Flood hazard on the Upper Angara river

The article provides the results of studies on flooding in the rivers of the northern Baikal on the example of the Upper Angara river basin. Some information about the situation with floods and mudflows in the dynamics since 1933 is highlighted. Spatial and temporal patterns of maximum levels, water discharge, duration of high levels, intensity of the water rise have been studied using standard methods of processing hydrological information to assess risks and hazard. On the basis of long-term observation series, expedition surveys we considered classification geohydrological characteristics of floods by genesis of their formation, recurrence of extreme levels, intensity and depth of floodplain inundation. The areas of possible flooding and waterlogging have been determined on the basis of large-scale maps using GIS technologies using ArcGIS. Settlements and infrastructure facilities located in hazardous areas have been identified. Engineering measures to mitigate flood risks in the Upper Angara river have been proposed.

An Agent-Based Model for Simulating Irrigated Agriculture in the Samambaia Basin in Goiás

Agriculture is one of the main economic activities in Brazil. The intensive use of water for irrigated agriculture leads to water rise demand contributing to increase water stress. Agent-based models help assess this problem with promising applications entailing an organizing principle to inform us of how to view a real-world system and effectively build a model. In this work, agent-based modeling is applied to simulate water usage for irrigation in agricultural production in the Samambaia river basin in the municipality of Cristalina in the Goias state of Brazil. The use of real data enables analysis of resource availability in a scenario with high demand irrigation, allowing a greater understanding of the needs of the parties involved.

Monitoring of Ground Movements Due to Mine Water Rise Using Satellite-Based Radar Interferometry—A Comprehensive Case Study for Low Movement Rates in the German Mining Area Lugau/Oelsnitz

In terms of its history and complexity, the Lugau/Oelsnitz mining area is a representative example of many hard coal fields in Europe. The special characteristic, however, is the low water inflow and the associated long flooding process with corresponding low and long-ongoing ground movements. In order to ensure the long-term monitoring of ground movements in the future, an adapted and cost-effective concept based on modern methods should be implemented. The today widely used radar interferometry, is well established as a method but the results offer many possibilities for interpretation, which one should be aware of in order to derive reliable information. Presented are the results of a complex interferometric evaluation, based on Sentinel-1 data from different orbits, and an analysis of the spatiotemporal characteristic of ground movements. The focus of this paper is a detailed presentation of the workflow and an application-related interpretation of the results. The pool of methods used includes radar interferometry, but also spatiotemporal analysis and modeling. The overall objective of this comprehensive case study is to present the possibilities but also the limitations of the application of radar interferometry and to provide a perspective for future monitoring in post-mining areas.

ANALYSIS OF HISTORICAL DATA USING ARTIFICIAL INTELLIGENCE TECHNOLOGIES FOR PREDICTING THREATS IN COMPLEX DISTRIBUTED SYSTEMS

A threat prediction method based on the mining of historical data in complex distributed systems is proposed. The relevance of the selected research topic is substantiated from the point of view of considering floods as a physical process of water rise, the level of which is measured at stationary hydrological posts. The mathematical formulation of the problem is formulated, within the framework of which an artificial neural network is implemented based on the free software library “TensorFlow”. An analysis of the effectiveness of the implemented artificial neural network was carried out, according to the results of which the weighted mean square-law deviation of the predicted water level value from the actual one when forecasting for one day at stationary hydrological posts was 0.032. Thus, the neural network allows predicting the flood situation with acceptable accuracy, which gives time for special services to carry out measures to counter this threat.

