Coupled effects of climate variability and land use pattern on surface water quality: An elasticity perspective and watershed health indicators

Assessment of watershed health, integrating environmental, social, and climate change criteria into a fuzzy logic framework

Spatio-temporal analyses of environmental and social criteria in the context of climate change, facilitate understanding of how historical and current conditions have influenced watershed health. Previous studies have analyzed watershed health, but very few have integrated fuzzy logic with the CRITIC method (Criteria Importance Through Intercriteria Correlation), which enables us to explore alternatives to improve watershed performance. The objective of this study was to evaluate changes in watershed health through historical and projected climate change scenario in the tropical Santa Cruz watershed in Aquismón, S.L.P., Mexico (1985-2027) considering environmental criteria (hydrological and sediment connectivity, runoff, flooding, drought, landscape fragmentation) and social criteria (indigenous population density, human impact on biodiversity, health index, income index, education index). The results indicate that spatio-temporal changes can alter the Watershed Health Score (WHS) from a value of 2.69 to 6.90, particularly in areas with precarious social conditions. Moreover, the study reveals how weighting evolves overt time, as seen in the case of landscape fragmentation, whose value increased 0.0113 to 0.254. This study shows how objective methods such as CRITIC can be integrated through fuzzy logic to analyze the spatio-temporal evolution of watershed problems without the need for a large number of experts to weight the variables (subjective methods). This method can subsequently be applied and reproduced in different zones or watersheds where there is no certainty as to which criteria have the greatest influence and thus enable decisions for watershed management or restoration.

Comparative assessment of Watershed Hydrological Health (WHH) using multi-criteria decision-making approach based on PSR framework

The health of a watershed is a crucial aspect that involves evaluating ecological, hydrological, and human factors to determine its overall well-being and functionality. Hydrological components are key parts of a watershed. Therefore, the present study aims to assess Watershed Hydrological Health (WHH) using the Pressure-State-Response (PSR) framework and to compare WHH priorities derived from Multi-Criteria Decision Making (MCDM) approaches in the Gorganroud Watershed, Iran. To do this, with a problem-oriented approach, 16 hydrological criteria were conceptualized in three indices of Pressure (P), State (S), and Response (R) (PSR). In the next step, each of the mentioned criteria was quantified in 16 sub-watersheds of the Gorganroud Watershed. Finally, WHH was calculated based on the PSR framework. According to the criteria Importance Through Intercriteria Correlation (CRITIC) method, the criteria were then weighted, and WHH was calculated using three MCDM methods. To compare the results, the results of the PSR framework were used as the basis and compared with three MCDM methods. The results showed that WHH values in the Gorganroud Watershed ranged from 0.31 to 0.67 in S15 and S9, respectively. Overall, the weighted average WHH in the watershed was 0.52, indicating moderate conditions. Weighting results showed that criteria C4 and C14 had the highest and lowest weights, respectively. WHH priorities based on MCDM methods showed that in the ELimination Et Choice Translating REality (ELECTRE) and Simple Additive Weighting (SAW) methods, sub-watershed S9 had the highest WHH priority, while in the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method, sub-watershed S7 achieved the highest priority. Among these, the ELECTRE and SAW methods performed better in determining WHH priorities and are recommended for future research.

Predicting the effect of hydro-climatic and land-use dynamic variables on watershed health status

