Abstract
Located in a semi-arid and arid zone, Iran is suffering from growing challenges of water scarcity. In the paradigm of a circular economy, the reuse of treated wastewater in agriculture is currently regarded as a possible solution for alleviating the issues of water scarcity and pollution. Accordingly, this research aims to assess the use of polluted water in the integrated management of water resources in Semnan. The research used the Water Evaluation and Planning System (WEAP) software package to model and analyze the water sector. Also, the Bayesian network method was used to assess the risk of using polluted water and its effects on humans and plants. The research explored two general scenarios for the study site of Semnan. The first scenario assumes the increase in population, crops (food), and industries, and the second has the same assumptions plus an increase in agricultural efficiency (food production). Based on the results, the agricultural, urban, and industrial water demands are 37, 0.06, and 0.01 million m3 in the base year, respectively. The water demand in the next years will be higher due to population growth. Finally, it is safer to use the wastewater of both treatment plants of the region (Mehdishahr and Semnan) in the industry than in other sectors. Additionally, the wastewater of the Mehdishahr Sewage Treatment Plant is more reliable than that of the Semnan Sewage Treatment Plant.
HIGHLIGHTS
Management of a smart city.
Critical assessment on Iran's water resources development.
A novel framework and multisectoral approach toward the implementation of IWRM and the W&F nexus in Iran, case study Semnan, is proposed.
Enhancing IWRM and W&F nexus may eradicate hunger as the agriculture sector is disconnected with water, by replacing water reuse.
Graphical Abstract
INTRODUCTION
Several decades ago water was considered an abundant natural resource because it was renewable in all seasons (Santos Pereira et al. 2009). However, the planet Earth is currently suffering from the growing scarcity of water (Aliabadi et al. 2020; Ofori et al. 2021), especially in arid and semi-arid regions whose limited water resources are depleting (Aliabadi et al. 2022; Es'haghi et al. 2022). According to FAO (2014), water, food, and energy are interrelated and at risk due to population growth, urbanization, economic and industrial development, and climate change. So, the concept of the water-energy-food nexus has emerged to describe their complicated interactions to allow sustainable use of these limited resources. Agriculture is, indeed, the biggest freshwater consumer (Singh 2021), accounting for 69 percent of global water use. However, this figure is as high as 92 percent in Iran. The annual water use of Iran amounts to 96 billion m3, out of which 52 billion m3 is supplied by groundwater tables, 42 billion m3 by surface water resources, and the remaining by water freshening and recycling (Ataei et al. 2019; Karimi & Ataei 2022).
Thus, water scarcity for agriculture can have important implications for food security and nourishment (Akbari et al. 2022). In addition, the existing water resources seem to be inadequate to meet the growing water demands, which will create a gap in water demand and supply (Nan et al. 2020; Ataei et al. 2021). Furthermore, pollution caused by human activities reduces water quality and renders it inappropriate for most purposes (Santos Pereira et al. 2009).
To cope with this situation, the reuse of treated wastewater as an unconventional water resource has recently gained much significance (Salgot 2018). Today, wastewater is considered a renewable and cheap unconventional resource, not a source of pollution (Almuktar et al. 2018; Chojnacka et al. 2020; Rizzo et al. 2020). Therefore, in regions where there is water scarcity, wastewater can be used to supplement or replace fresh water for applications in which freshwater quality is not important, especially in agriculture and industry (Helmecke et al. 2020; Ofori et al. 2021). Treated wastewater reuse provides an opportunity to address the gap between water demand and supply in Iran since wastewater can meet a significant part of total water demand if treated and recycled properly.
The history of wastewater reuse can provide a field for planning projects and adopting new policies on wastewater reuse. The evolution of wastewater treatment technology and its diverse applications have recently become more important incentives for wastewater reuse projects. Domestic wastewater has historically been used for irrigation by various civilizations including the civilizations of China, Egypt, and Mesopotamia (Angelakis et al. 2018). The first registered ‘wastewater farm’ was reported in Bunzlau, Poland in 1531. Farms in Edinburgh, Scotland were irrigated with urban wastewater in 1650 (Crites et al. 2021). Wastewater is broadly defined as the ‘used’ water that has been polluted by human activities (Mateo-Sagasta et al. 2015). It can be raw (gray or black water) or diluted and can potentially be very harmful to human health and the environment, but provided that the standards are observed, it is increasingly regarded as a reliable and economic source of water, particularly for agricultural or industrial applications (Qadir et al. 2010; Mizyed & Mays 2020).
In addition to reducing the burden on freshwater resources, treated wastewater reuse in agriculture has economic and environmental advantages, including the supply of nutrients (N and P) and organic matter. As such, it helps increase agriculture productivity besides reducing chemical fertilization and the relevant costs and preserving the quality of freshwater resources by reducing wastewater discharge into water bodies (Chojnacka et al. 2020). Although there are numerous benefits of wastewater reuse, it can have public health hazards if not managed soundly (Jaramillo & Restrepo 2017; Chojnacka et al. 2020; Rizzo et al. 2020). Wastewater reuse, indeed, entails extensive disadvantages regarding undesirable pollutants, e.g., organic matter with high levels of chemical oxygen demand (COD) and biochemical oxygen demand (BOD), total suspended solids (TSS), nutrients (e.g., N and P), heavy metals (e.g., cadmium, chromium, nickel, lead, copper, and zinc), emerging pollutants (e.g., organic solvents, pesticides, and medications), toxic anions, and pathogens (bacteria, viruses, protozoa, and nematodes) (Kaushal et al. 2018). These pollutants may adversely affect soil, groundwater quality, and human health (Jaramillo & Restrepo 2017; Chojnacka et al. 2020). To tackle these pitfalls, wastewater must be subjected to proper treatment as per the relevant standards and regulations to be safe for reuse in the industry, agriculture, and urban sector.
