Changes In Annual Streamflow Research Articles

Integrating conceptual and machine learning models to enhance daily-Scale streamflow simulation and assessing climate change impact in the watersheds of the Godavari basin, India

This study examined and addressed climate change's effects on hydrological patterns, particularly in critical places like the Godavari River basin. This study used daily gridded rainfall and temperature datasets from the Indian Meteorological Department (IMD) for model training and testing, 70% and 30%, respectively. To anticipate future hydrological shifts, the study harnessed the EC-Earth3 data, presenting an innovative methodology tailored to the unique hydrological dynamics of the Godavari River basin. The Sacramento model provided initial streamflow estimates for Kanhargaon, Nowrangpur, and Wairagarh. This approach melded traditional hydrological modeling with advanced multi-layer perceptron (MLP) capabilities. When combined with parameters like lagged rainfall, lagged streamflow, potential evapotranspiration (PET), and temperature variations, these initial outputs were further refined using the Sac-MLP model. A comparison with Sacramento revealed the superior performance of the Sac-MLP model. For instance, during training, the Nash Sutcliffe efficiency (NSE) values for the Sac-MLP witnessed an improvement from 0.610 to 0.810 in Kanhargaon, 0.580 to 0.692 in Nowrangpur, and 0.675 to 0.849 in Wairagarh. The results of the testing further corroborated these findings, as evidenced by the increase in the NSE for Kanhargaon from 0.890 to 0.910. Additionally, Nowrangpur and Wairagarh experienced notable improvements, with their NSE values rising from 0.629 to 0.785 and 0.725 to 0.902, respectively. Projections based on EC-Earth3 data across various scenarios highlighted significant shifts in rainfall and temperature patterns, especially in the far future (2071–2100). Regarding the relative change in annual streamflow, Kanhargaon projections under SSP370 and SSP585 for the far future indicate increases of 584.38% and 662.74%. Similarly, Nowrangpur and Wairagarh are projected to see increases of 98.27% and 114.98%, and 81.68% and 108.08%, respectively. This study uses EC-Earth3 estimates to demonstrate the Sac-MLP model's accuracy and importance in climate change water resource planning. The unique method for region-specific hydrological analysis provides vital insights for sustainable water resource management. This research provides a deeper understanding of climate-induced hydrological changes and a robust modeling approach for accurate predictions in changing environmental conditions.

A novel coupled algorithm-based method, and the characteristics and driving mechanism of water shortage in the upper Yellow River

ABSTRACT Gaining a clear understanding of the spatiotemporal characteristics of water shortage and their driving mechanism in the upper Yellow River (UYR) is crucial for the assessment and effective management of water resources in the region. The standardized streamflow index (SSI) and the improved Hilbert-Huang transform (IHHT) algorithm are combined to form a coupled SSI-IHHT method (CSIHM). The streamflow above Lanzhou Station over 1969–2015 is analysed. Results show that summer and autumn are high-risk periods of continuous water shortage. Annual streamflow has inter-annual change cycles of 3.5–9.0 a and inter-decadal change cycles between 16.4 and 28.2 a. The annual streamflow change is mainly affected by climate change. But the seasonal streamflow change is mainly influenced by human activities resulting from the operation of reservoirs. The CSIHM has advantages of mutual verification of the results and wide applicability to the field of water shortage.

Can direct CMIP6 model simulations reproduce mean annual historical streamflow change?

Direct streamflow outputs from CMIP6 models are important for studying future water supply under climate change. However, the hydrological community generally ignores such data as its ability to predict streamflow change is largely unquantified and presumably considered biased. Here, we examined the ability of the 15 CMIP6 models to directly reproduce the observed mean annual streamflow change (ΔQ) between 1999–2014 and 1982–1998 for 115 large basins across the globe. The ΔQ and error of ΔQ in CMIP6 models (ΔQ_error) were then attributed to nine independent climate and vegetation variables using a stepwise regression model. Compared to the observations, almost all of the CMIP6 models overestimate ΔQ. In variable attribution, the observed ΔQ in the 115 basins can be well attributed (R2 = 0.59) to changes in precipitation (66 %), temperature (15 %), and leaf area index (-18 %). However, these variables could not explain ΔQ obtained from CMIP6 models (R2 = 0.13). In error attribution, errors in precipitation change contributes the most (69 ± 12 %) to ΔQ_error in CMIP6 models, followed by location-related variables, changes in vegetation-related variables, and changes in temperature-related variables. Although the current performance of CMIP6 model outputs varies in simulating observed streamflow change, they may become more reliable with improved model structures for better representations of climate and land surface processes.

