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Widespread urban expansion around the world, combined with rapid demographic and climatic changes, has resulted in serious pollution issues in many coastal water bodies. To help formulate coastal management strategies to mitigate the impacts of these extreme changes (e.g., local land-use or climate change adaptation policies), research methodologies that incorporate participatory approaches alongside with computer simulation modeling tools have potential to be particularly effective. One such research methodology, called the “Participatory Coastal Land-Use Management” (PCLM) approach, consists of three major steps: (a) participatory approach to find key drivers responsible for the water quality deterioration, (b) scenario analysis using different computer simulation modeling tools for impact assessment, and (c) using these scientific evidences for developing adaptation and mitigation measures. In this study, we have applied PCLM approach in the Kendrapara district of India (focusing on the Brahmani River basin), a rapidly urbanizing area on the country’s east coast to evaluate current status and predict its future conditions. The participatory approach involved key informant interviews to determine key drivers of water quality degradation, which served as an input for scenario analysis and hydrological simulation in the next step. Future river water quality (BOD and Total coliform (Tot. coli) as important parameters) was simulated using the Water Evaluation and Planning (WEAP) tool, considering a different plausible future scenario (to 2050) incorporating diverse drivers and pressures (i.e., population growth, land-use change, and climate change). Water samples (collected in 2018) indicated that the Brahmani River in this district was already moderately-to-extremely polluted in comparison to the desirable water quality (Class B), and modeling results indicated that the river water quality is likely to further deteriorate by 2050 under all of the considered scenarios. Demographic changes emerged as the major driver affecting the future water quality deterioration (68% and 69% for BOD and Tot. coli respectively), whereas climate change had the lowest impact on river water quality (12% and 13% for BOD and Tot. coli respectively), although the impact was not negligible. Scientific evidence to understand the impacts of future changes can help in developing diverse plausible coastal zone management approaches for ensuring sustainable management of water resources in the region. The PCLM approach, by having active stakeholder involvement, can help in co-generation of the coastal management options followed by open access free software, and models can play a relevant cost-effective approach to enhance science-policy interface for conservation of natural resources.
Pankaj Kumar; Rajarshi Dasgupta; Shalini Dhyani; Rakesh Kadaverugu; Brian Johnson; Shizuka Hashimoto; Netrananda Sahu; Ram Avtar; Osamu Saito; Shamik Chakraborty; Binaya Mishra. Scenario-Based Hydrological Modeling for Designing Climate-Resilient Coastal Water Resource Management Measures: Lessons from Brahmani River, Odisha, Eastern India. Sustainability 2021, 13, 6339 .
AMA StylePankaj Kumar, Rajarshi Dasgupta, Shalini Dhyani, Rakesh Kadaverugu, Brian Johnson, Shizuka Hashimoto, Netrananda Sahu, Ram Avtar, Osamu Saito, Shamik Chakraborty, Binaya Mishra. Scenario-Based Hydrological Modeling for Designing Climate-Resilient Coastal Water Resource Management Measures: Lessons from Brahmani River, Odisha, Eastern India. Sustainability. 2021; 13 (11):6339.
Chicago/Turabian StylePankaj Kumar; Rajarshi Dasgupta; Shalini Dhyani; Rakesh Kadaverugu; Brian Johnson; Shizuka Hashimoto; Netrananda Sahu; Ram Avtar; Osamu Saito; Shamik Chakraborty; Binaya Mishra. 2021. "Scenario-Based Hydrological Modeling for Designing Climate-Resilient Coastal Water Resource Management Measures: Lessons from Brahmani River, Odisha, Eastern India." Sustainability 13, no. 11: 6339.
Indian monsoon rainfall has a very strong connection with the Indian economy. Any variation in trend or pattern of Indian summer monsoon rainfall will have serious implications on agronomy, water resources and various associated sectors of the economy in India. In this study, an in-depth investigation of the monsoon rainfall trend is analyzed for 146 years period (1871–2016). Three different spatial scales using a multimethod approach consisting of the Linear Regression Model (LRM), Mann Kendall Test (MKT) and Innovative Trend Analysis (ITA) are analyzed in particular and synchronized way. Monotonic trend with one or the other tests are found in Meteorological Sub-division (MetSD) 3, 4, 14, 11, 10, 19, 20, 27, 8, 29, 28, 23 and 32 (Assam, Meghalaya, Manipur, Mizoram, Nagaland, Tripura, Punjab, Uttar Pradesh, Madhya Pradesh, Chhattisgarh, Jharkhand, Andhra Pradesh, Telangana , Konkan & Goa and Coastal Karnataka). Whereas, no significant monotonic trend was found for India as a unit. Two Homogenous Monsoon Regions (HMR) i.e. Central Northeast and Northeast have the monotonic rainfall trend. Moreover, the synchronized methodology made it possible to identify the most refined significant monotonic trend. It revealed a decreasing monotonic trend in MetSD 4, 20 and 27 (Manipur, Mizoram, Nagaland, Tripura, East Madhya Pradesh and Chhattisgarh) only. ITA based results revealed that MetSD 14, 8, 19 and 29 (Punjab, Jharkhand, West Madhya Pradesh and Telangana) are a new addition to the list of MetSDs with the significant monotonic trend. Changepoint in the trend is obtained for Northeast HMR in the year 1956 and MetSD 4, 20, 23 and 27 in the year 1969, 1961, 1930 and 1961 respectively. This study provides insight into the most refined trend on monsoon rainfall at different spatial scales in India using the updated methods of analysis.
Atul Saini; Netrananda Sahu. Decoding trend of Indian summer monsoon rainfall using multimethod approach. Stochastic Environmental Research and Risk Assessment 2021, 1 -21.
