Abstract

This research is about how farmers adapt to water scarcity. Using experimental economics methods, field experiments were carried out in a region exposed to severe water scarcity in Colombia. Willingness of water users to cooperate in conforming to extraction caps, as a means of adapting to water availability declination was calculated. Two information treatment groups were implemented in order to assess water allocation decisions when: (i) the amount of water was reduced and (ii) time before aquifer exhaustion was announced. Extant literature on cooperation in common-pool resources (CPR) has focused on demonstrating to what extent resource users depart from egoistic attitudes. Alternatively, the sustainability of water resources requires more research to further understand cooperative behavior. Since the literature on water scarcity is classified in three orders, namely physical, institutional, and socio-political, behavioral dimensions are suggested as a subdivision of the social order. This, in turn, may help to operationalize strategies aimed at improving adaptation to all orders of scarcity. The quantitative results suggest that farmers are inclined to follow the cap. The main difference between the quantity and time treatments differs in that in the time treatments farmers allocate much more water to be consumed in the future, whereas in the former, they prefer to allocate more water to be consumed in the present. Adaptation options provide favorable inputs for implementing the Sustainable Development Goals, especially SDG 6, which is related to water use efficiency. Target 6.4 establishes that, by 2030, water efficiency and extraction sustainability should be accomplished. Thus, water policy interventions might benefit from this contribution. However, since success in water conservation programs might be difficult to achieve due to complexity in human-decision making, more research is needed to deepen our understanding of cooperation drivers in aquifer conservation.

Introduction

Despite the abundance and precision of current information on aquifers status ( van der Gun, 2022 ), this type of data – commonly managed by governmental institutions – rarely flows to the communities that depend upon them ( Margat & van der Gun, 2013 ). In effect, underground water availability data is currently assessed through satellite and underground monitoring of aquifer levels, but farmers´ communities do not have access to this information in a format they can readily use. Climate change is entering the aquifer overexploitation game as a new player ( Damania et al., 2017 ), since droughts are becoming more frequent than in the past ( UNWATER, 2023; Yuan et al., 2023 ); therefore, public environmental and water entities promote water conservation during droughts. Public entities usually stimulate the reduction of water extraction volumes by instructing users to consume less or save the resource. This information, however, lacks the necessary context and specificity, two features that play an important role in water extraction curbing adapted to ensuing water scarcity.

Although water scarcity has an important political dimension ( Metha, 2007 ), from the perspective of its physical and social dimensions, it can be observed how climate change is motivating farmers towards strategies to face the challenge. In spite of the complexity of hydrogeological information, farmers certainly want to know more about the status of the aquifers they are exploiting. They need information not only about the effects of their extraction decisions, but also about the way to moderate these decisions as an adaptation to scarcity according to aquifers’ statuses.

Conclusions

This article was designed for presenting the results on how farmers adapt to water scarcity. Framed field experiments were run to collect quantitative data on the decisions made by farmers when they were exposed to reductions in water availability. Time and water quantity treatment groups were prepared to test their effects on water allocation as limited by suggested extraction caps. Quantitative and qualitative analysis of data and information were carried out. Behavioral regularities and social institutions were drawn from the quantitative data and graphics and the narratives expressed by the players after the experiments.

The setting for the understanding of adaptation strategies was demarcated by the limits imposed by nature. For this reason, water availability as a physical limiting factor for water extraction was used as an instrument to connect allocation, decision-making and intertemporal consequences for adaptation. Thus, limited availability under time and quantity limits pushed the farmers (players) to decide whether to cooperate or not in water conservation. Thus, the individuals who cooperated better were adapting to water scarcity. More precisely, the farmers informed on time before aquifer exhaustion, revealed greater awareness about the possibilities of cooperation. Contrarily, in the control group situation, farmers allocated much more water to all uses and the cap volume was reached in most of the rounds. While in the time and quantity treatment groups, the aggregated water volumes declined through the time (rounds), in the control group this amount averaged 1800 m3 (close to the cap). It can be said that the communication amongst farmers on how to manage remaining stocks, and, similarly the hydrogeological information play a key role in incentivizing the cooperative behavior under extraction caps contexts. Since the stability of cooperation was part of the research aims, providing quantitative information to farmers on extraction decisions and the remaining time of aquifer availability is suggested as a key factor to more effectively address the adaptation to water scarcity.

