ABSTRACT
This study examines the impact of climate change on the Uluova Micro Basin, Turkey, employing an optimization model named ULUHEM across various water management and climate scenarios. With ULUHEM, the effects of different climate impact scenarios on agricultural water allocations, pumping costs, water scarcity, and scarcity costs were analyzed. The primary objective of this study is to identify gaps in demand within the current water supply infrastructure due to global warming and to develop adaptation strategies for basinwide water management operations. The research also emphasizes the importance of creating a basin-based hydroeconomic model that includes other surface water resources with a sustainable management approach to address the impact of climate change. In summary, the impacts of climate change on surface waters and groundwater in the Uluova Micro Basin include changes in water availability, water scarcity, and associated costs, and these have implications for agricultural water allocations and overall water management in the region. The study found that drier climate periods lead to reduced surface and groundwater input to farmland, resulting in increased water scarcity and scarcity costs. Conversely, periods characterized by wetter climates yield contrasting outcomes, alleviating water scarcity and its corresponding costs.
HIGHLIGHTS
Effects of climate change on agricultural irrigation.
Basin-based integrated surface and groundwater management.
Management of water resources with a hydroeconomic optimization model.
INTRODUCTION
Besides challenges posed by population growth, increasing demands for food and energy, urbanization, and industrialization, freshwater resources face mounting pressure due to climatic conditions and rising global temperature (Vörösmarty et al. 2000; Rosegrant et al. 2002; Molden & De Fraiture 2010). Increasing water scarcity and decreasing water availability caused by climate change could potentially have adverse impacts on the sustainability of economic activities and overall growth (Gohar et al. 2019). Climate change affects surface water and groundwater in various aspects, including changes in temperature, precipitation, water flows, and the amount of water recharge to the groundwater resources (Hatchett & McEvoy 2017). Sarker (2022) conducted a comprehensive study on the consequences of climatic effects on water resources.
Protecting the sustainability of natural resource access, notably water, carries significant global implications (Grey & Sadoff 2007). It is estimated that there will be long-term and significant changes in the flow sizes and timing of reservoir flows in the near future in regions with a Mediterranean climate, including Turkey, attributed to the impacts of global warming and climate change. Climate change drives rising temperatures, a shift from snowfall to rainfall, particularly evident in winter, and altered timing of snowmelt. These effects, which are already visible today, will become even more evident in the near future (National Water Plan 2019). Agricultural water withdrawal globally constituted 62.6% of total water withdrawal on average from 2003 to 2021, highlighting the sector's significant reliance on groundwater. As access to water will become more difficult with the impact of climate change, agricultural activities are expected to be negatively affected (Zhai et al. 2022). Management of water resources, which are under the threat of global warming and climate change, is a very important issue in terms of the sustainability of resources. It is also anticipated that the basin-based management approach will indirectly contribute to vital issues such as the international water policy of countries, socio-economic development of the country, water supply, and food security. It is clear that this situation will affect society not only in terms of water resources but also in a wide variety of areas, from the economy to social life (National Water Plan 2019). Pittock et al. (2016) emphasized in their study that the storage capacity of groundwater aquifers needs to be increased to mitigate the impacts of climate change. Baccour et al. (2021) stated that the pressure on water resources caused by climate change can significantly affect the sustainability of surface and groundwater reservoirs by managing them together with water use models. In other studies, it has been reported that climate change and the overdraft of groundwater resources, especially in dry and semi-dry regions, lead to serious water scarcity and land degradation (Greve et al. 2018; Dasgupta 2021). WMO (World Meteorological Organization) (2021) stated that climate change has caused not only environmental disasters in Europe in the last 50 years, but also serious economic losses due to the decrease in surface and groundwater resources resulting from climatic water stress. Baccour et al. (2022) stated that more efficient and sustainable adaptation policies should be created in order to manage water stress arising from surface and groundwater use.
