The impact of water infrastructure and climate change on the hydrology of the Upper Ganges River Basin

حوضه آجی­چای یکی از بزرگترین مناطق کشاورزی و مصرف آب در حوضه دریاچه ارومیه است که در سال­های اخیر به دلیل اثرات تغییر اقلیم و عوامل انسانی، کارکرد خود در تأمین حق­آبه دریاچه ارومیه را از دست داده است. از این­رو هدف مطالعه حاضر، بررسی اثرات سناریوهای اقلیمی و سناریوهای مدیریت منابع آب بر مقدار آب در دسترس، نیاز آبی گیاهان، الگوی کشت، عملکرد و سود کشاورزان در شهرستان سراب به عنوان یکی از سرشاخه­های اصلی آجی چای می­باشد. بدین منظور از مدل هیدرو- اقتصادی مبتنی بر ریسک بهره­ گرفته شد که در بخش اقتصادی از مدل برنامه­ریزی ریاضی درجه دوم توأم با ریسک و در بخش هیدرولوژیکی از مدل WEAP-MABIA استفاده گردید. داده­های مورد نیاز از تکمیل 210 پرسشنامه از کشاورزان در سال 1397 جمع­آوری گردید. برای تولید داده­های روزانه اقلیمی از مدل HadCM3 و ریزمقیاس­سازی LARS-WG تحت سناریوی­ها انتشار A2، B1 و A1B استفاده شد. نتایج نشان داد که تغییر اقلیم باعث کاهش سود و اشتغال بخش کشاورزی شده و الگوی کشت به سمت محصولات با نیاز آبی پایین تغییر خواهد یافت. اعمال سناریوی افزایش راندمان آبیاری علاوه بر استفاده مفید و موثرتر از آب تخصیصی، سود کشاورزان را نیز افزایش خواهد داد که نسبت به سناریو کاهش سهم آب کشاورزی وضعیت مطلوبتری را ارائه می­دهد. در مجموع نتایج این مطالعه بیانگر آن است که در صورت ثابت ماندن روش­های مدیریتی در آینده­ی نزدیک، عملکرد محصولات کاهش چشمگیری خواهد یافت. از این­رو بهینه­سازی روش­های مدیریتی و استفاده از ارقام با عملکرد بالاتر به­ عنوان راهکارهای مقابله با اثرات تغییر اقلیم توصیه می­شود.