AMA StyleAtul Saini, Netrananda Sahu. Decoding trend of Indian summer monsoon rainfall using multimethod approach. Stochastic Environmental Research and Risk Assessment. 2021; ():1-21.
Chicago/Turabian StyleAtul Saini; Netrananda Sahu. 2021. "Decoding trend of Indian summer monsoon rainfall using multimethod approach." Stochastic Environmental Research and Risk Assessment , no. : 1-21.
Corroboration of El Niño and Southern Oscillation (ENSO) events on the climatic variability in the Indian subcontinent is mentioned in various studies. In the Indian context, if we observe the rising number of dengue cases, it could be treated as a major cause of health concern for the government of this country. Nowadays, an increasing number of dengue incidences are reported from different Indian states which are leading to unfortunate hospitalization and fatal death of the people. Keeping the context in mind, we have examined the relationship between the ENSO events, inter-annual variability in dengue cases in major states of India and Indian summer monsoonal rainfall (ISMR). In this study, we use Pearson’s product-moment correlation (hereafter PPMC) to find out the interconnections between ‘+ winter ONI’ (OND, NDJ, DJF, and JFM seasons) events, rainfall index for the JJAS season (June, July, August, September) and annual 10 major state-level data of dengue cases index for the past 14 years. It has been observed through the study that the PPMC result between the ‘rainfall index’ and ‘dengue index’ is showing greater variation among different states of the country. Interestingly, we have observed that the correlation result between the ‘+ winter ONI’ and dengue incidence index have (r) value ranging from highly (−) to very high (+) value −0.53 to + 0.83 across the different states.
Netrananda Sahu; Martand Mani Mishra. Association and Effects of ISMR and El Niño Southern Oscillation on Dengue Outbreaks in India. COVID-19 Pandemic Trajectory in the Developing World 2021, 157 -166.
AMA StyleNetrananda Sahu, Martand Mani Mishra. Association and Effects of ISMR and El Niño Southern Oscillation on Dengue Outbreaks in India. COVID-19 Pandemic Trajectory in the Developing World. 2021; ():157-166.
Chicago/Turabian StyleNetrananda Sahu; Martand Mani Mishra. 2021. "Association and Effects of ISMR and El Niño Southern Oscillation on Dengue Outbreaks in India." COVID-19 Pandemic Trajectory in the Developing World , no. : 157-166.
Climate change is affecting human health worldwide. In particular, changes to local and global climate parameters influence vector and water-borne diseases like malaria, dengue fever, and tick-borne encephalitis. The Republic of Sakha in northern Russia is no exception. Long-term trends of increasing annual temperatures and thawing permafrost have corresponded with the northward range expansion of tick-species in the Republic. Indigenous communities living in these remote areas may be severely affected by human and livestock diseases introduced by disease vectors like ticks. To better understand the risk of vector-borne diseases in Sakha, we aimed to describe the increase and spatial spread of tick-bite cases in the Republic. Between 2000 and 2018, the frequency of tick bite cases increased 40-fold. At the start of the period, only isolated cases were reported in southern districts, but by 2018, tick bites had been reported in 21 districts in the Republic. This trend coincides with a noticeable increase in the average annual temperature in the region since the 2000s by an average of 1 °C. Maps illustrate the northward spread of tick-bite cases. A negative binomial regression model was used to correlate the increase in cases with a number of climate parameters. Tick bite case frequency per district was significantly explained by average annual temperature, average temperature in the coldest month of the year, the observation year, as well as Selyaninov’s hydrothermal coefficient. These findings contribute to the growing literature that describe the relationship between tick abundance and spread in Northern Latitudes and changes in temperatures and moisture. Future studies might use these and similar results to map and identify areas at risk of infestation by ticks, as climates continue to change in Sakha.
Leonid Vladimirov; Grigory Machakhtyrov; Varvara Machakhtyrova; Albertus Louw; Netrananda Sahu; Ali Yunus; Ram Avtar. Quantifying the Northward Spread of Ticks (Ixodida) as Climate Warms in Northern Russia. Atmosphere 2021, 12, 233 .
AMA StyleLeonid Vladimirov, Grigory Machakhtyrov, Varvara Machakhtyrova, Albertus Louw, Netrananda Sahu, Ali Yunus, Ram Avtar. Quantifying the Northward Spread of Ticks (Ixodida) as Climate Warms in Northern Russia. Atmosphere. 2021; 12 (2):233.
Chicago/Turabian StyleLeonid Vladimirov; Grigory Machakhtyrov; Varvara Machakhtyrova; Albertus Louw; Netrananda Sahu; Ali Yunus; Ram Avtar. 2021. "Quantifying the Northward Spread of Ticks (Ixodida) as Climate Warms in Northern Russia." Atmosphere 12, no. 2: 233.
Remote sensing technology has seen a massive rise in popularity over the last two decades, becoming an integral part of our lives. Space-based satellite technologies facilitated access to the inaccessible terrains, helped humanitarian teams, support complex emergencies, and contributed to monitoring and verifying conflict zones. The scoping phase of this review investigated the utility of the role of remote sensing application to complement international peace and security activities owing to their ability to provide objective near real-time insights at the ground level. The first part of this review looks into the major research concepts and implementation of remote sensing-based techniques for international peace and security applications and presented a meta-analysis on how advanced sensor capabilities can support various aspects of peace and security. With key examples, we demonstrated how this technology assemblage enacts multiple versions of peace and security: for refugee relief operations, in armed conflicts monitoring, tracking acts of genocide, providing evidence in courts of law, and assessing contravention in human rights. The second part of this review anticipates future challenges that can hinder the applicative capabilities of remote sensing in peace and security. Varying types of sensors pose discrepancies in image classifications and issues like cost, resolution, and difficulty of ground-truth in conflict areas. With emerging technologies and sufficient secondary resources available, remote sensing plays a vital operational tool in conflict-affected areas by supporting an extensive diversity in public policy actions for peacekeeping processes.
