Quantifying the impacts of land cover change on hydrological responses in the Mahanadi river basin in India

The objective of this study is to assess the impacts of land cover change on the hydrological responses of the Mahanadi river basin, a large river basin in India. Commonly, such assessments are accomplished by using distributed hydrological models in conjunction with different land use scenarios. However, these models, through their complex interactions among the model parameters to generate hydrological processes, can introduce significant uncertainties to the hydrological projections. Therefore, we seek to further understand the uncertainties associated with model parameterization in those simulated hydrological responses due to different land cover scenarios. We performed a sensitivity-guided model calibration of a physically semi-distributed model, the Variable Infiltration Capacity (VIC) model, within a Monte Carlo framework to generate behavioural models that can yield equally good or acceptable model performances for subcatchments of the Mahanadi river basin. These behavioural models are then used in conjunction with historical and future land cover scenarios from the recently released Land-Use Harmonization version 2 (LUH2) dataset to generate hydrological predictions and related uncertainties from behavioural model parameterization. The LUH2 dataset indicates a noticeable increase in the cropland (23.3 % cover) at the expense of forest (22.65 % cover) by the end of year 2100 compared to the baseline year, 2005. As a response, simulation results indicate a median percent increase in the extreme flows (defined as the 95th percentile or higher river flow magnitude) and mean annual flows in the range of 1.8 % to 11.3 % across the subcatchments. The direct conversion of forested areas to agriculture (of the order of 30 000 km2) reduces the leaf area index, which subsequently reduces the evapotranspiration (ET) and increases surface runoff. Further, the range of behavioural hydrological predictions indicated variation in the magnitudes of extreme flows simulated for the different land cover scenarios; for instance, uncertainty in scenario labelled “Far Future” ranges from 17 to 210 m3 s−1 across subcatchments. This study indicates that the recurrent flood events occurring in the Mahanadi river basin might be influenced by the changes in land use/land cover (LULC) at the catchment scale and suggests that model parameterization represents an uncertainty which should be accounted for in the land use change impact assessment.

Impacts of Agricultural Areas on Spatio-Temporal Variability of Daily Minimum Extreme Flows during the Transitional Seasons (Spring and Fall) in Southern Quebec

Several statistical methods were used to analyze the spatio-temporal variability of daily minimum extreme flows (DMEF) in 17 watersheds—divided into three homogenous hydroclimatic regions of southern Quebec—during the transitional seasons (spring and fall), during the 1930–2019 period. Regarding spatial variability, there was a clear difference between the south and north shores of the St. Lawrence River, south of 47° N. DMEF were lower in the more agricultural watersheds on the south shore during transitional seasons compared to those on the north shore. A correlation analysis showed that this difference in flows was mainly due to more agricultural areas ((larger area (>20%) on the south than on the north shore (<5%)). An analysis of the long-term trend of these flows showed that the DMEF of south-shore rivers have increased significantly since the 1960s, during the fall (October to December), due to an increase in rainfall and a reduction in cultivated land, which increased the infiltration in the region. Although there was little difference between the two shores in the spring (April to June), we observed a decrease in minimum extreme flows in half (50%) of the south-shore rivers located north of 47° N.

Quantifying the impact of land cover changes on hydrological responses in India

The objective of this study is to assess the impacts of Land Use Land Cover change on the hydrological responses of the Mahanadi river basin, a large river basin in India. Commonly, such assessments are accomplished by using distributed hydrological models in conjunction with different land use scenarios. However, these models through their complex interactions among the model parameters to generate hydrological processes, can introduce significant uncertainties to the hydrological projections. Therefore, we seek to further understand the uncertainties associated with model parameterization in those simulated hydrological responses due to different land cover scenarios. We performed a sensitivity-guided model calibration of a physically semi-distributed model, the Variable Infiltration Capacity (VIC) within a Monte Carlo Framework to generate behavioural models for subcatchments of the Mahanadi river basin. These behavioural models are then used in conjunction with historical and future land cover scenarios from the recently released, Land use Harmonisation (LUH2) to generate hydrological predictions and related uncertainties from behavioural model parameterisation. The LUH2 dataset indicates a noticeable increase in the cropland (23.3 % cover) at the expense of forest (22.65 % cover) by the end of year 2100 compared to the baseline year, 2005. As a response, simulation results indicate a median percent increase in the extreme flows (defined as the 95th percentile or higher river flow magnitude) and mean annual flows in the range of 1.8 to 11.3 % across the subcatchments. The direct conversion of forested areas to agriculture (on the order of 30,000 km2) reduces the Leaf Area Index and which subsequently reduces the Evapotranspiration (ET) and increases surface runoff. Further, the range of behavioural hydrological predictions indicated variation in the magnitudes of extreme flows simulated for the different land cover scenarios, for instance uncertainty in far future scenario ranges from 17 to 210 cumecs across subcatchments. This study indicates that the recurrent flood events occurring in the Mahanadi river basin might be influenced by the changes in LULC at the catchment scale and suggests that model parameterisation represents an uncertainty, which should be accounted for in the land-use change impact assessment.