Data on the current levels of produced, available, and reused wastewater quantities at different scales are dispersed so that they are rarely monitored and reported and are unavailable in most countries (Mateo-Sagasta et al. 2015; Janeiro et al. 2020). Furthermore, treatment can lead to very different levels of quality, and treatment plants may operate at capacities (much) lower than the capacities reported (Oliveira & Von Sperling 2008; Murray & Drechsel 2011). Also, data on on-site wastewater treatment are often missing although on-site systems may represent most populations. Even in high-income countries, a significant number of people rely on on-site systems such as septic tanks and are not connected to urban wastewater systems. For example, one out of five American households relies on small community cluster systems (septic systems) (Rocha Cuadros 2016).
Crites et al. (2021) state that most technological advancements that support the development of modern projects of agricultural water reuse improve the possibility of different competing applications of urban water reuse. The consequences of increasing water shortage for existing water quality and quantity influence agricultural water reuse projects. The historical trend of the development of concentrated and regional facilities of wastewater treatment in the vicinity of proper surface water discharge sites may be amended to better consider agricultural irrigation in integrated water resources planning.
Since Iran (especially the study site in Semnan province) is geographically located in an arid and semi-arid climate and considering the phenomenon of climate change in recent years, water resource management in the 20–25-year horizon is of high significance. Government officials should consider useful solutions for the future by presenting different scenarios based on the potential of the resources in the region. Population growth increases water use in the drinking and industrial sectors and escalates the demand for food production, resulting in greater water use for crop production. Almost half of the water consumed in different sectors, including drinking, agricultural, and industrial sectors, is returned to the environment as wastewater. The treatment of this wastewater and its reuse as contaminated water as per environmental considerations would allow a significant part of water consumption to be reduced. To resolve the deficiency of one of the most critical resources (water) in Semnan province, measures should be taken for the sound management of water resources. The present research aims to use solutions that are compatible with the potential capacities of the study site in Semnan. Although the study site is close to the capital city of Tehran and rainy regions in the north of Iran, the research has ignored such solutions as inter-basin water transfer and has tried to rely on the potential capabilities of the region.
It should be noted that polluted water in this research refers to the wastewater treated in the treatment plants within the study site of Semnan. There are three treatment plants in this region, including the treatment plants of Shahmirzad, Mehdishahr, and Semnan with capacities of 2,400, 6,000, and 15,000 m3/day, respectively. (Since the Shahmirzad treatment plant is at the pilot exploitation phase and has no outlet wastewater, it was not included in the analysis.) A measure considered in this research is the use of contaminated water to solve the problem of water deficiency in the coming years assuming that properly treated contaminated waters can be used as a key resource to meet the water demand of the agricultural and industrial sectors. This research attempts to explore the potential capacities of the study site for water consumption and to estimate the need for these resources in the study site.
MATERIALS AND METHODS
Background
Data sources
The relevant organizations and agencies, including the Department of Meteorology, Regional Water Company, and Water and Wastewater Company of Semnan province, have collected data on surface and groundwater flows, which represent the water resources existing in the region, and the amount of water consumption by the drinking water, industrial, and agricultural sectors.
METHODOLOGY
Study approach
In the next step, proper approaches should be adopted to meet the needs of the demand points on the horizon of water resources management. A method proposed and scrutinized in this research is the evaluation of contaminated water reuse. However, it is first necessary to quantify the pollutants in contaminated waters produced by the drinking resources in the study site. Then, the wastewater produced from these resources should be treated as per the environmental requirements and studies. Knowing the needs of different demand points and the amount of contaminated water used to satisfy these needs, different management scenarios are presented and studied.
The use of polluted water in the agricultural and industrial sectors can have various benefits, e.g., the alleviation of water limitations and the reduction of environmental pollution. But, the fact that there may be dangerous pollutants in polluted water limits its application. So, it is imperative to evaluate the risk of using polluted water as an efficient way of recognizing the possible hazards and their potential implications. The present research has used the Bayesian network to evaluate the risk of using polluted water and its impact on humans and plants as receptor factors.
The research investigated two general scenarios for the study site of Semnan. The first scenario assumes increases in population, crop production, and industries, and the second scenario assumes the first scenario's assumptions plus an increase in agriculture efficiency. Finally, the risk of polluted water consumption in the industrial and agricultural sectors is assessed.
Scenario 1&2 (connection/difference)
In Scenario 1, it is aimed to study the available water resources per population growth in the future years. Population growth in the coming years will increase water consumption. By food or crop increase in this scenario, we mean that since the food consumed within the study site is partially produced there, crop production in the study site must be increased to meet food demand given the population growth and consequently, the increase in food demand. Then, in addition to studying the population growth and the increase in crop production, the scenario addresses increasing industrial production in the study site with a focus on increasing industrial towns considering regional potential. Again, the issue of water demand for increasing industrial production is raised, and since the region is facing water scarcity, attention is drawn to the use of wastewater as the input water of the industries.
By wastewater, we mean the sewage treated by the treatment plants within the study site, including the treatment plants of Mehdishahr and Semanan. Their output can be consumed in the industrial and agricultural sectors.
Scenario 2 assumes an increase in agricultural efficiency in addition to population growth, the increase in industrial production, and the increase in crop production. The increase in agricultural efficiency contributes to reducing water consumption while producing more crops. In this scenario, it is aimed to study the effect of using modern irrigation methods (drip and sprinkler irrigation systems) at farms and orchards, which will enhance efficiency in the agricultural sector.
