Comparing High Accuracy t-LiDAR and UAV-SfM Derived Point Clouds for Geomorphological Change Detection

Analysis of two small semi-mountainous catchments in central Evia island, Greece, highlights the advantages of Unmanned Aerial Vehicle (UAV) and Terrestrial Laser Scanning (TLS) based change detection methods. We use point clouds derived by both methods in two sites (S1 & S2), to analyse the effects of a recent wildfire on soil erosion. Results indicate that topsoil’s movements in the order of a few centimetres, occurring within a few months, can be estimated. Erosion at S2 is precisely delineated by both methods, yielding a mean value of 1.5 cm within four months. At S1, UAV-derived point clouds’ comparison quantifies annual soil erosion more accurately, showing a maximum annual erosion rate of 48 cm. UAV-derived point clouds appear to be more accurate for channel erosion display and measurement, while the slope wash is more precisely estimated using TLS. Analysis of Point Cloud time series is a reliable and fast process for soil erosion assessment, especially in rapidly changing environments with difficult access for direct measurement methods. This study will contribute to proper georesource management by defining the best-suited methodology for soil erosion assessment after a wildfire in Mediterranean environments.

Can we use precipitation isotope outputs of Isotopic General Circulation Models to improve hydrological modeling in large mountainous catchments on the Tibetan Plateau?

Issues related to large uncertainty and parameter equifinality have posed big challenges for hydrological modeling in cold regions where runoff generation processes are particularly complex. Tracer-aided hydrological models coupling modules to simulate the transportation and fractionation of water stable isotope are increasingly used to constrain parameter uncertainty and refine the parameterizations of specific hydrological processes in cold regions. However, commonly unavailability of site sampling of spatially-distributed precipitation isotope hampers the practical applications of tracer-aided models in large scale catchments. This study, taken the precipitation isotope data (isoGSM) derived from the Isotopic General Circulation Models (iGCM) as an example, explored its utility in driving a tracer-aided hydrological model in the Yarlung Tsangpo River basin (YTR, around 2 × 105 km2) on the Tibetan Plateau (TP). The isoGSM product was first corrected based on the biases between gridded precipitation isotope estimates and limited site sampling measurements. Model simulations driven by the corrected isoGSM data were then compared with those forced by spatially interpolated precipitation isotope from site sampling measurements. Our results indicated that: (1) spatial precipitation isotope derived from the isoGSM data helped to reduce modeling uncertainty and improve parameter identifiability in a large mountainous catchment on the TP, in comparison to a calibration method using discharge and snow cover area fraction without any information of water isotope; (2) model parameters estimated by the corrected isoGSM data presented higher transferability to nested sub-basins and produced higher model performance in the validation period than that estimated by the interpolated precipitation isotope data from site sampling measurements; (3) model calibration procedure forced by the corrected isoGSM data successfully rejected parameter sets that overestimated glacier melt contribution and gave more reliable contributions of runoff components, indicating the corrected isoGSM data served as a better choice to provide informative spatial precipitation isotope than the interpolated data from site sampling measurements at macro scale. This work suggested plausible utility of combining isoGSM data with measurements from a sparse sampling network in improving hydrological modeling in large mountainous catchments.

Spatiotemporal variability in groundwater chemistry of a mountainous catchment with complex geologic and climate gradients in south west India

Mountainous catchments are one of the world’s important water sources that sustains a major portion of global population and a rich biodiversity. The groundwater quantity and quality of mountainous watersheds are depended generally on the geologic characteristics and climate gradients. Although many groundwater studies have been carried out in the midlands and lowlands of many river basins, not enough focus has been paid to the mountainous catchments of tropics. Here we report a case study on groundwater quality and controlling factors of a mountainous catchments of the Western Ghats mountain ranges of peninsular India - the Bhavani river basin, which is identified as a testbed for long-term monitoring of the Critical Zone process. A total of 88 water samples were collected seasonally for assessing various physico-chemical parameters, solute contents and scaling properties. The results of the study revealed that the hydrochemistry of groundwater is influenced by both silicate and carbonate weathering. Mineral stability indices computed for the groundwater reveal that about 52 % of the samples are supersaturated with carbonate minerals and often exhibit scaling due to solute overloading. Among the contributing factors that determine water quality of groundwaters, chemical weathering and anthropogenic activities play a significant role.

