Piedmont Plain Research Articles

Evaluation of shallow groundwater dynamics after water supplement in North China Plain based on attention-GRU model

The continuous ecological river supplement has enhanced the recharge of groundwater in the North China Plain, and alleviated the depletion of groundwater resources. In the study of ecological river supplement, efficient quantitative prediction of groundwater level (GWL) and groundwater storage (GWS) is a crucial issue. To predict GWL and estimate the variation of GWS in the North China Plain, this paper uses the attention-gated recurrent unit (Attention-GRU) model as a primary method and coefficient of determination (R2) and root mean square error (RMSE) as the indices to evaluate model performance. Compared to traditional recursive neural network (RNN) and long short-term memory (LSTM) model, Attention-GRU model demonstrated an outstanding performance, as the RMSE is respectively 0.5 m and 2.28 m in the training and testing periods, and the R2 is 0.87 and 0.68. With the usage of the convolution neural network (CNN) model, the specific yield field was continuously updated from 2018 to 2021. The average annual variation of GWS estimated by this method is respectively −15.19 × 104 m3, −13.29 × 104 m3, 2.55×104 m3 and 100.05×104 m3 from 2018 to 2021 in the North China Plain. Besides, the semiannual GWS variation, calculated using the updated specific yield, is −59.56 × 104 m3 in 2022. Furthermore, the influence of the reference time length and the driving factors were evaluated. Results show that the precipitation, evaporation and human activities are the most important temporal features influencing the changes in GWS, and the changes in different areas have varying local characteristics. In the piedmont plain, river ecological recharge played a crucial role for groundwater storage recovery. When it moved to the coastal plain, the contribution rate of recharge decreased from 23% to 11%. In addition, the optimal reference time length used in Attention-GRU model varies in different hydrogeology divisions, and the specific yield variation would result in substantial differences for the GWS estimation under different climate conditions and human activities. The systematic framework proposed in this paper is effective for evaluating and predicting GWL and GWS, and thereby able to support the management and development of groundwater, and provide a guidance for ecological river supplement.

Environment and Plant Use at La Tourasse (South-West France) at the Late Glacial–Holocene Transition

Abstract The aim of this study is to present new data on vegetation dynamics and plant collecting practices during the Late Glacial and the Early Holocene in southwestern France. La Tourasse cave is located in the Pyrenean piedmont plain, where the Azilian cultural complex was initially defined. The last excavations of the site took place in the 1980s and 1990s and the recovered materials are currently being studied or revisited from a multidisciplinary perspective. We present here the results of the charcoal analysis performed on La Tourasse’s Azilian (ca. 13000–11500 cal. BP) and Mesolithic (ca. 10500–9000 cal. BP) levels, complemented by the study of a small seed assemblage. Our results document the shift from an open landscape towards a forested environment, with the gradual passage from open vegetation dominated by shrubs of the Rose family (Prunus spp.) to the mixed oak forest, which speaks in favor of the biochronological coherence of this sequence. However, marked differences in taxonomic richness and state of the wood from one level to another, unrelated to the prevailing environmental conditions, suggest variable behavior of humans toward wood that could be the result of differing mobility strategies, hearth functionalities, or taxonomic preferences.

A dataset of water, heat, and carbon fluxes over the winter wheat-summer maize croplands in Luancheng during 2013–2017

The winter wheat-summer maize double-cropping agro-ecosystem holds the largest planting area in the North China Plain. The carbon and water flux observation data of the croplands are crucial to understanding regional carbon and water cycles and their regulation mechanism. Located in the piedmont Plain of Taihang Mountain, Luancheng Agro-ecosystem Experimental Station (Luancheng Station) is the typical groundwater irrigation district. We have been using the eddy covariance technology to carry out the observation work of the winter-summer maize croplands since October 2007. This is the dataset of water, heat, and carbon fluxes over the winter wheat-summer maize croplands in Luancheng from October 2013 to September 2017 (covering four complete growing seasons). The dataset includes latent heat flux (or evapotranspiration), sensible heat flux, net ecosystem exchange of CO2, solar radiation, photosynthetically active radiation, air temperature/humidity, precipitation, soil temperature and volumetric soil water content at the half-hourly, daily, crop-season, and crop-year scales. The network observation, quality control and storage process of this dataset strictly abide by ChinaFLUX data management technology system to ensure data reliability. This dataset can provide solid data support for deeply understanding the processes of water, heat and carbon exchange, and improving the management of water resource to relieve the overdraft of groundwater in North China.