Model developments
To model water and food resources, regional characteristics are first studied. Example characteristics are the geographical location, the physical features of the basin, the hydrological features of the basin including rivers and hydrometer stations, meteorological conditions, and climatology including precipitation, evapotranspiration, the status of groundwater resources, and basin water uses such as its use for drinking water, industry, and agriculture. Also, information such as the area of agricultural lands, the crops cultivated, and the crops harvested are studied to check the food production resources in the region.
The research has considered the aquatic year 2018–2019 (from September 2018 to August 2019) as the current accounts. To achieve the data required for running the water resources management scenarios, the precipitation rate was first calculated for the next 25 years by using the time series method with 35-year data of rainfall in the two basins of the Darjazin and Hajiabad rivers.
Data generation
Calculation of monthly supply and annual demand
Monthly demand
Monthly supply requirement
Water inflow and outflow
Agricultural water demand was calculated based on such parameters as the cultivation area, crop type, and irrigation method with the NETWAT software package, and the information required on agricultural needs was inputted into the WEAP software package.
RESULTS AND DISCUSSION
Water demand (drinking, agricultural, industrial)
The demand for drinking water was estimated by considering the per capita drinking water consumption for population centers (urban and rural) within the study site and their populations. The water demand of the industrial sector was also estimated per annum by WEAP according to the information and data received to estimate the annual need of the industry. The agricultural, drinking, and industrial water needs were 37, 0.06, and 0.01 million m3 for the current accounts, respectively.
The total, satisfied, and unsatisfied water demands (million m3)
Year . | Scenario 1 . | Scenario 2 . | ||||
---|---|---|---|---|---|---|
Total demand . | Satisfied demand . | Unsatisfied demand . | Total demand . | Satisfied demand . | Unsatisfied demand . | |
2018 | 37.44 | 37.44 | 0.00 | 37.44 | 37.44 | 0.00 |
2019 | 40.27 | 35.09 | 5.18 | 39.18 | 38.99 | 0.19 |
2020 | 40.67 | 40.58 | 0.09 | 39.58 | 39.58 | 0.00 |
2021 | 41.08 | 38.35 | 2.73 | 39.97 | 39.72 | 0.26 |
2022 | 41.49 | 39.14 | 2.34 | 40.37 | 40.37 | 0.00 |
2023 | 41.90 | 40.30 | 1.60 | 40.78 | 40.61 | 0.16 |
2024 | 42.32 | 41.92 | 0.41 | 41.19 | 41.19 | 0.00 |
2025 | 42.75 | 39.82 | 2.92 | 41.60 | 41.29 | 0.31 |
2026 | 43.18 | 36.32 | 6.86 | 42.01 | 41.17 | 0.84 |
2027 | 43.61 | 42.44 | 1.17 | 42.44 | 42.39 | 0.05 |
2028 | 44.04 | 43.03 | 1.02 | 42.86 | 42.86 | 0.00 |
2029 | 44.49 | 40.84 | 3.64 | 43.29 | 43.11 | 0.18 |
2030 | 44.93 | 34.48 | 10.46 | 43.72 | 42.02 | 1.71 |
2031 | 45.38 | 43.49 | 1.90 | 44.16 | 43.97 | 0.19 |
2032 | 45.84 | 42.60 | 3.23 | 44.60 | 44.20 | 0.40 |
2033 | 46.29 | 43.21 | 3.08 | 45.05 | 45.05 | 0.00 |
2034 | 46.76 | 44.81 | 1.95 | 45.50 | 45.25 | 0.25 |
2035 | 47.23 | 46.68 | 0.54 | 45.96 | 45.96 | 0.00 |
2036 | 47.70 | 44.25 | 3.45 | 46.42 | 45.96 | 0.46 |
2037 | 48.18 | 40.14 | 8.04 | 46.88 | 45.63 | 1.25 |
2038 | 48.66 | 47.13 | 1.53 | 47.35 | 47.24 | 0.11 |
2039 | 49.15 | 48.08 | 1.07 | 47.83 | 47.80 | 0.03 |
2040 | 49.64 | 48.22 | 1.42 | 48.30 | 48.30 | 0.00 |
2041 | 50.14 | 45.56 | 4.58 | 48.79 | 48.46 | 0.33 |
2042 | 50.64 | 50.27 | 0.37 | 49.28 | 49.28 | 0.00 |
2043 | 51.15 | 50.00 | 1.14 | 49.77 | 49.72 | 0.05 |
2044 | 51.66 | 50.10 | 1.56 | 50.27 | 50.27 | 0.00 |
Year . | Scenario 1 . | Scenario 2 . | ||||
---|---|---|---|---|---|---|
Total demand . | Satisfied demand . | Unsatisfied demand . | Total demand . | Satisfied demand . | Unsatisfied demand . | |
2018 | 37.44 | 37.44 | 0.00 | 37.44 | 37.44 | 0.00 |
2019 | 40.27 | 35.09 | 5.18 | 39.18 | 38.99 | 0.19 |
2020 | 40.67 | 40.58 | 0.09 | 39.58 | 39.58 | 0.00 |
2021 | 41.08 | 38.35 | 2.73 | 39.97 | 39.72 | 0.26 |
2022 | 41.49 | 39.14 | 2.34 | 40.37 | 40.37 | 0.00 |
2023 | 41.90 | 40.30 | 1.60 | 40.78 | 40.61 | 0.16 |
2024 | 42.32 | 41.92 | 0.41 | 41.19 | 41.19 | 0.00 |
2025 | 42.75 | 39.82 | 2.92 | 41.60 | 41.29 | 0.31 |
2026 | 43.18 | 36.32 | 6.86 | 42.01 | 41.17 | 0.84 |
2027 | 43.61 | 42.44 | 1.17 | 42.44 | 42.39 | 0.05 |
2028 | 44.04 | 43.03 | 1.02 | 42.86 | 42.86 | 0.00 |
2029 | 44.49 | 40.84 | 3.64 | 43.29 | 43.11 | 0.18 |
2030 | 44.93 | 34.48 | 10.46 | 43.72 | 42.02 | 1.71 |
2031 | 45.38 | 43.49 | 1.90 | 44.16 | 43.97 | 0.19 |
2032 | 45.84 | 42.60 | 3.23 | 44.60 | 44.20 | 0.40 |
