Sedimentation of reservoirs in Uzbekistan: a case study of the Akdarya Reservoir, Zerafshan River Basin

International audienceThe major rivers of Central Asia (Amu Darya, Syr Darya and Zerafshan) are turbid watercourses. Thus many man-made water reservoirs are affected by high sedimentation rates. It is of strategic importance to rationally quantify available water resources in existing reservoirs to ensure a guaranteed water supply to the different water users. Recent drought years and physical deterioration of hydraulic structures urged authorities to re-estimate the water availability in reservoirs of Uzbekistan for the sustainable use of the scarce water resources and safe operation of hydraulic infrastructure. This paper presents the results after the application of a geostatistical approach to assess the water resources availability in the Akdarya reservoir of Uzbekistan. The geostatistical approach creates digital surfaces that represent relatively accurate reservoir bottom conditions and support automated reservoir volumes and surface areas calculations. This in turn significantly reduces time, work load and financial burdens for sedimentation survey projects

SINKHOLES OF THE FRIULI VENEZIA GIULIA REGION: CHARACTERIZATION, DATA COLLECTION AND HAZARD DEFINITION

Il dottorato di ricerca si è focalizzato sull’identificazione, la caratterizzazione e l’analisi dei fenomeni di sinkhole (subsidence sinkhole sensu Gutiérrez et al., 2014) al fine di calcolare le distanze di rispetto e di sviluppare un protocollo informatico in grado di assegnare automaticamente a ciascun fenomeno la sua pericolosità. La regione Friuli Venezia Giulia (FVG) è stata scelta come area studio in quanto assieme al Carso Classico rappresenta un’area ricca di fenomeni di sprofondamento verificatisi in diversi contesti geologici. Un vasto censimento dei fenomeni presenti sul territorio regionale è stato fatto negli anni grazie ai diversi Accordi di ricerca tra il Servizio Geologico della regione e il Dipartimento di Matematica e Geoscienze dell'Università di Trieste al fine di implementare, con i fenomeni naturali, il geodatabase già esistente a livello nazionale. Il primo lavoro svolto all’interno del dottorato è stato quello di revisionare la struttura della banca dati, aggiornare le informazioni al suo interno e censire nuovi fenomeni in diversi contesti geomorfologici e litologici (inizialmente il censimento riguardava solo l’ambiente evaporitico). Tutto questo è stato possibile grazie agli innumerevoli sopralluoghi che hanno contribuito alla riduzione dei fenomeni "non definiti" (da 446 nel 2020 a 262 nel 2023), alla compilazione e/o all’aggiornamento di alcuni campi come la classificazione e, quando possibile, lo stato di attività e i parametri morfometrici, e all’aggiunta di 159 nuovi fenomeni. Il censimento si è concentrato in particolare sui carbonati a partire dal Carso Classico, e successivamente l'analisi è stata estesa a tutto il territorio regionale. La presenza di numerose grotte i cui ingressi possono essere riconducibili a dei collassi ha determinato la scelta di analizzare il catasto speleologico della regione FVG (CSR), esaminando un totale di 8004 grotte e definendo un protocollo metodologico per l’identificazione dei sinkhole in questo contesto. Parallelamente a quanto descritto, sono stati effettuati degli studi approfonditi su diverse aree test (es. abitati di Quinis e Baus (UD)) che hanno permesso di definire la miglior metodologia per caratterizzare questi fenomeni in diversi contesti geologico/geomorfologici. L'applicazione di diverse metodologie, come la combinazione di analisi di dati interferometrici e di livellamento, indagini geofisiche ecc., si è dimostrata fondamentale, non solo per la caratterizzazione tridimensionale di alcune forme, ma anche per l’analisi della loro evoluzione nel tempo evidenziando l'importanza del monitoraggio in continuo al fine di evitare danni ad abitazioni ed infrastrutture. Nell'area di Quinis sono state inoltre effettuate indagini di dettaglio tramite lo scavo di una trincea attraversando un sinkhole attivo. Questo studio, effettuato per la prima volta in Italia, ha permesso di descrivere e caratterizzare tridimensionalmente il fenomeno e l’area circostante. Tutte le attività svolte hanno portato allo sviluppo di un approccio metodologico in grado di definire automaticamente le distanze di rispetto dai sinkhole. Nella letteratura non esiste un metodo specifico per calcolarne il valore. Nel caso della regione FVG, è stato deciso di applicare una metodologia quantitativa basata sui dati disponibili raccolti nel geodatabase. In base allo stato di attività, alla classificazione e alla litologia, criteri specifici basati sul calcolo trigonometrico e sulle caratteristiche intrinseche del materiale coinvolto, hanno portato al calcolo di un buffer e all'assegnazione di una pericolosità a ciascuna area individuata. La metodologia è stata successivamente importata in ambiente GIS sviluppando un tool ad hoc applicabile ai fenomeni legati all'ambiente evaporitico per creare una mappa di pericolosità

Geographic Information Science (GIScience) and Geospatial Approaches for the Analysis of Historical Visual Sources and Cartographic Material