The Effect of Total Precipitation of Various Periods to Flow Regimes in Mountainous Catchments in Japan : Considering the Geological Characteristics of Catchments

<p>In order to conduct an appropriate management in each catchment, it is important to understand how the difference in geological conditions affect the relationship between precipitation and flow regimes.</p><p>Considering the differences in geological characteristics of catchments, this study aims 1)to clarify the period for calculating the total precipitation that is most influential to several levels of daily flow respectively and 2)to clarify the contribution of the change in the total precipitation of ‘the most influential period’ to the change in flow.</p><p>In this study, 63 mountainous catchments (dam catchments) within the Japanese Archipelago were selected as target areas. First, the 63 catchments were divided into 4 groups according to their geological characteristics. Second, from the observed data of daily flow lasting 26 years (from 1993 to 2018), 6 types of daily flow which represent flow of different scales within a year (1, 10, 25, 50, 75, 95 percentiles of daily flow within a year) were searched. In each geological classification, correlation coefficients between each 6 type of flow and total precipitation of various periods (from 2 days to 365 days) were calculated. Finally, for each geological classification and each type of flow, single regression analyses were conducted, setting the rate of change in flow amount as the objective variable, and the rate of change in total precipitation amount of the appropriate period as the explanatory variable.</p><p>As a result, in the analysis of correlation coefficients, significant differences among different geological classifications were seen for lower type of flows but not for higher type of flows. For catchments of volcanic rocks in the Quaternary period, total precipitation of 365 days before the flow occurrence had the highest correlation coefficient with lower type of flows. On the other hand, for catchments of sedimentary rocks in the Mesozoic or Paleozoic era, the most influential period was approximately 45 days, which was the shortest.</p><p>Also, increasing trends in flow (i.e. the rate of change in flow > 1.0) during the target period were seen regardless of the geological classification or the type of flow. However, from the simple regression analysis, the significant effect of the change in precipitation to the change in flow was only seen for annual maximum flow of catchments of sedimentary rocks from the Mesozoic or Paleozoic era. Except this specific geological characteristic and flow type, there is a possibility that other conditions of the catchments (e.g. change in land use) have larger effect to the change in flow compared to the change in precipitation.</p><p>In the analyses mentioned above, the effect of snowfall is not considered. Therefore, in the presentation, the difference between snow covered regions and others are compared in addition.</p>

Impact and uncertainty of climate projections on Alpine catchments using high-resolution models

<p>Hydrological processes in mountainous catchments will be subject to climate change on all scales, and their response is expected to vary considerably in space. Typical hydrological studies, which use coarse climate data inputs obtained from General Circulation Models (GCM) and Regional Climate Models (RCM), focus mostly on statistics at the outlet of the catchments, overlooking the effects within the catchments. Furthermore, the role of uncertainty, especially originated from natural climate variability, is rarely analyzed. In this work, we quantified the impacts of climate change on hydrological components and determined the sources of uncertainties in the projections for two mostly natural Swiss alpine catchments: Kleine Emme and Thur. Using a two-dimensional weather generator, AWE-GEN-2d, and based on nine different GCM-RCM model chains, we generated high-resolution (2 km, 1 hour) ensembles of gridded climate inputs until the end of the 21<sup>st</sup> century. The simulated variables were subsequently used as inputs into the fully distributed hydrological model Topkapi-ETH to estimate the changes in hydrological statistics at 100-m and hourly resolutions. Increased temperatures (by 4°C, on average) and changes in precipitation (decrease over high elevations by up to 10%, and increase at the lower elevation by up to 15%) results in increased evapotranspiration rates in the order of 10%, up to a 50% snowmelt, and drier soil conditions. These changes translate into important shifts in streamflow seasonality at the outlet of the catchments, with a significant increase during the winter months (up to 40%) and a reduction during the summer (up to 30%). Analysis at the sub-catchment scale reveals elevation-dependent hydrological responses: mean annual streamflow, as well as high and low flow extremes, are projected to decrease in the uppermost sub-catchments and increase in the lower ones. Furthermore, we computed the uncertainty of the estimations and compared them to the magnitude of the change signal. Although the signal-to-noise-ratio of extreme streamflow for most sub-catchments is low (below 0.5) there is a clear elevation dependency. In every case, internal climate variability (as opposed to climate model uncertainty) explains most of the uncertainty, averaging 85% for maximum and minimum flows, and 60% for mean flows. The results highlight the importance of modelling the distributed impacts of climate change on mountainous catchments, and of taking into account the role of internal climate variability in hydrological projections.</p>

Performance and sensitivity of a spatially distributed hydrological conceptual flood model with snow components.

