Climate change impact on water quality in the integrated Mahabad Dam watershed-reservoir system

Climate change, besides global warming, is expected to intensify the hydrological cycle, which can impact watershed nutrient yields and affect water quality in the receiving water bodies. The Mahabad Dam Reservoir in northwest Iran is a eutrophic reservoir due to excessive watershed nutrient input, which could be exacerbated due to climate change. In this regard, a holistic approach was employed by linking a climate model (CanESM2), watershed-scale model (SWAT), and reservoir water quality model (CE-QUAL-W2). The triple model investigates the cumulative climate change effects on hydrological parameters, watershed yields, and the reservoir’s water quality. The SDSM model downscaled the output of the climate model under moderate (RCP4.5) and extreme (RCP8.5) scenarios for the periods of 2021–2040 and 2041–2060. The impact of future climate conditions was investigated on the watershed runoff and total phosphorus (TP) load, and consequently, water quality status in the dam’s reservoir. The results of comparing future conditions (2021–2060) with observed present values under moderate to extreme climate scenarios showed a 4–7% temperature increase and a 6–11% precipitation decrease. Moreover, the SWAT model showed a 9–16% decline in streamflow and a 12–18% decline in the watershed TP load for the same comparative period. Finally, CE-QUAL-W2 model results showed a 3–8% increase in the reservoir water temperature and a 10–16% increase in TP concentration. It indicates that climate change would intensify the thermal stratification and eutrophication level in the reservoir, especially during the year’s warm months. This finding specifies an alarming condition that demands serious preventive and corrective measures.     

Impact of Human Intervention and Climate Change on Natural Flow Regime

According to the ‘natural flow paradigm’, any departure from the natural flow condition will alter the river ecosystem. River flow regimes have been modified by anthropogenic interventions and climate change is further expected to affect the biotic interactions and the distribution of stream biota by altering streamflow. This study aims to evaluate the hydrologic alteration caused by dam construction and climatic changes in a mesoscale river basin, which is prone to both droughts and monsoonal floods. To analyse the natural flow regime, 15 years of observed streamflow (1950–1965) prior to dam construction is used. Future flow regime is simulated by a calibrated hydrological model Soil and Water Assessment Tool (SWAT), using ensemble of four high resolution (~25 km) Regional Climate Model (RCM) simulations for the near future (2021–2050) based on the SRES A1B scenario. Finally, to quantify the hydrological alterations of different flow characteristics, the Indicators of Hydrological Alteration (IHA) program based on the Range of Variability Approach (RVA) is used. This approach enables the assessment of ecologically sensitive streamflow parameters for the pre- and post-impact periods in the regions where availability of long-term ecological data is a limiting factor. Results indicate that flow variability has been significantly reduced due to dam construction with high flows being absorbed and pre-monsoon low flows being enhanced by the reservoir. Climate change alone may reduce high peak flows while a combination of dam and climate change may significantly reduce variability by affecting both high and low flows, thereby further disrupting the functioning of riverine ecosystems. We find that, in the Kangsabati River basin, influence of dam is greater than that of the climate change, thereby emphasizing the significance of direct human intervention.     

Application of the SWAT Model for a Tile-Drained Lowland Catchment in North-Eastern Germany on Subbasin Scale

Tile drainage is a widespread practice in agriculturally dominated lowlands with naturally high groundwater tables. A realistic estimation of the stream flow composition including tile drainage is an essential precondition for identifying major flow sources of nutrients. In this study, the Soil Water Assessment Tool (SWAT) was applied to the partially tile-drained Warnow catchment in north-eastern Germany to evaluate the effect of tile drainage systems on stream flow composition on a subbasin scale. In addition, model performance was tested after excluding tile drainages from the calibrated model setup. A sensitivity analysis revealed the highest sensitivities for parameters concerning evapotranspiration, soil characteristics, and groundwater flow, with a large variability in sensitivity ranks among the subbasins. Nash-Suttcliffe-Efficiencies (NSE) varied strongly among the subbasins for the tile-drained model setup ranging from 0.22 to 0.81 for the calibration and from ?0.81 to 0.66 for the validation period. The percentage of tile flow varied between 0.3 and 31.9 %, and reflected statistically significantly (p?<?0.05) the spatial extent of tile-drained areas within the subbasins. Excluding tile drainages from the model setup led to a strong decrease in model quality and to a changed stream flow constitution dominated by groundwater. The results of our study indicate that the SWAT model realistically represented the actual fractions of tile flow on discharge on the subbasin scale within the Warnow catchment. Therefore, we conclude that the incorporation of tile drainage systems is essential to calculate flow components accurately.     