Identifying the impacts of land use landscape pattern and climate changes on streamflow from past to future

Identifying the individual and combined hydrological response of land use landscape pattern and climate changes is key to effectively managing the ecohydrological balance of regions. However, their nonlinearity, effect size, and multiple causalities limit causal investigations. Therefore, this study aimed to establish a comprehensive methodological framework to quantify changes in the landscape pattern and climate, evaluate trends in streamflow response, and analyze the attribution of streamflow events in five basins in Beijing from the past to the future. Future climate projections were based on three general circulation models (GCMs) under two shared socioeconomic pathways (SSPs). Additionally, the landscape pattern in 2035 under a natural development scenario was simulated by the patch-generating land use simulation (PLUS). The Soil and Water Assessment Tool (SWAT) was applied to evaluate the streamflow spatial and temporal dynamics over the period 2005–2035 with multiple scenarios. A bootstrapping nonlinear regression analysis and boosted regression tree (BRT) model were used to analyze the individual and combined attribution of landscape pattern and climate changes on streamflow, respectively. The results indicated that in the future, the overall streamflow in the Beijing basin would decrease, with a slightly reduced peak streamflow in most basins in the summer and a significant increase in the autumn and winter. The nonlinear quadratic regression more effectively explained the impact of landscape pattern and climate changes on streamflow. The trends in the streamflow change depended on where the relationship curve was in relation to the threshold. In addition, the impacts of landscape pattern and climate changes on streamflow were not isolated but were joint. They presented a nonlinear, non-uniform, and coupled relationship. Except for the YongDing River Basin, the annual streamflow change was influenced more by the landscape pattern. The dominant factors and the critical pair interactions varied from basin to basin. Our findings have implications for city planners and managers for optimizing ecohydrological functions and promoting sustainable development.

Climatic and different human influences on annual and seasonal streamflow with considering the soil water storage change in the middle reaches of the Yellow River basin, China

Recent climate change and more intensive human activities have induced significant changes in streamflow along the middle reaches of the Yellow River basin (MRYRB), which has attracted considerable attention from the scientific community. However, most previous studies have focused on changes in annual streamflow by examining data from a small number of hydrological stations and the role of the various human activities remains unclear. Here we used an extended Budyko-based framework that considered changes in soil water storage (ΔS) to determine the contributions of changes in streamflow, both at the annual and seasonal scale. These analysis were conducted on 40 catchments and three sections (Toudaoguai–Longmen, TDG–LM; Longmen-Huayuankou, LM–HYK; and Toudaoguai–Huayuankou, TDG–HYK) in the MRYRB from 1971 to 2015. Results showed that streamflow at most catchments and sections declined dramatically after years of abrupt change detected by the Pettitt test, with decreases occurring at a faster rate during flood seasons (42.9%) than during non-flood seasons (31.8%). Although human behaviors were often the main cause of streamflow reductions at the annual and seasonal scales, the effects of ΔS became more important at increasingly finer scales. Indeed, they were of equal or greater importance than human impacts in some catchments, with corresponding relative contributions up to 48%. The effects of human activities may possibly have been overestimated or underestimated by 1–16% in three sections when the impact of ΔS was not considered. Further analysis indicated that human water use – particularly the rapid increase in water withdrawals for domestic purposes, electricity generation, and manufacturing – was the primary factor among human activities that affected streamflow reduction in the LM–HYK and TDG–HYK sections at different timescales, comprising 60–90% of all impacts. By contrast, the effects of water use and other human factors were almost equal in the TDG–LM section. Among the other human factors, vegetation restoration played a more critical role in the TDG–LM section, whereas the construction of check-dams was more important in the LM–HYK section. These findings of our study can enhance the understanding of hydrological changes in response to environmental factors.