Ram Avtar; Asma Kouser; Ashwani Kumar; Deepak Singh; Prakhar Misra; Ankita Gupta; Ali Yunus; Pankaj Kumar; Brian Johnson; Rajarshi Dasgupta; Netrananda Sahu; Andi Besse Rimba. Remote Sensing for International Peace and Security: Its Role and Implications. Remote Sensing 2021, 13, 439 .
AMA StyleRam Avtar, Asma Kouser, Ashwani Kumar, Deepak Singh, Prakhar Misra, Ankita Gupta, Ali Yunus, Pankaj Kumar, Brian Johnson, Rajarshi Dasgupta, Netrananda Sahu, Andi Besse Rimba. Remote Sensing for International Peace and Security: Its Role and Implications. Remote Sensing. 2021; 13 (3):439.
Chicago/Turabian StyleRam Avtar; Asma Kouser; Ashwani Kumar; Deepak Singh; Prakhar Misra; Ankita Gupta; Ali Yunus; Pankaj Kumar; Brian Johnson; Rajarshi Dasgupta; Netrananda Sahu; Andi Besse Rimba. 2021. "Remote Sensing for International Peace and Security: Its Role and Implications." Remote Sensing 13, no. 3: 439.
Considering the well-documented impacts of land-use change on water resources and the rapid land-use conversions occurring throughout Africa, in this study, we conducted a spatiotemporal analysis of surface water quality and its relation with the land use and land cover (LULC) pattern in Mokopane, Limpopo province of South Africa. Various physico-chemical parameters were analyzed for surface water samples collected from five sampling locations from 2016 to 2020. Time-series analysis of key surface water quality parameters was performed to identify the essential hydrological processes governing water quality. The analyzed water quality data were also used to calculate the heavy metal pollution index (HPI), heavy metal evaluation index (HEI) and weighted water quality index (WQI). Also, the spatial trend of water quality is compared with LULC changes from 2015 to 2020. Results revealed that the concentration of most of the physico-chemical parameters in the water samples was beyond the World Health Organization (WHO) adopted permissible limit, except for a few parameters in some locations. Based on the calculated values of HPI and HEI, water quality samples were categorized as low to moderately polluted water bodies, whereas all water samples fell under the poor category (>100) and beyond based on the calculated WQI. Looking precisely at the water quality’s temporal trend, it is found that most of the sampling shows a deteriorating trend from 2016 to 2019. However, the year 2020 shows a slightly improving trend on water quality, which can be justified by lowering human activities during the lockdown period imposed by COVID-19. Land use has a significant relationship with surface water quality, and it was evident that built-up land had a more significant negative impact on water quality than the other land use classes. Both natural processes (rock weathering) and anthropogenic activities (wastewater discharge, industrial activities etc.) were found to be playing a vital role in water quality evolution. This study suggests that continuous assessment and monitoring of the spatial and temporal variability of water quality in Limpopo is important to control pollution and health safety in the future.
Mmasabata Molekoa; Ram Avtar; Pankaj Kumar; Huynh Thu Minh; Rajarshi Dasgupta; Brian Johnson; Netrananda Sahu; Ram Verma; Ali Yunus. Spatio-Temporal Analysis of Surface Water Quality in Mokopane Area, Limpopo, South Africa. Water 2021, 13, 220 .
AMA StyleMmasabata Molekoa, Ram Avtar, Pankaj Kumar, Huynh Thu Minh, Rajarshi Dasgupta, Brian Johnson, Netrananda Sahu, Ram Verma, Ali Yunus. Spatio-Temporal Analysis of Surface Water Quality in Mokopane Area, Limpopo, South Africa. Water. 2021; 13 (2):220.
Chicago/Turabian StyleMmasabata Molekoa; Ram Avtar; Pankaj Kumar; Huynh Thu Minh; Rajarshi Dasgupta; Brian Johnson; Netrananda Sahu; Ram Verma; Ali Yunus. 2021. "Spatio-Temporal Analysis of Surface Water Quality in Mokopane Area, Limpopo, South Africa." Water 13, no. 2: 220.
In this paper, the rainfall trend of the West Coast Plain and Hill Agro-Climatic Region is analyzed for 117 years (1901–2017). This region is a globally recognized biodiversity hotspot and known for one of the highest rainfall receiving regions in India. Rainfall grid dataset is used for the analysis of rainfall trends on monthly, seasonal, and decadal time scales. Modified Mann–Kendall’s test, Linear Regression, Innovative Trend Analysis, Sen’s Slope test, Weibull’s Recurrence Interval, Pearson’s Coefficient of Skewness, Consecutive Disparity Index, Kurtosis, and some other important statistical techniques are employed for trend analysis. Results indicate that the rainfall trend is significant in January, July, August, September as well as the Winter season. Among all the significant trends, January and July showed a decreasing rainfall trend. July has the highest contribution (30%) among all the obtained monotonic trend to annual rainfall and coincidentally has the highest trend magnitude. August and September months with a combined contribution of 30% to annual rainfall, show an increasing monotonic trend with high magnitude whereas Winter season shows a monotonic decreasing rainfall trend with comparatively low magnitudes. Decadal analysis along with the study of recurrence interval of excess and deficit years helps to understand the decadal rhythm of trend and the magnitude of extreme monthly and seasonal events. Skewness reveals that rainfall dataset of all the periodic results is right-skewed and the recurrence interval also supports the skewness results. Sharply decreasing rainfall in July and rising rainfall in August and September is predictive of the impact on agriculture, biodiversity and indicates the rainfall regime shift in the region.