Assessment of Future Climate Change Impacts on Water Resources of Upper Sind River Basin, India Using SWAT Model

A study has been conducted to assess future climate change impacts on water resources of the Upper Sind River Basin using Soil Water Assessment Tool. Sequential uncertainty fitting (SUFI-2) algorithm has been applied for model calibration and uncertainty analysis. Monthly observed stream flows matched well with simulated flows with respect to p-factor, d-factor, Correlation coefficient and Nash-Sutcliffe coefficients with values of 0.73, 0.42, 0.82, 0.80 during calibration (1992–2000) and 0.42, 0.36, 0.96, 0.93 during validation (2001–2005) respectively. PRECIS generated outputs under IPCC A1B Scenarios for Indian conditions corresponding to the baseline (1961–1990), midcentury (2021–2050) and endcentury (2071–2098); extracted by Indian Institute of Tropical Meteorology, Pune (India) have been used for the study. It has been found from the model results that the average annual streamflow could increase by 16.4 % for the midcentury and a significant increase of 93.5 % by the endcentury. The results also indicate that streamflow may rise drastically in monsoon season, but will decrease in non-monsoon season due to the projected future climate change.     

Statistical Downscaling of River Runoff in a Semi Arid Catchment

Linear and non-linear statistical ‘downscaling’ study is applied to relate large-scale climate information from a general circulation model (GCM) to local-scale river flows in west Iran. This study aims to investigate and evaluate the more promising downscaling techniques, and provides a through inter comparison study using Karkheh catchment as an experimental site in a semi arid region for the years of 2040 to 2069. A hybrid conceptual hydrological model was used in conjunction with modeled outcomes from a General Circulation Model (GCM), HadCM3, along with two downscaling techniques, Statistical Downscaling Model (SDSM) and Artificial Neural Network (ANN), to determine how future streamflow may change in a semi arid catchment. The results show that the choice of a downscaling algorithm having a significant impact on the streamflow estimations for a semi-arid catchment, which are mainly, influenced, respectively, by atmospheric precipitation and temperature projections. According to the SDSM and ANN projections, daily temperature will increase up to +0.58 0C (+3.90 %) and +0.48 0C (+3.48 %), and daily precipitation will decrease up to ?0.1 mm (?2.56 %) and ?0.4 mm (?2.82 %) respectively. Moreover streamflow changes corresponding to downscaled future projections presented a reduction in mean annual flow of ?3.7 m^3/s and ?9.47 m^3/s using SDSM and ANN outputs respectively. The results suggest a significant reduction of streamflow in both downscaling projections, particularly in winter. The discussion considers the performance of each statistical method for downscaling future flow at catchment scale as well as the relationship between atmospheric processes and flow variability and changes.     

Assessment of future climate change impacts on hydrological behavior of Richmond River Catchment

This study evaluated the impacts of future climate change on the hydrological response of the Richmond River Catchment in New South Wales (NSW), Australia, using the conceptual rainfall-runoff modeling approach (the Hydrologiska Byrans Vattenbalansavdelning (HBV) model). Daily observations of rainfall, temperature, and streamflow and long-term monthly mean potential evapotranspiration from the meteorological and hydrological stations within the catchment for the period of 1972–2014 were used to run, calibrate, and validate the HBV model prior to the streamflow prediction. Future climate signals of rainfall and temperature were extracted from a multi-model ensemble of seven global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 3 (CMIP3) with three regional climate scenarios, A2, A1B, and B1. The calibrated HBV model was then forced with the ensemble mean of the downscaled daily rainfall and temperature to simulate daily future runoff at the catchment outlet for the early part (2016–2043), middle part (2044–2071), and late part (2072–2099) of the 21st century. All scenarios during the future periods present decreasing tendencies in the annual mean streamflow ranging between 1% and 24.3% as compared with the observed period. For the maximum and minimum flows, all scenarios during the early, middle, and late parts of the century revealed significant declining tendencies in the annual mean maximum and minimum streamflows, ranging between 30% and 44.4% relative to the observed period. These findings can assist the water managers and the community of the Richmond River Catchment in managing the usage of future water resources in a more sustainable way.     

