Reconstruction of Incomplete Data Sets orImages Using Direct Sampling

With increasingly sophisticated acquisition methods, the amount of data available for mapping physical parameters in the geosciences is becoming enormous. If the density of measurements is sufficient, significant non-parametric spatial statistics can be derived from the data. In this context, we propose to use and adapt the Direct Sampling multiple-points simulation method (DS) for the reconstruction of partially informed images. The advantage of the proposed method is that it can accommodate any data disposition and that it can indifferently deal with continuous and categorical variables. The spatial patterns found in the data are mimicked without model inference. Therefore, very few assumptions are required to define the spatial structure of the reconstructed fields, and very limited parameterization is needed to make the proposed approach extremely simple from a user perspective. The different examples shown in this paper give appealing results for the reconstruction of complex 3D geometries from relatively small data set

High resolution multi-facies realizations of sedimentary reservoir and aquifer analogs

Geological structures are by nature inaccessible to direct observation. This can cause difficulties in applications where a spatially explicit representation of such structures is required, in particular when modelling fluid migration in geological formations. An increasing trend in recent years has been to use analogs to palliate this lack of knowledge, i.e., exploiting the spatial information from sites where the geology is accessible (outcrops, quarry sites) and transferring the observed properties to a study site deemed geologically similar. While this approach is appealing, it is difficult to put in place because of the lack of access to well-documented analog data. In this paper we present comprehensive analog data sets which characterize sedimentary structures from important groundwater hosting formations in Germany and Brazil. Multiple 2-D outcrop faces are described in terms of hydraulic, thermal and chemical properties and interpolated in 3-D using stochastic techniques. These unique data sets can be used by the wider community to implement analog approaches for characterizing reservoir and aquifer formations

Analog-based meandering channel simulation

Characterizing the complex geometries and the heterogeneity of the deposits in meandering river systems is a long-standing issue for the 3-D modeling of alluvial formations. Such deposits are important sources of accessible groundwater in alluvial aquifers throughout the world and also play a major role as hydrocarbons reservoirs. In this paper, we present a method to generate meandering river centerlines that are stochastic, geologically realistic, connected, and conditioned to local observations or global geomorphological characteristics. The method is based on fast 1-D multiple-point statistics in a transformed curvilinear domain: the succession in directions observed in a real-world meandering river (the analog) is considered as statistical model for multiple-point statistics simulation. The integration of local data is accomplished by an inverse procedure ensuring that the channels pass through a given set of locations while conserving the high-order spatial characteristics of an analog. The methodology is applied on seven real-world case studies. This work demonstrates the flexibility and the applicability of multiplepoint statistics outside the standard paradigm that considers the simulation of a 2-D or 3-D variable with spatial coordinates

Impacts of land use land cover change and climate change on river hydro-morphology- a review of research studies in tropical regions

Tropical regions have experienced the fastest Land Use Land Cover Change (LULCC) in the last decades, coupled with climate change (CC) this has affected the hydrological and geomorphological processes of river systems. With the increased demand for land, the general trend has been the loss of forest land to agriculture and settlements. These changes have altered the water balance components through enhanced or reduced evaporation, peak flow, flooding, and river morphology. The aim of this review paper is to provide a meta-analysis on the effects of spatiotemporal changes in climate and LULC on river hydro-morphology in the tropics. Following a systematic search, 60 case studies were identified, of which the majority (68%) experienced forest loss due to agricultural and urban expansion, resulting in increased streamflow, surface flow, and total water yield and decreased ET and groundwater recharge. 12% of the case studies showed the impacts of LULCC on channel morphology features through sediment transport and riverbank erosion. Results from this study show limited correlation between LULCC and hydrological variables, indicating that there are likely other factors controlling hydrological processes. Catchment heterogeneity including soil and topography play an important role. Based on studies that project these changes into the future, similar trends are expected over the next decades, with differences based on LU and climate scenarios. There are still limited studies on river hydro-morphology responses to LULCC and CC in the tropics despite the major changes taking place there. In light of future changes, more studies are needed to improve our understanding