Atul Saini; Netrananda Sahu; Pankaj Kumar; Sridhara Nayak; Weili Duan; Ram Avtar; Swadhin Behera. Advanced Rainfall Trend Analysis of 117 Years over West Coast Plain and Hill Agro-Climatic Region of India. Atmosphere 2020, 11, 1225 .
AMA StyleAtul Saini, Netrananda Sahu, Pankaj Kumar, Sridhara Nayak, Weili Duan, Ram Avtar, Swadhin Behera. Advanced Rainfall Trend Analysis of 117 Years over West Coast Plain and Hill Agro-Climatic Region of India. Atmosphere. 2020; 11 (11):1225.
Chicago/Turabian StyleAtul Saini; Netrananda Sahu; Pankaj Kumar; Sridhara Nayak; Weili Duan; Ram Avtar; Swadhin Behera. 2020. "Advanced Rainfall Trend Analysis of 117 Years over West Coast Plain and Hill Agro-Climatic Region of India." Atmosphere 11, no. 11: 1225.
The Himalayas have become synonymous with the hydropower developments for larger electricity demands of India’s energy sector. In the Himachal Himalayas though, there are only three large storage dams with more than 1000 megawatts (hereafter MW) capacity that have very serious environmental issues. However, hundreds of small runoff-river hydropower plants across the Himachal Himalayas are a serious threat to the river regimes and Himalayan biota. There are 965 identified hydropower projects (hereafter HPPs) having a potential capacity of 27,436 MW in the Himachal Pradesh as of December 2019 as per the Directorate of Energy of the state. Out of the 965 identified, 216 are commissioned, including less than 5 MW plants, with an installed capacity of 10,596 MW, and were operational by December 2019. Only 58 projects are under construction among the identified with an installed capacity of 2351 MW, 640 projects are in various stages of clearance and investigation with an installed capacity 9260 MW, 30 projects are to be allotted with 1304 MW installed capacity, and merely four projects are disputed/canceled with installed capacity of 50.50 MW. The large number of HPPs are sanctioned without proper consideration of negative environmental and geohazard impacts on the Himalayan terrestrial biota. In this work, our focus was on the hydropower and climate change impact on the Himalayan river regimes of the Chenab, the Ravi, the Beas, the Satluj, and the Yamuna river basins. We analyzed basin-wise rainfall, temperature, and soil moisture data from 1955 to 2019 to see the trend by applying the Mann–Kendall test, the linear regression model, and Sen’s slope test. A basin-wise hazard zonation map has been drawn to assess the disaster vulnerability, and 12 hydropower sites have been covered through the primary survey for first-hand information of local perceptions and responses owing to hydropower plants.
Netrananda Sahu; Takahiro Sayama; Atul Saini; Arpita Panda; Kaoru Takara. Understanding the Hydropower and Potential Climate Change Impact on the Himalayan River Regimes—A Study of Local Perceptions and Responses from Himachal Pradesh, India. Water 2020, 12, 2739 .
AMA StyleNetrananda Sahu, Takahiro Sayama, Atul Saini, Arpita Panda, Kaoru Takara. Understanding the Hydropower and Potential Climate Change Impact on the Himalayan River Regimes—A Study of Local Perceptions and Responses from Himachal Pradesh, India. Water. 2020; 12 (10):2739.
Chicago/Turabian StyleNetrananda Sahu; Takahiro Sayama; Atul Saini; Arpita Panda; Kaoru Takara. 2020. "Understanding the Hydropower and Potential Climate Change Impact on the Himalayan River Regimes—A Study of Local Perceptions and Responses from Himachal Pradesh, India." Water 12, no. 10: 2739.
The novel coronavirus pandemic (COVID-19) has brought countries around the world to a standstill in the early part of 2020. Several nations and territories around the world insisted their population stay indoors for practicing social distance in order to avoid infecting the disease. Consequently, industrial activities, businesses, and all modes of traveling have halted. On the other hand, the pollution level decreased ‘temporarily’ in our living environment. As fewer pollutants are supplied in to the hydrosphere, and human recreational activities are stopped completely during the lockdown period, we hypothesize that the hydrological residence time (HRT) has increased in the semi-enclosed or closed lake bodies, which can in turn increase the primary productivity. To validate our hypothesis, and to understand the effect of lockdown on primary productivity in aquatic systems, we quantitatively estimated the chlorophyll-a (Chl-a) concentrations in different lake bodies using established Chl-a retrieval algorithm. The Chl-a monitored using Landsat-8 and Sentinel-2 sensor in the lake bodies of Wuhan, China, showed an elevated concentration of Chl-a. In contrast, no significant changes in Chl-a are observed for Vembanad Lake in India. Further analysis of different geo-environments is necessary to validate the hypothesis.
Ram Avtar; Pankaj Kumar; Hitesh Supe; Dou Jie; Netranada Sahu; Binaya Kumar Mishra; Ali P. Yunus. Did the COVID-19 Lockdown-Induced Hydrological Residence Time Intensify the Primary Productivity in Lakes? Observational Results Based on Satellite Remote Sensing. Water 2020, 12, 2573 .
AMA StyleRam Avtar, Pankaj Kumar, Hitesh Supe, Dou Jie, Netranada Sahu, Binaya Kumar Mishra, Ali P. Yunus. Did the COVID-19 Lockdown-Induced Hydrological Residence Time Intensify the Primary Productivity in Lakes? Observational Results Based on Satellite Remote Sensing. Water. 2020; 12 (9):2573.
Chicago/Turabian StyleRam Avtar; Pankaj Kumar; Hitesh Supe; Dou Jie; Netranada Sahu; Binaya Kumar Mishra; Ali P. Yunus. 2020. "Did the COVID-19 Lockdown-Induced Hydrological Residence Time Intensify the Primary Productivity in Lakes? Observational Results Based on Satellite Remote Sensing." Water 12, no. 9: 2573.