Estimation of future water resources of Xiangjiang River Basin with VIC model under multiple climate scenarios

Variation trends of water resources in the Xiangjiang River Basin over the coming decades have been investigated using the variable infiltration capacity(VIC) model and 14 general circulation models'(GCMs') projections under the representative concentration pathway(RCP4.5) scenario. Results show that the Xiangjiang River Basin will probably experience temperature rises during the period from 2021 to2050, with precipitation decrease in the 2020 s and increase in the 2030 s. The VIC model performs well for monthly discharge simulations with better performance for hydrometric stations on the main stream of the Xiangjiang River than for tributary catchments. The simulated annual discharges are significantly correlated to the recorded annual discharges for all the eight selected target stations. The Xiangjiang River Basin may experience water shortages induced by climate change. Annual water resources of the Xiangjiang River Basin over the period from 2021 to 2050 are projected to decrease by 2.76% on average within the range from-7.81% to 7.40%. It is essential to consider the potential impact of climate change on water resources in future planning for sustainable utilization of water resources.     

Future Hydrological Drought Analysis Considering Agricultural Water Withdrawal Under SSP Scenarios

Hydrological drought is assessed through river flow, which depends on river runoff and water withdrawal. This study proposed a framework to project future hydrological droughts considering agricultural water withdrawal (AWW) for shared socioeconomic pathway (SSP) scenarios. The relationship between AWW and potential evapotranspiration (PET) was determined using a deep belief network (DBN) model and then applied to estimate future AWW using projections of the twelve global climate models (GCMs). 12 GCMs were bias-corrected using the quantile mapping method, climate variables were generated, and river flow was estimated using the soil and water assessment tool (SWAT) model. The standardized runoff index (SRI) was used to project the changes in hydrological drought characteristics. The results revealed a higher occurrence of severe droughts in the future. Droughts would be more frequent in the near future (2021–2060) than in the far future (2061–2100) and more severe when AWW is considered. Droughts would also be more severe for SSP5-8.5 than for SSP2-4.5. The study revealed that the increased PET due to rising temperatures is the primary cause of the increased drought frequency and severity. The AWW will accelerate the drought severities in the future in the Yeongsan River basin.

     

Climate Change and Hydrological Response in the Trans-State Oologah Lake Watershed–Evaluating Dynamically Downscaled NARCCAP and Statistically Downscaled CMIP3 Simulations with VIC Model

Statistically and dynamically downscaled climate projections are the two important data sources for evaluation of climate change and its impact on water availability, water quality and ecosystems. Though bias correction helps to adjust the climate model output to behave more similarly to observations, the hydrologic response still can be biased. This study uses Variable Infiltration Capacity (VIC) model to evaluate the hydrologic response of the trans-state Oologah Lake watershed to climate change by using both statistically and dynamically downscaled multiple climate projections. Simulated historical and projected climate data from the North American Regional Climate Change Assessment Program (NARCCAP) and Bias-Corrected and Spatially Downscaled–Coupled Model Intercomparison Phase 3 (BCSD-CMIP3) forced the hydrologic model. In addition, different river network upscaling methods are also compared for a higher VIC model performance. Evaluation and comparison shows the following the results. (1) From the hydrologic point of view, the dynamically downscaled NARCCAP projection performed better, most likely in capturing a larger portion of mesoscale-driven convective rainfall than the statistically downscaled CMIP3 projections; hence, the VIC model generated higher seasonal streamflow amplitudes that are closer to observations. Additionally, the statistically downscaled GCMs are less likely to capture the hydrological simulation probably due to missing integration of climate variables of wind, solar radiation and others, even though their precipitation and temperature are bias corrected to be more favorably than the NARCCAP simulations. (2) Future water availability (precipitation, runoff, and baseflow) in the watershed would increase annually by 3–4 %, suggested by both NARCCAP and BCSD-CMIP3. Temperature increases (2.5–3 °C) are much more consistent between the two types of climate projections both seasonally and annually. However, NARCCAP suggested 2–3 times higher seasonal variability of precipitation and other water fluxes than the BCSD-CMIP3 models. (3) The hydrologic performance could be used as a potential metric to comparatively differentiate climate models, since the land surface and atmosphere processes are considered integrally.     