Abstract

Significant population growth with rapid economic development have led to water scarcity problems around the world. Currently, most of the simple water scarcity assessment methods only refer to per capita water use, failing to take into account actual water availability and actual human domestic water use. Therefore, we have developed a simple and practical method to assess water scarcity, incorporating total water resources, water use efficiency, and the proportion of domestic water. In this approach, a new water scarcity index is employed to describe different levels of water scarcity using various thresholds based on the basic daily human water use per person. This may help to visualize the extent of water scarcity in a region while focusing on human interests. To illustrate this approach, we take China–the world’s largest developing country–as an example, analysing its nationwide water scarcity in 2021 while validating it with the results of other scholars on China’s water scarcity. The results show that our water scarcity assessment index is very accurate, revealing that in 2021, the disparity in water resources between the northern and southern regions of China remains substantial, with severe water scarcity still widely concentrated in northern China.

Introduction

Continuous water supply plays a vital role in daily life and social development ( Ethaib et al., 2022 ). However, increasing water consumption is due to the significant population growth and rapid economic development, resulting in extremely high water resource pressures, which cause water scarcity in numerous places around the world ( Liu et al., 2017 ). For instance, in regions such as Greater London with high population density, intense irrigation present in areas like the High Plains of the United States, and nations like India that exhibit both traits, there is a prevalent issue of water scarcity ( Mekonnen and Hoekstra, 2016 ). Nevertheless, in addition to direct water supply shortages caused by the forces of nature, human factors, as well as socio-political factors, are often overlooked, leading to the masking of the causes of scarcity. This complexity of water scarcity is labelled by Mehta as ‘real’ scarcity (related to socially and ecologically relevant physical phenomena like grass cover, fodder, distance to water for disadvantaged groups, cycles of natural resource abundance and scarcity, agro-meteorological hydrology, etc.) and ‘manufactured’ scarcity (constructing water scarcity as a perpetual and pervasive natural phenomenon, the industry of disaster relief and drought relief, and perverse benefits) ( Mehta, 2003 ). Moreover, there are also sudden and uncontrolled factors affecting water resources, such as the outbreak of the COVID-19 pandemic crisis, which has put many additional pressures on water resources, including the increase in local agricultural irrigation brought about by the localised production of food, and the parallel alteration of the virtual water trade caused by the changes that have taken place in the food trade ( Al-Saidi and Hussein, 2021 ).

Results

3.1. Statistical analysis of the results

A comparison of the water scarcity index calculated using Eq. (1) for each region of China, with a threshold of 0.2 (no stress), is shown in Fig. 2 . The results show that most regions in China are still suffering from water problems, including some economically developed cities with heavy water problems, such as Beijing (0.01), Tianjin (0.008), and Shanghai (0.02). In contrast, Qinghai (1.43) and Xizang (10.56) have abundant water resources, which are significantly higher than in other regions.

3.2. Spatial analysis of the results

In this study, ArcGIS Pro software was used to raster water resource data from various provinces in China in order to comprehensively and visually assess water scarcity across the country. As can be seen in Fig. 3 , the water scarcity index shows obvious spatial distribution differences, mainly between the northern and southern regions of China. Overall, the water scarcity index shows absolute scarcity in the north and no stress in the south. Specifically, a wide range of areas in northern China, including Inner Mongolia, Liaoning, and Shaanxi, exhibit water scarcity and some pressure on water resources. It is worth noting that some areas in the north also show absolute water scarcity, especially in Beijing, Tianjin, Hebei and Shanxi, indicating that the available water resources in these regions do not meet the minimum basic human needs of the region.

