Hydrological Variability and its Response to Climate Change in Turpan basin

Author(s):  
Lijuan Du

<p>The Turpan basin is one of the most arid and water insecure regions in China. The mountain snowmelt is the primary source of water. To assess the impact of climate change on stream flow, this study examined the long-term trends and change points of hydro-meteorological variables and explored the possible correlation between them at annual and seasonal scales. A set of non-parametric statistical tests including Mann-Kendall, Kendall’s tau, Sen’s slope estimator, and Pettitt test was applied, and change point of the hydro-meteorological variables. This study provided valuable information in understanding the changing properties of the stream flow in the basin and insights for a better integrated water resources management planning.</p>

2021 ◽  
Author(s):  
Bekam Bekele Gulti ◽  
Boja Mokonnen Manyazew ◽  
Abdulkerim Bedewi Serur

Abstract Climate change (CC) and land use/cover change (LUCC) are the main drivers of streamflow change. In this paper, we investigate the impact of climate and LULC change impact on stream flow of Guder catchment by using Soil and Water Assessment model (SWAT). The scenarios were designed in a way that LULC was changed while climate conditions remain constant; LULC was then held constant under a changing climate and combined effect of both. The result shows that, the combined impacts of climate change and LULC dynamics can be rather different from the effects that follow-on from LULC or climate change alone. Streamflow would be more sensitive to climate change than to the LULC changes scenario, even though changes in LULC have far-reaching influences on streamflow in the study region. A comprehensive strategy of low impact developments, smart growth, and open space is critical to handle future changes to streamflow systems.


2015 ◽  
Vol 19 (1) ◽  
pp. 379-387 ◽  
Author(s):  
I. Andrés-Doménech ◽  
R. García-Bartual ◽  
A. Montanari ◽  
J. B. Marco

Abstract. Measuring the impact of climate change on flood frequency is a complex and controversial task. Identifying hydrological changes is difficult given the factors, other than climate variability, which lead to significant variations in runoff series. The catchment filtering role is often overlooked and thus may hinder the correct identification of climate variability signatures on hydrological processes. Does climate variability necessarily imply hydrological variability? This research aims to analytically derive the flood frequency distribution based on realistic hypotheses about the rainfall process and the rainfall–runoff transformation. The annual maximum peak flow probability distribution is analytically derived to quantify the filtering effect of the rainfall–runoff process on climate change. A sensitivity analysis is performed according to typical semi-arid Mediterranean climatic and hydrological conditions, assuming a simple but common scheme for the rainfall–runoff transformation in small-size ungauged catchments, i.e. the CN-SCS model. Variability in annual maximum peak flows and its statistical significance are analysed when changes in the climatic input are introduced. Results show that depending on changes in the annual number of rainfall events, the catchment filtering role is particularly significant, especially when the event rainfall volume distribution is not strongly skewed. Results largely depend on the return period: for large return periods, peak flow variability is significantly affected by the climatic input, while for lower return periods, infiltration processes smooth out the impact of climate change.


Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1612
Author(s):  
Manling Xiong ◽  
Ching-Sheng Huang ◽  
Tao Yang

Various models based on Budyko framework, widely applied to quantify the impacts of climate change and land use/cover change (LUCC) on runoff, assumed a fixed partition used to distinguish the impacts. Several articles have applied a weighting factor describing arbitrary partitions for developing a total differential Budyko (TDB) model and a complementary Budyko (CB) model. This study introduces the weighting factor into a decomposition Budyko (DB) model and applies these three models to analyze runoff variation due to the impacts in the upper-midstream Heihe River basin. The Pettitt test is first applied to determine a change point of a time series expanded by the runoff coefficient. The cause for the change point is analyzed. Transition matrix is adopted to investigate factors of LUCC. Results suggest the consistency of the CB, TDB, and present DB models in estimating runoff variation due to the impacts. The existing DB model excluding the weighting factor overestimates the impact of climate change on runoff and underestimates the LUCC impact as compared with the present DB model. With two extreme values of the weighting factor, runoff decrease induced by LUCC falls in the range of 65.20%–66.42% predicted by the CB model, 65.01%–66.57% by the TDB model, and 64.83%–66.85% by the present DB model. The transition matrixes indicate the major factors of LUCC are climate warming in the upstream of the study area and cropping in the midstream. Our work provides researchers with a better understanding of runoff variation due to climate change and LUCC.


