Estimating Agricultural Water Consumption impacts on water level fluctuations of Urmia Lake, Iran

Transcription

1 Estimating Agricultural Water Consumption impacts on water level fluctuations of Urmia Lake, Iran Leila Eamen 1 and A. B. Dariane* 2 1. MSc. Student, Dept. of Civil Eng., K.N. Toosi Univ. of Tech. 2. Associate Professor, Dept. of Civil Eng., K.N. Toosi Univ. of Tech. borhani@kntu.ac.ir Abstract Urmia Lake located in northwestern Iran is currently facing a critical situation where climate change, drought, and by a greater extent recent developing projects in water consumption areas (mainly agricultural) have endangered the whole existence of the Lake. In such a circumstance, proper simulation of water resources and demands of the basin may help to find effective solutions for saving the Lake. Therefore, a recovery plan for Lake Urmia would include the accurate assessment of the amount and impacts of agricultural water consumption, as the main water user of the basin. In this respect, the historical data must be investigated after gathering them from various sources in order to assess their impact on the lake level fluctuations. Since monitored databases may not be available in most of developing countries, in this paper, the impact of agricultural water consumption on Urmia Lake level fluctuations is investigated. To accomplish this task, a method is also proposed for estimating agricultural water consumption in the absence of monitored data sets. For this purpose, the main basin is divided into several sub basins and characteristics of irrigated areas along with water balance components in each sub basin are determined using satellite images, site visits and database. Then the Water Evaluating and Planning system (WEAP) software is used to simulate the water resources system of the Urmia Lake basin and evaluate the impact of agricultural water use on the Lake level. Achievements of this study show that the agricultural water consumption and its recently growing rate play an important role on Urmia Lake level fluctuations and the Lake ecosystem. It also reveals that through an improved irrigation system the Lake level could rise substantially by saving water from higher irrigation efficiency. It is obvious that the impact of improved irrigation efficiency is granted assuming that the extra water saved through this procedure is returned to the Lake and not used for further developments. Key words: Agricultural water consumption, Urmia Lake Basin, Lake level Fluctuation, WEAP

2 1. Introduction The Urmia Lake is a terminal lake where the only way water leaves the lake is by evaporation. Therefore, shrinking of the lake is caused by either increased evaporation or decreased inflows to the lake. The Lake inflows mainly come from rivers flowing in the basin. Other sources include direct rainfall over the lake and a very small fraction through groundwater discharge [1, 2, 3]. According to relevant studies, the most significant causes of decline in Urmia Lake water level are over extraction from surface and ground water resources and the climate change [4, 3, 1]. Reports show that the main component of the water consumption in Urmia Lake basin is the agricultural water use that affects quantity and quality of water in the basin. On the other hand, agricultural development without fundamental studies threatened sustainability of the water resources in the basin. In arid and semi-arid regions where precipitation is insufficient to meet the agricultural water demands, required water should be provided by irrigation in order to avoid water deficit and the consequent reduction in crop production. Estimation of irrigation water consumption has been implemented by various approaches including evapotranspiration (ET) estimation. Evapotranspiration is the process of water losses from the hydrologic system due to evaporation from the soil and crop. Traditional ET estimation methods are mostly limited to localized estimation of ET providing potential or reference ET at specific points. However, considering spatial and temporal variability of vegetation, soils and management techniques, these methods are not practical for large scale use. Direct measurement methods that use sensors to measure ET directly, besides being costly, are also limited to small areas and do not account for the diversity of ET across the basin [5]. However, recent advances in satellite remote sensing technology led to the application of these methods widely in water resources management. Different methods have been developed to estimate evapotranspiration using remote sensing data, including the Surface Energy Balance Algorithm for Land (SEBAL) and Mapping Evapotranspiration at high Resolution and with Internalized Calibration (METRIC), which is a variant of SEBAL [6, 7, 8]. In addition, the variety of the METRIC ET model applications have been developed such as monitoring water rights compliance and aquifer depletion, as a tool for water resource planning, and hydrologic modeling [9]. The next step after ET estimating is checking and improving the accuracy of results using ground measurements of the basin. However, the notable point is the lack of monitored databases in most of developing countries, which is needed for checking and controlling the results. In most of developing countries, surveys and measurements are implemented every few years not monthly or even annually. As a result, there would be probable errors and problems in area and crop pattern of agricultural lands or withdrawal data from water resources (surface and ground resources) in various periods. These are some roots of uncertainties that appear in the estimations of agricultural water use calculations. It is evident that several parameters are affecting the Lake system, including climate change, drought, and by a greater extent recent developing projects in water consumption areas. It is essential to evaluate the impact of each parameter on the Lake fluctuations in order to find an effective solution for the crisis that the Lake faces these days. Therefore, this study attempts to evaluate impacts of agricultural water consumption on Urmia Lake fluctuations and present a method for estimating agricultural water use in the basin, using remote sensing, site visits, agricultural census and databases. Agricultural areas in this paper include all areas irrigated within the basin regardless of the type of the water source. That means areas covered by the reservoirs are also included in this study. Although,