Abstract

     With the rapid increase in the volume of data on the aquatic environment, machine learning has become an important tool for data analysis, classification, and prediction. Unlike traditional models used in water-related research, data-driven models based on machine learning can efficiently solve more complex nonlinear problems. In water environment research, models and conclusions derived from machine learning have been applied to the construction, monitoring, simulation, evaluation, and optimization of various water treatment and management systems. Additionally, machine learning can provide solutions for water pollution control, water quality improvement, and watershed ecosystem security management. In this review, we describe the cases in which machine learning algorithms have been applied to evaluate the water quality in different water environments, such as surface water, groundwater, drinking water, sewage, and seawater. Furthermore, we propose possible future applications of machine learning approaches to water environments.

Introduction

     With rapid economic development, wastewater containing various pollutants is generated, posing serious threats to natural water environments. Thus, various water pollution control measures have been developed. To a large extent, water quality analysis and evaluation have substantially improved the efficiency of water pollution control [1]. To date, many methods have been developed to monitor and assess water quality worldwide, such as the multivariate statistical method [2], fuzzy inference [3], and the water quality index (WQI) [4]. For evaluating water quality, although most water quality parameters can be monitored according to the procedures defined in the relevant standards, the final water quality evaluation results may widely vary owing to the choice of parameters [5]. Considering all water quality parameters is unrealistic because it is not only expensive and technically difficult but also fails to deal with the variability in water quality [6]. However, in recent years, with the advances in machine learning methods, an increasing number of researchers believe that vast amounts of data can be successfully captured and analyzed to meet the complex and large-scale water quality evaluation requirements.

Concluding remarks

     Machine learning has been widely used as a powerful tool to solve problems in the water environment because it can be applied to predict water quality, optimize water resource allocation, manage water resource shortages, etc. Despite this, several challenges remain in fully applying machine learning approaches in this field to evaluate water quality: (1) Machine learning is usually dependent on large amounts of high-quality data. Obtaining sufficient data with high accuracy in water treatment and management systems is often difficult owing to the cost or technology limitations. (2) As the conditions in real water treatment and management systems can be extremely complex, the current algorithms may only be applied to specific systems, which hinders the wide application of machine learning approaches. (3) The implementation of machine learning algorithms in practical applications requires researchers to have certain professional background knowledge.

The aim of this study is to assess the water quality of Lower Jhelum Canal (LJC) and its suitability for irrigation purposes. An effort has been made to develop a method by integrating water quality index with geographic information system (GIS) for an effective interpretation of LJC water quality. The pollution status of LJC was estimated by different physicochemical and biological parameters. Based on results of analysis, a spatial distribution map of selected water quality parameters was prepared using GIS. An inverse distance weighting (IDW), which is an interpolation technique, was applied to prepare a thematic layer of parameters at each station of Lower Jhelum canal. The results of individual parameters showed that the concentrations of contamination were within permissible limits of WHO and NEQS guidelines except for E. coli. Overall, most of the water falls in excellent quality category indicating the suitability of water for irrigation purpose. The results suggest that most of the water can be used for irrigation and various intended purposes except direct use of water for potable or drinking purposes without treatment.