Introduction: Forecasting the inflow to the reservoir is important issues due to the limited water resources and the importance of optimal utilization of reservoirs to meet the need for drinking, industry and agriculture in future time periods. In the meantime, ignoring the effects of climate change on meteorological and hydrological parameters and water resources in long-term planning of water resources cause inaccuracy. It is essential to assess the impact of climate change on reservoir operation in arid regions. In this research, climate change impact on hydrological and meteorological variables of the Shahcheragh dam basin, in Semnan Province, was studied using an integrated model of climate change assessment. Materials and Methods: The case study area of this study was located in Damghan Township, Semnan Province, Iran. It is an arid zone. The case study area is a part of the Iran Central Desert. The basin is in 12 km north of the Damghan City and between 53° E to 54° 30’ E longitude and 36° N to 36° 30’ N latitude. The area of the basin is 1,373 km2 with average annual inflow around 17.9 MCM. Total actual evaporation and average annual rainfall are 1,986 mm and 137 mm, respectively. This case study is chosen to test proposed framework for assessment of climate change impact hydrological and meteorological variables of the basin. In the proposed model, LARS-WG and ANN sub-models (7 sub models with a combination of different inputs such as temperature, precipitation and also solar radiation) were used for downscaling daily outputs of CGCM3 model under 3 emission scenarios, A2, B1 and A1B and reservoir inflow simulation, respectively. LARS-WG was tested in 99% confidence level before using it as downscaling model and feed-forward neural network was used as raifall-runoff model. Moreover, the base period data (BPD), 1990-2008, were used for calibration. Finally, reservoir inflow was simulated for future period data (FPD) of 2015-2044 and compared to BPD. The best ANN sub-model has minimum Mean Absolute Relative Error (MARE) index (0.27 in test phases) and maximum correlation coefficient (ρ) (0.82 in test phases). Results and Discussion: The tested climate change scenarios revealed that climate change has more impact on rainfall and temperature than solar radiation. The utmost growth of monthly rainfall occurred in May under all the three tested climate change scenarios. But, rainfall under A1B scenario had the maximum growth (52%) whereas the most decrease occurred (–21.5%) during January under the A2 climate change scenario. Rainfall dropped over the period of June to October under the three tested climate change scenarios. Furthermore, in all three scenarios, the maximum temperature increased about 2.2 to 2.6°C in May but the lowest increase of temperature occurred in January under A2 and B1 scenarios as 0.3 and 0.5°C, respectively. The maximum temperature usually increased in all months compared to the baseline period. Minimum and maximum temperatures enlarged likewise in all months, with 2.05°C in September under A2 climate change scenario. Conversely, solar radiation change was comparatively low and the most decreases occurred in February under A1B and A2 climate change scenarios as –4.2% and –4.3% , respectively, and in August under the B1 scenario as –4.2%. The greatest increase of solar radiation occurs in April, November, and March by 3.1%, 3.2%, and 4.9% for A1B, A2, and B1 scenarios, respectively. The impact of climate change on rainfall and temperature can origin changes on reservoir inflow and need new strategies to adapt reservoir operation for change inflows. Therefore, first, reservoir inflow in future period (after climate change impact) should be anticipated for the adaptation of the reservoir. A Feed-Forward (FF) Multilayer-Perceptron (MLP) Artificial Neural Network (ANN) model was nominated for the seven tested ANN models based on minimization of error function. The selected model had 12 neurons in the hidden layer, and two delays. The comparison of forecasted flow hydrograph by selecting an ANN model and observed one proved that forecasted flow hydrograph can follow observed one closely. By comparison with the IHACRES model, this model displayed a 54% and 46% lower error functions for validation data. The selected model was used to forecast flow for the climate change scenarios of the future period. Conclusions: The results show a reduction of monthly flow in most months and annual flow in all studied scenarios. The following main points can be concluded: • By climate change, flow growths in dry years and it declines in wet and normal years. • The studied climate change scenarios showed that climate change has more impact on rainfall and temperature than solar radiation.

With the continuing warming due to greenhouse gases concentration, it is important to examine the potential impacts on regional crop production spatially and temporally. We assessed China’s potential maize production at 50 × 50 km grid scale under climate change scenarios using modelling approach. Two climate changes scenarios (A2 and B2) and three time slices (2011–2040, 2041–2070, 2071–2100) produced by the PRECIS Regional Climate Model were used. Rain-fed and irrigated maize yields were simulated with the CERES-Maize model, with present optimum management practices. The model was run for 30 years of baseline climate and three time slices for the two climate change scenarios, without and with simulation of direct CO2 fertilization effects. Crop simulation results under climate change scenarios varied considerably between regions and years. Without the CO2 fertilization effect, China’s maize production was predicted to suffer a negative effect under both A2 and B2 scenarios for all time slices, with greatest production decreases in today’s major maize planting areas. When the CO2 fertilization effect is taken into account, production was predicted to increase for rain-fed maize but decrease for irrigated maize, under both A2 and B2 scenarios for most time periods.

