A Distributed Monthly Water Balance Model for Analyzing Impacts of Land Cover Change on Flow Regimes

The Miyun Reservoir is the most important water source for Beijing Municipality, the capital of China with a population of more than 12 million. In recent decades, the inflow to the reservoir has shown a decreasing trend, which has seriously threatened water use in Beijing. In order to analyze the influents of land use and cover change (LUCC) upon inflow to Miyun Reservoir, terrain and land use information from remote sensing were utilized with a revised evapotranspiration estimation formula; a water loss model under conditions of human impacts was introduced; and a distributed monthly water balance model was established and applied to the Chaobai River Basin controlled by the Miyun Reservoir. The model simulation suggested that not only the impact of land cover change on evapotranspiration, but also the extra water loss caused by human activities, such as the water and soil conservation development projects should be considered. Although these development projects were of great benefit to human and ecological protection, they could reallocate water resources in time and space, and in a sense thereby influence the stream flow.

Improvement in estimation of soil water deficit by integrating airborne imagery data into a soil water balance model

In this study,an approach that integrates airborne imagery data as inputs was used to improve the estimation of soil water deficit(SWD)for maize and sunflower grown under full and deficit irrigation treatments.The proposed model was applied to optimize the maximum total available soil water(TAWr)by minimizing the difference between a water stress coefficient ks and crop water stress index(1-CWSI).The optimal value of maximum TAWr was then used to calibrate a soil water balance model which in turn updated the estimation of soil water deficit.The estimates of SWD in the soil profile of both irrigated maize and sunflower fields were evaluated with the crop root zone SWD derived from neutron probe measurements and the FAO-56 SWD procedure.The results indicated a good agreement between the estimated SWD from the proposed approach and measured SWD for both maize and sunflower.The statistical analyses indicated that the maximum TAWr estimated from CWSI significantly improved the estimates of SWD,which reduced the mean absolute error(MAE)and root mean square error(RMSE)by 40%and 44%for maize and 22%for sunflower,compared with the FAO-56 model.The proposed procedure works better for crops under deficit irrigation condition.With the availability of higher spatial and temporal resolution airborne imagery during the growing season,the optimization procedure can be further improved.

Estimating water deficit and its uncertainties in water-scarce area using integrated modeling approach

Accurate assessment of water deficit and related uncertainties in water-scarce areas is strategically important in various fields of water resources management. This study developed a hybrid approach integrating conceptual water balance model and econometric regression to estimate water shortage and its related uncertainties in water-scarce areas. This hybrid approach was used to assess the agricultural water deficit of Beijing, an extremely water-scarce area in China. A predictive model of agricultural water demand was developed using the stepwise multiple regression method, and was validated by comparing the predicted values with observed data. Scenario analysis was employed to investigate the uncertainties of agricultural water shortage and agricultural water demand. This modeling approach can assist water administration in creating sustainable water allocation strategies in water-scarce areas.

Effect of reforestation on annual water yield in a large watershed in northeast China

A simplified water balance model in conjunc- tion with an evapotranspiration （ET） model and cumulative forest cover data were used to quantify the changes in annual water yield in response to reforestation in a large watershed, northeast China. Cumulative forest cover increased by 22 %, leading to a significant decrease in estimated annual water yield. Reforestation increased ET （P = 0.0144）, resulting in a remarkable decrease （P = 0.0001） in estimated annual water yield according to the water balance model. Reforestation increased ET by 33 mm and decreased annual water yield by 38 mm per decade. The effect of reforestation on annual water yield can be quantified using a simplified water balance model in a large watershed, although our reforestation area was small （about 20 %） in relation to the total watershed area.

A Setup for a Scenario-Driven Water Balance at Landscape Scale—Assessment with AKWA-M~-Embedded in a Model Framework for Land-Use Planning’s Decision Support in Mountainous Southwest China

Land-cover changes cause a loss of natural vegetation in many parts of the world. In the Xishuangbanna （西双版纳） district （Yunnan （云南） Province）, rubber plantations replace tropical rainforests covering already an area of about 10% of the study area （2007）. There, land-use allocation is mostly driven by economic considerations. Thus, local planning authorities need decision support for land-use planning issues, which integrate socio-economic and ecological aspects. Within the NabanFrame, an agro-economic, ecological and social model was applied, which, altogether, interacted with a land allocation model via defined interfaces. Effects on the water cycle, ecological conditions as well as socio-economic should be considered by integrating the spatially distributed rainfali-runoff and water balance model AKWA-M in the model setup.

Characteristics of land-atmosphere energy and turbulentfluxes over the plateau steppe in central Tibetan Plateau

The land-atmosphere energy and turbulence exchange is key to understanding land surface processes on the Tibetan Plateau(TP). Using observed data for Aug. 4 to Dec. 3, 2012 from the Bujiao observation point(BJ) of the Nagqu Plateau Climate and Environment Station(NPCE-BJ), different characteristics of the energy flux during the Asian summer monsoon(ASM) season and post-monsoon period were analyzed. This study outlines the impact of the ASM on energy fluxes in the central TP. It also demonstrates that the surface energy closure rate during the ASM season is higher than that of the post-monsoon period. Footprint modeling shows the distribution of data quality assessments(QA) and quality controls(QC) surrounding the observation point. The measured turbulent flux data at the NPCE-BJ site were highly representative of the target land-use type. The target surface contributed more to the fluxes under unstable conditions than under stable conditions. The main wind directions(180° and 210°) with the highest data density showed flux contributions reaching 100%, even under stable conditions. The lowest flux contributions were found in sectors with low data density, e.g., 90.4% in the 360° sector under stable conditions during the ASM season. Lastly, a surface energy water balance(SEWAB) model was used to gap-fill any absent or corrected turbulence data. The potential simulation error was also explored in this study. The Nash-Sutcliffe model efficiency coefficients(NSEs) of the observed fluxes with the SEWAB model runs were 0.78 for sensible heat flux and 0.63 for latent heat flux during the ASM season, but unrealistic values of-0.9 for latent heat flux during the post-monsoon period.

Suitability mapping of global wetland areas and validation with remotely sensed data

With increasing urbanization and agricultural expansion, large tracts of wetlands have been either disturbed or converted to other uses. To protect wetlands, accurate distribution maps are needed. However, because of the dramatic diversity of wetlands and difficulties in field work, wetland mapping on a large spatial scale is very difficult to do. Until recently there were only a few high resolution global wetland distribution datasets developed for wetland protection and restoration. In this paper, we used hydrologic and climatic variables in combination with Compound Topographic Index （CTI） data in modeling the average annual water table depth at 30 arc-second grids over the continental areas of the world except for Antarctica. The water table depth data were modeled without considering influences of anthropogenic activities. We adopted a relationship between poten- tial wetland distribution and water table depth to develop the global wetland suitability distribution dataset. The modeling re- suits showed that the total area of global wetland reached 3.316× 10^7 km^2. Remote-sensing-based validation based on a compi- lation of wetland areas from multiple sources indicates that the overall accuracy of our product is 83.7%. This result can be used as the basis for mapping the actual global wetland distribution. Because the modeling process did not account for the im- pact of anthropogenic water management such as irrigation and reservoir construction over suitable wetland areas, our result represents the upper bound of wetland areas when compared with some other global wetland datasets. Our method requires relatively fewer datasets and has a higher accuracy than a recently developed global wetland dataset.