Evaluating the Importance of Non-Unique Behavioural Parameter Sets on Surface Water Quality Variables under Climate Change Conditions in a Mesoscale Agricultural Watershed

The parameter uncertainty in the eco-hydrological model Soil and Water Assessment Tool (SWAT) was estimated using non-unique parameter sets for the Altmühl watershed (Bavaria, Germany). The Sequential Uncertainty Fitting Algorithm (SUFI-2) was used to calibrate SWAT. The non-unique parameter sets found were subsequently applied to SWAT concurrently with climate change simulations to determine the variables of streamflow, nitrate nitrogen (NO₃^?-N) and total phosphorus (TP). A suite of seven bias corrected climate change simulations provided reference (1970–2000) and future (2041–2070) climate data. The non-unique behavioural parameter sets that met an objective function of NSE >0.6 during calibration were applied to SWAT with the reference climate and with the future climate simulations. The best parameter set was also propagated through SWAT with each reference and future climate simulation in turn. Combining the non-unique behavioural parameter sets for estimating uncertainty bounds with an ensemble of climate change simulations led to a wider mean monthly spread (difference between maximum and minimum) of simulated NO₃^?-N and TP than using the best run with the future climate simulations. More monthly data was considered using the non-unique approach, resulting in statistical significances for more months of the year and overall lower interquartile ranges. The study quantifies the non-unique behavioural parameter set contributions to the modelling prediction, which assists in making more informed decisions based on available knowledge, with its limitations, of the future simulations. We outline a simple approach that can easily be replicated for similar hydrological modelling studies.     

A SWAT evaluation of the effect of climate change on the hydrology of the Volta River basin

The SWAT (Soil and Water Assessment Tool) was used to evaluate the impacts of a climate scenario based on IPCC A1B emissions on flows in the Volta River basin in West Africa for 2021–2050 and 2071–2100, using 1983–2012 as the reference period. Overall, the simulation indicates increased variability and a decrease of up to 40% in river flow as a consequence of decreasing rainfall and increasing temperature. In particular, the analysis shows smaller absolute but greater relative changes in the hydrology of the northern (upper) part of the basin, particularly at the end of the century.     

Effects of Land-Use and Climate Change on Hydrological Processes in the Upstream of Huai River, China

Land use/land cover and climate change can significantly alter water cycle at local and regional scales. Xixian Watershed, an important agricultural area in the upper reach of the Huaihe River, has undergone a dramatic change of cultivation style, and consequently substantial land use change, during the past three decades. A marked increase in temperature was also observed. A significant monotonic increasing trend of annual temperature was observed, while annual rainfall did not change significantly. To better support decision making and policy analysis relevant to land management under climate change, it is important to separate and quantify the effect of each factor on water availability. We used the Soil and Water Assessment Tool (SWAT), a physically based distributed hydrologic model, to assess the impact of Land use and climate changes separately. The SWAT model was calibrated and validated for monthly streamflow. Nash-Sutcliff efficiency (NSE), percentage bias (PBIAS), and coefficient of determination (R ²) were 0.90, 6.3 %, and 0.91 for calibration period and 0.91, 6.9 %, and 0.911 for validation period, respectively. To assess the separate effect of land use and climate change, we simulated streamflow under four scenarios with different combinations of two-period climate data and land use maps. The joint effect of land use and climate change increased surface flow, evapotranspiration, and streamflow. Climate variability increased the surface water and stream-flow and decreased actual evapotranspiration; and land use change played a counteractive role. Climate variability played a dominant role in this watershed. The differentiated impacts of land-use/climate variabilities on hydrological processes revealed that the unapparent change in stream-flow is implicitly because the effects of climate variability on hydrological processes were offset by the effects of land use change.     