Impacts of Climate Change and Human Activities on Streamflow of Upper Yongding River Basin, North China

Streamflow in semiarid areas, especially in North China, was rapidly decreasing, which made it important to analyze the characteristics and influencing factors of streamflow. Using the hydro-meteorological data series of 1961–2017 in the upper Yongding River Basin (UYRB) (including the Yang River Basin (YRB) and Sanggan River Basin (SRB)), spatio-temporal variation characteristics of air temperature, precipitation, and potential evapotranspiration (E0) were analyzed. The results showed that precipitation has no significant trend; the temperature showed a significant increase of 0.1–0.5 °C per decade; E0 showed a significant decrease of approximately −2 mm/10yr (in 18 stations); the estimated rates of streamflow change were −7 and −8 mm/10yr for SRB and YRB. As for spatial distribution, the YRB presented a higher E0 value than the SRB; the mountain areas had more precipitation than the plain areas. The change points of streamflow occurred in 1982 and 2003. Both the Budyko and the DMC methods were used to evaluate the impacts of climate change and human activities on the mean annual streamflow. In variation stage I (1983~2003), impacts of human activities account for 90.6% and 62.7% of the mean annual streamflow changes in YRB and SRB, respectively. In variation stage II (2004~2017), the percentages were 99.5% and 93.5%, respectively. It is also noted that the first change point in streamflow was indeed at the beginning of China’s land reform, when the farmers could manage their reallocated lands and, therefore, there was an increase in agricultural water consumption. The second change point coincided with “Capital Water Resources Planning”, including water conservation projects and irrigation district construction programs. In general, human activities were mainly responsible for the significant decline in the annual streamflow of UYRB. This paper will provide valuable results for water resources planning and give guidance on the construction of water conservation function areas and ecological environment support areas in the capital.

Streamflow Response to Wildfire Differs With Season and Elevation in Adjacent Headwaters of the Lower Colorado River Basin

AbstractFires increasingly impact forested watersheds, with uncertain water resources impacts. While research has revealed higher peak flows, longer‐term yields may increase or decrease following fire, and the mechanisms regulating post‐fire streamflow are little explored. Hydrologic response to disturbance is poorly understood in the Lower Colorado River Basin (LCRB), where snowmelt often occurs before the growing season. Here, we quantify annual streamflow changes following what have been, before 2020, two of the largest wildfires in the modern history of the contiguous United States. We evaluate nine nested watersheds with >50 years records within the Salt River Basin to evaluate fire impact over ranges of elevation, climate, vegetation, burned area, and spatial scale. We employ double‐mass comparison of paired watersheds, pre‐ and post‐fire runoff ratio comparison, multiple linear regression of climate and fire, and time‐trend analysis. Precipitation and streamflow are decoupled during dry periods; therefore we conduct separate change detection for wet and dry periods. Post‐fire summer streamflow increased by 24%–38% at all elevations. While winter/spring streamflow remained constant in the highest, coldest headwaters, winter flows declined in lower‐elevation headwaters. As a result, basin annual streamflow declined. These results support emerging understanding that warm semiarid watersheds respond differently to disturbance than well‐studied, colder watersheds. Asynchrony between winter snowmelt and summer evaporative demand is likely important when considering long‐term impacts of forest management and disturbance on water supply in the LCRB.