Introduction

Water is the most significant ingredient for supporting and evolution of life (Kuutondokwa, 2008). Humans get different sorts of benefits from freshwater, which includes water for drinking, industrialization, domestic uses, irrigation, for the production of waterfowl and fisheries, use for leisure, shipping, and waste discarding (Jackson et al., 2001). Water is a source of economic gain. Almost 70% of water is used in agricultural production, which is indirectly the cause of economic growth (Brown and Matlock, 2011). Water resources (Freshwater) are becoming limited for individuals due to overpopulation, so the accessibility of freshwater for human beings decreases (Iqbal et al., 2018). Quality of freshwater deteriorates by developmental activities that contaminate the water bodies, their effects on human health, ecosystem disturbance and issues related to its management and monitoring (Iqbal et al., 2019). Water quality deterioration is the primary threat to public health at the global level (Rahman et al., 2020). Anthropogenic actions, like improper disposal of municipal, industrialized effluents, and unsystematic use of chemicals in agriculture, are vital aspects causative in the worsening of water quality (Azizullah et al., 2011; Iqbal et al., 2020; Subedi et al., 2019; Shirani et al., 2018; Li et al., 2020). The result of these activities is eutrophication, loss of water quality, loss of biodiversity, effects on human health and social security, deposition of nutrients and other inorganic pollutants, acidification and significant economic losses (Kraemer et al., 2001). Contamination of water leads to water scarcity or it may be polluted at that level where it is expensive to treat (Gupta et al., 2012; Maged et al., 2020; Imran et al., 2020). Consequences of both water treatment and water scarcity with high cost would be the reason for the increase in water prices (Kuutondokwa, 2008). According to (Rogers et al., 2002), water is an efficient good. However, the nations which have water resources could grow their economies, while on the other hand, it will be difficult for poor or developing countries, even to avail of their essential needs.

Introduction

Materials and methods

Results and discussion

Conclusion

References

Abstract

Recently, arsenic-contaminated water has become a big concern. Therefore, the present study aimed to absorb arsenic from the aqueous solution using modifed saxaul tree ash. Arsenic adsorption process was performed in vitro by investigating the efect of various parameters such as pH, contact time, arsenic concentrations, temperature and adsorbent dosage on the adsorption efciency. Isotherms, kinetics and thermodynamic studies were also conducted to better understand the process of adsorption. Maximum level of arsenic adsorption was obtained at a pH of 7, adsorbent dosage of 1.5 g/L, contact time of 60 min, initial arsenic concentration of 250 µg/l and temperature of 323 K. The amount of adsorbed arsenic was increased with increasing initial concentration of arsenic and temperature. Freundlich adsorption isotherm clearly described the arsenic adsorption by modifed saxaul ash. Based on the results obtained, it could be concluded that the modifed saxaul ash can efciently remove arsenic from its aqueous solutions.

Introduction

Contamination of underground water caused by heavy metals is one of the most important hazards to water resources (Asgari et al. 2008). Arsenic is the third element of group V of the periodic table with atomic number of 32 and relative atomic mass of 74.92 (Golami et al. 2009). Arsenic concentrations are in the range of 2–5 ppm (Uddin et al. 2006). Arsenic contaminates the surface and underground water resources within the natural processes such as dissolving minerals, chemical decomposition and corruption, and human activities like animal husbandry, medicine, industry, electronics and metallurgy (Golami et al. 2009; Uddin et al. 2006; Zaw and Emett 2002). Human activities are the main cause of arsenic contamination of surface water and groundwater (Jafari-Mansoorian et al. 2016). Arsenic compounds based on the origin of production are mobile in the environment and could get into the food chain and hydrological cycle by rainfall (Babaakbry Sari et al. 2014). Arsenic is a toxic and accumulative substance and can inhibit SH-group enzymes. Trivalent arsenic (arsenite) is more toxic than arsenic (V) (arsenate) due to its high portability (Tyrovola et al. 2006; Triszcz et al. 2009). Arsenic may cause dysfunction in digestive system, shock leading to death, pulmonary and respiratory failures (Golami et al. 2009; Zaw and Emett 2002; Triszcz et al. 2009). It is also known as a carcinogenic substance and causes testicular, bladder, lung and liver cancers (Golami et al. 2009; Smedley and Kinniburgh. 2002). The resulting complications depend on factors such as duration of exposure, way of entering to body, type and sources of arsenic (Smith et al. 2000).