This book focuses on the use of GIScience in conjunction with historical visual sources to resolve past scenarios. The themes, knowledge gained and methodologies conducted might be of interest to a variety of scholars from the social science and humanities disciplines

Across Space and Time. Papers from the 41st Conference on Computer Applications and Quantitative Methods in Archaeology, Perth, 25-28 March 2013

This volume presents a selection of the best papers presented at the forty-first annual Conference on Computer Applications and Quantitative Methods in Archaeology. The theme for the conference was "Across Space and Time", and the papers explore a multitude of topics related to that concept, including databases, the semantic Web, geographical information systems, data collection and management, and more

Doctor of Philosophy

dissertationStrontium isotope ratio (87Sr/86Sr) has a strong potential to complement atmospherically-derived traditional stable isotopes in geochemical provenance studies because strontium (Sr) in Earth surface reservoirs is sourced from local bedrock. As such, 87Sr/86Sr variations are discrete and differ drastically from the large scale smoothed variations of atmospherically-derived stable isotopes. Among the most successful recent applications, 87Sr/86Sr has been used to interpret provenance of individuals in archeology, to identify the origin of dust aerosols, to reconstruct cation source and mobility in rivers, and to reconstruct animal or material movement pathways. However, extending the applications of 87Sr/86Sr for provenance to larger spatial scales is currently hampered by the absence of methods to predict the 87Sr/86Sr of Sr sources at the regional scale. In this dissertation, a flexible geostatistical framework is established to predict 87Sr/86Sr distributions in bedrock, river water and soil water at regional scale. This approach leverages publically-available geospatial data on rock geochemistry, surficial and bedrock geology, climate, hydrology, and aerosols to model the input and propagation of Sr from multiple geological sources through hydrosystems and ecosystems. In a first step, we develop predictive models for 87Sr/86Sr in bedrock as a function of variations in rock age and rock type. In a second step, we model the Sr release from different rock units, its transport as dissolved Sr or in aerosols, and its accumulation and mixing in ecosystems. The model was tested for the contiguous USA and circum-Caribbean region and the model showed promising results but the predictive power remained too low for routine provenance interpretations. In a final step, we develop a flexible geochemical framework that explicitly accounts for prediction uncertainty and local variability of 87Sr/ 86Sr and includes a Sr-specific process-based chemical weathering model. This improved model version is applied to predict 87Sr/86Sr in bedrock and rivers over Alaska and explain 82% of 87Sr/ 86Sr variance in Alaska Rivers. Integrated into a multi-isotopes framework, 87Sr/86Sr could dramatically improve the spatial resolution of provenance assignments. Predictive 87Sr/86Sr models are also a powerful standalone tool to visualize, identify and model mechanistic processes influencing local to global 87Sr/86Sr in Earth surface reservoirs

Across Space and Time Papers from the 41st Conference on Computer Applications and Quantitative Methods in Archaeology, Perth, 25-28 March 2013

The present volume includes 50 selected peer-reviewed papers presented at the 41st Computer Applications and Quantitative Methods in Archaeology Across Space and Time (CAA2013) conference held in Perth (Western Australia) in March 2013 at the University Club of Western Australia and hosted by the recently established CAA Australia National Chapter. It also hosts a paper presented at the 40th Computer Applications and Quantitative Methods in Archaeology (CAA2012) conference held in Southampton

Multisensor Fusion Remote Sensing Technology For Assessing Multitemporal Responses In Ecohydrological Systems