Estimating impacts of wildfire and climate variability on streamflow in Victoria, Australia

AbstractWildfires are common in Australia and can cause vegetation loss and affect hydrological processes such as interception, evapotranspiration, soil water storage and streamflow. This study investigates wildfire impacts on catchment mean annual streamflow for 14 Australian catchments that have been severely impacted by the 2009 Victoria wildfire, the second‐worst wildfire disaster in Australia. A statistical approach based on sensitivity coefficients was used for quantifying the climate variability impacts on streamflow and the time trend analysis method was used to estimate the annual streamflow changes due to wildfire respectively. Our results show that wildfire has caused a noticeable increase in mean annual streamflow in the catchments with a burnt area above 70% for an immediate post‐wildfire period (2009–2015) and the wildfire impact on streamflow is evidently larger than the climate change impact in the majority of burnt catchments. Furthermore, the wildfire impact on mean annual streamflow strongly increases with the burnt percentage area, indicated by R2 = 0.73 between the two. The results also illustrate that catchments with high burnt percentage areas can have more potential to gain increased streamflow due to wildfires compared with that due to climate variability and can have significant streamflow change after wildfires above the 70% threshold of burnt area. These results provide evidence for evaluating large‐scale wildfire impact on streamflow at small to medium‐sized catchments, and guidance for process‐based hydrological models for simulating wildfire impacts on hydrological processes for the immediate period after the wildfire.

Projected Streamflow and Sediment Supply under Changing Climate to the Coast of the Kalu River Basin in Tropical Sri Lanka over the 21st Century

Tropical countries are already experiencing the adverse impacts of climate change. This study presents projections of climate change-driven variations in hydrology and sediment loads in the Kalu River Basin, Sri Lanka. Bias-corrected climate projections (i.e., precipitation and temperature) from three high resolution (25 km) regional climate models (viz., RegCM4-MIROC5, MPI-M-MPI-ESM-MR, and NCC-NORESM1-M) are used here to force a calibrated hydrological model to project streamflow and sediment loads for two future periods (mid-century: 2046–2065, and end of the century: 2081–2099) under two representative concentration pathways (i.e., RCPs 2.6 and 8.5). By the end of the century under RCP 8.5, all simulations (forced with the three RCMs) project increased annual streamflow (67–87%) and sediment loads (128–145%). In general, streamflow and sediment loads are projected to increase more during the southwest monsoon season (May–September) than in other periods. Furthermore, by the end of the century, all simulations under the RCP 8.5 project a shift of streamflow and sediment loads in the southwest monsoon peak from May to June, while preserving the peak in the inter-monsoon 2 (in October). The projected changes in annual sediment loads are greater than the projected changes in annual streamflow (in percentage) for both future periods.

Impacts of Climate and Anthropogenic Activities on Streamflow Regimes in the Beiluo River, China

Quantitatively assessing the characteristics of river streamflow variation and conducting research on attribution identification are the basis for formulating climate-change response strategies and rational use of water resources. Based on the daily streamflow data of the Zhuangtou Hydrological Station in 1970–2018, this paper analyzes the streamflow changes in the Beiluo River Basin and studies the impact of climate change and anthropogenic activities on the streamflow in this basin. A non-parametric Mann–Kendall test and Pettitt’s test were used to determine the trend and detect abrupt changes of streamflow and baseflow. The method based on precipitation and potential evapotranspiration, as well as the double-mass curve of precipitation–streamflow, was established to evaluate the impact of climate change and non-climate factors on annual streamflow. The results reveal a statistically significant downward trend (p = 0.01) in both annual streamflow and baseflow, with the abrupt point year in 1994 and 1988, respectively. When comparing to a modest declining trend in annual average precipitation, we see that the temperature showed a significant upward trend (p = 0.01), whose abrupt point year was 1996. Under the policy of returning farmland to forest, land-use analysis shows that the area of farmland had decreased by 222.4 km2, of which 31.4% was mainly converted into the forestland. By the end of 2015, the area of forestland had increased by 123.4 km2, which has largely caused streamflow decrease. For the method based on precipitation and potential evapotranspiration, climate change contributed 43.7% of the annual streamflow change, and human activities (mainly refers to LUCC) contributed 56.3%. For the DMC of precipitation–streamflow, the precipitation contributed 9.4%, and non-precipitation factors (mainly refers to human activities) contributed 90.6%, and human activities played a more vital part in driving streamflow reduction in different decades, with a contribution rate of more than 70%. This study is of great practical significance to the planning, management, development and utilization of water resources in basins.

