Mashhad Plain Research Articles

Integrated approach to water resource management in Mashhad Plain, Iran: actor analysis, cognitive mapping, and roadmap development.

Iran's Mashhad Plain faces a severe water crisis due to the excessive exploitation of groundwater, leading to the depletion of its aquifer. While water demand management is recognized as a superior solution compared to supply projects, its implementation presents notable challenges. This study addresses the urgent necessity to curtail water demand in the Mashhad Plain by alleviating conflicts among various stakeholders, including water resource managers and consumers. Initially, the research identifies key water resource actors who collaborate in devising a comprehensive roadmap and conceptual model for efficient water resource management. An analysis uncovers significant conflicts among actors, representing approximately 6% of identified issues, with minor conflicts in 30% of cases. Encouragingly, stakeholders demonstrate potential for consensus on the remaining conflict items, with specific actors emerging as pivotal in conflict resolution. Efficient water resource management in regions facing scarcity, diverse interests, and sustainability challenges demands a multifaceted strategy. Future endeavors involve developing a dynamic system model to simulate policy impacts and strengthen conflict resolution efforts. This research introduces a roadmap-driven approach aimed at resolving conflicts and implementing water demand management in the Mashhad Plain. It emphasizes the critical need to address water scarcity challenges while effectively mitigating conflicts among water resource stakeholders.

Developing a fuzzy integrated index to assess the value of water resources using quantity, quality, and socioeconomic parameters (case study: Mashhad plain)

Developing a fuzzy integrated index to assess the value of water resources using quantity, quality, and socioeconomic parameters (case study: Mashhad plain)

Digital mapping of selected soil properties using machine learning and geostatistical techniques in Mashhad plain, northeastern Iran

Understanding the spatial variation of soil properties is essential for monitoring land capabilities as well as the sustainable management of soil resources. The aim of this study was to predict digital soil properties mapping using 23 environmental variables, i.e., terrain attributes and remote sensing (RS) indices, across 1500 km2 of Mashhad plain lands. To achieve this purpose, a total of 180 soil samples (0–10 cm) were taken. The random forest (RF) model combined with ordinary kriging (OK), as well as regression kriging (RK), were applied to relate environmental variables and the studied soil properties. The results revealed that RF-OK was the best model with R2 and RMSE for silt (0.89% and 0.10%), followed by calcium carbonate equivalent (0.88% and 3.30%), clay (0.87% and 2.26%), soil organic carbon (0.86% and 0.24%), sand (0.84% and 4.21%), and pH (0.82% and 5.42%). The RS covariates, including band 5 (B5), modified soil-adjusted vegetation index (MSAVI), difference vegetation index (DVI), band 2 (B2), carbonate rock index (CRI2), gypsum index (GI), and enhanced vegetation index (EVI), and terrain attributes, including topographic wetness index (TWI) and elevation (EL), and topographic position index (TPI), were the most important variables in modeling different soil properties. RF-OK showed the prediction and uncertainty maps related to high precision and low standard deviation in most study areas, which indicate low overfitting and overtraining in modeling processes. In general, the RF-OK model, with low cost and high accuracy, can be applicable to use for predicting different soil properties, as well as spatial information acquired from an effort to maps to managing agriculture in areas at different conditions. Finally, this method can be applied to other regions of similar properties and for similar purposes.

Identification of hidden faults using determining velocity structure profile by spatial autocorrelation method in the west of Mashhad plain (Northeast of Iran)

Identification of hidden faults using determining velocity structure profile by spatial autocorrelation method in the west of Mashhad plain (Northeast of Iran)

Effects of excessive water extraction on groundwater ecosystem services: Vulnerability assessments using biophysical approaches

