Search

The generality of the Christiansen model is verified using potential evaporation data as reference for the unit model developed in stella. The spatial model in SME is calibrated with data from six hydrological and meteorological stations around the study area. The results show that the observed and simulated data have a good fit, in which the revised Nash-Sutcliffe efficiency (NSE), balance error ( B), and explained variance (EV) are 0.56, −0.2, and 0.55, respectively. The best fit is seen in autumn and winter; for spring, the actual values are generally higher than in simulated observations. The spatial model can simulate the majority of summer peaks, but some are not simulated well. Running the model under different spatial resolutions shows a certain degree of stability, with the revised NSE ranging from 0.29 to 0.50. As spatial resolution increases, the simulation NSE values behave non-linearly. With the other parameters unchanged the impact of human activities, which is represented by climate change scenarios on the hydrological process, is analyzed. Assuming constant temperature, precipitation has a greater influence on runoff than on evaporation; while when precipitation is constant, evaporation is influenced more by temperature. Although the model can validate the effect of climate change on runoff and evapotranspiration, it is not enough to describe the complex relationship between runoff, evaporation, temperature, and precipitation accurately, because the description of the water cycle process is simplified compared with a highly specialized hydrological model. The water and heat coupling process is not included in the soil freezing and thawing process; the source code of SME needs to be deeply understood to improve the algorithms of interpolation and conflux. More importantly, the current work does not consider the impact of human activities endogenously. The main purpose of this paper is to build a better basis for developing a meaningful integrated ecological economic model in the Heihe River Basin to solve its ecological and economic problems. [ABSTRACT FROM AUTHOR]

In this paper, the FEST-FOREST model is presented. A FOREST module is written in the FORTRAN-90 programming language, and was included in the FEST-WB distributed hydrological model delivering the FEST-FOREST model. FEST-FOREST is a process-based dynamic model allowing the simulation at daily basis of gross primary production (GPP) and net primary production (NPP) together with the carbon allocation of a homogeneous population of trees (same age, same species). The model was implemented based on different equations from literature, commonly used in Eco-hydrological models. This model was developed within the framework of the INNOMED project co-funded under the ERA-NET WaterWorks2015 Call of the European Commission. The aim behind the implementation of the model was to simulate in a simplified mode the forest growth under different climate change and management scenarios, together with the impact on the water balance at the catchment. On a first application of the model, the results are considered very promising when compared to field measured data. [ABSTRACT FROM AUTHOR]

Summary: This paper combines hydrological observations and modelling results of a semi arid catchment in Brazil that could lead to a better understanding of the hydrology of similar catchments in semi-arid regions. The Tapacurá catchment (area 470.5km2) in the Northeast of Brazil was selected for this study. The Distributed Catchment Scale Model, DiCaSM, was calibrated and validated for the stream flows of the Tapacurá catchment. The model performance was further tested by comparing simulated and observed scaled soil moisture. The results showed the ability of the model to simulate the stream flow and the scaled soil moisture. The simulated impacts of climate change of low emission (B1) scenarios, on the worst perspective, indicated the possibility of reduction in surface water availability by −13.90%, −22.63% and −32.91% in groundwater recharge and by −4.98%, −14.28% and −20.58% in surface flows for the time spans 2010–2039, 2040–2069, 2070–2099, respectively. This would cause severe impacts on water supply in the region. Changing the land use, for example by reforestation of part of the catchment area which is currently arable land, would lead to a decrease in both groundwater recharge by −4.2% and stream flow by −2.7%. Changing land use from vegetables to sugar cane would result in decreasing groundwater recharge by almost −11%, and increasing stream flow by almost 5%. The combination of possible impacts of climate change and land use requires a proper plan for water resources management and mitigation strategies. [Copyright &y& Elsevier]