3 all evidences indicate the significant role of agricultural water use in Lake Urmia fluctuations, among all other factors, they do not mention the extent of its impact by figures and numbers. In this paper, we first develop a simulation model for the whole basin of the Lake extending to nearly Km 2, and then evaluate the role of agricultural water consumption on the Lake fluctuations. 2. Methodology In this study, agricultural water consumption is estimated using area and crop pattern of irrigated lands, crop water requirements, surface and ground water withdrawal data, and estimated irrigation efficiencies for the existing condition as input data. In order to evaluate these parameters more accurately, Urmia Lake basin is divided into 117 sub basins of different sizes. The first step after data gathering is data preparation process that includes checking time series of water resources data and demands for possible errors. The crop water requirements are determined according to the Iranian National Water Document. In this document, the whole country is divided into different zones based on climatic conditions. Then, crop water requirements are estimated for each zone. These estimates are used as the net water requirements of the crop pattern in our research. Results of the most recent agricultural census are the source for area and crop pattern information of Urmia Lake basin. The latest Iranian National Survey, resulted in databases for points of withdrawal from each water resource (surface and ground), is used as surface and groundwater withdrawal data. The other needed parameter is irrigation efficiency that was estimated according to ILRI publication No.19 on irrigation efficiency [10]. It should be mentioned that there have been uncertainties during the process of estimating irrigation efficiencies due to lack of access to the accurate measured data about irrigated land and crop. Moreover, water consumption rate is calculated in each sub basin for the base year (2006) comparing the gross water requirements of the crop pattern with the amounts of withdrawal from surface and ground water resources. Actual water consumption, shares of surface and ground water resources in supplying this amount, water shortages and surpluses, and return flow amount are obtained as the results of this procedure. Since the amount of agricultural water consumption calculated through the above mentioned procedure is actually the amount of water use for the base year, long-term water consumption series have to be generated for naturalizing river flows and as a consequent in integrated water resources management process. Information such as irrigated land area, crop pattern, water use and time series of rainfall and river flow data in statistical period are required to generate long-term water consumption series. As mentioned earlier, in developing countries like Iran accurate data and sufficient surveys are not available. For instance, the agricultural census in Iran is limited to specific years and not every year. Therefore, estimating methods should be applied to generate agricultural water consumption time series. In order to generate long term agricultural water consumption data, here the time period of the study is divided into 4 sections in accordance with the main changes occurred to the Lake level (Figure 1). The mentioned time sections are as follows: I to 1978:From the beginning of the study period to the year of Boukan reservoir first operation (normal lake level) II to1991: From the end of previous section to the beginning of Lake level rising period (normal lake level)

