observed at the station, while NSE ranges from 0.47 to 0.63 and r coefficient varies between 0.69 and 0.80. The LSTM model represented the observed values of daily SSC very well. The values of two dimensionless criteria are greater than 0.94 and its values of three-dimensional criteria are smaller than 2.0% of the observed magnitude of daily SSC in both training and validation steps. The LSTM model is found to be the best among the three investigated approaches. Then, the model is applied to estimate daily SSC values for the period from 1969 to 2008 and the year 2020.
{"title":"Estimation of daily suspended sediment concentration in the Ca River Basin using a sediment rating curve, multiple regression, and long short-term memory model","authors":"Chien Pham Van, Hien T. T. Le, Le Van Chin","doi":"10.2166/wcc.2023.229","DOIUrl":"https://doi.org/10.2166/wcc.2023.229","url":null,"abstract":"\u0000 \u0000 This study presents a sediment rating curve (SRC), multiple regression (MR), and long short-term memory (LSTM) model for estimating daily suspended sediment concentration (SSC). The data of daily SSC at Yen Thuong and daily flow at five locations in the Ca River Basin, Vietnam are used to demonstrate multiple approaches. Using the daily flow and SSC data in the period from 2009 to 2019, appropriate coefficients in each method are identified carefully using five popular criteria. The results showed that SRC and MR approaches reproduced acceptably the observed values, with the values of RMSE, MAE, and ME of daily SSC being less than 5% of daily SSC magnitude observed at the station, while NSE ranges from 0.47 to 0.63 and r coefficient varies between 0.69 and 0.80. The LSTM model represented the observed values of daily SSC very well. The values of two dimensionless criteria are greater than 0.94 and its values of three-dimensional criteria are smaller than 2.0% of the observed magnitude of daily SSC in both training and validation steps. The LSTM model is found to be the best among the three investigated approaches. Then, the model is applied to estimate daily SSC values for the period from 1969 to 2008 and the year 2020.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":" 7","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138617184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract In this research, the impact of climate change in the next 15 years (2036–2022) in the (LarDam) area has been investigated. The results showed that in the case of climate change under scenarios RCP2.6, RCP4.5, RCP8.5, the maximum temperature and the minimum temperature have increased by5, 5.23, 6.2% and 3.5, 5.6, 5.17%, respectively, and the amount of precipitation increased by 8.55, 9.5, 13%, respectively. Also, the highest rainfall will be in 2031 and the lowest will be in 2036. Then, based on the intermediate state of the scenarios, i.e. RCP4.5 scenario, the amount of runoff was obtained and the reliability index was calculated according to the upstream runoff of Lar Dam and downstream needs for drinking, agriculture, and environment. The simulation was also performed in the WEAP model. The obtained reliability showed that the highest reliability was 86.60% of the agriculture needs in the WEAP model, and by using the optimization of a honey badger and harmonic search algorithms, it was found that the reliability is approximately 5.06 and 1.73% higher than the reliability of the simulation, respectively. Moreover, in comparison with the optimization algorithms, due to the smaller value of the objective function of the honey badger algorithm and the greater reliability of this algorithm in optimizing downstream needs, it can be concluded that the performance of this algorithm was better than the harmonic search algorithm. The honey badger algorithm has a faster calculation speed than the harmony search algorithm with less execution time.