Summary: Miyun Reservoir is the main raw water source for Beijing’s domestic water supply. Flow discharge to Miyun Reservoir decreased drastically over a 50-year period, from 1956 to 2005, and had seriously affected Beijing’s water supply. Climate variability and human activity had been identified as the two main reasons for the decrease in flow. Here, climate variability refers to changes in precipitation and temperature. Impact of human activity includes direct withdrawal of water (referred to as “direct abstraction” in this paper) from the river (primary) or groundwater and indirect impact due to man-made changes in land use and vegetation in the upstream of the reservoir. According to the historical record, “direct abstraction” from the upstream of the reservoir has increased significantly since 1984. The study period was split into two sub-periods, from 1956 to 1983 and from 1984 to 2005. Based on the historical record, annual runoff in the upstream catchment of Miyun Reservoir (i.e., inflow into the reservoir) had decreased from 90.3mm to 41.8mm for the two sub-periods, a decrease of 48.5mm. Over the same period, average annual “direct abstraction” increased from 2.2mm to 13.4mm, an increase of 11.2mm. The latter accounted for 23% (11.2mm/48.5mm) of the decrease in inflow into the reservoir. This study utilised: (1) a distributed hydrological model (geomorphology-based hydrological model, or GBHM) and (2) a climate elasticity model to conduct a quantitative assessment of the impact of climate variability and the indirect impact of human activity on the inflow into the reservoir. Simulation results of GBHM and the climate elasticity model showed that climate impact was accountable for about 55% and 51% of the decrease in reservoir inflow, respectively. The indirect impact of human activity (mainly man-made land use and vegetation changes) accounted for 18% of the decrease in reservoir inflow. [Copyright &y& Elsevier]

As the two largest rivers in China, the Yangtze and Yellow Rivers are of great importance for water cycle and hydrological processes over the country, which have been significantly affected by climate change. In this study, by assessing the suitability of multiple GCMs (General Circulation Models) recommended by IPCC (Intergovernmental Panel on Climate Change), SDSM (Statistical Downscaling Model) and ASD (Automated Statistical Downscaling) were used to generate future climate change scenarios, which were used to drive VIC (Variable Infiltration Capacity) and SWAT (Soil and Water Assessment Tool) models to quantify climate change impacts in the Yangtze River Delta region and upper reaches of the Yellow River basin, respectively. Results showed that suitability assessment method adopted in this study coupled with statistical downscaling could effectively reduce uncertainties of GCMs. Compared with the baseline period (1961-1990), projected annual runoff in future periods (2046-2065 and 2081-2100) would decreased by 9.5% and 3% in the Yangtze River Delta region. While annual runoff in the upper Yellow River basin during future two periods would decrease by 16.9% and 22.2%. The results are of great significance to future water resources management and sustainable development under climate change in major river basins of China. [ABSTRACT FROM AUTHOR]

Rainwater harvesting could increase the resilience of ecosystems on the Loess Plateau and thus ensure the sustainability of livelihoods that depend on them. As such, it is a key component of strategies for adapting to global climate change. In this study, we used a new method to quantify the rainwater harvesting potential (RWHP) across the whole Loess Plateau and to characterize its spatial and temporal variation over the last four decades on the basis of the variable infiltration capacity model. It was found that that the mean RWHP of the study region was 731.10 × 108 m3, and the average water layer thickness was 114.34 mm. There is considerable scope for rainwater harvesting across the Loess Plateau as a whole, to the extent that it could potentially provide enough water to implement the 'Grain for Green' Project. The annual average RWHP decreased slightly from 1971 to 2010, and Hurst exponent analysis indicated that this trend will exhibit long-term persistence. The annual RWHP was highest in the southeast of the Loess Plateau and lowest in the northwest. Areas with high RWHP values tended to be clustered around the middle reach of the Yellow River. For most areas, there was no significant change between 1971 and 2010. Those areas for which there was a significant decrease in RWHP were primarily located around the upper-middle reaches of the Weihe River, the upper reach of Jinghe River, the eastern Guanzhong Plain, the Qinhe River watershed and the area around Dongsheng. Quantitative assessments of RWHP are likely to be useful for guiding the development and use of innovative rainwater harvesting technologies around the world and could help to relieve the problems caused by water shortages on the Loess Plateau while simultaneously eliminate the major cause of soil erosion. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this study, the Variable Infiltration Capacity model and Palmer Drought Severity Index (PDSI) were combined for drought identification on the Loess Plateau. The calibration method of climatic characteristic ( K) in PDSI was improved. Land cover datasets in 1980 and 2005 were used to drive the model. The driest periods over the past four decades of the study region emerged in 1976-1982, 1997-2001 and 2003-2008. Regardless of ranking by duration, spatial extent or severity, most of the prominent droughts occurred in the detected driest periods. The drought severity and area over the upper reaches of the Yellow River were higher than other domains. A total of 53 droughts with area greater than the 25,000 km threshold were identified with durations longer than 3 months using clustering algorithm. Most regions of the study area exhibited spatially increasing trends in drought severity and frequency, indicating that the Loess Plateau has experienced apparent drying and warming processes between 1971 and 2010. [ABSTRACT FROM AUTHOR]