The goal of this study is to take the self-adaption of rice production in future into consideration in the climate change impact studies, to enhance its rationality. The first step we did was to classify Fujian Province into three rice regions according to the topographic features and rice-based cropping systems. Altogether 17 sites and 9 representative rice varieties with different maturity types were selected to conduct the simulation experiments. The second step, to generate climate change scenarios in two periods (1961-1990 and 2021-2050), based on three emission schemes (A2, B2, and A1B) in IPCC Special Report (SRES), combined with the Regional Climate Model of PRECIS. The third step to run CERES-Rice model under the three climate change scenarios to simulate the influence of future climate change on rice production in Fujian Province, without considering the self-adaption of rice production. The direct effects of CO2 enrichment on photosynthesis and transpirations were also included. The forth step, to assess the possible change in rice-based cropping system, varietal type as well as sowing date in future in the studied area, based on the simulated results and some climatic indices, and these changes could be regarded as the results of self-adaption adjustment in future. The fifth step, to run CERES-Rice model again under the three climate change scenarios using the possible cropping systems, varietal types and sowing dates after self-adaption adjustment. Finally, to assess change in rice yield, yield stability in different rice regions and the overall output of rice in the province in future with considering the self-adaption adjustment. The results indicated that the simulated yields of early rice in the Double Rice Region in southeastern Fujian under A2, B2, and A1B scenarios increase by 15.9%, 18.0%, and 19.2% and that of late rice increase respectively by 9.2%, 7.4%, and 7.4% when the self-adaption adjustment was considered, compared without consideration. In the Double Rice Region in Northwestern Fujian, the simulated yields of early rice increase by 21.2%, 20.5%, 18.9% and that of late rice increase respectively by 14.7%, 14.8%, and 7.2% under the three climate change scenarios when the self-adaption was considered, compared with without consideration. Similar results could be obtained in the Single Rice Region in the mountain areas of Northwestern Fujian. The simulated yields of single rice increase respectively by 4.9%, 5.0%, and 2.9% under the three scenarios, comparing the two cases with and without consideration of self-adaption. In this rice region, double rice might be grown in future in the site of Changting under the A1 and B2 scenarios. When the self-adaption adjustment was considered, the overall output of rice crop in Fujian Province under the three climate change scenarios would increase by 5.9%, 5.2%, and 5.1%, respectively. It is concluded that more optimistic results could be obtained when self-adaption ability of food production was taken into consideration.

The goal of this study is to take the self-adaption of rice production in future into consideration in the climate change impact studies, to enhance its rationality. The first step we did was to classify Fujian Province into three rice regions according to the topographic features and rice-based cropping systems. Altogether 17 sites and 9 representative rice varieties with different maturity types were selected to conduct the simulation experiments. The second step, to generate climate change scenarios in two periods (1961-1990 and 2021-2050), based on three emission schemes (A2, B2, and A1B) in IPCC Special Report (SRES), combined with the Regional Climate Model of PRECIS. The third step to run CERES-Rice model under the three climate change scenarios to simulate the influence of future climate change on rice production in Fujian Province, without considering the self-adaption of rice production. The direct effects of CO2 enrichment on photosynthesis and transpirations were also included. The forth step, to assess the possible change in rice-based cropping system, varietal type as well as sowing date in future in the studied area, based on the simulated results and some climatic indices, and these changes could be regarded as the results of self-adaption adjustment in future. The fifth step, to run CERES-Rice model again under the three climate change scenarios using the possible cropping systems, varietal types and sowing dates after self-adaption adjustment. Finally, to assess change in rice yield, yield stability in different rice regions and the overall output of rice in the province in future with considering the self-adaption adjustment. The results indicated that the simulated yields of early rice in the Double Rice Region in southeastern Fujian under A2, B2, and A1B scenarios increase by 15.9%, 18.0%, and 19.2% and that of late rice increase respectively by 9.2%, 7.4%, and 7.4% when the self-adaption adjustment was considered, compared without consideration. In the Double Rice Region in Northwestern Fujian, the simulated yields of early rice increase by 21.2%, 20.5%, 18.9% and that of late rice increase respectively by 14.7%, 14.8%, and 7.2% under the three climate change scenarios when the self-adaption was considered, compared with without consideration. Similar results could be obtained in the Single Rice Region in the mountain areas of Northwestern Fujian. The simulated yields of single rice increase respectively by 4.9%, 5.0%, and 2.9% under the three scenarios, comparing the two cases with and without consideration of self-adaption. In this rice region, double rice might be grown in future in the site of Changting under the A1 and B2 scenarios. When the self-adaption adjustment was considered, the overall output of rice crop in Fujian Province under the three climate change scenarios would increase by 5.9%, 5.2%, and 5.1%, respectively. It is concluded that more optimistic results could be obtained when self-adaption ability of food production was taken into consideration.

