Assessment of agricultural groundwater users in Iran: a cultural environmental bias

Many environmental problems are rooted in human behavior. This study aimed to explore the causal effect of cultural environmental bias on ‘sustainable behavior’ among agricultural groundwater users in Fars province, Iran, according to Klockner’s comprehensive model. A survey-based research project was conducted to gathering data on the paradigm of environmental psychology. The sample included agricultural groundwater users (n = 296) who were selected at random within a structured sampling regime involving study areas that represent three (higher, medium and lower) bounds of the agricultural-groundwater-vulnerability spectrum. Results showed that the “environment as ductile (EnAD)” variable was a strong determinant of sustainable behavior as it related to groundwater use, and that EnAE had the highest causal effect on the behavior of agricultural groundwater users. The adjusted model explained 41% variance of “groundwater sustainable behavior”. Based on the results, the groundwater sustainable behaviors of agricultural groundwater users were found to be affected by personal and subjective norm variables and that they are influenced by casual effects of the “environment as ductile (EnAD)” variable. The conclusions reflect the Fars agricultural groundwater users’ attitude or worldview on groundwater as an unrecoverable resource; thus, it is necessary that scientific disciplines like hydrogeology and psycho-sociology be considered together in a comprehensive approach for every groundwater study.     

Uncertainty of climate change impact on crop characteristics: a case study of Moghan plain in Iran

Theoretical and Applied Climatology - Crop yield is one of the most critical factors in the food security chain. Climate plays a crucial role in crop water productivity in rainfed and irrigated...     

Rock Type Connectivity Estimation Using Percolation Theory

Complicated sedimentary processes control the spatial distribution of geological heterogeneities. This serves to make the nature of the fluid flow in the hydrocarbon reservoirs immensely complex. Proper modeling of these heterogeneities and evaluation of their connectivity are crucial and affects all aspects of fluid flow. Since the natural variability of heterogeneity occurs in a myriad of length scales, accurate modeling of the rock type connectivity requires a very fine scheme, which is computationally very expensive. Hence, this makes other alternative methods such as the percolation approach attractive and necessary. The percolation approach considers the hypothesis that a reservoir can be split into either permeable (sand/fracture) or impermeable rocks (shale/matrix). In this approach, the connectivity of the permeable fraction governs the flow. This method links the global properties of the system to the density of the permeable objects distributed randomly in the system. Moreover, this approach reduces many results to some simple master curves from which all-possible outcomes can be predicted by simple algebraic transformations. The current study contributes to extending the applicability of the methodology to anisotropic systems as well as using the complicated and more realistic sandbody shapes (for example, ellipsoids). This enables us to attain a better assessment of the connectivity and its associated uncertainty of the complicated rock types. Furthermore, to validate the approach, the Burgan reservoir dataset of the Norouz offshore oil field in the south of Iran was used. The findings are in conformity with the percolation approach predictions.     

Evaluating the performance of artificial intelligence methods for estimation of monthly mean soil temperature without using meteorological data

Soil temperature has an important role in agricultural, hydrological, meteorological and climatological studies. In the present research, monthly mean soil temperature at four different depths (5, 10, 50 and 100 cm) was estimated using artificial neural networks (ANN), adaptive neuro-fuzzy inference system (ANFIS) and gene expression programming (GEP). The monthly mean soil temperature data of 31 stations over Iran were employed. In this process, the data of 21 and 10 stations were used for training and testing stages of used models, respectively. Furthermore, the geographical information including latitude, longitude and altitude as well as periodicity component (the number of months) was considered as inputs in the mentioned intelligent models. The results demonstrated that the ANN and ANFIS models had good performance in comparison with the GEP model. Nevertheless, the ANFIS generally performed better than ANN model.     

Using InSAR to identify hydrological connectivity and barriers in a highly fragmented wetland

Hydrological connectivity is a critical determinant of wetland functions and health, especially in wetlands that have been heavily fragmented and regulated by human activities. However, investigating hydrological connectivity in these wetlands is challenging due to the costs of high-resolution and large-scale monitoring required in order to identify hydrological barriers within the wetlands. To overcome this challenge, we here propose an interferometric synthetic aperture radar (InSAR)-based methodology to map hydrologic connectivity and identify hydrological barriers in fragmented wetlands. This methodology was applied along 70 transects across the Baiyangdian, the largest freshwater wetland in northern China, using Sentinel 1A and 1B data, covering the period 2016–2019. We generated 58 interferograms providing information on relative water level changes across the transects that showed the high coherence needed for the assessment of hydrological connectivity. We mapped the permanent and conditional (temporary) barriers affecting connectivity. In total, 11% of all transects are permanently disconnected by hydrological barriers across all interferograms and 58% of the transects are conditionally disconnected. Areas covered by reed grasslands show the most undisturbed hydrological connectivity while some of these barriers are the result of ditches and channels within the wetland and low water levels during different periods of the year. This study highlights the potential of the application of Wetland InSAR to determine hydrological connectivity and location of hydrological barriers in highly fragmented wetlands, and facilitates the study of hydrological processes from large spatial scales and long-time scales using remote sensing technique.     