The optimal agricultural structure and population size within typical watersheds needs to be identified based on the water ecological carrying capacity (WECC). However, real-world systems of water ecological management are complicated as multiple uncertainties exist in the system parameters, which need some effective optimization methods to deal with. This research presents an inexact simulation-based fuzzy credibility-constrained mixed-integer programming (ISFCCMIP) model. Through integrating interval linear programming, fuzzy credibility-constrained programming, mixed-integer programming, global nutrient export from watersheds, and the KirchnereDillon model within a general framework, the developed ISFCCMIP model can effectively deal with the multiple uncertainties in the simulation and optimization processes of water ecological management systems. The developed ISFCCMIP model is applied to a real-world case study in the Xinfengjiang Reservoir Watershed. Results show that the total population that can be carried by the watershed WECC would decrease from [204885, 412367] to [121235, 271280], when the credibility level increases from 0.55 to 0.95. On the contrary, the total agricultural benefit would increase from [3.72, 5.06]
108 to [3.75, 5.10]
108 $. The total population in the base year far exceeds the watershed WECC. Although the total agricultural benefit in the base year is between the upper and lower bounds of the optimized results, the agricultural structure is not reasonable and needs to be adjusted. Concurrently, multiple results on the optimal agricultural structure and population size are obtained under different credibility levels and in different carrying capacity scenarios. Such results can provide a series of decision alternatives for watershed policy makers to consider the tradeoff between socio-economic development and water ecological protection. The results also assist the sustainable development of the Xinfengjiang Reservoir Watershed. The proposed model is effective for the optimal management of agricultural structure and population size within a reservoir watershed based on the WECC under multiple uncertainties. It also provides a reference for other areas with similar concerns.

Introduction

The aquatic ecosystem plays an important role in the sustainable development of the economy, society, and environment (Englert et al., 2013; He et al., 2018; Li et al., 2016; Reckendorfer et al., 2013). However, with the rapid growth of the social economy in recent years, the aquatic ecosystem has been subjected to intensive and large-scale human activities (ShabanzadehKhoshrody et al., 2016). The total consumption and development intensity of water resources, as well as emission loads of water pollution, have increased, leading to a series of consequences, such as water resource shortages, environment deterioration, and ecological degradation (Jing et al., 2015; Matios and Burney, 2017; Wang et al., 2015; Xu et al., 2017). Such consequences have placed great pressure on aquatic ecosystems and seriously affected the sustainable utilization of their service functions (Ren et al., 2013; Zhang et al., 2017). Therefore, socio-economic activity within a watershed should simultaneously consider water quantity and quality conditions, and these considerations must be based on the water ecological carrying capacity (WECC) (Wang et al., 2014; Zhang et al., 2014). In particular, agricultural industry development and frequent human activities can lead to an increase in water consumption and release of nutrients (e.g., nitrogen and phosphorus, N and P) from watersheds to water bodies downstream, which might further result in insufficient ecological flow and water eutrophication (Rong et al., 2018; Rudnick et al., 2017; Zhang et al., 2015, 2018). It is therefore important to conduct research on the identification of the optimal agricultural structure and population size within typical watersheds based on the WECC. This will help restrain the water ecological deterioration, protect the ecosystem service function, and promote the sustainable development of the socio-economic environment.

Abstract

Nanotechnology is a multidisciplinary field that has gained significant momentum in recent years. Nanoparticles are the key players that have promised many benefits through their nano-enabled applications in multiple sectors. This review summarizes the use of nanomaterials such as zero valent iron (nZVI) and carbon nanotubes (CNT) in environmental cleanup like ground water remediation for drinking and reuse. There are, however, concerns regarding the potential risks associated with the use of nanomaterials to the environment and human health. An understanding of the relationship between the properties of nanoparticles and their in vivo effects would provide an effective strategy to tackle the deleterious effects.

