ANALYSIS OF SPATIO-TEMPORAL DYNAMICS OF AEOLIAN PROCESSES IN ARID AND SEMI-ARID AREAS USING REMOTE SENSING

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Numerically Enhanced Conceptual Modelling (NECoM) applied to the Flumendosa Plain groundwater system (SE Sardinia, Italy)

The alluvial aquifer of the Flumendosa delta plain, in south-eastern Sardinia (Italy), is overexploited for drinking and agriculture purposes and it is subjected to ongoing sea water intrusion phenomena. In a context of progressive quali-quantitative deterioration of groundwater resources, development of a sustainable management plan and, eventually, effective remediation actions require a deep understanding of the investigated system. A systematic review of dataset collected from literature, integrated with new field hydrogeological and geochemical data, is performed to improve the knowledge of the aquifer system. Despite the large amount of processed data, many aspects require further investigations. In this frame, a fast-running steady state groundwater flow numerical model is developed as a tool for testing the preliminary assumptions, to address the main uncertainties, and to optimize the acquisition of new field data. The adopted approach follows the methodology proposed by Lotti et al. (2021) for the development of a Numerically Enhanced Conceptual Model (NECoM). Geometrical discretization of the numerical model is based on results of the 3D hydrogeological reconstruction of the plain area (Arras et al. 2019); simulation of main inflows and outflows, water exchange between surface water bodies and groundwater, irrigation and drinking water withdrawals is performed through the implementation of general head boundaries (GHB), river (RIV), and well (WEL) packages, respectively. Results from the application of the Soil Water Balance code (Porru et al. 2020) are used as input for simulating the average recharge from precipitation. Lateral recharge from the Paleozoic basement is also simulated. More than 4000 heads observations from about 350 wells and piezometers are used as targets in the calibration process; weights are assigned to deal with the high heterogeneity of the dataset quality. RIV and GHB conductance, irrigation well yields, direct and lateral recharge, and hydraulic conductivity are set as parameters in the calibration process. Due to the high sensitivity of some parameters, different calibration cycles are performed; hydraulic conductivities and lateral recharge are then calibrated in the last cycle. Model results show that the hydrogeological conceptualization used for implementing the numerical model can reproduce the main general features of the piezometric head field. According to field observations, the Flumendosa river shows losing conditions in the western part of the plain and next to the river mouth, while gaining conditions occur in its central part; gaining conditions are also observed along the abandoned branches of the Flumendosa river, also known as foxi. Moreover, mass balance analysis show that the Flumendosa river represents the main recharge input of the whole groundwater system, providing an average inflow of about 4.3 Mm3/year. Nevertheless, several local incongruencies with the observed data were precious to highlight the effects of unknown variables such as agricultural extraction wells, the hydrogeological role of the bedrock or the water exchange between surface and groundwater bodies. The discrepancies, rather than the agreements, provided useful direction for the detection of new data to be collected to capture the salient information needed for a proper water resource management

An interdisciplinary methodology to design integrated and innovative MAR systems in arid and semi-arid regions. Two case studies in Algeria and in Tunisia

Drought,  desertification, Managed Aquifer Recharge (MAR), Tunisia, Algeri

Land Cover Change Modeler: indicatori di trasformazione del territorio come driver per il monitoraggio della salinizzazione in un settore dell’Algeria