{"title":"Simulation and optimization of Lar Dam reservoir storage under climate change conditions","authors":"Hediyeh Sadeghijou, Amirpouya Sarraf, Hassan Ahmadi","doi":"10.2166/wcc.2023.225","DOIUrl":"https://doi.org/10.2166/wcc.2023.225","url":null,"abstract":"Abstract In this research, the impact of climate change in the next 15 years (2036–2022) in the (LarDam) area has been investigated. The results showed that in the case of climate change under scenarios RCP2.6, RCP4.5, RCP8.5, the maximum temperature and the minimum temperature have increased by5, 5.23, 6.2% and 3.5, 5.6, 5.17%, respectively, and the amount of precipitation increased by 8.55, 9.5, 13%, respectively. Also, the highest rainfall will be in 2031 and the lowest will be in 2036. Then, based on the intermediate state of the scenarios, i.e. RCP4.5 scenario, the amount of runoff was obtained and the reliability index was calculated according to the upstream runoff of Lar Dam and downstream needs for drinking, agriculture, and environment. The simulation was also performed in the WEAP model. The obtained reliability showed that the highest reliability was 86.60% of the agriculture needs in the WEAP model, and by using the optimization of a honey badger and harmonic search algorithms, it was found that the reliability is approximately 5.06 and 1.73% higher than the reliability of the simulation, respectively. Moreover, in comparison with the optimization algorithms, due to the smaller value of the objective function of the honey badger algorithm and the greater reliability of this algorithm in optimizing downstream needs, it can be concluded that the performance of this algorithm was better than the harmonic search algorithm. The honey badger algorithm has a faster calculation speed than the harmony search algorithm with less execution time.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":"31 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134991279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rihan Al Saodi, Mustafa Al Kuisi, Ahmed Al Salaymeh
Abstract The objective of this study was to evaluate the sensitivity of flash floods to future climate change in the Amman–Zarqa Basin, Jordan. Historical daily rainfall and temperature data from 1970 to 2018 were collected, along with projected daily data derived from general circulation models (GCMs) forecast spanning 2019–2060. The methodology involved analyzing historical and model forecast data, conducting trend analysis, mapping changes in land use, estimating runoff volume, selecting indicators, assigning their weights through the analytical hierarchy process, and generating vulnerability maps. Analysis of precipitation trends revealed a 14.61% decrease in total annual rainfall over the past 48 years; however, future projections indicate a 5.26% increase. Downstream sub-catchments in the arid portion are projected to receive higher rainfall, while upstream sub-catchments are expected to experience a substantial decline, resulting in an overall reduction in runoff. Moreover, our findings demonstrate a rising trend in mean temperature, which is expected to persist. Remote sensing data indicate a 14.76% expansion of urban areas, indicative of rapid population growth. Although no highly vulnerable sub-catchments were identified, downstream sub-catchments 8 and 9 exhibited moderate vulnerability to flash floods, which can be attributed to the increase in rainfall and insufficient stormwater infrastructure.
{"title":"Assessing the vulnerability of flash floods to climate change in arid zones: Amman–Zarqa Basin, Jordan","authors":"Rihan Al Saodi, Mustafa Al Kuisi, Ahmed Al Salaymeh","doi":"10.2166/wcc.2023.237","DOIUrl":"https://doi.org/10.2166/wcc.2023.237","url":null,"abstract":"Abstract The objective of this study was to evaluate the sensitivity of flash floods to future climate change in the Amman–Zarqa Basin, Jordan. Historical daily rainfall and temperature data from 1970 to 2018 were collected, along with projected daily data derived from general circulation models (GCMs) forecast spanning 2019–2060. The methodology involved analyzing historical and model forecast data, conducting trend analysis, mapping changes in land use, estimating runoff volume, selecting indicators, assigning their weights through the analytical hierarchy process, and generating vulnerability maps. Analysis of precipitation trends revealed a 14.61% decrease in total annual rainfall over the past 48 years; however, future projections indicate a 5.26% increase. Downstream sub-catchments in the arid portion are projected to receive higher rainfall, while upstream sub-catchments are expected to experience a substantial decline, resulting in an overall reduction in runoff. Moreover, our findings demonstrate a rising trend in mean temperature, which is expected to persist. Remote sensing data indicate a 14.76% expansion of urban areas, indicative of rapid population growth. Although no highly vulnerable sub-catchments were identified, downstream sub-catchments 8 and 9 exhibited moderate vulnerability to flash floods, which can be attributed to the increase in rainfall and insufficient stormwater infrastructure.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":"22 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135041806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mamush Tekle Assfaw, Bogale Gebremariam Neka, Elias Gebeyehu Ayele
Abstract In this study, we examined how future climate change will affect streamflow responses in the Kessem watershed. Climate variables from SSP2-4.5 and SSP5-8.5 emission scenarios were extracted from GCMs for the 2040s (2031–2060) and 2070s (2061–2090). The bias-corrected precipitation and temperature were converted into streamflow using a calibrated SWAT model. The simulated output of the future streamflow for the periods 2040s and 2070s was compared with the base period (1992–2020) and presented as percentage changes. During calibration and validation, the SWAT model showed Nash–Sutcliffe efficiency (NSE) values of 0.79 and 0.77, as well as coefficient of determination (R2) values of 0.8 and 0.79, demonstrating its capability of simulating streamflow. The annual mean maximum and minimum temperatures are predicted to increase, with a pronounced increase in the minimum temperature for the mid-term and long-term futures under both emission scenarios. As we approach the end of the century, we see an increase in annual mean rainfall and streamflow under the SSP5-8.5 emission scenario. The increment in annual mean rainfall (streamflow) is expected to be 3% (12.5%) and 23% (48.8%) for the 2040s and 2070s, respectively, under the SSP5-8.5 emission scenario.
