scholarly journals Impact of Indo-Pacific Climate Variability on High Streamflow Events in Mahanadi River Basin, India

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1952 ◽  
Author(s):  
Netrananda Sahu ◽  
Arpita Panda ◽  
Sridhara Nayak ◽  
Atul Saini ◽  
Manoranjan Mishra ◽  
...  
Keyword(s):  
Climate Variability ◽  
River Basin ◽  
Extreme Events ◽  
Indian Monsoon ◽  
El Nino ◽  
Mahanadi River ◽  
Monsoon Index ◽  
Mahanadi Basin ◽  
June July ◽  
The Impact

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.

scholarly journals Seasonal Rainfall Forecasts for the Yangtze River Basin in the Extreme Summer of 2020

2021 ◽  
Author(s):  
Philip E. Bett ◽  
Gill M. Martin ◽  
Nick Dunstone ◽  
Adam A. Scaife ◽  
Hazel E. Thornton ◽  
...  
Keyword(s):  
Linear Regression ◽  
River Basin ◽  
Yangtze River ◽  
Asian Summer Monsoon ◽  
Yangtze River Basin ◽  
Early Summer ◽  
Lead Times ◽  
Seasonal Forecasts ◽  
June July ◽  
The Impact

AbstractSeasonal forecasts for Yangtze River basin rainfall in June, May–June–July (MJJ), and June–July–August (JJA) 2020 are presented, based on the Met Office GloSea5 system. The three-month forecasts are based on dynamical predictions of an East Asian Summer Monsoon (EASM) index, which is transformed into regional-mean rainfall through linear regression. The June rainfall forecasts for the middle/lower Yangtze River basin are based on linear regression of precipitation. The forecasts verify well in terms of giving strong, consistent predictions of above-average rainfall at lead times of at least three months. However, the Yangtze region was subject to exceptionally heavy rainfall throughout the summer period, leading to observed values that lie outside the 95% prediction intervals of the three-month forecasts. The forecasts presented here are consistent with other studies of the 2020 EASM rainfall, whereby the enhanced mei-yu front in early summer is skillfully forecast, but the impact of midlatitude drivers enhancing the rainfall in later summer is not captured. This case study demonstrates both the utility of probabilistic seasonal forecasts for the Yangtze region and the potential limitations in anticipating complex extreme events driven by a combination of coincident factors.

The impact of climate variability and land use/cover change on the water balance in the Middle Yellow River Basin, China

2019 ◽  
Vol 577 ◽  
pp. 123942 ◽  
Author(s):  
Zhenxin Bao ◽  
Jianyun Zhang ◽  
Guoqing Wang ◽  
Qiuwen Chen ◽  
Tiesheng Guan ◽  
...  
Keyword(s):  
Land Use ◽  
Water Balance ◽  
Climate Variability ◽  
River Basin ◽  
Yellow River ◽  
Yellow River Basin ◽  
The Impact

scholarly journals Influence of Natural Climate Variability on Extreme Wave Power over Indo-Pacific Ocean Assessed using ERA5

2021 ◽  
Author(s):  
Prashant Kumar ◽  
Sukhwinder Kaur ◽  
Evan Weller ◽  
Ian R. Young
Keyword(s):  
Pacific Ocean ◽  
Indian Ocean ◽  
Climate Variability ◽  
El Niño ◽  
El Nino ◽  
Extreme Value Analysis ◽  
Wave Power ◽  
Central Pacific ◽  
Natural Climate ◽  
The Impact

Abstract In recent decades, wave power (WP) energy from the ocean is one of the cleanest renewable energy sources associated with oceanic warming. In Indo-Pacific Ocean, the WP is significantly influenced by natural climate variabilities, such as El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and Pacific Decadal Oscillation (PDO). In this study, the impact of major climate variability modes on seasonal extreme WP is examined over the period 1979–2019 using ERA5 reanalysis data and the non-stationary generalized extreme value analysis is applied to estimate the climatic extremes. Independent ENSO influence after removing the IOD trends (ENSO|IOD) on WP are evident over the eastern and central Pacific during December–February (DJF) and March–May (MAM), respectively, which subsequently shifts towards the western Pacific in June–August (JJA) and September–November (SON). The ENSO|PDO impact on WP exhibits similar yet weaker intensity year round compared to ENSO. Extreme WP responses due to the IOD|ENSO include widespread decreases over the tropical and eastern Indian Ocean (IO), with localized increases only over the South China and Philippine (SCP) seas and Bay of Bengal (BOB) during JJA, and the Arabian Sea during SON. Lastly, for the PDO|ENSO, the significant increases in WP are mostly confined to the Pacific, and most prominent in the North Pacific. Composite analysis of different phase combinations of PDO (IOD) with El Niño (La Niña) reveals stronger (weaker) influences year-round. The response patterns in significant wave height (SWH), peak wave period (PWP), sea surface temperatures (SST), and sea level pressure (SLP) helps to explain the seasonal variations in WP.