2016 ◽  
Vol 11 (3) ◽  
pp. 834-845
Author(s):  
Manti Patil

The Stream-flow is key component of hydro power project regulation. The present study has been conducted to identify the impact of climate change on stream flow of Ranganadi River, a sub-set of Brahmaputra basin situated at north-East region of India, which receives more rainfall as compare to other parts of India The three GCM model viz.HadCM3, CGCM2 and GFDL monthly data with A2 scenario have been choose for Downscaling by advanced neural technique (Artificial Neural Network).The prediction result show as an positive increasing trend up to 2040 for Ranganadi River. This will create the flood problem but capacity of hydroelectricity generation will be increase.


2020 ◽  
Vol 38 (2A) ◽  
pp. 265-276
Author(s):  
Mahmoud S. Al- Khafaji ◽  
Rana D. Al- Chalabi

The impact of climate change on stream flow and sediment yield in Darbandikhan Watershed is an important challenge facing the water resources in Diyala River, Iraq. This impact was investigated using five Global Circulation Models (GCM) based climate change projection models from the A1B scenario of medium emission. The Soil and Water Assessment Tool (SWAT) was used to compute the temporal and spatial distribution of streamflow and sediment yield of the study area for the period 1984 to 2050. The daily-observed flow recorded in Darbandikhan Dam for the period from 1984 to 2013 was used as a base period for future projection. The initial results of SWAT were calibrated and validated using SUFI-2 of the SWAT-CUP program in daily time step considering the values of the Nash-Sutcliffe Efficiency (NSE) coefficient of determination (R2) as a Dual objective function. Results of NSE and R2 during the calibration (validation) periods were equal to 0.61 and 0.62(0.53 and 0.68), respectively. In addition, the average future prediction for the five climate models indicated that the average yearly flow and sediment yield in the watershed would decrease by about 49% and 44%, respectively, until the year 2050 compared with these of the base period from 1984 to 2013. Moreover, spatial analysis shows that 89.6 % and 90 % of stream flow and sediment come from the Iranian part of Darbandikhan watershed while the remaining small percent comes from Iraq, respectively. However, the middle and southern parts of Darbandikhan Watershed contribute by most of the stream...


2021 ◽  
Vol 11 (24) ◽  
pp. 11821
Author(s):  
Giuseppe Marco Tina ◽  
Claudio F. Nicolosi

Climate change due to the greenhouse effect will affect meteorological variables, which in turn will affect the demand for electrical energy and its generation in coming years. These impacts will become increasingly important in accordance with the increasing penetration of renewable, non-programmable energy sources (e.g., wind and solar). Specifically, the speed and amplitude of power system transformation will be different from one country to another according to many endogenous and exogenous factors. Based on a literature review, this paper focuses on the impact of climate change on the current, and future, Italian power system. The paper shows a wide range of results, due not just to the adopted climate change models used, but also to the models used to assess the impact of meteorological variables on electricity generation and demand. Analyzing and interpreting the reasons for such differences in the model results is crucial to perform more detailed numerical analyses on the adequacy and reliability of power systems. Concerning Italian future scenarios, the double impact of uncertainties in national policies and changes in power plant productivity and demand, has been considered and addressed.


