Effect of changes in climate variables on hydrological regime of Chenab basin, western Himalaya

In high altitude, scarcely gauged basins, climate change impact assessment on river discharge is important for sustainable management of water resources. These basins are sources for irrigation, hydropower generation in the region. Expected changes in precipitation and temperature can affect the basin's hydrological regime which will have consequential impacts on the dependent sectors. For quantifying the impacts of major climatic variables on hydrological processes, this paper examined bias-corrected GCM outputs coupled with a hydrological model – HBV for Chenab basin. Trend analysis shows that precipitation would decrease after the short-term period and temperature is expected to increase throughout the century. Simulated river discharge is expected to increase throughout the 21st century under both RCP 4.5 and RCP 8.5 scenarios. It is also observed that there would be a shift in seasonal discharge pattern with increased pre- and post-monsoon contributions. Increase in snow and ice melt contribution to the overall discharge is also expected and would range between 50 and 59% until 2100. This study concluded that expected increase in discharge volume coupled with shift in seasonal discharge pattern would impact the basin water management and thus it is important to consider the impact of climate change on hydrological regime of basins.

Impact of bias correction techniques on an ensemble of seasonal discharge forecast for the Danube upstream of Vienna

<p>The skill of seasonal hydro-meteorological forecasts with a lead time of up to six months is currently limited, since they frequently exhibit random but also systematic errors. Bias correction algorithms can be applied and provide an effective approach in removing historical biases relative to observations. Systematic errors in hydrology model outputs can be consequence of different sources: i) errors in meteorological data used as input data, ii) errors in the hydrological model response to climate forcings, iii) unknown/unobservable internal states and iv) errors in the model parameterizations, also due to unresolved subgrid scale variability.</p><p>Normally, bias correction techniques are used to correct meteorological, e.g. precipitation data, provided by climate models. Only few studies are available applying these techniques to hydrological model outputs. Standard bias correction techniques used in literature can be classified into scaling-, and distributional-based methods. The former consists of using multiplicative or additive scaling factors to correct the modeled simulations, while the later methods are quantile mapping techniques that fit the distribution of the simulation to fit to the observations. In this study, the impact of different bias correction techniques on the seasonal discharge forecasts skill is assessed.</p><p>As a case study, a seasonal discharge forecasting system developed for the Danube basin upstream of Vienna, is used. The studied basin covers an area of around 100 000 km<sup>2</sup> and is subdivided in 65 subbasins, 55 of them gauged with a long historical record of observed discharge. The forecast system uses the calibrated hydrological model, COSERO, which is fed with an ensemble of seasonal temperature and precipitation forecasts. The output of the model provides an ensemble of seasonal discharge forecasts for each of the (gauged) subbasins. Seasonal meteorological forecasts for the past (hindcast), together with historical discharge observations, allow to assess the quality of the seasonal discharge forecasting system, also including the effects of different bias correction methods. The corrections applied to the discharge simulations allow to eliminate potential systematic errors between the modeled and observed values.</p><p>Our findings generally suggest that the quality of the seasonal forecasts improve when applying bias correction. Compared to simpler methods, which use additive or multiplicative scaling factors, quantile mapping techniques tend to be more appropriate in removing errors in the ensemble seasonal forecasts.</p>

Performance evaluation of global hydrological models in six large Pan-Arctic watersheds

Global Water Models (GWMs), which include Global Hydrological, Land Surface, and Dynamic Global Vegetation Models, present valuable tools for quantifying climate change impacts on hydrological processes in the data scarce high latitudes. Here we performed a systematic model performance evaluation in six major Pan-Arctic watersheds for different hydrological indicators (monthly and seasonal discharge, extremes, trends (or lack of), and snow water equivalent (SWE)) via a novel Aggregated Performance Index (API) that is based on commonly used statistical evaluation metrics. The machine learning Boruta feature selection algorithm was used to evaluate the explanatory power of the API attributes. Our results show that the majority of the nine GWMs included in the study exhibit considerable difficulties in realistically representing Pan-Arctic hydrological processes. Average APIdischarge (monthly and seasonal discharge) over nine GWMs is > 50% only in the Kolyma basin (55%), as low as 30% in the Yukon basin and averaged over all watersheds APIdischarge is 43%. WATERGAP2 and MATSIRO present the highest (APIdischarge > 55%) while ORCHIDEE and JULES-W1 the lowest (APIdischarge ≤ 25%) performing GWMs over all watersheds. For the high and low flows, average APIextreme is 35% and 26%, respectively, and over six GWMs APISWE is 57%. The Boruta algorithm suggests that using different observation-based climate data sets does not influence the total score of the APIs in all watersheds. Ultimately, only satisfactory to good performing GWMs that effectively represent cold-region hydrological processes (including snow-related processes, permafrost) should be included in multi-model climate change impact assessments in Pan-Arctic watersheds.