{"title":"Modeling the impact of climate change on streamflow responses in the Kessem watershed, Middle Awash sub-basin, Ethiopia","authors":"Mamush Tekle Assfaw, Bogale Gebremariam Neka, Elias Gebeyehu Ayele","doi":"10.2166/wcc.2023.541","DOIUrl":"https://doi.org/10.2166/wcc.2023.541","url":null,"abstract":"Abstract In this study, we examined how future climate change will affect streamflow responses in the Kessem watershed. Climate variables from SSP2-4.5 and SSP5-8.5 emission scenarios were extracted from GCMs for the 2040s (2031–2060) and 2070s (2061–2090). The bias-corrected precipitation and temperature were converted into streamflow using a calibrated SWAT model. The simulated output of the future streamflow for the periods 2040s and 2070s was compared with the base period (1992–2020) and presented as percentage changes. During calibration and validation, the SWAT model showed Nash–Sutcliffe efficiency (NSE) values of 0.79 and 0.77, as well as coefficient of determination (R2) values of 0.8 and 0.79, demonstrating its capability of simulating streamflow. The annual mean maximum and minimum temperatures are predicted to increase, with a pronounced increase in the minimum temperature for the mid-term and long-term futures under both emission scenarios. As we approach the end of the century, we see an increase in annual mean rainfall and streamflow under the SSP5-8.5 emission scenario. The increment in annual mean rainfall (streamflow) is expected to be 3% (12.5%) and 23% (48.8%) for the 2040s and 2070s, respectively, under the SSP5-8.5 emission scenario.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":" 1131","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135185921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract This work investigates the meteorological mechanisms forming a classical frontal system on 26 August 2020 in the northeast and eastern parts of Afghanistan. The weather system caused heavy rainfall and led to severe flash floods. Flooding, affected by torrential rain showers, struck mostly the city of Charikar in Parvan province early in the morning day, while most people were asleep. This caused 150 deaths, and nearly 500 houses were destroyed. This research explores atmospheric processes by examining the National Centers for Environmental Prediction dataset and MERRA Model database. The calculation of the convective available potential energy (CAPE) and Showalter index extracted from the Skew-T log-pressure diagram shows a high value of the CAPE at around 2,632 J/kg and −6.6 for the Showalter index, respectively. This presents a very extreme instability in the study area during the time of the flood. The study reveals that the triggering of this system was mostly by thermodynamical aspects, low-level deep convergence, and local topographical aspects rather than the PV streamer. However, the anomaly climate analysis for different atmospheric elements with a comparison of the climate normal values shows the importance of climate change in the weather system into a stronger frontal activity associated with stronger baroclinicity over the study area.
{"title":"A case study of an extreme flooding episode in Charikar, Eastern Afghanistan","authors":"Farahnaz Fazel-Rastgar, Venkataraman Sivakumar","doi":"10.2166/wcc.2023.462","DOIUrl":"https://doi.org/10.2166/wcc.2023.462","url":null,"abstract":"Abstract This work investigates the meteorological mechanisms forming a classical frontal system on 26 August 2020 in the northeast and eastern parts of Afghanistan. The weather system caused heavy rainfall and led to severe flash floods. Flooding, affected by torrential rain showers, struck mostly the city of Charikar in Parvan province early in the morning day, while most people were asleep. This caused 150 deaths, and nearly 500 houses were destroyed. This research explores atmospheric processes by examining the National Centers for Environmental Prediction dataset and MERRA Model database. The calculation of the convective available potential energy (CAPE) and Showalter index extracted from the Skew-T log-pressure diagram shows a high value of the CAPE at around 2,632 J/kg and −6.6 for the Showalter index, respectively. This presents a very extreme instability in the study area during the time of the flood. The study reveals that the triggering of this system was mostly by thermodynamical aspects, low-level deep convergence, and local topographical aspects rather than the PV streamer. However, the anomaly climate analysis for different atmospheric elements with a comparison of the climate normal values shows the importance of climate change in the weather system into a stronger frontal activity associated with stronger baroclinicity over the study area.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":"12 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135139455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hasan Nazari Mejdar, Ali Moridi, Saeid Najjar-Ghabel
Abstract This study combined hydrological and water quality simulation models with a water resources planning model to project future water supply conditions under the dam construction in the Harirud River, located at the Afghanistan, Turkmenistan, and the Iran border. The sustainability requirements and possible conflicts among riparian countries were assessed under climate change and future development in Afghanistan's upstream. The water quantity and quality of the Doosti Dam Basin on the Harirud River were investigated based on a contemporary time (1955–2015) to predict the future condition (2020–2099). The representative concentration pathway scenarios were applied based on five bias-corrected climate models. Results showed that most areas of the study area experienced an increase in temperature (1.5–3.8°C) and a decrease in precipitation (19–24%). The Doosti Dam inflow decreased by about 70% after the Salma Dam construction, and the reliability and sustainability of agricultural water supply in Iran and Turkmenistan will reduce to less than 3% under the RCP 8.5 climate change scenario. In most scenarios, the eutrophication status of the Doosti Reservoir changed to hypereutrophic during the wet months. The results show that the Doosti Dam is not a reliable source to supply the domestic water demand of Mashhad, the second most important city in Iran.
