Temperature trends and elevation dependent warming during 1965–2014 in headwaters of Yangtze River, Qinghai Tibetan Plateau

Stoch Environ Res Risk Assess

Wang

Booij

et al. 2021

Self Cite

The present study explored the changes in monthly stream ow in the Hindukush-Karakoram-Himalaya (HKH) region within Pakistan using the recently developed trend analysis method known as Innovative Polygon Trend Analysis (IPTA). The monthly stream ow data of 34 gauging stations installed in the HKH region was analyzed, and the Pettitt test was applied to check the homogeneity of the time series. The entire study area was divided into 13 sub-basins, and then changes in monthly stream ow of each subbasin were explored using the IPTA method. The stream ow of high elevated glaciated and snow/icecovered sub-basins (e.g., Shyok, Astore, and Chitral) have increased in high ow months (June-August), where there is a downward trend for the Hunza sub-basin in these months. In the Gilgit sub-basin, a transition occurred from no trend in May to a decreasing trend from June to August. The upstream gauges of Swat and Kabul sub-basins showed an increasing trend throughout the year, while downstream gauging stations in the same sub-basins exhibited a strong decreasing trend only in high ow months (June-August). The upper reaches of the Indus part in the Upper Indus Basin (UIB) showed increasing trends in high ow months (June-August), however the downstream gauges of UIB showed decreasing trends throughout the year. Overall, only the glaciated and snow/ice-covered sub-basins experienced increasing trends, while most other sub-basins faced decreasing trends in high ow months and increasing trends in low ow months (October -March). The enhancement of the seasonal pattern of stream ow in the upper reaches of UIB is possibly due to the melting of snow and ice that potentially in uence oods and hydropower generation. The results of this study can result in a better understanding of the hydrology of the HKH region and support sustainable water management.

Section: Introductionmentioning

confidence: 96%

Changes in monthly streamflow in the Hindukush–Karakoram–Himalaya Region of Pakistan using innovative polygon trend analysis

Stoch Environ Res Risk Assess

Wang

Booij

et al. 2021

Self Cite

“…The length of the Yangtze River is 6300 km making it the longest river in China and third-longest in the world. The catchment area upstream of the Zhimenda hydrological station is referred to as the Yangtze River Source Region (YRSR), located in the middle of the Qinghai-Tibetan Plateau [41]. The average elevation of YRSR is 4500 m above sea level, and it is located between longitudes 90 50 N. The YRSR catchment area is 137,000 km 2 , which is 7.6% of the total area of the Yangtze River Basin and it contributed 20% to the total volume of water of Yangtze River Basin.…”

Section: Catchment Areamentioning

confidence: 99%

“…Water resources planning and management can be tuned towards the significant driver of streamflow changes towards a more balanced and sustainable ecosystem [40]. We assumed that as the YRSR is located in the Qinghai Tibetan Plateau and, being hotspot of the climate change outside the polar region [41], the main driver of attribution in changes in streamflow is climate change rather than land cover in this region. Moreover, the quantifications of variations in the streamflow for this region simulated by a distributed hydrological model (i.e., SWAT model) have not been investigated so far in this region.…”

Section: Introductionmentioning

confidence: 99%

Attribution of Changes in Streamflow to Climate Change and Land Cover Change in Yangtze River Source Region, China

Wang

Lü

et al. 2022

Water

Self Cite

The quantitative attribution of changes in streamflow to climate change (CC) and land cover change (LCC) for the Yangtze River Source Region (YRSR), China, was assessed. We used a combination of the SWAT model along with the statistical technique one factor at a time (OFAT) and innovative trend analysis (ITA) to achieve the study objectives. The climate and hydrology data from 1961 to 2016 and land-cover maps of 5 years’ difference from 1985 to 2015 were used. The model was calibrated (1964–1989) using a land-cover map of 1985 and validated for 1990–2016. This validated model was further validated for all other land-cover maps used in this study. The SWAT model simulation showed that streamflow had been significantly influenced by CC compared to LCC using land-cover maps of 1985–1990, 1990–1995. However, the SWAT model simulations did not result in further changes in streamflow for land cover maps of 2000–2005, 2005–2010, and 2010–2015 because there have not been any significant changes in land cover after 2000 while the main contributing factor was climate change. The SWAT model simulations showed that the main driver of changes in streamflow in the Yangtze River Source Region is climate change. This study shows that the individual impacts are more critical than combined impacts for designing hydraulic structures, water resources planning and management, and decision-making policies at the regional/basin scale.

“…To provide the rainfall depths for the entire catchment, daily rainfall values were averaged for each catchment using the Thiessen polygon method (Thiessen 1911). This is a simple and practical method to compute average values of an area based on weighting stations (Ahmed et al 2020a(Ahmed et al , 2020b. However, we found that the mean elevations of the Thiessen stations were different from the mean elevations of the catchments.…”

Section: Hydrometeorological Datamentioning

confidence: 99%

Quantifying relative contribution of land use change and climate change to streamflow alteration in the Bengawan Solo River, Indonesia

Marhaento

Booij

Hydrological Sciences Journal

2021

Self Cite

This study investigated the influence of land use change and climate change on changes in streamflow in the Bengawan Solo River (BSR, 16 389 km 2 ) basin, Indonesia. We applied the excess water and energy approach to three tributaries of the BSR, namely Pidekso, Madiun and Kening rivers, which represent the up-, mid-, and downstream parts of the BSR, respectively. This study used hydrological data from 1982−2013 and land use data for the years 1994 and 2013. The results show that from 1982 to 2013, the annual streamflow of the Pidekso and Madiun River increased, while in the Kening River it decreased. Based on attribution measures, the increasing streamflow trend in the Pidekso and Madiun rivers is mainly attributed to land use change, while the decreasing streamflow trend in the Kening River is mainly attributed to climate change. These conclusions are supported by statistical analyses and land use change analysis.