scholarly journals Future climate change impacts on runoff of scarcely gauged Jhelum river basin using SDSM and RCPs

2021 ◽  
Author(s):  
Saira Munawar ◽  
Muhammad Naveed Tahir ◽  
Muhammad Hassan Ali Baig
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Climate Change Impacts ◽  
Baseline Period ◽  
Future Climate Change ◽  
Mean Annual Precipitation ◽  
Climatic Data ◽  
Global Issue ◽  
Jhelum River ◽  
Jhelum River Basin

Abstract Climate change is a global issue and causes great uncertainties in runoff and streamflow projections, especially in high-altitude basins. The quantification of climatic indicators remains a tedious job for the scarcely gauged mountainous basin. This study investigated climate change by incorporating GCM (CCSM4) using the SDSM method for RCPs in the Jhelum river basin. Historical climatic data were coupled with Aphrodite data to cope with the scarcity of weather stations. SDSM was calibrated for the period 1976–2005 and validated for the period 2006–2015 using R2 and RMSE. Future climatic indicators were downscaled and debiased using the MB-BC method. The de-biased downscaled data and MODIS data were used to simulate discharge of Jhelum river basin using SRM. Simulated discharge was compared with measured discharge by using Dv% and NSE. The R2 and RMSE for SDSM range between 0.89–0.95 and 0.8–1.02 for temperature and 0.86–0.96 and 0.57–1.02 for precipitation. Projections depicted a rising trend of 1.5 °C to 3.8 °C in temperature, 2–7% in mean annual precipitation and 3.3–7.4% in discharge for 2100 as compared to the baseline period. Results depicted an increasing trend for climatic indicators and discharge due to climate change for the basin.

Projection of future streamflow changes of the Pearl River basin in China using two delta-change methods

2015 ◽  
Vol 47 (1) ◽  
pp. 217-238 ◽  
Author(s):  
Fei Yuan ◽  
Yeou-Koung Tung ◽  
Liliang Ren
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Future Climate Change ◽  
Pearl River ◽  
Daily Maximum ◽  
Climatic Data ◽  
Pearl River Basin ◽  
Delta Change ◽  
The Pearl River ◽  
The Pearl River Basin

Considerable biases in precipitation simulations in climate models have required the adoption of delta-change approaches to construct future precipitation scenarios for hydrological climate change impact studies. However, different delta-change methods yield different future precipitation scenarios that might significantly affect the projected future streamflow. To assess these effects, two delta-change methods were compared: the simple delta-change (SDC) method with a constant scaling factor and the quantile-quantile delta-change (QQDC) method with a quantile mapping-based non-uniform delta factor. The Xinanjiang (XAJ) hydrological model was applied using historical climatic data and two future precipitation scenarios for streamflow simulations in the Pearl River basin, China. The results show that the two delta-change methods have significant influences on future precipitation and streamflow projections, and these impacts become more distinct at finer and extreme event time scales. For instance, the QQDC method projects the 20-year daily maximum precipitation to be 8.1–98.6% higher than the SDC method. Consequently, the XAJ model with the QQDC future precipitation produces the 20-year daily maximum streamflow to be approximately 7.0–65.0% higher than that using the SDC precipitation. It implies that future precipitation transformation methods are a source of uncertainty, affecting future discharge projections. Such uncertainty should be considered in water resources management and flood control strategies for future climate change adaptations.

scholarly journals Analyzing the future climate change of Upper Blue Nile River Basin (UBNRB) using statistical down scaling techniques

2016 ◽  
Author(s):  
Dagnenet Fenta Mekonnen ◽  
Markus Disse
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Future Climate ◽  
Maximum Temperature ◽  
Future Climate Change ◽  
Mean Annual Precipitation ◽  
Nile River ◽  
Climate Variables ◽  
Increasing Trend ◽  
Blue Nile River Basin