Influences of paleoclimatic environment and hydrogeochemical evolution on groundwater salinity in an arid inland plain in northwestern China

Highly saline groundwater limits the availability of freshwater resources, especially in arid/semi-arid inland areas with a growing demand but a scarcity of water resources. Understanding the spatial distribution of groundwater salinity and the factors that control their variability is vital for the scientific management of water resources in these areas. Integrated hydrogeochemistry and environmental isotopes (δD, δ18O, 3H, 14C) were used to study the distribution and evolution of fresh and saline groundwater in the Aksu Plain and its links to the paleo-climatic environment since the Late Pleistocene. The results indicated that the sources of groundwater was meteoric water from the Tianshan Mountains. Modern groundwater was found in the piedmont plain and shallow groundwater adjacent to the surface water. The paleo-atmospheric precipitation replenished the deep confined groundwater during the Last Glacial Period. There was no correlation between groundwater salinity and depth. Along the flow path, groundwater salinity has no increasing trend. We found that the paleoclimatic environment and water-rock interaction jointly determine the distribution of groundwater salinity, while evaporation had a slight effect based on the isotopic composition. The long residence time (8–19 ka) and evaporites in sediments (such as halite and gypsum) could provide the conditions for sufficient water-rock interactions, leading to the formation of brackish/saline groundwater. Conversely, the fresh, deep, confined groundwater corresponds to paleo-recharge conditions during the humid Last Glacial Period (21–24.5 ka). Surface water infiltration reduces the salinity of shallow groundwater, but the influence is limited. This study presents a mode that combines hydrogeochemical evolution and paleoclimatic environments to better assess groundwater salinity in the arid inland region.

Influence of hydrogeological and geochemical parameters on N2O in the groundwater in the irrigation area of lower reaches of Yellow River

The plains of the lower reaches of rivers are important areas for food production. In the groundwater of irrigated agricultural areas of these regions, the N2O concentration was generally observed to be higher than that of the water–gas equilibrium. Due to the complexity and uncertainty of the aquifers, the mechanisms by which groundwater N2O are affected by groundwater hydrogeology and geochemistry remain unexplored. In this study, 41 groundwater samples were collected from three zones of the irrigation area of the lower reaches of Yellow River (i.e., piedmont plain, coastal plain, and central plain), and the hydrogeological parameters of these three areas were characterized. The results showed significant differences of the N2O concentration in the groundwater of the three zones of the lower reaches of Yellow River plain, which was 14.1 ± 13.1 µg/L, 1.84 ± 1.48 µg/L, and 36.5 ± 40.5 µg/L for the piedmont plain, central plain, and coastal plain, respectively. The differences were attributed to different groundwater N input and hydrogeological parameters in the three zones. The infiltration coefficient of precipitation was found to be the most important hydrogeological parameter affecting groundwater N2O. This study also evaluated the indirect N2O emission factor in the irrigation area of the lower reaches of Yellow River. The N2O emissions induced by groundwater exploitation in the irrigation area of the lower reaches of Yellow River were found to be 1.87 g hm−2 year−1. These findings provide a foundation to develop strategies to reduce N2O production and emissions in the agricultural area of the lower reaches of rivers.