This study aimed to predict the impact of changing hydro-climatic variables and land use changes on the future health status of the Safaroud Watershed, northern Iran. It also sought to explore the significance of hydro-climatic and land use variables in prioritizing sub-watersheds based on the watershed health index. The study involved extracting key characteristics related to anthropogenetic, climatic, and hydrological factors for pressure, state, and response indicators. The current watershed health index was calculated, followed by predictions of watershed health based on dynamic hydro-climatic and land-use variables for the next 10 and 20 years. The Safaroud Watershed health assessment and zoning showed that the average value and standard deviation of the current pressure index were equal to 0.573 and 0.185, respectively. The lowest value of this index was around 0.290 and related to sub-watershed 5, and the highest value was around 0.840 and related to sub-watershed 11. The initial evaluation of the classification indicated the prevalence of moderate and high-pressure conditions with a range of about 79%. Finally, the physical factors of sub-watersheds (time of concentration with 15.72%) had the lowest role. In general, among the criteria used to calculate the pressure index in the current period, anthropogenetic and climatic factors showed the highest percentage of participation in determining the pressure index. The quantification of the current watershed health status and the 10- and 20-year-forecast periods showed that the values of the watershed health index were similar. However, the changes in the health index in the sub-watersheds at the beginning of the study period ranged from relatively unhealthy favorable conditions to moderately positive and moderately negative conditions.

Multi-scenario simulation of runoff and nutrient loads in a rapidly urbanizing watershed during China's Dual Carbon periods

Apprehending the hydrological and nutrient variations in rapidly urbanizing watersheds under changing environments is crucial for pollution control and water resource management. However, existing studies have primarily focused on hydrological processes, neglecting water quality aspects, and comprehensive assessment of future runoff and nutrient loads in these watersheds during China's Dual Carbon periods is limited. This study firstly bridges these gaps by constructing multi-scenario with different levels of "Urban Development - Ecological Conservation" and utilizing latest bias-corrected General Circulation Models or Global Climate Models (GCMs) projections to evaluate future runoff and nutrient loads in the Shenzhen River. The calibrated and validated models display satisfactory performance in simulating runoff, nutrient loads, and land use types. The bias-corrected GCMs projections exhibit enhanced accuracy for temperature variables, particularly during the wet season. Implementing effective ecological protection measures is paramount in mitigating water quantity fluctuations and controlling total nitrogen pollution, which is closely associated with urban development and human activities. Conversely, total phosphorus loads demonstrate greater simulation uncertainty, particularly during the dry season of the Carbon Neutrality period, requiring further exploration. Compared to the baseline period, runoff changes minimally, with notable seasonal variations. The findings highlight the escalating uncertainty in load predictions as time progresses. Additionally, addressing uncertainties in precipitation projections driven by GCMs is imperative, given their substantial influence on runoff and nutrient load simulations, particularly during challenging dry seasons. While further research is needed to reduce simulation uncertainty, our study provides valuable insights into nitrogen-phosphorus pollution control and sustainable water resource management in rapidly urbanizing watersheds, especially during the near-term period.

Integrated effects of co-evolutions among climate, land use and vegetation growing dynamics to changes of runoff quantity and quality

Climates, Land use/land cover (LULC) and vegetation growing dynamics have been regarded as the main factors affecting terrestrial hydrological process. However, the mechanisms underlying their integrated effects on terrestrial runoff and nutrient dynamics are not understood well. Here, we constructed a framework to disentangle and quantify the independent and coupled contributions of climate, LULC and vegetation leaf area index (LAI) changes to watershed runoff and nutrient yields changes. Long series of changing meteorological, LULC and LAI data between 1990 and 2020 were integrated into a factor-controlled simulation protocol in a distributed hydrological model, to quantify their comprehensive contributions (individual contribution of single factor change and coupling contribution of multiple factor synchronous changes) to runoff and nutrient changes. The results showed that changes of runoff and nutrient yields are more induced by climate change, rather than LULC and LAI transformations. Increase in annual precipitation significantly elevated runoff and nutrient yields. TP yield was more sensitive to climate change than runoff and TN yields. LULC transformation and climate change have synergistic effects on runoff and nutrient yields. Shift of vegetation areas to construction lands will amplify the effect of climate change on runoff and nutrient yields. Single LAI change has weak effect on runoff and nutrient yields, but it can significantly alter the hydrological effects derived from climate change and the synergistic effects between climate change and LULC transformation. This study considered the coupling and potential synergistic effects among climate change, LULC conversion and LAI variation, which elucidated the comprehensive effects of changing environment on runoff and nutrients evolutions in a more systematic and integrated perspective.