Flow regime alterations under changing climate in two river basins: implications for freshwater ecosystems

We examined impacts of future climate scenarios on flow regimes and how predicted changes might affect river ecosystems. We examined two case studies: Cle Elum River, Washington, and Chattahoochee–Apalachicola River Basin, Georgia and Florida. These rivers had available downscaled global circulation model (GCM) data and allowed us to analyse the effects of future climate scenarios on rivers with (1) different hydrographs, (2) high future water demands, and (3) a river–floodplain system. We compared observed flow regimes to those predicted under future climate scenarios to describe the extent and type of changes predicted to occur. Daily stream flow under future climate scenarios was created by either statistically downscaling GCMs (Cle Elum) or creating a regression model between climatological parameters predicted from GCMs and stream flow (Chattahoochee–Apalachicola). Flow regimes were examined for changes from current conditions with respect to ecologically relevant features including the magnitude and timing of minimum and maximum flows. The Cle Elum's hydrograph under future climate scenarios showed a dramatic shift in the timing of peak flows and lower low flow of a longer duration. These changes could mean higher summer water temperatures, lower summer dissolved oxygen, and reduced survival of larval fishes. The Chattahoochee–Apalachicola basin is heavily impacted by dams and water withdrawals for human consumption; therefore, we made comparisons between pre‐large dam conditions, current conditions, current conditions with future demand, and future climate scenarios with future demand to separate climate change effects and other anthropogenic impacts. Dam construction, future climate, and future demand decreased the flow variability of the river. In addition, minimum flows were lower under future climate scenarios. These changes could decrease the connectivity of the channel and the floodplain, decrease habitat availability, and potentially lower the ability of the river to assimilate wastewater treatment plant effluent. Our study illustrates the types of changes that river ecosystems might experience under future climates. Copyright © 2005 John Wiley & Sons, Ltd.     

气候变化对嘉陵江流域水资源量的影响分析

 嘉陵江是长江的最大支流,流域面积约16万km2。针对2050,2100年不同的气候变化情景,选取较为不利的参数组合,根据降水、气温、湿度、风速、日照等气候要素的变化,建立潜在蒸发量模型计算流域的潜在蒸发量（ET0）,再根据流域内植被的蒸散发系数（Kc）,计算流域的面平均蒸散发量（ETc）。并利用流域面平均降水量减去径流深得到流域的实际蒸散发量,对计算的流域面平均蒸散发量进行验证。对不同的水平年利用降水的预测成果（气候变化情景不同具有不同的降水量预测成果）及计算流域的面平均蒸散发量,根据水量平衡模型分析计算气候变化对嘉陵江流域水量的影响。结果表明：不利条件下2050年年径流将减少23.0%～27.9%;2100将减少28.2%～35.2%;2050,2100年平均年径流分别相当于目前7年一遇和12年一遇的干旱年。由此说明,气候变化对流域内的水资源量影响十分显著。      

Impact of El Niño and Climate Change on Rainwater Harvesting in a Caribbean State

The water situation of the Pusey district in St Catherine parish of Jamaica is acute because of the district’s hilly terrains which made connections to centralised public water supply difficult. Residents depend on rainwater harvesting (RWH) systems to meet potable needs, like many other catchments across Jamaica. Rainwater collecting practices and water use habits of the residents were surveyed and the present and future RWH capacity was evaluated using the available 18 years (1996 to 2013) rainfall data and downscaled PRECIS model A2 and B2 climate change scenarios. In addition, the effect of El Niño episodes on rainfall patterns was evaluated. The coefficients of variations for annual rainfall were found to be higher for the El Niño years than in normal years. In two of the El Niño years (1997 and 2009), rainwater harvesting capacity is negatively impacted as rainfall annual total is (42 % and 34 %) lesser than the average annual rainfall. The ability of RWH to meet potable needs in 2030s and 2050s will be reduced based on predicted shorter intense showers and frequent dry spells. A storage tank of 2.5 to 4.0 m³ per household (4 persons) is proposed to meet water demand during the maximum consecutive dry days, and January and February water shortage periods. Design of efficient RWH systems and provision of government subsidy on storage tanks will enable the residents to capture more rainwater to meet their daily domestic needs.     