In this research, a systematic, integrated framework was developed to evaluate the biophysical state and vulnerability intensity of groundwater supply ecosystem service (GSES) regarding excessive groundwater withdrawal in the Mashhad plain located in the northeastern of Khorasan Razavi province in Iran. At first, following an indexing approach, the biophysical aspects of the ecosystem, including capacity, flow, and the benefits of GSES, were analyzed. Afterward, the relationship between the capacity and flow ecosystem service (ES) was assessed to identify ecosystem's sustainability status. Furthermore, GSES stability was spatially shown. Finally, GSES vulnerability and its associated ESs was assessed based on 3D model of vulnerability via indexing three components of exposure, sensitivity, and adaptive capacity. The final map spatially indicated the zoning of groundwater ecosystem services’ vulnerability intensity in Mashhad Plain. The outcomes indicate a high and very high vulnerability in more than 35% of studying area. The results indicate that about 18%, 30%, and 15% of studying land show moderate, low, and no vulnerability, respectively. Finally, it was observed that due to groundwater's over-extraction, supplying the aquifer ecosystem services was disrupted. This method can be used as a solution for the sustainable management of groundwater resources, especially in the arid and semi-arid countries facing the depletion of water resources.

Evaluation of Integrating SWAT Model into a Multi-Criteria Decision Analysis towards Reliable Rainwater Harvesting Systems

Rainwater harvesting (RWH) has been recognized as one of the most reliable and efficient methods for water supply, especially in arid and semi-arid regions (ASARs) facing freshwater scarcity. Nevertheless, due to the inherent uncertainty of input data and subjectivity involved in the selection of influential parameters, the identification of RWH potential areas is a challenging procedure. In this study, two approaches for locating potential RWH sites were implemented. In the first approach, a frequently-used method of the multi-criteria decision analysis and geographic information system (MCDA-GIS) was utilized, while, in the second approach, a novel strategy of integrating the soil and water assessment tool (SWAT) model as a hydrology model into an MCDA-GIS method was proposed to evaluate its performance in locating potential RWH sites. The Mashhad Plain Basin (MPB) was selected as a case study area. The developed potential RWH maps of the two approaches indicated similar patterns for potential RWH areas; in addition, the correlation coefficient (CC) between the two obtained maps were relatively high (i.e., CC = 0.914) revealing that integration of SWAT as a comprehensive hydrologic model does not necessarily result in very different outputs from the conventional method of MCDA-GIS for RWH evaluation. The overlap of developed maps of the two approaches indicated that 3394 km2 of the study area, mainly located in the northern parts, was identified as high-potential RWH areas. The performed sensitivity analysis indicated that rainfall and slope criteria, with weights of 0.329 and 0.243, respectively, had the greatest sensitivity on the model in the first approach while in the second approach, the criterion of runoff coefficient (with weights of 0.358) had the highest impact. Based on results from the identification of the potential locations for conventional RWH techniques, pond and pan techniques are the most proper options, covering high-potential areas of RWH more effectively than other techniques over MPB.

Effects of contamination with gasoline on engineering properties of fine-grained silty soils with an emphasis on the duration of exposure

Leaking tanks may lead to severe contamination of their surrounding soil. The geotechnical behavior of the soil varies with the physicochemical processes that occur between the contaminant and the soil. In this respect, studying the geochemical properties of gasoline-contaminated soils and sediments seems to be important for engineering and especially environmental purposes. In this paper, laboratory tests were carried out to examine the effects of crude gasoline contamination on some of the geotechnical properties of a silty soil sampled from the Mashhad plain, located in the northeast of Iran. Tests consisted of basic properties, Atterberg limits, compaction, direct shear, and uniaxial compression tests, which were carried out on clean and contaminated soil samples at the same densities. The contaminated samples were prepared by mixing the soils with crude gasoline in the amounts of 3%, 6%, 9%, and 12% of dry weight and curing periods of 0, 7, 15, and 30 days. Results indicated a decrease in the friction angle and an increase in the cohesion of the soil by increasing gasoline content. Besides, a reduction in the maximum dry density and optimum moisture content was observed in the compaction test. The increase in gasoline percentage up to 6% also showed a direct effect on increasing the liquid limit and plastic limit of silty soil, which decreased thereafter. Moreover, any increase in gasoline percentage had a reverse effect on the modulus of elasticity of the soil. The increase in gasoline percentage up to 3% also had a direct impact on the uniaxial compressive strength of the soil, exceeding which it started to decline. Finally, the effects of contamination duration were examined by testing contaminated samples in periods of 7, 15, and 30 days under natural conditions. The results showed a reverse relationship with all geotechnical properties due to aging and a reduction in the gasoline content due to the evaporation of volatile compounds. Also, the numerical analysis of the laboratory results indicated an increase in settling and the percentage of shear strain beneath the foundation with increasing the contamination level, confirming the laboratory results.

