Summer maize (Zea mays L.) is one of the dominant crops in the North China Plain (NCP). Its growth is greatly influenced by the spatial-temporal variation of climatic variables, especially solar radiation, temperature and rainfall. The WOFOST (version 7.1) model was applied to evaluate the impact of climatic variability on summer maize yields using historical meteorological data from 1961 to 20...

To understand the characteristics of severe floods under global climate change, we created a design hyetograph for a 100-year return period. This incorporates a modified ranking method using the top 10 extreme rainfall events for present, near-future, and far-future periods. The rainfall data sets were projected with a general circulation model with high spatial and temporal resolution and used...

Recent regional climate-change models indicated significant changes in the temporal and spatial distribution of rainfall in the Mediterranean-Basin region. Understanding the consequences of rainfall alterations for soil respiration and carbon processing in these regions is essential, considering their crucial functions for soil fertility and ecosystem functioning. Our aim was to evaluate the ef...

This article evaluates an infrared-based satellite algorithm for rainfall estimation, the Convective Stratiform technique, over Mediterranean. Unlike a large number of works that evaluate remotely sensed estimates concentrating on global measures of accuracy, this work examines the relationship between ground truth and satellit0e derived data in a local scale. Hence, we examine the fit of groun...

The scarcity of water encourages scientists to develop new analytical tools to enhance water resource management. Water accounting and distributed hydrological models are examples of such tools. Water accounting needs accurate input data for adequate descriptions of water distribution and water depletion in river basins. Ground-based observatories are decreasing, and not generally accessible. R...

The west coast of the Indian peninsula receives very heavy rainfall during the summer monsoon (June-September) season with average rainfall over some parts exceeding 250 cm. Heavy rainfall events with rainfall more than 15 cm day −1 at one or more stations along the west coast of India occur frequently and cause considerable damage. out during the monsoon season of 2002 to study these events. T...

India's agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such ...

Rainfall erosivity, considering rainfall amount and intensity, is an important parameter for soil erosion risk assessment under future land use and climate change. Despite its importance, rainfall erosivity is usually implemented in models with a low spatial and temporal resolution. The purpose of this study is to assess the temporaland spatial distribution of rainfall erosivity in form of the ...

Most hydrologic/water quality (H/WQ) models that use rainfall as input assume spatial homogeneity of rainfall. Under this assumption this study assesses the variability induced in calibrated model parameters solely due to rainfall spatial variability. The AGNPS model and a network of 17 raingauges were used. Model parameters were estimated using rainfall observed at each gauge location, one at ...

Traditionally in the application of hydrologic/water quality (H/WQ) models, rainfall is assumed to be spatially homogeneous and is considered not to contribute to output uncertainty. The objective of this study was to assess the uncertainty induced in model outputs solely due to rainfall spatial variability. The study was conducted using the AGNPS model and the rainfall pattern captured by a ne...