Investigating water quality sensitivity to climate variability and its influencing factors in four Lake Erie watersheds

Climate change alters weather patterns and hydrological cycle, thus potentially aggravating water quality impairment. However, the direct relationships between climate variability and water quality are complicated by a multitude of hydrological and biochemical mechanisms dominate the process. Thus, little is known regarding how water quality responds to climate variability in the context of changing meteorological conditions and human activities. Here, a longitudinal study was conducted using trend, correlation, and redundancy analyses to explore stream water quality sensitivity to temperature, precipitation, streamflow, and how the sensitivity was affected by watershed climate, land cover percentage, landscape configuration, fertilizer application, and tillage types. Specifically, daily pollutant concentration data of suspended solid (SS), total phosphorus (TP), soluble reactive phosphorus (SRP), total Kjeldahl nitrogen (TKN), nitrate and nitrite (NO_x), and chloride (Cl) were used as water quality indicators in four Lake Erie watersheds from 1985 to 2017, during which the average temperature has increased 0.5 °C and the total precipitation has increased 9%. Results show that precipitation and flow were positively associated with SRP, NO_x, TKN, TP, and SS, except for SRP and NO_x in the urban basin. The rising temperatures led to increasing concentrations of SS, TKN, and TP in the urban basin. SRP and NO_x sensitivity to precipitation was higher in the years with more precipitation and higher precipitation seasonality, and the basins with more spatially aggregated cropland. No-tillage and reduced tillage management could decrease both precipitation and temperature sensitivity for most pollutants. As one of the first studies leveraging multiple watershed environmental variables with long-term historical climate and water quality data, this study can assist target land use planning and management policy to mitigate future climate change effects on surface water quality.

Spatial-Temporal Change of Land Use and Its Impact on Water Quality of East-Liao River Basin from 2000 to 2020

Land use change is an important driving force factor affecting the river water environment and directly affecting water quality. To analyze the impact of land use change on water quality change, this study first analyzed the land use change index of the study area. Then, the study area was divided into three subzones based on surface runoff. The relationship between the characteristics of land use change and the water quality grade was obtained by grey correlation analysis. The results showed that the land use types changed significantly in the study area since 2000, and water body and forest land were the two land types with the most significant changes. The transfer rate is cultivated field > forest land > construction land > grassland > unused land > water body. The entropy value of land use information is represented as Area I > Area III > Area II. The shift range of gravity center is forest land > grassland > water body > unused land > construction land > cultivated field. There is a strong correlation between land use change index and water quality, which can be improved and managed by changing the land use type. It is necessary to establish ecological protection areas or functional areas in Area I, artificial lawns or plantations shall be built in the river around the water body to intercept pollutants from non-point source pollution in Area II, and scientific and rational farming in the lower reaches of rivers can reduce non-point source pollution caused by farming.

Nitrogen sources, processes, and associated impacts of climate and land-use changes in a coastal China watershed: Insights from the INCA-N model

The Integrated Nitrogen CAtchments (INCA-N) model was applied to identify the sources and processes controlling riverine nitrogen (N) export in the Jiulong River watershed, coastal China. Future riverine N exports were simulated under various scenarios of climate and land-use changes. The modeling results showed good agreement between the observed and simulated values of streamflow, N concentrations, and loads. It was revealed that fertilizer application, atmospheric N deposition, and sewage discharges were the main N sources, while the primary N cycling processes included soil nitrification, soil denitrification, and N leaching. Nitrate-N exports were predominantly impacted by climate change, whereas ammonium-N exports were more affected by land-use change. The coupled effects of climate and land-use changes were projected to amplify nitrogen export by 30%, 36%, and 36% for nitrate-N and 32%, 48%, and 71% for ammonium-N during the years for 2030s, 2050s, and 2080s, respectively.