scholarly journals Global-scale modeling of groundwater recharge

2008 ◽  
Vol 12 (3) ◽  
pp. 863-885 ◽  
Author(s):  
P. Döll ◽  
K. Fiedler
Keyword(s):  
Water Resources ◽  
Groundwater Recharge ◽  
Arid Regions ◽  
Groundwater Resources ◽  
Global Scale ◽  
Unbiased Estimation ◽  
Data Sets ◽  
Total Runoff ◽  
Semi Arid

Abstract. Long-term average groundwater recharge, which is equivalent to renewable groundwater resources, is the major limiting factor for the sustainable use of groundwater. Compared to surface water resources, groundwater resources are more protected from pollution, and their use is less restricted by seasonal and inter-annual flow variations. To support water management in a globalized world, it is necessary to estimate groundwater recharge at the global scale. Here, we present a best estimate of global-scale long-term average diffuse groundwater recharge (i.e. renewable groundwater resources) that has been calculated by the most recent version of the WaterGAP Global Hydrology Model WGHM (spatial resolution of 0.5° by 0.5°, daily time steps). The estimate was obtained using two state-of-the-art global data sets of gridded observed precipitation that we corrected for measurement errors, which also allowed to quantify the uncertainty due to these equally uncertain data sets. The standard WGHM groundwater recharge algorithm was modified for semi-arid and arid regions, based on independent estimates of diffuse groundwater recharge, which lead to an unbiased estimation of groundwater recharge in these regions. WGHM was tuned against observed long-term average river discharge at 1235 gauging stations by adjusting, individually for each basin, the partitioning of precipitation into evapotranspiration and total runoff. We estimate that global groundwater recharge was 12 666 km3/yr for the climate normal 1961–1990, i.e. 32% of total renewable water resources. In semi-arid and arid regions, mountainous regions, permafrost regions and in the Asian Monsoon region, groundwater recharge accounts for a lower fraction of total runoff, which makes these regions particularly vulnerable to seasonal and inter-annual precipitation variability and water pollution. Average per-capita renewable groundwater resources of countries vary between 8 m3/(capita yr) for Egypt to more than 1 million m3/(capita yr) for the Falkland Islands, the global average in the year 2000 being 2091 m3/(capita yr). Regarding the uncertainty of estimated groundwater resources due to the two precipitation data sets, deviation from the mean is 1.1% for the global value, and less than 1% for 50 out of the 165 countries considered, between 1 and 5% for 62, between 5 and 20% for 43 and between 20 and 80% for 10 countries. Deviations at the grid scale can be much larger, ranging between 0 and 186 mm/yr.

scholarly journals Global-scale modeling of groundwater recharge

2007 ◽  
Vol 4 (6) ◽  
pp. 4069-4124 ◽  
Author(s):  
P. Döll ◽  
K. Fiedler
Keyword(s):  
Water Resources ◽  
Groundwater Recharge ◽  
Arid Regions ◽  
Groundwater Resources ◽  
Global Scale ◽  
Unbiased Estimation ◽  
Data Sets ◽  
Total Runoff ◽  
Semi Arid

Abstract. Long-term average groundwater recharge, which is equivalent to renewable groundwater resources, is the major limiting factor for the sustainable use of groundwater. Compared to surface water resources, groundwater resources are more protected from pollution, and their use is less restricted by seasonal and inter-annual flow variations. To support water management in a globalized world, it is necessary to estimate groundwater recharge at the global scale. Here, we present a best estimate of global-scale long-term average diffuse groundwater recharge (i.e. renewable groundwater resources) that has been calculated by the most recent version of the WaterGAP Global Hydrology Model WGHM (spatial resolution of 0.5° by 0.5°, daily time steps). The estimate was obtained using two state-of-the art global data sets of gridded observed precipitation that we corrected for measurement errors, which also allowed to quantify the uncertainty due to these equally uncertain data sets. The standard WGHM groundwater recharge algorithm was modified for semi-arid and arid regions, based on independent estimates of diffuse groundwater recharge, which lead to an unbiased estimation of groundwater recharge in these regions. WGHM was tuned against observed long-term average river discharge at 1235 gauging stations by adjusting, individually for each basin, the partitioning of precipitation into evapotranspiration and total runoff. We estimate that global groundwater recharge was 12 666 km3/yr for the climate normal 1961–1990, i.e. 32% of total renewable water resources. In semi-arid and arid regions, mountainous regions, permafrost regions and in the Asian Monsoon region, groundwater recharge accounts for a lower fraction of total runoff, which makes these regions particularly vulnerable to seasonal and inter-annual precipitation variability and water pollution. Average per-capita renewable groundwater resources of countries vary between 8 m3/(capita yr) for Egypt to more than 1 million m3/(capita yr) for the Falkland Islands, the global average in the year 2000 being 2091 m3/(capita yr). Regarding the uncertainty of estimated groundwater resources due to the two precipitation data sets, deviation from the mean is less than 1% for 50 out of the 165 countries considered, between 1 and 5% for 62, between 5 and 20% for 43 and between 20 and 80% for 10 countries. Deviations at the grid scale can be much larger, ranging between 0 and 186 mm/yr.