Questo studio ha come obiettivo la valutazione del trend spaziale di cambiamento della copertura e uso del suolo in un’area arida e semiarida del Nord Africa, nonché il potenziale di transizione da una classe di copertura del suolo ad un’altra considerando vari indicatori ambientali, culturali e socio-economici. Tali indicatori possono costituire i drivers per la costruzione degli scenari di evoluzione spaziale e temporale della salinizzazione dei suoli nel territorio dell’Oued Biskra in Algeria. Lo studio presentato fa parte delle attività del progetto dimostrativo WADIS-MAR, finanziato dalla Commissione Europea attraverso il Sustainable Water Integrated Management (SWIM) Programme (http://www.wadismar.eu). Partendo dalle mappe di land cover (LC) e salinizzazione elaborate da dati satellitari Landsat, sono stati testati alcuni algoritmi dedicati al Land Change Modeler (LCM). Lo studio si basa su un’analisi multitemporale di dati Landsat che ha portato allo sviluppo di un classificatore di tipo Decision Tree dedicato al riconoscimento delle aree salinizzate in ambiente arido e semiarido (Melis et al., 2013; Afrasinei et al., 2015). Questo classificatore è stato testato in particolare nel settore dell’Oued Biskra (Algeria orientale) lungo il limite settentrionale del sistema morfologico sahariano. La metodologia adottata propone di utilizzare queste mappe come base per la predizione degli scenari di evoluzione del fenomeno della salinizzazione. Tale fenomeno appare fortemente controllato dalle dinamiche sociali ed economiche legate all’utilizzo intensivo del territorio per l’agricoltura e in particolare per le coltivazioni di palme da dattero. Inoltre in questi ambienti il clima e le condizioni biofisiche locali hanno un’influenza immediata sulle variazioni di land cover anche con impatto giornaliero, pertanto questo tipo di driver, estremamente variabile, deve essere considerato nella sua dinamicità in modo differente rispetto ai parametri stabili nel tempo quali la morfologia e la litologia e rispetto a quelli a variabilità media come quelli socio-culturali ed economici

A Methodological Approach For The Effective Infiltration Assessment In A Coastal Groundwater

Accurate estimates of spatial and temporal distribution of groundwater recharge are of utmost importance to protect groundwater systems. In coastal areas, the fragility of the systems makes such estimates critical for the correct management and protection of water resources from saltwater intrusion. The Muravera coastal plain, in the south-eastern Sardinia, has been studied since 1960, due to important saltwater intrusion phenomena. Since the early fifties, the natural hydrodynamic equilibrium between groundwater, surface-water and seawater has been deeply modified by the construction of four dams across the Flumendosa river and the development of agriculture, tourism and aquaculture activities along the coast. To implement an integrated and sustainable management system addressed to slow down the process of saltwater intrusion and, on the other, satisfy human requirements, it is important to develop a flexible scenario analysis system that considers changes of land-use and inputs to the hydrogeological system, also in relation to climate change. In this study, the innovative Soil Water Balance code (SWB) has been applied to the Muravera plain groundwater body to calculate spatial and temporal variations of groundwater recharge. The code calculates the recharge (R) by using geographic system (GIS) data layers in combination with tabular climatological data. It is based on a modified Thornthwaite - Mather soil water balance approach, with components of the soil water balance calculated at a daily time-step. A combined experimental approach of hydrogeological, satellite remote sensing and pedological methodologies has been applied to derive data layers describing local features of: (1) land-use classification, (2) hydrologic soil group, (3) flow direction, and (4) soil-water capacity. The code has proved to be promising for the effective infiltration assessment and it can be easily updated with high resolution data acquired in the field and from satellite images

Assessment of remote sensing-based classification methods for change detection of salt-affected areas (Biskra area, Algeria)

In the Wadi Biskra arid and semiarid areas, sustainable development is restricted by land degradation processes such as secondary salinization of soils. Being an important highquality date production region of Algeria, this area needs continuous monitoring of desertification indicators, hence highly exposed to climate-related risks. Given the limited access to field data, appropriate methods were assessed for the identification and change detection of salt-affected areas, involving image interpretation and automated classifications employing Landsat imagery, ancillary and multisource ground truth data. First, a visual photointerpretation study of the land cover and land use classes was undergone according to acknowledged methodologies. Second, two automated classification approaches were developed: a customized decision tree classification (DTC) and an unsupervised one applied to the principal components of Knepper ratios composite. Five indices were employed in the DTC construction, among which also is a salinity index. The diachronic analysis was undergone for the 1984 to 2015 images (including seasonal approach), being supported by the interpreted land cover/land use map for error estimation. Considering also biophysical and socioeconomic data, comprehensive results are discussed. One of the most important aspects that emerged was that the accelerated expansion of agricultural land in the last three decades has led and continues to contribute to a secondary salinization of soils

Diachronic analysis of salt-Affected areas using remote sensing techniques: the case study of Biskra area, Algeria

