Rational Management Of Water Resources Research Articles

Analyzing the driving mechanisms of grain virtual water flow based on the case of China's main grains

To define the complicated driving mechanisms of virtual water flow (VWF) in China's main grains production, this study firstly uses the entropy method and a K-means clustering approach to classify the driving types of VWF based on the data from 31 provinces in the mainland of China, and then applies the PLS structural equation model to analyze the driving mechanisms of VWF in four representative provinces or municipalities(Zhejiang, Heilongjiang, Xinjiang and Shanghai)selected by the classified driving types. The results show that the driving types of VWF can be divided into four types, namely, ecology-economy, ecology-environment, ecology-water use, and comprehensive type. In the four typical regions at provincial level, the social factors directly affect the VWF, and reversely it has a direct impact on the nature, environment and economy of the above four regions. In particular, the water use has a direct impact on the VWF in Heilongjiang attached to the ecologic-environmental type. The findings of this paper manifest that the social indicators rather than the indicators in water use play an important role in the VWF, that is, our findings further testify the status quo of China's VWF: the regions with rich water resources import the virtual water while the regions with poor water resources export the virtual water. Finally, for promoting the rational flow of virtual water we propose some corresponding adjustment countermeasures and suggestions that provide a theoretical basis for the rational allocation and management of water resources.

Calculation of targeted eco-environmental water requirements in a dry inland river: a case study of the Yarkand River Basin, Xinjiang, China

Analysis of eco-environmental water requirements along a dry inland river under extreme drought conditions can provide a theoretical basis for the sustained utilization and management of water resources in arid regions. This paper uses the Yarkand River Basin in Xinjiang, China, as a case study to determine and assess a method to calculate targeted eco-environmental water requirements (TEEWR) for different ranges of ecological protection of inland riparian forests. The proposed method is intended to comprehensively analyze the water resources along arid inland rivers. Specifically, the ranges of ecological protection were gradually expanded at intervals of 1 km (or multiples of the smallest distance) away from the river course while the TEEWR was determined as a function of the ecological water demand of riparian forest vegetation (Yec) and its corresponding river loss (Xloss). The developed method was shown to be feasible for analyzing TEEWR in the Yarkand River Basin and thus provides a novel and effective approach for the rational utilization and management of water resources in inland river basins in arid regions.Article HighlightsZones of ecological protection were gradually expanded at intervals of 1 km (or multiples of the smallest distance) away from the river course on both sides of the dry inland riverThe targeted eco-environmental water requirement, defined as the ecological water demand of riparian forest vegetation (Yec) and its corresponding river loss (Xloss), was determined for a dry inland river basinThe developed methods for calculating targeted eco-environmental water requirements are useful, but have limitations.

Spatiotemporal variation in groundwater level within the Manas River Basin, Northwest China: Relative impacts of natural and human factors

Abstract The Manas River Basin (MRB), Northwest China, is an arid basin dependent on irrigation for agriculture, and human activities are believed to be the primary factor affecting the groundwater level fluctuations in this basin. Such fluctuations can have a significant adverse impact on the social economy, agricultural development, and natural environment of that region. This raises concerns regarding the sustainability of groundwater use. In this study, we used ArcGIS spatial interpolation and contrast coefficient variance analysis to analyse groundwater level, land-use change, and water resource consumption patterns from 2012 to 2019 in the plains of the MRB. The aim was to determine the main factors influencing the groundwater level and to provide a scientific basis for the rational development, utilisation, and management of water resources in this area. During the study period, the groundwater level decreased, increased, and then fluctuated with a gradually slowing downward trend; the decline ranged from −17.82 to −11.67 m during 2012–2019. Within a given year, groundwater levels declined from March/April to August/September, then rose from August/September to March/April, within a range of 0.29–19.05 m. Primary factors influencing the groundwater level included human activities (e.g., changes in land use, river regulation, irrigation, and groundwater exploitation) and natural causes (e.g., climate and weather anomalies). Human activities were the primary factors affecting groundwater level, especially land-use change and water resource consumption. These results provide a theoretical basis for the rational exploitation of groundwater and the optimisation of water resource management in this region.