Introduction

In recent years, nanoscience and technology has introduced a new dimension to scientific disciplines and technology sectors due to its ability to exhibit superfunctional properties of materials at nano-dimensions. There is a remarkable rise in research and development in all developed countries and many developing countries pertaining to this field. Organizations such as Universities, public research institutes and industrial R&D laboratories 1focus strongly on this new technology to benefit from its scientific and technological advantages [1]. Nanotechnology is a multidisciplinary field that applies engineering and manufacturing principles at molecular level [2]. In broad terms, nanotechnology is the development and use of techniques to study physical phenomena and construct structures in the physical size range of 1–100 nanometers (nm) as well as the incorporation of these structures into applications [3]. The past couple of decades have been dedicated to the synthesis, characterization, and application of nanomaterials

Water is recognized as a commodity fundamental to health but scarce, and achieving adequate water delivery to the public can be an overwhelming task anywhere in the world, especially when characterized by increasing population, urbanization and industrialization, as in developing countries especially. Yoe 2002, described associated problems with urban water supplies in achieving sustainability as a wicked task, since no answer can exactly be termed right, hence a compromise situation or solution is usually opted for. This is because the problem of uncertainty and human rationality is encapsulated in all wicked problems (Khisty and Mohammadi 2001). The renaissance to non-conventional or alternative water supply options are recognized as ecofriendly and sustainable, and their integration globally such as, reclaimed water, grey water, black water, rain water harvesting (RWH), desalination, borehole water, water importation, into water supply schemes is intrinsic. Hence exploring these pathways usually borders on the ‘soft path’ approach which suggest a combination of supply options that is usually not technology driven and viable, especially in new urban areas where no central infrastructure pre-exist. These systems undoubtedly can limit demand for fresh water resources, diversify water source, boost reliability of access to resource, and minimize volume of waste water discharged into the environment. These supply options over time, have undergone and undertaken diverse research patterns (Ukpong and Agunwamba 2012; Mara 2004; Dolnicar 2009; Contard and Gouvello 2013; Chowdhury and Rahman 2008; Kanakoudis et al. 2011; Angelakis and Gikas 2014). However the numerous difficulty, rigor, variability of criteria, and uncertainty encountered/ interplay during the decision making process for the best or appropriate supply option endears our employ of multi-criteria decision making approach (MCDA), a decision support tool in overcoming these shortcomings. Fuzzy TOPSIS (technique for order preference by similarity to ideal solution), is a MCDA approach, employed in this study for the first time in alternative water supply option, with consideration of the socio-cultural input in its analysis, a fundamental aspect of sustainability, to evaluate the preferred water supply alternative in the eastern Niger delta of Nigeria, based on economic, technical, environmental and socio-cultural criteria. This region is endowed with water resources including over 2200 mm of annual rainfall, but yet faced with gross inadequacies in water supply, evidenced by the proliferation of water vendors, a clear indication that supply are below acceptable levels. This condition is prevalent in most other parts of the country (Sule et al. 2010). (Okoli et al. 2010) identified major alternative sources of water in the region to be boreholes, wells and ground water.

5.1.1 Sources

Fresh water only represents approximately 3% of all water resources on earth, and its amount is estimated at 35millionm3 . Rivers, lakes, and shallow groundwater make up a mere 0.4% of the total volume of freshwater on the planet, with the rest being stored in the form of glaciers and snow cover in Antarctica and the Arctic or exists as groundwater. Access to drinking water in many countries is limited. Guidelines for the purity of drinking water are provided by European Union and government organizations. Criteria for drinking water quality are based on a few water quality variables such as microbiological and biological indicators, physical properties, organics, inorganics, and trace element concentrations.

5.1.2 Regulations

The World Health Organization (WHO) has proclaimed that “All people, whatever their stage of development and their social and economic conditions have the right to have access to an adequate supply of safe drinking water.” [1]. The EU standards for water quality are derived from WHO Guidelines for Drinking Water Quality. The EU Drinking Water Directive (98/83/EC, November 3, 1998, on the quality of water intended for human consumption) is a seminal document for European countries in this respect. It is reviewed every five years by the European Commission, which brings it in line with WHO guidelines. In 2015 the Polish minister of health published a decree (2), whose contents correspond to EU recommendations. In the US, the Environmental Protection Agency issued the Safe Drinking Water Act which establishes the water purity requirements for all states.