Hydroeconomic models integrate hydrological, engineering, environmental, and economic aspects of regional water resources systems into a cohesive framework. The idea is to operationalize economic concepts by incorporating them into the heart of water resources management models. These models have emerged as indispensable tools for facilitating integrated water resources management, offering solution-driven approaches to enhance efficiency and transparency in water use. The aim is to look at a system in a new way to investigate promising water management plans and policy insights (Harou et al. 2009). In integrated water resources management models, groundwater and surface water connections can be evaluated in a broader context through basin management. In other words, a basin-centric approach is necessary, beyond the aquifer, with a perspective that addresses intersectoral issues related to the economy, energy, climate, agriculture, and environment (UNEP 2008). Zhang & Guo (2016) emphasized the management of agricultural water resources with the economic optimization method in their studies. Several researchers have explored the impacts of climate change on basin hydrology across various regions under diverse real and potential scenarios (Albek et al. 2004; Fujihara et al. 2008; Önol et al. 2009; Türkeş 2012; Okkan & Fıstıkoglu 2014; Türkeş 2014; Kale et al. 2016; Turan 2018). In their study, Dogan et al. (2019) investigated historical hot-dry climate conditions in the California Central Valley basin to investigate the impact of climate change on groundwater with a hydroeconomic management model. Hydrological scenarios were carried out to determine the effects of climate change on water resources and to determine the optimal use of resources (Zaman et al. 2016; Farjad et al. 2017; Morid et al. 2019). Sarker et al. (2019) have carried out a number of studies to understand the weakness of river networks under external factors with an optimization approach. In another study, Sarker (2021) worked on a model that investigated the physical properties of river networks under different climatic conditions. Singhal et al. (2024) carried out a number of studies on stream flows and sediment formations in river basins using climatic parameters with the Soil and Water Assessment Tool (SWAT) simulation model. Gao et al. (2022), with the optimization approach in their studies, focused on the potential deterioration of dams at critical node points in the river network.
This study focuses on the management of groundwater and surface agricultural water resources, specifically investigating water deliveries, pumping costs, water shortages, and scarcity costs under various climatic scenarios. A hydroeconomic model was developed for the Uluova basin, located within Turkey's Euphrates and comprising significant agricultural areas. The Uluova basin and its groundwater aquifer have been used for years as the most important and easily accessible resource for agricultural activities. For this reason, we built a basin-based hydroeconomic model Uluova hydroeconomic (ULUHEM) that includes surface water and groundwater resources to study and eliminate groundwater overdraft for sustainable water management. Through our modeling efforts, we aim to identify potential demand gaps in the current water supply system within the Uluova Micro Basin due to global warming and propose adaptation strategies for basin-oriented water management operations. Six different climate impact scenarios were examined, apart from the historical period (Scenario 1), altering inflows of water resources feeding both surface and groundwater reservoirs in response to climatic changes.
Study area and management scenarios
Different climate scenarios cause different hydrological flows. A drier climate scenario results in smaller inflows, and a wetter climate scenario results in larger inflows. In this section, six different climatic scenarios, apart from the base case (Scenario 1), were examined by changing the inflows of water resources feeding the surface and groundwater reservoirs (other numerical parameters are the same), as given in Table 1.