Satellite time series analysis of vegetation dynamics for water resources management in semi-arid regions

2020 ◽  
Author(s):  
Robert Behling ◽  
Sigrid Roessner ◽  
Saskia Foerster
Keyword(s):  
Water Management ◽  
Land Use ◽  
Time Series ◽  
Water Resources ◽  
Water Resources Management ◽  
Vegetation Dynamics ◽  
Arid Regions ◽  
Resources Management ◽  
Semi Arid

<p>One of the consequences of global climate change is the more frequent occurrence of extreme weather conditions. Semi-arid regions are especially vulnerable since evapotranspiration significantly exceeds precipitation for most of the year and rainfall occurrence is dominantly sporadic and highly variable in amount and spatial extent. Consequently, these regions suffer from droughts of increasing duration and severity, occasionally interrupted by strong rainfall events generating high surface runoff and in part highly destructive floods. In semi-arid regions water retention capability is often further reduced by changes of the original vegetation cover due to conversion into farmland and intensification of land use. The result is widespread land degradation by a decrease in permanent vegetation cover and an increase in soil erosion. Under such conditions sustainable water resources management is of key importance, however, reliable long-term observations describing the water cycle and the resulting water budget are missing for many regions of the world. This situation requires new approaches in improving seasonal forecast for relevant water resources parameters as well as spatiotemporally explicit understanding the of influence of water and land use management on the long-term development of water availability and land surface conditions. <br>The German collaborative research project ‘Seasonal water resources management in semi-arid regions: Transfer of regionalized global information to practice’ (SaWaM) aims at the development of methods allowing the use of global data for deriving information needed for regional water resources management in semi-arid regions by integrating meteorological, hydrological and ecosystem sciences and supported by satellite remote sensing analysis. The performance, practical applicability and transferability of the developed methods are assessed in several semi-arid regions including Brazil, Iran and Sudan. Here, we present our work on the analysis of the seasonal and long-term vegetation dynamics at different spatial and temporal scales using satellite time series data of different spatial and temporal resolution (MODIS and Sentinel-2).  Our goal is linking the derived vegetation dynamics to changes in meteorological conditions, water availability and land use. In this context we put emphasis on the spatiotemporal analysis of bioproductivity related to different land use types and climatic conditions to identify and characterize hotspots of water usage in form of irrigated agriculture as a basis for further evaluation of the underlying water management practices.<br>We perform time series analysis of satellite-derived vegetation indices (VI) using various statistical aggregates, such as maximum, mean and temporal duration related to variable time periods (hydrological year, dry and wet season, growing patterns) as well as additive time series decomposition. Thus, we analyze long-term trends, seasonal deviations from long-term average conditions, and break points in the time series related to land use and water management changes. Moreover, we compare the derived spatiotemporal VI dynamics against the dynamics of hydrometeorological conditions (e.g. precipitation, evapotranspiration, temperature) as well as land use patterns in order to evaluate the impact of hydrometeorological drought conditions on different land use types and water management practices.  In conclusion, we present prototypes for information products supporting decision making of the local experts in the target regions.</p>

scholarly journals Groundwater surveys in Developing Regions

2010 ◽  
Vol 3 ◽  
pp. ASWR.S6053
Author(s):  
Jeff Lewis ◽  
Birgitta Liljedahl
Keyword(s):  
Arid Regions ◽  
Groundwater Resources ◽  
Large Area ◽  
Developing Regions ◽  
Well Drilling ◽  
Regional Flow ◽  
Groundwater Aquifer ◽  
Interpretation Patterns ◽  
Hydrogeological Information ◽  
Semi Arid

