Evaluation of water‐use policies for baseflow recovery during droughts in an agricultural intensive karst watershed: Case study of the lower Apalachicola–Chattahoochee–Flint River Basin,southeastern United States

The lower Apalachicola–Chattahoochee–Flint River Basin in the Southeast United States represents a major agricultural area underlain by the highly productive karstic Upper Floridan aquifer (UFA). During El Niño Southern Oscillation‐induced droughts, intense groundwater withdrawal for irrigation lowers streamflow in the Flint River due to its hydraulic connectivity with the UFA and threatens the habitat of the federally listed and endangered aquatic biota. This study assessed the compounding hydrologic effects of increased irrigation pumping during drought years (2010–2012) on stream–aquifer water exchange (stream–aquifer flux) between the Flint River and UFA using the United States Geological Survey modular finite element groundwater flow model. Principal component and K‐means clustering analyses were used to identify critical stream reaches and tributaries that are adversely affected by irrigation pumping. Additionally, the effectiveness of possible water restriction scenarios on stream–aquifer flux was also analysed. Moreover, a cost–benefit analysis of acreage buyout procedure was conducted for various water restriction scenarios. Results indicate that increased groundwater withdrawal in Water Year 2011 decreased baseflow in the lower Apalachicola–Chattahoochee–Flint River Basin, particularly, in Spring Creek, where irrigation pumping during April, June, and July changed the creek condition from a gaining to losing stream. Results from sensitivity analysis and simulated water restrictions suggest that reducing pumping in selected sensitive areas is more effective in streamflow recovery (approximately 78%) than is reducing irrigation intensity by a prescribed percentage of current pumping rates, such as 15% or 30%, throughout the basin. Moreover, analysis of acreage buyout indicates that restrictions on irrigation withdrawal can have significant impacts on stream–aquifer flux in the Basin, especially in critical watersheds such as Spring and Ichawaynochaway Creeks. The proposed procedure for ranking of stream reaches (sensitivity analysis) in this study can be replicated in other study areas/models. This study provides useful information to policymakers for devising alternate irrigation water withdrawal policies during droughts for maintaining flow levels in the study area.     

Runoff generation mechanisms in pastures of the Sand Mountain region of Alabama—a field investigation

Excessive application of poultry litter to pastures in the Sand Mountain region of north Alabama has resulted in phosphorus (P) contamination of surface water bodies and buildup of P in soils of this region. Since surface runoff is recognized as the primary mechanism of P transport, understanding surface runoff generation mechanisms are crucial for alleviating water quality problems in this region. Identification of surface runoff generation mechanisms is also important for delineation of hydrologically active areas (HAAs). Therefore, the specific objective of this study was to identify surface runoff generation mechanisms (infiltration excess versus saturation excess) using distributed surface and subsurface sensors and rain gauge. Results from three rainfall events (2·13–3·43 cm) of differing characteristics, and sensor data at four locations with differing soil hydraulic properties along the hillslope showed that the main surface runoff generation mechanism in this region is infiltration excess. Because of this, rainfall intensity and soil hydraulic conductivity were found to play dominant roles in surface runoff generation in this region. Further, only short periods of a few rainfall events during which the rainfall intensity is high produce surface runoff. This study indicates that perhaps subsurface flows and transport of P in subsurface flows need to be quantified to reduce P contamination of surface water bodies in this region. Current studies at this location are identifying spatial and temporal distribution of HAAs, quantifying rainfall characteristics that generate runoff, and estimating runoff volume that results from connected HAAs. Copyright © 2008 John Wiley & Sons, Ltd.     

Characterization and prediction of stormwater runoff quality in sub-tropical rural catchments

Due to scarcity of local data on stormwater pollution levels and rainfall-runoff generation process, very few attempts have been made towards the management of stormwater in sub-tropical rural catchments. An attempt has been made in the present study to characterize and predict the stormwater runoff characteristics using regression modeling from five rural catchments in north-west India. Stormwater samples and flow data were collected from 75 storm events. Samples were analyzed for pH, total suspended solids (TSS), 5-day biochemical oxygen demand (BOD₅), chemical oxygen demand (COD), total kjeldhal nitrogen (TKN), total phosphorous (TP), nitrate-nitrogen (NO ₃ ^- –N), total coliform count (TC), fecal coliform count (FC), Zn, Cu and Fe. It was found that size of the catchment and the land use practices influenced the stormwater quality even in predominantly rural areas, otherwise thought to be homogeneous. The results obtained were related with the antecedent dry days (ADD) and average rainfall. ADD was found to be positively correlated with pollutant loads whereas average rainfall showed negative correlation. The study highlights the importance of ADD in causing greater mean pollutant concentrations except for TKN, TP and NO ₃ ^- –N. Regression models were developed for the studied catchments to estimate mean pollutant concentrations as a function of rainfall variables. Results revealed that measured pollutant concentrations demonstrated high variability with ADD and average rainfall in small rural catchments, whereas in large catchments, factors like land use, extent of imperviousness etc. resulted in low predictability of measured parameters.     