Geospatial variability of soil physico-chemical properties of Moridhal watershed in Dhemaji district of Assam, India using Remote sensing and GIS

Remote sensing and GIS have opened new vistas towards understanding spatial variability of properties of the soil and ensuring resource use in a sustainable manner. The current study was conducted to assess the variability of physical and chemical properties of the flood-prone soils of the Moridhal watershed under Dhemaji district of Assam. The watershed was delineated using toposheets (1:50,000) and geocoded FCC (False Colour Composite) of Resourcesat-2, LISS-4. Four physiographic units of the Moridhal watershed were delineated which included upper piedmont plain, lower piedmont plain, alluvial plain and flood plain. A total of 170 geo-tagged soil samples collected from different physiographic units were analyzed for various physico-chemical properties. The assessed physico-chemical properties of the watershed showed wide spatial variability. The results showed an increasing trend in the amount of very fine sand and silt from the upper piedmont plain to the floodplain. Bulk density, particle density and porosity of the studied area varied from 1.10 to 1.67 g/cm3, 2.16 to 2.74 g/cm3 and 24.99 to 54.68 %. The pH was extremely acidic to slightly acidic and the soils were found to be moderate to high in organic carbon. The CEC of the soils ranged from 3.88 to 19.40 cmol(p+)/kg and the available nitrogen, phosphorus and potassium varied from low to high. The spatial distribution showed that about 20,408 ha soils of the study area contained more than 40-60 per cent sand, 24,833 ha soils had 20 to 40 per cent silt and 13,915 ha of soils exhibited 20 to 30 per cent clay. Nearly 97.85 % of the watershed area had medium status of available nitrogen as well as available P2O5 content, while 79.96 % of soils had low K2O content.

Quantitative Assessment of Shallow Groundwater Sustainability in North China Plain

The depletion of shallow groundwater has seriously affected the sustainable development of water resources in the North China Plain (NCP). Based on 556 well monitoring observations over a period of 13 years, we quantitatively evaluated the shallow groundwater sustainability in the NCP via various indices (e.g., the reliability, resilience, vulnerability, and sustainability indices), and further discussed the contribution of different drivers (including climatic and non-climatic factors). The main conclusions are summarized as follows: (1) the yearly trend of shallow groundwater shows a serious long-term deficit in the Piedmont Plain but is not significant in the East-Central Plain. (2) As for the sustainability of shallow groundwater in the NCP, the reliability is below the medium level (reliability < 0.5) in most areas and the ability of shallow aquifers to restore groundwater is very weak (resilience < 0.2), while the lack of groundwater storage in most shallow aquifers is not serious (vulnerability < 0.4). The final sustainability index (<0.1) shows the poor sustainability of most shallow aquifers in the NCP. (3) The non-climatic factor is the dominant driver of shallow groundwater depletion in the NCP when compared to the climatic factor. This result is helpful to formulate the water management policies for sustainable shallow groundwater storage in the NCP.

Determining the role of land resource, cropping and management practices in soil organic carbon status of rice-based cropping systems

Rice-based cropping systems (RBCS) cover the majority of cultivated land in Bangladesh and are the country's primary source of food security. To bolster food security, cropping intensity has increased by 192% in the last 30 years. Concerns have been raised about the sustainability of such cropping increases, particularly for soil productivity and resilience, with many areas reporting low soil organic carbon (SOC). The research assessed the levels of SOC, total nitrogen (TN) and soil pH in RBCS to identify relative importance of the land resource, cropping and management settings on these soil properties and to determine options for sustainable land use intensification. Soil samples (0–30 cm) were collected following stratified random design from a range of RBCS and analyzed for SOC, TN and soil pH. These soil properties were interpreted against previously developed farming system typology of Soil Carbon Improvement Likelihood (SCIL) and the legacy soil datasets. SOC was recorded higher in the stop-go triple cropping (12.00–16.33 g/kg) compared to the triple and double cropping intensities (6.90–8.30 g/kg). The crop-diversified and mustard-rice cropping systems of High SCIL, where there is crop rotational diversity and high residue retention, recorded a higher SOC. However these systems were also located on inherently fertile soil (Floodplain medium highland) compared to the less diverse cropping systems (wheat-rice, veg.-rice and rice-rice) of Medium and Low SCIL. The wheat-rice system had the lowest SOC (5.46 g/kg), which is considered to be a consequence of low crop residue retention and reduced periods of inundation in highland on the Piedmont plain or Terrace. However, the build up of SOC and TN was linked to soil acidification associated with altered fertilizer regime and crop residue removal. Cropping intensity, and in particular, the associated cropping systems and management, were determinants of SOC, depending on which land resource setting and cropping systems were practiced by the smallholders. The types of cropping systems and management options in land resource settings were identified that have the potential for sustainable land use intensification. The implications would be to ensure these cropping systems are conserved, and trade offs contemplated to meet the rising food demand and carbon sequestration goals to counteract smallholder vulnerability to climate change in Bangladesh and South Asian countries.