4 III. IV to 1999: From the end of previous section to the beginning of declining period (high lake level) 1999 to 2006: From the end of previous section to the end of study period (low lake level) I II III IV Figure 1: Showing Urmia Lake water level ( ) and divided periods For each time section, a first order linear equation is used for estimating the amount of agricultural water consumption based on changes occurred in the area of irrigated lands and climatic conditions. Area of irrigated lands varies according to the amount of available water and the extent of agricultural development. Therefore, the amount of agricultural water consumption for the study period should be estimated considering these changes. During this process, it should be noted that traditionally, farmers change the crop pattern according to the amount of water they expect to receive each year. As a result, while the irrigated area is not changed, agricultural water requirements may change (decrease or increase) by changing the crop pattern. The amount of water available depends on the hydro-climatic conditions including rainfall and river flow. Rainfall, due to its quantity and temporal distribution affects agricultural water consumption. Withdrawal from surface and ground water resources decline in wet years because of more rainfall received during cropping season. In wet years where the streamflow is high, farmers prefer using cheaper streamflow than more costly groundwater for irrigating their farms. Therefore, there would be less tension on groundwater source during wet years and they get the chance to be recharged in these periods. In contrast, arid climate, especially continuing for more than one year, deteriorates the aquifer system in supplying the adequate water to the agricultural users. Considering these factors, coefficients of the above mentioned equations are being determined. The equations were then applied to the amount of water consumption in the base year (2006) to generate water consumption time series. The accuracy of calculated time series of agricultural water use, generated by this method, is then checked by the water balance relations of the basin and time series of river flows. In this research, the WEAP (Water Evaluating and Planning System) software is applied to simulate the system of water resources and demands of Urmia Lake basin for the period of Water consumption data, including agricultural water use that is estimated through the above mentioned method, and water resources data of Urmia Lake basin are the inputs of this model.

5 3.The study area Urmia Lake basin is located in northwestern Iran, with the area of about km 2. The basin located in three provinces namely the west Azerbaijan, east Azerbaijan and Kurdistan. In order to more accurately evaluate the required parameters, Urmia Lake basin is divided into 117 sub basins in this study. Figure 2 shows the lake basin and its location in Iran. 4. Results Figure 2: Location of Urmia Lake basin A review of climatic parameters of Urmia Lake basin during the study period ( ) shows that there is considerable shift in some of these parameters. Figure 3 and 4 reveals that the mean annual temperature increases while the precipitation shows a decline. The effect of increasing temperature together with decreasing precipitation could greatly affect the hydrological system of the basin. Under these circumstances, more water is lost through evapotranspiration while less precipitation is available to replenish the basin soil. The end result would be a trend of using more irrigation water to fulfill the increasing crop water needs and inserting more pressure on already shrinking surface and groundwater sources. On the other hand, the country s desire to have a self-sufficient agriculture productions has had a tremendous pressure on farmers in the region to increase their products through converting their lands to irrigated agriculture and extent them further to larger farms.

6 Figure 3: Annual Temperature in Urmia Lake basin ( C) Figure 4: Annual precipitation in Urmia Lake basin (cm) Annual time series of total surface discharge into the Urmia Lake basin as shown in Figure 5 indicates a decline during the study period. Lower streamflow discharge is in synchronize with higher temperatures and lower precipitations in the basin, as described above. Since more water is used for irrigation, therefore it is obvious that less water reaches the Lake Urmia. Figure 5: Annual river flow in Urmia Lake basin (mcm)

7 According to Integrated Water Resources Management studies of Urmia Lake basin [10], total area of irrigated lands in this basin, in the base year (2006), is about 512 thousand hectares from which 70 percent are crops and the rest 30 percent are orchards. Irrigation efficiencies were estimated for each sub basin considering agricultural and irrigation factors like crop pattern, irrigation method, conveyance system and the type of water resource whether it is surface or groundwater. The average irrigation efficiency for Urmia lake basin was found to be 37 percent for crops and 45 percent for orchards. Gross water requirement of irrigated crop pattern in the basin was estimated about 6600 million cubic meters which is approximately 1300 cubic meters per hectare. The spatial distribution of gross water requirements of irrigated crop pattern in the sub basins is shown in Figure 6. Figure 6: Spatial distribution of gross water requirement in (m 3 /hec) Total withdrawal from water resources of the basin is about 5300 million cubic meters for the base year (2006). Withdrawal from surface water resources is 57 percent of the total amount, where 43 percent was extracted from ground water resources of the basin. The spatial distribution of agricultural water consumption in sub basins of Urmia Lake basin is shown in Figure 7. Figure 8 demonstrates a comparison between surface and ground water consumptions in sub basins of Urmia Lake basin.