Climatic management scenarios
Scenario . | Description . | Implementation . | Importance . |
---|---|---|---|
Scenario 1 | Operations with historical | Historical (1991–2011) long-term water operations for the entire Uluova Basin for 20 years. | Historical base case operation |
Scenario 2 | Somewhat dry | A situation in which the flows entering the reservoirs for a hot and dry climate decrease by −10% (less dry) compared to the historical period. | 10% drier than historical period |
Scenario 3 | Dry | A situation in which the flows entering the reservoirs for a hot and dry climate decrease by −20% (dry) compared to the historical period. | 20% drier than historical period |
Scenario 4 | Very dry | A situation in which the flows entering the reservoirs for a hot and dry climate decrease by −30% (extremely dry) compared to the historical period. | 30% drier than historical period |
Scenario 5 | Somewhat wet | For a wet climate, the inflows into reservoirs increase by +10% compared to the historical period. | 10% wetter than historical period |
Scenario 6 | Wet | For a wet climate, the inflows into reservoirs increase by +20% compared to the historical period. | 20% wetter than historical period |
Scenario 7 | Very wet | For a wet climate, the inflows into reservoirs increase by +30% compared to the historical period. | 30% wetter than historical period |
Scenario . | Description . | Implementation . | Importance . |
---|---|---|---|
Scenario 1 | Operations with historical | Historical (1991–2011) long-term water operations for the entire Uluova Basin for 20 years. | Historical base case operation |
Scenario 2 | Somewhat dry | A situation in which the flows entering the reservoirs for a hot and dry climate decrease by −10% (less dry) compared to the historical period. | 10% drier than historical period |
Scenario 3 | Dry | A situation in which the flows entering the reservoirs for a hot and dry climate decrease by −20% (dry) compared to the historical period. | 20% drier than historical period |
Scenario 4 | Very dry | A situation in which the flows entering the reservoirs for a hot and dry climate decrease by −30% (extremely dry) compared to the historical period. | 30% drier than historical period |
Scenario 5 | Somewhat wet | For a wet climate, the inflows into reservoirs increase by +10% compared to the historical period. | 10% wetter than historical period |
Scenario 6 | Wet | For a wet climate, the inflows into reservoirs increase by +20% compared to the historical period. | 20% wetter than historical period |
Scenario 7 | Very wet | For a wet climate, the inflows into reservoirs increase by +30% compared to the historical period. | 30% wetter than historical period |
ULUHEM MODEL
Mathematically, ULUHEM is a network-flow reservoir optimization model. Within the scope of the model, the physical water allocation and distribution system is represented by nodes, and links connecting these nodes and their parameters. Links are defined by (i, j, k) ∈ A. Where ‘i’ is the initial node, ‘j’ is the final node, and ‘k’ is a piecewise component used to represent linear penalty (or cost) curves with a convex piecewise description. The ‘k’ component creates multiple links from the initial node ‘i’ to the terminal node ‘j’ (Şekerci 2023).
Each link has the following parameters:
Loss factor ‘a’, unit cost ‘c’, lower bound ‘l’, and upper bound (or capacity) ‘u’.
The ULUHEM model uses historical hydrological data from 1991 to 2001 to represent hydrological variability. The model was developed using the Python-based Pyomo platform. Pyomo is a high-level optimization modeling language written in Python programming language. This platform uses the GNU Linear Programming Kit (GLPK) solver (Dogan et al. 2018).
RESULTS
Six different climatic impact scenarios were examined, apart from the historical period (Scenario 1), by changing the inflow of surface and groundwater reservoirs, while keeping other numerical parameters constant. The results presented in this section show the interaction of agricultural water allocations, pumping costs, water scarcity (from groundwater and surface water sources), and scarcity costs for each of the six different management scenarios. These results are compared with Scenario 1, involving water operations in the historical period.
Uluova basin historical period agricultural water operations and reservoir storage
Total annual surface-groundwater deliveries for Uluova agricultural irrigation.
Uluova basin agricultural water operations according to different management scenarios
Water portfolios formed according to historical periods and climate scenarios.
Table 2 compares six different climatic impact scenarios with the historical period in the ULUHEM model and expresses the annual water allocations from surface and groundwater to the agricultural area, pumping costs, water shortages, scarcity costs, and flows that return to the groundwater aquifer through infiltration as a result of irrigation. While the annual water scarcity of the Uluova Micro Basin was approximately 92.27 million m3 in the historical period, the cost of scarcity resulting from the loss of agricultural production due to water deficiency is approximately 53.6 million dollars annually. The cost of pumping from groundwater and surface reservoirs to irrigate agricultural areas is a total of $1.87 million per year.