2033 | 46.29 | 43.21 | 3.08 | 45.05 | 45.05 | 0.00 |
2034 | 46.76 | 44.81 | 1.95 | 45.50 | 45.25 | 0.25 |
2035 | 47.23 | 46.68 | 0.54 | 45.96 | 45.96 | 0.00 |
2036 | 47.70 | 44.25 | 3.45 | 46.42 | 45.96 | 0.46 |
2037 | 48.18 | 40.14 | 8.04 | 46.88 | 45.63 | 1.25 |
2038 | 48.66 | 47.13 | 1.53 | 47.35 | 47.24 | 0.11 |
2039 | 49.15 | 48.08 | 1.07 | 47.83 | 47.80 | 0.03 |
2040 | 49.64 | 48.22 | 1.42 | 48.30 | 48.30 | 0.00 |
2041 | 50.14 | 45.56 | 4.58 | 48.79 | 48.46 | 0.33 |
2042 | 50.64 | 50.27 | 0.37 | 49.28 | 49.28 | 0.00 |
2043 | 51.15 | 50.00 | 1.14 | 49.77 | 49.72 | 0.05 |
2044 | 51.66 | 50.10 | 1.56 | 50.27 | 50.27 | 0.00 |
As was already mentioned, the two scenarios differ in agricultural efficiency. In other words, it is attempted to enhance agricultural efficiency in Scenario 2, which is achieved by modifying the cropping pattern and/or implementing modern irrigation schemes. Water consumption can be optimized by changing the cropping pattern and using crops whose water requirements match the water potential of the study site. Furthermore, equipping agricultural lands with modern irrigation systems, e.g., sprinkler and drip irrigation systems, can contribute to saving agricultural water use and preventing water loss.
The year 2018, which was considered the base year, represents a normal year whose water demands are met by the water potential of the region. Given the long-term statistical period of the region, the input of the water resources in the future years along with rainy and dry years was estimated by the time-series method. For example, the unmet demand of the basin would reach about 10 million m3 in 2030 given the regional potential, showing that the year 2030 will be a dry year or the precipitation will be deficient in previous years.
Since the water demand is not satisfied, it is recommended to use polluted water to supply agricultural and industrial water requirements using the risk assessment of these water resources by the Bayesian network.
The water requirement for the three demand groups (m3)
Year . | Total demand . | ||
---|---|---|---|
Agriculture . | Urban . | Industry . | |
2018 | 37,368,230 | 62,129.12 | 11,814.45 |
2019 | 40,191,576 | 63,309.47 | 11,873.52 |
2020 | 40,593,492 | 64,512.5 | 11,932.89 |
2021 | 40,999,427 | 65,738.65 | 11,992.55 |
2022 | 41,409,421 | 66,988.35 | 12,052.52 |
2023 | 41,823,516 | 68,262.08 | 12,112.78 |
2024 | 42,241,751 | 69,560.29 | 12,173.34 |
2025 | 42,664,168 | 70,883.45 | 12,234.21 |
2026 | 43,090,810 | 72,232.06 | 12,295.38 |
2027 | 43,521,718 | 73,606.61 | 12,356.86 |
2028 | 43,956,935 | 75,007.59 | 12,418.64 |
2029 | 44,396,505 | 76,435.53 | 12,480.74 |
2030 | 44,840,470 | 77,890.94 | 12,543.14 |
2031 | 45,288,874 | 79,374.36 | 12,605.86 |
2032 | 45,741,763 | 80,886.34 | 12,668.88 |
2033 | 46,199,181 | 82,427.42 | 12,732.23 |
2034 | 46,661,172 | 83,998.17 | 12,795.89 |
2035 | 47,127,784 | 85,599.17 | 12,859.87 |
2036 | 47,599,062 | 87,231.01 | 12,924.17 |
2037 | 48,075,053 | 88,894.28 | 12,988.79 |
2038 | 48,555,803 | 90,589.6 | 13,053.73 |
2039 | 49,041,361 | 92,317.58 | 13,119 |
2040 | 49,531,775 | 94,078.87 | 13,184.6 |
2041 | 50,027,093 | 95,874.11 | 13,250.52 |
2042 | 50,527,363 | 97,703.95 | 13,316.77 |
2043 | 51,032,637 | 99,569.08 | 13,383.36 |
2044 | 51,542,964 | 101,470.2 | 13,450.27 |
Year . | Total demand . | ||
---|---|---|---|
Agriculture . | Urban . | Industry . | |
2018 | 37,368,230 | 62,129.12 | 11,814.45 |
2019 | 40,191,576 | 63,309.47 | 11,873.52 |
2020 | 40,593,492 | 64,512.5 | 11,932.89 |
2021 | 40,999,427 | 65,738.65 | 11,992.55 |
2022 | 41,409,421 | 66,988.35 | 12,052.52 |
2023 | 41,823,516 | 68,262.08 | 12,112.78 |
2024 | 42,241,751 | 69,560.29 | 12,173.34 |
2025 | 42,664,168 | 70,883.45 | 12,234.21 |
2026 | 43,090,810 | 72,232.06 | 12,295.38 |
2027 | 43,521,718 | 73,606.61 | 12,356.86 |
2028 | 43,956,935 | 75,007.59 | 12,418.64 |
2029 | 44,396,505 | 76,435.53 | 12,480.74 |
2030 | 44,840,470 | 77,890.94 | 12,543.14 |
2031 | 45,288,874 | 79,374.36 | 12,605.86 |
2032 | 45,741,763 | 80,886.34 | 12,668.88 |
2033 | 46,199,181 | 82,427.42 | 12,732.23 |
2034 | 46,661,172 | 83,998.17 | 12,795.89 |
2035 | 47,127,784 | 85,599.17 | 12,859.87 |
2036 | 47,599,062 | 87,231.01 | 12,924.17 |
2037 | 48,075,053 | 88,894.28 | 12,988.79 |
2038 | 48,555,803 | 90,589.6 | 13,053.73 |
2039 | 49,041,361 | 92,317.58 | 13,119 |
2040 | 49,531,775 | 94,078.87 | 13,184.6 |
2041 | 50,027,093 | 95,874.11 | 13,250.52 |
2042 | 50,527,363 | 97,703.95 | 13,316.77 |
2043 | 51,032,637 | 99,569.08 | 13,383.36 |
2044 | 51,542,964 | 101,470.2 | 13,450.27 |
The percentage of water requirement of different demand points in the study site of Semnan.