Global climate changes caused by increased atmospheric concentrations of carbon dioxide (CO 2 ) and other greenhouse gases will change patterns of water yield. Increases in CO 2 affect water yield through changes in temperature, precipitation, runoff, and evapotranspiration (ET). The Soil and Water Assessment Tool (SWAT) was applied to five watersheds in the Missouri River basin with different types of land cover to study the hydrologic responses under doubled CO 2 and climate change. The high-resolution climate change scenario developed from the National Center for Atmosphere Research (NCAR) Regional Climate Model (RegCM) was used to provide the climate change scenario. Sensitivity analysis was performed to study the effect of increased leaf area index on ET. Results showed that ET decreased 2–11% and water yield increased 9–34% under a simple doubled CO 2 scenario for the different land cover watersheds. When climate change were added, ET increased significantly compared to the doubled CO 2 simulation due the effects of increased temperature, solar radiation, and other climatic variables. Some sub-basins even show larger ET than that of baseline simulation. Water yield increased dramatically under climate change due to significant increases in precipitation. The sensitivity analysis on leaf area index showed no significant change to ET and water yield.

The Mekong Basin is threatened by accelerated hydropower development and extreme events from climate change. The transboundary Srepok, Sesan, and Sekong (3S) basins contribute the largest discharge of Mekong River’s tributaries, providing critical ecosystem services to the Tonle Sap and the Mekong delta downstream, including sediments, biodiversity, and fish production. This study aims to assess the potential impact of climate change and hydropower development scenarios on flow patterns and hydropower production in the 3S through multi-general circulation models (GCMs), hydrological simulations, and reservoir operation models. Full hydropower development coupled with energy-focused operations will increase dry season flows by 96 % and reduce wet season flows by 25 % at the basin outlet as compared to historical baseline conditions. Climate change is likely to decrease dry season flows by 6–24 %, but projections of wet season and annual flows using different climate change scenarios and GCMs are relatively uncertain. Energy production in the 3S is not likely to be affected substantially by climate-driven changes in flows; only minor changes resulting from either A2 and B2 climate change scenarios and different GCMs. Predicted climate change, however, will result in significant changes in the magnitude and frequency of extreme flood events, which will undoubtedly impact on future dam design and operation rules. Coordination of hydropower operations within the 3S basin will be critical to maximise development benefits within the basin and reduce negative environmental impacts at the local, national, and transboundary levels.

The climate impact studies in hydrology often rely on climate change information at fine spatial resolution. However, the general circulation model (GCM), which is widely used to simulate future climate scenario, operates on a coarse scale and does not provide reliable data on local or regional scale for hydrological modeling. Therefore the outputs from GCM have to be downscaled to obtain the information fit for hydrologic studies. The variable infiltration capacity (VIC) distributed hydrological model with 9×9 km2 grid resolution was applied and calibrated in the Hanjiang Basin. Validation results show that SSVM can approximate observed precipitation and temperature data reasonably well, and that the VIC model can simulate runoff hydrograph with high model efficiency and low relative error. By applying the SSVM model, the trends of precipitation and temperature (including daily mean temperature, daily maximum temperature and daily minimum temperature) projected from CGCM2 under A2 and B2 scenarios will decrease in the 2020s (2011–2040), and increase in the 2080s (2071–2100). However, in the 2050s (2041–2070), the precipitation will be decreased under A2 scenario and no significant changes under B2 scenario, but the temperature will be not obviously changed under both climate change scenarios. Under both climate change scenarios, the impact analysis of runoff, made with the downscaled precipitation and temperature time series as input of the VIC distributed model, has resulted in a decreasing trend for the 2020s and 2050s, and an overall increasing trend for the 2080s.

This study aimed to assess the differences in modelling disaster risks results when using historical precipitation and when using simulated precipitation associated with future Intergovernmental Panel on Climate Change (IPCC) climate scenarios. Subsequently, the relationship between climate change and climate hazards was analyzed in this study. The secondary data analyzed included historical precipitation (1983-2017), flood and landslide events records, and Providing Regional Climates for Impacts Studies (PRECIS) regional climate model (RCM):A1B, A2 and B2 scenarios. By comparing the historical precipitation data with the RCM scenarios, the results showed that the precipitation was correlated with A1B scenario (r= 0.695). The relationship between climate change and hazards was identified to be a positive correlation. The historical daily precipitation (1983-2017) showed a positive correlation with flood and landslide events (r= 0.530, r = 0.797, respectively). As for prediction of climate hazards, the RCM A1B, A2 and B2 scenarios showed correlations with flood event: r= 0.648, 0.384 and 0.417, respectively. Similar results were obtained for landslide and the RCM A1B, A2 and B2 scenario: r = 0.498, 0.751 and 0.654, respectively. Precipitation simulation by PRECIS RCM indicated increased levels of precipitation in the Cameron Highlands for the 2018 - 2069. Commensurate with this, great possibility of increasingly serious consequential hazards such as flood and landslide events are expected.