Spatial Distribution and Cultural Features of Traditional Villages in Beijing and Influencing Factors

Traditional villages are important part of Beijing, an internationally famous historic and cultural city. Exploring the spatial distribution and cultural features of traditional villages, and the factors that have shaped them, will help promote the protection and utilization of traditional villages in Beijing. ArcGIS spatial analysis, literature analysis, fieldwork and in-depth interviews were mainly carried out to analyze the spatial distribution and cultural features of traditional villages in Beijing and their influencing factors. The results show three main features. (1) The overall distribution of traditional villages in Beijing is random, although there are more traditional villages in the southwest and northeast and less in the southeast and northwest. Most of them are distributed along the higher piedmont plains or intermountain basins, and most of them are backed by hills and surrounded by rivers or along the ancient road. (2) There are some cultural commonalities among the traditional villages in Beijing, and nine typical traditional village cultures have been formed, including traditional residential culture, traditional folklore culture, the Great Wall garrison culture, mausoleum guarding culture, etc. (3) The formation of the spatial distribution and cultural features of traditional villages in Beijing is influenced by natural environmental factors like terrain, climate, and rivers, as well as human activities such as royal life, capital construction, ancient military defense, transportation, trade, etc. This study can provide a reference for the scientific protection and effective utilization of traditional villages in Beijing and all over the country.

Characterization of Ground Thermal Conditions for Shallow Geothermal Exploitation in the Central North China Plain (NCP) Area

The central North China Plain (NCP) is one of the rapidly developing regions in China which has a great potential for ground source heat pump (GSHP) system applications. However, the ground thermal property, which is a prerequisite for GSHP system design, has been insufficiently investigated. In this paper, the ground thermal conditions including ground temperature and thermal conductivity are characterized in three representative hydrogeological regions in the NCP area: the piedmont alluvial plain, the central alluvial plain, and the coastal plain. Results show that the geothermal gradient below 40 m in depth in this area ranges from 0.018 °C/m to 0.029 °C/m. Although the thermal conductivity measured by soil samples differs slightly among the three regions, parameters in the piedmont plain have a larger variability than in the central and coastal plain due to the significant heterogeneity of the lithology. Thermal conductivity measured by the thermal response test (TRT) ranges between 2.37 and 2.68 W/(m·K) in the piedmont plain and varies between 1.35 and 1.94 W/(m·K) in the central and coastal plain, indicating that the piedmont plain has a higher potential for shallow geothermal exploitation than other two sub-areas. Comparing the TRT with laboratory measurements, the thermal conductivity obtained by the TRT is greater than that of the lab measurements in the piedmont plain due to the TRT outputs including the effects of groundwater flow. Therefore, the TRT is highly recommended to estimate the effective thermal conductivity of the ground in the piedmont plain, while laboratory and field tests are both suitable methods for the determination of thermal conductivity in the central and coastal plains.