The percentage of water requirement of different demand points in the study site of Semnan.
Water demand (satisfied/unsatisfied) in Scenario 1
Table 3 tabulates the results of Scenario 1. This scenario investigates the water consumption of the agricultural, drinking water, and industrial sectors within the study site of Semnan over 2019–2044. In this scenario, all water demand is satisfied using the potential resources of the region, which mostly include groundwater tables. In this scenario, the population in the population centers of the region is increasing from the base year (2018) to the horizon year (2044), so the increase in crop (food) production and the expansion of the industry are also considered. Finally, the results of Scenario 1 in Table 3 present the water requirements of the agricultural, drinking water, and industrial sectors. The table also shows the satisfied and unsatisfied water demands in this scenario for the studied years. It is observed that the demand for drinking water is fully satisfied in all studied years.
The amount of satisfied and unsatisfied water demands in Scenario 1 (m3)
Year . | Satisfied . | Unsatisfied . | ||||
---|---|---|---|---|---|---|
Agriculture . | Urban . | Industry . | Agriculture . | Urban . | Industry . | |
2018 | 37,368,230 | 62,129.12 | 11,814.45 | 0 | 0 | 0 |
2019 | 35,016,672 | 63,309.47 | 11,592.05 | 5,174,904 | 0 | 281.4765 |
2020 | 40,502,913 | 64,512.5 | 11,903.96 | 90,578.7 | 0 | 28.93128 |
2021 | 38,272,203 | 65,738.65 | 11,907.2 | 2,727,224 | 0 | 85.35913 |
2022 | 39,064,767 | 66,988.35 | 11,971.65 | 2,344,654 | 0 | 80.86266 |
2023 | 40,220,104 | 68,262.08 | 12,053.58 | 1,603,412 | 0 | 59.19735 |
2024 | 41,834,538 | 69,560.29 | 12,144.48 | 407,213 | 0 | 28.86003 |
2025 | 39,740,167 | 70,883.45 | 12,176.15 | 2,924,002 | 0 | 58.05765 |
2026 | 36,231,481 | 72,232.06 | 12,123.2 | 6,859,329 | 0 | 172.1859 |
2027 | 42,351,577 | 73,606.61 | 12,267.86 | 1,170,141 | 0 | 88.99798 |
2028 | 42,937,717 | 75,007.59 | 12,361.27 | 1,019,218 | 0 | 57.36771 |
2029 | 40,753,817 | 76,435.53 | 12,359.13 | 3,642,688 | 0 | 121.6068 |
2030 | 34,385,659 | 77,890.94 | 12,305.39 | 10,454,811 | 0 | 237.7475 |
2031 | 43,393,787 | 79,374.36 | 12,453.17 | 1,895,088 | 0 | 152.686 |
2032 | 42,508,928 | 80,886.34 | 12,582.4 | 3,232,835 | 0 | 86.47943 |
2033 | 43,116,788 | 82,427.42 | 12,652.91 | 3,082,393 | 0 | 79.32086 |
2034 | 44,713,780 | 83,998.17 | 12,733.62 | 1,947,392 | 0 | 62.26526 |
2035 | 46,585,367 | 85,599.17 | 12,798.58 | 542,416.8 | 0 | 61.28557 |
2036 | 44,148,877 | 87,231.01 | 12,839.87 | 3,450,185 | 0 | 84.29419 |
2037 | 40,034,722 | 88,894.28 | 12,804.76 | 8,040,331 | 0 | 184.0345 |
2038 | 47,027,500 | 90,589.6 | 12,964.36 | 1,528,303 | 0 | 89.37007 |
2039 | 47,975,261 | 92,317.58 | 13,026.81 | 1,066,101 | 0 | 92.19454 |
2040 | 48,116,107 | 94,078.87 | 13,099.47 | 1,415,668 | 0 | 85.1295 |
2041 | 45,450,399 | 95,874.11 | 13,128.81 | 4,576,694 | 0 | 121.709 |
2042 | 50,161,998 | 97,703.95 | 13,284.44 | 365,365.8 | 0 | 32.33329 |
2043 | 49,887,794 | 99,569.08 | 13,290.71 | 1,144,843 | 0 | 92.64186 |
2044 | 49,984,378 | 101,470.2 | 13,362.83 | 1,558,585 | 0 | 87.44587 |
Year . | Satisfied . | Unsatisfied . | ||||
---|---|---|---|---|---|---|
Agriculture . | Urban . | Industry . | Agriculture . | Urban . | Industry . | |
2018 | 37,368,230 | 62,129.12 | 11,814.45 | 0 | 0 | 0 |
2019 | 35,016,672 | 63,309.47 | 11,592.05 | 5,174,904 | 0 | 281.4765 |
2020 | 40,502,913 | 64,512.5 | 11,903.96 | 90,578.7 | 0 | 28.93128 |
2021 | 38,272,203 | 65,738.65 | 11,907.2 | 2,727,224 | 0 | 85.35913 |
2022 | 39,064,767 | 66,988.35 | 11,971.65 | 2,344,654 | 0 | 80.86266 |
2023 | 40,220,104 | 68,262.08 | 12,053.58 | 1,603,412 | 0 | 59.19735 |