How Climate Change and Land Use/Land Cover Change Affect Domestic Water Vulnerability in Yangambi Watersheds (D. R. Congo)

In the tropics, the domestic water supply depends principally on ecosystem services, including the regulation and purification of water by humid, dense tropical forests. The Yangambi Biosphere Reserve (YBR) landscape is situated within such forests in the Democratic Republic of Congo (DRC). Surprisingly, given its proximity to the Congo River, the YBR is confronted with water issues. As part of its ecosystem function, the landscape is expected to reduce deterioration of water quality. However, environmental consequences are increasing due to conversion of its dense forest into other types of land use/land cover (LULC) in response to human activities. It is therefore important to check how the physicochemical quality parameters of water resources are influenced by landscape parameters—and to know if the population can adapt to this water vulnerability. To do this, we analyzed the watershed typology (including morphometric and LULC characteristics) and the physical and chemical parameters of water within the principal watershed’s rivers. We also analyzed data from surveys and the Yangambi meteorological station. We found that some landscape indices related to LULC significantly influence water quality deterioration in Yangambi. On average, each person in the Yangambi landscape uses 29–43 liters of water per day. Unfortunately, this falls short of World Health Organization standards regarding some parameters. The best fitted simple linear regression model explains the variation in pH as a function of edge density of perturbed forest, edge density of crop land and patch density of dense forest up to 94%, 92% and 90%, respectively. While many researchers have identified the consequences of climate change and human activities on these water resources, the population is not well-equipped to deal with them. These results suggest that water management policies should consider the specificities of the Yangambi landscape in order to develop better mitigation strategies for a rational management of water resources in the YBR in the context of climate change.

Improving water resources management in the irrigated zone of the Aral Sea region

One of the most important objectives in the world is to improve rational water resources management methods. In this regard, the rational management of water resources and optimal water resources distribution, especially on on-farm systems, are considered very important. In this direction, given the negative consequences that have developed over the past more than 40 years in the lower reaches of the Amu Darya River, the need to improve the methods of effective management of water resources in the Aral Sea basin is urgent.

Challenges in the Development of Hydropower in Selected European Countries

Hydropower in Europe is playing an increasingly important role as a renewable source of energy. Its share of the final energy consumption varies from country to country, posing different challenges in each. The European Union member states are obliged, according to energy policy, to increase the share of renewable energy. This article presents the challenges related to the development of hydropower in four countries with different shares of domestic electricity production from hydropower plants: Albania (100% share in 2019), Slovenia (25.7%), Poland (1.1%), and Estonia (0.3%). Particular attention is paid to the issues of rational management of water resources in connection to Europe’s energy policy. As a result of the case study analysis, the challenges in the development of hydropower are identified, as well as ways to solve them. In addition, a comprehensive analysis of the impact of social, economic, environmental and climate change factors on the development of hydropower was conducted. At present, whether the assumed goals of the European Union’s energy policy will be achieved is impossible to determine for the whole of Europe. Achieving these goals will be possible only after individual countries prepare comprehensive reports on the topics of renewable energy sources, including hydropower.

Integrating the InVEST and SDSM Model for Estimating Water Provision Services in Response to Future Climate Change in Monsoon Basins of South China

An assessment of how future climate change will impact water provision services is important for formulating rational water resources management and development strategies as well as for ecosystem protection. The East Asian monsoon is an important component of the Asian climate and its changes affect the climate in East Asia and seriously affect the provision of water services. In this study, through the coupling of the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and Statistical Downscaling Technique Model (SDSM), we evaluated the impact of future climate change on water provisions in a typical East Asian monsoon basin of South China. The results demonstrate the applicability of the InVEST model combined with the SDSM model over the East Asian monsoon river basins. Under representative concentration pathway 4.5 scenario (RCP4.5), the annual average maximum and minimum temperatures would continually increase far into the future (2080–2095). However, the maximum and minimum temperatures slightly decreased under representative concentration pathway 2.6 scenario (RCP2.6) in the far future (2080–2095). The annual average precipitation and reference evapotranspiration experienced slight but steady increasing trends under the RCP2.6 and RCP4.5 scenarios. Based on the InVEST model simulation, annual average water yield would increase by 19.3% (33.5%) far in the future (2080–2095) under RCP2.6 (4.5) scenario. This study provides a valuable reference for studying future climate change impacts on water provisions in East Asian monsoon basins.