Earth ecosystems and environment have been changing rapidly due to the advanced technologies and developments of humans. Impacts caused by human activities and developments are difficult to acquire for evaluations due to the rapid changes. Remote sensing (RS) technology has been implemented for environmental managements. A new and promising trend in remote sensing for environment is widely used to measure and monitor the earth environment and its changes. RS allows large-scaled measurements over a large region within a very short period of time. Continuous and repeatable measurements are the very indispensable features of RS. Soil moisture is a critical element in the hydrological cycle especially in a semiarid or arid region. Point measurement to comprehend the soil moisture distribution contiguously in a vast watershed is difficult because the soil moisture patterns might greatly vary temporally and spatially. Space-borne radar imaging satellites have been popular because they have the capability to exhibit all weather observations. Yet the estimation methods of soil moisture based on the active or passive satellite imageries remain uncertain. This study aims at presenting a systematic soil moisture estimation method for the Choke Canyon Reservoir Watershed (CCRW), a semiarid watershed with an area of over 14,200 km2 in south Texas. With the aid of five corner reflectors, the RADARSAT-1 Synthetic Aperture Radar (SAR) imageries of the study area acquired in April and September 2004 were processed by both radiometric and geometric calibrations at first. New soil moisture estimation models derived by genetic programming (GP) technique were then developed and applied to support the soil moisture distribution analysis. The GP-based nonlinear function derived in the evolutionary process uniquely links a series of crucial topographic and geographic features. Included in this process are slope, aspect, vegetation cover, and soil permeability to compliment the well-calibrated SAR data. Research indicates that the novel application of GP proved useful for generating a highly nonlinear structure in regression regime, which exhibits very strong correlations statistically between the model estimates and the ground truth measurements (volumetric water content) on the basis of the unseen data sets. In an effort to produce the soil moisture distributions over seasons, it eventually leads to characterizing local- to regional-scale soil moisture variability and performing the possible estimation of water storages of the terrestrial hydrosphere. A new evolutionary computational, supervised classification scheme (Riparian Classification Algorithm, RICAL) was developed and used to identify the change of riparian zones in a semi-arid watershed temporally and spatially. The case study uniquely demonstrates an effort to incorporating both vegetation index and soil moisture estimates based on Landsat 5 TM and RADARSAT-1 imageries while trying to improve the riparian classification in the Choke Canyon Reservoir Watershed (CCRW), South Texas. The CCRW was selected as the study area contributing to the reservoir, which is mostly agricultural and range land in a semi-arid coastal environment. This makes the change detection of riparian buffers significant due to their interception capability of non-point source impacts within the riparian buffer zones and the maintenance of ecosystem integrity region wide. The estimation of soil moisture based on RADARSAT-1 Synthetic Aperture Radar (SAR) satellite imagery as previously developed was used. Eight commonly used vegetation indices were calculated from the reflectance obtained from Landsat 5 TM satellite images. The vegetation indices were individually used to classify vegetation cover in association with genetic programming algorithm. The soil moisture and vegetation indices were integrated into Landsat TM images based on a pre-pixel channel approach for riparian classification. Two different classification algorithms were used including genetic programming, and a combination of ISODATA and maximum likelihood supervised classification. The white box feature of genetic programming revealed the comparative advantage of all input parameters. The GP algorithm yielded more than 90% accuracy, based on unseen ground data, using vegetation index and Landsat reflectance band 1, 2, 3, and 4. The detection of changes in the buffer zone was proved to be technically feasible with high accuracy. Overall, the development of the RICAL algorithm may lead to the formulation of more effective management strategies for the handling of non-point source pollution control, bird habitat monitoring, and grazing and live stock management in the future. Soil properties, landscapes, channels, fault lines, erosion/deposition patches, and bedload transport history show geologic and geomorphologic features in a variety of watersheds. In response to these unique watershed characteristics, the hydrology of large-scale watersheds is often very complex. Precipitation, infiltration and percolation, stream flow, plant transpiration, soil moisture changes, and groundwater recharge are intimately related with each other to form water balance dynamics on the surface of these watersheds. Within this chapter, depicted is an optimal site selection technology using a grey integer programming (GIP) model to assimilate remote sensing-based geo-environmental patterns in an uncertain environment with respect to some technical and resources constraints. It enables us to retrieve the hydrological trends and pinpoint the most critical locations for the deployment of monitoring stations in a vast watershed. Geo-environmental information amassed in this study includes soil permeability, surface temperature, soil moisture, precipitation, leaf area index (LAI) and normalized difference vegetation index (NDVI). With the aid of a remote sensing-based GIP analysis, only five locations out of more than 800 candidate sites were selected by the spatial analysis, and then confirmed by a field investigation. The methodology developed in this remote sensing-based GIP analysis will significantly advance the state-of-the-art technology in optimum arrangement/distribution of water sensor platforms for maximum sensing coverage and information-extraction capacity. Effective water resources management is a critically important priority across the globe. While water scarcity limits the uses of water in many ways, floods also have caused so many damages and lives. To more efficiently use the limited amount of water or to resourcefully provide adequate time for flood warning, the results have led us to seek advanced techniques for improving streamflow forecasting. The objective of this section of research is to incorporate sea surface temperature (SST), Next Generation Radar (NEXRAD) and meteorological characteristics with historical stream data to forecast the actual streamflow using genetic programming. This study case concerns the forecasting of stream discharge of a complex-terrain, semi-arid watershed. This study elicits microclimatological factors and the resultant stream flow rate in river system given the influence of dynamic basin features such as soil moisture, soil temperature, ambient relative humidity, air temperature, sea surface temperature, and precipitation. Evaluations of the forecasting results are expressed in terms of the percentage error (PE), the root-mean-square error (RMSE), and the square of the Pearson product moment correlation coefficient (r-squared value). The developed models can predict streamflow with very good accuracy with an r-square of 0.84 and PE of 1% for a 30-day prediction

The SAR Handbook: Comprehensive Methodologies for Forest Monitoring and Biomass Estimation

This Synthetic Aperture Radar (SAR) handbook of applied methods for forest monitoring and biomass estimation has been developed by SERVIR in collaboration with SilvaCarbon to address pressing needs in the development of operational forest monitoring services. Despite the existence of SAR technology with all-weather capability for over 30 years, the applied use of this technology for operational purposes has proven difficult. This handbook seeks to provide understandable, easy-to-assimilate technical material to remote sensing specialists that may not have expertise on SAR but are interested in leveraging SAR technology in the forestry sector