Assessing Climate Change Impacts on Water Resources in the Songhua River Basin

The adaptability and irrigation constraints analysis of the WOFOST model for grain production in the Songhua River Basin

BACKGROUND

The Songhua River Basin, a vital grain-producing area in China, faces challenges due to the uneven distribution of water resources and the intensive water demands of agriculture. To enhance agricultural development and effectively manage water scarcity, it is essential to identify the water-saving potential of major staple crops - corn, wheat, and rice. This study enhances the World Food Studies (WOFOST) model by refining the day of year for the developmental vegetative stage (DVS), thereby improving the representation of phenological stages for spring maize, spring wheat, and rice within the model. This refinement offers a detailed analysis of the potential and rainfed yields.

RESULTS

The results from the modified WOFOST model show promising simulation outcomes for the biomass and yield of maize, wheat, and rice, with Nash-Sutcliffe efficiency (NS) and index of agreement (IoA) values all exceeding 0.7. An analysis of photothermal potential yields (Yp) and rainfed yields (Yr) revealed minimal differences in yields for spring maize and rice across various rainfall frequencies. Specifically, the average photothermal utilization rates (LTs) are 93.57% for maize and 85.25% for rice. In contrast, the rainfed yield for wheat is lower than its photothermal yield, with an LT of 43.66%.

CONCLUSIONS

These findings suggest that in the Songhua River Basin, maize and rice offer greater potential for water conservation compared to wheat. It is recommended to judiciously reduce irrigation during the growing seasons of spring maize and rice to help alleviate agricultural water use pressures. © 2024 Society of Chemical Industry.

Optimal Planning and Management of Land Use in River Source Region: A Case Study of Songhua River Basin, China

Adjusting land use is a practical way to protect the ecosystem, but protecting water resources by optimizing land use is indirect and complex. The vegetation, soil, and rock affected by land use are important components of forming the water cycle and obtaining clean water sources. The focus of this study is to discuss how to optimize the demands and spatial patterns of different land use types to strengthen ecological and water resources protection more effectively. This study can also provide feasible watershed planning and policy suggestions for managers, which is conducive to the integrity of the river ecosystem and the sustainability of water resources. A watershed-scale land use planning framework integrating a hydrological model and a land use model is established. After quantifying the water retention value of land use types through a hydrological model, a multi-objective land use demands optimization model under various development scenarios is constructed. Moreover, a regional study was completed in the source area of the Songhua River in Northeast China to verify the feasibility of the framework. The results show that the method can be used to optimize land use requirements and obtain future land use maps. The water retention capacity of forestland is strong, about 2500–3000 m³/ha, and there are differences among different forest types. Planning with a single objective of economic development will expand the area of cities and cultivated land, and occupy forests, while multi-objective planning considering ecological and water source protection tends to occupy cultivated land. In the management of river headwaters, it is necessary to establish important forest reserves and strengthen the maintenance of restoration forests. Blindly expanding forest area is not an effective way to protect river headwaters. In conclusion, multi-objective land use planning can effectively balance economic development and water resources protection, and find the limits of urban expansion and key areas of ecological barriers.

Altitudinal Gradient Characteristics of Spatial and Temporal Variations of Snowpack in the Changbai Mountain and Their Response to Climate Change

The variations in the snowpack in water towers of the world due to climate change have threatened the amount and timing of freshwater supplied downstream. However, it remains to be further investigated whether snowpack variation in water towers exhibits elevational heterogeneity at different altitude gradients and which climatic factors mainly influence these differences. Therefore, Changbai Mountain, a high-latitude water tower, was selected to analyze the changes in the snowpack by the methods of modified Mann–Kendall based on the daily meteorological data from the China Meteorological Data Service Centre. Meanwhile, the responses of snowpack change to climatic factors over recent decades were assessed and generalized using additive models. The results showed that the snow depth was greater in the higher altitude areas than in the lower elevation areas at different times. Areas with a snow depth of over 70 mm increased significantly in the 2010s. Increasing trends were shown at different altitudes from December to March of the next year during 1960~2018. However, a significant decreasing trend was shown in April, except for altitudes of 600–2378 m. The snow cover time at different altitudes showed a trend of first increasing and then decreasing during 1960~2018. The date of maximum snow depth appears to be more lagged as the altitude increases. In addition, the spring snowpack melted significantly faster in the 2010s than that in the 1960s. The snowpack variation in low-altitude regions is mainly influenced by ET and relative humidity. However, the mean temperature gradually became an important factor, affecting the snow depth variation with the increase in altitude. Therefore, the results of this study will be beneficial to the ecological protection and sustainable development of water towers.