Impact of Population Growth and Climate Change on the Resilience of Florina’s Hydrosystem

This research work deals with an integrated assessment regarding a hydrosystem’s resilience under changing conditions. Particularly, the analysis is performed for Florina, a rural area in Northern Greece. In Florina, four reservoirs operate to meet water requirements for agriculture and industrial use, as well as, to satisfy the urban water demand of the local population. The analysis initially includes the hydrologic simulation of the natural system that is achieved by developing and implementing a hydrologic model on a monthly basis, using the available historic data for the region. It also incorporates the development of the reservoirs’ monthly water balance models to assess the reliability of the system based on the current water requirements and the historic datasets. In terms of rational water resources management under changing conditions, various combinations are investigated; all of which are based on four main scenarios (i.e., zero, three climate change scenarios, population growth scenario, scenarios regarding different distribution of irrigation water). The comparison among the aforementioned scenarios is finally shown through the variation in the hydrosystem’s reliability to meet water demands. Results show that each reservoir presents its own behavior with respect to its particular technical characteristics and the scenario performed. In general, reliability decreases, while, the implementation of the scenarios that introduce different practices regarding water distribution for irrigation showed that this practice can ensure a relatively higher reliability to the local hydrosystem

Variations of Stable Oxygen and Deuterium Isotopes in River and Lake Waters During Flooding Season Along the Middle and Lower Reaches of the Yangtze River Regions

Stable isotope tracers have been widely applied to water sources and evolution, transforming relations, and pollution sources of various water bodies. This study analyzed the spatial variations of δ2H and δ18O in river and lake waters during flooding season, and revealed the factors underlying their variations along the middle and lower reaches of the Yangtze River based on a field sampling campaign in July 2018. Our results showed that δ2H and δ18O in the Yangtze River water were enriched from the Three Gorges reservoir region to the lower reaches of the Yangtze River, which was closely linked to isotopic variations in precipitation. There was no significant difference in δ2H and δ18O values in the mainstream river waters between the Three Gorges Reservoir Region and Yichang-Chenglingji. However, d-excess values in river water displayed a small variation range. In contrast, δ2H and δ18O values in the lake group from Dongting to Jianghan and Huayang to Poyang Lake were lower than in the lake group from Taihu to the Yangtze Delta. Negative d-excess values were observed in lake water from Taihu to the Yangtze Delta, suggesting the combined influence of enriched isotopic compositions in precipitation and strong evaporative enrichment. Of the lakes, the highest isotopic values were found in Dianshan Lake and Datong Lake, whereas the lowest isotopic values were recorded in Dongting Lake and Poyang Lake because of their direct connection with the Yangtze River. The water regimes of Dongting Lake and Poyang Lake were influenced by the Yangtze River, especially when a high water level of the Yangtze River occurred, and thus altered the isotopic compositions of Dongting Lake and Poyang Lake water. Hence, these findings will provide scientific data revealing the precipitation-river-lake interactions and investigating the rational utilization and management of water resources in the middle and lower reaches of the Yangtze River regions.

Climate indicators of changes in hydrological characteristics (a case of the Psyol river basin)

Formulation of the problem. A national climate program, complying with the Association Agreement between Ukraine and the EU, is aimed at long-term adaptation measures to climate change, providing for the development of legislation in the field of environmental protection, sectoral strategies, improving air and water quality. These measures require identification of climatic factors’ impact on hydrological characteristics of water bodies in any area in order to protect and improve them, as well as a comprehensive approach to the rational management of water resources. Analysis of previous research. Using mathematical models of atmospheric circulation allows us to obtain generalized calculations of the average global and regional air temperature, characterized by significant errors in case of different models. Problems of further research. Modern changes in climatic conditions in Ukraine are characterized by locality and rapidity: increasing number of anomalous atmospheric phenomena, frequency of droughts, dry winds which, according to preliminary estimates, may lead to reduction of water resources, changes in internal annual redistribution of water temperature and runoff against the background of increasing thermal resources of the territory. The purpose. The article analyses climatic indicators’ influence on the main hydrological characteristics on the example of the Psyol river basin within Ukraine. Research methods. Research methods are presented by statistical and cartographic analysis (correlation analysis method). The initial information is the results of observations contained in the State Climate Cadastre and the State Water Cadastre for the Dnieper Valley. Presentation of the main research material. Analysis of climate change in the Psyol river basin indicates a decrease in water consumption, both in the main river of the basin and in its main tributaries. In addition to changes in temperature and humidity, the reasons for this process were the shifts that occurred in the nature of the intra-annual distribution of the runoff. During the late XX – early XXI century the share of spring floods decreased due to the reduced period of ice phenomena and corresponding decrease in the thickness of the snow cover on the rivers. As a result, the most important component of the annual runoff of rivers began to decrease rapidly. The role of groundwater in the formation of water runoff increased against the background of a predominant decrease in precipitation. This is especially true for medium-size and small rivers, subject to significant anthropogenic pressure: over-regulation of channels, creation of artificial lakes, their shallowing. Practical value. Based on the main provisions of the national environmental policy of Ukraine on the use of water resources and the implementation of European principles of the Water Framework Directive 2000/60 / EC (ERVD) the study of changes in hydrological regime of rivers is of practical importance for sustainable management. Research results. The study of the impact of changes in climatic indicators on hydrological characteristics makes it possible to determine the reference conditions and classes of ecological status of rivers under conditions of anthropogenic pressure against the background of further changes in climatic indicators that will have different trends.

