The interaction between vegetation and hydrologic processes is particularly tight in water-limited environments where a positive-feedback links soil moisture and vegetation. The vegetation of these systems is commonly patterned, that is, arranged in a two phase mosaic composed of patches with high biomass cover interspersed within a low-cover or bare soil component. These patterns are strongly linked to the redistribution of runoff and resources from source areas (bare patches) to sink areas (vegetation patches) and play an important role in controlling erosion. In this paper, the dynamics of these systems is investigated using a new modeling framework that couples landform and vegetation evolution, explicitly accounting for the dynamics of runon-runoff areas. The objective of this study is to analyze water-limited systems on hillslopes with mild slopes, in which overland flow occurs predominantly in only one direction and vegetation displays a banded pattern. Our simulations reproduce bands that can be either stationary or upstream migrating depending on the magnitude of the runoff-induced seed dispersal. We also found that stationary banded systems redistribute sediment so that a stepped microtopography is developed. The modelling results are the first to incorporate the effects of runoff redistribution and variable infiltration rates on the development of both the vegetation patterns and microtopography. The microtopography for stationary bands is characterized by bare soil on the lower gradient areas and vegetation on steeper gradients areas. For the case of migrating vegetation bands the model generates hillslope profiles with planar topography. The success at generating not only the observed patterns of vegetation, but also patterns of runoff and sediment redistribution suggests that the hydrologic and erosion mechanisms represented in the model are correctly capturing some of the key processes driving these ecosystems.

Vegetation cover change is one of the key indicators used for monitoring environmental quality. It can accurately reflect changes in hydrology, climate, and human activities, especially in arid and semi-arid regions. The main goal of this paper is to review the remote sensing satellite sensors and the methods used for monitoring and mapping vegetation cover changes in arid and semi-arid. Arid and semi-arid lands are eco-sensitive environments with limited water resources and vegetation cover. Monitoring vegetation changes are especially important in arid and semi-arid regions due to the scarce and sensitive nature of the plant cover. Due to expected changes in vegetation cover, land productivity and biodiversity might be affected. Thus, early detection of vegetation cover changes and the assessment of their extent and severity at the local and regional scales become very important in preventing future biodiversity loss. Remote sensing data are useful for monitoring and mapping vegetation cover changes and have been used extensively for identifying, assessing, and mapping such changes in different regions. Remote sensing data, such as satellite images, can be obtained from satellite-based and aircraft-based sensors to monitor and detect vegetation cover changes. By combining remotely sensed images, e.g., from satellites and aircraft, with ground truth data, it is possible to improve the accuracy of monitoring and mapping techniques. Additionally, satellite imagery data combined with ancillary data such as slope, elevation, aspect, water bodies, and soil characteristics can detect vegetation cover changes at the species level. Using analytical methods, the data can then be used to derive vegetation indices for mapping and monitoring vegetation.

Our current understanding of semiarid ecosystems is that they tend to display higher vegetation greenness on polar‐facing slopes (PFS) than on equatorial‐facing slopes (EFS). However, recent studies have argued that higher vegetation greenness can occur on EFS during part of the year. To assess whether this seasonal reversal of aspect‐driven vegetation is a common occurrence, we conducted a global‐scale analysis of vegetation greenness on a monthly time scale over an 18‐year period (2000–2017). We examined the influence of climate seasonality on the normalized difference vegetation index (NDVI) values of PFS and EFS at 60 different catchments with aspect‐controlled vegetation located across all continents except Antarctica. Our results show that an overwhelming majority of sites (70%) display seasonal reversal, associated with transitions from water‐limited to energy‐limited conditions during wet winters. These findings highlight the need to consider seasonal variations of aspect‐driven vegetation patterns in ecohydrology, geomorphology, and Earth system models.

Dryland wetlands are resilient ecosystems that can adapt to extreme periodic drought–flood episodes. Climate change projections show increased drought severity in drylands that could compromise wetland resilience and reduce important habitat services. These recognized risks have been difficult to evaluate due to our limited capacity to establish comprehensive relationships between flood–drought episodes and vegetation responses at the relevant spatiotemporal scales. We address this issue by integrating detailed spatiotemporal flood–drought simulations with remotely sensed vegetation responses to water regimes in a dryland wetland known for its highly variable inundation. We show that a combination of drought tolerance and dormancy strategies allow wetland vegetation to recover after droughts and recolonize areas invaded by terrestrial species. However, climate change scenarios show widespread degradation during drought and limited recovery after floods. Importantly, the combination of degradation extent and increase in drought duration is critical for the habitat services wetland systems provide for waterbirds and fish.