Exploring the Factors Affecting Streamflow Conditions in the Han River Basin from a Regional Perspective

Considerable attention has recently been focused on the impacts of climate change and human activities on river streamflow conditions. This study explored these effects using three hydrological modeling techniques such as multi-regression, a two-parameter hydrological model, and hydrological sensitivity analysis, followed by trend analysis and change point detection. The non-parametric Mann-Kendall test was used to analyze the trends in hydro-meteorological parameters. The non-parametric Pettitt test and double cumulative curve techniques were used to identify change points in annual streamflow series during 1978–2014. After determining the change point year to be 1997, the series were split into two parts: a pre-change (natural) period (1978–1997) and a post-change (human-induced) period (1998–2014). The hydrological models were calibrated and estimated for the pre-change (natural) period, which provided the relative change in annual streamflow for the post-change (human-induced) period. The contribution of climate variability ranged from 36.3% to 55.9%, and human activities accounted for 44.5% to 63.7% of streamflow variability. These results suggest that human activities are more impactful than climate variability. The outcomes of this study show that streamflow in the basin was influenced by climate variability, but human actions were also major driving forces in altering the streamflow.

Derivation of the relative contributions of the climate change and human activities to mean annual streamflow change

Both climate change and anthropogenic activities are known to induce streamflow change. It is important to understand how it works. Here we integrate the long-term water balance equation with the Budyko framework to analytically attribute the mean annual streamflow change to changes in precipitation and potential evapotranspiration caused by climate change, and to changes in watershed properties caused by anthropogenic activities. The attribution approach is applied to six sub-basins in Mekong River basin as a case study for attributing the decadal change in streamflow during 1960–2018 over the baseline (1960–1969). Results indicate that the observed streamflow decadal changes are mostly due to anthropogenic activities with some decadal contributions from changes in precipitation. The rapid rate of water infrastructure (e.g., dams) development has been reported there. The streamflow record and the attribution approach described here can be used to explicitly unravel the climatic and anthropogenic drivers of the hydrologic cycle.

Derivation of Interannual Climate Elasticity of Streamflow

AbstractBesides climate change (i.e., change on an average condition), streamflow change is also affected by interannual variability of climate (i.e., change from year to year). To quantify the impact of interannual climatic variability, in this study, we first clarify the content and definition of interannual climate elasticity that represents the sensitivity of streamflow to climatic variability from year to year and equals to the ratio of proportional annual change in streamflow and a climatic variable. Then, we analytically derive the interannual climate (i.e., potential evapotranspiration and precipitation) elasticities of streamflow by integrating the annual water balance with a conceptual hydrologic model (i.e., extended Budyko framework). At interannual scale, the terrestrial water storage change (i.e., ∆S) is a substantial component of water balance equation. Consequently, the analytical solutions of the interannual climate elasticities are functions of precipitation, potential evapotranspiration, and ∆S. The newly derived interannual climate elasticities are applied to 335 Model Parameter Estimation Experiment watersheds as a case study to evaluate the hypotheses in this study and construct the regional map of the streamflow sensitivity to interannual variability of climate. Results show that the interannual precipitation elasticity is generally larger than the absolute interannual potential evapotranspiration elasticity across study watersheds. Spatially, streamflow in the arid region tends to be more sensitive to interannual variability of climate than that in humid region. This study may be useful for understanding the extreme events and annual streamflow change caused by the ∆S (e.g., groundwater abstraction) across watersheds or regions.