Evaluation of a machine-based learning method to estimate the rate of nitrate penetration and groundwater contamination

Groundwater is among the most important water resources around the globe. However, their contaminations are more difficult, costly, and time-consuming to detect and control than those of surface waters. Therefore, the preparation and deployment of vulnerability maps can help monitor and prevent contamination. In this study, the risk assessment of groundwater nitrate contamination was performed. For this purpose, nitrate concentration data in 130 wells in the Mashhad Plain were used to prepare the contamination mapping. Four machine learning models were used to assess the probability of groundwater contamination, including generalized linear model (GLM), boosted regression trees (BRT), and support vector machine (SVM). The validity of each model was assessed by the AUC characteristic curve. To mix the models, a minimum threshold of 80% was assumed. The results showed that the accuracy of the four models ranged from 80 to 90%, so all models were considered in the combination section. Considering the risk map of groundwater contamination due to vulnerability, contamination, and probability mapping, the western and southwestern areas of the aquifer are at high and very high risks of being exposed to nitrate contamination, which is consistent with the land use map of agricultural and urban areas. According to the results, the ensemble method can provide good efficiency.

Landscape Archaeological Approach to Explain the Settlement and Cultural Pattern of Kashfarud Basin (Mashhad Plain) from Neolithic to Middle Bronze.

Landscape Archaeological Approach to Explain the Settlement and Cultural Pattern of Kashfarud Basin (Mashhad Plain) from Neolithic to Middle Bronze.

DETERMINING SUITABLE LANDFILLS FOR DRY AND WET URBAN WASTESTHROUGH COMBINATION OFGIS AND AHP (CASE STUDY: MASHHAD PLAIN)

Ponte Academic JournalFeb 2020, Volume 76, Issue 2 DETERMINING SUITABLE LANDFILLS FOR DRY AND WET URBAN WASTESTHROUGH COMBINATION OFGIS AND AHP (CASE STUDY: MASHHAD PLAIN)Author(s): Amir Shahriar Faghihnia Torshizi ,Ebrahim AlamatianJ. Ponte - Feb 2020 - Volume 76 - Issue 2 doi: 10.21506/j.ponte.2020.2.1 Abstract:The population of the country, and especially of the urban population, has increased over the past decades, with 75% of the urban population now having such a population at the country that has increased the amount of wet and dry waste; The amount of rainfall and prolongation of the drought period and the reduction of groundwater levels have increased the importance of attention to groundwater. The purpose of this study is to present a model to determine optimal locations for landfill by applying GIS and Hierarchical Analysis Model. In this research, water resource indices, distance from infrastructure, natural environment and human-made environment are used. To determine the weight of each criterion and sub criterion, a paired comparison questionnaire was prepared and distributed among 40 experts and their managers and their opinions were collected and entered into the model. According to the results, the criteria of water resources and manmade environment are in the first and second ranks with weights of 0.339 and 0.229, respectively. Infrastructure (0.221) and natural environment (0.159) met the third and fourth ranks. Finally, by integrating the weights obtained with the layers of GIS environment, three zones were suggested as suitable sites for landfill in Mashhad. Download full text:Check if you have access through your login credentials or your institution Username Password

A Hybrid Meta-Heuristic for a Bi-Objective Stochastic Optimization of Urban Water Supply System

The restoration and remodeling of the urban water supply system are traditional challenges for water companies due to either aged existing water supply networks or lodging expansion. These challenges involve the uncertainties induced by their lengthy-planned prospects and the impossible exact prediction of forthcoming events. In this regard, correlations exacerbate unpredictable data and parameters and probably undermine taking effective decisions in this context. Therefore, the remodel and restoration decision of water supply systems must be made using approaches that can effectively deal with correlation uncertainties. The present study develops a bi-objective stochastic optimization model that can handle interrelated uncertain parameters in the water supply system remodeling and restoration issue. The proposed mathematical model is validated using the data of the Mashhad Plain water supply system as a real case study, followed by performing and comparing different levels of conservatism and reliability. As a complex optimization problem, an efficient algorithm is needed to solve the problem. To this end, a hybrid meta-heuristic algorithm, which is a combination of the Red Deer Algorithm (as a newly introduced nature-inspired heuristic) and Simulated Annealing (as a traditional local search algorithm), is proposed. Considering the advantages of these algorithms, it is possible to alleviate the disadvantages of current methods when solving large-scale networks. Finally, an extensive comparison and discussion are made and then the main findings with practical solutions are presented to significantly evaluate the proposed model and algorithm.