The impact of Indo-Pacific climate variability in the South Asian region is very pronounced and their impact on agriculture is very important for the Indian subcontinent. In this study, rice productivity, climatic factors (Rainfall, Temperature and Soil Moisture) and associated major Indo-Pacific climate indices in Bihar were investigated. Bihar is one of the major rice-producing states of India and the role of climate variability and prevailing climate indices in six events (between 1991–2014) with severer than −10% rice productivity are analyzed. The Five-year moving average, Pearson’s Product Moment Correlation, Partial Correlation, Linear Regression Model, Mann Kendall Test, Sen’s Slope and some other important statistical techniques were used to understand the association between climatic variables and rice productivity. Pearson’s Product Moment Correlation provided an overview of the significant correlation between climate indices and rice productivity. Whereas, Partial Correlation provided the most refined results on it and among all the climate indices, Niño 3, Ocean Niño Index and Southern Oscillation Index are found highly associated with years having severer than −10% decline in rice productivity. Rainfall, temperature and soil moisture anomalies are analyzed to observe the importance of climate factors in rice productivity. Along with the lack of rainfall, lack of soil moisture and persistent above normal temperature (especially maximum temperature) are found to be the important factors in cases of severe loss in rice productivity. Observation of the dynamics of ocean-atmosphere coupling through the composite map shows the Pacific warming signals during the event years. The analysis revealed a negative (positive) correlation of rice productivity with the Niño 3 and Ocean Niño Index (Southern Oscillation Index).
Netrananda Sahu; Atul Saini; Swadhin Behera; Takahiro Sayama; Sridhara Nayak; Limonlisa Sahu; Weili Duan; Ram Avtar; Masafumi Yamada; R. Singh; Kaoru Takara. Impact of Indo-Pacific Climate Variability on Rice Productivity in Bihar, India. Sustainability 2020, 12, 7023 .
AMA StyleNetrananda Sahu, Atul Saini, Swadhin Behera, Takahiro Sayama, Sridhara Nayak, Limonlisa Sahu, Weili Duan, Ram Avtar, Masafumi Yamada, R. Singh, Kaoru Takara. Impact of Indo-Pacific Climate Variability on Rice Productivity in Bihar, India. Sustainability. 2020; 12 (17):7023.
Chicago/Turabian StyleNetrananda Sahu; Atul Saini; Swadhin Behera; Takahiro Sayama; Sridhara Nayak; Limonlisa Sahu; Weili Duan; Ram Avtar; Masafumi Yamada; R. Singh; Kaoru Takara. 2020. "Impact of Indo-Pacific Climate Variability on Rice Productivity in Bihar, India." Sustainability 12, no. 17: 7023.
Apple cultivation is one of the most important sources of livelihood in Indian side of the Himalayas. The present study focuses on the apple orchards of Himachal Pradesh, a state within the Himalayan Mountains, a major apple producers of India. In the study, it is found that the optimum apple growing conditions in the region have been consistently shifting and farmers are shifting their orchards to the higher altitudes. For example, orchards have shifted to 1500–2500 meters in the 2000s compared to the cultivated elevation of 1200–1500 meters during 1980s. As of 2014, apples are being cultivated at an elevation of more than 3500 meters, for example, the newly developed orchards of Leo village in upper Kinnaur and Keylong area of Lahul and Spiti districts. Chilling hours for different districts are calculated. The trend of temperature during the growth period, winter session and annual rainfall have been analysed using Mann-Kendall and Sen’s slope test. Data catalogued from different time periods indicates that the northward shift (towards higher altitude) is due to changes in chilling hours, total annual rainfall and mean surface temperature during the apple growing season. The mean surface temperature in all the districts has increased by almost 0.5°C during last 2000–2014. These changes are directly related to global warming. While the changing climate is reducing the apple production in low altitudinal regions of the state, it is creating new opportunities for apple cultivation in higher altitudes as conditions are getting more favourable for apple growth in those higher regions. The associated socio-economic changes are posing new societal issues for the local farmers.
Netrananda Sahu; Atul Saini; Swadhin K. Behera; Takahiro Sayama; Limonlisa Sahu; Van-Thanh-Van Nguyen; Kaoru Takara. Why apple orchards are shifting to the higher altitudes of the Himalayas? PLOS ONE 2020, 15, e0235041 .
AMA StyleNetrananda Sahu, Atul Saini, Swadhin K. Behera, Takahiro Sayama, Limonlisa Sahu, Van-Thanh-Van Nguyen, Kaoru Takara. Why apple orchards are shifting to the higher altitudes of the Himalayas? PLOS ONE. 2020; 15 (7):e0235041.
Chicago/Turabian StyleNetrananda Sahu; Atul Saini; Swadhin K. Behera; Takahiro Sayama; Limonlisa Sahu; Van-Thanh-Van Nguyen; Kaoru Takara. 2020. "Why apple orchards are shifting to the higher altitudes of the Himalayas?" PLOS ONE 15, no. 7: e0235041.