Ice Dynamics and Morphological Changes During Proglacial Lake Development at Exploradores Glacier, Patagonia

Proglacial lakes are ubiquitous features formed during deglaciarization and are currently increasing in number in Patagonia and elsewhere. Proglacial lakes can affect glacier dynamics, catchment hydrology and have the potential to cause glacial lake outburst floods. Therefore, monitoring the onset and development of proglacial lake formation is relevant to understand glacial processes and anticipate glacier response to climate change. In this study, we integrate geomorphological and ice-dynamic information to assess proglacial lake development in Exploradores Glacier, Chilean Patagonia. We monitor recent spatial and temporal changes in the lower trunk of Exploradores Glacier (10 km2) to provide a 20-year observation record by combining eight uncrewed aerial vehicles (UAV) surveys between 2019 and 2020, with high-medium resolution satellite imagery (Rapid Eye and Landsat) between 2000 and 2018. We use feature tracking techniques, digital surface elevation model analysis and field data to create a multi-temporal scale (inter-annual and seasonal) and a multi-spatial (cm to km) data set. Our analysis shows that surface velocity overall trend has not changed over the last 20 years and that surface velocity near the terminus is significant (>10 m a−1). Moreover, an exceptional advance over moraine deposits was detected. We also found low downwasting rates (<0.5 m a−1) close to the glacier terminus which are attributed to sufficient ice flux and the insulation effect of the debris-covered surface. However, hundreds of supraglacial ponds were observed and are currently coalescing and expanding by ice-cliff backwasting favoring glacier disintegration. Lastly, it was found that calving losses at the east marginal lake equaled ice-flux input into the lake for the UAV monitored period. This study contributes to a better understanding of glacial lake dynamics during proglacial lake development, and our results may help ice modelling efforts to predict glacier response to future climate scenarios

Potential of satellite and reanalysis evaporation datasets for hydrological modelling under various model calibration strategies

Twelve actual evaporation datasets are evaluated for their ability to improve the performance of the fully distributed mesoscale Hydrologic Model (mHM). The datasets consist of satellite-based diagnostic models (MOD16A2, SSEBop, ALEXI, CMRSET, SEBS), satellite-based prognostic models (GLEAM v3.2a, GLEAM v3.3a, GLEAM v3.2b, GLEAM v3.3b), and reanalysis (ERA5, MERRA-2, JRA-55). Four distinct multivariate calibration strategies (basin-average, pixel-wise, spatial bias-accounting and spatial bias-insensitive) using actual evaporation and streamflow are implemented, resulting in 48 scenarios whose results are compared with a benchmark model calibrated solely with streamflow data. A process-diagnostic approach is adopted to evaluate the model responses with in-situ data of streamflow and independent remotely sensed data of soil moisture from ESA-CCI and terrestrial water storage from GRACE. The method is implemented in the Volta River basin, which is a data scarce region in West Africa, for the period from 2003 to 2012. Results show that the evaporation datasets have a good potential for improving model calibration, but this is dependent on the calibration strategy. All the multivariate calibration strategies outperform the streamflow-only calibration. The highest improvement in the overall model performance is obtained with the spatial bias-accounting strategy (+29%), followed by the spatial bias-insensitive strategy (+26%) and the pixel-wise strategy (+24%), while the basin-average strategy (+20%) gives the lowest improvement. On average, using evaporation data in addition to streamflow for model calibration decreases the model performance for streamflow (-7%), which is counterbalance by the increase in the performance of the terrestrial water storage (+11%), temporal dynamics of soil moisture (+6%) and spatial patterns of soil moisture (+89%). In general, the top three best performing evaporation datasets are MERRA-2, GLEAM v3.3a and SSEBop, while the bottom three datasets are MOD16A2, SEBS and ERA5. However, performances of the evaporation products diverge according to model responses and across climatic zones. These findings open up avenues for improving process representation of hydrological models and advancing the spatiotemporal prediction of floods and droughts under climate and land use changes