This paper discusses the interpretation of surface features that can assist in the evaluation of groundwater resources in semi-arid and arid developing regions. The lack of infrastructure in these areas places serious constraints on borehole drilling, which in turn limits the data which can be obtained directly from the subsurface. Under these conditions, surface indicators may be used to infer useful information about the subsurface, which includes shallow aquifers. This article summarizes those surface indicators which provide useful data in arid and semi-arid regions and provides a review of the literature to assist in their interpretation. Patterns of surface indicators covering a large area may be more effective and less costly for interpreting basic regional hydrogeological conditions than detailed data obtained from a limited number of boreholes. The hydrogeological information which can be obtained by using the methods discussed in this article include the regional flow patterns, an estimate of the depth to groundwater, aquifer geology and estimates of the regional recharge and discharge zones. This data may in turn provide support for subsequent well drilling campaigns, limited environmental assessments, and potable water assessments for humanitarian base camps in developing regions.

scholarly journals Is Annual Recharge Coefficient a Valid Concept in Arid and Semi-Arid Region?

2017 ◽  
Author(s):  
Yiben Cheng ◽  
Hongbin Zhan ◽  
Wenbin Yang ◽  
Hongzhong Dang ◽  
Wei Li
Keyword(s):  
Arid Regions ◽  
Groundwater Resources ◽  
Heavy Precipitation ◽  
Annual Precipitation ◽  
Precipitation Event ◽  
Precipitation Pattern ◽  
Deep Soil ◽  
Bare Sand ◽  
Sand Land ◽  
Semi Arid

Abstract. Deep soil recharge (DSR) (at depth more than 200 cm) is an important part of water circulation in arid and semi-arid regions. Quantitative monitoring of DSR is of great importance to assess water resources and study water balance in arid and semi-arid regions. Simple estimates of recharge based on fixed fractions of annual precipitation are misleading because they do not reflect the plant and soil factors controlling recharge. This study used a typical bare land on the Eastern margin of Mu Us Sandy Land of China an example to illustrate a new lysimeter method of measuring DSR underneath bare sand land in arid and semi-arid regions. Positioning monitoring was done on precipitation and DSR measurement underneath mobile sand dunes from 2013 to 2015 in the study area. Results showed that use of a constant recharge coefficient for estimating DSR in bare sand land in arid and semi-arid regions is questionable and could lead to considerable errors. It appeared that DSR in those regions was influenced by precipitation pattern, and was closely correlated with spontaneous heavy precipitation (defined for an event with more than 10 mm precipitation) other than the average precipitation strength. This study showed that as much as 42 % of precipitation in a single heavy precipitation event can be transformed into DSR. During the observation period, the maximum annual DSR could make up to 24.33 % of the annual precipitation. This study provided a reliable method of estimating DSR in sandy area of arid and semi-arid regions, which is valuable for managing groundwater resources and ecological restoration in those regions.

scholarly journals Extreme rainfall deficits were not the cause of recurring colonial era famines of southern Indian semi-arid regions

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ranjini Ray ◽  
Atreyee Bhattacharya ◽  
Gaurav Arora ◽  
Kushank Bajaj ◽  
Keyle Horton ◽  
...  
Keyword(s):  
Arid Regions ◽  
Human Impacts ◽  
Rainfall Variability ◽  
Extreme Rainfall ◽  
Southern India ◽  
Colonial Era ◽  
Regional Rainfall ◽  
Semi Arid ◽  
Rainfall Deficits

AbstractUsing information contained in the eighteenth to twentieth century British administrative documents, preserved in the National Archives of India (NAI), we present a 218-year (1729–1947 AD) record of socioeconomic disruptions and human impacts (famines) associated with ‘rain failures’ that affected the semi-arid regions (SARs) of southern India. By mapping the southern Indian famine record onto long-term spatiotemporal measures of regional rainfall variability, we demonstrate that the SARs of southern India repeatedly experienced famines when annual rainfall reduced by ~ one standard deviation (1 SD), or more, from long-term averages. In other words, ‘rain failures’ listed in the colonial documents as causes of extreme socioeconomic disruptions, food shortages and human distress (famines) in the southern Indian SARs were fluctuations in precipitation well within the normal range of regional rainfall variability and not extreme rainfall deficits (≥ 3 SD). Our study demonstrates that extreme climate events were not necessary conditions for extreme socioeconomic disruptions and human impacts rendered by the colonial era famines in peninsular India. Based on our findings, we suggest that climate change risk assessement should consider the potential impacts of more frequent low-level anomalies (e.g. 1 SD) in drought prone semi-arid regions.

scholarly journals Annual amount of renewable transboundary groundwater resources per capita

2017 ◽  
Author(s):  
Chloé Meyer
Keyword(s):  
Groundwater Recharge ◽  
Groundwater Resources ◽  
Per Capita ◽  
Annual Amount