Projecting staple crop production including wheat under future climate plays a fundamental role in planning the required adaptation and mitigation strategies for climate change effects especially in developing countries. The main aim of this study was to investigate the direction and magnitude of climate change impacts on grain yield of rainfed wheat (Triticum aestivum L.) production and precipitation within growing season. This study was performed for various regions in Khorasan province which is located in northeast of Iran. Climate projections of two General Circulation Models (GCM) for four locations under three climate change scenarios were employed in this study for different future time periods. A stochastic weather generator (LARS-WG5) was used for downscaling to generate daily climate parameters from GCMs output. The Decision Support System for Agrotechnology Transfer (DSSAT) Version 4.5 was employed to evaluate rainfed wheat performance under future climate. Grain yield of rainfed wheat and precipitation during growth period considerably decreased under different scenarios in various time periods in contrast to baseline. Highest grain yield and precipitation during growth period was obtained under B1 scenario but A1B and A2 scenarios resulted in sharp decrease (by −57 %) of grain yield. Climate change did not have marked effects on evapotranspiration during the rainfed wheat growth. A significant correlation was detected between grain yield, precipitation and evapotranspiration under climate change for both GCMs and under all study scenarios. It was concluded, that rainfed wheat production may decline during the next 80 years especially under A2 scenario. Therefore, planning the comprehensive adaptation and mitigation program is necessary for avoiding climate change negative impact on rainfed wheat production.

The combined effect of urbanization and climate change on catchment runoff has been drawing attention in the recent years to assess the impact of climate change on urbanizing catchments. There has been extensive development of paved areas within the city of Turnhout in Belgium in combination with several modifications of the neighbouring rivers. Moreover, the city authority has decided to encourage more densification of housing and industries within or next to the cores, which would lead to frequent overflows out of the existing combined sewer system. This combination leads to a faster flow of larger quantities of water which physically cannot be retained by the valleys over this region and thus causes increasingly frequent and harmful flood events affecting agricultural lands. The situation could be indisputably exacerbated under climate change scenarios. This study focuses on assessing the effects of urban development and climate change on flood risks in the downstream of Turnhout. For this study, a lumped conceptual hydrological model NAM was developed for generating runoff from the catchment. The CCI-HYDR perturbation tool, developed by Katholieke Universiteit Leuven, was applied to generate time series of future rainfall and evapotranspiration. The urban runoffs were obtained from the simulation of existing InfoWorks CS model under both current and climate change (A1B, A2, B1 and B2) scenarios. Rainfall-runoff was then uniformly distributed along the river reaches and urban runoff was applied as point source boundary conditions in the calibrated and validated MIKE 11 river flood model. Composite hydrographs with different return periods for all the boundary conditions were generated through extreme value analysis. The results show intensified and more frequent peak runoff resulting from combined effect of urbanization and climate change, in comparison to the individual effect of urbanization or climate change each. The increased peak runoff in the river due to heavy rainfall coinciding with development of paved surfaces within the city would lead to severe urban flooding when urbanization and climate change scenarios are accounted for.