Seasonal discharge response to temperature-driven changes in evaporation and snow processes

This study analyses how temperature-driven changes in evaporation and snow processes influence the discharge in large river basins. Using a distributed efficient hydrological model at high spatio-temporal resolution, we investigate the relative contribution of snow and evaporation. Comparing two 10-year periods (1980s and 2010s) in the Rhine allowed to determine the contribution of changes in snow, evaporation and precipitation to the discharge. Around half of the observed changes could be explained by the changes induced by snow (11 %), evaporation (19 %) and precipitation (18 %), while 52 % was driven by a combination of these variables. Increased temperature scenarios show that seasonal changes in snow-dynamics could offset a fairly constant negative change in relative runoff induced by evaporation, but not during the melt season. This study shows how the combined effect of temperature-driven changes affect discharge. With many basins around the world depending on meltwater, correct understanding of these changes is vital.

Reasons for the homogenization of the seasonal discharges in the Yangtze River

Allocations of water discharges between dry and flood seasons along the Yangtze River have significantly homogenized during the past decades, mainly due to precipitation change, regulation of key hydraulic works on the mainstream like the Three Gorges Reservoir (TGR), and the construction of numerous dams scattered in sub-basins. To reveal the specific roles of these three major factors in changing the seasonal discharges of the whole Yangtze River, this paper analyzes daily discharges during 1961–2014 at 16 hydrological stations from the far upper reach (the Jinshajiang Reach) to the estuary. We found that precipitation has only homogenized in areas 427 km downstream of the TGR, contributing 9.5–23.6% to the homogenized discharges. Even though the TGR is the largest hydraulic works in the world, it only contributes 17.5–27.2% to the downstream homogenization of seasonal discharge. By comparison, dams in sub-regions are a major contributor (61.1–100%) in the homogenized reach either upper or lower to the TGR. Of all the sub-basins, dams in Hanjiang River basin have the most significant effect (16.9%) on changing the allocations of seasonal discharges to the sea, followed by Wujiang (11.5%), Jialingjiang (10.1%), Yalongjiang (9.4%), Qingjiang (8.4%), and Daduhe-Minjiang (4.7%) river basins.

Reconstructing the channel shifting pattern of the Torsa River on the Himalayan Foreland Basin over the last 250 years

The varied physiography, incidences of high seasonal discharge, influences of neo-tectonic activity and the young geological foundation with less consolidated cohesive and non-cohesive sediment have left the Himalayan foreland basin a formidable ground, where silt-laden rivers tend to migrate frequently. A set of maps prepared after 1764, space photographs captured in 1970 and current satellite images from 2015 and 2017 were studied to reconstruct the fluvial dynamics of the Torsa River on the foreland basin of Sikkim-Bhutan Himalaya considering a time span of nearly 250 years. Evidence collected from colonial literature, the above-mentioned satellite images and a field survey, were combined to verify results taken from the old maps used as the base of the study. The application of satellite remote sensing and analysis of the topographic signatures of the palaeo-courses in the form of the palaeo-levee, abandoned courses and ox-bow lakes were the major operational attributes in this study. As a consequence of the channel migration of Torsa River since 1764, the historical floodplain of Torsa has been topographically marked by beheaded old distributaries, a misfit channel system and the presence of abandoned segments. Morphometric changes in the old courses, major flood events and neo-tectonic activity guided an overall trend of channel migration eastwards and has led to a couple of channel oscillation events in the Torsa River over the last 250 years. The mechanism of the avulsion events was thoroughly driven by sedimentation-induced channel morphometric changes and occasional high discharge.