Climate, Irrigation, and Land Cover Change Explain Streamflow Trends in Countries Bordering the Northeast Atlantic

AbstractAttribution of trends in streamflow is complex, but essential, in identifying optimal management options for water resources. Disagreement remains on the relative role of climate change and human factors, including water abstractions and land cover change, in driving change in annual streamflow. We construct a very dense network of gauging stations (n = 1,874) from Ireland, the United Kingdom, France, Spain, and Portugal for the period of 1961–2012 to detect and then attribute changes in annual streamflow. Using regression‐based techniques, we show that climate (precipitation and atmospheric evaporative demand) explains many of the observed trends in northwest Europe, while for southwest Europe human disturbances better explain both temporal and spatial trends. For the latter, large increases in irrigated areas, agricultural intensification, and natural revegetation of marginal lands are inferred to be the dominant drivers of decreases in streamflow.

Hydrologic alteration and possible underlying causes in the Wuding River, China

Understanding hydrological alteration of rivers and the potential driving factors are crucial for water resources management in the watershed. This study analyzed the daily runoff time series at six gauging stations during 1960–2016 in Wuding River basin, northwestern China. The Mann–Kendall test and Lee-Heghinian method were employed to detect the temporal trends and abrupt changes in annual streamflow. The flow duration curve (FDC) and the index of hydrologic alteration (IHA)/Range of Variability Approach (RVA) were applied to assess the daily streamflow and degree of hydrologic alteration (DHA). In addition, we analyzed the changes of index of hydrological connectivity (IC) and reservoirs/dams (RI) in 1990, 1995, 2000 and 2015 in the basin. The relationship between IC, RI and DHA were assessed to investigate the potential influences of land use changes and constructions of reservoirs/dams on hydrological alteration. The results indicated that annual streamflow at five stations showed significant downward trends (p < 0.01) from 1960 to 2016, and an abrupt changing point appeared in the beginning of 1970s in Wuding River basin. Exception is Qingyangcha station without significant changes, and Hanjiamao station with changing point in 1967. FDC analysis indicated that both high and low flow indices reduced greatly. The integral DHA were higher than 70% at all the stations in the Wuding River basin, suggesting great variation in the magnitude, duration, frequency, timing and rate of change of daily streamflow. Both IC value and RI had close relationship with DHA, implying that DHA was highly affected by land use changes and dams/reservoirs constructions, and was more sensitive to the land use change (p < 0.01). This study provides good insight to understand the effects of soil and water conservation measures on hydrological regime.

Contribution of climatic variability and human activities to stream flow changes in the Haraz River basin, northern Iran

In northern Iran’s Haraz River basin between 1975 and 2010, hydrological sensitivity, double mass curve, and Soil and Water Assessment Tool (SWAT) methods were applied to monitoring and analysing changes in stream flow brought on by climatic variability and human activities. Applied to analyse trends in annual and seasonal runoff over this period, the sequential MK test showed a sudden change point in stream flow in 1994. The study period was, therefore, divided into two sub-periods: 1975–1994 and 1995–2010. The SWAT model showed obvious changes in water resource components between the two periods: in comparison to the period of 1975–1994, sub-watershed-scale stream flow and soil moisture decreased during 1995–2010. Changes in evapotranspiration were negligible compared to those in stream flow and soil moisture. The hydrological sensitivity method indicated that climatic variability and human activities contributed to 29.86% and 70.14%, respectively, of changes in annual stream flow, while the SWAT model placed these contributions at 34.78% and 65.21%, respectively. The double mass curve method indicated the contribution of climatic variability to stream flow changes to be 57.5% for the wet season and 22.87% for the dry season, while human activities contributed 42.5% and 77.13%, respectively. Accordingly, in the face of climatic variability, measures should be developed and implemented to mitigate its impacts and maintain eco-environmental integrity and water supplies.