Abstract. Climate change is becoming one of the most arguable and threatening issues in terms of global context and their responses to environment and socio/economic drivers. Its direct impact becomes critical for water resource development and indirectly for agricultural production, environmental quality, economic development, social well-being. However, a large uncertainty between different Global Circulation Models (GCM) and downscaling methods exist that makes reliable conclusions for a sustainable water management difficult. In order to understand the future climate change of the Upper Blue Nile River Basin, two widely used statistical down scaling techniques namely LARS-WG and SDSM models were applied. Six CMIP3 GCMs for LARS-WG (CSIRO-MK3, ECHAM5-OM, MRI-CGCM2.3.2, HaDCM3, GFDL-CM2.1, CCSM3) model while HadCM3 GCM and canESM2 from CMIP5 GCMs for SDSM were used for climate change analysis. The downscaled precipitation results from the prediction of the six GCMs by LARS WG showed inconsistency and large inter model variability, two GCMs showed decreasing trend while 4 GCMs showed increasing in the range from −7.9 % to +43.7 % while the ensemble mean of the six GCM result showed increasing trend ranged from 1.0 % to 14.4 %. NCCCS GCM predicted maximum increase in mean annual precipitation. However, the projection from HadCM3 GCM is consistent with the multi-model average projection, which predicts precipitation increase from 1.7 % to 16.6 %. Conversely, the result from all GCMs showed a similar continuous increasing trend for maximum temperature (Tmax) and minimum temperature (Tmin) in all three future periods. The change for mean annual Tmax may increase from 0.4 °c to 4.3 °c whereas the change for mean annual Tmin may increase from 0.3 °c to 4.1 °c. Meanwhile, the result from SDSM showed an increasing trend for all three climate variables (precipitation, minimum and maximum temperature) from both HadCM3 and canESM2 GCMs. The relative change of mean annual precipitation range from 2.1 % to 43.8 % while the change for mean annual Tmax and Tmin may increase from 0.4 °c to 2.9 °c and from 0.3 °c to 1.6 °c respectively. The change in magnitude for precipitation is higher in RCP8.5 scenarios than others as expected. The present result illustrate that both down scaling techniques have shown comparable and good ability to simulate the current local climate variables which can be adopted for future climate change study with high confidence for the UBNRB. In order to see the comparative downscaling results from the two down scaling techniques, HadCM3 GCM of A2 scenario was used in common. The result obtained from the two down scaling models were found reasonably comparable and both approaches showed increasing trend for precipitation, Tmax and Tmin. However, the analysis of the downscaled climate data from the two techniques showed, LARS WG projected a relatively higher increase than SDSM.

scholarly journals Changes in flow and sediment load of poorly gauged Brahmaputra river basin under an extreme climate scenario

2020 ◽  
Author(s):  
Shammi Haque ◽  
Md. Mostafa Ali ◽  
A. K. M. Saiful Islam ◽  
Jamal Uddin Khan
Keyword(s):  
Climate Change ◽  
River Basin ◽  
River Flow ◽  
Sediment Load ◽  
Monsoon Season ◽  
Climate Scenario ◽  
Baseline Period ◽  
Future Climate Change ◽  
Brahmaputra River ◽  
Sediment Routing

Abstract Brahmaputra River Basin (BRB), the largest contributor of sediment load in Ganges–Brahmaputra–Meghna delta, is highly vulnerable to future climate change. Several studies assessed the effects of climate change of BRB on river flow but an assessment on sediment load has not been conducted. Changes in sediment load in the future need to be assessed to control and manage sediment flows in large catchments properly. The present study focuses on developing a hydrological and sediment routing model of BRB using the HEC-HMS model to estimate future sediment load together with the flow for the RCP 8.5 climate scenario. Modified Universal Soil Loss Equation and Engelund Hansen method of HEC-HMS have been applied for the sediment transport of BRB. The model has been calibrated using daily runoff for the period 1983–1996 and validated for the period 1997–2010, respectively. The uncertainty in the percentage change in seasonal sediment load during the pre-monsoon season is higher than that of the monsoon season. However, the contribution of the sediment load of pre-monsoon is very much lower than the monsoon season. The percentage changes in mean annual sediment load compared to the baseline period for the 2020s, 2050s and 2080s are 34, 67 and 115%, respectively.

scholarly journals Projected Moisture Index (MI) for Tropical Sri Lanka

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Charuni Wickramarachchi ◽  
Jayanga T. Samarasinghe ◽  
Yousif Alyousifi ◽  
Upaka Rathnayake
Keyword(s):  
Climate Change ◽  
Sri Lanka ◽  
Climate Change Impacts ◽  
Future Climate Change ◽  
Climatic Data ◽  
Moisture Index ◽  
Climate Conditions ◽  
Climatic Scenarios ◽  
Temporal And Spatial ◽  
Projected Changes

