Trend in river water quality: tracking the overall impacts of climate change and human activities onwater quality in the Dez River Basin

A perceptible degradation in water quality complicates safe water supply for drinking and irrigation purposes. Therefore, this study aims at monitoring water quality changes and effective factors in the Dez River Basin, which are required to manage water resources effectively. To this end, the common influence of flow rate changes on water quality was separated by implementing seasonal Mann– Kendall test on residuals resulting from the LOWESS test. The results show that after adjusting the effects of seasonality and streamflow fluctuations, significant positive trends in most water quality parameters are still observed. It emphasizes the role of other factors controlling river water quality in the basin. Comparison of the trends of modified quality parameter time series (residuals) in different subbasins having natural or mad-made conditions, with or without significant groundwater resources, shows almost the same presented trends in water quality. This supports that, overall, minor changes occurred in land use, groundwater table, and environmental and human factors with no important influences on presented trends in water quality. Our analyses show that overall reduction in precipitation as well as positive trends in temperature and evaporation led to intensified streamflow variations, explaining the main changes in the river water quality of the basin.


GRAPHICAL ABSTRACT INTRODUCTION
The Dez River, as the second largest river in Iran and one of the major tributaries of the Karun River, is one of the main water resources in the Khuzestan province in order to provide fresh water needed for drinking, domestic uses, and agriculture purposes. Hence, besides water quantity, it is important to evaluate the water quality of the Dez River Basin. In arid and semi-arid climates, with considerable shortage of potable water, monitoring of river water quality and the influencing factors should receive great importance.
Analysis of water quality as well as monitoring possible water quality changes are important tasks for better management of water resources. Therefore, many studies have In river basin management, analysis of the relationship between water quality parameters and streamflow rate is a crucial step to distinguish changes in water quality (Assilis et al. ). Therefore, this case study considers the influence of common seasonal fluctuations and flow rate changes on water quality using a set of non-parametric statistical techniques, i.e., modified Kendall, LOWESS, and seasonal Kendall on residues resulting from the LOWESS test, to identify possible climate, environmental, and anthropogenic factors controlling water quality changes in the Dez River Basin.

Study area and data set
The Dez River Basin, located in the western part of Iran between 48 22 0 16″ to 50 18 0 54″ E and 32 33 0 48″ to 34 06 0 52″ N, covers approximately 15,990 km 2 . Elevation of the study site ranges from 292 to 4,049 meters above sea level (masl), and the length of the river is 415 km (Figure 1 (Table 1). Human activities such as dam construction do not effect these monitoring sites. In addition, there are no main industrial companies in the upstream of the Dez River, where cities are located in the downstream of the Dez dam. The Dez dam is located in the downstream of the outlet of the study area ( Figure 1).

Seasonal Kendall test (SK)
Obviously, most parameters of the surface water quality show a strong seasonal pattern (Helsel & Hirsch ). In order to identify trends in surface water quality over time, like other exogenous effects, the seasonal effects should be By summing the S Kendal data for each season (S i ), the overall statistics of seasonal Kendal S k is calculated as follows: The null hypothesis in this test is defined as the absence of trend in the time series. In the absence of trend, S k will have a normal distribution and its average (μ sk ¼ 0), and variance (σ sk ) can be calculated as follows: where (n i ) is the number of data in the i th season.
The Z sk seasonal Kendall statistic can be calculated as follows:

Sen's slope estimator
The slope of the trend line can be calculated by Theil-Sen method as follows: where Q is the slope of the trend line between consecutive data X j and X k , at times j and k, respectively, and J is always greater than K. Positive values indicate increasing trends and negative values indicate decreasing trends.