A multi-criteria decision analysis approach towards efficient rainwater harvesting

Rainwater Harvesting (RWH) is becoming one of the most promising alternative sources of fresh water which can be potentially captured and utilized, particularly in arid and semi-arid regions (ASARs). However, identification of potential sites for RWH on a large scale has always been a great challenge, and therefore, requires further studies. Most recent studies on this topic select RWH zones employing Geographic Information Systems (GIS), combined with multi-criteria analysis and hydrological models. Nevertheless, there are a few studies, mostly in small catchments, that locate potential zones considering socio-economic factors. In this paper, a GIS-based Multi-Criteria Decision Analysis (MCDA) is presented to identify potential RWH areas incorporating socio-economic factors including distance from drainage networks, roads, urban areas, faults, farms and wells. The proposed methodology was implemented at a large catchment scale in Mashhad Plain Basin with an area of 9762 (km2) located in the northeast of Iran. Results show that 48% of the study area is not suitable for RWH. The rest of the study area is divided into three potential zones that are poor, moderate and good for RWH, covering 31%, 43%, and 26% of the potential areas, respectively. Ponds and pans, check dams and terracing were considered as the best practices for the good RWH potential areas. Preliminary estimates suggest that up to 158, 135 and 110 M m3 of precipitation could be received respectively by each system.

The use of multivariate statistical analysis and soil quality indices as tools to be included in regional management plans. A case study from the Mashhad Plain, Iran

Several methods have been used to model reality and explain soil pedogenesis and evolution. However, there is a lack of information about which soil properties truly condition soil quality indicators and indices particularly at the pedon scale and at different soil depths to be used in land management planning. Thus, the main goals of this research were: i) to assess differences in soil properties (particle size, saturation point, bulk density, soil organic carbon, pH and electrical conductivity) at different soil depths (0-30 and 30-60 cm); ii) to check their statistical correlation with soil quality indicators (CEC, total N, Olsen-P, available K, exchangeable Na, calcium carbonate equivalent, Fe, Mn, Zn, and Cu); and, iii) to elaborate a soil quality index and maps for each soil layer. To achieve this, forty-eight soil samples were analysed in the laboratory and subjected to statistical analyses by ANOVA, Spearman Rank coefficients and Principal Component Analyses. Finally, a soil quality index was developed based on indicators of sensitivity. The study was conducted in a semiarid catchment in northeast Iran with irrigated farming and well-documented land degradation issues. We found that: i) organic carbon and bulk density were not similar in the topsoil and subsoil; ii) calcium carbonate and sand content conditioned organic carbon content and bulk density; iii) organic carbon showed the highest correlations with soil quality indicators; iv) particle size conditioned cation-exchange capacity; and, v) heavy metals such as Mn and Cu were highly correlated with organic carbon due to non-suitable agricultural practices. Based on the communality analysis to map of soil quality, CEC, Mn, Zn, and Cu had the highest weights (≥0.11) at both depths, coinciding with the same level of relevance in the multivariate analysis. Exchangeable Na, CaCO3, and Fe had the lowest weights (≤0.1) and N, P, and K had intermediate weights (0.1- 0.11). In general, the map of the soil quality index shows a lower soil quality in the subsoil increment than in the topsoil.

