The role of topography in the emergence of African savannas

Includes bibliographical references (leaves 93-96).Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2003.The coexistence of trees and grasses in savannas are not well understood even though savannas occupy a wide area of West Africa. In this study, a hypothesis is proposed to investigate the question of how trees and grasses coexist in a region. The hypothesis suggests that the variation in elevation leads to the variation in soil moisture, which in turn can explain the coexistence of trees and grasses in savannas. To test this hypothesis, experimental simulations are performed using biospheric model, IBIS, and distributed hydrologic model, SHE. We, first, estimate the amount of rainfall required for trees and grasses under a certain atmospheric condition. Here, the variation of rainfall is prescribed to force a similar variation of soil moisture. A 30% decrease in rainfall is sufficient to simulate grasses at 9°N. A 100% increase in rainfall is sufficient to simulate trees at II°N. However, even with a five fold increase in rainfall, the model fails to simulate trees at 13°N. To study the influences of topography explicitly, a distributed hydrologic modeling is performed using SHE. The results suggest that the variation of the depth to water table induced by the varying elevation is highly correlated with the variation of soil moisture. Consequently, an asynchronous coupling of SHE and IBIS is designed to investigate the stated hypothesis. The coupling is performed by modifying IBIS to include the groundwater table as a boundary variable. The modified IBIS simulates both trees and grasses according to a different water table boundary condition in natural savannas of 11°N. The shallow water table of valleys allows the growth of trees, and the deep water table of hills allows the growth of grasses. The simulations in this study suggest that the variability of soil moisture resulting from the topographic variation can be a determinant of savanna ecosystems. Moreover, grasslands in 13°N cannot be changed into forests only by adjusting soil moisture. It suggests that the role of soil moisture can be significant to dictate the vegetation type only in a certain window characteristic of savanna climate.by Yeonjoo Kim.S.M

Parameter Calibration Method Based On GA Technique For Multi-Event

Accurate parameter estimation based catchment modeling systems requires considerable work to establish credibility. In this paper, a methodology for parameter estimation of hydrologic simulation model is proposed to simultaneously include several rainfall events using Shannon entropy. The proposed methodology uses Genetic Algorithm(GA) optimization techniques for the Storm Water Management Model (SWMM). Shannon entropy theory was applied to calculate weights according to each rainfall event in study area. A case study application was undertaken using the Milyang-dam basin, in Korea. Three events are applied to calculate Shannon entropy weights. Then, Nash-Sutcliffe Efficiency(NSE) & Root Mean Square Error(RMSE) are compared with those from single event. This study suggests that the proposed methodology is capable of providing effective parameter estimation method

VIKOR Application For Climate Change Adaptation Strategies Under Uncertain Environments

This study developed a decision making frame for climate change adaptation strategies under an uncertain environment. We developed a VIKOR-based procedure, providing a compromise solution with the objective weights of multiple climate change scenarios. We chose a watershed in South Korea and established adaptation alternatives of using the effluents of wastewater treatment plants (WWTPs) in potential sub-watersheds to improve the water quantity and quality situations. Under multiple climate scenarios, the environmental and hydrologic responses of treated wastewater (TWW) use were determined with a hydrologic model and the results were used to derive the sustainability scores of TWW reuse. Finally, sustainability scores under multiple scenarios were integrated using the VIKOR and the objective weights among the climate change scenarios, and the final decision for adaptation strategies were made. This framework can be a very effective decision making tool for climate change adaptation strategies as it consider not only uncertainties but also the relative importance of various climate change scenarios

Soil moisture-vegetation-precipitation feedback at the seasonal time scale over North America

The soil moisture-vegetation-precipitation feedback at the seasonal time scale can play a critical role in the North American seasonal climate. To investigate such feedback mechanisms, we first incorporate into the land model (CLM) the vegetation phenology scheme, which can simulate the seasonal variation of vegetation in response to hydrometorological conditions. The modified land model is validated against the remotely-sensed MODIS LAI observations. Using the coupled land-atmosphere model CAM-CLM that includes the modified land model, a series of ensemble simulations are performed to examine how initial soil moisture anomalies influence the subsequent precipitation at the seasonal time scale. The simulations are performed with different initial soil moisture conditions and with different vegetation treatments. When vegetation feedback is excluded, initial wet/dry soil moisture anomalies in the model tend to cause increase/decrease of precipitation in general, leading to a positive soil moisture-precipitation feedback. Precipitation responses are found to vary with the characteristics of soil moisture anomalies, including their timing, magnitude/direction, spatial coverage and vertical depth. For example, during summer the decrease of precipitation due to dry soil moisture anomalies tends to persist longer than the increases of precipitation due to wet soil moisture anomalies. With vegetation feedback included, LAI increases/decreases as a result of the initial wet/dry soil moisture anomalies. This increase/decrease of LAI tends to increase/decrease evapo-transpiration and decrease/increase albedo, and thus further increase/decrease precipitation (i.e., positive vegetation feedback). On the other hand, the increase/decrease of LAI tends to increase/decrease water consumption by vegetation and decrease/increase soil moisture, and thus decrease/increase precipitation (i.e. negative vegetation feedback). Whether positive feedback or negative feedback is dominant varies with the characteristics of soil moisture anomalies. As a result of initial wet summer soil moisture anomalies, for instance, the increase of LAI leads to reduce soil moisture, but still enhance the precipitation response through vegetation\u27s impact on evapotranspiration and albedo. Furthermore, additional ensemble simulations are performed after modifying CAM-CLM to reduce its dry biases. Results from the modified model suggest that modeling studies on the soil moisture-vegetation-precipitation feedback must consider the dependence of results on model climate and model parameterization.