Different climatic management scenarios
Climatic situation . | Scenarios . | Groundwater pumping (hm3/year) . | Surface water distribution (hm3/year) . | Infiltration returning to the groundwater (hm3/year) . | Water scarcity hm3/year . | Total pumping cost (GW + SW) million $/year . | Scarcity cost . |
---|---|---|---|---|---|---|---|
Somewhat dry | Scenario 2 | 20 | 22.07 | 4.94 | 95.23 | 1.82 | 55.30 |
Dry | Scenario 3 | 16.84 | 21.54 | 4.54 | 98.92 | 1.76 | 57.44 |
Very dry | Scenario 4 | 13.79 | 21.01 | 4.31 | 102.5 | 1.70 | 59.52 |
Historical | Scenario 1 | 22.42 | 22.61 | 4.95 | 92.27 | 1.87 | 53.58 |
Somewhat wet | Scenario 5 | 25.32 | 20.34 | 4.98 | 91.08 | 1.67 | 52.89 |
Wet | Scenario 6 | 27.44 | 20.06 | 5.19 | 89.8 | 1.68 | 52.15 |
Very wet | Scenario 7 | 30.03 | 20.63 | 5.53 | 86.64 | 1.72 | 50.31 |
Climatic situation . | Scenarios . | Groundwater pumping (hm3/year) . | Surface water distribution (hm3/year) . | Infiltration returning to the groundwater (hm3/year) . | Water scarcity hm3/year . | Total pumping cost (GW + SW) million $/year . | Scarcity cost . |
---|---|---|---|---|---|---|---|
Somewhat dry | Scenario 2 | 20 | 22.07 | 4.94 | 95.23 | 1.82 | 55.30 |
Dry | Scenario 3 | 16.84 | 21.54 | 4.54 | 98.92 | 1.76 | 57.44 |
Very dry | Scenario 4 | 13.79 | 21.01 | 4.31 | 102.5 | 1.70 | 59.52 |
Historical | Scenario 1 | 22.42 | 22.61 | 4.95 | 92.27 | 1.87 | 53.58 |
Somewhat wet | Scenario 5 | 25.32 | 20.34 | 4.98 | 91.08 | 1.67 | 52.89 |
Wet | Scenario 6 | 27.44 | 20.06 | 5.19 | 89.8 | 1.68 | 52.15 |
Very wet | Scenario 7 | 30.03 | 20.63 | 5.53 | 86.64 | 1.72 | 50.31 |
The results of the scenarios created under climate change are as follows:
In Scenario 2, which is one of the dry climate scenarios, the total annual water shortage is 95.23 hm3, the resulting scarcity cost due to loss of production is $55.3 million, and the cost of pumping water from surface and groundwater reservoirs to the agricultural area is $1.82 million.
In Scenario 3, the total annual water shortage is 98.92 hm3, the cost of the resulting shortage due to loss of production is $57.44 million, and the cost of pumping water from surface and groundwater reservoirs to the agricultural area is $1.76 million.
In Scenario 4, the total annual water shortage is 102.50 hm3, the cost of the resulting shortage due to loss of production is $59.52 million, and the cost of pumping water from surface and groundwater reservoirs to the agricultural area is $1.70 million.
In Scenario 5, which is one of the wet climate scenarios, the total annual water shortage was 91.08 hm3, the cost of the resulting shortage due to production loss was 52.89 million dollars, and the cost of pumping water from surface and groundwater reservoirs to the agricultural area was $1.67 million.
In Scenario 6, the total annual water shortage was 89.80 hm3, the cost of the resulting shortage due to production loss was 52.15 million dollars, and the cost of pumping water from surface and groundwater reservoirs to the agricultural area was 1.68 million dollars.
