Hydro-climatic aspects of Indus River flow propagation

You

Intl Journal of Climatology

et al. 2018

This study uses the daily maximum and minimum temperature data sets of 48 meteorological stations to assess the observed changes in temperature extremes over China–Pakistan Economic Corridor (CPEC) during 1980–2016. The nonparametric Mann–Kendall, Sen's slope estimator, least squares method, and two‐tailed simple t‐test methods were used to assess the trend in nine temperature extreme indices. The results of the study indicated that the trends in annual mean anomalies of cold nights, cold days, and frost days significantly decreased at the rates of −1.09, −1.58, and −1.05 day/decade, respectively. The number of warm nights, warm days, and summer days exhibited significant positive trends at the rates of 1.49, 1.04, and 4.32 day/decade, respectively. In addition, the trends of the warmest day and coldest day also increased significantly at the rates of 0.45 and 0.51 °C/decade, respectively. The trend of diurnal temperature range decreased significantly with −0.35 °C/decade. The spatial distribution of temperature extreme indices indicated that the number of cold nights, cold days, and diurnal temperature range have been decreased, while the trends of warm nights, warm days, summer days, warmest day, and coldest day have been increased over the whole country. Large‐scale atmospheric circulation changes derived from ERA‐Interim reanalysis show that a weak (strong) wind pressure, increasing (decreasing) geopotential height, and rapid warming (cooling) over the northern (southern) region have contributed to the changes in temperature extremes in Pakistan to some extent. With respect to elevation‐dependent warming (EDW), the trends of cold nights, warm days, summer days, warmest day, and diurnal temperature range showed significant positive correlations with increasing elevation. However, the trends of cold days, warm nights, frost days, and coldest day showed significant negative relationships with increasing elevation. The findings of this study will be helpful in the adaptation of climate change and mitigation of climatological disasters in the region. The study recommends that future studies should investigate the natural and anthropogenic drivers of temperature extremes and the possible mechanism of EDW in the CPEC region.

Section: Elevation-dependent Warmingmentioning

confidence: 99%

Observed changes in temperature extremes over China–Pakistan Economic Corridor during 1980–2016

You

Intl Journal of Climatology

et al. 2018

“…The intensity and annual pattern (illustrates the twelve-month cycle) of temperature of Chitral, Gilgit, Skardu (Fig. 4 & 5b) supports the regional regular snow-glacier melts runoff [15]. These seasonal/annual variations of rainfall and temperature influence the regional river flow can be analysed by ACF and PACF analyses.…”

Section: Methodsmentioning

confidence: 53%

“…6a). In comparison with the same of the Indus river flow at Tarbela station [15] shows sustainable roll off pattern (Fig. 9), ( [15] the reference there in Fig.…”

Section: Proficiency Of the Modelmentioning

confidence: 71%

See 1 more Smart Citation

Impact Assessment of Hydroclimatic and Stochastic Variations on Water Stress of Jhelum River Flow Forecast

Hassan¹,

Nazia²

2019

ijSciences

The hydrological system of a country significantly influences the ecological, agricultural and consequently the economic structure. Since, the accessibility of water resources has governed the power generation sector and agronomic establishments of the region like Pakistan. Moreover, Pakistan is sensitive in climatic variation and faces gradually higher threats regarding rainfall variability, floods and prolonged droughts. Sometimes, these climate change impact embedded with the high frequency and strength of extreme events caused by global warming. These extreme situations occur mostly in the hydrological phase that occurs because of the unexpected variations in temperature and rainfall. UN-ICC report pronounces that Pakistan is in top four unsafe countries that are undesirably affected by climate variability. The water stress Index established by Mallin Falkenmark conferred that Pakistan is in the list of countries that can face serious scarcity of water as its population is continuously increasing and water resources are shrinking. A perfect assessment of upcoming water resources under fluctuating climatic situations is significant for water resource availability and management. This study analyses the impact of hydroclimatic and stochastic conditions of river flow prediction and forecast of Jhelum River flow at Mangla station (second major reservoir of Pakistan, serve about 6 million hectares of cultivated area and generating 6% (about 1000MW) of the country's electrical power generation). Forecasting of river flow is helpful in understanding the prevailing situation of climate variations. The preliminary analysis of 34 years monthly data (Jan. 1976 to December 2010) of river flow, temperature and precipitation indicates that the precipitation of the seasonal and monsoon rainfall (June to September) is dominant on the yearly cycle. During these months the temperature rise is at its year maximums, so, the melting of snow/glaciers contributes a large amount of water in the natural river flow. The autocorrelation function (ACF) shows a strong seasonal variation of river flow, correlation analysis shows that the strong contribution of monsoon and orographic regular runoff is significant. To include the embedded periodic variation of the river flow, seasonal autoregressive moving average (SARIMA) will be used to predict and forecast the river flow. Additionally, the stepwise linear regression is applied to analysis the regular flow along with climatic variations by multiple linear regression show good results and will be helpful in forecasting of the river flow on monthly and annual basis. However, the reduce prediction and forecast accuracy shows that the inconsistence stochastic and hydroclimatic influenced river flows variation from the last 20 years, may be caused by Global and local impact. The results of this study are hoped to contribute considerably in current and future hydrological researches and studies, particularly in the Jhelum River flow at Mangla station of Pakistan.

“…The arena of problems like correct assessment, proper storage, reliable control and judicious distribution of existing water masses among various provinces/regions within Pakistan is properly encompassed by technical research and mathematical modelling. Keeping in view the preliminary local climatic analyses as presented in Hassan and Ansari (2015) and linear and nonlinear analyses performed in Hassan and Ansari, (2010), and Hassan (2011) [1][2][3][4][5], this paper assess the impact of climatic parameters (Temperature & Rainfall) on mean 10daily river flow (TDF) along the Indus River.…”

Section: Introductionmentioning

confidence: 99%

Modelling Space-time Propagation of Climate Sensitive Variation in the Indus River Flow

Hassan¹

2019

ijSciences

The linear and nonlinear analyses of the impacts of local climatic parameters on Indus River flows as discussed in [1] and [2] gives provision to investigate the influential role of the regional climatic parameters. For this purpose this paper simulates the Indus River flow network using exponentially distributed river network (SRN) feed by employs synthetically generated local temperature and rainfall dependent runoffs. The local temperature and rainfall is generated using the stochastic, autoregressive and Poisson process methods respectively. To explore the influential role, the sensitivity analyses are performed by changing the local climatic parameter values. This demonstrates the existence of relation between the variability of temperature and rainfall on the river flow in the form of linear and nonlinear information and its propagation along the network. In the mean 10daily flow (TDF) propagation the dominant precipitation characteristic is linear. It is to be saying that the temperature variations make some way of only nonlinear behaviour in the TDF propagation. Accordingly, it explores the impact of local climatic parameters on the river flow and its propagation in the form of linear and nonlinear information.