scholarly journals Trends in climatic variables and future reference evapotranspiration in Duero Valley (Spain)

2011 ◽  
Vol 11 (6) ◽  
pp. 1795-1805 ◽  
Author(s):  
R. Moratiel ◽  
R. L. Snyder ◽  
J. M. Durán ◽  
A. M. Tarquis
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Reference Evapotranspiration ◽  
Stomatal Resistance ◽  
Dew Point ◽  
Maximum Temperature ◽  
Net Radiation ◽  
Maximum Water ◽  
June July ◽  
The Impact

Abstract. The impact of climate change and its relation with evapotranspiration was evaluated in the Duero River Basin (Spain). The study shows possible future situations 50 yr from now from the reference evapotranspiration (ETo). The maximum temperature (Tmax), minimum temperature (Tmin), dew point (Td), wind speed (U) and net radiation (Rn) trends during the 1980–2009 period were obtained and extrapolated with the FAO-56 Penman-Montheith equation to estimate ETo. Changes in stomatal resistance in response to increases in CO2 were also considered. Four scenarios were done, taking the concentration of CO2 and the period analyzed (annual or monthly) into consideration. The scenarios studied showed the changes in ETo as a consequence of the annual and monthly trends in the variables Tmax, Tmin, Td, U and Rn with current and future CO2 concentrations (372 ppm and 550 ppm). The future ETo showed increases between 118 mm (11 %) and 55 mm (5 %) with respect to the current situation of the river basin at 1042 mm. The months most affected by climate change are May, June, July, August and September, which also coincide with the maximum water needs of the basin's crops.

Spatio-temporal variability of streamflow in the Huaihe River Basin, China: climate variability or human activities?

2017 ◽  
Vol 49 (1) ◽  
pp. 177-193 ◽  
Author(s):  
Zharong Pan ◽  
Xiaohong Ruan ◽  
Mingkai Qian ◽  
Jian Hua ◽  
Nan Shan ◽  
...  
Keyword(s):  
Climate Variability ◽  
River Basin ◽  
Human Activities ◽  
River System ◽  
Kendall Test ◽  
Driving Factor ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
The Huaihe River ◽  
The Impact

AbstractThe water shortage in the Huaihe River Basin (HRB), China, has been aggravated by population growth and climate change. To identify the characteristics of streamflow change and assess the impact of climate variability and human activities on hydrological processes, approximately 50 years of natural and observed streamflow data from 20 hydrological stations were examined. The Mann–Kendall test was employed to detect trends. The results showed the following. (i) Both the natural and the observed streamflow in the HRB present downward trends, and the decreasing rate of observed streamflow is generally faster than that of the natural streamflow. (ii) For the whole period, negative trends dominate in the four seasons in the basin. The highest decreasing trends for two kinds of streamflow both occurred in spring, and the lowest ones were in autumn and winter. (iii) Based on the above analysis and quantifying assessment for streamflow decrease, human activity was the main driving factor in the Xuanwu (80.78%), Zhuangqiao (79.92%), Yongcheng (74.80%), and Mengcheng (64.73%) stations which all belong to the Huaihe River System (HRS). On the other hand, climate variability was the major driving factor in the Daguanzhuang (68.89%) and Linyi (63.38%) stations which all belong to the Yishusi River System (YSR).

scholarly journals Quantifying the impact of land cover changes on hydrological responses in India

2021 ◽  
Author(s):  
Shaini Naha ◽  
Miguel A. Rico-Ramirez ◽  
Rafael Rosolem
Keyword(s):  
Land Use ◽  
Land Cover ◽  
River Basin ◽  
Distributed Model ◽  
Model Parameters ◽  
Area Index ◽  
Mahanadi River ◽  
Extreme Flows ◽  
Hydrological Responses ◽  
The Impact