Variability of Carbonate Isotope Signatures in a Hydrothermally Influenced System: Insights from the Pastos Grandes Caldera (Bolivia)

Laguna Pastos Grandes (Bolivia), nesting in a volcanic caldera, is a large, palustrine-to-lacustrine system fed by meteoric and hydrothermal calco–carbonic fluids. These different fluid inputs favor a complex mosaic of depositional environments, including hydrothermal springs, pools, and an ephemeral lake, producing abundant present-day carbonates developing over a Holocene carbonate crust dated by U–Th. Present-day carbonates (muds, concretions, and microbialites) recorded a large range of isotope variations, reaching 13.9‰ in δ13C and 11.1‰ in δ18O. Sedimentological and geochemical data indicated that the main processes influencing the isotope record were: (i) rapid CO2 degassing and temperature decreases along hydrothermal discharges; (ii) strong evaporation favored by the arid high-altitude Andean climate, locally enhanced by capillary water rise within microbial mats or by wind-induced spray falling on vadose concretions. Unlike past or present perennial lake systems in Central Andes, the short residence time of brine waters in the ephemeral central lake prevents enrichment of lacustrine carbonates in 13C and 18O. The very low fraction modern F14C in these present-day carbonates demonstrates that incorporation of fossil magmatic carbon related to the volcanic context also prevents any radiocarbon dating. The use of isotopes for the interpretation of ancient continental series should always be accompanied by a thorough characterization of the environmental setting.

A Success Story of Unlocking Depleted Channel Reserves in Tunu Gas Field, Mahakam Delta, Indonesia

Crestal part of Tunu Main Zone has been heavily developed with infill wells mainly targeting the isolated bars, while channel reservoirs in western flank have been depleted and considered as upsides. A novel strategy in targeting depleted channel reservoirs is initiated to challenge the conventional gridding method. The workflow comprises of integration of channel geometry update with current static data, connected gas in place reconciliation, production history, pressure update, and water rise analysis. These become key points in geological mapping of the channel which helps to identify remaining potential channels in the field. The recent result of four wells that have been drilled targeting the depleted channels in Tunu Main Zone gave significant higher reserves and have been producing with more than 1 Bcf cumulative. The success story of those four wells leads the opportunity to propose new wells targeting proven depleted channels. Statistically, those channels have 6-8 meters of thickness, 14-16% of porosity, and 30-60 mD of permeability. A considerable amount of remaining potential in channel reservoirs was caused by commingled production strategy and relatively high flowing pressure in the past existing wells resulting in basket gas. Better production result than prognosis in depleted channel reservoirs is due to selective perforation strategy and lower back pressure due to lower production flowing pressure. Depleted channel reservoirs are still promising to be targeted for future wells candidate using more systematic approach. This paper endeavors to exhibit a systematical approach in converting undervalued potential of depleted channel reservoirs to compelling prospects as an incremental value creation process in a mature gas field.

Hydrometeorological conditions and water regime of the lake Krasilovskoye (Altai krai) in 2013-2017

The paper presents the analysis of the data on monitoring the hydrological state of the basinal freshwater lake Krasilovskoye (Altai Krai) and hydrometeorological conditions in its catchment in 2013-2017. The data from the automated measuring complex developed at the Institute of monitoring of climatic and ecological systems of SB RAS as well as the data on snow surveys carried out by researchers from IWEP SB RAS in the catchment and water area of the lake are used. Observations of water regime in the basin lake in the years with contrasting hydro-climatic conditions made it possible to identify the dominant factor determining its spring filling and to quantify its level dynamics. The magnitude and rate of level rise in spring mainly depend on hydro-climatic conditions of air and soil of the previous cold period, which in turn determine the ratio of surface and underground runoff in spring. It was found that in the winter of 2014 and 2016, hydro-climatic conditions of the cold period contributed to the freezing of soil and the formation of a "locking" ice layer, which prevented vertical infiltration of melt water. Intensive surface runoff induced a drastic level rise up to 1-1.5 m. In 2015 and 2017, at the absence of soil freezing, the water rise was much lower, despite large snow reserves and intensive snowmelt. In the spring of 2017, the driven out to the water surface diluted near-bottom layer enriched with hydrogen sulfide caused mass fish death after insignificant water inflow to the lake.