Probabilistic assessment of projected climatological drought characteristics over the Southeast USA

The study makes a probabilistic assessment of drought risks due to climate change over the southeast USA based on 15 Global Circulation Model (GCM) simulations and two emission scenarios. The effects of climate change on drought characteristics such as drought intensity, frequency, areal extent, and duration are investigated using the seasonal and continuous standard precipitation index (SPI) and the standard evapotranspiration index (SPEI). The GCM data are divided into four time periods namely Historical (1961–1990), Near (2010–2039), Mid (2040–2069), and Late (2070–2099), and significant differences between historical and future time periods are quantified using the mapping model agreement technique. Further, the kernel density estimation approach is used to derive a novel probability-based severity-area-frequency (PBS) curve for the study domain. Analysis suggests that future increases in temperature and evapotranspiration will outstrip increases in precipitation and significantly affect future droughts over the study domain. Seasonal drought analysis suggest that the summer season will be impacted the most based on SPI and SPEI. Projections based on SPI follow precipitation patterns and fewer GCMs agree on SPI and the direction of change compared to the SPEI. Long-term and extreme drought events are projected to be affected more than short-term and moderate ones. Based on an analysis of PBS curves, especially based on SPEI, droughts are projected to become more severe in the future. The development of PBS curves is a novel feature in this study and will provide policymakers with important tools for analyzing future drought risks, vulnerabilities and help build drought resilience. The PBS curves can be replicated for studies around the world for drought assessment under climate change.     

Effect of irrigation pumpage during drought on karst aquifer systems in highly agricultural watersheds: example of the Apalachicola-Chattahoochee-Flint river basin,southeastern USA

In the Apalachicola-Chattahoochee-Flint (ACF) river basin in Alabama, Georgia, and Florida (USA), population growth in the city of Atlanta and increased groundwater withdrawal for irrigation in southwest Georgia are greatly affecting the supply of freshwater to downstream regions. This study was conducted to understand and quantify the effect of irrigation pumpage on the karst Upper Floridan Aquifer and river–aquifer interactions in the lower ACF river basin in southwest Georgia. The groundwater MODular Finite-Element model (MODFE) was used for this study. The effect of two drought years, a moderate and a severe drought year, were simulated. Comparison of the results of the irrigated and non-irrigated scenarios showed that groundwater discharge to streams is a major outflow from the aquifer, and irrigation can cause as much as 10 % change in river–aquifer flux. The results also show that during months with high irrigation (e.g., June 2011), storage loss (34 %), the recharge and discharge from the upper semi-confining unit (30 %), and the river–aquifer flux (31 %) are the major water components contributing towards the impact of irrigation pumpage in the study area. A similar scenario plays out in many river basins throughout the world, especially in basins in which underlying karst aquifers are directly connected to a nearby stream. The study suggests that improved groundwater withdrawal strategies using climate forecasts needs to be developed in such a way that excessive withdrawals during droughts can be reduced to protect streams and river flows.     

Spatiotemporal variability of meteorological droughts in southeastern USA

Droughts in the southeast USA have been linked to economic losses and intractable water conflicts. The region has witnessed several severe droughts events during the period from 1901 to 2005. In this study, spatiotemporal variability in meteorological drought characteristics in the southeast were analyzed using two different datasets by the means of standard precipitation index and standard precipitation evapotranspiration index for the period 1901–2005 for agricultural and non-agricultural seasons. The study periods were divided into three epochs 1901–1935, 1936–1970, and 1971–2005 and drought characteristics, in terms of severity, frequency, number, and trends were analyzed. Additionally, areal extent, drought severities and return periods associated with three severe drought years 1904, 1954, and 2000 were analyzed. Except for the state of Florida, results indicate decrease in drought severity during the recent epoch of 1970–2005 in the study domain. Trend analysis confirms that the study domain has become wetter over the last 105 years. Wetting trends were more prominent in the agricultural season. Additionally, droughts seem to have migrated from the western part of the study area encompassing the states of Alabama, Tennessee, Louisiana, and Mississippi to the Florida panhandle region during the recent epoch. Droughts exhibited higher spatiotemporal variability during the agricultural season compared to the non-agricultural seasons. Results also showed that early to mid-1950s experienced some of the most severe droughts in the study domain. Some of the drought events, such as the drought of 1954 and 2000, have been equivalent to a 100-year drought event in the southeast. The results from this study form the benchmark for studying the impacts of future climate change projections on meteorological droughts in the southeast.     

Hydrologic simulation approach for El Niño Southern Oscillation (ENSO)-affected watershed with limited raingauge stations

ABSTRACT

Since the performance of hydrological models relies on numerous factors, the selection of an appropriate modeling approach for hydrological study has always been a crucial issue. The major objective of this research is to demonstrate that data-driven models such as the Adaptive Neuro-Fuzzy Inference system (ANFIS) are more suitable in a region where spatially distributed precipitation datasets are not available. Since precipitation has a teleconnection with the El Niño Southern Oscillation (ENSO) in different parts of the world, the sea surface temperatures (SSTs) and sea level pressures (SLPs) of the equatorial Pacific can be expected to act as surrogates for the precipitation if there are insufficient raingauge stations in the watershed. Moreover, in contrast to conceptual and physically-based models, data driven models can incorporate SST and SLP in their input vectors, and hence additional forcing of SST with precipitation has been experimented with in past studies. Therefore, our second objective is to test whether the additional forcing of SST and SLP will improve the hydrologic simulation. For this, various ANFIS models for the winter season were developed considering 10 raingauge stations situated at various locations in the watershed. Rainfall from each raingauge station was considered in the ANFIS model one at a time with and without SST/SLP. The results show that the performance of the ANFIS model improved with the additional fusion of SST and SLP, especially when a raingauge station from a remote location was considered. However, this improvement was observed when the analysis was primarily focused on the winter season which is a period with a strong ENSO signal.

Editor D. Koutsoyiannis Associate editor L. See