<p>In France, flash floods are responsible for a significant proportion of damages caused by natural hazards, either human or material. Hence, advanced modeling tools are needed to perform effective predictions. However for mountainous catchments snow modeling components may be required to correctly simulate river discharge.</p><p>This contribution investigates the implementation and constrain of snow components in the spatially distributed SMASH* platform (Jay-Allemand et al. 2020). The goal is to upgrade model structure and spatially distributed calibration strategies for snow-influenced catchments, as well as to investigate parametric sensitivity and equifinality issues. First, the implementation of snow modules of varying complexity is addressed based on Cemaneige (Valery et al. 2010) in the spatially distributed framework. Next, tests are performed on a sample of 55 catchments in the French North Alps. Numerical experiments and global sensitivity analysis enable to determine pertinent combinations of flow components (including a slow flow one) and calibration parameters. Spatially uniform or distributed calibrations using a variational method (Jay-Allemand 2020) are performed and compared on the dataset, for different model structures and constrains. These tests show critical improvements in outlet discharge modeling by adding slow flow and snow modules, especially considering spatially varying parameters. Current and future works focus on testing and improving the constrains of snow modules and calibration strategy, as well as potential validation and multiobjective calibration with snow signatures gained from in situ or satellite data. </p><p>*SMASH: Spatially-distributed Modelling and ASsimilation for Hydrology, platform developped by INRAE-Hydris corp. for operational applications in the french flood forecast system VigicruesFlash</p>

Simulating catchment scale river discharges and flood events from large scale atmospheric information: Example of the Upper Rhône River (European Alps)

<p>Floods are highly destructive natural hazards causing widespread impacts on socio-ecosystems. This hazard could be further amplified with the ongoing climate change, which will likely alter magnitude and frequency of floods. Estimating how flood regimes could change in the future is however not straightforward. The classical approach is to estimate future hydrological regimes from hydrological simulations forced by time series scenarii of weather variables for different future climate scenarii. The development of relevant weather scenarii for this is often critical. To be adapted to the critical space and time scales of the considered basins, weather scenarii are thus typically produced from climate models with downscaling models (either dynamic or statistical).</p><p>In this study, we aim to evaluate the capacity of such a simulation chain to reproduce floods observed in the upper Rhône River (10900 km², European Alps) over the last century. The modeling chain is made up of (i) the atmospheric reanalysis ERA-20C (1900-2010), (ii) the statistical downscaling model Analog, and (iii) the glacio-hydrological model GSM-SOCONT (Glacier and Snowmelt SOil CONTribution model; Schaefli et al., 2005). To assess the performance of this modeling chain, the simulated scenarii of mean areal precipitation and temperature are compared to the observed time series over the common period (1961-2010), whereas the discharge scenarii are compared to the reference time series (1920-2010).</p><p>In this presentation, we will discuss (i) the results obtained by the basic Analog method, namely a flood events underestimation due to an underestimation of extreme precipitation values, in particular 3-day and 5-day extreme precipitation, and (ii) the enhanced results obtained by the improved version of Analog SCAMP (Sequential Constructive Atmospheric Analogues for Multivariate weather Predictions; Raynaud et al., 2020) combined to the Schaake Shuffle method.</p><p>References:</p><p>Schaefli, B., Hingray, B., M. Niggli, M., Musy, A. (2005). A conceptual glacio-hydrological model for high mountainous catchments. Hydrology and Earth System Sciences Discussions, European Geosciences Union, 9, 95-109.</p><p>Raynaud, D., Hingray, B., Evin, G., Favre, A.-C., Chardon, J. (2020). Assessment of meteorological extremes using a synoptic weather generator and a downscaling model based on analogues. Hydrology and Earth System Sciences Discussions, European Geosciences Union, 24(9), 4339-4352.</p>