Calculated as the long-term mean transboundary groundwater recharge, including man-made components, divided by the number of inhabitants of the area occupied by the aquifer. Indicator is expressed in m3/yr/capita Groundwater Population Recharge Transboundary

scholarly journals Soil salinization under different climate change scenarios: A global scale analysis

2021 ◽  
Author(s):  
Nima Shokri ◽  
Amirhossein Hassani ◽  
Adisa Azapagic
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Soil Salinity ◽  
Global Scale ◽  
Soil Salinization ◽  
Water Evaporation ◽  
Climate Change Scenarios ◽  
Spatio Temporal ◽  
Salt Affected Soils

<p>Population growth and climate change is projected to increase the pressure on land and water resources, especially in arid and semi-arid regions. This pressure is expected to affect all driving mechanisms of soil salinization comprising alteration in soil hydrological balance, sea salt intrusion, wet/dry deposition of wind-born saline aerosols — leading to an increase in soil salinity. Soil salinity influences soil stability, bio-diversity, ecosystem functioning and soil water evaporation (1). It can be a long-term threat to agricultural activities and food security. To devise sustainable action plan investments and policy interventions, it is crucial to know when and where salt-affected soils occur. However, current estimates on spatio-temporal variability of salt-affected soils are majorly localized and future projections in response to climate change are rare. Using Machine Learning (ML) algorithms, we related the available measured soil salinity values (represented by electrical conductivity of the saturated paste soil extract, EC<sub>e</sub>) to some environmental information (or predictors including outputs of Global Circulation Models, soil, crop, topographic, climatic, vegetative, and landscape properties of the sampling locations) to develop a set of data-driven predictive tools to enable the spatio-temporal predictions of soil salinity. The outputs of these tools helped us to estimate the extent and severity of the soil salinity under current and future climatic patterns at different geographical levels and identify the salinization hotspots by the end of the 21<sup>st</sup> century in response to climate change. Our analysis suggests that a soil area of 11.73 Mkm<sup>2</sup> located in non-frigid zones has been salt-affected in at least three-fourths of the 1980 - 2018 period (2). At the country level, Brazil, Peru, Sudan, Colombia, and Namibia were estimated to have the highest rates of annual increase in the total area of soils with an EC<sub>e</sub> ≥ 4 dS m<sup>-1</sup>. Additionally, the results indicate that by the end of the 21<sup>st</sup> century, drylands of South America, southern and Western Australia, Mexico, southwest United States, and South Africa will be the salinization hotspots (compared to the 1961 - 1990 period). The results of this study could inform decision-making and contribute to attaining the United Nation’s Sustainable Development Goals for land and water resources management.</p><p>1. Shokri-Kuehni, S.M.S., Raaijmakers, B., Kurz, T., Or, D., Helmig, R., Shokri, N. (2020). Water Table Depth and Soil Salinization: From Pore-Scale Processes to Field-Scale Responses. Water Resour. Res., 56, e2019WR026707. https://doi.org/ 10.1029/2019WR026707</p><p>2. Hassani, A., Azapagic, A., Shokri, N. (2020). Predicting Long-term Dynamics of Soil Salinity and Sodicity on a Global Scale, Proc. Nat. Acad. Sci., 117, 52, 33017–33027. https://doi.org/10.1073/pnas.2013771117</p>

scholarly journals Survey of ancient water technologies in semi-arid and arid regions: traditional knowledge for the future

2017 ◽  
Vol 17 (5) ◽  
pp. 1278-1286 ◽  
Author(s):  
Larry W. Mays
Keyword(s):  
Water Resources ◽  
Traditional Knowledge ◽  
Arid Regions ◽  
Poor People ◽  
Water Shortages ◽  
The Poor ◽  
The World ◽  
Sustainability Problems ◽  
Semi Arid ◽  
Water Resources Sustainability

There are many people on Earth today that live with severe water shortages and severe lack of sanitation, particularly among the poor. These people for the most part do not understand the knowledge base of methodologies of harvesting and conveying water and sanitation methods that have been around for thousands of years. A survey of ancient water technologies used in semi-arid and arid regions is presented in this paper. The survey will include methodologies used by Mesopotamians, the Persians, the Egyptians, and the Nabataeans. The attempt here is to explore how these traditional methods developed by the ancients in semi-arid and arid regions of the world could possibly be used to help solve the present-day water resources sustainability problems, especially in developing parts of the world. The advantages of the traditional knowledge of ancient water technologies are explored with the goal of determining ways to help poor people with water shortages and sanitation.

Sign in / Sign up

Export Citation Format

Share Document