8 Figure 7: Spatial distribution of agricultural water consumption (m 3 /hec) Figure 8: Comparison of Surface and ground water consumption As it was mentioned earlier, water resources and demands of Urmia Lake basin were simulated using WEAP software. A great amount of effort was used to calibrate the model using the data. The calibration process will be discussed in another paper and here we only show the results related to the objects followed in this paper. In order to evaluate the impact of agricultural water consumption on Lake level fluctuations, the model was run with and without agricultural water use in the study period ( ). Results as shown in Figure 9 indicate that the Lake level would have reached to about 1278 m instead of 1273 m, the observed level, in 2006 without any agricultural withdrawal from water resources in the basin. Even without eliminating agricultural water demands from the system and by improving irrigation efficiency the Lake level is increased. Average existing irrigation efficiency for the basin was estimated at about 38 percent. By improving this amount to 65 percent, the Lake level would have increased to about 1275 meters in the base year (Figure 9), indicating 3 meters higher than the observed level.

9 Figure 9: Urmia Lake level fluctuations with and without agricultural consumptions and by improving irrigation efficiency (m) Figure 10 show a similar comparison using volumetric values of the Lake. It can be seen that the Lake storage would have increased significantly to about 50 billion cubic meters in 2006 under no agricultural water consumption, about 30 billion cubic meters more than the observed volume in the same year. Moreover, an increase of about 10 billion cubic meters would have occurred in the Lake storage by improving the irrigation efficiency of agricultural farms in the basin. Figure 10: Urmia Lake volumes with and without agricultural consumptions and by improving irrigation efficiency (mcm) Observed surface area of Urmia Lake in 2006 was 4274 square-kilometers, while under no irrigation and improved irrigation efficiency scenarios, the surface area of the Lake would have reached to about 6319 and 5115 square-kilometers, respectively. Achievements of this study shows that apart from other parameters, like climate change and reservoirs, water withdrawal for agriculture has a considerable influence on the lake level. It is clear that if a modern irrigation method with higher efficiency is used the level of Lake could rise to a safe level. This should be followed considering that the extra water released

10 through better irrigation method should be returned to the Lake and not be used to further extend agricultural lands. Unfortunately, the process of converting the old fashioned irrigation system to a modern one requires several years and a huge amount of money. But considering the other alternatives, such as water transfer from adjacent basins the proposed approach should be more economical. Nevertheless, the action of modernizing the irrigation system must be taken sooner or later. It should be mentioned that effective integrated management and planning program, needs accurate input data and information. Therefore, all uncertainties such as estimated amounts of irrigation efficiencies and the lack of reliable observed data for should be considered and if possible be lessened to reduce their erroneous effect on the result. This could be accomplished through planning a good measurement network throughout the basin for all data needed currently and in the future by the models in order to carry out a reliable study in the basin. More attentions should be given to key data including rainfall, river discharge and water used for irrigation at different sites throughout the basin. 5. Conclusion According to the considerable impact of agricultural water consumption on Urmia Lake level fluctuations, accurate estimation of this component can improve the whole process of water resources management and help to make better decisions. Therefore in this paper, agricultural water consumption was estimated for Urmia Lake basin and its impact on the Lake system was studied. Results indicate that without any agricultural withdrawal from water resources in the basin, the Lake level would have reached to about 1278 m instead of 1273 m, the observed level in Moreover, an increase of about 3 meters (10 billion cubic meters) would have occurred in the Lake level by improving the irrigation efficiency of the basin. 7. Appreciation The authors would like to appreciate all people and organizations for providing data and information for this research. In specific, we would like to thank the Ministry of Energy and Mahab Ghodss Consulting Engineers for their help. References [1] Eimanifar A, Mohebbi F. Urmia Lake (Northwest Iran): a brief review. Saline Systems, 3:5. 1-8, [2] Ghaheri M, Baghal-Vayjooee M.H, Naziri J. Lake Urmia: a summary review. International Jout\rnal of Salt Lake Research, 8: 19-22, [3] UNEP (GEAS). The drying of Iran s Lake Urmia and its environmental consequences. UNEP Global Environmental Alert Service; 2012.

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