The hydrological cycle has been highly influenced by climate change and human activities, and it is significant for analyzing the hydrological trends that occurred in past decades in order to understand past changes and to predict future trends. The water crisis of the Yellow River basin has drawn much attention from around the world, especially the drying up of the main river along the lower reaches during the 1990s. By incorporating historical meteorological data and available geographic information related to the conditions of the landscape, a distributed hydrological model has been employed to simulate the natural runoff without consideration of artificial water intake. On the basis of the data observed and the results simulated by the model, the hydrological trends have been analyzed quantitatively for evaluating the impact from climate change and human activity. It is found that the simulated natural runoff follows a similar trend as the precipitation in the entire area being studied during the last half century, and this implies that changes in the natural runoff are mainly controlled by the climate change rather than land use change. Changes in actual evapotranspiration upstream of the Lanzhou gauge are controlled by changes in both precipitation and potential evaporation, while changes of actual evapotranspiration downstream of the Lanzhou gauge are controlled mainly by the changes in precipitation. The difference between the annual observed runoff and the simulated runoff indicates that there is little artificial water consumption upstream of the Lanzhou gauge, but the artificial water consumption becomes larger downstream of the Lanzhou gauge. The artificial water consumption shows a significant increasing trend during the past 50 years and is the main cause of the drying up of the Yellow River. However, in contrast to the common perception that the serious drying up downstream of the Yellow River during the 1990s is caused by the rapid increase of artificial water consumption during the same period, it has been found that the main cause of this aggravation is the drier climate that has existed since the 1990s. The main reason that the drying-up situation became better in the 21st century is because of the enhanced water resources management since 2000. [ABSTRACT FROM AUTHOR]

In the 21st century, heavier rainfall events and warmer temperatures in mountainous regions have significant impacts on hydrological processes and the occurrence of flood/drought extremes. Long-term modeling and peak flow detection of streamflow series are crucial in understanding the behavior of flood and drought. This study was conducted to analyze the impacts of future climate change on extreme flows in the Kaidu River Basin, northwestern China. The soil water assessment tool (SWAT) was used for hydrological modeling. The projected future precipitation and temperature under Intergovernmental Panel on Climate Change (IPCC) representative concentration pathway (RCP) scenarios were downscaled and used to drive the validated SWAT model. A generalized extreme value (GEV) distribution was employed to assess the probability distribution of flood events. The modeling results showed that the simulated discharge well matched the observed ones both in the calibration and validation periods. Comparing with the historical period, the ensemble with 15 general circulation models (GCMs) showed that the annual precipitation will increase by 7.9–16.1% in the future, and extreme precipitation events will increase in winter months. Future temperature will increase from 0.42 °C/10 a to 0.70 °C/10 a. However, with respect to the hydrological response to climate change, annual mean runoff will decrease by 21.5–40.0% under the mean conditions of the four RCP scenarios. A reduction in streamflow will occur in winter, while significantly increased discharge will occur from April to May. In addition, designed floods for return periods of five, 10 and 20 years in the future, as predicted by the GEV distribution, will decrease by 3–20% over the entire Kaidu watershed compared to those in the historical period. The results will be used to help local water resource management with hazard warning and flood control. [ABSTRACT FROM AUTHOR]