Partitioning climate and human contributions to changes in mean annual streamflow based on the Budyko complementary relationship in the Loess Plateau, China

Reliable attribution of changes in streamflow is fundamental to our understanding of the hydrological cycle and is needed to enable decision makers to manage water resources in a sustainable way. Here, we used a new attribution method based on the Budyko framework (complementary method) to quantify the contributions of climate change and human activities to the changes in annual streamflow in 22 catchments on China's Loess Plateau during the past three decades. Our results showed that after the Grain-for-Green (GFG) project, the annual streamflow decreased by 36% on average (3–72%), with reductions being more intense in northern catchments. The sensitivity of streamflow to precipitation and potential evapotranspiration also decreased, with a mean rate of −0.7 mm yr−1/mm yr−1 and −0.2 mm yr−1/mm yr−1, respectively. Using the upper and lower bounds of the human effects on streamflow from the complementary method as a reference, we found that these effects at half of the stations were under- or over-estimated by the total differential method. The contribution analysis from the complementary method showed that although human activities decreased streamflow by 26% (or 54% as a relative value) on average, the contribution of potential evapotranspiration alone to the decrease in streamflow was 9% (42%), highlighting the important role of increasing atmospheric moisture demand in the water cycle. In addition, the 5-year incremental analysis showed that the impacts of climate and human activities on streamflow had strong spatiotemporal variability.

Hydrological response to future land-use change and climate change in a tropical catchment

ABSTRACTHydrological response to expected future changes in land use and climate in the Samin catchment (278 km2) in Java, Indonesia, was simulated using the Soil and Water Assessment Tool model. We analysed changes between the baseline period 1983–2005 and the future period 2030–2050 under both land-use change and climate change. We used the outputs of a bias-corrected regional climate model and six global climate models to include climate model uncertainty. The results show that land-use change and climate change individually will cause changes in the water balance components, but that more pronounced changes are expected if the drivers are combined, in particular for changes in annual streamflow and surface runoff. The findings of this study will be useful for water resource managers to mitigate future risks associated with land-use and climate changes in the study catchment.

Streamflow response under different climate change scenarios in data-scarce White Volta basin of West-Africa using a semi-distributed hydrologic model

In this study, streamflow response in White Volta basin of West Africa was evaluated using ECHAM5 (MPEH5) GCM for two IPCC climate change scenarios (A1B and B1) and semi-distributed hydrologic model (SWAT) for three future time periods; 2020s, 2050s and 2080s using 1987-1996 as baseline. Both climate change scenarios project decrease in rainfall in 2020s but increases in 2050s and 2080s. Decrease in rainfall in 2020s was higher in B1 scenario compared to A1B; whereas for 2050s and 2080s, increases in rainfall were higher in A1B scenario than B1. Projected average changes indicate that overall the climate will be warmer and wetter in future. Projected annual streamflow volumes show disproportionate change (~220%) in response to slight changes in mean annual rainfall. Streamflow volume shows sharp changes for A1B scenario than B1 in 2020s whilst in 2050s and 2080s, the changes are moderate. Projected average annual streamflow changes are -3.1% in 2020s, 5.1% in 2050s and 13.3% in 2080s. Overall projected streamflow changes for both A1B and B1 scenarios were not so dramatic (less than ±20%). These call for adaptation strategies to reduce vulnerability and ensure water security within the basin.

Assessment of potential impact of climate change on streamflow: a case study of the Brahmani River basin, India

AbstractThe impact of future climate change on streamflow in the Brahmani River basin, India has been assessed using a distributed parameter hydrological model Precipitation Runoff Modelling System (PRMS) and multi-model ensemble climate change scenarios. The multi-model ensemble climate change scenarios were generated using the Hybrid-Delta ensemble method for A2, A1B, and B1 emission scenarios for three different future periods of the 2020s (2010–2039), 2050s (2040–2069) and 2080s (2070–2099). There is an increase in annual mean temperature in the range of 0.8–1.0, 1.5–2.0 and 2.0–3.3 °C during the 2020s, 2050s, and 2080s, respectively. Annual rainfall is projected to change in the range of −1.6–1.6, 1.6–3.1, and 4.8–8.1% during the 2020s, 2050s and 2080s, respectively. Simulation results indicated changes in annual streamflow in the range of −2.2–2.5, 2.4–4.7, and 7.3–12.6% during the 2020s, 2050s, and 2080s, respectively. Simulation results showed an increase in high flows and reduction in low flows, but the frequency of both high and low flow increases during future periods. The results of this work will be useful in developing a water management adaptation plan in the study basin.