Finally, in Scenario 7, the total annual water shortage was 86.64 hm3, the cost of the resulting shortage due to production loss was 50.31 million dollars, and the cost of pumping water from surface and groundwater reservoirs to the agricultural area was 1.72 million dollars.
Share of surface and groundwater in the Uluova Basin according to different management scenarios
Water deliveries from groundwater and surface reservoirs according to historical period and climate scenarios (in percentage terms).
Water deliveries from groundwater and surface reservoirs according to historical period and climate scenarios (in percentage terms).
DISCUSSION
In this section, similar studies and results of our study conducted by other researchers are discussed. Tian et al. (2018) emphasized in their studies that agricultural sustainability will be possible with the efficient use of water resources. They emphasized the importance of introducing many economic elements for water resources management using the optimization method (Davijani et al. 2016).
In other studies, a framework is presented for measuring and solving the negative effects of climate change through local water management decisions based on the basin economy (Auffhammer 2018; Eamen et al. 2021). Aytac et al. (2024) carried out some studies on water resources management and climate change adaptation strategies with the hydroeconomic model called Upper Euphrates Basin Hydro-economic Model (FEHEM). In their study results, they emphasized the importance of including agricultural and urban demands and groundwater basins into the system for a better-integrated water system representation.
Previous researchers have emphasized the importance of investigating factors such as integrated water management for agricultural sustainability, efficient use of water resources, monitoring the negative effects of climate change, and incorporating economic parameters into water resources management with the optimization method. In this study, the issues whose importance was emphasized and recommended above were discussed with a holistic approach using the optimization method on a basin-based scale. The study attracts attention in terms of containing concrete outputs such as examining the negative effects of climate change mentioned in the literature, economic parameters of water resources management, and integrated use of water resources for agricultural sustainability.
CONCLUSION
In this study, six different climatic impact scenarios created by changing the historical period water operations and the inlet currents of water resources feeding surface and groundwater reservoirs under the influence of climate change (other numerical parameters are the same) were compared with the ULUHEM hydroeconomic model.
As the climate dries, surface, and groundwater inflow to agricultural areas is decreasing as a result of the decrease in flows entering reservoirs. Water inflows from the flow (infiltration) returning from the agricultural irrigation area to the groundwater reservoir also decrease as climatic drought increases. In wet climate scenarios, the flow from groundwater pumping to agricultural areas increases. Inflows from surface reservoirs decreased in +10, +20, and +30% (wet climate situations) scenarios as the effect of the wet climate scenario increased, as the water entering the agricultural area through the more cost-effective groundwater pumping increased. Although water inflow from surface reservoirs to the agricultural area decreased in Scenarios 5, 6, and 7 compared to Scenario 1, which is the base case, surface water delivery in Scenario 7, where the climatic precipitation was the highest, increased compared to Scenarios 5 and 6. With the increase in precipitation, the amount of water entering the groundwater reservoir by infiltration during the wet seasons has also increased. Due to water shortages in agricultural areas, scarcity costs increase as the severity (percentage) of the climatic drought scenario increases. In wet climate scenarios, water scarcity and scarcity costs tend to decrease according to the basic situation with the increase in incoming water.
It can be said that the only advantage of dry climate scenarios compared to the historical period is the reduction of pumping costs paid for irrigation. In wet climate scenarios, as the degree of wetness increases (percentage), it has been observed that the water pumping costs of agricultural users have increased compared to the base case, but the total pumping cost has decreased since the water drawn from the surface water, which has a high unit cost, will decrease. As the severity (percentage) of climatic wetness increases, the total pumping cost for agricultural users decreases in wet climate scenarios compared to the base case, as agricultural users will turn to groundwater pumping rather than getting water from Eyup Baglari with high pumping costs.
In the results obtained, it has been seen that the agricultural activities of the plain are directly affected according to different climatic change scenarios. The ULUHEM model represents hydrological events on a 20-year time scale. As better data for the model becomes available, it will be useful to revisit the model.
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.