Author(s):  
Safieh Javadinejad ◽  
Rebwar Dara ◽  
Forough Jafary

Abstract California is severely exposed to drought and damage due to the climate change and drought belt, which has a major impact on agriculture. So, after the drought crisis, there are various reactions from farmers. The extent of the damage caused by the socioeconomic, environment and the extent of the resistance of farmers to this crisis is manifested in a variety of ways. Recognizing the population’s resilience and the involved human groups is a tool for preventing a catastrophe-based increase in life-threatening areas in high-risk areas. Sometimes the inability to manage this phenomenon (especially under the climate change) leads to farmers’ desertification and agricultural land release, which itself indicates a low level of resilience and resilience to the crisis. The recent drought under the climate change condition in California and the severity of the damage sustained by farmers continue to be vulnerable. The present study seeks to prioritize and prioritize resilience of farmers to the crisis under the climate change. This study simulated drought condition with using PDSI value for current and future time period. In order to calculate PDSI values, the climatic parameters extracted from CMIP5 models and downscaled under the scenario of RCP 8.5. Also in order to understand the resilience of the agriculture activities under the climate change, this study was performed using statistical tests and data from the questionnaire completed in the statistical population of 320 farmers in the Tulare region in California. The findings of the research by t test showed that the average level of effective factors in increasing the resilience of farmers in the region is low. This is particularly significant in relation to the factors affecting government policies and support. So that only the mean of five variables is higher than the numerical desirability of the test and the other 15 variables do not have a suitable status for increasing the resilience of the farmers. Also, the results of the Vikor model showed that most of the impact on their resilience to drought and climate change was the development of agricultural insurance, the second important impact belongs to drought monitoring system, climate change and damage assessment, and variable of attention to knowledge is in third place of the important factor.


Atmosphere ◽  
2020 ◽  
Vol 11 (10) ◽  
pp. 1081 ◽  
Author(s):  
Mohammad Valipour ◽  
Sayed M. Bateni ◽  
Mohammad Ali Gholami Sefidkouhi ◽  
Mahmoud Raeini-Sarjaz ◽  
Vijay P. Singh

Understanding the trends of reference evapotranspiration (ETo) and its influential meteorological variables due to climate change is required for studying the hydrological cycle, vegetation restoration, and regional agricultural production. Although several studies have evaluated these trends, they suffer from a number of drawbacks: (1) they used data series of less than 50 years; (2) they evaluated the individual impact of a few climatic variables on ETo, and thus could not represent the interactive effects of all forces driving trends of ETo; (3) they mostly studied trends of ETo and meteorological variables in similar climate regions; (4) they often did not eliminate the impact of serial correlations on the trends of ETo and meteorological variables; and finally (5) they did not study the extremum values of meteorological variables and ETo. This study overcame the abovementioned shortcomings by (1) analyzing the 50-year (1961–2010) annual trends of ETo and 12 meteorological variables from 18 study sites in contrasting climate types in Iran, (2) removing the effect of serial correlations on the trends analysis via the trend-free pre-whitening approach, (3) determining the most important meteorological variables that control the variations of ETo, and (4) evaluating the coincidence of annual extremum values of meteorological variables and ETo. The results showed that ETo and several meteorological variables (namely wind speed, vapor pressure deficit, cloudy days, minimum relative humidity, and mean, maximum and minimum air temperature) had significant trends at the confidence level of 95% in more than 50% of the study sites. These significant trends were indicative of climate change in many regions of Iran. It was also found that the wind speed (WS) had the most significant influence on the trend of ETo in most of the study sites, especially in the years with extremum values of ETo. In 83.3% of the study sites (i.e., all arid, Mediterranean and humid regions and 66.7% of semiarid regions), both ETo and WS reached their extremum values in the same year. The significant changes in ETo due to WS and other meteorological variables have made it necessary to optimize cropping patterns in Iran.


2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Yonggang Ma ◽  
Yue Huang ◽  
Xi Chen ◽  
Yongping Li ◽  
Anming Bao

An integrated modeling system has been developed for analyzing the impact of climate change on snowmelt runoff in Kaidu Watershed, Northwest China. The system couples Hadley Centre Coupled Model version 3 (HadCM3) outputs with Snowmelt Runoff Model (SRM). The SRM was verified against observed discharge for outlet hydrological station of the watershed during the period from April to September in 2001 and generally performed well for Nash-Sutcliffe coefficient (EF) and water balance coefficient (RE). The EF is approximately over 0.8, and the water balance error is lower than ± 10%, indicating reasonable prediction accuracy. The Statistical Downscaling Model (SDSM) was used to downscale coarse outputs of HadCM3, and then the downscaled future climate data were used as inputs of the SRM. Four scenarios were considered for analyzing the climate change impact on snowmelt flow in the Kaidu Watershed. And the results indicated that watershed hydrology would alter under different climate change scenarios. The stream flow in spring is likely to increase with the increased mean temperature; the discharge and peck flow in summer decrease with the decreased precipitation under Scenarios 1 and 2. Moreover, the consideration of the change in cryosphere area would intensify the variability of stream flow under Scenarios 3 and 4. The modeling results provide useful decision support for water resources management.


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