The potential impact of climate variability on the hydrological regime in the Mahanadi river basin is of great importance for sustainable water resources management. The impact of climate variability on streamflow is analyzed in this study. The impact of climate variability modes on extreme events of Mahanadi basin during June, July, and August (JJA), and September, October, and November (SON) seasons were analyzed, with daily streamflow data of four gauge stations for 34 years from 1980 to 2013 found to be associated with the sea surface temperature variations over Indo-Pacific oceans and Indian monsoon. Extreme events are identified based on their persistent flow for six days or more, where selection of the stations was based on the fact that there was no artificially regulated streamflow in any of the stations. Adequate scientific analysis was done to link the streamflow variability with the climate variability and very significant correlation was found with Indian Ocean Dipole (IOD), El Nino Southern Oscillation (ENSO), El Nino Modoki Index (EMI), and Indian monsoon. Agriculture covers major portion of the basin; hence, the streamflow is very much essential for agriculture as well as population depending on it. Any disturbances in the general flow of the river has subjected an adverse impact on the inhabitants’ livelihood. While analyzing the correlation values, it was found that all stations displayed a significant positive correlation with Indian Monsoon. The respective correlation values were 0.53, 0.38, 0.44, and 0.38 for Andhiyarkore, Baronda, Rajim, and Kesinga during JJA season. Again in the case of stepwise regression analysis, Monsoon Index for the June, July, and August (MI-JJA) season (0.537 for Andhiyarkore) plays significant role in determining streamflow of Mahanadi basin during the JJA season and Monsoon Index for July, August, and September (MI-JAS) season (0.410 for Baronda) has a strong effect in affecting streamflow of Mahanadi during the SON season. Flood frequency analysis with Weibull’s plotting position method indicates future floods in the Mahanadi river basin in JJA season.
Netrananda Sahu; Arpita Panda; Sridhara Nayak; Atul Saini; Manoranjan Mishra; Takahiro Sayama; Limonlisa Sahu; Weili Duan; Ram Avtar; Swadhin Behera. Impact of Indo-Pacific Climate Variability on High Streamflow Events in Mahanadi River Basin, India. Water 2020, 12, 1952 .
AMA StyleNetrananda Sahu, Arpita Panda, Sridhara Nayak, Atul Saini, Manoranjan Mishra, Takahiro Sayama, Limonlisa Sahu, Weili Duan, Ram Avtar, Swadhin Behera. Impact of Indo-Pacific Climate Variability on High Streamflow Events in Mahanadi River Basin, India. Water. 2020; 12 (7):1952.
Chicago/Turabian StyleNetrananda Sahu; Arpita Panda; Sridhara Nayak; Atul Saini; Manoranjan Mishra; Takahiro Sayama; Limonlisa Sahu; Weili Duan; Ram Avtar; Swadhin Behera. 2020. "Impact of Indo-Pacific Climate Variability on High Streamflow Events in Mahanadi River Basin, India." Water 12, no. 7: 1952.
Spatial urban growth and its impact on land surface temperature (LST) is a high priority environmental issue for urban policy. Although the impact of horizontal spatial growth of cities on LST is well studied, the impact of the vertical spatial distribution of buildings on LST is under-investigated. This is particularly true for cities in sub-tropical developing countries. In this study, TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-XDEM), Advanced Spaceborne Thermal Emission and Reflection (ASTER)-Global Digital Elevation Model (GDEM), and ALOS World 3D-30m (AW3D30) based Digital Surface Model (DSM) data were used to investigate the vertical growth of the Dhaka Metropolitan Area (DMA) in Bangladesh. Thermal Infrared (TIR) data (10.6-11.2µm) of Landsat-8 were used to investigate the seasonal variations in LST. Thereafter, the impact of horizontal and vertical spatial growth on LST was studied. The result showed that: (a) TanDEM-X DSM derived building height had a higher accuracy as compared to other existing DSM that reveals mean building height of the Dhaka city is approximately 10 m, (b) built-up areas were estimated to cover approximately 94%, 88%, and 44% in Dhaka South City Corporation (DSCC), Dhaka North City Corporation (DNCC), and Fringe areas, respectively, of DMA using a Support Vector Machine (SVM) classification method, (c) the built-up showed a strong relationship with LST (Kendall tau coefficient of 0.625 in summer and 0.483 in winter) in comparison to vertical growth (Kendall tau coefficient of 0.156 in the summer and 0.059 in the winter), and (d) the ‘low height-high density’ areas showed high LST in both seasons. This study suggests that vertical development is better than horizontal development for providing enough open spaces, green spaces, and preserving natural features. This study provides city planners with a better understating of sustainable urban planning and can promote the formulation of action plans for appropriate urban development policies.
Mustafizur Rahman; Ram Avtar; Ali P. Yunus; Jie Dou; Prakhar Misra; Wataru Takeuchi; Netrananda Sahu; Pankaj Kumar; Brian Alan Johnson; Rajarshi Dasgupta; Ali Kharrazi; Shamik Chakraborty; Tonni Agustiono Kurniawan. Monitoring Effect of Spatial Growth on Land Surface Temperature in Dhaka. Remote Sensing 2020, 12, 1191 .
AMA StyleMustafizur Rahman, Ram Avtar, Ali P. Yunus, Jie Dou, Prakhar Misra, Wataru Takeuchi, Netrananda Sahu, Pankaj Kumar, Brian Alan Johnson, Rajarshi Dasgupta, Ali Kharrazi, Shamik Chakraborty, Tonni Agustiono Kurniawan. Monitoring Effect of Spatial Growth on Land Surface Temperature in Dhaka. Remote Sensing. 2020; 12 (7):1191.
Chicago/Turabian StyleMustafizur Rahman; Ram Avtar; Ali P. Yunus; Jie Dou; Prakhar Misra; Wataru Takeuchi; Netrananda Sahu; Pankaj Kumar; Brian Alan Johnson; Rajarshi Dasgupta; Ali Kharrazi; Shamik Chakraborty; Tonni Agustiono Kurniawan. 2020. "Monitoring Effect of Spatial Growth on Land Surface Temperature in Dhaka." Remote Sensing 12, no. 7: 1191.