Abstract. The objective of this study is to assess the impacts of Land Use Land Cover change on the hydrological responses of the Mahanadi river basin, a large river basin in India. Commonly, such assessments are accomplished by using distributed hydrological models in conjunction with different land use scenarios. However, these models through their complex interactions among the model parameters to generate hydrological processes, can introduce significant uncertainties to the hydrological projections. Therefore, we seek to further understand the uncertainties associated with model parameterization in those simulated hydrological responses due to different land cover scenarios. We performed a sensitivity-guided model calibration of a physically semi-distributed model, the Variable Infiltration Capacity (VIC) within a Monte Carlo Framework to generate behavioural models for subcatchments of the Mahanadi river basin. These behavioural models are then used in conjunction with historical and future land cover scenarios from the recently released, Land use Harmonisation (LUH2) to generate hydrological predictions and related uncertainties from behavioural model parameterisation. The LUH2 dataset indicates a noticeable increase in the cropland (23.3 % cover) at the expense of forest (22.65 % cover) by the end of year 2100 compared to the baseline year, 2005. As a response, simulation results indicate a median percent increase in the extreme flows (defined as the 95th percentile or higher river flow magnitude) and mean annual flows in the range of 1.8 to 11.3 % across the subcatchments. The direct conversion of forested areas to agriculture (on the order of 30,000 km2) reduces the Leaf Area Index and which subsequently reduces the Evapotranspiration (ET) and increases surface runoff. Further, the range of behavioural hydrological predictions indicated variation in the magnitudes of extreme flows simulated for the different land cover scenarios, for instance uncertainty in far future scenario ranges from 17 to 210 cumecs across subcatchments. This study indicates that the recurrent flood events occurring in the Mahanadi river basin might be influenced by the changes in LULC at the catchment scale and suggests that model parameterisation represents an uncertainty, which should be accounted for in the land-use change impact assessment.

Assessing the impact of climate variability and human activities on streamflow from the Wuding River basin in China

2007 ◽  
Vol 21 (25) ◽  
pp. 3485-3491 ◽  
Author(s):  
Li-Juan Li ◽  
Lu Zhang ◽  
Hao Wang ◽  
Juan Wang ◽  
Jun-Wei Yang ◽  
...  
Keyword(s):  
Climate Variability ◽  
River Basin ◽  
Human Activities ◽  
The Impact ◽  
The Wuding River

scholarly journals Quantifying the impact of land cover changes on hydrological extremes in India

2020 ◽  
Author(s):  
Shaini Naha ◽  
Miguel A. Rico-Ramirez ◽  
Rafael Rosolem
Keyword(s):  
Land Use ◽  
Land Cover ◽  
River Basin ◽  
Land Surface ◽  
Distributed Model ◽  
Model Parameters ◽  
Land Cover Changes ◽  
Area Index ◽  
Mahanadi River ◽  
The Impact

Abstract. Several research studies have addressed the effects of future climate changes on the hydrological regime of Mahanadi river basin located in eastern part of India. However, studies investigating the effects of future land cover changes on hydrology are limited owing to the lack of availability of projected land cover scenarios. Our study investigates how the hydrology of Mahanadi river basin would respond to the current and future land cover scenarios under a large-scale hydrological modelling framework. Both historical and future land cover scenarios from the recently released, Land use Harmonisation (LUH2) project for CMIP6, indicates cropland and forest are the major land cover types in the basin with a noticeable increase in the cropland (23.3 %) at the expense of forest (22.65 %) by the end of year 2100 compared to the baseline year, 2005. A physically semi-distributed model, the Variable Infiltration Capacity has been set up and implemented over the Mahanadi river basin system for the time period 1990–2010. The uncertain model parameters were subjected to Sensitivity Analysis and calibrated within a Monte Carlo framework. The best set of calibrated models obtained is used in conjunction with the harmonized set of present and future land use scenarios from LUH2 at 25 km by 25 km resolution to generate an ensemble of model simulations that captures a range of plausible impacts of land cover changes on discharge and other hydrological components of the basin. Overall, model simulation results indicate an increase in the extreme flows (i.e., 95th percentile or higher) in the range of 0.12 to 21 % at multiple subcatchments within the basin. This increase can be attributed to the direct conversion of forested areas to agriculture (on the order of 30,000 km2) that has reduced the Leaf Area Index and subsequently reduces the Evapotranspiration (ET). These changes ultimately affect other water balance components at the land surface, resulting in an increase in surface runoff and baseflow, respectively.

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