In the Wadi Biskra arid and semi-arid area, sustainable development is limited by land degradation, such as secondary salinization of soils. As an important high quality date production region of Algeria, it needs continuous monitoring of desertification indicators, since the bio-physical setting defines it as highly exposed to climate-related risks. For this particular study, for which little ground truth data was possible to acquire, we set up an assessment of appropriate methods for the identification and change detection of salt-affected areas, involving image interpretation and processing techniques employing Landsat imagery. After a first phase consisting of a visual interpretation study of the land cover types, two automated classification approaches were proposed and applied for this specific study: decision tree classification and principal components analysis (PCA) of Knepper ratios. Five of the indices employed in the Decision Tree construction were set up within the current study, among which we propose a salinity index (SMI) for the extraction of highly saline areas. The results of the 1984 to 2014 diachronic analysis of salt - affected areas variation were supported by the interpreted land cover map for accuracy estimation. Connecting the outputs with auxiliary bio-physical and socio-economic data, comprehensive results are discussed, which were indispensable for the understanding of land degradation dynamics and vulnerability to desertification. One aspect that emerged was the fact that the expansion of agricultural land in the last three decades may have led and continue to contribute to a secondary salinization of soils. This study is part of the WADIS-MAR Demonstration Project, funded by the European Commission through the Sustainable Water Integrated Management (SWIM) Program (www.wadismar.eu)

Long-Term Annual Average Aquifer Recharge assessment for the island of Sardinia (Italy)

Evaluation of Long-Term Annual Average Recharge (LTAAR) is a challenge for sustainable management of groundwaters. Despite many methods were developed based on different kind of input dataset, inverse water balance is one of the most effective approach when long term climatic data series are available. In this work, the inverse water balance for all the aquifers of the Hydrographic District of Sardinia (Arras et al. 2019) is presented. The proposed model adopts a geographically based integrated evaluation system. Daily precipitation and temperatures data from the official weather stations network of Sardinia was collected for the periods 1981-2010 and 2009-2018, while average precipitation and temperature maps, elaborated by the Sardinian Regional Agency for Environmental Protection (ARPAS: Hydro-meteoclimatic Department), were used for the period 1971-2000. Elevation data comes from the 10 m grid Digital Terrain Model (DTM) of Sardinia, downscaled to a 40 meters grid. Daily measurements were used to calculate climate Normal according to the World Meteorological Organization guidelines (WMO 2017). Spatial interpolation of punctual Normal was performed through the application of the ordinary kriging of residuals from linear regression between climatic data and elevation. The method provides good results in terms of accuracy in reproducing missing data for both the climatic dataset, as demonstrated in similar context (Di Piazza et al. 2015). The Turc modified method by Santoro (1970) was used to calculate the actual evapotranspiration term. Based on literature data and field measurements potential infiltration indexes were evaluated. Then, runoff was calculated as difference between effective precipitation and effective annual aquifer recharge. Results have shown that LTAAR for the whole hydrographic district of Sardinia ranges from 1600 (1971-2000) to 1540 (1981-2010) and 1690 (2009-2018) Mm3, representing 15% of the average annual precipitation; more than 65% of the annual available water is lost through evapotranspiration; the remaining 20% occurs as runoff

Spatiotemporal and spectral analysis of sand encroachment dynamics in southern Tunisia

Aeolian processes in drylands often transcend into sand encroachment, a common form of land degradation. Highly reflective desert features, hence sandy areas, often cause spectral confusion, and mapping through remote sensing techniques can be challenging. This work aims at designing an efficient classification method that minimises spectral confusion of desert features, hence two types of sandy areas. Moreover, we employ land cover (LC) change detection over the last 30 years. The extraction and spatiotemporal variations of LC and sand encroachment areas in the Dahar-Jeffara Medenine site (southeastern Tunisia) are assessed by employing Landsat imagery (1984 and 2014), a 30 m digital elevation model of Shuttle Radar Topography Mission (SRTMGL 1 arc second), field data and X-ray diffraction analyses of sand samples. Five new spectral indices were designed and employed in a Decision Tree (DT) classifier for the extraction of 11 LC classes, including two different types of sandy areas. The DT map yielded an overall accuracy of around 89%. Change detection results showed substantial change in several landscape components and an increase of sand units by 29% within the Jeffara-Medenine plain over the last three decades. Geomorphological observations and multi-temporal, spectral and mineral analyses indicate a main, possible in-situ source area of sand