{"title":"Water quantity–quality assessment in the transboundary river basin under climate change: a case study","authors":"Hasan Nazari Mejdar, Ali Moridi, Saeid Najjar-Ghabel","doi":"10.2166/wcc.2023.421","DOIUrl":"https://doi.org/10.2166/wcc.2023.421","url":null,"abstract":"Abstract This study combined hydrological and water quality simulation models with a water resources planning model to project future water supply conditions under the dam construction in the Harirud River, located at the Afghanistan, Turkmenistan, and the Iran border. The sustainability requirements and possible conflicts among riparian countries were assessed under climate change and future development in Afghanistan's upstream. The water quantity and quality of the Doosti Dam Basin on the Harirud River were investigated based on a contemporary time (1955–2015) to predict the future condition (2020–2099). The representative concentration pathway scenarios were applied based on five bias-corrected climate models. Results showed that most areas of the study area experienced an increase in temperature (1.5–3.8°C) and a decrease in precipitation (19–24%). The Doosti Dam inflow decreased by about 70% after the Salma Dam construction, and the reliability and sustainability of agricultural water supply in Iran and Turkmenistan will reduce to less than 3% under the RCP 8.5 climate change scenario. In most scenarios, the eutrophication status of the Doosti Reservoir changed to hypereutrophic during the wet months. The results show that the Doosti Dam is not a reliable source to supply the domestic water demand of Mashhad, the second most important city in Iran.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":" 28","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135242419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Stephanie Yolan Parker, Kimalie Fabian Parchment, Georgiana Marie Gordon-Strachan
Abstract Water resources, whether exceeding per capita water abundance thresholds or below water scarcity thresholds, are health determinants within small island developing states (SIDS). Thresholds indicate water stress vulnerability in SIDS, however, underestimate the physicality associated with a lack of water. The objectives of this study are to capture the main challenges of consistently meeting water demand in SIDS and to present their intersection with certain diseases or factors associated with specific health conditions like dengue fever, gastrointestinal disorders, dehydration, and malnutrition. This review utilizes archival evidence to categorize the challenges undermining water availability in SIDS with the view that these issues present or exacerbate health outcomes. Seasonal rainfall variations (73%), inadequate distribution infrastructure (64%), saltwater intrusion (61%), contamination (58%), human-induced watershed change (19%), and sea level rise (17%) were identified from 108 country-specific sources as challenges to consistently meeting water demand by 59 SIDS. Any water stress indicator must consider that it is contingent on its human burden. These challenges affect food security through agricultural drought and soil salinization, and the proliferation of vector-borne and sanitation-related diseases across SIDS. This review is the first step in determining the human health burden of water insecurity in SIDS.