The Impact of Climate Change on Groundwater Temperature of the Piedmont Po Plain (NW Italy)

This paper represents the first regional-scale investigation in the Piedmont Po plain about the relationship between groundwater temperature (GWT) and climate variability. The understanding of relationships between air temperature (AT) and GWT is really important, especially in the context of global climate change. The aim of this investigation is to study the relationship between GWT and AT over a 10-year time period (from 2010 to 2019) to analyse how these two parameters interrelate and to evaluate possible trends. To carry out this study, basic statistic interpolations were performed on both parameters to facilitate comparison. Both AT and GWT showed an increase over the observed decade with a more pronounced growth of the AT; this allow to state that GWT is more resilient to climate change than AT. However, some areas in the Piedmont plain showed a behaviour that partially deviated from the standard trend observe for the majority of the region. These areas were influenced by particular anthropic factors (for example the paddy fields in the Novara plain) or natural elements (as the monitoring wells in the “Canavese” area, located downstream of melting glaciers, or the wells located close to the Tanaro River). Moreover, this study wanted to stress the importance of the knowledge of the localization in wells of the instruments for the GWT measurement, to have the most accurate and comparable data. It was proved that as the depth increased, the maximum and minimum peaks of the GWT shifted in time respect to the maximum and minimum peaks of the AT, and, in addition, the GWT fluctuation in the bottom part of the aquifer was milder than the fluctuation observed in the most superficial part. Further investigations will be conducted in future in Piedmont plain areas with different behavior, in order to better understand their dynamics and the factors that may influence GWT and how they are affected by climate change.

Application and comparison of different statistical methods for the analysis of groundwater levels over time: Response to rainfall and resource evolution in the Piedmont Plain (NW Italy)

Monitoring and analysis of groundwater level (GWL) in space and time is one of the tools used to evaluate the quantitative status of groundwater (GW) resources and identify possible alterations and critical cases due to climate change and variability, anthropogenic influences and other driving factors.In this study, four statistical methodologies (trend, change-point, percentile and non-standardized anomaly analyses) were applied for GWL and rainfall (R) analysis in the Piedmont Plain (western Po Plain, NW Italy). To detect the interannual variations in the GW maximum annual amplitude, the coefficient of variation was also used.The aims of the study were 1) to compare the results of different statistical methods, highlighting their applicability and differences to evaluate the quantitative evolution of GW, 2) to identify the relationship between GWL and R, 3) to investigate the spatiotemporal variation in the GWL of shallow aquifers in the Piedmont Plain, and 4) to describe critical situations of GW depletion.The study highlights that the application of a single method for assessing the shallow GW resource status does not always guarantee a reliable evaluation. For this reason, it is advisable to apply different analysis methods at the same time. Completeness of data and medium to long time series are prerequisites for meaningful analyses. The use of the same time interval is always necessary for comparisons between different monitoring wells and between the results of different statistical analyses. Last, by spatializing the results, it was possible to identify areas characterized by similar GWL behaviour due to hydrological structure, climate variability, land use and the evolution of anthropogenic activities over time. These factors influence vary locally in the Piedmont plain and require local assessments to determine the impact of changes in GWL.

Assessing Machine Learning-Based Prediction under Different Agricultural Practices for Digital Mapping of Soil Organic Carbon and Available Phosphorus

Predicting soil chemical properties such as soil organic carbon (SOC) and available phosphorus (Ava-P) content is critical in areas where different land uses exist. The distribution of SOC and Ava-P is influenced by both natural and anthropogenic factors. This study aimed at (1) predicting SOC and Ava-P in a piedmont plain of Northeast Iran using the Random Forests (RF) and Cubist mathematical models and hybrid models (Regression Kriging), (2) comparing the models’ results, and (3) identifying the key variables that influence the spatial dynamics of soil SOC and Ava-P under different agricultural practices. The machine learning models were trained with 201 composite surface soil samples and 24 ancillary data, including climate (C), organism (O), topography- relief (R), parent material (P) and key soil features (S) according to the SCORPAN digital soil mapping framework, which can predictively represent soil formation factors spatially. Clay, one of the most critical soil properties with a well-known relationship to SOC, was the most important predictor of SOC, followed by open-access multispectral satellite images-based vegetation and soil indices. Ava-P had a similar set of effective variables. Hybrid approaches did not improve model accuracy significantly, but they did reduce map uncertainty. In the validation set, Ava-P was calculated using the RF algorithm with a normalized root mean square (NRMSE) of 96.8, while SOC was calculated using the Cubist algorithm with an NRMSE of 94.2. These values did not change when using the hybrid technique for Ava-P; however, they changed just by 1% for SOC. The management of SOC content and the supply of Ava-P in agricultural activities can be guided by SOC and Ava-P digital distribution maps. Produced digital maps in which the soil scientist plays an active role can be used to identify areas where concentrations are high and need to be protected, where uncertainty is high and sampling is required for further monitoring.