Impact of cities adaptation to climate change on water resources management on the example of selected cities of the Silesian Agglomeration

Climate change and the resulting threats create a new challenge for local authorities and residents of cities. The nationwide Project addressed for biggest Polish cities assessed their sensitivity and counteracting capabilities in selected urban areas. Within the Project various actions were proposed. To some extent, the implementation of these activities may, however, threaten the water resources. The paper presents risk assessment and shows the possibilities of rational management of water resources in selected cities of Upper Silesia.

Quantitative estimation of wastewater quality parameters by hyperspectral band screening using GC, VIP and SPA.

Water pollution has been hindering the world’s sustainable development. The accurate inversion of water quality parameters in sewage with visible-near infrared spectroscopy can improve the effectiveness and rational utilization and management of water resources. However, the accuracy of spectral models of water quality parameters is usually prone to noise information and high dimensionality of spectral data. This study aimed to enhance the model accuracy through optimizing the spectral models based on the sensitive spectral intervals of different water quality parameters. To this end, six kinds of sewage water taken from a biological sewage treatment plant went through laboratory physical and chemical tests. In total, 87 samples of sewage water were obtained by adding different amount of pure water to them. The raw reflectance (Rraw) of the samples were collected with analytical spectral devices. The Rraw-SNV were obtained from the Rraw processed with the standard normal variable. Then, the sensitive spectral intervals of each of the six water quality parameters, namely, chemical oxygen demand (COD), biological oxygen demand (BOD), NH3-N, the total dissolved substances (TDS), total hardness (TH) and total alkalinity (TA), were selected using three different methods: gray correlation (GC), variable importance in projection (VIP) and set pair analysis (SPA). Finally, the performance of both extreme learning machine (ELM) and partial least squares regression (PLSR) was investigated based on the sensitive spectral intervals. The results demonstrated that the model accuracy based on the sensitive spectral ranges screened through different methods appeared different. The GC method had better performance in reducing the redundancy and the VIP method was better in information preservation. The SPA method could make the optimal trade-offs between information preservation and redundancy reduction and it could retain maximal spectral band intervals with good response to the inversion parameters. The accuracy of the models based on varied sensitive spectral ranges selected by the three analysis methods was different: the GC was the highest, the SPA came next and the VIP was the lowest. On the whole, PLSR and ELM both achieved satisfying model accuracy, but the prediction accuracy of the latter was higher than the former. Great differences existed among the optimal inversion accuracy of different water quality parameters: COD, BOD and TN were very high; TA relatively high; and TDS and TH relatively low. These findings can provide a new way to optimize the spectral model of wastewater biochemical parameters and thus improve its prediction precision.

Agriwater: An R package for spatial modelling of energy balance and actual evapotranspiration using satellite images and agrometeorological data

Aiming to subsidize the rational water resources management, an R package called “agriwater” was created in order to obtain the energy balance on the soil and actual evapotranspiration using satellite imagery and agrometeorological data. This package apply the Simple Algorithm for Evapotranspiration Retrieving - SAFER to calculate the evapotranspiration fraction ETr (or ETAET0−1), actual evapotranspiration (ETA) and latent heat flux (λE); the Slob equation calculate the net radiation (RN); ground heat flux (G) is modeled from RN; and the sensible heat flux (H) is retrieved as the residue of the energy balance equation. Landsat-8 (with and without thermal bands), Sentinel-2 and MODIS digital images can be used. Results are presented in raster format and can be post-processed by GIS analysis or anothers R procedures. A study case using Sentinel-2 images and agrometeorological data of a semiarid area from Brazil was performed. The requirements and conditions for use of the package are explained.