Extreme flow variability analysis at the Bianouan hydrometric station on the Bia River watershed in Côte d'Ivoire

Extreme hydrological phenomena recurrence in West Africa in recent decades is a problem in the anthropized watershed management. Link analysis between extreme hydrological phenomena and climate variability is necessary to guard against their consequences. However, qualitative data accessing difficulties and explanatory variable definition of extremes hydrological phenomena limit extreme flows rate studies. This study proposes the analysis the variability of the floods and the low flows at the Bianouan hydrometric station. Thus, five (5) floods characteristics variables (QCX5, QXJA, F90p, F95p and F99p) and three (3) for, the low flows (VCN10, QJNA and F10p) were extracted daily flows from the Bianouan hydrometric station from 1 January 1962 to 31 December 2005. The variability of these extremes has been studied by the trend analysis (linear regression) and of the stationarity (Pettitt and Hubert tests). The results show that for flood variables the negative trend is very significant and ruptures are observed in 1980. For low flow variables the negative trend is significant and the ruptures are observed in 1981. From this study, we can deduce that the ruptures observed in the rains and flows average in the end 1960s and early 1970s have affected later the extreme flows around the 1980s.

Flood hazard in Slovenia and assessment of extreme design floods

Due to the lack of hydrological measurements in the torrential areas and smaller catchment areas of Slovenian rivers, in accordance with the European Floods Directive, we used an empirical equation to estimate the magnitude of a 500-year flood (Q500). In this paper, we critically evaluate the proposed empirical equations for estimating the Q500 discharge, as defined in the Slovenian Rules on the methodology for determining areas at risk of floods and related erosion of inland waters and the sea, and on the method of classifying land into risk classes. In this assessment, we use publicly available measured data from Slovenia’s hydrological monitoring network and data on extreme flows for selected Slovenian high dams, and thus compare the database with empirical equations for determining extreme flows in Europe and elsewhere in the world that are used for planning high dams. Although the reach of the Q500 flood line determines the area of residual flood danger, it makes sense to abandon the determination of extreme flows in Slovenia using empirical equations and move to a hydrological-hydraulic modelling system using modern software tools.

Climate Change Impacts on Extreme Flows Under IPCC RCP Scenarios in the Mountainous Kaidu Watershed, Tarim River Basin

In the 21st century, heavier rainfall events and warmer temperatures in mountainous regions have significant impacts on hydrological processes and the occurrence of flood/drought extremes. Long-term modeling and peak flow detection of streamflow series are crucial in understanding the behavior of flood and drought. This study was conducted to analyze the impacts of future climate change on extreme flows in the Kaidu River Basin, northwestern China. The soil water assessment tool (SWAT) was used for hydrological modeling. The projected future precipitation and temperature under Intergovernmental Panel on Climate Change (IPCC) representative concentration pathway (RCP) scenarios were downscaled and used to drive the validated SWAT model. A generalized extreme value (GEV) distribution was employed to assess the probability distribution of flood events. The modeling results showed that the simulated discharge well matched the observed ones both in the calibration and validation periods. Comparing with the historical period, the ensemble with 15 general circulation models (GCMs) showed that the annual precipitation will increase by 7.9–16.1% in the future, and extreme precipitation events will increase in winter months. Future temperature will increase from 0.42 °C/10 a to 0.70 °C/10 a. However, with respect to the hydrological response to climate change, annual mean runoff will decrease by 21.5–40.0% under the mean conditions of the four RCP scenarios. A reduction in streamflow will occur in winter, while significantly increased discharge will occur from April to May. In addition, designed floods for return periods of five, 10 and 20 years in the future, as predicted by the GEV distribution, will decrease by 3–20% over the entire Kaidu watershed compared to those in the historical period. The results will be used to help local water resource management with hazard warning and flood control.