Impact of water source dynamics on dissolved reactive phosphorus loadings in heterogenous karst agroecosystems with phosphatic limestones

Karst landscapes underlain with phosphatic limestones are now recognized to be an important contributor of fluvial phosphorus (P) to coastal waters. Specifically, karst agroecosystems may be a hotspot for dissolved reactive P (DRP) due to chronic over-application of organic and inorganic fertilizers that create legacy P accumulation in surface soils. Nevertheless, few studies have assessed the hydrologic controls on DRP transport in these systems at the watershed scale, which is the focus of this study. We analysed soil moisture, soil water extractable P, and storm event hydrologic and water quality data from a small heterogenous karst watershed (10.7 km²) in the Inner-Bluegrass Region of Central Kentucky, USA. Four storm events were sampled in winter, 2020 and were analysed for flow pathways using hydrograph recession analysis and water source connectivity using a tracer-based unmixing model. Based on hydrograph separation results, multiple linear regression analysis was performed to assess drivers of DRP concentrations and loadings. Soil water extractable P results showed stark vertical gradients with greater concentrations at both the surface and deeper soil zones, and minimum concentrations in the root zone. Results for the storm event analysis showed that water source connectivity provided superior prediction of DRP concentrations over the flow pathway analysis, which reflected the heterogeneity of karst maturity masking intermediate flow pathways. Findings from the MLR and loading analysis suggest waters sourced from the soil/epikarst produced significantly higher loadings compared with phreatic and precipitation water source in the three largest events, although concentrations fell between the phreatic (low) and precipitation (high) sources. Findings highlight variable activation of matrix-macropore exchange at different depths throughout the event. Collectively these results suggest existing models and approaches to assess karst hydrology need revision to improve management strategies in this critical landscape.     

Carbonate diagenesis of the upper Jurassic successions in the west of Binalud — Eastern Alborz (NE Iran)

The upper Jurassic carbonate settings in Iran are widely exposed in north and northeastern parts. Five stratigraphic columns were selected in the north eastern Iran. Their thickness ranges from 330 to 500 m. The various diagenetic processes identified include, micritization, cementation, compaction (physical and chemical), dissolution, neomorphism, pyritization, hematitization, silicification and dolomitization, which affected these carbonates. Elemental and stable isotopes analysis indicated that these deposits have undergone both meteoric and burial diagenesis in a relatively open system with moderate water-rock interaction. The positive trend between trace elements and oxygen isotope depletion also support these burial conditions. Lighter δ^l8O values of the dolomite samples may be related to an increase in temperature during the burial, which correspond to coarser euhedral crystals. Relatively higher δ¹⁸O values in finer dolomite crystals indicate their formation at lower burial depths relative to coarser crystals. Petrographic evidences such as coarse euhedral crystals with bright and dull zonation prove this interpretation. Chert nodules also have lighter ¹⁸O values relative to carbonate host rock, thus indicating the influence of burial diagenetic processes in their formation. The average environmental palaeotemperature was estimated to be 26°C on the basis of oxygen isotope values of less altered lime-mudstones.     

Total Suspended Sediments Mapping by Using ALOS Imagery Over the Coastal Waters of Langkawi Island, Malaysia

Remote sensing has been extensively used for water delineation and has played an important role in water quality evaluation and environmental management strategies. Suspended sediments are important determinants of water quality in coastal zones. Remote sensing enables the effective monitoring of total suspended sediments (TSS) and the detection of areas with critical water quality issues. This study aims to develop and implement regression models for estimating and mapping TSS concentrations from Advanced Land Observation Satellite (ALOS) images over the coastal waters of Langkawi Island, Malaysia. The algorithm was developed based on the water reflectance model, which is a function of the inherent optical properties of water. Such properties can then be linked to TSS concentration. In this study, an ALOS Advanced Visible and Near Infrared Radiometer type 2 device was used as the imaging sensor system. Concurrent complementary in-situ water samples were collected within the area coverage of the sensor, and digital numbers (DN) for each band corresponding to the sea-truth locations were determined. The extracted DN values were converted into reflectance values and then regressed with their respective sea-truth data. An algorithm was proposed to obtain the regression coefficient. This algorithm can estimate TSS concentrations with a high correlation coefficient (R²?=?0.96) and low root-mean-square error (RMSE?=?1.98 mg/l). Finally, a map of the TSS concentration was generated by using the proposed algorithm. This study found that TSS mapping can be conducted by using ALOS data over the coastal waters of Langkawi Island, Malaysia.     

The measurement of gamma-emitting radionuclides in beach sand cores of coastal regions of Ramsar,Iran using HPGe detectors

Radionuclides which present in different beach sands are sources of external exposure that contribute to the total radiation exposure of human. ²²⁶Ra, ²³⁵U, ²³²Th, ⁴⁰K and ¹³⁷Cs analysis has been carried out in sand samples collected at six depth levels, from eight locations of the northern coast of Iran, Ramsar, using high-resolution gamma-ray spectroscopy. The average Specific activities of natural radionuclides viz., ²²⁶Ra, ²³⁵U, ²³²Th, ⁴⁰K and ¹³⁷Cs, in the 0–36 cm depth sand were found as: 19.2 ± 0.04, 2.67 ± 0.17, 17.9 ± 0.06, 337.5 ± 0.61 and 3.35 ± 0.12 Bq kg⁻¹, respectively. The effects of organic matter content and pH value of sand samples on the natural radionuclide levels were also investigated. Finally, the measured radionuclide concentrations in the Ramsar beach were compared with the world average values, as reported by UNSCEAR (2000). None of the studied beaches were considered as a radiological risk.