Anumber ofMediterraneancountries suffer fromwater scarcity, which has become severe in recent years due to global climate change causing frequent and long lasting periods of drought. Particularly during the summer, these areas experience severe water supply and demand imbalances. In the last decades, many Italian regions have faced the negative impact of drought and the resource scarcityhasmostlypenalizedagricultural activities, which uses more than 50% of the total available water, while other high priority demands, such as those from civil and industrial sectors, are satisfied (Coppola et al., 2004). Particularly, in Apulia Region (South-Eastern Italy), water shortage has a serious impact on the local economy, mostly based on agriculture. Moreover, the agricultural coastal areas ofApuliaRegionsuffer fromrelevantphenomena of seawater intrusion into the water table, due to the excessive and often uncontrolled groundwater withdrawals for irrigation (Libutti andMonteleone, 2012). For these reasons, alternative water sources are needed. Treated municipal wastewater is the most readily available source of water to meet the increasing demand for crop irrigation. Indeed, in recent years, wastewater recycling in agriculture has gained importance as component of agricultural water supply in several water-scarce countries (Qadir et al., 2007; Pedrero et al., 2010). Wastewater reuse not only provides significant amount of irrigation water, but also contributes to conserve potable resources and reduces the environmental impact related to the effluents discharge into water bodies (Aiello et al., 2007; Pedrero et al., 2010; Agrafioti and Diamadopoulos, 2012). Furthermore, soil application of treated wastewater also constitutes a reliable source of nutrients (especially nitrogen, phosphorus and potassium) and organic matter useful for maintaining the fertility and the productivity of the soil (Meli et al., 2002; Rusan et al., 2007). Treated wastewater use for crop irrigation can improve growth and yield of herbaceous species (Kiziloglu et al., 2008; Bedbabis et al., 2010) and can also enhance the economic benefits for farmers, due to reduced need for fertilizer (Bedbabis et al., 2010; Paranychianakis et al., 2006). However, the chemical composition of wastewater has to be monitored to avoid imbalance in nutrient supply, which may result in excessive vegetative growth, uneven fruit maturity, reduced quality and quantity of yields (Pedrero et al., 2010). Treated wastewater should be used for irrigation under controlled conditions, also to minimize hazards to agricultural products, soil and groundwater from toxic and pathogenic contaminants (Aiello et al., 2007; Qadir et al., 2007). Wastewater may contain a variety of pollutants, such as salts, heavy metals, organic compounds, enteric bacteria and viruses. An excessive accumulation of trace metals, such as Cd, Cu, Fe, Mn, Pb and Zn, in soils through irrigation creates problems for agricultural production (Singh et al., 2004) and leads to metal uptake by crops, so affecting food quality and safety (Khan et al., 2008). One of the crucial issues in the reuse of treated wastewater for crop irrigation is the residual presence of pathogenic microorganism (Rubino and Lonigro, 2008; Petterson et al., 2011) which represents a potential health risk to consumers when they enter in the food chain (Toze, 2006). In Italy, there are strict regulations for reclaimed wastewater reuse (Decree No. 152, 2006, Ministry for Environment), especially for levels of some chemical compounds and for microbial parameters. With regard to microbiological contamination levels, the corresponding guidelines allow unrestricted crop irrigation with a bacteriological effluent quality characterized by less than 10 CFU 100 ml−1 of E. coli in 80% of samples.