The effect of Tous fault on groundwater resources in northern parts of Mashhad plain

Mashhad Plain affects by a series of active faults in the northern margin of the Binalud and the southern margin of the Kopet-Dagh mountain ranges. The activity of these faults forms the morphology of the stepped bedrock of the Plain. In addition, the faults’ activities in the Quaternary period are the main effective parameters in thickness and texture of aquifer deposits in Mashhad Plain. In this regard, one of the active and important faults in Mashhad Plain is Tous fault, which runs from the northwest of Mashhad Plain into the city of Mashhad. The present research aims to analyze the effect of this fault on groundwater resources in the north of Mashhad Plain. For this purpose, ancient geoelectric studies and many well logs data are gathered, interpreted and by the combination of all of the geology information a new model for groundwater resource of the area proposed. The results of this study indicate that activities of Tous fault results to the uplifting of the Neogene Marly bedrock of Mashhad Plain, which such as a barrier prevents the flow of groundwater from the northern plain to the main aquifer of Mashhad Plain, and practically has divided the alluvial aquifer of Mashhad Plain into two parts. The maximum sediment thickness can be seen adjacent to the fault in the north of the Tous region and the tomb of Ferdowsi.

Geological parameters affected land subsidence in Mashhad plain, north-east of Iran

Mashhad plain is an area with a dry-to-semi-dry climate in Razavi Khorasan Province, Iran. About 60% of 6 million population of the province live in this plain, and mainly in Mashhad city. Overexploitation of ground water during the past decades has led to a severe drop in groundwater table and land subsidence. In this respect, some parts of the plain show an annual groundwater-level decline of 1.5 m. The surface subsidence features such as rising of the well casing, well collapse, and tension cracks observed in different parts of the area. Studying of ENVISAT ASAR images in a period of 2003/06/30 to 2010/05/24 shows the maximum subsidence rate of 32 cm/year in the north-west of the Mashhad city, but there was a mismatch between groundwater drop and ground subsidence in some parts of the plain. The evaluation of geological characteristics of subsidence area reveals, in addition to the groundwater decline, tectonic condition and active faults which change the bedrock depth have a key role in the pattern and rate of subsidence. Also, consolidation of the Pleistocene marl bedrock located in the central part of the plain is effective in the increased subsidence rate of the study area.

River basin-scale flood hazard assessment using a modified multi-criteria decision analysis approach: A case study

Flood is a major natural hazard with extremely large impact on social-ecological systems. Therefore, developing reliable and efficient tools to identify areas vulnerable to potential flooding is vital for water managers, engineers and decision makers. Moreover, being able to accurately classify the level of hazard is a step forward towards more efficient flood hazard mapping. This study presents a multi-criteria index approach to classify potential flood hazards at the river basin scale. The presented methodology was implemented in the Mashhad Plain basin in North-east Iran, where flood has been a major issue in the last few decades. In the present study, seven factors, selected based on their greater influence towards flooding, were identified and extracted from the basic thematic layers to be used to generate a five-class Flood Hazard Index (FHI) map. The Soil and Water Assessment Tool (SWAT) was used to develop a runoff coefficient map, which was found to be the most influential factor. A sensitivity analysis was performed and the results incorporated to generate a modified Flood Hazard Index (mFHI) map. The accuracy of the proposed method was evaluated against the well-documented flood records in the last 42 years at the study area. The results showed that, for both FHI and mFHI maps, more than 97% of historical flood events have occurred in moderate to very high flood hazard areas. This demonstrates that incorporating hydrological model (such as SWAT) and multi-criteria analysis introduces a robust methodology to generate comprehensive potential flood hazard maps. Moreover, the proposed modified methodology can be used to identify high potential flood hazard zones and work towards more efficient flood management and mitigation strategies.

Ecological risk assessment and source apportionment of heavy metal contamination in agricultural soils of Northeastern Iran

ABSTRACTThe present work was designed to study the pH, sand, silt, clay, lime, organic carbon (OC), cation exchange capacity and heavy metals (Fe, Mn, Cu and Zn) in agricultural soils of Mashhad plain, Northeastern Iran. Pearson’s correlation analysis showed that OC influenced the retention of Cu and Mn in both surface and subsurface agricultural soil samples. The results of contamination factor, pollution index and potential ecological risk (RI) indicated low pollution of Mn, Zn and Cu in the agricultural soil samples. The enrichment factor showed very high enrichment of heavy metals in surface (88.1%) and subsurface (79.1%) agricultural soil samples. The geoaccumulation index also indicated very high contamination of heavy metals in surface (87.5%) and subsurface (82.6%) soil samples. The modified potential ecological risk (MRI) showed 37.5% ecological risk in surface, and 32.5% ecological risk in subsurface soil samples of Mashhad plain, Northeastern Iran.Abbreviation: Fe: Iron; Mn: Manganese; Cu: Copper; Zn: Zinc; PCA: Principal component analysis; CA: Cluster analysis; CF: Contamination factor; EF: Enrichment factor; Igeo: Geoaccumulation index; PI: Pollution index; MPI: Modified pollution index; RI: Potential ecological risk index; MRI: Modified potential ecological risk index