{"title":"The burden of water insecurity: a review of the challenges to water resource management and connected health risks associated with water stress in small island developing states","authors":"Stephanie Yolan Parker, Kimalie Fabian Parchment, Georgiana Marie Gordon-Strachan","doi":"10.2166/wcc.2023.239","DOIUrl":"https://doi.org/10.2166/wcc.2023.239","url":null,"abstract":"Abstract Water resources, whether exceeding per capita water abundance thresholds or below water scarcity thresholds, are health determinants within small island developing states (SIDS). Thresholds indicate water stress vulnerability in SIDS, however, underestimate the physicality associated with a lack of water. The objectives of this study are to capture the main challenges of consistently meeting water demand in SIDS and to present their intersection with certain diseases or factors associated with specific health conditions like dengue fever, gastrointestinal disorders, dehydration, and malnutrition. This review utilizes archival evidence to categorize the challenges undermining water availability in SIDS with the view that these issues present or exacerbate health outcomes. Seasonal rainfall variations (73%), inadequate distribution infrastructure (64%), saltwater intrusion (61%), contamination (58%), human-induced watershed change (19%), and sea level rise (17%) were identified from 108 country-specific sources as challenges to consistently meeting water demand by 59 SIDS. Any water stress indicator must consider that it is contingent on its human burden. These challenges affect food security through agricultural drought and soil salinization, and the proliferation of vector-borne and sanitation-related diseases across SIDS. This review is the first step in determining the human health burden of water insecurity in SIDS.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":"87 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135341837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Remote sensing-based data on vegetation conditions provide important information for agriculture. In this study, the potential uses of the freely available High-Resolution Vegetation Phenology and Productivity Product (HR-VPP) are tested. This test examines the 2018 drought year in the state of Saxony, Germany, and the capabilities and limitations of the HR-VPP product in use with Integrated Administration and Control System (IACS) data. The results show that field and crop type-specific spatial (re)analyses of a drought are possible and that there is still great potential in this data analysis. Using the data in a new proposed VPP-based Farm-Level Temporal Comparison Indicator (VPP-FLTCI), it was not possible to tease out patterns in why farms applied for state drought aid in 2018 compared to other farms. In the future, even better and more detailed analyses based on the HR-VPP can be expected, as the data series with now a total of 5 years is still very short to generate sufficient references, especially in Central European agriculture, which is characterized by crop rotation.
{"title":"Determining the usefulness of the Copernicus High-Resolution Vegetation Phenology and Productivity Product (HR-VPP) with official agricultural data on cropland in case of the 2018 drought in the Federal State of Saxony, Germany","authors":"Sebastian Goihl","doi":"10.2166/wcc.2023.501","DOIUrl":"https://doi.org/10.2166/wcc.2023.501","url":null,"abstract":"Abstract Remote sensing-based data on vegetation conditions provide important information for agriculture. In this study, the potential uses of the freely available High-Resolution Vegetation Phenology and Productivity Product (HR-VPP) are tested. This test examines the 2018 drought year in the state of Saxony, Germany, and the capabilities and limitations of the HR-VPP product in use with Integrated Administration and Control System (IACS) data. The results show that field and crop type-specific spatial (re)analyses of a drought are possible and that there is still great potential in this data analysis. Using the data in a new proposed VPP-based Farm-Level Temporal Comparison Indicator (VPP-FLTCI), it was not possible to tease out patterns in why farms applied for state drought aid in 2018 compared to other farms. In the future, even better and more detailed analyses based on the HR-VPP can be expected, as the data series with now a total of 5 years is still very short to generate sufficient references, especially in Central European agriculture, which is characterized by crop rotation.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":"9 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135634500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jessica Penny, Dibesh Khadka, Mukand Babel, Priscila Alves, Slobodan Djordjević, Albert S. Chen, Slobodan Djordjević, Ho Huu Loc
Abstract Projecting flood and drought characteristics under climate change is important to management plans and enhancement of the resiliency of the society. However, studies that provide the integration of flood–drought hazard events is scarce. This study assessed the flood and drought hazards for future climate in the Mun River basin. A non-modelling approach is used to assess the flood hazard, while a multi-variate approach is used for the drought hazard. The results suggest that areas under ‘high’ and ‘very high’ drought hazard levels will increase from 27 and 4% during the baseline period to 43 and 37%, during the near-future period. Similarly, an increase in the ‘high’ and ‘very high’ flood hazard levels from 11 and 22% during the baseline period to 16 and 24% during the near-future period is projected. When both hazards are considered together, the total hazard is projected to increase by 155% in the near-future period. 76% of the catchment during the near-future period will have a combined hazard level from ‘medium’ to ‘very high’ compared to the 30% during the baseline period. The research presents a grim outlook on future floods and droughts in the basin, with the areas of Nakhon Ratchasima, Rio Et and Si Sa Ket provinces particularly at risk from both hydro-meteorological hazards.
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