Groundwater is among the vital water resources on the earth planet, being exploited for fundamental uses such as drinking, agriculture and industry (Wu and Sun, 2016; Li et al., 2016; Chitsaz and Azarnivand, 2016; Jamshidzadeh and Mirbagheri, 2011). Rainfall penetration through the soil and stones on the ground surface is the most important source of groundwater provision. This water resource accompanied by water penetration of rivers/lakes as well as artificial recharge of groundwater and reused waste waters are the major sources for augmentation of groundwater resources (Adetunde et al., 2011). In general, population growth and the expansion of urbanization as the chief cause of agriculture and industry evolution gave rise to instability of aquifers (Krishan et al., 2016). Moreover, the exponential rise of population and over exploitation of groundwater resources has ended in quality degradation of groundwater (Pophare et al., 2014). In particular, just like the quantity, quality of groundwater should be taken into a serious consideration (Aghazadeh and Asghari-Moghadam, 2010). Considering this fact that, artificial recharge, environmental rainfall, ground water penetration and groundwater geo-chemical reactions might influence the quality of groundwater (Vasanthavigar et al., 2010), its pollution would threaten human’s health, economic development and social welfare (Milovanovic, 2007). Several factors and methods have so far, been innovated to present water quality parameters. Among all, Water Quality Index (WQI) is appreciated as a prominent factor for classification and quality management of groundwater (Hosseini-Moghari et al., 2015). In order to evaluate the quality of drinking water in Sabalan aquifer eas a volcanic region- Mosaferi and his colleagues (Mosaferi et al., 2015) put WQI into practice using 7 qualitative parameters. In addition, Sadat-Noori et al. (2013) performed zoning of adequate regions for drinking exploitations in Saveh-Arak plane. While having a positive effect on the qualitative assessment of groundwater resources, WQI is expected to entail drawbacks. Lermontov et al. (2009) stated that classifications which are adopted from this index would generate inflexible and definite results. Moreover, Dahiya et al. (2007) explained that this analysis, in some cases, presents unreliable consequences. For instance, based on the analysis made by WQI, the quality of water has been reported to be adequate for drinking purposes, while assessed to be inadequate for agriculture using Wilcox diagram. Such an assumption should be considered a genuine contradiction as sensitivities to drinking water is remarkably higher compared to the water used in agriculture. In line with the above elucidation, Multicriteria decision making methods were recommended in order to avoid conflicts in the qualitative classification of samples.

پیش بینی کمیتی تاثیرات زیست محیطی بر سناریو های تغییر جوی و کاربری زمین در آبخیز می تواند به عنوان مبنایی عالی برای توسعه الگوهای مدیریت آبخیز خدمت می کنند . کمیت و کیفیت آب از جمله شاخص های کلیدی زیست محیطی می باشند که نسبت به انواع اختلال های بیرونی حساس می باشند . هدف این بررسی این است تا تاثیرات تغییر کاربری و تغییرات جوی بر مقدار و کیفیت آب در مقیاس آبخیز و درک روابط بین اجزای آب شناسی و کیفیت آب در آن مقیاس تحت سناریو های مختلف جوی و استفاده از زمین را ارزیابی نمایند . ما یک رویکرد را برای مدل سازی و بررسی تاثیرات استفاده از زمین و سناریو های تغییر جوی در چرخه های آب و ماده مغذی و آب شناسی آبخیز و مدل ماده مغذی را برای آبخیز رودخانه نشیو در هوکایدو در شمال ژاپن توسعه داده ایم . تغییر کاربری زمین پیش بینی شده تحت شرایط جوی و خط مبناء باعث کاهش بارهای رسوب ، نیتروژن و فسفر کلی از آبخیز به رودخانه گردید . این وضعیت را به دریافت ماده مغذی بالاتر توسط غلات و ماده مغذی کمتر معدنی سازی توسط میکروب ها ، نشت ماده مغذی کاهش یافته از خاک و راندمان های آب کمتر در مزرعه نسبت می دهند . تغییرات جوی ( رسوب و دما ) برنامه ریزی شده بودند تا تاثیر بیشتر بر افزایش یافتن جریان آب سطحب ، جریان جانبی ، تخلیه آب زیرزمینی و بازده آب نسبت به تغییر کاربری زمین داشته باشند . رواناب سطحی بویژه در ماه های اوریل و می کاهش یافته بود و در ماه های مارس و دسامبر با زیاد شدن دما کاهش یافته بود .