2024 | 41,834,538 | 69,560.29 | 12,144.48 | 407,213 | 0 | 28.86003 |
2025 | 39,740,167 | 70,883.45 | 12,176.15 | 2,924,002 | 0 | 58.05765 |
2026 | 36,231,481 | 72,232.06 | 12,123.2 | 6,859,329 | 0 | 172.1859 |
2027 | 42,351,577 | 73,606.61 | 12,267.86 | 1,170,141 | 0 | 88.99798 |
2028 | 42,937,717 | 75,007.59 | 12,361.27 | 1,019,218 | 0 | 57.36771 |
2029 | 40,753,817 | 76,435.53 | 12,359.13 | 3,642,688 | 0 | 121.6068 |
2030 | 34,385,659 | 77,890.94 | 12,305.39 | 10,454,811 | 0 | 237.7475 |
2031 | 43,393,787 | 79,374.36 | 12,453.17 | 1,895,088 | 0 | 152.686 |
2032 | 42,508,928 | 80,886.34 | 12,582.4 | 3,232,835 | 0 | 86.47943 |
2033 | 43,116,788 | 82,427.42 | 12,652.91 | 3,082,393 | 0 | 79.32086 |
2034 | 44,713,780 | 83,998.17 | 12,733.62 | 1,947,392 | 0 | 62.26526 |
2035 | 46,585,367 | 85,599.17 | 12,798.58 | 542,416.8 | 0 | 61.28557 |
2036 | 44,148,877 | 87,231.01 | 12,839.87 | 3,450,185 | 0 | 84.29419 |
2037 | 40,034,722 | 88,894.28 | 12,804.76 | 8,040,331 | 0 | 184.0345 |
2038 | 47,027,500 | 90,589.6 | 12,964.36 | 1,528,303 | 0 | 89.37007 |
2039 | 47,975,261 | 92,317.58 | 13,026.81 | 1,066,101 | 0 | 92.19454 |
2040 | 48,116,107 | 94,078.87 | 13,099.47 | 1,415,668 | 0 | 85.1295 |
2041 | 45,450,399 | 95,874.11 | 13,128.81 | 4,576,694 | 0 | 121.709 |
2042 | 50,161,998 | 97,703.95 | 13,284.44 | 365,365.8 | 0 | 32.33329 |
2043 | 49,887,794 | 99,569.08 | 13,290.71 | 1,144,843 | 0 | 92.64186 |
2044 | 49,984,378 | 101,470.2 | 13,362.83 | 1,558,585 | 0 | 87.44587 |
The amount of satisfied and unsatisfied water demands in Scenario 1.
Water demand (satisfied/unsatisfied) in Scenario 2
As with Table 3, Table 4 presents the total water requirements of the agricultural, drinking water, and industrial sectors over the studied period for Scenario 2. The table presents the results of Scenario 2 for the satisfied and unsatisfied needs of the three demand sectors for the period 2018–2044.
The amount of satisfied and unsatisfied water needs in Scenario 2 (m3)
Year . | Satisfied . | Unsatisfied . | ||||
---|---|---|---|---|---|---|
Agriculture . | Urban . | Industry . | Agriculture . | Urban . | Industry . | |
2018 | 37,368,230 | 62,129.12 | 11,814.45 | 0 | 0 | 0 |
2019 | 38,917,435 | 63,309.47 | 11,760.71 | 191,512 | 0 | 112.8092 |
2020 | 39,500,037 | 64,512.5 | 11,932.89 | 0 | 0 | 0 |
2021 | 39,639,504 | 65,738.65 | 11,938.38 | 255,532.6 | 0 | 54.1748 |
2022 | 40,293,988 | 66,988.35 | 12,025.04 | 0 | 0 | 27.47368 |
2023 | 40,532,632 | 68,262.08 | 12,083.22 | 164,294.9 | 0 | 29.55804 |
2024 | 41,103,897 | 69,560.29 | 12,173.34 | 0 | 0 | 0 |
2025 | 41,207,685 | 70,883.45 | 12,175.15 | 307,250.9 | 0 | 59.05766 |
2026 | 41,088,211 | 72,232.06 | 12,186.34 | 841,874 | 0 | 109.0366 |
2027 | 42,299,164 | 73,606.61 | 12,327.25 | 50,221.37 | 0 | 29.61109 |
2028 | 42,772,880 | 75,007.59 | 12,399.46 | 0 | 0 | 19.17812 |
2029 | 43,022,980 | 76,435.53 | 12,434.05 | 177,628.1 | 0 | 46.68369 |
2030 | 41,924,809 | 77,890.94 | 12,390.43 | 1,707,806 | 0 | 152.7056 |
2031 | 43,875,847 | 79,374.36 | 12,544.87 | 193,094.1 | 0 | 60.98839 |
2032 | 44,106,754 | 80,886.34 | 12,613.14 | 402,875.8 | 0 | 55.74191 |
2033 | 44,954,726 | 82,427.42 | 12,703.46 | 0 | 0 | 28.77308 |
2034 | 45,157,214 | 83,998.17 | 12,764.57 | 247,059.6 | 0 | 31.32433 |
2035 | 45,858,316 | 85,599.17 | 12,828.5 | 0 | 0 | 31.36757 |
2036 | 45,856,380 | 87,231.01 | 12,862.78 | 460,519.9 | 0 | 61.39269 |
2037 | 45,528,597 | 88,894.28 | 12,863.07 | 1,251,472 | 0 | 125.719 |
2038 | 47,134,951 | 90,589.6 | 13,022.35 | 112,918.4 | 0 | 31.38099 |
2039 | 47,695,173 | 92,317.58 | 13,086.81 | 25,175.24 | 0 | 32.19549 |
2040 | 48,197,551 | 94,078.87 | 13,161.95 | 0 | 0 | 22.64235 |
2041 | 48,353,109 | 95,874.11 | 13,200.77 | 326,417.6 | 0 | 49.74644 |