未来气候变化影响下的流域面源污染负荷特征响应评估

针对流域面源污染负荷在未来气候变化影响下的变化特征,以我国新安江上游率水流域为例,使用通用流域污染负荷模型(GWLF),对其2000-2013年的水量及总氮、总磷面源污染负荷通量进行了模拟,并解析了其负荷来源分配。在此基础上,基于政府间气候变化专业委员会(IPCC)的气候变化评估报告结果,利用GWLF模型分析了到21世纪20年代、50年代、80年代在A1FI(最高排放)和B1(最低排放)情景下,率水流域的水文及总氮、总磷面源污染负荷特征变化。结果表明:未来气候变化对流域水文及面源污染负荷特征均有一定影响。年水资源量先减少后增加,地表径流量和蒸发量逐渐上升而地下水量逐渐下降。到2080s,A1FI情景比B1情景有更多的水资源量。年总氮通量先增加后减少,在2050s最高,而年总磷通量则逐渐增加,且两种污染物均在A1FI排放情景下有更高的污染负荷量,表明人类温室气体的排放会潜在地增加流域水体面源污染负荷。     

Climate Change Impacts on Water Resources and Reservoir Management: Uncertainty and Adaptation for a Mountain Catchment in Northeast Portugal

Reservoirs often play an important role in mitigating water supply problems. However, the implications of climate change are not always considered in reservoir planning and management. This study aimed to address this challenge in the Alto Sabor watershed, northeast Portugal. The study analysed whether or not the shortage of water supply can be effectively addressed through the construction of a new reservoir (two-reservoir system) by considering future climate projections. The hydrological model Soil and Water Assessment Tool (SWAT) was calibrated and validated against daily-observed discharge and reservoir volume, with a good agreement between model predictions and observations. Outputs from four General Circulation Models (GCM) for two scenarios (RCP 4.5 and 8.5) were statistically downscaled and bias-corrected with ground observations. A general increase in temperature is expected in the future while the change in precipitation is more uncertain as per the differences among climatic models. In general, annual precipitation would slightly decrease while seasonal changes would be more significant, with more precipitation in winter and much less in spring and summer. SWAT simulations suggest that the existence of two-reservoir will better solve the water supply problems under current climate conditions compared to a single-reservoir system. However in the future, the reliability of this solution will decrease, especially due to the variability of projections from the different climatic models. The solution to water supply problems in this region, adopted taking only present-day climate into account, will likely be inefficient for water supply management under future climate conditions.     

Evapotranspiration from a Mixed Deciduous Forest Ecosystem

The objectives of this paper were to determine evapotranspiration (ET) from an oak-beech dominated forest ecosystem in Belgrad Forest near Istanbul, Turkey by using catchment water balance method and compare it with potential evapotranspiration (PET) computed by using Thornthwaite method. Data, in this study, were derived from a long-term hydrological research conducted in Belgrad Forest. Long-term stream flow measurements (1979–1995) were conducted with concrete sharp-crested V-notch weirs instrumented with automatic water level recorders in two close experimental watersheds. ET values of the watersheds were determined by using water balance equation. Average annual ET values from the old growth oak-beech forest ecosystem during the monitoring period of 17 years were around 833.20 mm for W-I and 752.07 mm for W-IV whereas PET estimated according to Thornthwaite method was found to be 726.14 mm. In other words, 79.68%, and 71.93% of mean annual precipitation evaporated from W-I and W-IV, respectively while 69.45% of precipitation evaporated according to Thornthwaite method. PET estimated with Thornthwaite method differed significantly only from W-I whereas W-I and W-IV had similar ET values.     

An Empirical Water Budget Model As a Tool to Identify the Impact of Land-use Change in Stream Flow in Southeastern Australia

In western Victoria, Australia the water table and lake level in the Glenelg-Hopkins catchment have been declining for the last 15 years, and this is attributed to either the low rainfall over this time and/or a substantial change in land use. Stream flow modelling was carried out using monthly empirical water balance model (modified tanh function together with double mass curve analysis), on 37 stream gauges to assess whether the impact of land use change could be detected by a change in the magnitude of the resulting runoff. The empirical hydrological model was able to distinguish impact of land use change on stream flow from the climatic variables. There were substantial decreases in stream flow in the 1970s–1980s, probably related to increasing livestock densities in the region. Furthermore, the methodology can be a powerful tool to monitor and evaluate the possible impacts of future land use changes. It can be concluded that the use of such empirical hydrological modelling greatly improves the ability to analyse the impact of land use on catchment runoff. The model is a practical tool that can be readily used for identifying and quantifying the effect of landuse changes on catchment for water resource decision-making, which could be hardly possible using the time consuming, data hungry and expensive physical process models available.