Spatial Distribution Pattern and Natural Causes Analysis of Sandy Desertification Land in Ali Area

In order to explore the spatial distribution pattern and natural causes of the sandy desertification land in the Ali area, on the basis of clarifying the dynamic change laws of sandy desertification land areas, sandy desertification degree and spatial distribution pattern, the main controlling factors of sandy desertification land distribution are analyzed from three aspects of landform, climate and vegetation. During the 22 years from 1992 to 2014, the sandy desertification land area in the Ali area shows a law of first increase and then decrease, reaching a peak of 61,054.14 km2 in 2004, accounting for 20.57%, and decreasing to 60,892.65 km2 in 2014, accounting for 20.51%, which do not return to the level of 1992. Sandy land desertification is mainly slight and moderate, accounting for 53.29% and 45.73%, respectively, in 2014. Sandy desertification land in the Ali area is mainly distributed among intermountain basins, river valleys, lake basins, piedmont plains and other landform units. The landform and wind speed are the main natural factors that determine the spatial distribution pattern of sandy desertification land in the Ali area, that is, the spatial distribution pattern of sandy desertification land in the Ali area is the coupled result of sand source and wind speed.

Digital mapping of soil texture classes for efficient land management in the Piedmont plain of Iran

AbstractAccurate prediction of digital soil maps allows for the evaluation of larger areas with respect to the design of efficient land management plans at the regional scale. Nowadays, there is an increasing demand for high spatial resolution‐gridded soil data for crop planning and management because it saves time and costs. One of the most essential soil physical properties affecting water holding capacity, nutrient availability and crop growth is soil texture. It exhibits a high spatial variability, but accurate maps for larger scales are lacking. The aim of this research was to produce gridded maps of soil texture fractions (clay, silt and sand) using regression‐based approaches and to establish soil texture classes using classification‐based techniques for the semi‐arid Piedmont plain of Iran. To this end, a digital elevation model and derived topographic indices, vegetation and soil‐based indices generated from 4‐year timeseries of remote sensing products of Landsat 8 OLI were used as covariates. The decision tree (linear) and its improved version of random forest (nonlinear) algorithms were used for both the regression and classification analysis. For both algorithms, the topography‐based indices and remotely sensed products were the most important predictors for the soil particle fractions. For the estimation of the different textural classes with multiple algorithms, we recorded a moderate overall accuracy rate of 54% and a Kappa coefficient of 17% for the validation datasets. It was observed that the nonlinear classification method of the random forest was more effective, and this was also the case for the regression modelling. In general, the random forest algorithm produced a more useful gridded map to help to design regional management plans based on soil properties.

Characterizing the trend of channel braiding of a tropical transboundary river using spatial growth component analysis and ARIMA model