2042 | 49,166,322 | 97,703.95 | 13,316.77 | 0 | 0 | 0 |
2043 | 49,611,118 | 99,569.08 | 13,350.85 | 46,867.68 | 0 | 32.51141 |
2044 | 50,154,565 | 101,470.2 | 13,420.12 | 0 | 0 | 30.1515 |
Year . | Satisfied . | Unsatisfied . | ||||
---|---|---|---|---|---|---|
Agriculture . | Urban . | Industry . | Agriculture . | Urban . | Industry . | |
2018 | 37,368,230 | 62,129.12 | 11,814.45 | 0 | 0 | 0 |
2019 | 38,917,435 | 63,309.47 | 11,760.71 | 191,512 | 0 | 112.8092 |
2020 | 39,500,037 | 64,512.5 | 11,932.89 | 0 | 0 | 0 |
2021 | 39,639,504 | 65,738.65 | 11,938.38 | 255,532.6 | 0 | 54.1748 |
2022 | 40,293,988 | 66,988.35 | 12,025.04 | 0 | 0 | 27.47368 |
2023 | 40,532,632 | 68,262.08 | 12,083.22 | 164,294.9 | 0 | 29.55804 |
2024 | 41,103,897 | 69,560.29 | 12,173.34 | 0 | 0 | 0 |
2025 | 41,207,685 | 70,883.45 | 12,175.15 | 307,250.9 | 0 | 59.05766 |
2026 | 41,088,211 | 72,232.06 | 12,186.34 | 841,874 | 0 | 109.0366 |
2027 | 42,299,164 | 73,606.61 | 12,327.25 | 50,221.37 | 0 | 29.61109 |
2028 | 42,772,880 | 75,007.59 | 12,399.46 | 0 | 0 | 19.17812 |
2029 | 43,022,980 | 76,435.53 | 12,434.05 | 177,628.1 | 0 | 46.68369 |
2030 | 41,924,809 | 77,890.94 | 12,390.43 | 1,707,806 | 0 | 152.7056 |
2031 | 43,875,847 | 79,374.36 | 12,544.87 | 193,094.1 | 0 | 60.98839 |
2032 | 44,106,754 | 80,886.34 | 12,613.14 | 402,875.8 | 0 | 55.74191 |
2033 | 44,954,726 | 82,427.42 | 12,703.46 | 0 | 0 | 28.77308 |
2034 | 45,157,214 | 83,998.17 | 12,764.57 | 247,059.6 | 0 | 31.32433 |
2035 | 45,858,316 | 85,599.17 | 12,828.5 | 0 | 0 | 31.36757 |
2036 | 45,856,380 | 87,231.01 | 12,862.78 | 460,519.9 | 0 | 61.39269 |
2037 | 45,528,597 | 88,894.28 | 12,863.07 | 1,251,472 | 0 | 125.719 |
2038 | 47,134,951 | 90,589.6 | 13,022.35 | 112,918.4 | 0 | 31.38099 |
2039 | 47,695,173 | 92,317.58 | 13,086.81 | 25,175.24 | 0 | 32.19549 |
2040 | 48,197,551 | 94,078.87 | 13,161.95 | 0 | 0 | 22.64235 |
2041 | 48,353,109 | 95,874.11 | 13,200.77 | 326,417.6 | 0 | 49.74644 |
2042 | 49,166,322 | 97,703.95 | 13,316.77 | 0 | 0 | 0 |
2043 | 49,611,118 | 99,569.08 | 13,350.85 | 46,867.68 | 0 | 32.51141 |
2044 | 50,154,565 | 101,470.2 | 13,420.12 | 0 | 0 | 30.1515 |
Results of comparing the two scenarios
Based on the results of the two scenarios, the amount of unsatisfied needs decreases in the studied years by modifying the cropping pattern in Scenario 2. Out of the total water need in the study site of Semnan, almost 94.1 percent is satisfied and 5.9 percent is left unsatisfied in Scenario 1 whereas the amount of satisfied need increases to 99.4 percent and the amount of unsatisfied need falls to 0.6 percent in Scenario 2. Therefore, if the cropping pattern is modified at the study site, 5.3 percent of the unsatisfied water need can be met by the internal resources.
Model validation and calibration
In modeling the study site using WEAP, after all data on demand and supply points are inputted into the simulation environment, the simulation should be validated. Since there was no precise and complete information for calibration, the research used the data available for the base year for model calibration. However, the values simulated for the hydrometry station of Jazin (the calculated values) were also compared with real values (registered values), and the error criteria were calculated. For example, RMSE and MAE were estimated at 0.06 and 0.05, respectively. The comparison of the observed values with the real values reveals the desirable capability of the model in simulating water for the study site using WEAP.
The risk assessment for the wastewater (Bayesian network)
The Bayesian network for the wastewater treatment plants of Semnan and Mehdishahr.
The Bayesian network for the wastewater treatment plants of Semnan and Mehdishahr.