Most tropical regions in the world are vulnerable to climate variability, given their dependence on rain-fed agricultural production and limited adaptive capacity owing to socio-economic conditions. The Kalahandi, Bolangir, and Koraput districts of the south-western part of Odisha province of India experience an extreme sub-humid tropical climate. Based on the observed changes in the magnitude and distribution of rainfall and temperature, this study evaluates the potential impact of climate variation on agricultural yield and production in these districts. The study is conducted by taking into account meteorological data like rainfall and temperature from 1980 to 2017 and crop productivity data from 1980–81 to 2016–17. Additionally, climate variability indices like Monsoon Index, Oceanic Nino Index, and NINO-3 and NINO 3.4 are used. To analyse the data, various statistical techniques like correlation and multiple linear regression are used. The amount of monsoon rainfall is found to have a significant impact on crop productivity, compared to temperature, in the study area, and as a result the Monsoon Index has a determining impact on crop yield among various indices.
Arpita Panda; Netrananda Sahu; Swadhin Behera; Takahiro Sayama; Limonlisa Sahu; Ram Avtar; R.B. Singh; Masafumi Yamada. Impact of Climate Variability on Crop Yield in Kalahandi, Bolangir, and Koraput Districts of Odisha, India. Climate 2019, 7, 126 .
AMA StyleArpita Panda, Netrananda Sahu, Swadhin Behera, Takahiro Sayama, Limonlisa Sahu, Ram Avtar, R.B. Singh, Masafumi Yamada. Impact of Climate Variability on Crop Yield in Kalahandi, Bolangir, and Koraput Districts of Odisha, India. Climate. 2019; 7 (11):126.
Chicago/Turabian StyleArpita Panda; Netrananda Sahu; Swadhin Behera; Takahiro Sayama; Limonlisa Sahu; Ram Avtar; R.B. Singh; Masafumi Yamada. 2019. "Impact of Climate Variability on Crop Yield in Kalahandi, Bolangir, and Koraput Districts of Odisha, India." Climate 7, no. 11: 126.
Renewable energy has received noteworthy attention during the last few decades. This is partly due to the fact that fossil fuels are depleting and the need for energy is soaring because of the growing population of the world. This paper attempts to provide an idea of what is being done by researchers in remote sensing and geographical information system (GIS) field for exploring the renewable energy resources in order to get to a more sustainable future. Several studies related to renewable energy resources viz. geothermal energy, wind energy, hydropower, biomass, and solar energy, have been considered in this paper. The focus of this review paper is on exploring how remote sensing and GIS-based techniques have been beneficial in exploring optimal locations for renewable energy resources. Several case studies from different parts of the world which use such techniques in exploring renewable energy resource sites of different kinds have also been included in this paper. Though each of the remote sensing and GIS techniques used for exploration of renewable energy resources seems to efficiently sell itself in being the most effective among others, it is important to keep in mind that in actuality, a combination of different techniques is more efficient for the task. Throughout the paper, many issues relating to the use of remote sensing and GIS for renewable energy are examined from both current and future perspectives and potential solutions are suggested. The authors believe that the conclusions and recommendations drawn from the case studies and the literature reviewed in the present study will be valuable to renewable energy scientists and policymakers.
Ram Avtar; Netrananda Sahu; Ashwani Kumar Aggarwal; Shamik Chakraborty; Ali Kharrazi; Ali P. Yunus; Jie Dou; Tonni Agustiono Kurniawan. Exploring Renewable Energy Resources Using Remote Sensing and GIS—A Review. Resources 2019, 8, 149 .
AMA StyleRam Avtar, Netrananda Sahu, Ashwani Kumar Aggarwal, Shamik Chakraborty, Ali Kharrazi, Ali P. Yunus, Jie Dou, Tonni Agustiono Kurniawan. Exploring Renewable Energy Resources Using Remote Sensing and GIS—A Review. Resources. 2019; 8 (3):149.
Chicago/Turabian StyleRam Avtar; Netrananda Sahu; Ashwani Kumar Aggarwal; Shamik Chakraborty; Ali Kharrazi; Ali P. Yunus; Jie Dou; Tonni Agustiono Kurniawan. 2019. "Exploring Renewable Energy Resources Using Remote Sensing and GIS—A Review." Resources 8, no. 3: 149.
Arpita Panda; Netrananda Sahu. Trend analysis of seasonal rainfall and temperature pattern in Kalahandi, Bolangir and Koraput districts of Odisha, India. Atmospheric Science Letters 2019, 20, 1 .
AMA StyleArpita Panda, Netrananda Sahu. Trend analysis of seasonal rainfall and temperature pattern in Kalahandi, Bolangir and Koraput districts of Odisha, India. Atmospheric Science Letters. 2019; 20 (10):1.
Chicago/Turabian StyleArpita Panda; Netrananda Sahu. 2019. "Trend analysis of seasonal rainfall and temperature pattern in Kalahandi, Bolangir and Koraput districts of Odisha, India." Atmospheric Science Letters 20, no. 10: 1.
Manish Kumar; R. B. Singh; Ram Pravesh; Pankaj Kumar; Dinesh Kumar Tripathi; Netrananda Sahu. Urban Growth Dynamics and Modelling Using Remote Sensing Data and Multivariate Statistical Techniques. Current Science 2018, 114, 1 .
AMA StyleManish Kumar, R. B. Singh, Ram Pravesh, Pankaj Kumar, Dinesh Kumar Tripathi, Netrananda Sahu. Urban Growth Dynamics and Modelling Using Remote Sensing Data and Multivariate Statistical Techniques. Current Science. 2018; 114 (10):1.
Chicago/Turabian StyleManish Kumar; R. B. Singh; Ram Pravesh; Pankaj Kumar; Dinesh Kumar Tripathi; Netrananda Sahu. 2018. "Urban Growth Dynamics and Modelling Using Remote Sensing Data and Multivariate Statistical Techniques." Current Science 114, no. 10: 1.