Atmospheric moisture loading can cause a great impact on the performance and integrity of building exteriors in a tropical climate. Buildings can be highly impacted due to the changing climate conditions over the world. Therefore, it is important to incorporate the projected changes of moisture loads in structural designs under changing climates. The moisture index (MI) is widely used in many countries as a climate-based indicator to guide the building designs for their durability performance. However, this was hardly considered in structural designs in Sri Lanka, even though the country is one of the most affected countries under climate change. Therefore, this study investigates future climate change impacts on the environmental moisture in terms of MI, which can be used in climate zoning, investigating indoor air quality, understanding thermal comfort and energy consumption, etc. The moisture index was found as a function of the drying index (DI) and wetting index (WI) to the whole country for its four rainfall seasons. The temporal and spatial distributions were plotted as MI maps and showcased under two categories; including historical MI maps (1990–2004) and future projected MI maps (2021–2040, 2041–2070, and 2071–2100). Future projected MI maps were constructed using bias-corrected climatic data for two RCP climatic scenarios (RCP4.5 and RCP8.5). Results showed that the temporal and spatial variations of MIs are justifiable to the country’s rainfall patterns and seasons. However, notable increases of MIs can be observed for future projected MIs in two seasons, and thus a careful investigation of their impacts should be assessed in terms of the construction of buildings and various agricultural activities. Therefore, the outcome of this research can be essentially used in policy implementation in adapting to the ongoing climate changes in Sri Lanka.

scholarly journals Impact of Climate Change on the Snow Hydrology of Koshi River Basin

2016 ◽  
Vol 9 (1) ◽  
pp. 28-44 ◽  
Author(s):  
A. Khadka ◽  
L.P. Devkota ◽  
R.B. Kayastha
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Climate Change Impacts ◽  
Baseline Period ◽  
Himalayan Region ◽  
Climate Change Scenarios ◽  
Snow Hydrology ◽  
Monsoon Flow ◽  
Change Impact ◽  
Koshi River Basin

Koshi river basin which is one of the largest river basins of Nepal has its headwaters in the northern Himalayan region of the country covered with perennial snow and glaciers. Increased warming due to climate change is most likely to impact snowpack of this Himalayan region. Snowmelt Runoff Model, a degree day based method, was used in this study to assess the snowmelt hydrology of the five sub-basins, viz. Tamor, Arun, Dudhkoshi, Tamakoshi and Sunkoshi of the Koshi river basin, with and without climate change impacts. The model has been fairly able to simulate the flow. Daily bias-corrected RCM data of PRECIS-ECHAM05 and PRECIS-HadCM3 for the period of 2041-2060 were used for future projection. A period of 2000-2008 was set as baseline period to evaluate changes in future flow. In climate change scenarios, magnitude and frequency of peak flows are expected to increase and snowmelt contribution to total river flows are likely to be more. Simulated flow results indicate that the annual flow would still be governed by monsoon flow even in the future under the climate change impact. A high probability of having more flows and snowmelt in 50’s decade than that in 40’s decade is seen. The estimated future flow by ECHAM05 is found more than those estimated by HadCM3 both seasonally and annually.Journal of Hydrology and Meteorology, Vol. 9(1) 2015, p.28-44

Future climate change impacts on the ecohydrology of Guishui River Basin, China

2014 ◽  
Vol 14 (1) ◽  
pp. 55-67 ◽  
Author(s):  
Binbin Guo ◽  
Jing Zhang ◽  
Huili Gong ◽  
Xiaoguang Cheng
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Climate Change Impacts ◽  
Future Climate ◽  
Future Climate Change

scholarly journals Climate Change Impact on the Hydrologic Regimes and Sediment Yield of Pulangi River Basin (PRB) for Watershed Sustainability

2021 ◽  
Vol 13 (16) ◽  
pp. 9041
Author(s):  
Warda Panondi ◽  
Norihiro Izumi
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Sediment Yield ◽  
Assessment Tool ◽  
Baseline Period ◽  
Annual Runoff ◽  
The Philippines ◽  
Mean Annual Precipitation ◽  
Climate Projections ◽  
Global Circulation Models

The impacts of climate change are increasingly threatening the sustainability of ecosystems around the world. The Pulangi River Basin (PRB) in the Philippines is experiencing sedimentation beyond the tolerable amount (11.2 tons/ha/yr) due to land conversion and the effects of climate change. Changes in precipitation and temperature due to climate change are likely to further affect the annual runoff and sediment yield of PRB. In this study, the Soil and Water Assessment Tool (SWAT) was employed to simulate various scenarios of twelve downscaled climate projections from three Global Circulation Models (GCM) of CMIP5 under two Representative Concentration Pathways (RCP 4.5 and 6.0) for 2040–2069 and 2070–2099 timeframes, and the results were compared to a baseline period (1975–2005). This study revealed that the maximum mean annual precipitation is expected to increase by 39.10%, and the minimum and maximum temperatures are expected to increase by 3.04 °C and 3.83 °C, respectively. These observed changes correspond to an increase in runoff (44.58–76.80%) and sediment yield (1.33–26.28%) within the sub-basins. These findings suggest a general increase in the threat of severe flooding and excessive soil loss, leading to severe erosion and reservoir sedimentation throughout the PRB.

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