The present research determined the probability of a base node's success (S) or failure (F), displayed in green, by calculating the number of violated data to the total data. For example, regarding the pH node connected to soil fertility loss, 70 percent of the data were within the standard range, but 30 percent violated it. These figures were determined by comparing the data with the standard ranges published in Presidential Deputy of Planning and Strategic Monitoring Journal No. 535 (Environmental regulations for the reuse of return water and wastewater) and Journal No. 426 (Guideline to categorize the quality of raw water, wastewater, and return water for industrial and recreational uses). The standard values are given in Table 5.
The allowed levels of wastewater consumption in different sectors
Parameter . | Discharge to surface water . | Discharge to absorbent wells (groundwater tables) . | Agricultural and irrigation uses . | Industrial uses (3rd group categorization) . |
---|---|---|---|---|
BOD | 30 | 30 | 100 | – |
COD | 60 | 60 | 200 | 0–20 |
pH | 6.5–8.5 | 5–9 | 6–8.5 | 5–10 |
DO | 2 | – | 2 | – |
NTU (obscurity) | 50 | – | 50 | – |
TSS | 40 | – | 100 | 0–10 |
TDS | – | – | – | 0–500 |
Cl | 1 | 1 | 0.2 | – |
EC | – | – | 300 | – |
Parameter . | Discharge to surface water . | Discharge to absorbent wells (groundwater tables) . | Agricultural and irrigation uses . | Industrial uses (3rd group categorization) . |
---|---|---|---|---|
BOD | 30 | 30 | 100 | – |
COD | 60 | 60 | 200 | 0–20 |
pH | 6.5–8.5 | 5–9 | 6–8.5 | 5–10 |
DO | 2 | – | 2 | – |
NTU (obscurity) | 50 | – | 50 | – |
TSS | 40 | – | 100 | 0–10 |
TDS | – | – | – | 0–500 |
Cl | 1 | 1 | 0.2 | – |
EC | – | – | 300 | – |
Results of risk assessment for the wastewater of sewage treatment plants
The results of the risk assessment for the wastewater of the Semnan treatment plant.
The results of the risk assessment for the wastewater of the Semnan treatment plant.
The results of the risk assessment for the wastewater of the Mehdishahr treatment plant.
The results of the risk assessment for the wastewater of the Mehdishahr treatment plant.
RECOMMENDATIONS
Mehdishahr and Shahmirzad region
Given the existence of three sewage treatment plants in the study site (Shahmirzad, Mehdishahr, and Semnan), it is recommended to use the treated wastewater of the Mehdishahr plant in the industries in the region including Semnan Tile Factory and Pre-fabricated Concrete Manufacturing Factory, which have demanded wastewater purchase according to a report by Semnan province's Water and Sewage Company.
In addition, since Shahmirzad is located in the north of Mehdishahr and has a mountainous climate and its sewage treatment plant with a nominal capacity of 2,400 m3/day, which is at the pilot operation stage, and has the advanced treatment process of extensive aeration active sediment during which N and P are removed, it is recommended to plan for using its wastewater in the Shahmirzad Agro-Industrial Company in order to make savings in the consumption of groundwater resources.
Semnan region
Since the study site has a hot and arid climate and is located in the vicinity of the Kavir, the application of the treated wastewater of Semnan to irrigate urban green spaces can supply the minimum per capita need of urban green spaces. Also, some part of the wastewater can be transferred to the industrial town for the use of water-intensive industries like Zafar Steel Factory, Oghab Bus Manufacturing Factory, and so on, which will result in savings on the abstraction from groundwater tables. As such, the industrial water demand will be partially satisfied by the wastewater, leaving the freshwater wells for the use of regional people considering the drought and water deficit crisis. The next point is camel farming in the Kavir. Presently, these camels may use the wastewater (which is disposed of in the Kavir), putting them at risk of catching parasites and viral infections and transferring them to humans. So, the optimization of wastewater use for the industry will contribute to enhancing the health and food security of the communities.
There are farms around the Semnan Sewage Treatment Plant, which may use its wastewater to irrigate their crops, e.g., wheat and barley, even in untreated form. Since the environmental standard says that the treated wastewater is not allowed to be used in the cultivation of crops, fruit trees, vegetables, and any items that are directly related to people's food baskets, it is recommended to conduct soil tests and determine the trees that can be cultivated in the region to use their wood in furniture production and can contribute to improving regional ecosystems and alleviating climate change.
CONCLUSIONS
Risk and reliability of the wastewater (Semnan and Mehdishahr)
This research presented two models for assessing the risk and reliability of the wastewater produced by sewage treatment plants. The two treatment plants of Semnan and Mehdishahr were selected as the case study. The input data for the models were derived from the opinions of treatment plant experts and specialists and the field data of the treatment plants. After the two Bayesian network models were analyzed, the results of the risk assessment gave 27% for the Mehdishahr plant and 33% for the Semnan plant, showing the better performance of the latter treatment plant. It was also found that the output wastewater of both plants could be used in the industrial sector more safely with less risk. The models provided to the treatment plant managers and users can help them determine solutions for increasing the reliability of wastewater use by determining the risk of their use.
The scenario of irrigation
The comparison of the scenario of irrigation efficiency enhancement by applying modern irrigation systems and/or changing the cropping pattern versus the current cropping pattern and irrigation method shows that when the study site of Semnan is faced with rainfall shortage and drought, the latter scenario can be a turning point to prevent groundwater over-abstraction. However, as was mentioned, the study site had an arid climate and the application of polluted water by the agricultural sector and, especially, the industrial sector can partially meet the regional water demand from groundwater and surface water resources.
DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.
CONFLICT OF INTEREST
The authors declare there is no conflict.