Appraising climate change impacts on future water resources and agricultural productivity in agro-urban river basins

Climate change can have an adverse effect on agricultural productivity and water availability in semi-arid regions, as changes in surface water availability lead to groundwater depletion and resultant losses in crop yield. These inter-relationships necessitate an integrated management approach for surface water, groundwater, and crop yield as a holistic system. This study quantifies the future availability of surface water and groundwater and associated crop production in a large semi-arid agro-urban river basin in which agricultural irrigation is a leader consumer of water. The region of study is the South Platte River Basin (72,000 km²), Colorado, USA. The coupled SWAT-MODFLOW modeling code is used as the hydrologic simulator and forced with five different CMIP5 climate models downscaled by Multivariate Adaptive Constructed Analogs (MACA), each for two climate scenarios, RCP4.5, and RCP8.5, for 1980-2100. The hydrologic model accounts for surface runoff, soil lateral flow, groundwater flow, groundwater-surface water interactions, irrigation from surface water and groundwater, and crop yield on a per-field basis. In all climate models and emission scenarios, an increase of 3 to 5 °C in annual average temperature is projected. Whereas, variation in the projected precipitation depends on topography and distances from mountains. Based on the results of this study, the worst-case climate model in the basin is IPSL-CM5A-MR-8.5. Under this climate scenario, for a 1 °C increase in temperature and the 1.3% reduction in annual precipitation, the basin will experience an 8.5% decrease in stream discharge, 2-5% decline in groundwater storage, and 11% reduction in crop yield. These results indicate the significant effect of climate change on water and food resources of a large river basin, pointing to the need for immediate implementation of conservation practices.

Projection of Future Drought Characteristics under Multiple Drought Indices

Drought is a natural phenomenon caused by the variability of climate. This study was conducted in the Songhua River Basin of China. The drought events were estimated by using the Reconnaissance Drought Index (RDI) and Standardized Precipitation Index (SPI) which are based on precipitation (P) and potential evapotranspiration (PET) data. Furthermore, drought characteristics were identified for the assessment of drought trends in the study area. Short term (3 months) and long term (12 months) projected meteorological droughts were identified by using these drought indices. Future climate precipitation and temperature time series data (2021–2099) of various Representative Concentration Pathways (RCPs) were estimated by using outputs of the Global Circulation Model downscaled with a statistical methodology. The results showed that RCP 4.5 have a greater number of moderate drought events as compared to RCP 2.6 and RCP 8.5. Moreover, it was also noted that RCP 8.5 (40 events) and RCP 4.5 (38 events) showed a higher number of severe droughts on 12-month drought analysis in the study area. A severe drought conditions projected between 2073 and 2076 with drought severity (DS-1.66) and drought intensity (DI-0.42) while extreme drying trends were projected between 2097 and 2099 with drought severity (DS-1.85) and drought intensity (DI-0.62). It was also observed that Precipitation Decile predicted a greater number of years under deficit conditions under RCP 2.6. Overall results revealed that more severe droughts are expected to occur during the late phase (2050–2099) by using RDI and SPI. A comparative analysis of 3- and 12-month drying trends showed that RDI is prevailing during the 12-month drought analysis while almost both drought indices (RDI and SPI) indicated same behavior of drought identification at 3-month drought analysis between 2021 and 2099 in the research area. The results of study will help to evaluate the risk of future drought in the study area and be beneficial for the researcher to make an appropriate mitigation strategy.

Evaluation of Climate Change Impact on Groundwater Recharge in Groundwater Regions in Taiwan

Climate change can directly or indirectly influence groundwater resources. The mechanisms of this influence are complex and not easily quantified. Understanding the effect of climate change on groundwater systems can help governments adopt suitable strategies for water resources. The baseflow concept can be used to relate climate conditions to groundwater systems for assessing the climate change impact on groundwater resources. This study applies the stable baseflow concept to the estimation of the groundwater recharge in ten groundwater regions in Taiwan, under historical and climate scenario conditions. The recharge rates at the main river gauge stations in the groundwater regions were assessed using historical data. Regression equations between rainfall and groundwater recharge quantities were developed for the ten groundwater regions. The assessment results can be used for recharge evaluation in Taiwan. The climate change estimation results show that climate change would increase groundwater recharge by 32.6% or decrease it by 28.9% on average under the climate scenarios, with respect to the baseline quantity in Taiwan. The impact of climate change on groundwater systems may be positive. This study proposes a method for assessing the impact of climate change on groundwater systems. The assessment results provide important information for strategy development in groundwater resources management.