Groundwater Augmentation through the Site Selection of Floodwater Spreading Using a Data Mining Approach (Case study: Mashhad Plain, Iran)

It is a well-known fact that sustainable development goals are difficult to achieve without a proper water resources management strategy. This study tries to implement some state-of-the-art statistical and data mining models i.e., weights-of-evidence (WoE), boosted regression trees (BRT), and classification and regression tree (CART) to identify suitable areas for artificial recharge through floodwater spreading (FWS). At first, suitable areas for the FWS project were identified in a basin in north-eastern Iran based on the national guidelines and a literature survey. Using the same methodology, an identical number of FWS unsuitable areas were also determined. Afterward, a set of different FWS conditioning factors were selected for modeling FWS suitability. The models were applied using 70% of the suitable and unsuitable locations and validated with the rest of the input data (i.e., 30%). Finally, a receiver operating characteristics (ROC) curve was plotted to compare the produced FWS suitability maps. The findings depicted acceptable performance of the BRT, CART, and WoE for FWS suitability mapping with an area under the ROC curves of 92, 87.5, and 81.6%, respectively. Among the considered variables, transmissivity, distance from rivers, aquifer thickness, and electrical conductivity were determined as the most important contributors in the modeling. FWS suitability maps produced by the proposed method in this study could be used as a guideline for water resource managers to control flood damage and obtain new sources of groundwater. This methodology could be easily replicated to produce FWS suitability maps in other regions with similar hydrogeological conditions.

Prioritize Agri-Environmental Measures of Water-Related Ecosystem Services: The Case of Mashhad

Current structure of agricultural input consumption eventually influences bases of natural environment and ecosystem services (especially water related) from which human communities benefit. This research aims at assisting decision making and prioritizing ecosystem services and their improvement measures according to interconnection of different ecosystem services and agri-environmental schemes of improving these services with help of fuzzy analytic network process (FANP) in Mashhad plain. Results show that among water-related ecosystem services, water quality and having healthy products, are first priorities. Providing needed water for agriculture section stands in the second rank with minor difference. Third and fourth places go to soil conservation and biodiversity relatively and agricultural tourism which is categorized under cultural services is placed in the last place. Also, based on this study results, among the seven agri-environmental water-related ecosystem services improvement, integrated pest management (IPM) ranks first. The second and third priorities belong to proposed crop pattern and conservative tillage implementation.

Spatial and fractal characterization of soil properties across soil depth in an agricultural field, Northeast Iran

The present study was conducted to explore the fractal behavior and establish fractal dimensions of soil physical and chemical properties (i.e., sand, silt, and clay contents, bulk density, degree of moisture saturation, pH, organic carbon content, total nitrogen, available phosphorus, and available potassium) to characterize their spatial patterns. Soil samples were collected from 0-30 (surface) and 30-60 cm (subsurface) depths from an agricultural field, Mashhad Plain, Northeast Iran. Descriptive statistics and fractal analysis were used to describe the extent and form of variability. Spatial patterns of the soil properties were estimated using GS+ 10.0 software. Soil properties showed low to high variations in both surface and subsurface layers across the field, where bulk density and pH being the most reliable soil physical and chemical properties in the study area. The variability was high (CV > 35%) for total N, available P, available K and organic carbon in both surface and subsurface soils and it could be attributed to management practices and micro-topographical variations as these are the dynamic properties of soil. The fractal dimension (D) values of soil physical properties ranged from 1.398 to 1.913 at the surface, and from 1.874 to 1.934 at the subsurface indicating both short and long range variations. The D values for the chemical properties ranged from 1.331 to 1.975, and 1.148 to 1.990 in the surface and subsurface layers, respectively. The results showed that fractal analysis could be employed to effectively describe the structure of soil heterogeneity in spatial scale for effective agricultural and environmental management of soil.