Research on soil moisture prediction model based on deep learning.

Soil moisture is one of the main factors in agricultural production and hydrological cycles, and its precise prediction is important for the rational use and management of water resources. However, soil moisture involves complex structural characteristics and meteorological factors, and it is difficult to establish an ideal mathematical model for soil moisture prediction. Existing prediction models have problems such as prediction accuracy, generalization, and multi-feature processing capability, and prediction performance must improve. Based on this, taking the Beijing area as the research object, the deep learning regression network (DNNR) with big data fitting capability was proposed to construct a soil moisture prediction model. By integrating the dataset, analyzing the time series of the predictive variables, and clarifying the relationship between features and predictive variables through the Taylor diagram, selected meteorological parameters can provide effective weights for moisture prediction. Test results prove that the deep learning model is feasible and effective for soil moisture prediction. Its’ good data fitting and generalization capability can enrich the input characteristics while ensuring high accuracy in predicting the trends and values of soil moisture data and provides an effective theoretical basis for water-saving irrigation and drought control.

TRATAMENTO DE ESGOTO DOMÉSTICO A PARTIR DO SISTEMA LEITO DE RAÍZES: EXPERIÊNCIA EM UMA PEQUENA COMUNIDADE RURAL DO SEMIÁRIDO BRASILEIRO.

O presente artigo aborda de forma sucinta a necessidade do manejo racional dos recursos hídricos e manejo ecológico da água no Semiárido Brasileiro, a partir da experiência de uma atividade extensionista na Escola Família Agrícola de Colônia, Itaetê-BA (EFACI), com o objetivo principal de realizar a instalação e operação de uma unidade experimental de tratamento de efluentes domésticos, por meio da técnica leito de raízes. Nesta etapa da pesquisa procedeu-se metodologicamente a execução de oficinas de capacitação com enfoque no planejamento ambiental participativo, manejo da água e do solo, bem como o tratamento de águas servidas, trabalhos de campo, com intuito de apresentar/compartilhar conteúdos técnicos e proporcionar a integração destes conhecimentos científicos com os saberes tradicionais da comunidade.

Machine Learning Models for Spring Discharge Forecasting

Nowadays, drought phenomena increasingly affect large areas of the globe; therefore, the need for a careful and rational management of water resources is becoming more pressing. Considering that most of the world’s unfrozen freshwater reserves are stored in aquifers, the capability of prediction of spring discharges is a crucial issue. An approach based on water balance is often extremely complicated or ineffective. A promising alternative is represented by data-driven approaches. Recently, many hydraulic engineering problems have been addressed by means of advanced models derived from artificial intelligence studies. Three different machine learning algorithms were used for spring discharge forecasting in this comparative study: M5P regression tree, random forest, and support vector regression. The spring of Rasiglia Alzabove, Umbria, Central Italy, was selected as a case study. The machine learning models have proven to be able to provide very encouraging results. M5P provides good short-term predictions of monthly average flow rates (e.g., in predicting average discharge of the spring after 1 month, R2=0.991, RAE=14.97%, if a 4-month input is considered), while RF is able to provide accurate medium-term forecasts (e.g., in forecasting average discharge of the spring after 3 months, R2=0.964, RAE=43.12%, if a 4-month input is considered). As the time of forecasting advances, the models generally provide less accurate predictions. Moreover, the effectiveness of the models significantly depends on the duration of the period considered for input data. This duration should be close to the aquifer response time, approximately estimated by cross-correlation analysis.