Evaluating the effectiveness of the pollutant discharge permit program in China: A case study of the Nenjiang River Basin

China is continually seeking to improve river water quality. Implemented in 1996, the total pollutant load control system (TPLCS) is a regulatory strategy to reduce total pollutant loads, under which a Pollutant Discharge Permit (PDP) program tracks and regulates nutrient inputs from point source polluters. While this has been promising, the input-response relationship between discharge permits and water quality targets is largely unclear - especially in China's large and complex river basins. In response, this study involved a quantitative analysis method to combine the water quality targets of the 12th Five-Year Plan (2011-2015) with allocated PDPs in the Nenjiang River Basin, China. We demonstrated our approach by applying the Soil and Water Assessment Tool (SWAT) to the Nenjiang River Basin for hydrological and water quality simulation. Ammonia nitrogen (NH₃-N) was used as the primary water quality indicator. Modelling indicated that only one control section in the wider river basin did not achieve the water quality target, suggesting that the TPLCS is largely effective. The framework should be applied in other basins to study the effectiveness of PDP policies, advise further updates to the TPLCS, and ultimately aim to achieve freshwater quality targets nationally.

Study on the Optimization of Dry Land Irrigation Schedule in the Downstream Songhua River Basin Based on the SWAT Model

The optimization of irrigation schedules is of great significance for saving water resources and ensuring food security. For the downstream of the Songhua River Basin, the key growth stages of crops were determined by the coupling degree between the effective precipitation and crop water requirement and the sensitivity indexes of the crop water production function. A Soil and Water Assessment Tool (SWAT) model was used to simulate 16 irrigation schedules in different scenarios. Taking four factors into consideration, Analytic Hierarchy Process (AHP)-Gray Interconnect Degree Analysis (GIDA) was used to establish the optimal irrigation schedule. The results showed that the key growth stages of corn and soybean were vegetative, reproductive and pod formation, seed enlargement. Deficit treatments were beneficial to improving crop yield and WUE. The optimal schedules were: the corn was irrigated with four times in key growth stages, and the irrigation quota was 21 mm; irrigation occurred six times in both normal and dry year, with quotas of 84 mm and 134 mm, respectively; the soybean was filled with six times in key growth stages, and the irrigation quotas were 10 mm, 28 mm and 89 mm in wet, normal and dry year, respectively. The evaluation method of irrigation schedule provided a theoretical basis for agricultural management and planting in the basin.

Land Use Change Impacts on Hydrology in the Nenjiang River Basin, Northeast China

The objectives of this study were to assess land use changes and their hydrological impacts in the Nenjiang River Basin (NRB). The Soil and Water Assessment Tool (SWAT) model was employed to evaluate the impacts of land use changes. The Cellular Automata-Markov model was used to predict a land use map in 2038. Streamflow under each land use state was simulated by the SWAT model. The results showed that there was a significant expansion of agriculture area at the expense of large areas of grassland, wetland, and forest during 1975–2000. The land use changes during the period of 1975 to 2000 had decreased the water yield (3.5%), surface runoff (1.7%), and baseflow (19%) while they increased the annual evapotranspiration (2.1%). For impacts of individual land use type, the forest proved to have reduced streamflow in the flood season (10%–28%) and increased surface runoff in the drought season (20%–38%). Conversely, grassland, dry land, and paddy land scenarios resulted in increase of streamflow during summer months by 7%–37% and a decrease of streamflow in the cold seasons by 11.7%–59.7%. When the entire basin was changed to wetland, streamflow reduced over the whole year, with the largest reduction during January to March. The 2038 land use condition is expected to increase the annual water yield, surface runoff and wet season flow, and reduce evapotranspiration and baseflow. These results could help to improve sustainable land use management and water utilization in the NRB.

