Aridity index is a numerical indicator of the degree of dryness of the climate at a given location. Time series of annual precipitation, minimum and maximum temperature records for 22 meteorological stations in Kurdistan region-Iraq were collected from different agencies. In Kurdistan region-Iraq neither aridity index non it's trend have been studied, therefore the purpose of this paper is to document the range of an aridity index, called De Martonne's aridity index (I DM) and to find the trend of aridity index using Mann-Kendal nonparametric test. Spatial zoning of the region was done using inverse distance weight (IDW) interpolation method by ArcGIS software. Results showed that different types of climate in the region were appeared however most of the study area falls in the range of semi-arid zone. Seasonal aridity showed that Kurdistan region-Iraq has extremely humid climate in winter and arid climate in summer. The De Martonne aridity index, average precipitation and average temperature were drawn for 10, 20 and 30 years according to availability of the data. Aridity index for 30 years from De Martonne were compared with two other indices and the results were very close. Trend analyses were performed for precipitation, temperature, and aridity index for the average data of 10, 20, and 30 years. Results revealed that for 10 year duration Dukan temperature has significant increasing trend at the 95% confidence level. It can be concluded that the last decade (2006-2015) undergo insignificant increasing in precipitation and temperature. For 20 year duration Dukan and Hawler temperature showed significant increasing trend at the 95% confidence level. For 30 year duration all stations temperature increased, Dukan precipitation showed decreasing trend while Dukan aridity index showed increasing trend significantly at the 95% confidence level. Increased significant trends at the 95% confidence level for temperature appears at both short and long durations (10, 20 and 30 years) while precipitation and aridity index trends appear only in long duration (30 years).

The precise and accurate models of hydrological time series that are embedded with high complexity, nonstationarity, and non-linearity in both spatial and temporal scales can provide important information for decision-making in water resources management and environmental related issues. Hybrid wavelet transform (WT) and adaptive neuro-fuzzy inference system (ANFIS) has been used in this study to improve the forecasting capability of ANFIS model by decomposing the time series into sub-time series (approximation and details) using wavelet transform then combining the effective and significant time lags of sub-time series to form a set of input variables. The present study attempts to add the effective and significant time lags of original time series as extra variables to the input variables set. In addition, different combinations of variables, 1-3, from the set of input variables as inputs to the ANFIS model were used to forecast the time series.To examine the potential of the approach for practical applications, the model is applied to forecast, one step-ahead, the monthly data of hydrological time series (rainfall, evaporation, minimum and maximum temperature, average wind speed and reservoir inflow) for Kirkuk, Sulaimani, Dokan and Darbandikhan meteorological stations in Iraq. The best fit models were selected using the coefficient of determination ( ) and root mean square error ( ). Based on the results, the proposed model has high performance in forecasting the monthly minimum and maximum temperature, evaporation and reservoir inflow with values ranged from 0.93 to 0.99 and relatively good performances in forecasting the monthly rainfall and average wind speed with values ranged from 0.77 to 0.93.

A field experiment was conducted at Bazian Agricultural Research Center, Sulaimani governorate in clay loam soil to investigate the effect of different irrigation systems (Furrow "F", Sprinkler "S", Drip "D", and Sub-surface drip irrigation system "SD" with three different depths (10cm-SD 10 ,25cm-SD 25 , and 40cm-SD 40 ) on irrigation water use efficiency, growth and yield of potato (SYLVANA c.v). Results showed that the total amount of water delivered from the source was significantly smaller for (SD 25 ) and (SD 40 ). Maximum water used by potato root and the higher application efficiency were observed by (SD 25 ). There are no significant differences between (SD 25 ) and (SD 40 ) in irrigation water use efficiency IWUE, while the both systems were superior significantly on the other irrigation systems in this trait.(SD 25 ) recorded the highest value and significantly dominated on other irrigation systems in many growth characteristics of potato. As well as this irrigation system (SD 25 ) was significantly increased potato yield and the percentages of yield increase were 35.5% and 27.6% compared to (F) and (S) respectively. There were no significant differences between (SD 25 ) and (D) in the average of tuber weight, while both treatments were superior significantly on the other irrigation systems. No significant different recorded between (S) and (F) for all growth and yield characteristics. Generally (SD 25 ) gave better results in water use and potato production.

Flow, low flow statistics, and variability of Darbandikhan and Dukan inflow time series have been analyzed. Darbandikhan and Dukan dams’ inflow time series were best fitted with three parameter inverse Gaussian distribution. Long term, annual, and monthly flow duration curves (FDCs) are constructed. Two parameters logarithmic function appeared to be the most appropriate functions fitted to FDCs. Low flow percentiles are extracted from flow duration curves for 95, 90, 75, 70, 50, and 25 percentiles. Annual minimum 1-, 3-, 7-, 14-, 30-, 60-, and 90-day mean inflow with recurrence intervals of 2, 5, 10, 20, 30, and 50 years were estimated.Base flows were separated from long-term inflow time series. Results indicated that a large amount of long-term inflow was supported by base flow for both Darbandikhan and Dukan dams’ inflow time series. The discharges were generally less than their mean inflow with no large fluctuations. The trend of monthly mean inflow discharge versus time have been analyzed using different methods. Results are indicating a significant negative monthly trends of 0.488 m3/s and 0.593 m3/s with reduction percentages of 0.0127 % and 0.0120% for Darbandikhan and Dukan dams’ inflow time series; respectively. The results of current study were compared with USGS Data Series 540 results. All month’s inflow defined a reduction that maximized in August. Comparison of low flow statistics are also referred to maximum reduction percentage in Q95% which is occurring commonly in summer. The larger reduction during summer months is indicating artificial water withdrawals from feeding streams of the dams during periods of no rain.

Rainwater harvesting is the collection of rainwater and runoff from catchment areas such as roofs or other urban surfaces. Collected water has productive end-uses such as irrigation, industry, domestic, and can recharge groundwater. Sulaimani heights have been selected as a study area, which is located in Sulaimani Governorate in Kurdistan Region, North Iraq. The main objective of this study was to estimate the amount of harvested rainwater form Sulaimani heights urban area in Sulaimani City. Three methods for runoff calculation have been compared, the storm water management model (SWMM), the soil conservation service (SCS) method, and the runoff coefficient (RC) using daily rainfall data from 1991 to 2019. The annual harvested runoff results with the three different methods SWMM, SCS, and RC were estimated as 836,470 m3, 508,454 m3, and 737,381 m3, respectively. The results showed that SWMM method has the highest runoff result and could meet 31% of the total demand of the study area and 28% and 19% for RC and SCS methods, respectively.