Detecting the Quantitative Hydrological Response to Changes in Climate and Human Activities at Temporal and Spatial Scales in a Typical Gully Region of the Loess Plateau, China

This study examined the Chabagou River watershed in the gully region of the Loess Plateau in China’s Shaanxi Province, and was based on measured precipitation and runoff data in the basin over a 52-year period (1959–2010), land-use types, normalized difference vegetation index (NDVI), and other data. Statistical models and distributed hydrological models were used to explore the influences of climate change and human activity on the hydrological response and on the temporal and spatial evolution of the basin. It was found that precipitation and runoff in the gully region presented a downward trend during the 52-year period. Since the 1970s, the hydrological response to human activities has become the main source of regional hydrological evolution. Evapotranspiration from the large silt dam in the study area has increased. The depth of soil water decreased at first, then it increased by amount that exceeded the evaporation increase observed in the second and third change periods. The water and soil conservation measures had a beneficial effect on the ecology of the watershed. These results provide a reference for water resource management and soil and water conservation in the study area.

INTEGRATION OF A GIS AND HEC-HMS MODELING TO IMPROVE URBAN RESILIENCE TO FLOOD RISK IN ALGIERS. ALGERIA

The study of the phenomenon of flooding in an urban environment requires the integration of the city in its physical context, in this case the entire impluvium. Thus, the consideration of all the hydrological, morphometric and physical characteristics (topography, lithology, land cover...). In order to put in place appropriate measures to improve urban resilience and protect the population and their property in the capital of Algeria (City of Algiers), a hydrological modeling must be carried out upstream to evaluate the hydrological response of the watershed. This modeling was done using the auxiliary tool HEC-GEO HMS, an extension that works in a GIS environment (ArcGIS).

Spatial Delimitation of Small Headwater Catchments and Their Classification in Terms of Runoff Risks

The hydrological similarity of catchments forms a basis for generalizing their hydrological response. This similarity of the hydrological response enables catchments to be classified from numerous perspectives, e.g., hydrological extremes or ecological aspects of catchments. A specific group is formed by so-called “first-order catchments”. This article describes the derivation process of small headwater catchments up to 5 km2 in size on the territory of the Czech Republic. The delimitation is based on the digital terrain model, the stream network, and the water reservoirs. The catchments derived in this way cover 80% of the country. Five mutually independent and sufficiently representative parameters were selected with Principal Components Analysis (PCA), and were used for the cluster analysis performed on two to eight clusters. Clustering Validity Indices (CVI) was used to determine the optimal number of clusters. Subsequently, each generated cluster was assessed for the potential risk of the occurrence of direct runoff, in five classes, on a scale from a moderate degree of risk to a high degree of risk. Six clusters were generated, which is the optimal number in terms of the CVI and their hydrological properties. In this case, 17% of the Czech Republic territory is assessed as lying within a high-risk area, 39% as lying within a medium-risk area, and 24% as lying within a below-average risk area in terms of the occurrence of direct runoff.

Quantifying the Impact of Future Climate Change on Runoff in the Amur River Basin Using a Distributed Hydrological Model and CMIP6 GCM Projections

The Amur River is one of the top ten longest rivers in the world, and its hydrological response to future climate change has been rarely investigated. In this study, the outputs of four GCMs in the Coupled Model Intercomparison Project Phase 6 (CMIP6) were corrected and downscaled to drive a distributed hydrological model. Then, the spatial variations of runoff changes under the future climate conditions in the Amur River Basin were quantified. The results suggest that runoffs will tend to increase in the future period (2021–2070) compared with the baseline period (1961–2010), particularly in August and September. Differences were also found among different GCMs and scenarios. The ensemble mean of the GCMs suggests that the basin-averaged annual precipitation will increase by 14.6% and 15.2% under the SSP2-4.5 and SSP5-8.5 scenarios, respectively. The increase in the annual runoff under the SSP2-4.5 scenario (22.5%) is projected to be larger than that under the SSP5-8.5 scenario (19.2%) at the lower reach of the main channel. Future climate changes also tend to enhance the flood peak and flood volume. The findings of this study bring new understandings of the hydrological response to future climate changes and are helpful for water resource management in Eurasia.

Seasonal flow forecasting in Africa; exploratory studies for large lakes

For many applications, it would be extremely useful to have insights into river flows at timescales of a few weeks to months ahead. However, seasonal predictions of this type are necessarily probabilistic which raises challenges both in generating forecasts and their interpretation. Despite this, an increasing number of studies have shown promising results and this is an active area for research. In this paper, we discuss insights gained from previous studies using a novel combined water balance and data-driven approach for two of Africa's largest lakes, Lake Victoria and Lake Malawi. Factors which increased predictability included the unusually long hydrological response times and statistically significant links to ocean-atmosphere processes such as the Indian Ocean Dipole. Other lessons learned included the benefits of data assimilation and the need for care in the choice of performance metrics.

Integrating Remote and In-Situ Data to Assess the Hydrological Response of a Post-Fire Watershed

Forest fire is a common concern in Mediterranean watersheds. Fire-induced canopy mortality may cause the degradation of chemical–physical properties in the soil and influence hydrological processes within and across watersheds. However, the prediction of the pedological and hydrological effect of forest fires with heterogenous severities across entire watersheds remains a difficult task. A large forest fire occurred in 2017 in northern Italy providing the opportunity to test an integrated approach that exploits remote and in-situ data for assessing the impact of forest fires on the hydrological response of semi-natural watersheds. The approach is based on a combination of remotely-sensed information on burned areas and in-situ measurements of soil infiltration in burned areas. Such collected data were used to adapt a rainfall–runoff model over an experimental watershed to produce a comparative evaluation of flood peak and volume of runoff in pre- and post-fire conditions. The model is based on a semi-distributed approach that exploits the Soil Conservation Service Curve Number (SCS-CN) and lag-time methods for the estimation of hydrological losses and runoff propagation, respectively, across the watershed. The effects of fire on hydrological losses were modeled by adjusting the CN values for different fire severities. Direct infiltration measurements were carried out to better understand the effect of fire on soil infiltration capacity. We simulated the hydrological response of the burned watershed following one of the most severe storm events that had hit the area in the last few years. Fire had serious repercussions in regard to the hydrological response, increasing the flood peak and the runoff volume up to 125% and 75%, respectively. Soil infiltration capacity was seriously compromised by fire as well, reducing unsaturated hydraulic conductivity up to 75% compared with pre-fire conditions. These findings can provide insights into the impact of forest fires on the hydrological response of a whole watershed and improve the assessment of surface runoff alterations suffered by a watershed in post-fire conditions.