Analysis of Dam Inflow Variation Using the Hydrological Sensitivity Method in a Trans-Boundary River Basin: Case Study in the Korean Peninsula

Water resource planning in a trans-boundary river basin is complex because of different institutional and scientific concerns and it may become increasingly difficult as a consequence of water scarcity caused by climate change. The analysis of discharge variations in a trans-boundary river basin is very important because the results can be key to resolve complex problems including decreased hydropower generation, degraded water quality, and deficient water supplies. Despite its importance, there are relatively few studies dealing with hydrological variation in a trans-boundary river basin. Therefore, this study used the hydrological sensitivity method to identify the discharge variation in the Hwacheon dam upper basin, a representative trans-boundary river basin between South Korea and North Korea. This particular basin was selected because the inflow into the Hwacheon dam in South Korea has decreased significantly after the construction of the Imnam dam in North Korea in 2000. The hydrological sensitivity method is a simple approach to analyze variations in discharge. After collecting 51 years (1967–2017) of rainfall and inflow data, a change point that represents an abrupt change in the time series was detected by using moving average, double-mass curve analysis, Pettitt’s test, and Bayesian change-point analysis. The change point detected by these methods was 1999. The hydrological sensitivity method using five Budyko-based functions was applied to a time series divided into before and after the detected change point. The average decrease after 1999 was 464.91 mm/y (or 1899 × 106 m3/y). Also, the maximum and minimum decreases after 1999 were 515.24 mm/y (or 2105 × 106 m3/y) and 435.32 mm/y (or 1778 × 106 m3/y), respectively. Because of the increase in rainfall and the decrease in inflow since 2000, the values determined in this study are slightly larger than those from conventional studies. Finally, it is suggested that the results from this study can be used effectively to establish reasonable water resource planning in the trans-boundary river basin between South Korea and North Korea.

Long-term groundwater storage variations estimated in the Songhua River Basin by using GRACE products, land surface models, and in-situ observations

Influences of climatic change and anthropogenic activities on the terrestrial water storage (TWS) change are significant in the mid- and high-latitude areas. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) satellite mission has provided quantitative measurements of TWS changes with unprecedented accuracy at global, regional and basin scales. In this study, the noise level of various GRACE-derived TWS anomalies (TWSA) data were evaluated by using a generalized three-cornered hat (GTCH) method. A time-dependent weights approach was adopted to obtain a combined TWSA series over the Songhua River Basin (SRB) from 2003 to 2013. Monthly TWSA data during the past decades (1982-2002) were reconstructed by using an artificial neural network (ANN) approach with the good performance evaluated by the correlation coefficient of 0.89 and the Nash-Sutcliff efficiency of 0.79 over the study region. In-situ groundwater level measurements were used for validation of the groundwater storage (GWS) changes (estimated by using GRACE-derived TWS changes in association with the other simulated components of water storage changes from land surface models (LSMs)). The primary driving factors of spatiotemporal variations of GWS, as well as their inter-/intra-annually varying characteristics, were explored. The present study revealed that the variations of GWS featured a "downward fluctuations" (1982-1994), "stable upward" (1998-2008) and "decreasing dramatically" (2009-2013) period, respectively, over the SRB. In general, GWS had varied in a steady decline trend at a decreasing rate of 1.04 ± 0.59 mm year^-1 from 1982 to 1994. With the enhanced climatic and anthropogenic influences over the region since 2000, several severe fluctuations characterized the GWS variations with occurrences of spring droughts and flooding over the region, which suggested significant effects of global changes posed on GWS variations of the region.

Development and application of a novel method for regional assessment of groundwater contamination risk in the Songhua River Basin

The main objective of this study is to quantify the groundwater contamination risk of Songhua River Basin by applying a novel approach of integrating public datasets, web services and numerical modelling techniques. To our knowledge, this study is the first to establish groundwater risk maps for the entire Songhua River Basin, one of the largest and most contamination-endangered river basins in China. Index-based groundwater risk maps were created with GIS tools at a spatial resolution of 30arc sec by combining the results of groundwater vulnerability and hazard assessment. Groundwater vulnerability was evaluated using the DRASTIC index method based on public datasets at the highest available resolution in combination with numerical groundwater modelling. As a novel approach to overcome data scarcity at large scales, a web mapping service based data query was applied to obtain an inventory for potential hazardous sites within the basin. The groundwater risk assessment demonstrated that <1% of Songhua River Basin is at high or very high contamination risk. These areas were mainly located in the vast plain areas with hotspots particularly in the Changchun metropolitan area. Moreover, groundwater levels and pollution point sources were found to play a significantly larger impact in assessing these areas than originally assumed by the index scheme. Moderate contamination risk was assigned to 27% of the aquifers, predominantly associated with less densely populated agricultural areas. However, the majority of aquifer area in the sparsely populated mountain ranges displayed low groundwater contamination risk. Sensitivity analysis demonstrated that this novel method is valid for regional assessments of groundwater contamination risk. Despite limitations in resolution and input data consistency, the obtained groundwater contamination risk maps will be beneficial for regional and local decision-making processes with regard to groundwater protection measures, particularly if other data availability is limited.