Based on 169 stations, annual, seasonal and monthly precipitation trends for the northern Japanese island of Hokkaido were analysed for the period 1980–2011 using the Mann–Kendall test and geostatistical interpolation techniques. Possible association with water vapour flux was explored using ERA-Interim reanalysis data. Precipitation increased in Hokkaido over the study period at both the annual and seasonal scales. In general, the northwest had higher precipitation than the southeast in winter, autumn and on an interannual basis and precipitation tended to be concentrated in the southeast in both spring and summer. There was also more precipitation during warm times of the year. For example, precipitation occurred mainly during the summer, ranging from 233 to 751 mm and autumn, ranging from 218 to 724 mm, while precipitation was significantly less in winter and spring. Most stations with declining precipitation trends were located in areas with higher precipitation, such as the west in winter and autumn and the southeast fringe in summer and scattered across the areas with lower precipitation in spring. Increases in precipitation were mainly seen in February, May, June, July, September, November and December at more than 100 stations. Amongst these, almost all of the stations showed positive trends in May (168 stations) and July (165 stations). Finally, the changes of the water vapour transport and budget in whole-layers between the period 1980–2011 possibly explained the spatiotemporal distribution of precipitation trends in Hokkaido.
Weili Duan; Bin He; Netrananda Sahu; Pingping Luo; Daniel Nover; Maochuan Hu; Kaoru Takara. Spatiotemporal variability of Hokkaido's seasonal precipitation in recent decades and connection to water vapour flux. International Journal of Climatology 2016, 37, 3660 -3673.
AMA StyleWeili Duan, Bin He, Netrananda Sahu, Pingping Luo, Daniel Nover, Maochuan Hu, Kaoru Takara. Spatiotemporal variability of Hokkaido's seasonal precipitation in recent decades and connection to water vapour flux. International Journal of Climatology. 2016; 37 (9):3660-3673.
Chicago/Turabian StyleWeili Duan; Bin He; Netrananda Sahu; Pingping Luo; Daniel Nover; Maochuan Hu; Kaoru Takara. 2016. "Spatiotemporal variability of Hokkaido's seasonal precipitation in recent decades and connection to water vapour flux." International Journal of Climatology 37, no. 9: 3660-3673.
In this study we discuss probabilistic forecasts of Citarum River streamflow, which supplies 80 % of the water demands in Jakarta, Indonesia, based on general circulation model (GCM) output, for the September–November (SON) season. Retrospective forecasts of precipitation made over the period 1982–2010 with two coupled-ocean atmosphere GCMs, initialized in August, are used in conjunction historical streamflow records, with a cross-validated regression model. Pearson’s product moment correlation skill values of 0.58–0.67 are obtained, with relative operating characteristic scores of 0.67–0.84 and 0.74–0.92 for the lower and upper tercile categories of flows respectively. Both GCMs thus demonstrate promising ability to forecast below/above normal streamflow for the Citarum River flow during the SON season.
Netrananda Sahu; Andrew W. Robertson; Rizaldi Boer; Swadhin Behera; David G. DeWitt; Kaoru Takara; Manish Kumar; R. B. Singh. Probabilistic seasonal streamflow forecasts of the Citarum River, Indonesia, based on general circulation models. Stochastic Environmental Research and Risk Assessment 2016, 31, 1747 -1758.
AMA StyleNetrananda Sahu, Andrew W. Robertson, Rizaldi Boer, Swadhin Behera, David G. DeWitt, Kaoru Takara, Manish Kumar, R. B. Singh. Probabilistic seasonal streamflow forecasts of the Citarum River, Indonesia, based on general circulation models. Stochastic Environmental Research and Risk Assessment. 2016; 31 (7):1747-1758.
Chicago/Turabian StyleNetrananda Sahu; Andrew W. Robertson; Rizaldi Boer; Swadhin Behera; David G. DeWitt; Kaoru Takara; Manish Kumar; R. B. Singh. 2016. "Probabilistic seasonal streamflow forecasts of the Citarum River, Indonesia, based on general circulation models." Stochastic Environmental Research and Risk Assessment 31, no. 7: 1747-1758.
The extremely high-streamflow events of the Paranaíba River basin are found to be associated with La Niña phenomenon during December–February (DJF). Extreme events are identified based on their persistent flow for seven days and more after taking retention time into consideration. The extremely high-streamflow events are associated with the La Niña years; 80% of the high-streamflow events have occurred during La Niña phases. Therefore, a very-significant 80% and above correspondence of the La Niña events and the seasonal streamflow anomalies are found in DJF. Although climate variations have direct relationship with the rainfall, streamflow variations are considered as the surrogates to rainfalls. However, apart from climate variations the anthropogenic and land-use changes also influence streamflow variations. In this study, we have applied multivelocity TOPMODEL approach and residual trend analysis to examine the impact of land-use to the streamflow at the Fazenda Santa Maria gauge stations. However, the model residual trend analysis of the TOPMODEL approach cannot quantify the extent of land-use impact. Thus, La Niña phase is important components to understand and predict the streamflow variations in the Paranaíba River basin.
Netrananda Sahu; R.B. Singh; Pankaj Kumar; Roberto Valmir da Silva; Swadhin Behera. La Niña Impacts on Austral Summer Extremely High-Streamflow Events of the Paranaíba River in Brazil. Advances in Meteorology 2013, 2013, 1 -6.
AMA StyleNetrananda Sahu, R.B. Singh, Pankaj Kumar, Roberto Valmir da Silva, Swadhin Behera. La Niña Impacts on Austral Summer Extremely High-Streamflow Events of the Paranaíba River in Brazil. Advances in Meteorology. 2013; 2013 ():1-6.
Chicago/Turabian StyleNetrananda Sahu; R.B. Singh; Pankaj Kumar; Roberto Valmir da Silva; Swadhin Behera. 2013. "La Niña Impacts on Austral Summer Extremely High-Streamflow Events of the Paranaíba River in Brazil." Advances in Meteorology 2013, no. : 1-6.