Channel braiding is one of the fundamental fluvial processes in the context of sediment-energy nexus. The present study intends to simulate the channel braiding pattern of a tropical river (Jaldhaka River) on the Himalayan foreland plains. The grain size of the bed material in the Jaldhaka River decreases with distance from the mountain front, as does the surface gradient from the piedmont plains to the northern alluvial plains accompanied by the development of alluvial fans. Such assemblage results in multiple facets of hydro-geomorphic controls on channel planform dynamicity. This study is one of the pioneering attempts to characterize the spatial and temporal trend of channel braiding in any river running through the foreland region of the Sikkim-Bhutan Himalayas. The type of channel braiding is determined by the three indices – (1) Braiding Index (BI*), (2) Channel Count Index (BI), and (3) Channel Length Index (Pt), in cases where no gradual and uniform trend of development has been seen.The spatial allometric growth of the channel braiding and time series association using the ARIMA model was examined on the twenty stretches of the river. The results depict nonuniformity in planform development with distance downstream during a 30-year time span (1990–2020). The nature of the planform value distribution concerning all three applied indices has projected a polynomial trend where certain intermediate channel segments break the general trend of the braiding intensity with downstream distance. Since the downstream braiding intensity of the Jaldhaka River hasn't decreased either linearly or exponentially, we were unable to find any significant relationship of it with surface gradient. The nature and association of the channel braiding of the Jaldhaka River point towards the influence of local controls (e.g. river terracing on the upper part and faultline controls in the middle part) on channel planform dynamicity. The prediction of channel braiding for 2030 and 2050 coupled with the model fitted with RMSE, and BIC bears great significance in revealing the future bar growth which may be useful for the different planners and stakeholders concerned with the river basin development.

Geomatics and smart tools in Digital Land Resources Mapping and Sustainability of Coastal Agriculture, Egypt

The northwestern coast of Egypt is characterized by an international interest due to its history and magnificent environment. The area was known as being the bread basket during the Greek and Roman periods. Recently, drastic changes in land use resulting in destructing many of water harvesting tools, thus diminution of the agriculture importance. Restoration of the area and planning self-sufficient communities needs to develop a sustainable land resources database for these regions. Multi concept of remote sensing and the Geographic Information System (GIS) permit to store, merge, and manipulate the huge amounts of thematic maps and attribute data. Sentinel satellite image 2018 scenes, covering the study area at the Egyptian northwestern coast, were acquired. ENVI software was used for image processing. A number of 53 topographic maps at scale 1:50000 were used to input GIS thematic layers relevant to land resources, using Arc_GIS 10.2 system. Field investigation was carried out to represent different soil units and collect ground control points. Chemical and physical soil properties were determined to assist soil classification. Soil map was produced including dominant geographic units and soil association. MicroLEIS system was employed to define soil suitability classes to olives, peach, wheat, beans, and sunflower crops. An intelligent module will be added to analyze the digital maps, interact the given data with learning tool (layer) to provide the decision makers with suggested solution not only information. The results showed that the soils are generally characterized by the presence of Calcic, Petrogypsic and Salic horizons. The limiting factors found in the piedmont and coastal plains are salinity, soil depth and texture. These factors decrease the suitability classes to be between S2 and S5.It can be concluded that the digital mapping of land resources using Geographic Information System (GIS) and satellite data preserve in the investment spent in soil and other thematic mapping.

Automated versus Manual Mapping of Gravel Pit Lakes from South-Eastern Romania for Detailed Morphometry and Vegetation

In recent years, the accelerated development of the remote sensing domain and the improvement of the resolution and frequency of satellite images allowed the increase in the accuracy of the evaluation of morphometric characteristics and the spatiotemporal distribution of pit lakes, including the small ones. Our study quantitatively analyzes small-scale pit lakes in the piedmont and subsidence plains from contact with the Getic and Curvature Subcarpathians from Romania using the normalized difference water index (NDWI) and data series, with different resolutions, from Landsat 8, Google Earth, and Sentinel 2A. The problems encountered in extracting the contours of the gravel pit lakes were determined by the different resolution of the images, the uneven quality of the images exported from Google Earth, and an additional challenge was given by the diversity of the analyzed land surfaces, the land use, and the optical properties of the lakes. A comparison of the obtained NDWI values using data series from Sentinel 2A and Landsat 8 highlighted the importance of resolution and also showed a larger spectral difference between the identified water bodies and the surrounding land in favor of Sentinel 2A. Regarding the vegetation-derived indices, superior leaf area index (1.8–3) was recorded in low-lying plains and mixed areas (tall shrubs, wetlands, etc.) because the river banks have increased moisture that supports taller species with denser foliage and the sparsely vegetated areas are located in agricultural crops and in/near villages. Changes in vegetation richness and abundance can be spatiotemporally monitored using indices derived from the spectral bands of satellite imagery.