Distributed Hydrological Modeling: Determination of Theoretical Hydraulic Potential & Streamflow Simulation of Extreme Hydrometeorological Events

The progressive change in climatic conditions worldwide has increased frequency and severity of extreme hydrometeorological events (EHEs). México is an example that has been affected by the occurrence of EHE leading to economic, social, and environmental losses. The objective of this research was to apply a Canadian distributed hydrological model (DHM) to tropical conditions and to evaluate its capacity to simulate flows in a basin in the central Gulf of Mexico. In addition, the DHM (once calibrated and validated) was used to calculate the theoretical hydraulic power (THP) and the performance to predict streamflow before the presence of an EHE. The results of the DHM show that the goodness of fit indicators between the observed and simulated flows in the calibration process Nash-Sutcliffe efficiency (NSE) = 0.83, ratio of the root mean square error to the standard deviation of measured data (RSR) = 0.41, and percent bias (PBIAS) = −4.3) and validation (NSE = 0.775, RSR = 0.4735, and PBIAS = 2.45) are satisfactory. The DHM showed its applicability: determination of THP showed that the mean flows are in synchrony with the order of the river reaches and streamflow simulation of 13 EHEs (NSE = 0.78 ± 0.13, RSR = 0.46 ± 0.14 and PBIAS = −0.48 ± 7.5) confirmed a reliable efficiency. This work can serve as a tool for identifying vulnerabilities before floods and for the rational and sustainable management of water resources.

IMPLEMENTATION OF DPSIR FRAMEWORK IN THE MANAGEMENT OF THE ALMYROS BASIN, MAGNESIA PREFECTURE

In this paper, the implementation of the framework DPSIR is presented in the coastal part of the Almyros Basin, Magnesia Prefecture. The procedure included the use of previous relevant geological, hydrological, hydrogeological and management studies, regarding the study area, the results of which are classified and assigned to the driving forces, pressures, states, impacts and responses of the DPSIR method for the area under investigation. The approach concluded to an interesting visualization of the current situation of the urban and natural environment of the study area, promoting the recognition of problems arising from the intervention of the human factor and directing environmental actions towards a rational water resources management in the wider region.

Application ro techniques with "open channel" membranes to treat wastewater for recycling and reuse: modern methods of environmental protection and water resources management

The solution to contemporary ecological problems such as wastewater reuse requires rational water resources management, and in turn, rational water resources management requires the development of new, more efficient techniques. The modern concept of rational water resources management requires the development of new efficient techniques that provide wastewater treatment and reuse. For many local industries, the problem of wastewater treatment and discharge into surface reservoirs can’t be solved through the use of conventional biological treatment techniques. Current discharge standards require very strict removal of a number of impurities such as ammonia, nitrates, phosphate, etc. To reach this level of removal, expensive reagents and sorbents are used. As RO membranes simultaneously reject all dissolved impurities such as BOD, TDS, ammonia, phosphates etc., they become very attractive for the direct treatment of wastewater without biological stage. To treat wastewater, specially designed membrane "open channel" modules are used that do not possess "dead areas" that cause fouling or require pretreatment. A solution to the concentrate disposal problem is presented that consists of reducing of initial wastewater volume by 100 times. Concentrate is withdrawn from membrane unit as sludge humidity. Local utilities and privately-held industrial sites are encouraged to reuse wastewater and reduce freshwater intake, thereby prompting rational water management and reducing environmental pollution.

Large-scale radiation and energy balances with Landsat 8 images and agrometeorological data in the Brazilian semiarid region

Aiming to subsidize the rational water resources management, four Landsat 8 (L8) images along different conditions of the year 2014 were used for modeling the radiation and energy balances in the mixed agroecosystems inside a Brazilian reference semiarid area. The SAFER algorithm was applied to calculate the latent heat flux (λE); net radiation (Rn) was acquired by the Slob equation; ground heat flux (G) was considered a fraction of Rn; and the sensible heat flux (H) was retrieved by residue in the energy balance equation. For classifying the vegetation, the surface resistance algorithm (SUREAL) was used to estimate the surface resistance to the water fluxes (rs) with threshold values for rs. Clearly, one could see higher λE values from irrigated crops (ICs) than those for natural vegetation (NV) with some situations of heat horizontal advection. The respective λE, H, and G average ratios to Rn for the ICs ecosystem were 64% to 79%, 18% to 28%, and 3%, respectively. For the NV ecosystem, the corresponding fractions were 4% to 37%, 60% to 94%, and 4%, respectively. The algorithms proved to have strong sensibility to quantifying the large-scale energy and mass exchanges by applying L8 images in mixed agroecosystems of semiarid environments.