Downscaling climate change scenarios in an urban land use change model

The study highlights the potential characteristics of droughts under future climate change scenarios. For this purpose, the changes in Standardized Precipitation Evapotranspiration Index (SPEI) under the A1B, A2, and B1 climate change scenarios in Iran were assessed. The daily weather data of 30 synoptic stations from 1992 to 2010 were analyzed. The HadCM3 statistical model in the LARS-WG was used to predict the future weather conditions between 2011 and 2112, for three 34-year periods; 2011-2045, 2046-2079, and 2080-2112. In regard to the findings, the upward trend of the potential evapotranspiration in parallel with the downward trend of the precipitation in the next 102 years in three scenarios to the base timescale was transparent. The frequency of the SPEI in the base month indicated that 17.02% of the studied months faced the drought. Considering the scenarios of climate change for three 34-year periods (i.e., 2011-2045, 2046-2079, and 2080-2112) the average percentages of potential drought occurrences for all the stations in the next three periods will be 8.89, 16.58, and 27.27 respectively under the B1 scenario. While the predicted values under the A1B scenario are 7.63, 12.66, and 35.08%respectively. The relevant findings under the A2 scenario are 6.73, 10.16, 40.8%. As a consequence, water shortage would be more serious in the third period of study under all three scenarios. The percentage of drought occurrence in the future years under the A2, B1, and A1B will be 19.23%, 17.74%, and 18.84%, respectively which confirms the worst condition under the A2 scenario. For all stations, the number of months with moderate drought was substantially more than severe and extreme droughts. Considering the A2 scenario as a high emission scenario, the analysis of SPEI frequency illustrated that the proportion of dry periods in regions with humid and cool climate is more than hot and warm climates; however, the duration of dry periods in warmer climates is longer than colder climates. Moreover, the temporal distribution of precipitation and potential evapotranspiration indicated that in a large number of stations, there is a significant difference between them in the middle months of the year, which justifies the importance of prudent water management in warm months.

This paper examines changes in the surface area of glaciers in the North and South Chuya Ridges, Altai Mountains in 1952–2004 and their links with regional climatic variations. The glacier surface areas for 2004 were derived from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery. Data from the World Glacier Inventory (WGI) dating to 1952 and aerial photographs from 1952 were used to estimate the changes. 256 glaciers with a combined area of 253 ± 5.1 km2 have been identified in the region in 2004. Estimation of changes in extent of 126 glaciers with the individual areas not less than 0.5 km2 in 1952 revealed a 19.7 ± 5.8% reduction. The observed glacier retreat is primarily driven by an increase in summer temperatures since the 1980s when air temperatures were increasing at a rate of 0.10–0.13°C a−1 at the glacier tongue elevation. The regional climate projections for A2 and B2 CO2 emission scenarios developed using PRECIS regional climate model indicate that summer temperatures will increase in the Altai in 2071–2100 by 6–7°C and 3–5°C respectively in comparison with 1961–1990 while annual precipitation will increase by 15% and 5%. The length of the ablation season will extend from June–August to the late April–early October. The projected increases in precipitation will not compensate for the projected warming and glaciers will continue to retreat in the 21st century under both B2 and A2 scenarios.

Impact assessments on climate change are essential for the evaluation and management of irrigation water in farming practices in semi-arid environments. This study was conducted to evaluate climate change impacts on water productivity of maize in farming practices in the Lower Chenab Canal (LCC) system. Two fields of maize were selected and monitored to calibrate and validate the model. A water productivity analysis was performed using the Soil–Water–Atmosphere–Plant (SWAP) model. Baseline climate data (1980–2010) for the study site were acquired from the weather observatory of the Pakistan Meteorological Department (PMD). Future climate change data were acquired from the Hadley Climate model version 3 (HadCM3). Statistical downscaling was performed using the Statistical Downscaling Model (SDSM) for the A2 and B2 scenarios of HadCM3. The water productivity assessment was performed for the midcentury (2040–2069) scenario. The maximum increase in the average maximum temperature (Tmax) and minimum temperature (Tmin) was found in the month of July under the A2 and B2 scenarios. The scenarios show a projected increase of 2.8 °C for Tmax and 3.2 °C for Tmin under A2 as well as 2.7 °C for Tmax and 3.2 °C for Tmin under B2 for the midcentury. Similarly, climate change scenarios showed that temperature is projected to decrease, with the average minimum and maximum temperatures of 7.4 and 6.4 °C under the A2 scenario and 7.7 and 6.8 °C under the B2 scenario in the middle of the century, respectively. However, the highest precipitation will decrease by 56 mm under the A2 and B2 scenarios in the middle of the century for the month of September. The input and output data of the SWAP model were processed in R programming for the easy working of the model. The negative impact of climate change was found under the A2 and B2 scenarios during the midcentury. The maximum decreases in Potential Water Productivity (WPET) and Actual Water Productivity (WPAI) from the baseline period to the midcentury scenario of 1.1 to 0.85 kgm−3 and 0.7 to 0.56 kgm−3 were found under the B2 scenario. Evaluation of irrigation practices directs the water managers in making suitable water management decisions for the improvement of water productivity in the changing climate.