Interaction Between Brackish Water Intermittent Infiltration and Cultivated Soil Environment: A Case Study From Arid Piedmont Plain of Northwest China

Brackish groundwater was widely used in arid areas which may cause soil salinization and groundwater environmental declines. To ensure the sustainable development of agriculture in arid areas, brackish water intermittent infiltration experiments were conducted in Southern Xinjiang, Northwest China between June to September 2018, and Hydrus-2D numerical simulation was used to analyze the underground pipe drainage systems. The field experiments were carried out during cotton growth stages after the first freshwater flood infiltration and salt washing. Two control experiments were, respectively, designed as freshwater (0.68 g/L) and brackish water (1.66 g/L) with water amount of 1.0 Q = 572 mm. Other eight groups (1.05–1.40 Q) were compared to analyze the effect of soil salt leaching by increasing the brackish water amount. The results showed that the soil moisture content was almost less than the field capacity of 0.203 at depth of 0–60 cm before each infiltration due to roots water uptake, and the soil water holding capacity rate was lower than 0.2 after 5 days under 1.20–1.40 Q brackish water treatments. Variation of EC1:5 at depth of 0–30 cm was less than 0.5 dS/m. Salt mainly accumulated at the depth of 40–60 cm whether the water amount was excessive or insufficient even under the fresh water infiltration. The optimal brackish water amount was 1.15 Q = 657.8 mm, and the soil total salinity was less than 0.55 dS/m (EC1:5) and reached mild salinization degree. Numerical simulations were used based on the 2018 field experimental results and extended by another 10 years. The soil salt accumulated to 1.10–2.99 dS/m (EC1:5) at the depth of 40–60 cm during 0–30 days. The no salinization area expanded to depth of 40–45 cm after 120 days and reduced during non-infiltration period due to evaporation effect. The soil salt was gradually leached and less than 0.55 dS/m (EC1:5) after 10 years. The optimized leaching–drainage system could not only provide a low salinity soil condition for cotton growth and realize sustainable cultivation but also greatly protect the soil and groundwater environment.

Hydrochemical Characteristics and Genetic Analysis of Shallow High-Fluorine Groundwater in Fuyang River Basin

In order to understand the sustainable and effective utilization of groundwater resources in Fuyang River Basin, the chemical characteristics and genetic evolution process of characteristic shallow fluoride groundwater in the region were carried out. The results show that the chemical characteristics of groundwater are zonal in horizontal direction. From the piedmont plain to the central plain, the hydrochemical types of the first and second aquifers are mainly HCO3-Ca-Mg-type water, HCO3-Cl-Ca-Mg-type water, Cl-SO4-Na-Ca-type water, and Cl-SO4-Na-Mg-type water. The main mineral sources of hydrochemical ions are salt rock, carbonate rock, sulfate rock, and silicate rock. F- has a significant positive correlation with HCO3- while it is negatively correlated with K+. In the strong evaporation and alkaline environment created by climatic conditions in the study area, F- mainly comes from the dissolution of minerals. Gypsum and fluorite are in a relatively stable dissolved state continuously providing F- and Ca2+ for groundwater; the adsorption of cation was gradually strengthened from the piedmont plain to the central plain. The high HCO3- content is also conducive to F- desorption in alkaline environments. The samples with F- concentration greater than 1 mg·L-1 accounted for 35.7% and mainly distributed in the south of the study area. In summary, the chemical characteristics of shallow groundwater in Fuyang River Basin are affected by the combined effects including leaching effect, evaporation concentration, ion exchange-desorption, and human factors.