On the Role of Leaf Area Index Parameterization in Simulating the Terrestrial Carbon Fluxes of Africa Using a Regional Coupled Climate–Vegetation Model

In this study, the Regional Climate Model version 4 (RegCM4) coupled with the Community Land Model version 4.5 (CLM45) including a module of carbon–nitrogen cycling (CN) (RegCM4-CLM45-CN) was used to examine the sensitivity of the terrestrial carbon fluxes of Africa to leaf area index (LAI) parameterization. Two LAI formulas were implemented in CLM45-CN. The new LAI formula is based on a modified BioGeochemical Cycles ecosystem model. The two simulations were designated as LAIorg and LAImod, respectively, they both shared the same initial and lateral boundary conditions, and they were evaluated concerning reanalysis products and FLUXNET measurements. In LAIorg, the above-ground terrestrial carbon fluxes were overestimated to the reanalysis products, which were also noted for the below-ground terrestrial fluxes. On the other hand, in LAImod, terrestrial carbon fluxes were notably decreased relative to LAIorg, and the model bias was reduced. In the in situ observation, LAImod was better matched to the observation than LAIorg, although both were limited in capturing the observed magnitude and seasonality of gross primary production (GPP) to some extent. In conclusion, switching between the two formulas has a substantial effect on the simulated terrestrial carbon fluxes. Despite noted biases, the regional coupled RegCM4-CLM4-CN-LAImod model can be recommended for future studies to investigate the influence of climate change on the terrestrial carbon fluxes of Africa

On the Role of Leaf Area Index Parameterization in Simulating the Terrestrial Carbon Fluxes of Africa Using a Regional Coupled Climate–Vegetation Model

In this study, the Regional Climate Model version 4 (RegCM4) coupled with the Community Land Model version 4.5 (CLM45) including a module of carbon–nitrogen cycling (CN) (RegCM4-CLM45-CN) was used to examine the sensitivity of the terrestrial carbon fluxes of Africa to leaf area index (LAI) parameterization. Two LAI formulas were implemented in CLM45-CN. The new LAI formula is based on a modified BioGeochemical Cycles ecosystem model. The two simulations were designated as LAIorg and LAImod, respectively, they both shared the same initial and lateral boundary conditions, and they were evaluated concerning reanalysis products and FLUXNET measurements. In LAIorg, the above-ground terrestrial carbon fluxes were overestimated to the reanalysis products, which were also noted for the below-ground terrestrial fluxes. On the other hand, in LAImod, terrestrial carbon fluxes were notably decreased relative to LAIorg, and the model bias was reduced. In the in situ observation, LAImod was better matched to the observation than LAIorg, although both were limited in capturing the observed magnitude and seasonality of gross primary production (GPP) to some extent. In conclusion, switching between the two formulas has a substantial effect on the simulated terrestrial carbon fluxes. Despite noted biases, the regional coupled RegCM4-CLM4-CN-LAImod model can be recommended for future studies to investigate the influence of climate change on the terrestrial carbon fluxes of Africa

Spatial and Temporal Variations in Reference Crop Evapotranspiration in a Mountainous Island, Jeju, in South Korea

This study aims to assess the spatial and temporal variability of reference crop evapotranspiration (ET) over the mountainous Jeju Island, South Korea. In this mountainous region, only limited observed, station-based meteorological data are available, and thus statistical approaches are used to construct monthly reference crop ET maps. The maximum and minimum temperatures, wind speed, and relative humidity are gap filled using principal component regression (PCR) or multiple linear regression (MLR) and are then spatially interpolated using the hybrid Kriging method to construct monthly maps of reference crop ET at a resolution of 100 m. This study reveals various reference crop ET characteristics for Jeju Island that have not been investigated in previous studies. With increasing elevation and distance from the coast, the air temperature decrease and relative humidity (RH) increase. Therefore, the reference crop ET generally decreases. An increasing trend until the mid-2000s is present in the annual average reference crop ET values, and most of this increase arises from increasing trends in spring and summer. Summer reference crop ET values exhibit increasing trends over time below 1000 m a.s.l. and decreasing trends over time above 1000 m a.s.l