LOWESS (locally weighted scatter plot smoothing)
After elimination of seasonal variations, other variables can affect water quality parameters where the river discharge is the main variable. For a more detailed analysis of trend in water quality and separating the effect of discharge, LOWESS test was applied to all time series. As well as LOWESS test separating the effect of discharge, studying the residuals is an appropriate approach to determine the role of other possible environmental factors affecting water quality, such as changes in groundwater-surface water interaction, temperature, evaporation, etc. After obtaining water quality parameter values (Y″) using LOWESS curve, residuals (R) can be calculated as follows: where Y and Y″ are observed and estimated (by LOWESS) water quality parameter values, respectively. The smoothing technique, LOWESS, will define the relationship between water quality parameters and river discharge without assuming the normality of residuals or linear relationship (Helsel & Hirsch ). In this regard, an example is presented in

Serial correlation
The lack of internal correlation between the data is required for using non-parametric tests. It is because such correlations can have an effect on data analysis and significance of trend statistics (Kumar et al. ). Therefore, the effects of autocorrelation were considered in trend analysis of whole time series data.

Categorization of trends
The significance levels were considered at confidence levels of The slopes of the trend lines calculated by Theil-Sen method are presented in Table 5. After elimination of the two major exogenous variables, i.e., discharge and seasonal patterns, any possible effects on water quality can be clari-    might help for better understanding the changes in river water quality and identifying any possible controller.

River Basin
Land-use change and human influence   obvious changes occurred in the rangeland areas, about þ3.9% (Table 6) Possible changes in groundwater levels (an environmental factor resulted from natural and man-made change) The relationship between surface water and groundwater is inevitable, as in most arid and semi-arid basins in Iran such as central wadis, the base flow is supplied by shallow aquifer (Mahmoodi et al. a, b). In a particular area, a large difference between surface water and groundwater quality is common. In the Dez Basin, EC of groundwater is greater than the EC of surface water. Therefore, the different contri- Kendall test is applied to these available short time series (Table 7). The geographical positions of piezometers are presented in Figure 1. The results of the test show mostly declining trends in groundwater level of both aquifers, but these negative trends are significant only in P 2 and P 4 in Azna-Aligudarz plain and in P 1 , P 8 , P 11 , and P 12 in Doroud-Borujerd plain at a confidence level of 90%.
Obviously, because of higher EC of groundwater rather than that of surface water, declining trends in groundwater levels can improve surface water quality in rivers which are affected by groundwater depletion and result in negative trends of EC values of surface water. While EC of surface water has positive significant trends in many cases, especially for station S 2 , it can be interpreted that the minor declining trends in groundwater table cannot explain the observed positive trends in surface water quality constituents.

Precipitation and streamflow discharge variations
One of the climate factors affecting streamflow is precipitation, which can change water quality by change in river discharge. As mentioned in previous sections, streamflow discharge is the main controller of stream water quality around the world, but it is not responsible for the whole change in river water quality. The trend in precipitation of three rain gauges R 1 , R 2 , and R 3 (Figure 1) was analyzed.
More details are available in Mahmoodi et al. (under review). They reported that the trends were not significant for any of the mentioned stations, but streamflow reductions were possibly caused by overall reductions in precipitation.
Due to a general strong relation between both precipitation and discharge with water quality, any small changes in precipitation, and consequently streamflow rates, can lead to significant changes in water quality parameters. Therefore, it can be concluded that precipitation may justify parts of the observed trends in the Dez River water quality thorough changes in the Dez River water quantity.

Temperature and evaporation variations
The effects of temperature on evaporation rate, discharge, and, in addition, on dissolution can influence river water quality. Hence, the temporal changes in temperature at three stations T 1 , T 2 , and T 3 were analyzed by modified   1. Combination of non-parametric statistical methods is a suitable approach to evaluate the temporal variability of hydrochemical components as well as to separate the impact of climate change, environmental, and anthropogenic factors on variability of these components.
2. In addition to alterations in streamflow as a main factor, climate variability present in temperature and, consequently, in evaporation plays a key role on temporal trends of hydrochemical components.
3. Impact of groundwater contribution on stream water quality is more pronounced in subbasins where the groundwater-surface interaction is higher.
4. Comparing subbasin 2, with a considerable land-use alteration, with other subbasins corroborates that although land-use change could have an impact on water quality of the Dez River Basin, it is not the main driver over the study period.
Changes in temperature and evaporation emphasize a new aspect of climate change effects on river water quality and warn of a new challenge for water resources management in semi-arid areas facing climate changes.
specific funding for this article. The authors have declared that no competing interests exist.

DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.