Dynamic Hydrological Modeling in Drylands with TRMM Based Rainfall
نویسندگان
چکیده
This paper introduces and evaluates DryMOD, a dynamic water balance model of the key hydrological process in drylands that is based on free, public-domain datasets. The rainfall model of DryMOD makes optimal use of spatially disaggregated Tropical Rainfall Measuring Mission (TRMM) datasets to simulate hourly rainfall intensities at a spatial resolution of 1-km. Regional-scale applications of the model in seasonal catchments in Tunisia and Senegal characterize runoff and soil moisture distribution and dynamics in response to varying rainfall data inputs and soil properties. The results highlight the need for hourly-based rainfall simulation and for correcting TRMM 3B42 rainfall intensities for the fractional cover of rainfall (FCR). Without FCR correction and disaggregation to 1 km, TRMM 3B42 based rainfall intensities are too low to generate surface runoff and to induce substantial changes to soil moisture storage. The outcomes from the sensitivity analysis show that topsoil porosity is the most important soil property for simulation of runoff and soil moisture. Thus, we demonstrate the benefit of hydrological investigations at a scale, for which reliable information on soil profile characteristics exists and which is sufficiently fine to account for the heterogeneities of these. Where such information is available, application of DryMOD can assist in the spatial and temporal planning of water harvesting OPEN ACCESS Remote Sens. 2013, 5 6692 according to runoff-generating areas and the runoff ratio, as well as in the optimization of agricultural activities based on realistic representation of soil moisture conditions.
منابع مشابه
TRMM satellite rainfall data
Spatial rainfall is a key input to Distributed Hydrological Models, which is the most important limitation for the accuracy of hydrological models. Model performance and uncertainty could increase when rain gauge is sparse. Satellite-based precipitation products would be an alternative to ground-based rainfall estimates in present and 5 the foreseeable future, however, it is necessary to evalua...
متن کاملA Rainfall Model Based on a Geographically Weighted Regression Algorithm for Rainfall Estimations over the Arid Qaidam Basin in China
Accurate rainfall estimations based on ground-based rainfall observations and satellite-based rainfall measurements are essential for hydrological and environmental modeling in the Qaidam Basin of China. We evaluated the accuracy of daily and monthly scale Tropical Rainfall Measuring Mission (TRMM) rainfall products in the Qaidam Basin. A Geographically Weighted Regression (GWR) was used to est...
متن کاملHydrological Evaluation of TRMM Rainfall over the Upper Senegal River Basin
The availability of climatic data, especially on a daily time step, has become very rare in West Africa over the last few years due to the high costs of climate data monitoring. This scarcity of climatic data is a huge obstacle to conduct hydrological studies over some watersheds. In this context, our study aimed to evaluate the capacity of Tropical Rainfall Measuring Mission (TRMM) satellite d...
متن کاملSpatiotemporal Interpolation of Rainfall by Combining BME Theory and Satellite Rainfall Estimates
The accurate assessment of spatiotemporal rainfall variability is a crucial and challenging task in many hydrological applications, mainly due to the lack of a sufficient number of rain gauges. The purpose of the present study is to investigate the spatiotemporal variations of annual and monthly rainfall over Fujian province in China by combining the Bayesian maximum entropy (BME) method and sa...
متن کاملEvaluation of gridded multi-satellite precipitation (TRMM -TMPA) estimation performance in the Upper Indus Basin (UIB)
Data with acceptable gridded resolution of daily climatic variables are critical for hydrological and water resource modeling. The gauge-based interpolation methods usually used by hydrologic models in general do not cover the spatial heterogeneity of the variability of climatic variables in a catchment. The errors in the interpolated data fields have the potential to significantly bias hydrolo...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Remote Sensing
دوره 5 شماره
صفحات -
تاریخ انتشار 2013