Drought is a complex natural hazard that impacts ecosystems and society in many ways. Many of these impacts are associated with hydrological drought (drought in rivers, lakes, and groundwater). It is, therefore, crucial to understand the development and recovery of hydrological drought. In this review an overview is given of the current state of scientific knowledge of definitions, processes, and quantification of hydrological drought. Special attention is given to the influence of climate and terrestrial properties (geology, land use) on hydrological drought characteristics and the role of storage. Furthermore, the current debate about the use and usefulness of different drought indicators is highlighted and recent advances in drought monitoring and prediction are mentioned. Research on projections of hydrological drought for the future is summarized. This review also briefly touches upon the link of hydrological drought characteristics with impacts and the issues related to drought management. Finally, four challenges for future research on hydrological drought are defined that relate international initiatives such as the Intergovernmental Panel on Climate Change (IPCC) and the ‘Panta Rhei’ decade of the International Association of Hydrological Sciences (IAHS). WIREs Water 2015, 2:359–392. doi: 10.1002/wat2.1085

For further resources related to this article, please visit the WIREs website.

/pdf/hydrological-drought-explained-22b5t1sxan.pdf

Hydrological drought explained

Adaptation strategies for agricultural water management under climate change in Europe

This article presents an analysis of the projected performance of urban residential rainwater harvesting systems in the United States (U.S.). The objectives are to quantify for 23 cities in seven climatic regions (1) water supply provided from rainwater harvested at a residential parcel and (2) stormwater runoff reduction from a residential drainage catchment. Water-saving efficiency is determined using a water-balance approach applied at a daily time step for a range of rainwater cistern sizes. The results show that performance is a function of cistern size and climatic pattern. A single rain barrel (190 l [50 gal]) installed at a residential parcel is able to provide approximately 50% water-saving efficiency for the nonpotable indoor water demand scenario in cities of the East Coast, Southeast, Midwest, and Pacific Northwest, but <30% water-saving efficiency in cities of the Mountain West, Southwest, and most of California. Stormwater management benefits are quantified using the U.S. Environmental Protection Agency Storm Water Management Model. The results indicate that rainwater harvesting can reduce stormwater runoff volume up to 20% in semiarid regions, and less in regions receiving greater rainfall amounts for a long-term simulation. Overall, the results suggest that U.S. cities and individual residents can benefit from implementing rainwater harvesting as a stormwater control measure and as an alternative source of water.

/pdf/water-supply-and-stormwater-management-benefits-of-1ghu3kxcrq.pdf

Water Supply and Stormwater Management Benefits of Residential Rainwater Harvesting in U.S. Cities

Multi-criteria analysis and GIS modeling for identifying prospective water harvesting and artificial recharge sites for sustainable water supply

The role of water harvesting to achieve sustainable agricultural intensification and resilience against water related shocks in sub-Saharan Africa

Balancing watershed and local scale impacts of rain water harvesting in India—A review

Hydrological impacts of rainwater harvesting (RWH) in a case study catchment: The Arvari River, Rajasthan, India. Part 1: Field-scale impacts

Dry spell trend analysis in Kenya and the Murray Darling Basin using daily rainfall

Deep drainage (DD) is recognised as one of the main drivers for dryland and irrigated salinity. Review of the literature on risk and hazard highlights few Australian studies on assessing DD risk and the need to develop new methods for determining DD risk. This study developed a method to map DD risk for the Northern Murray Darling Basin Catchment of the Border Rivers. Deep drainage was predicted at 85 points in the landscape using the mechanistic soil-water model SWAP, with soil hydraulic inputs created using pedotransfer functions and crop input from supervised classification of LANDSAT imagery. Uncertainty of the hydraulic property estimation was included using Monte Carlo simulations. The DD values were subsequently translated to probabilities of exceeding 5 or 100 mm/year for different land management options. The outcomes indicated that exceeding 100mm/year deep drainage had a probability of 60, 25, 1 and 5% for irrigated cotton, wheat, pasture and native vegetation, respectively. Using regression kriging based on ancillary information from the LANDSAT imagery, DD probabilities were predicted spatially over the study area to create a risk map. Soil type was less important than land use in determining the probability of exceeding a certain value, because land uses tended to be already aligned with certain soil types. Areas that require further research include incorporation of temporal variability in land-use and spatial variability in climate.

/pdf/developing-a-deep-drainage-risk-map-for-the-border-rivers-5af3mssnmb.pdf

R. W. Vervoort

Papers

Balancing watershed and local scale impacts of rain water harvesting in India—A review

Hydrological impacts of rainwater harvesting (RWH) in a case study catchment: The Arvari River, Rajasthan, India. Part 1: Field-scale impacts

Dry spell trend analysis in Kenya and the Murray Darling Basin using daily rainfall

Developing A Deep Drainage Risk Map For The Border Rivers Area

The Behaviour of Hydrological Model Parameters in Extreme Environments: Constants or Variables?